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Sample records for multi-attribute decision model

  1. Supporting Nurses’ Decisions with a Multi-Attribute Model for Patient Health Evaluation

    PubMed Central

    Rajkovič, Uroš; Dinevski, Dejan; Šušteršič, Olga; Prijatelj, Vesna; Rajkovič, Vladislav

    2012-01-01

    Nurses are required to make many important decisions, for instance on determining the level of the nursing problem, setting nursing diagnoses and interventions. The model presented in this paper is a tool for better and easier decision making is such situations. Multi-attribute modeling of patients’ basic living activities is used for evaluation and explanation of their health status. It offers also visualization and quantification of the data which facilitate decision making in the framework of the process work method. The model can be viewed as an active check-list as it helps us reduce the possibility of “overlooking the queen on the chess board”. The model was critically evaluated in practice. PMID:24199115

  2. Evaluating patients' health using a hierarchical multi-attribute decision model.

    PubMed

    Sustersic, O; Rajkovic, U; Dinevski, D; Jereb, E; Rajkovic, Vladislav

    2009-01-01

    Evaluation of a patient's health status is an essential part of the healthcare process. For this purpose, Henderson's model of basic living activities (BLA) is often proposed as a set of criteria to be used in nursing. Despite its clarity and theoretical background, the model is only partially used in clinical practice. In this paper, we present the methodology for a hierarchical multi-attribute decision model to increase the practical efficiency of the BLA model. The result is a computerized model for the evaluation of a patient's health status. This model was tested in clinical practice by 17 nurses in two health centres in Slovenia and a strengths, weaknesses, opportunities and threats (SWOT) analysis was carried out. The strengths included providing a holistic understanding of the nature and level of the nursing problems, enriching the documentation and reducing the possibility of overlooking something important. As a part of electronic documentation, this computerized model supports systematic patient data gathering and evaluation. PMID:19930874

  3. An improvement of multi-attribute decision model of grey target with interval number

    NASA Astrophysics Data System (ADS)

    Hu, Ming-li

    2013-10-01

    In view of the limits of existing decision model of grey target with interval number, a new formula for normalizing decision matrix is given based on range transformation. At the same time, on the basis of the principle of TOPSIS, a new decision model of grey target is set up considering not only the distance from positive bulls eye but also from negative one. An example is given to show the application of the method, and the results are compared with other methods. The results verify the validity and practicability of the method.

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

    NASA Astrophysics Data System (ADS)

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

    1981-05-01

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

  5. Detecting Hotspot Information Using Multi-Attribute Based Topic Model

    PubMed Central

    Wang, Jing; Li, Li; Tan, Feng; Zhu, Ying; Feng, Weisi

    2015-01-01

    Microblogging as a kind of social network has become more and more important in our daily lives. Enormous amounts of information are produced and shared on a daily basis. Detecting hot topics in the mountains of information can help people get to the essential information more quickly. However, due to short and sparse features, a large number of meaningless tweets and other characteristics of microblogs, traditional topic detection methods are often ineffective in detecting hot topics. In this paper, we propose a new topic model named multi-attribute latent dirichlet allocation (MA-LDA), in which the time and hashtag attributes of microblogs are incorporated into LDA model. By introducing time attribute, MA-LDA model can decide whether a word should appear in hot topics or not. Meanwhile, compared with the traditional LDA model, applying hashtag attribute in MA-LDA model gives the core words an artificially high ranking in results meaning the expressiveness of outcomes can be improved. Empirical evaluations on real data sets demonstrate that our method is able to detect hot topics more accurately and efficiently compared with several baselines. Our method provides strong evidence of the importance of the temporal factor in extracting hot topics. PMID:26496635

  6. Detecting Hotspot Information Using Multi-Attribute Based Topic Model.

    PubMed

    Wang, Jing; Li, Li; Tan, Feng; Zhu, Ying; Feng, Weisi

    2015-01-01

    Microblogging as a kind of social network has become more and more important in our daily lives. Enormous amounts of information are produced and shared on a daily basis. Detecting hot topics in the mountains of information can help people get to the essential information more quickly. However, due to short and sparse features, a large number of meaningless tweets and other characteristics of microblogs, traditional topic detection methods are often ineffective in detecting hot topics. In this paper, we propose a new topic model named multi-attribute latent dirichlet allocation (MA-LDA), in which the time and hashtag attributes of microblogs are incorporated into LDA model. By introducing time attribute, MA-LDA model can decide whether a word should appear in hot topics or not. Meanwhile, compared with the traditional LDA model, applying hashtag attribute in MA-LDA model gives the core words an artificially high ranking in results meaning the expressiveness of outcomes can be improved. Empirical evaluations on real data sets demonstrate that our method is able to detect hot topics more accurately and efficiently compared with several baselines. Our method provides strong evidence of the importance of the temporal factor in extracting hot topics. PMID:26496635

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

    SciTech Connect

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

    1992-12-31

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

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

    SciTech Connect

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

    1992-01-01

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

  9. Application of Choquet integral in solving multi-attribute decision making problems

    NASA Astrophysics Data System (ADS)

    Krishnan, Anath Rau; Mat Kasim, Maznah; Engku Abu Bakar, Engku Muhammad Nazri

    2011-10-01

    Aggregation is one of the imperative phases in solving a multi-attribute decision making (MADM) problems where the performance values of each choice will be composed into single score. Based on these final scores, the decision maker (DM) will make the decision by selecting, ranking or sorting the choices. The major issue in aggregation phase is most of the DMs are being ignorant or insensitive to the aspect of interaction between evaluation criteria while aggregating the performance values. Therefore, this paper intended to offer an appraisal on definition and several properties of aggregation operator, types of aggregation operator, and finally suggests Choquet integral operator and its associated fuzzy measure as the most appropriate tool in solving MADM problems. The suggested operator considers the interaction among evaluation criteria during aggregation. A simple numerical example is presented to emphasize the advantage of Choquet integral. However, the complexity of applying Choquet integral is discussed as well to provide some indications for future study.

  10. Decision Support for Personalized Cloud Service Selection through Multi-Attribute Trustworthiness Evaluation

    PubMed Central

    Ding, Shuai; Xia, Chen-Yi; Zhou, Kai-Le; Yang, Shan-Lin; Shang, Jennifer S.

    2014-01-01

    Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer. Many existing models cannot easily deal with cloud services which have very few historical records. In this paper, we propose a novel service selection approach in which the missing value prediction and the multi-attribute trustworthiness evaluation are commonly taken into account. By simply collecting limited historical records, the current approach is able to support the personalized trustworthy service selection. The experimental results also show that our approach performs much better than other competing ones with respect to the customer preference and expectation in trustworthiness assessment. PMID:24972237

  11. Decision support for personalized cloud service selection through multi-attribute trustworthiness evaluation.

    PubMed

    Ding, Shuai; Xia, Cheng-Yi; Xia, Chen-Yi; Zhou, Kai-Le; Yang, Shan-Lin; Shang, Jennifer S

    2014-01-01

    Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer. Many existing models cannot easily deal with cloud services which have very few historical records. In this paper, we propose a novel service selection approach in which the missing value prediction and the multi-attribute trustworthiness evaluation are commonly taken into account. By simply collecting limited historical records, the current approach is able to support the personalized trustworthy service selection. The experimental results also show that our approach performs much better than other competing ones with respect to the customer preference and expectation in trustworthiness assessment. PMID:24972237

  12. A Generalized Measurement Model to Quantify Health: The Multi-Attribute Preference Response Model

    PubMed Central

    Krabbe, Paul F. M.

    2013-01-01

    After 40 years of deriving metric values for health status or health-related quality of life, the effective quantification of subjective health outcomes is still a challenge. Here, two of the best measurement tools, the discrete choice and the Rasch model, are combined to create a new model for deriving health values. First, existing techniques to value health states are briefly discussed followed by a reflection on the recent revival of interest in patients’ experience with regard to their possible role in health measurement. Subsequently, three basic principles for valid health measurement are reviewed, namely unidimensionality, interval level, and invariance. In the main section, the basic operation of measurement is then discussed in the framework of probabilistic discrete choice analysis (random utility model) and the psychometric Rasch model. It is then shown how combining the main features of these two models yields an integrated measurement model, called the multi-attribute preference response (MAPR) model, which is introduced here. This new model transforms subjective individual rank data into a metric scale using responses from patients who have experienced certain health states. Its measurement mechanism largely prevents biases such as adaptation and coping. Several extensions of the MAPR model are presented. The MAPR model can be applied to a wide range of research problems. If extended with the self-selection of relevant health domains for the individual patient, this model will be more valid than existing valuation techniques. PMID:24278141

  13. 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.

  14. 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.

  15. A multi-attribute decision analysis for decommissioning offshore oil and gas platforms.

    PubMed

    Henrion, Max; Bernstein, Brock; Swamy, Surya

    2015-10-01

    The 27 oil and gas platforms off the coast of southern California are reaching the end of their economic lives. Because their decommissioning involves large costs and potential environmental impacts, this became an issue of public controversy. As part of a larger policy analysis conducted for the State of California, we implemented a decision analysis as a software tool (PLATFORM) to clarify and evaluate decision strategies against a comprehensive set of objectives. Key options selected for in-depth analysis are complete platform removal and partial removal to 85 feet below the water line, with the remaining structure converted in place to an artificial reef to preserve the rich ecosystems supported by the platform's support structure. PLATFORM was instrumental in structuring and performing key analyses of the impacts of each option (e.g., on costs, fishery production, air emissions) and dramatically improved the team's productivity. Sensitivity analysis found that disagreement about preferences, especially about the relative importance of strict compliance with lease agreements, has much greater effects on the preferred option than does uncertainty about specific outcomes, such as decommissioning costs. It found a near-consensus of stakeholders in support of partial removal and "rigs-to-reefs" program. The project's results played a role in the decision to pass legislation enabling an expanded California "rigs-to-reefs" program that includes a mechanism for sharing cost savings between operators and the state. PMID:26415010

  16. Propulsion Airframe Aeroacoustics Technology Evaluation and Selection Using a Multi-Attribute Decision Making Process and Non-Deterministic Design

    NASA Technical Reports Server (NTRS)

    Burg, Cecile M.; Hill, Geoffrey A.; Brown, Sherilyn A.; Geiselhart, Karl A.

    2004-01-01

    The Systems Analysis Branch at NASA Langley Research Center has investigated revolutionary Propulsion Airframe Aeroacoustics (PAA) technologies and configurations for a Blended-Wing-Body (BWB) type aircraft as part of its research for NASA s Quiet Aircraft Technology (QAT) Project. Within the context of the long-term NASA goal of reducing the perceived aircraft noise level by a factor of 4 relative to 1997 state of the art, major configuration changes in the propulsion airframe integration system were explored with noise as a primary design consideration. An initial down-select and assessment of candidate PAA technologies for the BWB was performed using a Multi-Attribute Decision Making (MADM) process consisting of organized brainstorming and decision-making tools. The assessments focused on what effect the PAA technologies had on both the overall noise level of the BWB and what effect they had on other major design considerations such as weight, performance and cost. A probabilistic systems analysis of the PAA configurations that presented the best noise reductions with the least negative impact on the system was then performed. Detailed results from the MADM study and the probabilistic systems analysis will be published in the near future.

  17. Multi-attribute mate choice decisions and uncertainty in the decision process: a generalized sequential search strategy.

    PubMed

    Wiegmann, Daniel D; Weinersmith, Kelly L; Seubert, Steven M

    2010-04-01

    The behavior of females in search of a mate determines the likelihood that high quality males are encountered and adaptive search strategies rely on the effective use of available information on the quality of prospective mates. The sequential search strategy was formulated, like most models of search behavior, on the assumption that females obtain perfect information on the quality of encountered males. In this paper, we modify the strategy to allow for uncertainty of male quality and we determine how the magnitude of this uncertainty and the ability of females to inspect multiple male attributes to reduce uncertainty influence mate choice decisions. In general, searchers are sensitive to search costs and higher costs lower acceptance criteria under all versions of the model. The choosiness of searchers increases with the variability of the quality of prospective mates under conditions of the original model, but under conditions of uncertainty the choosiness of searchers may increase or decrease with the variability of inspected male attributes. The behavioral response depends on the functional relationship between observed male attributes and the fitness return to searchers and on costs associated with the search process. Higher uncertainty often induces searchers to pay more for information and under conditions of uncertainty the fitness return to searchers is never higher than under conditions of the original model. Further studies of the performance of alternative search strategies under conditions of uncertainty may consequently be necessary to identify search strategies likely to be used under natural conditions. PMID:19499223

  18. Assessment of distance-based multi-attribute group decision-making methods from a maintenance strategy perspective

    NASA Astrophysics Data System (ADS)

    Ding, Siew-Hong; Kamaruddin, Shahrul

    2015-07-01

    Maintenance has been acknowledged by industrial management as a significant influencing factor of plant performance. Effective plant maintenance can be realized by developing a proper maintenance strategy. However, selecting an appropriate maintenance strategy is difficult because maintenance is a non-repetitive task such as production activity. Maintenance also does not leave a consistent traceable record that can be referred to during the decision-making process. The involvement of tangible and intangible factors in the assessment process further increases the complexity of the decision-making process. The technique of preference order by similarity to ideal solution (TOPSIS) is one of the most well-known decision-making methods and has been widely used by organizations to conduct effective decisions regarding maintenance issues. TOPSIS has also evolved by integrating different approaches such as the fuzzy concept. Although numerous TOPSIS applications for maintenance decision making have been published, the effectiveness of crisp TOPSIS and fuzzy TOPSIS needs to be investigated further. This paper attempts to present a comparison between conventional crisp TOPSIS and fuzzy TOPSIS from a group maintenance decision-making perspective by an empirical illustration. Sensitivity analysis is conducted to demonstrate further the resilience of crisp TOPSIS and fuzzy TOPSIS.

  19. Hierarchical competitions subserving multi-attribute choice.

    PubMed

    Hunt, Laurence T; Dolan, Raymond J; Behrens, Timothy E J

    2014-11-01

    Valuation is a key tenet of decision neuroscience, where it is generally assumed that different attributes of competing options are assimilated into unitary values. Such values are central to current neural models of choice. By contrast, psychological studies emphasize complex interactions between choice and valuation. Principles of neuronal selection also suggest that competitive inhibition may occur in early valuation stages, before option selection. We found that behavior in multi-attribute choice is best explained by a model involving competition at multiple levels of representation. This hierarchical model also explains neural signals in human brain regions previously linked to valuation, including striatum, parietal and prefrontal cortex, where activity represents within-attribute competition, competition between attributes and option selection. This multi-layered inhibition framework challenges the assumption that option values are computed before choice. Instead, our results suggest a canonical competition mechanism throughout all stages of a processing hierarchy, not simply at a final choice stage. PMID:25306549

  20. Multi-Attribute Consensus Building Tool

    ERIC Educational Resources Information Center

    Shyyan, Vitaliy; Christensen, Laurene; Thurlow, Martha; Lazarus, Sheryl

    2013-01-01

    The Multi-Attribute Consensus Building (MACB) method is a quantitative approach for determining a group's opinion about the importance of each item (strategy, decision, recommendation, policy, priority, etc.) on a list (Vanderwood, & Erickson, 1994). This process enables a small or large group of participants to generate and discuss a set…

  1. Multi-Attribute Sequential Search

    ERIC Educational Resources Information Center

    Bearden, J. Neil; Connolly, Terry

    2007-01-01

    This article describes empirical and theoretical results from two multi-attribute sequential search tasks. In both tasks, the DM sequentially encounters options described by two attributes and must pay to learn the values of the attributes. In the "continuous" version of the task the DM learns the precise numerical value of an attribute when she…

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

    NASA Astrophysics Data System (ADS)

    Chen, Ting-Yu

    2012-06-01

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

  3. Multi-Attribute Tradespace Exploration in Space System Design

    NASA Astrophysics Data System (ADS)

    Ross, A. M.; Hastings, D. E.

    2002-01-01

    The complexity inherent in space systems necessarily requires intense expenditures of resources both human and monetary. The high level of ambiguity present in the early design phases of these systems causes long, highly iterative, and costly design cycles. This paper looks at incorporating decision theory methods into the early design processes to streamline communication of wants and needs among stakeholders and between levels of design. Communication channeled through formal utility interviews and analysis enables engineers to better understand the key drivers for the system and allows a more thorough exploration of the design tradespace. Multi-Attribute Tradespace Exploration (MATE), an evolving process incorporating decision theory into model and simulation- based design, has been applied to several space system case studies at MIT. Preliminary results indicate that this process can improve the quality of communication to more quickly resolve project ambiguity, and enable the engineer to discover better value designs for multiple stakeholders. MATE is also being integrated into a concurrent design environment to facilitate the transfer knowledge of important drivers into higher fidelity design phases. Formal utility theory provides a mechanism to bridge the language barrier between experts of different backgrounds and differing needs (e.g. scientists, engineers, managers, etc). MATE with concurrent design couples decision makers more closely to the design, and most importantly, maintains their presence between formal reviews.

  4. Using Consumer Behavior and Decision Models to Aid Students in Choosing a Major.

    ERIC Educational Resources Information Center

    Kaynama, Shohreh A.; Smith, Louise W.

    1996-01-01

    A study found that using consumer behavior and decision models to guide students to a major can be useful and enjoyable for students. Students consider many of the basic parameters through multi-attribute and decision-analysis models, so time with professors, who were found to be the most influential group, can be used for more individual and…

  5. Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

    PubMed Central

    Li, Lian-hui; Mo, Rong

    2015-01-01

    The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility. PMID:26414758

  6. Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop.

    PubMed

    Li, Lian-Hui; Mo, Rong

    2015-01-01

    The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility. PMID:26414758

  7. Weight sensitivity measurement, analysis, and application in multi-attribute evaluation

    NASA Astrophysics Data System (ADS)

    Zhao, Yong; Huang, Chongyin; Chen, Yang

    2013-11-01

    Weights are used to measure relative importance of multiple attributes or objectives, which influence evaluation or decision results to a great degree. Thus, analyzing weight sensitivity is an important work for a multi-attribute evaluation or decision. A measuring method based on the inclined angle of two vectors is proposed in this paper in order to solve the weight sensitivity of a multi-attribute evaluation with isotonicity characteristic. This method uses the cosine of the inclined angle to measure the weight sensitivity based on preferences or preference combinations. Concepts of sensitivity space, degree, and angle are given, and the relevant measurement method is discussed and proved. Also, this method is used for the choice of the water environment protection projects in Heyuan City.

  8. Zoning of an agricultural field using a fuzzy indicator model in combination with tool for multi-attributed decision-making

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Zoning of agricultural fields is an important task for utilization of precision farming technology. This paper extends previously published work entitled “Zoning of an agricultural field using a fuzzy indicator model” to a general case where there is disagreement between groups of managers or expert...

  9. Comparison of Decision Models

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  10. LineUp: Visual Analysis of Multi-Attribute Rankings

    PubMed Central

    Gratzl, Samuel; Lex, Alexander; Gehlenborg, Nils; Pfister, Hanspeter; Streit, Marc

    2014-01-01

    Rankings are a popular and universal approach to structuring otherwise unorganized collections of items by computing a rank for each item based on the value of one or more of its attributes. This allows us, for example, to prioritize tasks or to evaluate the performance of products relative to each other. While the visualization of a ranking itself is straightforward, its interpretation is not, because the rank of an item represents only a summary of a potentially complicated relationship between its attributes and those of the other items. It is also common that alternative rankings exist which need to be compared and analyzed to gain insight into how multiple heterogeneous attributes affect the rankings. Advanced visual exploration tools are needed to make this process efficient. In this paper we present a comprehensive analysis of requirements for the visualization of multi-attribute rankings. Based on these considerations, we propose LineUp - a novel and scalable visualization technique that uses bar charts. This interactive technique supports the ranking of items based on multiple heterogeneous attributes with different scales and semantics. It enables users to interactively combine attributes and flexibly refine parameters to explore the effect of changes in the attribute combination. This process can be employed to derive actionable insights as to which attributes of an item need to be modified in order for its rank to change. Additionally, through integration of slope graphs, LineUp can also be used to compare multiple alternative rankings on the same set of items, for example, over time or across different attribute combinations. We evaluate the effectiveness of the proposed multi-attribute visualization technique in a qualitative study. The study shows that users are able to successfully solve complex ranking tasks in a short period of time. PMID:24051794

  11. Decision Impact Assessment Model

    Energy Science and Technology Software Center (ESTSC)

    1991-08-01

    DIAMOND represents the decision-making environment that utility planners and executives face. Users interact with the model after every year or two of simulation, which provides an opportunity to modify past decisions as well as to make new decisions. For example, construction of a power plant can be started one year, and if circumstances change, the plant can be accelerated, mothballed, cancelled, or continued as originally planned. Similarly, the marketing and financial incentives for demand-side managementmore » programs can be changed from year to year. This frequent user interaction with the model, an operational game, should build greater understanding and insights among utility planners about the risks associated with different types of resources.« less

  12. Visual analytics techniques for large multi-attribute time series data

    NASA Astrophysics Data System (ADS)

    Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.

    2008-01-01

    Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year's monthly sales with last year's sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need to detect the outliers early enough to act upon them. In this paper, two new visual analytic techniques are introduced: The color cell-based Visual Time Series Line Charts and Maps highlight significant changes over time in a long time series data and the new Visual Content Query facilitates finding the contents and histories of interesting patterns and anomalies, which leads to root cause identification. We have applied both methods to two real-world applications to mine enterprise data warehouse and customer credit card fraud data to illustrate the wide applicability and usefulness of these techniques.

  13. Automated modeling of medical decisions.

    PubMed Central

    Egar, J. W.; Musen, M. A.

    1993-01-01

    We have developed a graph grammar and a graph-grammar derivation system that, together, generate decision-theoretic models from unordered lists of medical terms. The medical terms represent considerations in a dilemma that confronts the patient and the health-care provider. Our current grammar ensures that several desirable structural properties are maintained in all derived decision models. PMID:8130509

  14. Measurement of patient-derived utility values for periodontal health using a multi-attribute scale.

    PubMed

    Bellamy, C A; Brickley, M R; McAndrew, R

    1996-09-01

    Periodontal health states are difficult to quantify and no formal scale quantifying patients' utilities for periodontal health states exits. Multi-attribute utility (MAU) techniques were used to develop such a scale. The MAU scale may be used to quantify patients' assessment of their current periodontal health and that of possible treatment outcomes. Such data, combined with probability values in formal decision analysis techniques would result in improved rationality of treatment planning for periodontal disease. 20 patients attending for routine undergraduate care were interviewed. Data from these interviews were sorted into groups of common interest (domains). Intra-domain health statements were complied from the interview content. 21 patients ranked the intra-domain statements on a scale of 0-100. This same group of patients also performed an inter-domain weighting. Mean results showed that patients were 2X as concerned with how they felt and with the prognosis of possible outcomes, than with how they looked and what facts they knew about their oral health. However, the real value of utilities research lies in application of individual results to treatment planning as there is a wide range of opinion regarding outcome health states. PMID:8891929

  15. Models of Affective Decision Making

    PubMed Central

    Charpentier, Caroline J.; De Neve, Jan-Emmanuel; Li, Xinyi; Roiser, Jonathan P.; Sharot, Tali

    2016-01-01

    Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to the value function in prospect theory, our feeling function showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighted when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision. PMID:27071751

  16. Multi-Attribute Utility Theory and Adaptive Techniques for Intelligent Web-Based Educational Software

    ERIC Educational Resources Information Center

    Kabassi, K.; Virvou, M.

    2006-01-01

    This paper describes how the Multi-Attribute Utility Theory can be combined with adaptive techniques to improve individualised teaching in an Intelligent Learning Environment (ILE). The ILE is called Web F-SMILE, it operates over the Web and is meant to help novice users learn basic skills of computer use. Tutoring is dynamically adapted to the…

  17. MULTI-ATTRIBUTE SEISMIC/ROCK PHYSICS APPROACH TO CHARACTERIZING FRACTURED RESERVOIRS

    SciTech Connect

    Gary Mavko

    2000-10-01

    This project consists of three key interrelated Phases, each focusing on the central issue of imaging and quantifying fractured reservoirs, through improved integration of the principles of rock physics, geology, and seismic wave propagation. This report summarizes the results of Phase I of the project. The key to successful development of low permeability reservoirs lies in reliably characterizing fractures. Fractures play a crucial role in controlling almost all of the fluid transport in tight reservoirs. Current seismic methods to characterize fractures depend on various anisotropic wave propagation signatures that can arise from aligned fractures. We are pursuing an integrated study that relates to high-resolution seismic images of natural fractures to the rock parameters that control the storage and mobility of fluids. Our goal is to go beyond the current state-of-the art to develop and demonstrate next generation methodologies for detecting and quantitatively characterizing fracture zones using seismic measurements. Our study incorporates 3 key elements: (1) Theoretical rock physics studies of the anisotropic viscoelastic signatures of fractured rocks, including up scaling analysis and rock-fluid interactions to define the factors relating fractures in the lab and in the field. (2) Modeling of optimal seismic attributes, including offset and azimuth dependence of travel time, amplitude, impedance and spectral signatures of anisotropic fractured rocks. We will quantify the information content of combinations of seismic attributes, and the impact of multi-attribute analyses in reducing uncertainty in fracture interpretations. (3) Integration and interpretation of seismic, well log, and laboratory data, incorporating field geologic fracture characterization and the theoretical results of items 1 and 2 above. The focal point for this project is the demonstration of these methodologies in the Marathon Oil Company Yates Field in West Texas.

  18. The Application of a Multi-Attribute Decision-Making Algorithm to Learning Management Systems Evaluation

    ERIC Educational Resources Information Center

    Cavus, Nadire

    2011-01-01

    Recently, because of the rapid increase in the popularity of the Internet, the delivery of learning programmes has gradually shifted from local desktop to online-based applications. As more and more technological tools become available for online education, there is an increasing interest among educators and other professionals in the application…

  19. How Well Do the Generic Multi-attribute Utility Instruments Incorporate Patient and Public Views Into Their Descriptive Systems?

    PubMed

    Stevens, Katherine J

    2016-02-01

    Multi-attribute utility instruments (MAUIs) are increasingly being used to generate utility data, which can be used to calculate quality-adjusted life-years (QALYs). These QALY data can then be incorporated into a cost-utility analysis as part of an economic evaluation, to inform health care resource allocation decisions. Many health care decision-making bodies around the world, such as the National Institute for Health and Care Excellence, require the use of generic MAUIs. Recently, there has been a call for greater input of patients into the development of patient-reported outcome measures, and this is now actively encouraged. By incorporating the views of patients, greater validity of an instrument is expected and it is more likely that patients will be able to self-complete the instrument, which is the ideal when obtaining information about a patient's health-related quality of life. This paper examines the stages of MAUI development and the scope for patient and/or public involvement at each stage. The paper then reviews how much the main generic MAUIs have incorporated the views of patients/the public into the development of their descriptive systems at each of these stages, and the implications of this. The review finds that the majority of MAUIs had very little input from patients/the public. Instead, existing literature and/or the views of experts were used. If we wish to incorporate patient/public views into future development of MAUIs, qualitative methods are recommended. PMID:25663152

  20. A decision-analytic model for early stage breast cancer: lumpectomy vs mastectomy.

    PubMed

    Büyükdamgaci-Alogan, G; Elele, T; Hayran, M; Erman, M; Kiliçkap, S

    2008-01-01

    The purpose was to construct a decision model that incorporated patient preferences over differing health state prospects and to analyze the decision context of early stage breast cancer patients in relation to two main surgical treatment options. A Markov chain was constructed to project the clinical history of breast carcinoma following surgery. A Multi Attribute Utility Model was developed for outcome evaluation. Transition probabilities were obtained by using subjective probability assessment. This study was performed on the sample population of female university students and utilities were elicited from these healthy volunteers. The results were validated by using Standard Gamble technique. Finally, Monte Carlo Simulation was utilized in Treeage-Pro 2006-Suit software program in order to calculate expected utility generated by each treatment option. The results showed that, if the subject had mastectomy, mean value for the quality adjusted life years gained was 6.42; on the other hand, if the preference was lumpectomy, it was 7.00 out of a possible 10 years. Sensitivity analysis on transition probabilities to local recurrence and salvaged states was performed and two threshold values were observed. Additionally, sensitivity analysis on utilities showed that the model was more sensitive to no evidence of disease state; however, was not sensitive to utilities of local recurrence and salvaged states. The decision model was developed with reasonable success for early stage breast cancer patients, and tested by using general public data. The results obtained from these data showed that lumpectomy was more favourable for these participants. PMID:18348655

  1. Decision tree modeling using R

    PubMed Central

    2016-01-01

    In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building. PMID:27570769

  2. Decision tree modeling using R.

    PubMed

    Zhang, Zhongheng

    2016-08-01

    In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building. PMID:27570769

  3. MAT - MULTI-ATTRIBUTE TASK BATTERY FOR HUMAN OPERATOR WORKLOAD AND STRATEGIC BEHAVIOR RESEARCH

    NASA Technical Reports Server (NTRS)

    Comstock, J. R.

    1994-01-01

    MAT, a Multi-Attribute Task battery, gives the researcher the capability of performing multi-task workload and performance experiments. The battery provides a benchmark set of tasks for use in a wide range of laboratory studies of operator performance and workload. MAT incorporates tasks analogous to activities that aircraft crew members perform in flight, while providing a high degree of experiment control, performance data on each subtask, and freedom to use non-pilot test subjects. The MAT battery primary display is composed of four separate task windows which are as follows: a monitoring task window which includes gauges and warning lights, a tracking task window for the demands of manual control, a communication task window to simulate air traffic control communications, and a resource management task window which permits maintaining target levels on a fuel management task. In addition, a scheduling task window gives the researcher information about future task demands. The battery also provides the option of manual or automated control of tasks. The task generates performance data for each subtask. The task battery may be paused and onscreen workload rating scales presented to the subject. The MAT battery was designed to use a serially linked second computer to generate the voice messages for the Communications task. The MATREMX program and support files, which are included in the MAT package, were designed to work with the Heath Voice Card (Model HV-2000, available through the Heath Company, Benton Harbor, Michigan 49022); however, the MATREMX program and support files may easily be modified to work with other voice synthesizer or digitizer cards. The MAT battery task computer may also be used independent of the voice computer if no computer synthesized voice messages are desired or if some other method of presenting auditory messages is devised. MAT is written in QuickBasic and assembly language for IBM PC series and compatible computers running MS-DOS. The

  4. Values in Decision Making: The INVOLVE Model.

    ERIC Educational Resources Information Center

    Elfrink, Victoria L.; Coldwell, LuAnn Linson

    1993-01-01

    Describes the function of values and participatory decision making within the student affairs profession. Introduces a process model as a means of operationalizing values in the decision-making process and uses case studies to illustrate how the model can be used to improve student affairs professionals' decision making. (RJM)

  5. Modelling decision-making by pilots

    NASA Technical Reports Server (NTRS)

    Patrick, Nicholas J. M.

    1993-01-01

    Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).

  6. The KONVERGENCE Model for Sustainable Decisions

    SciTech Connect

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

    2002-08-01

    The KONVERGENCE Model for Sustainable Decisions is a new way of viewing, developing, organizing, and evaluating alternatives for decisions that may affect a wide range of interests and that must factor in long timeframes, enduring hazards, and/or continuing responsibilities. It differs from other models in that it addresses the need for decisions to continue to "work" over long time periods in an ever-changing decision environment. The authors show that the model contains three major universes - knowledge, values, and resources (the K, V, and R in KONVERGENCE)- that interact and overlap throughout the effective lifetime of a decision. They discuss how decision-makers and decision participants can use the model to craft and analyze decisions and decision processes that stand the test of time. The authors use the U.S. moon-landing program as an example of a major decision process that was sustained over time. They use the model to explain why events unfolded in the way that they did - and why we are where we are today in that program. The authors believe that this model will be especially useful in long-term decision processes such as those that address contamination cleanup programs, long-term environmental stewardship, and the initial siting of facilities with long-term objectives. Companion papers describe the KONVERGENCE Model process steps and implications for intractable cleanup decisions.

  7. Model choice for decision making under uncertainty

    NASA Astrophysics Data System (ADS)

    Bàrdossy, Andràs

    2015-04-01

    Present and future water management decisions are often supported by modelling. The choice of the appropriate model and model parameters depend on the decision related question, the quality of the model and the available information. While spatially detailed physics based models might seem very transferable, the uncertainty of the parametrization and of the input may lead to highly diverging results, which are of no use for decision making. The optimal model choice requires a quantification of the input/natural parameter uncertainty. As a next step the influence of this uncertainty on predictions using models with different complexity has to be quantified. Finally the influence of this prediction uncertainty on the decisions to be taken has to be assessed. Different data/information availability and modelling questions thus might require different modelling approaches. A framework for this model choice and parametrization problem will be presented together with examples from regions with very different data availability and data quality.

  8. Shared Problem Models and Crew Decision Making

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

    The importance of crew decision making to aviation safety has been well established through NTSB accident analyses: Crew judgment and decision making have been cited as causes or contributing factors in over half of all accidents in commercial air transport, general aviation, and military aviation. Yet the bulk of research on decision making has not proven helpful in improving the quality of decisions in the cockpit. One reason is that traditional analytic decision models are inappropriate to the dynamic complex nature of cockpit decision making and do not accurately describe what expert human decision makers do when they make decisions. A new model of dynamic naturalistic decision making is offered that may prove more useful for training or aiding cockpit decision making. Based on analyses of crew performance in full-mission simulation and National Transportation Safety Board accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation and reflect the crew's metacognitive skill. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relation between communication that serves to build performance. Implications of these findings for crew training will be discussed.

  9. Disentangling Decision Models: From Independence to Competition

    ERIC Educational Resources Information Center

    Teodorescu, Andrei R.; Usher, Marius

    2013-01-01

    A multitude of models have been proposed to account for the neural mechanism of value integration and decision making in speeded decision tasks. While most of these models account for existing data, they largely disagree on a fundamental characteristic of the choice mechanism: independent versus different types of competitive processing. Five…

  10. Research on the Comparability of Multi-attribute Evaluation Methods for Academic Journals

    NASA Astrophysics Data System (ADS)

    Liping, Yu

    This paper first constructs a classification framework for multi-attribute evaluation methods oriented to academic journals, and then discusses the comparability of the vast majority of non-linear evaluation methods and the majority of linear evaluation methods theoretically, taking the TOPSIS method as an example and the evaluation data on agricultural journals as an exercise of validation. The analysis result shows that we should attach enough importance to the comparability of evaluation methods for academic journals; the evaluation objectives are closely related to the choice of evaluation methods, and also relevant to the comparability of evaluation methods; the specialized organizations for journal evaluation had better release the evaluation data, evaluation methods and evaluation results to the best of their abilities; only purely subjective evaluation method is of broad comparability.

  11. Recognition of human-vehicle interactions in group activities via multi-attributed semantic message generation

    NASA Astrophysics Data System (ADS)

    Elangovan, Vinayak; Shirkhodaie, Amir

    2015-05-01

    Improved Situational awareness is a vital ongoing research effort for the U.S. Homeland Security for the past recent years. Many outdoor anomalous activities involve vehicles as their primary source of transportation to and from the scene where a plot is executed. Analysis of dynamics of Human-Vehicle Interaction (HVI) helps to identify correlated patterns of activities representing potential threats. The objective of this paper is bi-folded. Primarily, we discuss a method for temporal HVI events detection and verification for generation of HVI hypotheses. To effectively recognize HVI events, a Multi-attribute Vehicle Detection and Identification technique (MVDI) for detection and classification of stationary vehicles is presented. Secondly, we describe a method for identification of pertinent anomalous behaviors through analysis of state transitions between two successively detected events. Finally, we present a technique for generation of HVI semantic messages and present our experimental results to demonstrate the effectiveness of semantic messages for discovery of HVI in group activities.

  12. A Structured Decision Approach for Integrating and Analyzing Community Perspectives in Re-Use Planning of Vacant Properties in Cleveland, Ohio

    EPA Science Inventory

    An integrated GIS-based, multi-attribute decision model deployed in a web-based platform is presented enabling an iterative, spatially explicit and collaborative analysis of relevant and available information for repurposing vacant land. The process incorporated traditional and ...

  13. Optimal Decision Making in Neural Inhibition Models

    ERIC Educational Resources Information Center

    van Ravenzwaaij, Don; van der Maas, Han L. J.; Wagenmakers, Eric-Jan

    2012-01-01

    In their influential "Psychological Review" article, Bogacz, Brown, Moehlis, Holmes, and Cohen (2006) discussed optimal decision making as accomplished by the drift diffusion model (DDM). The authors showed that neural inhibition models, such as the leaky competing accumulator model (LCA) and the feedforward inhibition model (FFI), can mimic the…

  14. A visual analysis of multi-attribute data using pixel matrix displays

    NASA Astrophysics Data System (ADS)

    Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel; Schreck, Tobias

    2007-01-01

    Charts and tables are commonly used to visually analyze data. These graphics are simple and easy to understand, but charts show only highly aggregated data and present only a limited number of data values while tables often show too many data values. As a consequence, these graphics may either lose or obscure important information, so different techniques are required to monitor complex datasets. Users need more powerful visualization techniques to digest and compare detailed multi-attribute data to analyze the health of their business. This paper proposes an innovative solution based on the use of pixel-matrix displays to represent transaction-level information. With pixelmatrices, users can visualize areas of importance at a glance, a capability not provided by common charting techniques. We present our solutions to use colored pixel-matrices in (1) charts for visualizing data patterns and discovering exceptions, (2) tables for visualizing correlations and finding root-causes, and (3) time series for visualizing the evolution of long-running transactions. The solutions have been applied with success to product sales, Internet network performance analysis, and service contract applications demonstrating the benefits of our method over conventional graphics. The method is especially useful when detailed information is a key part of the analysis.

  15. The multi-attribute task battery for human operator workload and strategic behavior research

    NASA Technical Reports Server (NTRS)

    Comstock, J. Raymond, Jr.; Arnegard, Ruth J.

    1992-01-01

    The Multi-Attribute Task (MAT) Battery provides a benchmark set of tasks for use in a wide range of lab studies of operator performance and workload. The battery incorporates tasks analogous to activities that aircraft crewmembers perform in flight, while providing a high degree of experimenter control, performance data on each subtask, and freedom to use nonpilot test subjects. Features not found in existing computer based tasks include an auditory communication task (to simulate Air Traffic Control communication), a resource management task permitting many avenues or strategies of maintaining target performance, a scheduling window which gives the operator information about future task demands, and the option of manual or automated control of tasks. Performance data are generated for each subtask. In addition, the task battery may be paused and onscreen workload rating scales presented to the subject. The MAT Battery requires a desktop computer with color graphics. The communication task requires a serial link to a second desktop computer with a voice synthesizer or digitizer card.

  16. Computer modeling of human decision making

    NASA Technical Reports Server (NTRS)

    Gevarter, William B.

    1991-01-01

    Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making.

  17. EXPERIMENTING WITH MULTI-ATTRIBUTE UTILITY SURVEY METHODS IN A MULTI-DIMENSIONAL VALUATION PROBLEM. (R824699)

    EPA Science Inventory

    Abstract

    The use of willingness-to-pay (WTP) survey techniques based on multi-attribute utility (MAU) approaches has been recommended by some authors as a way to deal simultaneously with two difficulties that increasingly plague environmental valuation. The first of th...

  18. Diffusion Decision Model: Current Issues and History.

    PubMed

    Ratcliff, Roger; Smith, Philip L; Brown, Scott D; McKoon, Gail

    2016-04-01

    There is growing interest in diffusion models to represent the cognitive and neural processes of speeded decision making. Sequential-sampling models like the diffusion model have a long history in psychology. They view decision making as a process of noisy accumulation of evidence from a stimulus. The standard model assumes that evidence accumulates at a constant rate during the second or two it takes to make a decision. This process can be linked to the behaviors of populations of neurons and to theories of optimality. Diffusion models have been used successfully in a range of cognitive tasks and as psychometric tools in clinical research to examine individual differences. In this review, we relate the models to both earlier and more recent research in psychology. PMID:26952739

  19. Comprehensive Decision Tree Models in Bioinformatics

    PubMed Central

    Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

    2012-01-01

    Purpose Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. Methods This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. Results The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. Conclusions The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class

  20. A decision model for planetary missions

    NASA Technical Reports Server (NTRS)

    Hazelrigg, G. A., Jr.; Brigadier, W. L.

    1976-01-01

    Many techniques developed for the solution of problems in economics and operations research are directly applicable to problems involving engineering trade-offs. This paper investigates the use of utility theory for decision making in planetary exploration space missions. A decision model is derived that accounts for the objectives of the mission - science - the cost of flying the mission and the risk of mission failure. A simulation methodology for obtaining the probability distribution of science value and costs as a function spacecraft and mission design is presented and an example application of the decision methodology is given for various potential alternatives in a comet Encke mission.

  1. A Stochastic Multi-Attribute Assessment of Energy Options for Fairbanks, Alaska

    NASA Astrophysics Data System (ADS)

    Read, L.; Madani, K.; Mokhtari, S.; Hanks, C. L.; Sheets, B.

    2012-12-01

    Many competing projects have been proposed to address Interior Alaska's high cost of energy—both for electricity production and for heating. Public and private stakeholders are considering the costs associated with these competing projects which vary in fuel source, subsidy requirements, proximity, and other factors. As a result, the current projects under consideration involve a complex cost structure of potential subsidies and reliance on present and future market prices, introducing a significant amount of uncertainty associated with each selection. Multi-criteria multi-decision making (MCMDM) problems of this nature can benefit from game theory and systems engineering methods, which account for behavior and preferences of stakeholders in the analysis to produce feasible and relevant solutions. This work uses a stochastic MCMDM framework to evaluate the trade-offs of each proposed project based on a complete cost analysis, environmental impact, and long-term sustainability. Uncertainty in the model is quantified via a Monte Carlo analysis, which helps characterize the sensitivity and risk associated with each project. Based on performance measures and criteria outlined by the stakeholders, a decision matrix will inform policy on selecting a project that is both efficient and preferred by the constituents.

  2. Multi-attributed tagged big data exploitation for hidden concepts discovery

    NASA Astrophysics Data System (ADS)

    Habibi, Mohammad S.; Shirkhodaie, Amir

    2014-06-01

    Analysts who are using visualization methods for big data concept exploration increasingly expect to comprehend more distinct relationships and prominent concepts in support of their hypotheses or decisions. To expedite this knowledge discovery process, Vector Space Modeling (VSM) in conjunction with probabilistic analysis enables rapid knowledgebased relationship discovery while allowing for exploration of multi-embedded concepts than otherwise it is difficult to perceive. In this paper, we present a technique for intrinsic ontology concepts similarity matching based on VSM for exploitation and knowledge discovery from multimodality sensors metadata generated in Persistent Surveillance Systems (PSS). To reduce data dimensionality, Principal Component Analysis (PCA) and Latent Dirichlet Allocation (LDA) is applied to arrive at more abstract concepts. The proposed technique is able to reveal intrinsic concept relationships from multi-dimensional metadata structures. Experimental results demonstrate effectiveness of this approach for analytical ontological patterns exploitation. In this paper, the expediency of this technique for Visual Analytics application is demonstrated. The result indicates that the newly developed system can significantly enhance situation awareness and expedite actionable decision making.

  3. Modeling Choice and Valuation in Decision Experiments

    ERIC Educational Resources Information Center

    Loomes, Graham

    2010-01-01

    This article develops a parsimonious descriptive model of individual choice and valuation in the kinds of experiments that constitute a substantial part of the literature relating to decision making under risk and uncertainty. It suggests that many of the best known "regularities" observed in those experiments may arise from a tendency for…

  4. Neurally Constrained Modeling of Perceptual Decision Making

    ERIC Educational Resources Information Center

    Purcell, Braden A.; Heitz, Richard P.; Cohen, Jeremiah Y.; Schall, Jeffrey D.; Logan, Gordon D.; Palmeri, Thomas J.

    2010-01-01

    Stochastic accumulator models account for response time in perceptual decision-making tasks by assuming that perceptual evidence accumulates to a threshold. The present investigation mapped the firing rate of frontal eye field (FEF) visual neurons onto perceptual evidence and the firing rate of FEF movement neurons onto evidence accumulation to…

  5. Decision models for capital investment and financing decisions in hospitals.

    PubMed Central

    Vraciu, R A

    1980-01-01

    The literature on capital investment and financing decisions for hospitals has suggested several approaches to analyzing sets of options. In this paper, I present a taxonomy of the different approaches; analyze and compare the different elements of the taxonomy; and illustrate and discuss the information that can be gained by using each approach. I view these different analytic methods as complementary rather than competing methods of providing information to decision makers, and argue that the complex nature of hospital objectives demands the use of more than one approach. Failure to do this may lead to biased evaluations and poor decision making. PMID:6768699

  6. Variable Perceptions of Decision: An Operationalization of Four Models.

    ERIC Educational Resources Information Center

    Benjamin, Beverly P.; Kerchner, Charles T.

    Decision-making and the models of decision-making that people carry in their minds were assessed. Participants in a public policy decision involving early childhood education were mapped onto four frequently used models of decision making: the rational, the bureaucratic, organizational process (Allison, 1971) and the garbage can or organized…

  7. Adaptive Decision Modeling in Wisconsin River Islands

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  8. Modelling and Decision Support of Clinical Pathways

    NASA Astrophysics Data System (ADS)

    Gabriel, Roland; Lux, Thomas

    The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.

  9. Flood Impact Modelling to support decision making

    NASA Astrophysics Data System (ADS)

    Owen, Gareth; Quinn, Paul; O'Donnell, Greg

    2015-04-01

    Much of what is known about the impacts of landuse change and Natural Flood Management (NFM) is at the local/plot scale. Evidence of the downstream impacts at the larger catchment scale is limited. However, the strategic and financial decisions of land managers, stakeholders and policy makers are made at the larger scale. There are a number of techniques that have the potential to scale local impacts to the catchment scale. This poster will show findings for the 30km2 Leven catchment, North Yorkshire, England. A NFM approach has been adopted by the Environment Agency to reduce flood risk within the catchment. A dense network of stream level gauges were installed in the catchment at the commencement of this project to gain a detailed understanding of the catchment behaviour during storm events. A novel Flood Impact Modelling (FIM) approach has been adopted which uses the network of gauges to disaggregate the outlet hydrograph in terms of source locations. Using a combination of expert opinion and local evidence, the model can be used to assess the impacts of distributed changes in land use management and NFM on flood events. A number of potential future landuse and NFM scenarios have been modelled to investigate their impact on flood peaks. These modelled outcomes are mapped to a simple Decision Support Matrix (DSM). The DSM encourages end users (e.g. land managers and policy makers) to develop an NFM scheme by studying the degree to which local runoff can be attenuated and how that flow will propagate through the network to the point of impact. The DSM relates the impact on flood peaks in terms of alterations to soil management practices and landscape flow connectivity (e.g. soil underdrainage), which can be easily understood by farmers and land managers. The DSM and the FIM together provide a simple to use and transparent modelling tool, making best use of expert knowledge, to support decision making.

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

    NASA Technical Reports Server (NTRS)

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

    1971-01-01

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

  11. Decision Tree Modeling for Ranking Data

    NASA Astrophysics Data System (ADS)

    Yu, Philip L. H.; Wan, Wai Ming; Lee, Paul H.

    Ranking/preference data arises from many applications in marketing, psychology, and politics. We establish a new decision tree model for the analysis of ranking data by adopting the concept of classification and regression tree. The existing splitting criteria are modified in a way that allows them to precisely measure the impurity of a set of ranking data. Two types of impurity measures for ranking data are introduced, namelyg-wise and top-k measures. Theoretical results show that the new measures exhibit properties of impurity functions. In model assessment, the area under the ROC curve (AUC) is applied to evaluate the tree performance. Experiments are carried out to investigate the predictive performance of the tree model for complete and partially ranked data and promising results are obtained. Finally, a real-world application of the proposed methodology to analyze a set of political rankings data is presented.

  12. A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

    NASA Astrophysics Data System (ADS)

    Zhang, Wancheng; Xu, Yejun; Wang, Huimin

    2016-01-01

    The aim of this paper is to put forward a consensus reaching method for multi-attribute group decision-making (MAGDM) problems with linguistic information, in which the weight information of experts and attributes is unknown. First, some basic concepts and operational laws of 2-tuple linguistic label are introduced. Then, a grey relational analysis method and a maximising deviation method are proposed to calculate the incomplete weight information of experts and attributes respectively. To eliminate the conflict in the group, a weight-updating model is employed to derive the weights of experts based on their contribution to the consensus reaching process. After conflict elimination, the final group preference can be obtained which will give the ranking of the alternatives. The model can effectively avoid information distortion which is occurred regularly in the linguistic information processing. Finally, an illustrative example is given to illustrate the application of the proposed method and comparative analysis with the existing methods are offered to show the advantages of the proposed method.

  13. Difficult Budgetary Decisions: A Desk-Top Calculator Model to Facilitate Executive Decisions.

    ERIC Educational Resources Information Center

    Tweddale, R. Bruce

    Presented is a budgetary decision model developed to aid the executive officers in arriving at tentative decisions on enrollment, tuition rates, increased compensation, and level of staffing as they affect the total institutional budget. The model utilizes a desk-top programmable calculator (in this case, a Burroughs Model C 3660). The model…

  14. Contribution of the Multi Attribute Value Theory to conflict resolution in groundwater management. Application to the Mancha Oriental groundwater system, Spain

    NASA Astrophysics Data System (ADS)

    Apperl, B.; Andreu, J.; Karjalainen, T. P.; Pulido-Velazquez, M.

    2014-09-01

    The implementation of the EU Water Framework Directive demands participatory water resource management approaches. Decision making in groundwater quantity and quality management is complex because of the existence of many independent actors, heterogeneous stakeholder interests, multiple objectives, different potential policies, and uncertain outcomes. Conflicting stakeholder interests have been often identified as an impediment to the realization and success of water regulations and policies. The management of complex groundwater systems requires clarifying stakeholders' positions (identifying stakeholders preferences and values), improving transparency with respect to outcomes of alternatives, and moving the discussion from the selection of alternatives towards definition of fundamental objectives (value-thinking approach), what facilitates negotiation. The aims of the study are to analyse the potential of the multi attribute value theory for conflict resolution in groundwater management and to evaluate the benefit of stakeholder incorporation in the different stages of the planning process to find an overall satisfying solution for groundwater management. The research was conducted in the Mancha Oriental groundwater system (Spain), subject to an intensive use of groundwater for irrigation. A complex set of objectives and attributes were defined, and the management alternatives were created by a combination of different fundamental actions, considering different implementation stages and future changes in water resources availability. Interviews were conducted with representative stakeholder groups using an interactive platform, showing simultaneously the consequences of changes of preferences to the alternative ranking. Results show that the acceptation of alternatives depends strongly on the combination of measures and the implementation stages. Uncertainties of the results were notable but did not influence heavily on the alternative ranking. The expected

  15. Contribution of the multi-attribute value theory to conflict resolution in groundwater management - application to the Mancha Oriental groundwater system, Spain

    NASA Astrophysics Data System (ADS)

    Apperl, B.; Pulido-Velazquez, M.; Andreu, J.; Karjalainen, T. P.

    2015-03-01

    The implementation of the EU Water Framework Directive demands participatory water resource management approaches. Decision making in groundwater quantity and quality management is complex because of the existence of many independent actors, heterogeneous stakeholder interests, multiple objectives, different potential policies, and uncertain outcomes. Conflicting stakeholder interests have often been identified as an impediment to the realisation and success of water regulations and policies. The management of complex groundwater systems requires the clarification of stakeholders' positions (identifying stakeholder preferences and values), improving transparency with respect to outcomes of alternatives, and moving the discussion from the selection of alternatives towards the definition of fundamental objectives (value-thinking approach), which facilitates negotiation. The aims of the study are to analyse the potential of the multi-attribute value theory for conflict resolution in groundwater management and to evaluate the benefit of stakeholder incorporation into the different stages of the planning process, to find an overall satisfying solution for groundwater management. The research was conducted in the Mancha Oriental groundwater system (Spain), subject to intensive use of groundwater for irrigation. A complex set of objectives and attributes was defined, and the management alternatives were created by a combination of different fundamental actions, considering different implementation stages and future changes in water resource availability. Interviews were conducted with representative stakeholder groups using an interactive platform, showing simultaneously the consequences of changes in preferences to the alternative ranking. Results show that the approval of alternatives depends strongly on the combination of measures and the implementation stages. Uncertainties in the results were notable, but did not influence the alternative ranking heavily. The

  16. Subjective Expected Utility: A Model of Decision-Making.

    ERIC Educational Resources Information Center

    Fischoff, Baruch; And Others

    1981-01-01

    Outlines a model of decision making known to researchers in the field of behavioral decision theory (BDT) as subjective expected utility (SEU). The descriptive and predictive validity of the SEU model, probability and values assessment using SEU, and decision contexts are examined, and a 54-item reference list is provided. (JL)

  17. A communication model of shared decision making: accounting for cancer treatment decisions.

    PubMed

    Siminoff, Laura A; Step, Mary M

    2005-07-01

    The authors present a communication model of shared decision making (CMSDM) that explicitly identifies the communication process as the vehicle for decision making in cancer treatment. In this view, decision making is necessarily a sociocommunicative process whereby people enter into a relationship, exchange information, establish preferences, and choose a course of action. The model derives from contemporary notions of behavioral decision making and ethical conceptions of the doctor-patient relationship. This article briefly reviews the theoretical approaches to decision making, notes deficiencies, and embeds a more socially based process into the dynamics of the physician-patient relationship, focusing on cancer treatment decisions. In the CMSDM, decisions depend on (a) antecedent factors that have potential to influence communication, (b) jointly constructed communication climate, and (c) treatment preferences established by the physician and the patient. PMID:16045427

  18. High dimensional decision dilemmas in climate models

    NASA Astrophysics Data System (ADS)

    Bracco, A.; Neelin, J. D.; Luo, H.; McWilliams, J. C.; Meyerson, J. E.

    2013-05-01

    An important source of uncertainty in climate models is linked to the calibration of model parameters. Interest in systematic and automated parameter optimization procedures stems from the desire to improve the model climatology and to quantify the average sensitivity associated with potential changes in the climate system. Neelin et al. (2010) used a quadratic metamodel to objectively calibrate an atmospheric circulation model (AGCM) around four adjustable parameters. The metamodel accurately estimates global spatial averages of common fields of climatic interest, from precipitation, to low and high level winds, from temperature at various levels to sea level pressure and geopotential height, while providing a computationally cheap strategy to explore the influence of parameter settings. Here, guided by the metamodel, the ambiguities or dilemmas related to the decision making process in relation to model sensitivity and optimization are examined. Simulations of current climate are subject to considerable regional-scale biases. Those biases may vary substantially depending on the climate variable considered, and/or on the performance metric adopted. Common dilemmas are associated with model revisions yielding improvement in one field or regional pattern or season, but degradation in another, or improvement in the model climatology but degradation in the interannual variability representation. Challenges are posed to the modeler by the high dimensionality of the model output fields and by the large number of adjustable parameters. The use of the metamodel in the optimization strategy helps visualize trade-offs at a regional level, e.g. how mismatches between sensitivity and error spatial fields yield regional errors under minimization of global objective functions.

  19. High dimensional decision dilemmas in climate models

    NASA Astrophysics Data System (ADS)

    Bracco, A.; Neelin, J. D.; Luo, H.; McWilliams, J. C.; Meyerson, J. E.

    2013-10-01

    An important source of uncertainty in climate models is linked to the calibration of model parameters. Interest in systematic and automated parameter optimization procedures stems from the desire to improve the model climatology and to quantify the average sensitivity associated with potential changes in the climate system. Building upon on the smoothness of the response of an atmospheric circulation model (AGCM) to changes of four adjustable parameters, Neelin et al. (2010) used a quadratic metamodel to objectively calibrate the AGCM. The metamodel accurately estimates global spatial averages of common fields of climatic interest, from precipitation, to low and high level winds, from temperature at various levels to sea level pressure and geopotential height, while providing a computationally cheap strategy to explore the influence of parameter settings. Here, guided by the metamodel, the ambiguities or dilemmas related to the decision making process in relation to model sensitivity and optimization are examined. Simulations of current climate are subject to considerable regional-scale biases. Those biases may vary substantially depending on the climate variable considered, and/or on the performance metric adopted. Common dilemmas are associated with model revisions yielding improvement in one field or regional pattern or season, but degradation in another, or improvement in the model climatology but degradation in the interannual variability representation. Challenges are posed to the modeler by the high dimensionality of the model output fields and by the large number of adjustable parameters. The use of the metamodel in the optimization strategy helps visualize trade-offs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional errors under minimization of global objective functions.

  20. A Model for Evaluation of Decision Passages.

    ERIC Educational Resources Information Center

    Stimac, Michele

    In an age when decision making is becoming more and more significant for us human beings as we face dilemmas about whether or not to clone, to engineer behavior on mass scale, to expand or to decrease nuclear power, we educators must assist students to increase their decision-making skills. Many of our students will soon be decision makers for…

  1. Modeling boolean decision rules applied to multiple-observer decision strategies.

    PubMed

    Maguire, W

    1996-01-01

    A model that derives multiple-observer decision strategy ROC curves for boolean decision rules applied to binary decisions of two or three observers is presented. It is assumed that covert decision variables consistent with ROC models of observer performance underlie decisions and that readers' decision criteria are in a fixed relationship. The specific parameters of individual ROC curves and the correlational structure that describes interobserver agreement have dramatic effects upon the relative benefits to be derived from different boolean strategies. A common strategy employed in clinical practice, in which the overall decision is positive if any observer makes a positive decision, is most effective when the readers are of similar ability, when they adopt similar decision criteria, when interreader agreement is greater for negative than for positive cases, and when the individual ROC slope is <1.0. Different multiple-observer decision strategies can be evaluated using the model equations. A bootstrap method for testing model-associated hypotheses is described. PMID:8717599

  2. 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.

  3. Application of the Multi-Attribute Value Theory for engaging stakeholders in groundwater protection in the Vosvozis catchment in Greece.

    PubMed

    Stefanopoulos, Kyriakos; Yang, Hong; Gemitzi, Alexandra; Tsagarakis, Konstantinos P

    2014-02-01

    Multi-Attribute Value Theory (MAVT) was used to investigate stakeholders' preferences and beliefs in ameliorating a deteriorating ecosystem, i.e. Vosvozis River and Ismarida Lake in Northeastern Greece. Various monetary and environmental criteria were evaluated with scores and weights by different stakeholder groups and key individuals such as farmers, fishermen, entrepreneurs, residents and ecologists to elicit their preferences concerning alternative protection scenarios. The ultimate objective was to propose policy recommendations for a sustainable water resources management for the case study area. The analysis revealed an overwhelming agreement among stakeholders regarding the dire need for immediate actions in order to preserve and enhance Vosvozis ecosystem. With a two stage evaluation process, the MAVT analysis led to a high consensus among the stakeholders on the alternative that favors water recycling from the wastewater treatment plant combined with small dams for rainwater harvesting. PMID:24121661

  4. The Multi-Attribute Task Battery II (MATB-II) Software for Human Performance and Workload Research: A User's Guide

    NASA Technical Reports Server (NTRS)

    Santiago-Espada, Yamira; Myer, Robert R.; Latorella, Kara A.; Comstock, James R., Jr.

    2011-01-01

    The Multi-Attribute Task Battery (MAT Battery). is a computer-based task designed to evaluate operator performance and workload, has been redeveloped to operate in Windows XP Service Pack 3, Windows Vista and Windows 7 operating systems.MATB-II includes essentially the same tasks as the original MAT Battery, plus new configuration options including a graphical user interface for controlling modes of operation. MATB-II can be executed either in training or testing mode, as defined by the MATB-II configuration file. The configuration file also allows set up of the default timeouts for the tasks, the flow rates of the pumps and tank levels of the Resource Management (RESMAN) task. MATB-II comes with a default event file that an experimenter can modify and adapt

  5. A Bayesian Attractor Model for Perceptual Decision Making

    PubMed Central

    Bitzer, Sebastian; Bruineberg, Jelle; Kiebel, Stefan J.

    2015-01-01

    Even for simple perceptual decisions, the mechanisms that the brain employs are still under debate. Although current consensus states that the brain accumulates evidence extracted from noisy sensory information, open questions remain about how this simple model relates to other perceptual phenomena such as flexibility in decisions, decision-dependent modulation of sensory gain, or confidence about a decision. We propose a novel approach of how perceptual decisions are made by combining two influential formalisms into a new model. Specifically, we embed an attractor model of decision making into a probabilistic framework that models decision making as Bayesian inference. We show that the new model can explain decision making behaviour by fitting it to experimental data. In addition, the new model combines for the first time three important features: First, the model can update decisions in response to switches in the underlying stimulus. Second, the probabilistic formulation accounts for top-down effects that may explain recent experimental findings of decision-related gain modulation of sensory neurons. Finally, the model computes an explicit measure of confidence which we relate to recent experimental evidence for confidence computations in perceptual decision tasks. PMID:26267143

  6. Leadership of risk decision making in a complex, technology organization: The deliberative decision making model

    NASA Astrophysics Data System (ADS)

    Flaming, Susan C.

    2007-12-01

    The continuing saga of satellite technology development is as much a story of successful risk management as of innovative engineering. How do program leaders on complex, technology projects manage high stakes risks that threaten business success and satellite performance? This grounded theory study of risk decision making portrays decision leadership practices at one communication satellite company. Integrated product team (IPT) leaders of multi-million dollar programs were interviewed and observed to develop an extensive description of the leadership skills required to navigate organizational influences and drive challenging risk decisions to closure. Based on the study's findings the researcher proposes a new decision making model, Deliberative Decision Making, to describe the program leaders' cognitive and organizational leadership practices. This Deliberative Model extends the insights of prominent decision making models including the rational (or classical) and the naturalistic and qualifies claims made by bounded rationality theory. The Deliberative Model describes how leaders proactively engage resources to play a variety of decision leadership roles. The Model incorporates six distinct types of leadership decision activities, undertaken in varying sequence based on the challenges posed by specific risks. Novel features of the Deliberative Decision Model include: an inventory of leadership methods for managing task challenges, potential stakeholder bias and debates; four types of leadership meta-decisions that guide decision processes, and aligned organizational culture. Both supporting and constraining organizational influences were observed as leaders managed major risks, requiring active leadership on the most difficult decisions. Although the company's engineering culture emphasized the importance of data-based decisions, the uncertainties intrinsic to satellite risks required expert engineering judgment to be exercised throughout. An investigation into

  7. A control theory model for human decision making

    NASA Technical Reports Server (NTRS)

    Levison, W. H.

    1972-01-01

    The optimal control model for pilot-vehicle systems has been extended to handle certain types of human decision tasks. The model for decision making incorporates the observation noise, optimal estimation, and prediction concepts that form the basis of the model for control behavior. Experiments are described for the following task situations: (1) single decision tasks; (2) two decision tasks; and (3) simultaneous manual control and decision tasks. Using fixed values for model parameters, single-task and two-task decision performance scores to within an accuracy of 10 percent can be predicted. The experiment on simultaneous control and decision indicates the presence of task interference in this situation, but the results are not adequate to allow a conclusive test of the predictive capability of the model.

  8. Use of Multi-attribute Utility Functions in Evaluating Security Systems

    SciTech Connect

    Meyers, C; Lamont, A; Sicherman, A

    2008-06-13

    In analyzing security systems, we are concerned with protecting a building or facility from an attack by an adversary. Typically, we address the possibility that an adversary could enter a building and cause damage resulting in an immediate loss of life, or at least substantial disruption in the operations of the facility. In response to this setting, we implement security systems including devices, procedures, and facility upgrades designed to (a) prevent the adversary from entering, (b) detect and neutralize him if he does enter, and (c) harden the facility to minimize damage if an attack is carried out successfully. Although we have cast this in terms of physical protection of a building, the same general approach can be applied to non-physical attacks such as cyber attacks on a computer system. A rigorous analytic process is valuable for quantitatively evaluating an existing system, identifying its weaknesses, and proposing useful upgrades. As such, in this paper we describe an approach to assess the degree of overall protection provided by security measures. Our approach evaluates the effectiveness of the individual components of the system, describes how the components work together, and finally assesses the degree of overall protection achieved. This model can then be used to quantify the amount of protection provided by existing security measures, as well as to address proposed upgrades to the system and help identify a robust and cost effective set of improvements. Within the model, we use multiattribute utility functions to perform the overall evaluations of the system.

  9. Multi-Attribute Seismic/Rock Physics Approach to Characterizing Fractured Reservoirs

    SciTech Connect

    Gary Mavko

    2004-11-30

    is likely to be more intense near faults--sometimes referred to as the damaged zone. Yet another constraint, based on world-wide observations, is that the maximum likely fracture density increases with depth in a well-defined way. Defining these prior constrains has several benefits: they lead to a priori probability distributions of fractures, that are important for objective statistical integration; they limit the number of geologic hypotheses that need to be theoretically modeled; they provide plausible models for fracture distributions below the seismic resolution. The second element was theoretical rock physics modeling of optimal seismic attributes, including offset and azimuth dependence of traveltime, amplitude, and impedance signatures of anisotropic fractured rocks. The suggested workflow is to begin with an elastic earth model, based on well logs, theoretically add fractures to the likely facies as defined by the geologic prior information, and then compute synthetic seismic traces and attributes, including variations in P and S-wave velocities, Poisson's ratio, reflectivity, travel time, attenuation, and anisotropies of these parameters. This workflow is done in a Monte-Carlo fashion, yielding ranges of expected fracture signatures, and allowing realistic assessments of uncertainty to be honored. The third element was statistical integration of the geophysical data and prior constraints to map fracture intensity and orientations, along with uncertainties. A Bayesian framework was developed that allowed systematic integration of the prior constraints, the theoretical relations between fractures and their seismic signatures, and the various observed seismic observations. The integration scheme was successfully applied on an East Texas field site. The primary benefit from the study was the optimization and refinement of practical workflows for improved geophysical characterization of natural fractures and for quantifying the uncertainty of these

  10. Seasonal to Interannual Hydroclimatic Prediction: From Identification of Dynamics to Multi-Attribute Forecasts

    NASA Astrophysics Data System (ADS)

    Lall, U.

    2004-12-01

    Dynamical and Statistical Models for seasonal to interannual forecasts of key hydroclimatic state variables have been explored in recent years. Many authors report success based on typical performance metrics. Thus, a casual external observer may feel that we are at the verge of a breakthrough in hydrologic prediction, and hence in water resource management. This talk explores this notion, with particular regard to the multi-scale (time and space) nature of hydrologic fluxes, and of the management variables and styles that the water resources community has become accustomed to. A conceptual framework for the nascent predictive science of hydroclimatology is developed and exemplified. Aspects of the dynamics that need to be understood, and a unifying estimation/inference framework are proposed.

  11. Seasonal to Interannual Hydroclimatic Prediction: From Identification of Dynamics to Multi-Attribute Forecasts

    NASA Astrophysics Data System (ADS)

    Lall, U.

    2004-05-01

    Dynamical and Statistical Models for seasonal to interannual forecasts of key hydroclimatic state variables have been explored in recent years. Many authors report success based on typical performance metrics. Thus, a casual external observer may feel that we are at the verge of a breakthrough in hydrologic prediction, and hence in water resource management. This talk explores this notion, with particular regard to the multi-scale (time and space) nature of hydrologic fluxes, and of the management variables and styles that the water resources community has become accustomed to. A conceptual framework for the nascent predictive science of hydroclimatology is developed and exemplified. Aspects of the dynamics that need to be understood, and a unifying estimation/inference framework are proposed.

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

    ERIC Educational Resources Information Center

    Horgan, Dianne D.

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

  13. Recognizing Multiple Decision-Making Models: A Guide for Managers.

    ERIC Educational Resources Information Center

    Giesecke, Joan

    1993-01-01

    Provides a theoretical overview of decision-making models which are applicable to libraries; presents a framework for comparing the rational, political bargaining, and garbage can models; describes a case study that applied the models to a decision regarding an academic library governance system; and discusses strategies for library managers for…

  14. Making Insulation Decisions through Mathematical Modeling

    ERIC Educational Resources Information Center

    Yanik, H. Bahadir; Memis, Yasin

    2014-01-01

    Engaging students in studies about conservation and sustainability can support their understanding of making environmental conscious decisions to conserve Earth. This article aims to contribute these efforts and direct students' attention to how they can use mathematics to make environmental decisions. Contributors to iSTEM: Integrating…

  15. Multi-attribute criteria applied to electric generation energy system analysis LDRD.

    SciTech Connect

    Kuswa, Glenn W.; Tsao, Jeffrey Yeenien; Drennen, Thomas E.; Zuffranieri, Jason V.; Paananen, Orman Henrie; Jones, Scott A.; Ortner, Juergen G.; Brewer, Jeffrey D.; Valdez, Maximo M.

    2005-10-01

    This report began with a Laboratory-Directed Research and Development (LDRD) project to improve Sandia National Laboratories multidisciplinary capabilities in energy systems analysis. The aim is to understand how various electricity generating options can best serve needs in the United States. The initial product is documented in a series of white papers that span a broad range of topics, including the successes and failures of past modeling studies, sustainability, oil dependence, energy security, and nuclear power. Summaries of these projects are included here. These projects have provided a background and discussion framework for the Energy Systems Analysis LDRD team to carry out an inter-comparison of many of the commonly available electric power sources in present use, comparisons of those options, and efforts needed to realize progress towards those options. A computer aid has been developed to compare various options based on cost and other attributes such as technological, social, and policy constraints. The Energy Systems Analysis team has developed a multi-criteria framework that will allow comparison of energy options with a set of metrics that can be used across all technologies. This report discusses several evaluation techniques and introduces the set of criteria developed for this LDRD.

  16. Feature Integration in the Mapping of Multi-Attribute Visual Stimuli to Responses

    PubMed Central

    Ishizaki, Takuya; Morita, Hiromi; Morita, Masahiko

    2015-01-01

    In the human visual system, different attributes of an object, such as shape and color, are separately processed in different modules and then integrated to elicit a specific response. In this process, different attributes are thought to be temporarily “bound” together by focusing attention on the object; however, how such binding contributes to stimulus-response mapping remains unclear. Here we report that learning and performance of stimulus-response tasks was more difficult when three attributes of the stimulus determined the correct response than when two attributes did. We also found that spatially separated presentations of attributes considerably complicated the task, although they did not markedly affect target detection. These results are consistent with a paired-attribute model in which bound feature pairs, rather than object representations, are associated with responses by learning. This suggests that attention does not bind three or more attributes into a unitary object representation, and long-term learning is required for their integration. PMID:25762010

  17. Incorporating affective bias in models of human decision making

    NASA Technical Reports Server (NTRS)

    Nygren, Thomas E.

    1991-01-01

    Research on human decision making has traditionally focused on how people actually make decisions, how good their decisions are, and how their decisions can be improved. Recent research suggests that this model is inadequate. Affective as well as cognitive components drive the way information about relevant outcomes and events is perceived, integrated, and used in the decision making process. The affective components include how the individual frames outcomes as good or bad, whether the individual anticipates regret in a decision situation, the affective mood state of the individual, and the psychological stress level anticipated or experienced in the decision situation. A focus of the current work has been to propose empirical studies that will attempt to examine in more detail the relationships between the latter two critical affective influences (mood state and stress) on decision making behavior.

  18. The medical decision model and decision maker tools for management of radiological and nuclear incidents.

    PubMed

    Koerner, John F; Coleman, C Norman; Murrain-Hill, Paula; FitzGerald, Denis J; Sullivan, Julie M

    2014-06-01

    Effective decision making during a rapidly evolving emergency such as a radiological or nuclear incident requires timely interim decisions and communications from onsite decision makers while further data processing, consultation, and review are ongoing by reachback experts. The authors have recently proposed a medical decision model for use during a radiological or nuclear disaster, which is similar in concept to that used in medical care, especially when delay in action can have disastrous effects. For decision makers to function most effectively during a complex response, they require access to onsite subject matter experts who can provide information, recommendations, and participate in public communication efforts. However, in the time before this expertise is available or during the planning phase, just-in-time tools are essential that provide critical overview of the subject matter written specifically for the decision makers. Recognizing the complexity of the science, risk assessment, and multitude of potential response assets that will be required after a nuclear incident, the Office of the Assistant Secretary for Preparedness and Response, in collaboration with other government and non-government experts, has prepared a practical guide for decision makers. This paper illustrates how the medical decision model process could facilitate onsite decision making that includes using the deliberative reachback process from science and policy experts and describes the tools now available to facilitate timely and effective incident management. PMID:24776895

  19. A Layered Decision Model for Cost-Effective System Security

    SciTech Connect

    Wei, Huaqiang; Alves-Foss, James; Soule, Terry; Pforsich, Hugh; Zhang, Du; Frincke, Deborah A.

    2008-10-01

    System security involves decisions in at least three areas: identification of well-defined security policies, selection of cost-effective defence strategies, and implementation of real-time defence tactics. Although choices made in each of these areas affect the others, existing decision models typically handle these three decision areas in isolation. There is no comprehensive tool that can integrate them to provide a single efficient model for safeguarding a network. In addition, there is no clear way to determine which particular combinations of defence decisions result in cost-effective solutions. To address these problems, this paper introduces a Layered Decision Model (LDM) for use in deciding how to address defence decisions based on their cost-effectiveness. To validate the LDM and illustrate how it is used, we used simulation to test model rationality and applied the LDM to the design of system security for an e-commercial business case.

  20. Anticipatory network models of multicriteria decision-making processes

    NASA Astrophysics Data System (ADS)

    Skulimowski, Andrzej M. J.

    2014-01-01

    In this article, we will investigate the properties of a compromise solution selection method based on modelling the consequences of a decision as factors influencing the decision making in subsequent problems. Specifically, we assume that the constraints and preference structures in the (k + 1)st multicriteria optimisation problem depend on the values of criteria in the k-th problem. To make a decision in the initial problem, the decision maker should take into account the anticipated outcomes of each linked future decision problem. This model can be extended to a network of linked decision problems, such that causal relations are defined between the time-ordered nodes. Multiple edges starting from a decision node correspond to different future scenarios of consequences at this node. In addition, we will define the relation of anticipatory feedback, assuming that some decision makers take into account the anticipated future consequences of their decisions described by a network of optimisers - a class of information processing units introduced in this article. Both relations (causal and anticipatory) form a feedback information model, which makes possible a selection of compromise solutions taking into account the anticipated consequences. We provide constructive algorithms to solve discrete multicriteria decision problems that admit the above preference information structure. An illustrative example is presented in Section 4. Various applications of the above model, including the construction of technology foresight scenarios, are discussed in the final section of this article.

  1. Evolution of quantum-like modeling in decision making processes

    NASA Astrophysics Data System (ADS)

    Khrennikova, Polina

    2012-12-01

    The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

  2. Evolution of quantum-like modeling in decision making processes

    SciTech Connect

    Khrennikova, Polina

    2012-12-18

    The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schroedinger equation to describe the evolution of people's mental states. A shortcoming of Schroedinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

  3. Modeling Adversaries in Counterterrorism Decisions Using Prospect Theory.

    PubMed

    Merrick, Jason R W; Leclerc, Philip

    2016-04-01

    Counterterrorism decisions have been an intense area of research in recent years. Both decision analysis and game theory have been used to model such decisions, and more recently approaches have been developed that combine the techniques of the two disciplines. However, each of these approaches assumes that the attacker is maximizing its utility. Experimental research shows that human beings do not make decisions by maximizing expected utility without aid, but instead deviate in specific ways such as loss aversion or likelihood insensitivity. In this article, we modify existing methods for counterterrorism decisions. We keep expected utility as the defender's paradigm to seek for the rational decision, but we use prospect theory to solve for the attacker's decision to descriptively model the attacker's loss aversion and likelihood insensitivity. We study the effects of this approach in a critical decision, whether to screen containers entering the United States for radioactive materials. We find that the defender's optimal decision is sensitive to the attacker's levels of loss aversion and likelihood insensitivity, meaning that understanding such descriptive decision effects is important in making such decisions. PMID:25039254

  4. LATER models of neural decision behavior in choice tasks

    PubMed Central

    Noorani, Imran

    2014-01-01

    Reaction time has been increasingly used over the last few decades to provide information on neural decision processes: it is a direct reflection of decision time. Saccades provide an excellent paradigm for this because many of them can be made in a very short time and the underlying neural pathways are relatively well-known. LATER (linear approach to threshold with ergodic rate) is a model originally devised to explain reaction time distributions in simple decision tasks. Recently, however it is being extended to increasingly more advanced tasks, including those with decision errors and those requiring voluntary control such as the antisaccade task and those where sequential decisions are required. The strength of this modeling approach lies in its detailed, quantitative predictions of behavior, yet LATER models still retain their conceptual simplicity that made LATER initially successful in explaining reaction times in simple decision tasks. PMID:25202242

  5. Relevance of a Managerial Decision-Model to Educational Administration.

    ERIC Educational Resources Information Center

    Lundin, Edward.; Welty, Gordon

    The rational model of classical economic theory assumes that the decision maker has complete information on alternatives and consequences, and that he chooses the alternative that maximizes expected utility. This model does not allow for constraints placed on the decision maker resulting from lack of information, organizational pressures,…

  6. Ethical Decision-Making Models: A Review of the Literature.

    ERIC Educational Resources Information Center

    Cottone, R. Rocco; Claus, Ronald E.

    2000-01-01

    Presents a review of literature on ethical decision-making models in counseling, beginning in the fall of 1984 through the summer of 1998. Surveys theoretically or philosophically based, practice-based, and specialty-relevant approaches. Results indicate the literature is rich with decision-making model descriptions, although few have been…

  7. Development of a quantitative mass spectrometry multi-attribute method for characterization, quality control testing and disposition of biologics

    PubMed Central

    Rogers, Richard S; Nightlinger, Nancy S; Livingston, Brittney; Campbell, Phil; Bailey, Robert; Balland, Alain

    2015-01-01

    Regulatory agencies have recently recommended a Quality by Design (QbD) approach for the manufacturing of therapeutic molecules. A QbD strategy requires deep understanding at the molecular level of the attributes that are crucial for safety and efficacy and for insuring that the desired quality of the purified protein drug product is met at the end of the manufacturing process. A mass spectrometry (MS)-based approach to simultaneously monitor the extensive array of product quality attributes (PQAs) present on therapeutic molecules has been developed. This multi-attribute method (MAM) uses a combination of high mass accuracy / high resolution MS data generated by Orbitrap technology and automated identification and relative quantification of PQAs with dedicated software (Pinpoint). The MAM has the potential to replace several conventional electrophoretic and chromatographic methods currently used in Quality Control to release therapeutic molecules. The MAM represents an optimized analytical solution to focus on the attributes of the therapeutic molecule essential for function and implement QbD principles across process development, manufacturing and drug disposition. PMID:26186204

  8. Cotton Modeling for Climate Change, On-farm Decision Support, and Policy Decisions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop simulation models are valuable tools that scientists can use in testing hypothesis. Models also are used to identify the areas where knowledge is lacking, indicating the needs for future research activities. In addition, models are being used as decision support systems at the farm level to opt...

  9. Modeling uncertainty in requirements engineering decision support

    NASA Technical Reports Server (NTRS)

    Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.

    2005-01-01

    One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

  10. Models of Affective Decision Making: How Do Feelings Predict Choice?

    PubMed

    Charpentier, Caroline J; De Neve, Jan-Emmanuel; Li, Xinyi; Roiser, Jonathan P; Sharot, Tali

    2016-06-01

    Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to the value function in prospect theory, our feeling function showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighted when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision. PMID:27071751

  11. Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data

    PubMed Central

    Romo Bucheli, David Edmundo; Madabhushi, Anant

    2016-01-01

    Medical diagnostics is often a multi-attribute problem, necessitating sophisticated tools for analyzing high-dimensional biomedical data. Mining this data often results in two crucial bottlenecks: 1) high dimensionality of features used to represent rich biological data and 2) small amounts of labelled training data due to the expense of consulting highly specific medical expertise necessary to assess each study. Currently, no approach that we are aware of has attempted to use active learning in the context of dimensionality reduction approaches for improving the construction of low dimensional representations. We present our novel methodology, AdDReSS (Adaptive Dimensionality Reduction with Semi-Supervision), to demonstrate that fewer labeled instances identified via AL in embedding space are needed for creating a more discriminative embedding representation compared to randomly selected instances. We tested our methodology on a wide variety of domains ranging from prostate gene expression, ovarian proteomic spectra, brain magnetic resonance imaging, and breast histopathology. Across these various high dimensional biomedical datasets with 100+ observations each and all parameters considered, the median classification accuracy across all experiments showed AdDReSS (88.7%) to outperform SSAGE, a SSDR method using random sampling (85.5%), and Graph Embedding (81.5%). Furthermore, we found that embeddings generated via AdDReSS achieved a mean 35.95% improvement in Raghavan efficiency, a measure of learning rate, over SSAGE. Our results demonstrate the value of AdDReSS to provide low dimensional representations of high dimensional biomedical data while achieving higher classification rates with fewer labelled examples as compared to without active learning. PMID:27421116

  12. A Framework and Model for Evaluating Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper, we develop a four-phase model for evaluating architectures for clinical decision support that focuses on: defining a set of desirable features for a decision support architecture; building a proof-of-concept prototype; demonstrating that the architecture is useful by showing that it can be integrated with existing decision support systems and comparing its coverage to that of other architectures. We apply this framework to several well-known decision support architectures, including Arden Syntax, GLIF, SEBASTIAN and SAGE PMID:18462999

  13. A quantitative risk model for early lifecycle decision making

    NASA Technical Reports Server (NTRS)

    Feather, M. S.; Cornford, S. L.; Dunphy, J.; Hicks, K.

    2002-01-01

    Decisions made in the earliest phases of system development have the most leverage to influence the success of the entire development effort, and yet must be made when information is incomplete and uncertain. We have developed a scalable cost-benefit model to support this critical phase of early-lifecycle decision-making.

  14. Medical Specialty Decision Model: Utilizing Social Cognitive Career Theory

    ERIC Educational Resources Information Center

    Gibson, Denise D.; Borges, Nicole J.

    2004-01-01

    Objectives: The purpose of this study was to develop a working model to explain medical specialty decision-making. Using Social Cognitive Career Theory, we examined personality, medical specialty preferences, job satisfaction, and expectations about specialty choice to create a conceptual framework to guide specialty choice decision-making.…

  15. A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

    ERIC Educational Resources Information Center

    Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

    2015-01-01

    In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

  16. Rationality Validation of a Layered Decision Model for Network Defense

    SciTech Connect

    Wei, Huaqiang; Alves-Foss, James; Zhang, Du; Frincke, Deb

    2007-08-31

    We propose a cost-effective network defense strategy built on three key: three decision layers: security policies, defense strategies, and real-time defense tactics for countering immediate threats. A layered decision model (LDM) can be used to capture this decision process. The LDM helps decision-makers gain insight into the hierarchical relationships among inter-connected entities and decision types, and supports the selection of cost-effective defense mechanisms to safeguard computer networks. To be effective as a business tool, it is first necessary to validate the rationality of model before applying it to real-world business cases. This paper describes our efforts in validating the LDM rationality through simulation.

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

    PubMed

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

    2014-02-01

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

  18. A Representation for Gaining Insight into Clinical Decision Models

    PubMed Central

    Jimison, Holly B.

    1988-01-01

    For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient- specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.

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

    PubMed

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

    2016-08-01

    Individuals with schizophrenia have a diminished ability to use reward history to adaptively guide behavior. However, tasks traditionally used to assess such deficits often rely on multiple cognitive and neural processes, leaving etiology unresolved. In the current study, we adopted recent computational formalisms of reinforcement learning to distinguish between model-based and model-free decision-making in hopes of specifying mechanisms associated with reinforcement-learning dysfunction in schizophrenia. Under this framework, decision-making is model-free to the extent that it relies solely on prior reward history, and model-based if it relies on prospective information such as motivational state, future consequences, and the likelihood of obtaining various outcomes. Model-based and model-free decision-making was assessed in 33 schizophrenia patients and 30 controls using a 2-stage 2-alternative forced choice task previously demonstrated to discern individual differences in reliance on the 2 forms of reinforcement-learning. We show that, compared with controls, schizophrenia patients demonstrate decreased reliance on model-based decision-making. Further, parameter estimates of model-based behavior correlate positively with IQ and working memory measures, suggesting that model-based deficits seen in schizophrenia may be partially explained by higher-order cognitive deficits. These findings demonstrate specific reinforcement-learning and decision-making deficits and thereby provide valuable insights for understanding disordered behavior in schizophrenia. (PsycINFO Database Record PMID:27175984

  20. Decision making in bipolar disorder: a cognitive modeling approach.

    PubMed

    Yechiam, Eldad; Hayden, Elizabeth P; Bodkins, Misty; O'Donnell, Brian F; Hetrick, William P

    2008-11-30

    A formal modeling approach was used to characterize decision-making processes in bipolar disorder. Decision making was examined in 28 bipolar patients (14 acute and 14 remitted) and 25 controls using the Iowa Gambling Task (Bechara et al., 1994), a decision-making task used for assessing cognitive impulsivity. To disentangle motivational and cognitive aspects of decision-making processes, we applied a formal cognitive model to the performance on the Iowa Gambling Task. The model has three parameters: The relative impact of rewards and punishments on evaluations, the impact of recent and past payoffs, and the degree of choice consistency. The results indicated that acute bipolar patients were characterized by low choice consistency, or a tendency to make erratic choices. Low choice consistency improved the prediction of acute bipolar disorder beyond that provided by cognitive functioning and self-report measures of personality and temperament. PMID:18848361

  1. Healthcare ethics: a patient-centered decision model.

    PubMed

    Oddo, A R

    2001-01-01

    A common financial model used in business decisions is the cost/benefit comparison. The costs of a proposed project are compared with the benefits, and if the benefits outweigh the costs, the project is accepted; if the costs exceed the benefits, the project is rejected. This model is applicable when tangible costs and benefits can be reasonably measured in monetary units. However, it is difficult to consider intangible factors in this model because intangible factors cannot be readily quantified in money. While some might argue that the financial model should not apply to healthcare decisions, the fact is that costs do enter into the picture. People may decide to forego needed healthcare because they cannot afford it. Healthcare providers may make choices based in part on the costs of diagnosis and treatment, rather than solely on medical information and what is best for the patient. Should financial issues enter into healthcare decisions--decisions about human health and well being? If so, how should the costs and benefits be measured and evaluated? What are some ethical issues and dilemmas involved in such decisions. This paper addresses ethical dilemmas and financial issues in healthcare. A healthcare decision model, which considers medical information, financial information, as well as ethical and other intangible factors, is proposed. PMID:12530441

  2. Climate change decision-making: Model & parameter uncertainties explored

    SciTech Connect

    Dowlatabadi, H.; Kandlikar, M.; Linville, C.

    1995-12-31

    A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.

  3. RNA search with decision trees and partial covariance models.

    PubMed

    Smith, Jennifer A

    2009-01-01

    The use of partial covariance models to search for RNA family members in genomic sequence databases is explored. The partial models are formed from contiguous subranges of the overall RNA family multiple alignment columns. A binary decision-tree framework is presented for choosing the order to apply the partial models and the score thresholds on which to make the decisions. The decision trees are chosen to minimize computation time subject to the constraint that all of the training sequences are passed to the full covariance model for final evaluation. Computational intelligence methods are suggested to select the decision tree since the tree can be quite complex and there is no obvious method to build the tree in these cases. Experimental results from seven RNA families shows execution times of 0.066-0.268 relative to using the full covariance model alone. Tests on the full sets of known sequences for each family show that at least 95 percent of these sequences are found for two families and 100 percent for five others. Since the full covariance model is run on all sequences accepted by the partial model decision tree, the false alarm rate is at least as low as that of the full model alone. PMID:19644178

  4. A Conditional Model of Evidence-Based Decision Making

    PubMed Central

    Falzer, Paul R.; Garman, D. Melissa

    2009-01-01

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

  5. Evaluation information integration model on book purchasing bids

    NASA Astrophysics Data System (ADS)

    Wang, Wei; Jiao, Yang

    2011-12-01

    The multi attributes decision model is presented basing on a number of indicators of book procurement bidders, and by the characteristics of persons to engage in joint decision-making. For each evaluation to define the ideal solution and negative ideal solution, further the relative closeness of each evaluation person and each supplier. The ideal solution and negative ideal solution of the evaluation committee is defined based on the group closeness matrix, and then the results of the ultimate supplier evaluation are calculated by decision-making groups. In this paper, the model is through the application of experimental data.

  6. Crop Simulation Models and Decision Support Systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The first computer simulation models for agricultural systems were developed in the 1970s. These early models simulated potential production for major crops as a function of weather conditions, especially temperature and solar radiation. At a later stage, the water component was added to be able to ...

  7. Critical infrastructure protection decision support system decision model : overview and quick-start user's guide.

    SciTech Connect

    Samsa, M.; Van Kuiken, J.; Jusko, M.; Decision and Information Sciences

    2008-12-01

    The Critical Infrastructure Protection Decision Support System Decision Model (CIPDSS-DM) is a useful tool for comparing the effectiveness of alternative risk-mitigation strategies on the basis of CIPDSS consequence scenarios. The model is designed to assist analysts and policy makers in evaluating and selecting the most effective risk-mitigation strategies, as affected by the importance assigned to various impact measures and the likelihood of an incident. A typical CIPDSS-DM decision map plots the relative preference of alternative risk-mitigation options versus the annual probability of an undesired incident occurring once during the protective life of the investment, assumed to be 20 years. The model also enables other types of comparisons, including a decision map that isolates a selected impact variable and displays the relative preference for the options of interest--parameterized on the basis of the contribution of the isolated variable to total impact, as well as the likelihood of the incident. Satisfaction/regret analysis further assists the analyst or policy maker in evaluating the confidence with which one option can be selected over another.

  8. Measuring and modeling behavioral decision dynamics in collective evacuation.

    PubMed

    Carlson, Jean M; Alderson, David L; Stromberg, Sean P; Bassett, Danielle S; Craparo, Emily M; Guiterrez-Villarreal, Francisco; Otani, Thomas

    2014-01-01

    Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In a controlled laboratory setting, our results quantify several key factors influencing individual evacuation decision making in a controlled laboratory setting. The experiment includes tensions between broadcast and peer-to-peer information, and contrasts the effects of temporal urgency associated with the imminence of the disaster and the effects of limited shelter capacity for evacuees. Based on empirical measurements of the cumulative rate of evacuations as a function of the instantaneous disaster likelihood, we develop a quantitative model for decision making that captures remarkably well the main features of observed collective behavior across many different scenarios. Moreover, this model captures the sensitivity of individual- and population-level decision behaviors to external pressures, and systematic deviations from the model provide meaningful estimates of variability in the collective response. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios, specifically the development and testing of robust strategies for training and control of evacuations that account for human behavior and network topologies. PMID:24520331

  9. Measuring and Modeling Behavioral Decision Dynamics in Collective Evacuation

    PubMed Central

    Carlson, Jean M.; Alderson, David L.; Stromberg, Sean P.; Bassett, Danielle S.; Craparo, Emily M.; Guiterrez-Villarreal, Francisco; Otani, Thomas

    2014-01-01

    Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In a controlled laboratory setting, our results quantify several key factors influencing individual evacuation decision making in a controlled laboratory setting. The experiment includes tensions between broadcast and peer-to-peer information, and contrasts the effects of temporal urgency associated with the imminence of the disaster and the effects of limited shelter capacity for evacuees. Based on empirical measurements of the cumulative rate of evacuations as a function of the instantaneous disaster likelihood, we develop a quantitative model for decision making that captures remarkably well the main features of observed collective behavior across many different scenarios. Moreover, this model captures the sensitivity of individual- and population-level decision behaviors to external pressures, and systematic deviations from the model provide meaningful estimates of variability in the collective response. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios, specifically the development and testing of robust strategies for training and control of evacuations that account for human behavior and network topologies. PMID:24520331

  10. A model of the human observer and decision maker

    NASA Technical Reports Server (NTRS)

    Wewerinke, P. H.

    1981-01-01

    The decision process is described in terms of classical sequential decision theory by considering the hypothesis that an abnormal condition has occurred by means of a generalized likelihood ratio test. For this, a sufficient statistic is provided by the innovation sequence which is the result of the perception an information processing submodel of the human observer. On the basis of only two model parameters, the model predicts the decision speed/accuracy trade-off and various attentional characteristics. A preliminary test of the model for single variable failure detection tasks resulted in a very good fit of the experimental data. In a formal validation program, a variety of multivariable failure detection tasks was investigated and the predictive capability of the model was demonstrated.

  11. Coming Apart: A Model of the Marital Dissolution Decision.

    ERIC Educational Resources Information Center

    Edwards, John N.; Saunders, Janice M.

    1981-01-01

    Proposes a social-psychological model of the dissolution decision in marriage based on prior theoretical formulations. Sequential in character and emphasizing the duality of the marital relationship, the model modifies and refines previous theoretical efforts, and seeks to extend their explanatory power by incorporating various principles of…

  12. Helping Students Make Decisions with the Help of Egan's Model.

    ERIC Educational Resources Information Center

    Stephens, Ginny Lee; Reynolds, JoLynne

    1992-01-01

    Discusses using Gerald Egan's model for creative decision making as a career counseling tool. Explains why to use this model and how it was adapted to meet career counseling issues. Describes its successful use in three case studies with a college sophomore in search of a major, a new graduate in search of a first job, and a homemaker. (Author/ABL)

  13. A Utility Model for Teaching Load Decisions in Academic Departments.

    ERIC Educational Resources Information Center

    Massey, William F.; Zemsky, Robert

    1997-01-01

    Presents a utility model for academic department decision making and describes the structural specifications for analyzing it. The model confirms the class-size utility asymmetry predicted by the authors' academic rachet theory, but shows that marginal utility associated with college teaching loads is always negative. Curricular structure and…

  14. A sequential decision-theoretic model for medical diagnostic system.

    PubMed

    Li, Aiping; Jin, Songchang; Zhang, Lumin; Jia, Yan

    2015-01-01

    Although diagnostic expert systems using a knowledge base which models decision-making of traditional experts can provide important information to non-experts, they tend to duplicate the errors made by experts. Decision-Theoretic Model (DTM) is therefore very useful in expert system since they prevent experts from incorrect reasoning under uncertainty. For the diagnostic expert system, corresponding DTM and arithmetic are studied and a sequential diagnostic decision-theoretic model based on Bayesian Network is given. In the model, the alternative features are categorized into two classes (including diseases features and test features), then an arithmetic for prior of test is provided. The different features affect other features weights are also discussed. Bayesian Network is adopted to solve uncertainty presentation and propagation. The model can help knowledge engineers model the knowledge involved in sequential diagnosis and decide evidence alternative priority. A practical example of the models is also presented: at any time of the diagnostic process the expert is provided with a dynamically updated list of suggested tests in order to support him in the decision-making problem about which test to execute next. The results show it is better than the traditional diagnostic model which is based on experience. PMID:26410326

  15. Modeling Lexical Decision: The Form of Frequency and Diversity Effects

    ERIC Educational Resources Information Center

    Adelman, James S.; Brown, Gordon D. A.

    2008-01-01

    What is the root cause of word frequency effects on lexical decision times? W. S. Murray and K. I. Forster (2004) argued that such effects are linear in rank frequency, consistent with a serial search model of lexical access. In this article, the authors (a) describe a method of testing models of such effects that takes into account the…

  16. A Transcultural Integrative Model for Ethical Decision Making in Counseling.

    ERIC Educational Resources Information Center

    Garcia, Jorge, G.; Cartwright, Brenda; Winston, Stacey M.; Borzuchowska, Barbara

    2003-01-01

    The Transcultural Integrative Ethical Decision-Making Model in counseling addresses the need for including cultural factors in the process of ethical dilemma resolution. The proposed model is presented in a step-by-step, linear format that can be used by counselors facing ethical dilemmas in a variety of settings and with different cultural…

  17. Dissolving decision making? Models and their roles in decision-making processes and policy at large.

    PubMed

    Zeiss, Ragna; van Egmond, Stans

    2014-12-01

    This article studies the roles three science-based models play in Dutch policy and decision making processes. Key is the interaction between model construction and environment. Their political and scientific environments form contexts that shape the roles of models in policy decision making. Attention is paid to three aspects of the wider context of the models: a) the history of the construction process; b) (changes in) the political and scientific environments; and c) the use in policy processes over longer periods of time. Models are more successfully used when they are constructed in a stable political and scientific environment. Stability and certainty within a scientific field seems to be a key predictor for the usefulness of models for policy making. The economic model is more disputed than the ecology-based model and the model that has its theoretical foundation in physics and chemistry. The roles models play in policy processes are too complex to be considered as straightforward technocratic powers. PMID:25549446

  18. A decision model for environmental R and D

    SciTech Connect

    Chao, H.P.; Peck, S.

    1999-09-01

    In this paper, a simple decision model is formulated to investigate the optimal funding level for an environmental R and D activity. The Bayesian approach is extended to research in situations where the researchers have prior beliefs different from the ultimate decision makers. Sensitivity analysis demonstrated how the optimal level of R and D varies with assumptions about: (1) the shadow price of R and D resources, which is a measure of the scarcity of funds; (2) the technical difficulty of the research area; (3) the potential payoffs involved in the decision that may be influenced by the research outcome; and (4) the prior knowledge of the key decision makers. Among other insights, analysis of the model demonstrated that the optimal research expenditure jumped from zero to a significant amount or conversely with small changes in parameters. The jump occurred when the expected cost of an uniformed decision equals the cost of research plus the expected cost of the contingent decision. In addition, the optimal research expenditure was sensitive to the technical difficulty of the research area.

  19. Beyond pain: modeling decision-making deficits in chronic pain

    PubMed Central

    Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

    2014-01-01

    Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients’ behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals’ choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis. PMID:25136301

  20. Beyond pain: modeling decision-making deficits in chronic pain.

    PubMed

    Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

    2014-01-01

    Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients' behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals' choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis. PMID:25136301

  1. Consumer's Online Shopping Influence Factors and Decision-Making Model

    NASA Astrophysics Data System (ADS)

    Yan, Xiangbin; Dai, Shiliang

    Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.

  2. Bridging groundwater models and decision support with a Bayesian network

    USGS Publications Warehouse

    Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert

    2013-01-01

    Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

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

    PubMed

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

    2009-01-01

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

  4. Emergent collective decision-making: Control, model and behavior

    NASA Astrophysics Data System (ADS)

    Shen, Tian

    In this dissertation we study emergent collective decision-making in social groups with time-varying interactions and heterogeneously informed individuals. First we analyze a nonlinear dynamical systems model motivated by animal collective motion with heterogeneously informed subpopulations, to examine the role of uninformed individuals. We find through formal analysis that adding uninformed individuals in a group increases the likelihood of a collective decision. Secondly, we propose a model for human shared decision-making with continuous-time feedback and where individuals have little information about the true preferences of other group members. We study model equilibria using bifurcation analysis to understand how the model predicts decisions based on the critical threshold parameters that represent an individual's tradeoff between social and environmental influences. Thirdly, we analyze continuous-time data of pairs of human subjects performing an experimental shared tracking task using our second proposed model in order to understand transient behavior and the decision-making process. We fit the model to data and show that it reproduces a wide range of human behaviors surprisingly well, suggesting that the model may have captured the mechanisms of observed behaviors. Finally, we study human behavior from a game-theoretic perspective by modeling the aforementioned tracking task as a repeated game with incomplete information. We show that the majority of the players are able to converge to playing Nash equilibrium strategies. We then suggest with simulations that the mean field evolution of strategies in the population resemble replicator dynamics, indicating that the individual strategies may be myopic. Decisions form the basis of control and problems involving deciding collectively between alternatives are ubiquitous in nature and in engineering. Understanding how multi-agent systems make decisions among alternatives also provides insight for designing

  5. Landslide risk models for decision making.

    PubMed

    Bonachea, Jaime; Remondo, Juan; de Terán, José Ramón Díaz; González-Díez, Alberto; Cendrero, Antonio

    2009-11-01

    This contribution presents a quantitative procedure for landslide risk analysis and zoning considering hazard, exposure (or value of elements at risk), and vulnerability. The method provides the means to obtain landslide risk models (expressing expected damage due to landslides on material elements and economic activities in monetary terms, according to different scenarios and periods) useful to identify areas where mitigation efforts will be most cost effective. It allows identifying priority areas for the implementation of actions to reduce vulnerability (elements) or hazard (processes). The procedure proposed can also be used as a preventive tool, through its application to strategic environmental impact analysis (SEIA) of land-use plans. The underlying hypothesis is that reliable predictions about hazard and risk can be made using models based on a detailed analysis of past landslide occurrences in connection with conditioning factors and data on past damage. The results show that the approach proposed and the hypothesis formulated are essentially correct, providing estimates of the order of magnitude of expected losses for a given time period. Uncertainties, strengths, and shortcomings of the procedure and results obtained are discussed and potential lines of research to improve the models are indicated. Finally, comments and suggestions are provided to generalize this type of analysis. PMID:19732396

  6. A neuro-computational model of economic decisions.

    PubMed

    Rustichini, Aldo; Padoa-Schioppa, Camillo

    2015-09-01

    Neuronal recordings and lesion studies indicate that key aspects of economic decisions take place in the orbitofrontal cortex (OFC). Previous work identified in this area three groups of neurons encoding the offer value, the chosen value, and the identity of the chosen good. An important and open question is whether and how decisions could emerge from a neural circuit formed by these three populations. Here we adapted a biophysically realistic neural network previously proposed for perceptual decisions (Wang XJ. Neuron 36: 955-968, 2002; Wong KF, Wang XJ. J Neurosci 26: 1314-1328, 2006). The domain of economic decisions is significantly broader than that for which the model was originally designed, yet the model performed remarkably well. The input and output nodes of the network were naturally mapped onto two groups of cells in OFC. Surprisingly, the activity of interneurons in the network closely resembled that of the third group of cells, namely, chosen value cells. The model reproduced several phenomena related to the neuronal origins of choice variability. It also generated testable predictions on the excitatory/inhibitory nature of different neuronal populations and on their connectivity. Some aspects of the empirical data were not reproduced, but simple extensions of the model could overcome these limitations. These results render a biologically credible model for the neuronal mechanisms of economic decisions. They demonstrate that choices could emerge from the activity of cells in the OFC, suggesting that chosen value cells directly participate in the decision process. Importantly, Wang's model provides a platform to investigate the implications of neuroscience results for economic theory. PMID:26063776

  7. Weighted Hybrid Decision Tree Model for Random Forest Classifier

    NASA Astrophysics Data System (ADS)

    Kulkarni, Vrushali Y.; Sinha, Pradeep K.; Petare, Manisha C.

    2016-06-01

    Random Forest is an ensemble, supervised machine learning algorithm. An ensemble generates many classifiers and combines their results by majority voting. Random forest uses decision tree as base classifier. In decision tree induction, an attribute split/evaluation measure is used to decide the best split at each node of the decision tree. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation among them. The work presented in this paper is related to attribute split measures and is a two step process: first theoretical study of the five selected split measures is done and a comparison matrix is generated to understand pros and cons of each measure. These theoretical results are verified by performing empirical analysis. For empirical analysis, random forest is generated using each of the five selected split measures, chosen one at a time. i.e. random forest using information gain, random forest using gain ratio, etc. The next step is, based on this theoretical and empirical analysis, a new approach of hybrid decision tree model for random forest classifier is proposed. In this model, individual decision tree in Random Forest is generated using different split measures. This model is augmented by weighted voting based on the strength of individual tree. The new approach has shown notable increase in the accuracy of random forest.

  8. Integrated Environmental Modelling: human decisions, human challenges

    USGS Publications Warehouse

    Glynn, Pierre D.

    2015-01-01

    Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to issues with frequent, sharply distinguished, feedbacks. Unfortunately, human behaviour is not adapted to the more diffusely experienced problems that IEM typically seeks to address. Twelve biases are identified that affect IEM (and science in general). These biases are supported by personal observations and by the findings of behavioural scientists. A process for critical analysis is proposed that addresses some human challenges of IEM and solicits explicit description of (1) represented processes and information, (2) unrepresented processes and information, and (3) accounting for, and cognizance of, potential human biases. Several other suggestions are also made that generally complement maintaining attitudes of watchful humility, open-mindedness, honesty and transparent accountability. These suggestions include (1) creating a new area of study in the behavioural biogeosciences, (2) using structured processes for engaging the modelling and stakeholder communities in IEM, and (3) using ‘red teams’ to increase resilience of IEM constructs and use.

  9. Model-based decision support in diabetes care.

    PubMed

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

    2011-05-01

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

  10. Simple model for multiple-choice collective decision making.

    PubMed

    Lee, Ching Hua; Lucas, Andrew

    2014-11-01

    We describe a simple model of heterogeneous, interacting agents making decisions between n≥2 discrete choices. For a special class of interactions, our model is the mean field description of random field Potts-like models and is effectively solved by finding the extrema of the average energy E per agent. In these cases, by studying the propagation of decision changes via avalanches, we argue that macroscopic dynamics is well captured by a gradient flow along E. We focus on the permutation symmetric case, where all n choices are (on average) the same, and spontaneous symmetry breaking (SSB) arises purely from cooperative social interactions. As examples, we show that bimodal heterogeneity naturally provides a mechanism for the spontaneous formation of hierarchies between decisions and that SSB is a preferred instability to discontinuous phase transitions between two symmetric points. Beyond the mean field limit, exponentially many stable equilibria emerge when we place this model on a graph of finite mean degree. We conclude with speculation on decision making with persistent collective oscillations. Throughout the paper, we emphasize analogies between methods of solution to our model and common intuition from diverse areas of physics, including statistical physics and electromagnetism. PMID:25493831

  11. Simple model for multiple-choice collective decision making

    NASA Astrophysics Data System (ADS)

    Lee, Ching Hua; Lucas, Andrew

    2014-11-01

    We describe a simple model of heterogeneous, interacting agents making decisions between n ≥2 discrete choices. For a special class of interactions, our model is the mean field description of random field Potts-like models and is effectively solved by finding the extrema of the average energy E per agent. In these cases, by studying the propagation of decision changes via avalanches, we argue that macroscopic dynamics is well captured by a gradient flow along E . We focus on the permutation symmetric case, where all n choices are (on average) the same, and spontaneous symmetry breaking (SSB) arises purely from cooperative social interactions. As examples, we show that bimodal heterogeneity naturally provides a mechanism for the spontaneous formation of hierarchies between decisions and that SSB is a preferred instability to discontinuous phase transitions between two symmetric points. Beyond the mean field limit, exponentially many stable equilibria emerge when we place this model on a graph of finite mean degree. We conclude with speculation on decision making with persistent collective oscillations. Throughout the paper, we emphasize analogies between methods of solution to our model and common intuition from diverse areas of physics, including statistical physics and electromagnetism.

  12. Overcoming barriers to development of cooperative medical decision support models.

    PubMed

    Hudson, Donna L; Cohen, Maurice E

    2012-01-01

    Attempts to automate the medical decision making process have been underway for the at least fifty years, beginning with data-based approaches that relied chiefly on statistically-based methods. Approaches expanded to include knowledge-based systems, both linear and non-linear neural networks, agent-based systems, and hybrid methods. While some of these models produced excellent results none have been used extensively in medical practice. In order to move these methods forward into practical use, a number of obstacles must be overcome, including validation of existing systems on large data sets, development of methods for including new knowledge as it becomes available, construction of a broad range of decision models, and development of non-intrusive methods that allow the physician to use these decision aids in conjunction with, not instead of, his or her own medical knowledge. None of these four requirements will come easily. A cooperative effort among researchers, including practicing MDs, is vital, particularly as more information on diseases and their contributing factors continues to expand resulting in more parameters than the human decision maker can process effectively. In this article some of the basic structures that are necessary to facilitate the use of an automated decision support system are discussed, along with potential methods for overcoming existing barriers. PMID:23366358

  13. Emulation Modeling with Bayesian Networks for Efficient Decision Support

    NASA Astrophysics Data System (ADS)

    Fienen, M. N.; Masterson, J.; Plant, N. G.; Gutierrez, B. T.; Thieler, E. R.

    2012-12-01

    Bayesian decision networks (BDN) have long been used to provide decision support in systems that require explicit consideration of uncertainty; applications range from ecology to medical diagnostics and terrorism threat assessments. Until recently, however, few studies have applied BDNs to the study of groundwater systems. BDNs are particularly useful for representing real-world system variability by synthesizing a range of hydrogeologic situations within a single simulation. Because BDN output is cast in terms of probability—an output desired by decision makers—they explicitly incorporate the uncertainty of a system. BDNs can thus serve as a more efficient alternative to other uncertainty characterization methods such as computationally demanding Monte Carlo analyses and others methods restricted to linear model analyses. We present a unique application of a BDN to a groundwater modeling analysis of the hydrologic response of Assateague Island, Maryland to sea-level rise. Using both input and output variables of the modeled groundwater response to different sea-level (SLR) rise scenarios, the BDN predicts the probability of changes in the depth to fresh water, which exerts an important influence on physical and biological island evolution. Input variables included barrier-island width, maximum island elevation, and aquifer recharge. The variability of these inputs and their corresponding outputs are sampled along cross sections in a single model run to form an ensemble of input/output pairs. The BDN outputs, which are the posterior distributions of water table conditions for the sea-level rise scenarios, are evaluated through error analysis and cross-validation to assess both fit to training data and predictive power. The key benefit for using BDNs in groundwater modeling analyses is that they provide a method for distilling complex model results into predictions with associated uncertainty, which is useful to decision makers. Future efforts incorporate

  14. OASIS: A GRAPHICAL DECISION SUPPORT SYSTEM FOR GROUNDWATER CONTAMINANT MODELING

    EPA Science Inventory

    Three new software technologies were applied to develop an efficient and easy to use decision support system far ground-water contaminant modeling. raphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces....

  15. The Decision/Adoption Model as a Heuristic Program Theory.

    ERIC Educational Resources Information Center

    Tedrick, William E.

    The emerging concept of program theory and its function in program evaluation practice is the central focus of this paper. It appears that the traditional decision/adoption model, when considered in conjunction with the institutionalized beliefs, values, and methodological procedures of the state Cooperative Extension Services, meets the criteria…

  16. Modelling Human Emotions for Tactical Decision-Making Games

    ERIC Educational Resources Information Center

    Visschedijk, Gillian C.; Lazonder, Ard W.; van der Hulst, Anja; Vink, Nathalie; Leemkuil, Henny

    2013-01-01

    The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studies were performed to investigate the relation between fidelity and human emotion recognition in virtual human characters. Study 1 compared five versions of a virtual…

  17. A group decision-making model for siting LULUs

    SciTech Connect

    Juang, C.H.; Wu, S.; Sheu, H.J.

    1995-03-01

    This paper presents a group decision-making model for siting locally unwanted land uses (LULUs) such as hazardous and nonhazardous solid waste landfills. The new model is based on fuzzy set theory, which has been proven to be effective and efficient in handling ambiguous information such as opinions expressed by a panel of representatives with diverse backgrounds. The model involves an operation called fuzzy weighted average (FWA) for aggregating opinions. The weights used in the FWA operation are determined by the entropy method. Entropy is a measure of the uncertainty associated with a piece of information such as an opinion. By measuring the entropy of each of the opinions to be aggregated, the weight of each opinion may be objectively determined. The result of the FWA operation may be used to aid in making decisions. Examples are presented to illustrate the proposed model.

  18. How to Say "No" to a Nonword: A Leaky Competing Accumulator Model of Lexical Decision

    ERIC Educational Resources Information Center

    Dufau, Stephane; Grainger, Jonathan; Ziegler, Johannes C.

    2012-01-01

    We describe a leaky competing accumulator (LCA) model of the lexical decision task that can be used as a response/decision module for any computational model of word recognition. The LCA model uses evidence for a word, operationalized as some measure of lexical activity, as input to the "YES" decision node. Input to the "NO" decision node is…

  19. A decision-making process model of young online shoppers.

    PubMed

    Lin, Chin-Feng; Wang, Hui-Fang

    2008-12-01

    Based on the concepts of brand equity, means-end chain, and Web site trust, this study proposes a novel model called the consumption decision-making process of adolescents (CDMPA) to understand adolescents' Internet consumption habits and behavioral intention toward particular sporting goods. The findings of the CDMPA model can help marketers understand adolescents' consumption preferences and habits for developing effective Internet marketing strategies. PMID:19025465

  20. Robust Decision-making Applied to Model Selection

    SciTech Connect

    Hemez, Francois M.

    2012-08-06

    The scientific and engineering communities are relying more and more on numerical models to simulate ever-increasingly complex phenomena. Selecting a model, from among a family of models that meets the simulation requirements, presents a challenge to modern-day analysts. To address this concern, a framework is adopted anchored in info-gap decision theory. The framework proposes to select models by examining the trade-offs between prediction accuracy and sensitivity to epistemic uncertainty. The framework is demonstrated on two structural engineering applications by asking the following question: Which model, of several numerical models, approximates the behavior of a structure when parameters that define each of those models are unknown? One observation is that models that are nominally more accurate are not necessarily more robust, and their accuracy can deteriorate greatly depending upon the assumptions made. It is posited that, as reliance on numerical models increases, establishing robustness will become as important as demonstrating accuracy.

  1. Towards a controlled sensitivity analysis of model development decisions

    NASA Astrophysics Data System (ADS)

    Clark, Martyn; Nijssen, Bart

    2016-04-01

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

  2. On anthropomorphic decision making in a model observer

    NASA Astrophysics Data System (ADS)

    Avanaki, Ali R. N.; Espig, Kathryn S.; Kimpe, Tom R. L.; Maidment, Andrew D. A.

    2015-03-01

    By analyzing human readers' performance in detecting small round lesions in simulated digital breast tomosynthesis background in a location known exactly scenario, we have developed a model observer that is a better predictor of human performance with different levels of background complexity (i.e., anatomical and quantum noise). Our analysis indicates that human observers perform a lesion detection task by combining a number of sub-decisions, each an indicator of the presence of a lesion in the image stack. This is in contrast to a channelized Hotelling observer, where the detection task is conducted holistically by thresholding a single decision variable, made from an optimally weighted linear combination of channels. However, it seems that the sub-par performance of human readers compared to the CHO cannot be fully explained by their reliance on sub-decisions, or perhaps we do not consider a sufficient number of subdecisions. To bridge the gap between the performances of human readers and the model observer based upon subdecisions, we use an additive noise model, the power of which is modulated with the level of background complexity. The proposed model observer better predicts the fast drop in human detection performance with background complexity.

  3. Aggregation of Environmental Model Data for Decision Support

    NASA Astrophysics Data System (ADS)

    Alpert, J. C.

    2013-12-01

    Weather forecasts and warnings must be prepared and then delivered so as to reach their intended audience in good time to enable effective decision-making. An effort to mitigate these difficulties was studied at a Workshop, 'Sustaining National Meteorological Services - Strengthening WMO Regional and Global Centers' convened, June , 2013, by the World Bank, WMO and the US National Weather Service (NWS). The skill and accuracy of atmospheric forecasts from deterministic models have increased and there are now ensembles of such models that improve decisions to protect life, property and commerce. The NWS production of numerical weather prediction products result in model output from global and high resolution regional ensemble forecasts. Ensembles are constructed by changing the initial conditions to make a 'cloud' of forecasts that attempt to span the space of possible atmospheric realizations which can quantify not only the most likely forecast, but also the uncertainty. This has led to an unprecedented increase in data production and information content from higher resolution, multi-model output and secondary calculations. One difficulty is to obtain the needed subset of data required to estimate the probability of events, and report the information. The calibration required to reliably estimate the probability of events, and honing of threshold adjustments to reduce false alarms for decision makers is also needed. To meet the future needs of the ever-broadening user community and address these issues on a national and international basis, the weather service implemented the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS provides real-time and retrospective format independent access to climate, ocean and weather model data and delivers high availability content services as part of NOAA's official real time data dissemination at its new NCWCP web operations center. An important aspect of the server's abilities is to aggregate the matrix of

  4. Modeling Common-Sense Decisions in Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Zak, Michail

    2010-01-01

    A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation

  5. A Product Development Decision Model for Cockpit Weather Information Systems

    NASA Technical Reports Server (NTRS)

    Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin

    2003-01-01

    There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

  6. A Product Development Decision Model for Cockpit Weather Information System

    NASA Technical Reports Server (NTRS)

    Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin; Johnson, Edward J., Jr. (Technical Monitor)

    2003-01-01

    There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

  7. 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.

  8. 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.

  9. Model Checking with Edge-Valued Decision Diagrams

    NASA Technical Reports Server (NTRS)

    Roux, Pierre; Siminiceanu, Radu I.

    2010-01-01

    We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic functions and its implementation in a model checking library. We provide efficient algorithms for manipulating EVMDDs and review the theoretical time complexity of these algorithms for all basic arithmetic and relational operators. We also demonstrate that the time complexity of the generic recursive algorithm for applying a binary operator on EVMDDs is no worse than that of Multi- Terminal Decision Diagrams. We have implemented a new symbolic model checker with the intention to represent in one formalism the best techniques available at the moment across a spectrum of existing tools. Compared to the CUDD package, our tool is several orders of magnitude faster

  10. 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

  11. An environmentally sustainable decision model for urban solid waste management.

    PubMed

    Costi, P; Minciardi, R; Robba, M; Rovatti, M; Sacile, R

    2004-01-01

    The aim of this work is to present the structure and the application of a decision support system (DSS) designed to help decision makers of a municipality in the development of incineration, disposal, treatment and recycling integrated programs. Specifically, within a MSW management system, several treatment plants and facilities can generally be found: separators, plants for production of refuse derived fuel (RDF), incinerators with energy recovery, plants for treatment of organic material, and sanitary landfills. The main goal of the DSS is to plan the MSW management, defining the refuse flows that have to be sent to recycling or to different treatment or disposal plants, and suggesting the optimal number, the kinds, and the localization of the plants that have to be active. The DSS is based on a decision model that requires the solution of a constrained non-linear optimization problem, where some decision variables are binary and other ones are continuous. The objective function takes into account all possible economic costs, whereas constraints arise from technical, normative, and environmental issues. Specifically, pollution and impacts, induced by the overall solid waste management system, are considered through the formalization of constraints on incineration emissions and on negative effects produced by disposal or other particular treatments. PMID:15016417

  12. Reverse engineering cellular decisions for hybrid reconfigurable network modeling

    NASA Astrophysics Data System (ADS)

    Blair, Howard A.; Saranak, Jureepan; Foster, Kenneth W.

    2011-06-01

    Cells as microorganisms and within multicellular organisms make robust decisions. Knowing how these complex cells make decisions is essential to explain, predict or mimic their behavior. The discovery of multi-layer multiple feedback loops in the signaling pathways of these modular hybrid systems suggests their decision making is sophisticated. Hybrid systems coordinate and integrate signals of various kinds: discrete on/off signals, continuous sensory signals, and stochastic and continuous fluctuations to regulate chemical concentrations. Such signaling networks can form reconfigurable networks of attractors and repellors giving them an extra level of organization that has resilient decision making built in. Work on generic attractor and repellor networks and on the already identified feedback networks and dynamic reconfigurable regulatory topologies in biological cells suggests that biological systems probably exploit such dynamic capabilities. We present a simple behavior of the swimming unicellular alga Chlamydomonas that involves interdependent discrete and continuous signals in feedback loops. We show how to rigorously verify a hybrid dynamical model of a biological system with respect to a declarative description of a cell's behavior. The hybrid dynamical systems we use are based on a unification of discrete structures and continuous topologies developed in prior work on convergence spaces. They involve variables of discrete and continuous types, in the sense of type theory in mathematical logic. A unification such as afforded by convergence spaces is necessary if one wants to take account of the affect of the structural relationships within each type on the dynamics of the system.

  13. An environmentally sustainable decision model for urban solid waste management

    SciTech Connect

    Costi, P.; Minciardi, R.; Robba, M.; Rovatti, M.; Sacile, R

    2004-07-01

    The aim of this work is to present the structure and the application of a decision support system (DSS) designed to help decision makers of a municipality in the development of incineration, disposal, treatment and recycling integrated programs. Specifically, within a MSW management system, several treatment plants and facilities can generally be found: separators, plants for production of refuse derived fuel (RDF), incinerators with energy recovery, plants for treatment of organic material, and sanitary landfills. The main goal of the DSS is to plan the MSW management, defining the refuse flows that have to be sent to recycling or to different treatment or disposal plants, and suggesting the optimal number, the kinds, and the localization of the plants that have to be active. The DSS is based on a decision model that requires the solution of a constrained non-linear optimization problem, where some decision variables are binary and other ones are continuous. The objective function takes into account all possible economic costs, whereas constraints arise from technical, normative, and environmental issues. Specifically, pollution and impacts, induced by the overall solid waste management system, are considered through the formalization of constraints on incineration emissions and on negative effects produced by disposal or other particular treatments.

  14. 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.

  15. Behavioural modelling of irrigation decision making under water scarcity

    NASA Astrophysics Data System (ADS)

    Foster, T.; Brozovic, N.; Butler, A. P.

    2013-12-01

    Providing effective policy solutions to aquifer depletion caused by abstraction for irrigation is a key challenge for socio-hydrology. However, most crop production functions used in hydrological models do not capture the intraseasonal nature of irrigation planning, or the importance of well yield in land and water use decisions. Here we develop a method for determining stochastic intraseasonal water use that is based on observed farmer behaviour but is also theoretically consistent with dynamically optimal decision making. We use the model to (i) analyse the joint land and water use decision by farmers; (ii) to assess changes in behaviour and production risk in response to water scarcity; and (iii) to understand the limits of applicability of current methods in policy design. We develop a biophysical model of water-limited crop yield building on the AquaCrop model. The model is calibrated and applied to case studies of irrigated corn production in Nebraska and Texas. We run the model iteratively, using long-term climate records, to define two formulations of the crop-water production function: (i) the aggregate relationship between total seasonal irrigation and yield (typical of current approaches); and (ii) the stochastic response of yield and total seasonal irrigation to the choice of an intraseasonal soil moisture target and irrigated area. Irrigated area (the extensive margin decision) and per-area irrigation intensity (the intensive margin decision) are then calculated for different seasonal water restrictions (corresponding to regulatory policies) and well yield constraints on intraseasonal abstraction rates (corresponding to aquifer system limits). Profit- and utility-maximising decisions are determined assuming risk neutrality and varying degrees of risk aversion, respectively. Our results demonstrate that the formulation of the production function has a significant impact on the response to water scarcity. For low well yields, which are the major concern

  16. Economic decision making and the application of nonparametric prediction models

    USGS Publications Warehouse

    Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

    2007-01-01

    Sustained increases in energy prices have focused attention on gas resources in low permeability shale or in coals that were previously considered economically marginal. Daily well deliverability is often relatively small, although the estimates of the total volumes of recoverable resources in these settings are large. Planning and development decisions for extraction of such resources must be area-wide because profitable extraction requires optimization of scale economies to minimize costs and reduce risk. For an individual firm the decision to enter such plays depends on reconnaissance level estimates of regional recoverable resources and on cost estimates to develop untested areas. This paper shows how simple nonparametric local regression models, used to predict technically recoverable resources at untested sites, can be combined with economic models to compute regional scale cost functions. The context of the worked example is the Devonian Antrim shale gas play, Michigan Basin. One finding relates to selection of the resource prediction model to be used with economic models. Models which can best predict aggregate volume over larger areas (many hundreds of sites) may lose granularity in the distribution of predicted volumes at individual sites. This loss of detail affects the representation of economic cost functions and may affect economic decisions. Second, because some analysts consider unconventional resources to be ubiquitous, the selection and order of specific drilling sites may, in practice, be determined by extraneous factors. The paper also shows that when these simple prediction models are used to strategically order drilling prospects, the gain in gas volume over volumes associated with simple random site selection amounts to 15 to 20 percent. It also discusses why the observed benefit of updating predictions from results of new drilling, as opposed to following static predictions, is somewhat smaller. Copyright 2007, Society of Petroleum Engineers.

  17. Economic decision making and the application of nonparametric prediction models

    USGS Publications Warehouse

    Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

    2008-01-01

    Sustained increases in energy prices have focused attention on gas resources in low-permeability shale or in coals that were previously considered economically marginal. Daily well deliverability is often relatively small, although the estimates of the total volumes of recoverable resources in these settings are often large. Planning and development decisions for extraction of such resources must be areawide because profitable extraction requires optimization of scale economies to minimize costs and reduce risk. For an individual firm, the decision to enter such plays depends on reconnaissance-level estimates of regional recoverable resources and on cost estimates to develop untested areas. This paper shows how simple nonparametric local regression models, used to predict technically recoverable resources at untested sites, can be combined with economic models to compute regional-scale cost functions. The context of the worked example is the Devonian Antrim-shale gas play in the Michigan basin. One finding relates to selection of the resource prediction model to be used with economic models. Models chosen because they can best predict aggregate volume over larger areas (many hundreds of sites) smooth out granularity in the distribution of predicted volumes at individual sites. This loss of detail affects the representation of economic cost functions and may affect economic decisions. Second, because some analysts consider unconventional resources to be ubiquitous, the selection and order of specific drilling sites may, in practice, be determined arbitrarily by extraneous factors. The analysis shows a 15-20% gain in gas volume when these simple models are applied to order drilling prospects strategically rather than to choose drilling locations randomly. Copyright ?? 2008 Society of Petroleum Engineers.

  18. Modeling human decision making behavior in supervisory control

    NASA Technical Reports Server (NTRS)

    Tulga, M. K.; Sheridan, T. B.

    1977-01-01

    An optimal decision control model was developed, which is based primarily on a dynamic programming algorithm which looks at all the available task possibilities, charts an optimal trajectory, and commits itself to do the first step (i.e., follow the optimal trajectory during the next time period), and then iterates the calculation. A Bayesian estimator was included which estimates the tasks which might occur in the immediate future and provides this information to the dynamic programming routine. Preliminary trials comparing the human subject's performance to that of the optimal model show a great similarity, but indicate that the human skips certain movements which require quick change in strategy.

  19. Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED)

    PubMed Central

    Fontaine, Reid Griffith; Dodge, Kenneth A.

    2009-01-01

    Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social–cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions. PMID:20802851

  20. A Spiking Network Model of Decision Making Employing Rewarded STDP

    PubMed Central

    Bazhenov, Maxim

    2014-01-01

    Reward-modulated spike timing dependent plasticity (STDP) combines unsupervised STDP with a reinforcement signal that modulates synaptic changes. It was proposed as a learning rule capable of solving the distal reward problem in reinforcement learning. Nonetheless, performance and limitations of this learning mechanism have yet to be tested for its ability to solve biological problems. In our work, rewarded STDP was implemented to model foraging behavior in a simulated environment. Over the course of training the network of spiking neurons developed the capability of producing highly successful decision-making. The network performance remained stable even after significant perturbations of synaptic structure. Rewarded STDP alone was insufficient to learn effective decision making due to the difficulty maintaining homeostatic equilibrium of synaptic weights and the development of local performance maxima. Our study predicts that successful learning requires stabilizing mechanisms that allow neurons to balance their input and output synapses as well as synaptic noise. PMID:24632858

  1. Quantum-Like Bayesian Networks for Modeling Decision Making

    PubMed Central

    Moreira, Catarina; Wichert, Andreas

    2016-01-01

    In this work, we explore an alternative quantum structure to perform quantum probabilistic inferences to accommodate the paradoxical findings of the Sure Thing Principle. We propose a Quantum-Like Bayesian Network, which consists in replacing classical probabilities by quantum probability amplitudes. However, since this approach suffers from the problem of exponential growth of quantum parameters, we also propose a similarity heuristic that automatically fits quantum parameters through vector similarities. This makes the proposed model general and predictive in contrast to the current state of the art models, which cannot be generalized for more complex decision scenarios and that only provide an explanatory nature for the observed paradoxes. In the end, the model that we propose consists in a nonparametric method for estimating inference effects from a statistical point of view. It is a statistical model that is simpler than the previous quantum dynamic and quantum-like models proposed in the literature. We tested the proposed network with several empirical data from the literature, mainly from the Prisoner's Dilemma game and the Two Stage Gambling game. The results obtained show that the proposed quantum Bayesian Network is a general method that can accommodate violations of the laws of classical probability theory and make accurate predictions regarding human decision-making in these scenarios. PMID:26858669

  2. A naturalistic decision making model for simulated human combatants

    SciTech Connect

    HUNTER,KEITH O.; HART,WILLIAM E.; FORSYTHE,JAMES C.

    2000-05-01

    The authors describe a naturalistic behavioral model for the simulation of small unit combat. This model, Klein's recognition-primed decision making (RPD) model, is driven by situational awareness rather than a rational process of selecting from a set of action options. They argue that simulated combatants modeled with RPD will have more flexible and realistic responses to a broad range of small-scale combat scenarios. Furthermore, they note that the predictability of a simulation using an RPD framework can be easily controlled to provide multiple evaluations of a given combat scenario. Finally, they discuss computational issues for building an RPD-based behavior engine for fully automated combatants in small conflict scenarios, which are being investigated within Sandia's Next Generation Site Security project.

  3. A new framework for modeling decisions about changing information: The Piecewise Linear Ballistic Accumulator model.

    PubMed

    Holmes, William R; Trueblood, Jennifer S; Heathcote, Andrew

    2016-03-01

    In the real world, decision making processes must be able to integrate non-stationary information that changes systematically while the decision is in progress. Although theories of decision making have traditionally been applied to paradigms with stationary information, non-stationary stimuli are now of increasing theoretical interest. We use a random-dot motion paradigm along with cognitive modeling to investigate how the decision process is updated when a stimulus changes. Participants viewed a cloud of moving dots, where the motion switched directions midway through some trials, and were asked to determine the direction of motion. Behavioral results revealed a strong delay effect: after presentation of the initial motion direction there is a substantial time delay before the changed motion information is integrated into the decision process. To further investigate the underlying changes in the decision process, we developed a Piecewise Linear Ballistic Accumulator model (PLBA). The PLBA is efficient to simulate, enabling it to be fit to participant choice and response-time distribution data in a hierarchal modeling framework using a non-parametric approximate Bayesian algorithm. Consistent with behavioral results, PLBA fits confirmed the presence of a long delay between presentation and integration of new stimulus information, but did not support increased response caution in reaction to the change. We also found the decision process was not veridical, as symmetric stimulus change had an asymmetric effect on the rate of evidence accumulation. Thus, the perceptual decision process was slow to react to, and underestimated, new contrary motion information. PMID:26760448

  4. A National Modeling Framework for Water Management Decisions

    NASA Astrophysics Data System (ADS)

    Bales, J. D.; Cline, D. W.; Pietrowsky, R.

    2013-12-01

    The National Weather Service (NWS), the U.S. Army Corps of Engineers (USACE), and the U.S. Geological Survey (USGS), all Federal agencies with complementary water-resources activities, entered into an Interagency Memorandum of Understanding (MOU) "Collaborative Science Services and Tools to Support Integrated and Adaptive Water Resources Management" to collaborate in activities that are supportive to their respective missions. One of the interagency activities is the development of a highly integrated national water modeling framework and information services framework. Together these frameworks establish a common operating picture, improve modeling and synthesis, support the sharing of data and products among agencies, and provide a platform for incorporation of new scientific understanding. Each of the agencies has existing operational systems to assist in carrying out their respective missions. The systems generally are designed, developed, tested, fielded, and supported by specialized teams. A broader, shared approach is envisioned and would include community modeling, wherein multiple independent investigators or teams develop and contribute new modeling capabilities based on science advances; modern technology in coupling model components and visualizing results; and a coupled atmospheric - hydrologic model construct such that the framework could be used in real-time water-resources decision making or for long-term management decisions. The framework also is being developed to account for organizational structures of the three partners such that, for example, national data sets can move down to the regional scale, and vice versa. We envision the national water modeling framework to be an important element of North American Water Program, to contribute to goals of the Program, and to be informed by the science and approaches developed as a part of the Program.

  5. Effects of dynamic agricultural decision making in an ecohydrological model

    NASA Astrophysics Data System (ADS)

    Reichenau, T. G.; Krimly, T.; Schneider, K.

    2012-04-01

    Due to various interdependencies between the cycles of water, carbon, nitrogen, and energy the impacts of climate change on ecohydrological systems can only be investigated in an integrative way. Furthermore, the human intervention in the environmental processes makes the system even more complex. On the one hand human impact affects natural systems. On the other hand the changing natural systems have a feedback on human decision making. One of the most important examples for this kind of interaction can be found in the agricultural sector. Management dates (planting, fertilization, harvesting) are chosen based on meteorological conditions and yield expectations. A faster development of crops under a warmer climate causes shorter cropping seasons. The choice of crops depends on their profitability, which is mainly determined by market prizes, the agro-political framework, and the (climate dependent) crop yield. This study investigates these relations for the district Günzburg located in the Upper Danube catchment in southern Germany. The modeling system DANUBIA was used to perform dynamically coupled simulations of plant growth, surface and soil hydrological processes, soil nitrogen transformations, and agricultural decision making. The agro-economic model simulates decisions on management dates (based on meteorological conditions and the crops' development state), on fertilization intensities (based on yield expectations), and on choice of crops (based on profitability). The environmental models included in DANUBIA are to a great extent process based to enable its use in a climate change scenario context. Scenario model runs until 2058 were performed using an IPCC A1B forcing. In consecutive runs, dynamic crop management, dynamic crop selection, and a changing agro-political framework were activated. Effects of these model features on hydrological and ecological variables were analyzed separately by comparing the results to a model run with constant crop

  6. Using health economic models to help guide healthcare decisions.

    PubMed

    Charokopou, M

    2016-01-01

    This editorial accompanies a research article being published by Clinical Medical Research and Opinion (CMRO) journal, entitled "Methods applied in cost-effectiveness models for treatment strategies in type 2 diabetes mellitus and their use in Health Technology Assessments: a systematic review of the literature from 2008 to 2013". The importance and the contribution of this research to the scientific community are presented on the grounds of serving the decision-making process of evaluating and approving T2DM treatments for public funding. PMID:26473453

  7. Model-Checking with Edge-Valued Decision Diagrams

    NASA Technical Reports Server (NTRS)

    Roux, Pierre; Siminiceanu, Radu I.

    2010-01-01

    We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic functions and its implementation in a model checking library along with state-of-the-art algorithms for building the transition relation and the state space of discrete state systems. We provide efficient algorithms for manipulating EVMDDs and give upper bounds of the theoretical time complexity of these algorithms for all basic arithmetic and relational operators. We also demonstrate that the time complexity of the generic recursive algorithm for applying a binary operator on EVMDDs is no worse than that of Multi-Terminal Decision Diagrams. We have implemented a new symbolic model checker with the intention to represent in one formalism the best techniques available at the moment across a spectrum of existing tools: EVMDDs for encoding arithmetic expressions, identity-reduced MDDs for representing the transition relation, and the saturation algorithm for reachability analysis. We compare our new symbolic model checking EVMDD library with the widely used CUDD package and show that, in many cases, our tool is several orders of magnitude faster than CUDD.

  8. Collocated cokriging and neural-network multi-attribute transform in the prediction of effective porosity: A comparative case study for the Second Wall Creek Sand of the Teapot Dome field, Wyoming, USA

    NASA Astrophysics Data System (ADS)

    Moon, Seonghoon; Lee, Gwang H.; Kim, Hyeonju; Choi, Yosoon; Kim, Han-Joon

    2016-08-01

    Collocated cokriging (CCK) and neural-network multi-attribute transform (NN-MAT) are widely used in the prediction of reservoir properties because they can integrate sparsely-distributed, high-resolution well-log data and densely-sampled, low-resolution seismic data. CCK is a linear-weighted averaging method based on spatial covariance model. NN-MAT, based on a nonlinear relationship between seismic attributes and log values, treats data as spatially independent observations. In this study, we analyzed 3-D seismic and well-log data from the Second Wall Creek Sand of the Teapot Dome field, Wyoming, USA to investigate: (1) how CCK and NN-MAT perform in the prediction of porosity and (2) how the number of wells affects the results. Among a total of 64 wells, 25 wells were selected for CCK and NN-MAT and 39 wells were withheld for validation. We examined four cases: 25, 20, 15, and 10 wells. CCK overpredicted the porosity in the validation wells for all cases likely due to the strong influence of high values, but failed to predict very large porosities. Overprediction of CCK porosity becomes more pronounced with decreasing number of wells. NN-MAT largely underpredicted the porosity for all cases probably due to the band-limited nature of seismic data. The performance of CCK appears to be not affected significantly by the number of wells. Overall, NN-MAT performed better than CCK although its performance decreases continuously with decreasing number of wells.

  9. Modeling violations of the race model inequality in bimodal paradigms: co-activation from decision and non-decision components

    PubMed Central

    Zehetleitner, Michael; Ratko-Dehnert, Emil; Müller, Hermann J.

    2015-01-01

    The redundant-signals paradigm (RSP) is designed to investigate response behavior in perceptual tasks in which response-relevant targets are defined by either one or two features, or modalities. The common finding is that responses are speeded for redundantly compared to singly defined targets. This redundant-signals effect (RSE) can be accounted for by race models if the response times do not violate the race model inequality (RMI). When there are violations of the RMI, race models are effectively excluded as a viable account of the RSE. The common alternative is provided by co-activation accounts, which assume that redundant target signals are integrated at some processing stage. However, “co-activation” has mostly been only indirectly inferred and the accounts have only rarely been explicitly modeled; if they were modeled, the RSE has typically been assumed to have a decisional locus. Yet, there are also indications in the literature that the RSE might originate, at least in part, at a non-decisional or motor stage. In the present study, using a distribution analysis of sequential-sampling models (ex-Wald and Ratcliff Diffusion model), the locus of the RSE was investigated for two bimodal (audio-visual) detection tasks that strongly violated the RMI, indicative of substantial co-activation. Three model variants assuming different loci of the RSE were fitted to the quantile reaction time proportions: a decision, a non-decision, and a combined variant both to vincentized group as well as individual data. The results suggest that for the two bimodal detection tasks, co-activation has a shared decisional and non-decisional locus. These findings point to the possibility that the mechanisms underlying the RSE depend on the specifics (task, stimulus, conditions, etc.) of the experimental paradigm. PMID:25805987

  10. Decision Models for Determining the Optimal Life Test Sampling Plans

    NASA Astrophysics Data System (ADS)

    Nechval, Nicholas A.; Nechval, Konstantin N.; Purgailis, Maris; Berzins, Gundars; Strelchonok, Vladimir F.

    2010-11-01

    Life test sampling plan is a technique, which consists of sampling, inspection, and decision making in determining the acceptance or rejection of a batch of products by experiments for examining the continuous usage time of the products. In life testing studies, the lifetime is usually assumed to be distributed as either a one-parameter exponential distribution, or a two-parameter Weibull distribution with the assumption that the shape parameter is known. Such oversimplified assumptions can facilitate the follow-up analyses, but may overlook the fact that the lifetime distribution can significantly affect the estimation of the failure rate of a product. Moreover, sampling costs, inspection costs, warranty costs, and rejection costs are all essential, and ought to be considered in choosing an appropriate sampling plan. The choice of an appropriate life test sampling plan is a crucial decision problem because a good plan not only can help producers save testing time, and reduce testing cost; but it also can positively affect the image of the product, and thus attract more consumers to buy it. This paper develops the frequentist (non-Bayesian) decision models for determining the optimal life test sampling plans with an aim of cost minimization by identifying the appropriate number of product failures in a sample that should be used as a threshold in judging the rejection of a batch. The two-parameter exponential and Weibull distributions with two unknown parameters are assumed to be appropriate for modelling the lifetime of a product. A practical numerical application is employed to demonstrate the proposed approach.

  11. The collaborative autonomy model of medical decision-making.

    PubMed

    Rubin, Michael A

    2014-04-01

    While the bioethical principle of beneficence originated in antiquity, the ascension of autonomy, or "self-rule," has redefined the physician-patient relationship to the extent that autonomy often dominates medical decision-making. Philosophical and social movements, medical research atrocities, consumerism, and case law have all had their influence on this paradigm shift. Consequently, the contemporary physician encounters an uncertainty in medical practice on how to resolve conflicts that arise in the pursuit of valuing both autonomy and beneficence. This is especially true in the practice of neurologic critical care where physicians may be advising comfort care measures for neurologically devastated patients while surrogates request physiologically futile interventions. This conundrum has been an important subject of the bioethics and social science literature but often this discourse is not disseminated to the clinicians confronting these issues. The purpose of this essay is to present a history of the principles of autonomy and beneficence and then present a shared medical decision-making model, collaborative autonomy, to provide guidance to neurologic critical care providers in how to resolve such dilemmas. Clinical vignettes will help illustrate the model. PMID:24233814

  12. Classification images in a very general decision model.

    PubMed

    Murray, Richard F

    2016-06-01

    Most of the theory supporting our understanding of classification images relies on standard signal detection models and the use of normally distributed stimulus noise. Here I show that the most common methods of calculating classification images by averaging stimulus noise samples within stimulus-response classes of trials are much more general than has previously been demonstrated, and that they give unbiased estimates of an observer's template for a wide range of decision rules and non-Gaussian stimulus noise distributions. These results are similar to findings on reverse correlation and related methods in the neurophysiology literature, but here I formulate them in terms that are tailored to signal detection analyses of visual tasks, in order to make them more accessible and useful to visual psychophysicists. I examine 2AFC and yes-no designs. These findings make it possible to use and interpret classification images in tasks where observers' decision strategies may not conform to classic signal detection models such as the difference rule, and in tasks where the stimulus noise is non-Gaussian. PMID:27174841

  13. Assembling Tools and Data for Climate Model Decision Support

    NASA Astrophysics Data System (ADS)

    Batcheller, A. L.; VanWijngaarden, F.

    2011-12-01

    The Global Earth Observation System of Systems (GEOSS) effort has identified nine areas in which society benefits from appropriate environmental information. We have targeted specific issues within these societal benefit areas by determining appropriate data sets needed and transforming these data into information useable by decision makers. Here we describe the service-oriented architecture that allows us to ingest real-time or static data into a database with a spatial data engine, make appropriate manipulations to the data using domain knowledge relevant to the problem, and expose the data as services. We then build custom portals using a library of common widgets to display and overlay the data for users to analyze. By using portals and a service-oriented architecture we can reuse services and widgets to rapidly assemble a view of geographic data, and assist decision-makers in applying and interpreting the latest scientific results. As a case study with our system, we have integrated data from Intergovernmental Panel on Climate Change (IPCC) climate models, crop yields, and environmental thresholds for crops to present a first level analysis of the impact of climate change on key crops grown in Mexico. Knowledge about changes in the regions that are favorable for crop growth is important for many stakeholders, ranging from individual farmers, to governments, to scientists working to create new seed varieties. Our work also highlights research opportunities in climate science by identifying the types and resolution of parameters modeled.

  14. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    NASA Astrophysics Data System (ADS)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  15. Decision Making Methods in Space Economics and Systems Engineering

    NASA Technical Reports Server (NTRS)

    Shishko, Robert

    2006-01-01

    This viewgraph presentation reviews various methods of decision making and the impact that they have on space economics and systems engineering. Some of the methods discussed are: Present Value and Internal Rate of Return (IRR); Cost-Benefit Analysis; Real Options; Cost-Effectiveness Analysis; Cost-Utility Analysis; Multi-Attribute Utility Theory (MAUT); and Analytic Hierarchy Process (AHP).

  16. Modelling sustainable development planning: a multicriteria decision conferencing approach.

    PubMed

    Quaddus, M A; Siddique, M A

    2001-09-01

    Development planning is multidimensional in nature. On the one hand, it addresses economic growth, and on the other, it deals with economic development of the whole nation. Sustainable development, on the other hand, emphasizes the need for integration of economics and environment, as well as promoting intra- and intergenerational equity. While the literature deals extensively with the issues of sustainable development, it lacks a prescription of an easy-to-use, yet rigorous, methodology for it. In this paper, we offer a decision conferencing approach to sustainable development planning based on a multicriteria model. The integrated model is presented and applied to a sustainable development planning exercise in a third world country. Sample results are presented and detailed sensitivity analyses show the environmental variables that are of major concern. PMID:11697680

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

    PubMed

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

    2013-01-10

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

  18. Trade-offs underlying maternal breastfeeding decisions: a conceptual model.

    PubMed

    Tully, Kristin P; Ball, Helen L

    2013-01-01

    This paper presents a new conceptual model that generates predictions about breastfeeding decisions and identifies interactions that affect outcomes. We offer a contextual approach to infant feeding that models multi-directional influences by expanding on the evolutionary parent-offspring conflict and situation-specific breastfeeding theories. The main hypothesis generated from our framework suggests that simultaneously addressing breastfeeding costs and benefits, in relation to how they are interpreted by mothers, will be most effective. Our approach focuses on contributors to the attitudes and commitment underlying breastfeeding outcomes, beginning in the prenatal period. We conclude that some maternal-offspring conflict is inherent with the dynamic infant feeding relationship. Guidance that anticipates and addresses family trade-offs over time can be incorporated into breastfeeding support for families. PMID:22188564

  19. Influence of proxy attributes on multiattribute decision analysis: An empirical investigation in the context of air pollution control

    SciTech Connect

    Damodaran, N.

    1988-01-01

    Three separate studies in decision analysis were conducted in the context of air pollution control wherein the preferences of informed subjects were individually assessed. The first study was designed to develop a decision model for the control of sulfur dioxide emissions by incorporating multi-media effects of pollution control using both fundamental and proxy attributes. The second study specifically compared fundamental and proxy attributes and tested the hypothesis that proxy attributes lead to biased decisions. The third study validated the results of the previous one and was extended to examine the hypothesis that proxy bias could be reduced by appropriate elicitation techniques. The findings of this study indicated that subjects behaved according to the norms of expected utility theory when the unidimensional utility function for the proxy attribute was assessed. However, subjects exhibited a near universal bias to overweight the proxy attribute, relative to prescriptions of expected utility theory, in a multi-attribute scenario.

  20. A queueing model of pilot decision making in a multi-task flight management situation

    NASA Technical Reports Server (NTRS)

    Walden, R. S.; Rouse, W. B.

    1977-01-01

    Allocation of decision making responsibility between pilot and computer is considered and a flight management task, designed for the study of pilot-computer interaction, is discussed. A queueing theory model of pilot decision making in this multi-task, control and monitoring situation is presented. An experimental investigation of pilot decision making and the resulting model parameters are discussed.

  1. Representation requirements for supporting knowledge-based construction of decision models in medicine.

    PubMed Central

    Leong, T. Y.

    1991-01-01

    This paper analyzes the medical knowledge required for formulating decision models in the domain of pulmonary infectious diseases (PIDs) with acquired immunodeficiency syndrome (AIDS). Aiming to support dynamic decision-modeling, the knowledge characterization focuses on the ontology of the clinical decision problem. Relevant inference patterns and knowledge types are identified. PMID:1807680

  2. CASE STUDIES IN THE APPLICATION OF AIR QUALITY MODELING IN ENVIRONMENTAL DECISION MAKING: SUMMARY AND RECOMMENDATIONS

    EPA Science Inventory

    Eleven case studies of the application of air quality models were undertaken in order to examine the problems encountered when trying to use these models in making environmental policy decisions. The case studies of air pollution control decisions describe the decision process, t...

  3. Decoding Problem Gamblers' Signals: A Decision Model for Casino Enterprises.

    PubMed

    Ifrim, Sandra

    2015-12-01

    The aim of the present study is to offer a validated decision model for casino enterprises. The model enables those users to perform early detection of problem gamblers and fulfill their ethical duty of social cost minimization. To this end, the interpretation of casino customers' nonverbal communication is understood as a signal-processing problem. Indicators of problem gambling recommended by Delfabbro et al. (Identifying problem gamblers in gambling venues: final report, 2007) are combined with Viterbi algorithm into an interdisciplinary model that helps decoding signals emitted by casino customers. Model output consists of a historical path of mental states and cumulated social costs associated with a particular client. Groups of problem and non-problem gamblers were simulated to investigate the model's diagnostic capability and its cost minimization ability. Each group consisted of 26 subjects and was subsequently enlarged to 100 subjects. In approximately 95% of the cases, mental states were correctly decoded for problem gamblers. Statistical analysis using planned contrasts revealed that the model is relatively robust to the suppression of signals performed by casino clientele facing gambling problems as well as to misjudgments made by staff regarding the clients' mental states. Only if the last mentioned source of error occurs in a very pronounced manner, i.e. judgment is extremely faulty, cumulated social costs might be distorted. PMID:24938732

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

    PubMed Central

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

    2007-01-01

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

  5. Accounting for uncertainty in health economic decision models by using model averaging.

    PubMed

    Jackson, Christopher H; Thompson, Simon G; Sharples, Linda D

    2009-04-01

    Health economic decision models are subject to considerable uncertainty, much of which arises from choices between several plausible model structures, e.g. choices of covariates in a regression model. Such structural uncertainty is rarely accounted for formally in decision models but can be addressed by model averaging. We discuss the most common methods of averaging models and the principles underlying them. We apply them to a comparison of two surgical techniques for repairing abdominal aortic aneurysms. In model averaging, competing models are usually either weighted by using an asymptotically consistent model assessment criterion, such as the Bayesian information criterion, or a measure of predictive ability, such as Akaike's information criterion. We argue that the predictive approach is more suitable when modelling the complex underlying processes of interest in health economics, such as individual disease progression and response to treatment. PMID:19381329

  6. Qualitative modeling of the decision-making process using electrooculography.

    PubMed

    Marandi, Ramtin Zargari; Sabzpoushan, S H

    2015-12-01

    A novel method based on electrooculography (EOG) has been introduced in this work to study the decision-making process. An experiment was designed and implemented wherein subjects were asked to choose between two items from the same category that were presented within a limited time. The EOG and voice signals of the subjects were recorded during the experiment. A calibration task was performed to map the EOG signals to their corresponding gaze positions on the screen by using an artificial neural network. To analyze the data, 16 parameters were extracted from the response time and EOG signals of the subjects. Evaluation and comparison of the parameters, together with subjects' choices, revealed functional information. On the basis of this information, subjects switched their eye gazes between items about three times on average. We also found, according to statistical hypothesis testing-that is, a t test, t(10) = 71.62, SE = 1.25, p < .0001-that the correspondence rate of a subjects' gaze at the moment of selection with the selected item was significant. Ultimately, on the basis of these results, we propose a qualitative choice model for the decision-making task. PMID:25515839

  7. Pharmaceutical expenditure forecast model to support health policy decision making

    PubMed Central

    Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and objective With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project ‘European Union (EU) Pharmaceutical expenditure forecast’ – http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods A model was built to assess policy scenarios’ impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Results Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Conclusions Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate

  8. A Stochastic Decision Model for Experiments in Discrimination Learning.

    ERIC Educational Resources Information Center

    Egelston, Richard L.

    Decisions to terminate training for subjects involved with discrete trial experiments in discrimination learning should utilize a probability criterion rather than a deterministic criterion. Furthermore, these decisions should be based upon the number of correct and error responses made by the subject, with the decision made to terminate training…

  9. Decision-making models of Finnish nurses and public health nurses.

    PubMed

    Lauri, S; Salanterä, S

    1995-03-01

    This study described nursing decision-making models and variables related to these models. For this purpose a 56-item Likert-type questionnaire was constructed according to the Dreyfus model of skill acquisition as applied to nursing by Benner and information processing theory. The target group consisted of 100 registered nurses working in inpatient clinics and 100 public health nurses working in preventive health care. The decision-making variables explored were nurses' experience, education and knowledge as well as the nature of the nursing task and context. The results revealed four different types of decision-making: (a) unquestioning/questioning decision-making, (b) creative-diversive decision-making, (c) patient/nurse-oriented decision-making, and (d) rule- and situation-based decision-making. The most important factors related to decision-making were experience and the nature of the nursing task and context. PMID:7745207

  10. An Integrated Decision-Making Model for Categorizing Weather Products and Decision Aids

    NASA Technical Reports Server (NTRS)

    Elgin, Peter D.; Thomas, Rickey P.

    2004-01-01

    The National Airspace System s capacity will experience considerable growth in the next few decades. Weather adversely affects safe air travel. The FAA and NASA are working to develop new technologies that display weather information to support situation awareness and optimize pilot decision-making in avoiding hazardous weather. Understanding situation awareness and naturalistic decision-making is an important step in achieving this goal. Information representation and situation time stress greatly influence attentional resource allocation and working memory capacity, potentially obstructing accurate situation awareness assessments. Three naturalistic decision-making theories were integrated to provide an understanding of the levels of decision making incorporated in three operational situations and two conditions. The task characteristics associated with each phase of flight govern the level of situation awareness attained and the decision making processes utilized. Weather product s attributes and situation task characteristics combine to classify weather products according to the decision-making processes best supported. In addition, a graphical interface is described that affords intuitive selection of the appropriate weather product relative to the pilot s current flight situation.

  11. Agricultural Model for the Nile Basin Decision Support System

    NASA Astrophysics Data System (ADS)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

    To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

  12. 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.

  13. Agricultural climate impacts assessment for economic modeling and decision support

    NASA Astrophysics Data System (ADS)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  14. A Markov decision model for determining optimal outpatient scheduling.

    PubMed

    Patrick, Jonathan

    2012-06-01

    Managing an efficient outpatient clinic can often be complicated by significant no-show rates and escalating appointment lead times. One method that has been proposed for avoiding the wasted capacity due to no-shows is called open or advanced access. The essence of open access is "do today's demand today". We develop a Markov Decision Process (MDP) model that demonstrates that a short booking window does significantly better than open access. We analyze a number of scenarios that explore the trade-off between patient-related measures (lead times) and physician- or system-related measures (revenue, overtime and idle time). Through simulation, we demonstrate that, over a wide variety of potential scenarios and clinics, the MDP policy does as well or better than open access in terms of minimizing costs (or maximizing profits) as well as providing more consistent throughput. PMID:22089944

  15. The Role of Intent in Ethical Decision Making: The Ethical Choice Model

    ERIC Educational Resources Information Center

    King, Christine; Powell, Toni

    2007-01-01

    This paper reviews the major theories, studies and models concerning ethical decision making in organizations. The authors drew upon Jones' Model (1991) as the foundation for their Ethical Choice Model, which is designed to further clarify the ethical decision making process as it relates to the construct of intentionality. The model, illustrated…

  16. Time-variant clustering model for understanding cell fate decisions.

    PubMed

    Huang, Wei; Cao, Xiaoyi; Biase, Fernando H; Yu, Pengfei; Zhong, Sheng

    2014-11-01

    Both spatial characteristics and temporal features are often the subjects of concern in physical, social, and biological studies. This work tackles the clustering problems for time course data in which the cluster number and clustering structure change with respect to time, dubbed time-variant clustering. We developed a hierarchical model that simultaneously clusters the objects at every time point and describes the relationships of the clusters between time points. The hidden layer of this model is a generalized form of branching processes. A reversible-jump Markov Chain Monte Carlo method was implemented for model inference, and a feature selection procedure was developed. We applied this method to explore an open question in preimplantation embryonic development. Our analyses using single-cell gene expression data suggested that the earliest cell fate decision could start at the 4-cell stage in mice, earlier than the commonly thought 8- to 16-cell stage. These results together with independent experimental data from single-cell RNA-seq provided support against a prevailing hypothesis in mammalian development. PMID:25339442

  17. Time-variant clustering model for understanding cell fate decisions

    PubMed Central

    Huang, Wei; Cao, Xiaoyi; Biase, Fernando H.; Yu, Pengfei; Zhong, Sheng

    2014-01-01

    Both spatial characteristics and temporal features are often the subjects of concern in physical, social, and biological studies. This work tackles the clustering problems for time course data in which the cluster number and clustering structure change with respect to time, dubbed time-variant clustering. We developed a hierarchical model that simultaneously clusters the objects at every time point and describes the relationships of the clusters between time points. The hidden layer of this model is a generalized form of branching processes. A reversible-jump Markov Chain Monte Carlo method was implemented for model inference, and a feature selection procedure was developed. We applied this method to explore an open question in preimplantation embryonic development. Our analyses using single-cell gene expression data suggested that the earliest cell fate decision could start at the 4-cell stage in mice, earlier than the commonly thought 8- to 16-cell stage. These results together with independent experimental data from single-cell RNA-seq provided support against a prevailing hypothesis in mammalian development. PMID:25339442

  18. Management decision making for fisher populations informed by occupancy modeling

    USGS Publications Warehouse

    Fuller, Angela K.; Linden, Daniel W.; Royle, J. Andrew

    2016-01-01

    Harvest data are often used by wildlife managers when setting harvest regulations for species because the data are regularly collected and do not require implementation of logistically and financially challenging studies to obtain the data. However, when harvest data are not available because an area had not previously supported a harvest season, alternative approaches are required to help inform management decision making. When distribution or density data are required across large areas, occupancy modeling is a useful approach, and under certain conditions, can be used as a surrogate for density. We collaborated with the New York State Department of Environmental Conservation (NYSDEC) to conduct a camera trapping study across a 70,096-km2 region of southern New York in areas that were currently open to fisher (Pekania [Martes] pennanti) harvest and those that had been closed to harvest for approximately 65 years. We used detection–nondetection data at 826 sites to model occupancy as a function of site-level landscape characteristics while accounting for sampling variation. Fisher occupancy was influenced positively by the proportion of conifer and mixed-wood forest within a 15-km2 grid cell and negatively associated with road density and the proportion of agriculture. Model-averaged predictions indicated high occupancy probabilities (>0.90) when road densities were low (<1 km/km2) and coniferous and mixed forest proportions were high (>0.50). Predicted occupancy ranged 0.41–0.67 in wildlife management units (WMUs) currently open to trapping, which could be used to guide a minimum occupancy threshold for opening new areas to trapping seasons. There were 5 WMUs that had been closed to trapping but had an average predicted occupancy of 0.52 (0.07 SE), and above the threshold of 0.41. These areas are currently under consideration by NYSDEC for opening a conservative harvest season. We demonstrate the use of occupancy modeling as an aid to management

  19. A Critical Analysis of HRD Evaluation Models from a Decision-Making Perspective

    ERIC Educational Resources Information Center

    Holton, Elwood F., III; Naquin, Sharon

    2005-01-01

    HRD evaluation models are recommended for use by organizations to improve decisions made about HRD interventions. However, the organizational decision-making literature has been virtually ignored by evaluation researchers. In this article, we review the organizational decision-making literature and critically review HRD evaluation research through…

  20. Logit Estimation of a Gravity Model of the College Enrollment Decision.

    ERIC Educational Resources Information Center

    Leppel, Karen

    1993-01-01

    A study investigated the factors influencing students' decisions about attending a college to which they had been admitted. Logit analysis confirmed gravity model predictions that geographic distance and student ability would most influence the enrollment decision and found other variables, although affecting earlier stages of decision making, did…

  1. Decision-Making Models in a Tunisian University: Towards a Framework for Analysis

    ERIC Educational Resources Information Center

    Khefacha, I.; Belkacem, L.

    2014-01-01

    This study investigates how decisions are made in Tunisian public higher education establishments. Some factors are identified as having a potentially significant impact on the odds that the decision-making process follows the characteristics of one of the most well known decision-making models: collegial, political, bureaucratic or anarchical…

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  3. Between Safety and Risk: A Model for Outdoor Adventure Decision Making.

    ERIC Educational Resources Information Center

    Boyes, Michael A.; O'Hare, David

    2003-01-01

    Decision making by outdoor adventure educators revolves around balancing risk and competence. A model of outdoor adventure decision making is presented that draws on naturalistic decision-making processes and emphasizes the importance of situational recognition and prior experience. Leaders draw key information from the natural environment,…

  4. A novel sustainable decision making model for municipal solid waste management

    SciTech Connect

    Hung, M.-L. . E-mail: d89541004@ntu.edu.tw; Ma Hwongwen . E-mail: hwma@ntu.edu.tw; Yang, W.-F. . E-mail: wfyang@ntu.edu.tw

    2007-07-01

    This paper reviews several models developed to support decision making in municipal solid waste management (MSWM). The concepts underlying sustainable MSWM models can be divided into two categories: one incorporates social factors into decision making methods, and the other includes public participation in the decision-making process. The public is only apprised or takes part in discussion, and has little effect on decision making in most research efforts. Few studies have considered public participation in the decision-making process, and the methods have sought to strike a compromise between concerned criteria, not between stakeholders. However, the source of the conflict arises from the stakeholders' complex web of value. Such conflict affects the feasibility of implementing any decision. The purpose of this study is to develop a sustainable decision making model for MSWM to overcome these shortcomings. The proposed model combines multicriteria decision making (MCDM) and a consensus analysis model (CAM). The CAM is built up to aid in decision-making when MCDM methods are utilized and, subsequently, a novel sustainable decision making model for MSWM is developed. The main feature of CAM is the assessment of the degree of consensus between stakeholders for particular alternatives. A case study for food waste management in Taiwan is presented to demonstrate the practicality of this model.

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

    PubMed

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

    2016-08-01

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

  6. Applications of a simulation model to decisions in mallard management

    USGS Publications Warehouse

    Cowardin, L.M.; Johnson, D.H.; Shaffer, T.L.; Sparling, D.W.

    1988-01-01

    A system comprising simulation models and data bases for habitat availability and nest success rates was used to predict results from a mallard (Anas platyrhynchos) management plan and to compare six management methods with a control. Individual treatments in the applications included land purchase for waterfowl production, wetland easement purchase, lease of uplands for waterfowl management, cropland retirement, use of no-till winter wheat, delayed cutting of alfalfa, installation of nest baskets, nesting island construction, and use of predator-resistant fencing.The simulations predicted that implementation of the management plan would increase recruits by 24%. Nest baskets were the most effective treatment, accounting for 20.4% of the recruits. No-till winter wheat was the second most effective, accounting for 5.9% of the recruits. Wetland loss due to drainage would cause an 11% loss of breeding population in 10 years.The models were modified to account for migrational homing. The modification indicated that migrational homing would enhance the effects of management. Nest success rates were critical contributions to individual management methods. The most effective treatments, such as nest baskets, had high success rates and affected a large portion of the breeding population.Economic analyses indicated that nest baskets would be the most economical of the three techniques tested. The applications indicated that the system is a useful tool to aid management decisions, but data are scarce for several important variables. Basic research will be required to adequately model the effect of migrational homing and density dependence on production. The comprehensive nature of predictions desired by managers will also require that production models like the one described here be extended to encompass the entire annual cycle of waterfowl.

  7. Bayesian Decision Theory Guiding Educational Decision-Making: Theories, Models and Application

    ERIC Educational Resources Information Center

    Pan, Yilin

    2016-01-01

    Given the importance of education and the growing public demand for improving education quality under tight budget constraints, there has been an emerging movement to call for research-informed decisions in educational resource allocation. Despite the abundance of rigorous studies on the effectiveness, cost, and implementation of educational…

  8. Modeling Decision-Specific Stress: Some Methodological Considerations.

    ERIC Educational Resources Information Center

    Holbrook, Morris B.; Ryan, Michael J.

    1982-01-01

    A national questionnaire survey of 324 automotive fleet administrators, examining the effects of three stress variables (decisional ambiguity, conflict, and work overload) in the administrators' 17 decision areas, tested whether managerial stress is decision-specific. Individual-level correlations and aggregate-level multidimensional scaling…

  9. A Four Value Personnel Decision Model: Remedial Placement.

    ERIC Educational Resources Information Center

    Boldt, Robert F.

    The personnel decision principally treated in this paper is that of remedial placement. The decision made with respect to candidates is to accept or reject, and performances by candidates are evaluated as pass or fail. A criterion and a selection variable were assumed, and the problem is to choose a cutting score on the selection variable such…

  10. Modeling Prosecutors' Charging Decisions in Domestic Violence Cases

    ERIC Educational Resources Information Center

    Worrall, John L.; Ross, Jay W.; McCord, Eric S.

    2006-01-01

    Relatively little research explaining prosecutors' charging decisions in criminal cases is available. Even less has focused on charging decisions in domestic violence cases. Past studies have also relied on restrictive definitions of domestic violence, notably cases with male offenders and female victims, and they have not considered prosecutors'…

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  13. Determining the optimal planting density and land expectation value -- a numerical evaluation of decision model

    SciTech Connect

    Gong, P. . Dept. of Forest Economics)

    1998-08-01

    Different decision models can be constructed and used to analyze a regeneration decision in even-aged stand management. However, the optimal decision and management outcomes determined in an analysis may depend on the decision model used in the analysis. This paper examines the proper choice of decision model for determining the optimal planting density and land expectation value (LEV) for a Scots pine (Pinus sylvestris L.) plantation in northern Sweden. First, a general adaptive decision model for determining the regeneration alternative that maximizes the LEV is presented. This model recognizes future stand state and timber price uncertainties by including multiple stand state and timber price scenarios, and assumes that the harvest decision in each future period will be made conditional on the observed stand state and timber prices. Alternative assumptions about future stand states, timber prices, and harvest decisions can be incorporated into this general decision model, resulting in several different decision models that can be used to analyze a specific regeneration problem. Next, the consequences of choosing different modeling assumptions are determined using the example Scots pine plantation problem. Numerical results show that the most important sources of uncertainty that affect the optimal planting density and LEV are variations of the optimal clearcut time due to short-term fluctuations of timber prices. It is appropriate to determine the optimal planting density and harvest policy using an adaptive decision model that recognizes uncertainty only in future timber prices. After the optimal decisions have been found, however, the LEV should be re-estimated by incorporating both future stand state and timber price uncertainties.

  14. ICADS: A cooperative decision making model with CLIPS experts

    NASA Technical Reports Server (NTRS)

    Pohl, Jens; Myers, Leonard

    1991-01-01

    A cooperative decision making model is described which is comprised of six concurrently executing domain experts coordinated by a blackboard control expert. The focus application field is architectural design, and the domain experts represent consultants in the area of daylighting, noise control, structural support, cost estimating, space planning, and climate responsiveness. Both the domain experts and the blackboard were implemented as production systems, using an enhanced version of the basic CLIPS package. Acting in unison as an Expert Design Advisor, the domain and control experts react to the evolving design solution progressively developed by the user in a 2-D CAD drawing environment. A Geometry Interpreter maps each drawing action taken by the user to real world objects, such as spaces, walls, windows, and doors. These objects, endowed with geometric and nongeometric attributes, are stored as frames in a semantic network. Object descriptions are derived partly from the geometry of the drawing environment and partly from knowledge bases containing prototypical, generalized information about the building type and site conditions under consideration.

  15. Making Risk Models Operational for Situational Awareness and Decision Support

    SciTech Connect

    Paulson, Patrick R.; Coles, Garill A.; Shoemaker, Steven V.

    2012-06-12

    Modernization of nuclear power operations control systems, in particular the move to digital control systems, creates an opportunity to modernize existing legacy infrastructure and extend plant life. We describe here decision support tools that allow the assessment of different facets of risk and support the optimization of available resources to reduce risk as plants are upgraded and maintained. This methodology could become an integrated part of the design review process and a part of the operations management systems. The methodology can be applied to the design of new reactors such as small nuclear reactors (SMR), and be helpful in assessing the risks of different configurations of the reactors. Our tool provides a low cost evaluation of alternative configurations and provides an expanded safety analysis by considering scenarios while early in the implementation cycle where cost impacts can be minimized. The effects of failures can be modeled and thoroughly vetted to understand their potential impact on risk. The process and tools presented here allow for an integrated assessment of risk by supporting traditional defense in depth approaches while taking into consideration the insertion of new digital instrument and control systems.

  16. Assessing electronic health record systems in emergency departments: Using a decision analytic Bayesian model.

    PubMed

    Ben-Assuli, Ofir; Leshno, Moshe

    2016-09-01

    In the last decade, health providers have implemented information systems to improve accuracy in medical diagnosis and decision-making. This article evaluates the impact of an electronic health record on emergency department physicians' diagnosis and admission decisions. A decision analytic approach using a decision tree was constructed to model the admission decision process to assess the added value of medical information retrieved from the electronic health record. Using a Bayesian statistical model, this method was evaluated on two coronary artery disease scenarios. The results show that the cases of coronary artery disease were better diagnosed when the electronic health record was consulted and led to more informed admission decisions. Furthermore, the value of medical information required for a specific admission decision in emergency departments could be quantified. The findings support the notion that physicians and patient healthcare can benefit from implementing electronic health record systems in emergency departments. PMID:26033468

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  18. Integrated Modelling Frameworks for Environmental Assessment and Decision Support

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Modern management of environmental resources defines problems from a holistic and integrated perspective, imposing strong requirements to Environmental Decision Support Systems (EDSSs) and Integrated Assessment Tools (IATs), which tend to be increasingly complex in terms of software architecture and...

  19. 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

  20. Decision Support Model for Introduction of Gamification Solution Using AHP

    PubMed Central

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

  1. Decision support model for introduction of gamification solution using AHP.

    PubMed

    Kim, Sangkyun

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

  2. A Model of Decision-Making for Teachers Engaged in Developmental Research.

    ERIC Educational Resources Information Center

    Impey, William D.

    An analysis of the rationale, concepts and procedures for designing and implementing a model of decision-making for teachers engaged in developmental research is presented. The decision-making model is conceptualized as the intersection of four sets of data sources derived from the performance of preactive/planning tasks,…

  3. A Review of Contemporary Ethical Decision-Making Models for Mental Health Professionals

    ERIC Educational Resources Information Center

    Francis, Perry C.

    2015-01-01

    Mental health professionals are faced with increasingly complex ethical decisions that are impacted by culture, personal and professional values, and the contexts in which they and their clients inhabit. This article presents the reasons for developing and implementing multiple ethical decision making models and reviews four models that address…

  4. Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments

    ERIC Educational Resources Information Center

    Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.

    2009-01-01

    The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…

  5. Methodology for the use of DSSAT Models for Precision Agriculture Decision Support

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A prototype decision support system (DSS) called Apollo was developed to assist researchers in using the Decision Support System for Agrotechnology Transfer (DSSAT) crop growth models to analyze precision farming datasets. Because the DSSAT models are written to simulate crop growth and development...

  6. Decision-making Strategies and Performance among Seniors1

    PubMed Central

    Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

    2011-01-01

    Using paper and pencil experiments administered in senior centers, we examine decision-making performance in multi-attribute decision problems. We differentiate the effects of declining cognitive performance and changing cognitive process on decision-making performance of seniors as they age. We find a significant decline in performance with age due to reduced reliance on common heuristics and increased decision-making randomness among our oldest subjects. However, we find that increasing the number of options in a decision problem increases the number of heuristics brought to the task. This challenges the choice overload view that people give up when confronted with too much choice. PMID:22408282

  7. Impact of model development, calibration and validation decisions on hydrological simulations in West Lake Erie Basin

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Watershed simulation models are used extensively to investigate hydrologic processes, landuse and climate change impacts, pollutant load assessments and best management practices (BMPs). Developing, calibrating and validating these models require a number of critical decisions that will influence t...

  8. Decision-Making Models with Sets of Strategies for Applications to Individuals and Groups in Higher Education.

    ERIC Educational Resources Information Center

    Gill, Wanda E.

    Three decision-making models that have applications for college presidents and administrators are reviewed. While both individual and group decision-making are addressed, emphasis is placed on the importance of group decisions on institutional policy planning. The model of Edmund M. Burke (1979) presents specific decision-making strategies in…

  9. Decision support models for solid waste management: Review and game-theoretic approaches

    SciTech Connect

    Karmperis, Athanasios C.; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios

    2013-05-15

    Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.

  10. 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

  11. Stochastic model for fatigue crack size and cost effective design decisions. [for aerospace structures

    NASA Technical Reports Server (NTRS)

    Hanagud, S.; Uppaluri, B.

    1975-01-01

    This paper describes a methodology for making cost effective fatigue design decisions. The methodology is based on a probabilistic model for the stochastic process of fatigue crack growth with time. The development of a particular model for the stochastic process is also discussed in the paper. The model is based on the assumption of continuous time and discrete space of crack lengths. Statistical decision theory and the developed probabilistic model are used to develop the procedure for making fatigue design decisions on the basis of minimum expected cost or risk function and reliability bounds. Selections of initial flaw size distribution, NDT, repair threshold crack lengths, and inspection intervals are discussed.

  12. Modeling Hospital Discharge and Placement Decision Making: Whither the Elderly.

    ERIC Educational Resources Information Center

    Clark, William F.; Pelham, Anabel O.

    This paper examines the hospital discharge decision making process for elderly patients, based on observations of the operations of a long term care agency, the California Multipurpose Senior Services Project. The analysis is divided into four components: actors, factors, processes, and strategy critique. The first section discusses the major…

  13. A Three-Phase Model of Retirement Decision Making

    ERIC Educational Resources Information Center

    Feldman, Daniel C.; Beehr, Terry A.

    2011-01-01

    The present article organizes prominent theories about retirement decision making around three different types of thinking about retirement: imagining the possibility of retirement, assessing when it is time to let go of long-held jobs, and putting concrete plans for retirement into action at present. It also highlights important directions for…

  14. 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…

  15. A Social Constructivism Model of Ethical Decision Making in Counseling.

    ERIC Educational Resources Information Center

    Cottone, R. Rocco

    2001-01-01

    Examines social constructivism as an intellectual movement in the mental health field that directs a social consensual interpretation of reality. Presents a social constructivism approach to counseling which redefines the ethical decision-making process as an interactive rather than individual or intrapsychic process. Explores how the process…

  16. A new fit-for-purpose model testing framework: Decision Crash Tests

    NASA Astrophysics Data System (ADS)

    Tolson, Bryan; Craig, James

    2016-04-01

    Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building

  17. Modeling for health care and other policy decisions: uses, roles, and validity.

    PubMed

    Weinstein, M C; Toy, E L; Sandberg, E A; Neumann, P J; Evans, J S; Kuntz, K M; Graham, J D; Hammitt, J K

    2001-01-01

    The role of models to support recommendations on the cost-effective use of medical technologies and pharmaceuticals is controversial. At the heart of the controversy is the degree to which experimental or other empirical evidence should be required prior to model use. The controversy stems in part from a misconception that the role of models is to establish truth rather than to guide clinical and policy decisions. In other domains of public policy that involve human life and health, such as environmental protection and defense strategy, models are generally accepted as decision aids, and many models have been formally incorporated into regulatory processes and governmental decision making. We formulate an analytical framework for evaluating the role of models as aids to decision making. Implications for the implementation of Section 114 of the Food and Drug Administration Modernization Act (FDAMA) are derived from this framework. PMID:11705125

  18. Analysis and Management of Animal Populations: Modeling, Estimation and Decision Making

    USGS Publications Warehouse

    Williams, B.K.; Nichols, J.D.; Conroy, M.J.

    2002-01-01

    This book deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal populations. KEY FEATURES * Integrates population modeling, parameter estimation and * decision-theoretic approaches to management in a single, cohesive framework * Provides authoritative, state-of-the-art descriptions of quantitative * approaches to modeling, estimation and decision-making * Emphasizes the role of mathematical modeling in the conduct of science * and management * Utilizes a unifying biological context, consistent mathematical notation, * and numerous biological examples

  19. An engineering approach to modelling, decision support and control for sustainable systems.

    PubMed

    Day, W; Audsley, E; Frost, A R

    2008-02-12

    Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems. PMID:17656345

  20. Enabling Integrated Decision Making for Electronic-Commerce by Modelling an Enterprise's Sharable Knowledge.

    ERIC Educational Resources Information Center

    Kim, Henry M.

    2000-01-01

    An enterprise model, a computational model of knowledge about an enterprise, is a useful tool for integrated decision-making by e-commerce suppliers and customers. Sharable knowledge, once represented in an enterprise model, can be integrated by the modeled enterprise's e-commerce partners. Presents background on enterprise modeling, followed by…

  1. Assessment of Trading Partners for China's Rare Earth Exports Using a Decision Analytic Approach

    PubMed Central

    He, Chunyan; Lei, Yalin; Ge, Jianping

    2014-01-01

    Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies. PMID:25051534

  2. Assessment of trading partners for China's rare earth exports using a decision analytic approach.

    PubMed

    He, Chunyan; Lei, Yalin; Ge, Jianping

    2014-01-01

    Chinese rare earth export policies currently result in accelerating its depletion. Thus adopting an optimal export trade selection strategy is crucial to determining and ultimately identifying the ideal trading partners. This paper introduces a multi-attribute decision-making methodology which is then used to select the optimal trading partner. In the method, an evaluation criteria system is established to assess the seven top trading partners based on three dimensions: political relationships, economic benefits and industrial security. Specifically, a simple additive weighing model derived from an additive utility function is utilized to calculate, rank and select alternatives. Results show that Japan would be the optimal trading partner for Chinese rare earths. The criteria evaluation method of trading partners for China's rare earth exports provides the Chinese government with a tool to enhance rare earth industrial policies. PMID:25051534

  3. A Strategic Model for the Business Communication Field Training Decision in the Commercial Enterprises

    NASA Astrophysics Data System (ADS)

    Ioannis, Seimenis; Damianos, Sakas P.; Nikolaos, Konstantopoulos

    2009-08-01

    This article examines the factors that affect the decision making of the training managers responsible in case of business communication field as they have emerged from the study of the decision that have taken place in the commercial sector in this specific Greek market. Previous researches have indicated the participation of a number of variables in this kind of decision. The aim of this article is to locate the main factors which determine, in the commercial sector the decision for the training of the employees in the field of business communication. On the basis of quality research, dynamic simulation model have been created for some of this main factors.

  4. A Multilevel Model of Minority Opinion Expression and Team Decision-Making Effectiveness

    ERIC Educational Resources Information Center

    Park, Guihyun; DeShon, Richard P.

    2010-01-01

    The consideration of minority opinions when making team decisions is an important factor that contributes to team effectiveness. A multilevel model of minority opinion influence in decision-making teams is developed to address the conditions that relate to adequate consideration of minority opinions. Using a sample of 57 teams working on a…

  5. Assessing the Utility of the Willingness/Prototype Model in Predicting Help-Seeking Decisions

    ERIC Educational Resources Information Center

    Hammer, Joseph H.; Vogel, David L.

    2013-01-01

    Prior research on professional psychological help-seeking behavior has operated on the assumption that the decision to seek help is based on intentional and reasoned processes. However, research on the dual-process prototype/willingness model (PWM; Gerrard, Gibbons, Houlihan, Stock, & Pomery, 2008) suggests health-related decisions may also…

  6. A Leadership Decision-Making Model for the Program Development and Management of Adult Education Agencies.

    ERIC Educational Resources Information Center

    Sample, John A.

    1985-01-01

    Addresses the issue of participation in the development and management of programs for adult learners. The Vroom and Yetton model of leadership decision making, a contingency approach that utilizes a range of decision styles, is described through various case examples. (CT)

  7. A Socioecological Model of Rape Survivors' Decisions to Aid in Case Prosecution

    ERIC Educational Resources Information Center

    Anders, Mary C.; Christopher, F. Scott

    2011-01-01

    The purpose of our study was to identify factors underlying rape survivors' post-assault prosecution decisions by testing a decision model that included the complex relations between the multiple social ecological systems within which rape survivors are embedded. We coded 440 police rape cases for characteristics of the assault and characteristics…

  8. Examination of a Group Counseling Model of Career Decision Making with College Students

    ERIC Educational Resources Information Center

    Rowell, P. Clay; Mobley, A. Keith; Kemer, Gulsah; Giordano, Amanda

    2014-01-01

    The authors examined the effectiveness of a group career counseling model (Pyle, K. R., 2007) on college students' career decision-making abilities. They used a Solomon 4-group design and found that students who participated in the career counseling groups had significantly greater increases in career decision-making abilities than those who…

  9. A Framework for Making Sustainable Cleanup Decisions Using the KONVERGENCE Model

    SciTech Connect

    Piet, Steven James; Dettmers, Dana Lee; Dakins, Maxine Ellen; Eide, Steven Arvid; Gibson, Patrick Lavern; Joe, Jeffrey Clark; Kerr, Thomas A; Nitschke, Robert Leon; Oswald, Kyle Blaine; Reisenauer, John Phillip

    2002-08-01

    The effects of closure decisions for used nuclear facilities can extend centuries into the future. Yet, the longevity of decisions made over the past half century has been poor. Our goal is an improved decision framework for decommissioning, stewardship, and waste management. This paper describes our overall framework. Companion papers describe the underlying philosophy of the KONVERGENCE Model for Sustainable Decisions1 and implications for a class of intractable decision problems.2 Where knowledge, values, and resources converge (the K, V, and R in KONVERGENCE), you will find a sustainable decision – a decision that works over time. Our approach clarifies what is needed to make and keep decisions over relevant time periods. The process guides participants through establishing the real problem, understanding the universes of knowledge, values, resources, and generating alternatives. We explore three classes of alternatives – reusable (e.g. greenfield), closed (e.g. entombed structures), and adaptable. After testing for konvergence of alternatives among knowledge, values, resources, we offer suggestions to diagnose divergence, to reduce divergence by refining alternatives to address identified weaknesses, and to plan to keep konvergence over the life of the decision. We believe that decisions made via this method will better stand the test of time – because it will be either acceptable to keep them unchanged or possible to adapt them as knowledge, values, and resources change.

  10. Clarity versus complexity: land-use modeling as a practical tool for decision-makers

    USGS Publications Warehouse

    Sohl, Terry L.; Claggett, Peter R.

    2013-01-01

    The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

  11. Models in animal collective decision-making: information uncertainty and conflicting preferences.

    PubMed

    Conradt, Larissa

    2012-04-01

    Collective decision-making plays a central part in the lives of many social animals. Two important factors that influence collective decision-making are information uncertainty and conflicting preferences. Here, I bring together, and briefly review, basic models relating to animal collective decision-making in situations with information uncertainty and in situations with conflicting preferences between group members. The intention is to give an overview about the different types of modelling approaches that have been employed and the questions that they address and raise. Despite the use of a wide range of different modelling techniques, results show a coherent picture, as follows. Relatively simple cognitive mechanisms can lead to effective information pooling. Groups often face a trade-off between decision accuracy and speed, but appropriate fine-tuning of behavioural parameters could achieve high accuracy while maintaining reasonable speed. The right balance of interdependence and independence between animals is crucial for maintaining group cohesion and achieving high decision accuracy. In conflict situations, a high degree of decision-sharing between individuals is predicted, as well as transient leadership and leadership according to needs and physiological status. Animals often face crucial trade-offs between maintaining group cohesion and influencing the decision outcome in their own favour. Despite the great progress that has been made, there remains one big gap in our knowledge: how do animals make collective decisions in situations when information uncertainty and conflict of interest operate simultaneously? PMID:23565335

  12. Models in animal collective decision-making: information uncertainty and conflicting preferences

    PubMed Central

    Conradt, Larissa

    2012-01-01

    Collective decision-making plays a central part in the lives of many social animals. Two important factors that influence collective decision-making are information uncertainty and conflicting preferences. Here, I bring together, and briefly review, basic models relating to animal collective decision-making in situations with information uncertainty and in situations with conflicting preferences between group members. The intention is to give an overview about the different types of modelling approaches that have been employed and the questions that they address and raise. Despite the use of a wide range of different modelling techniques, results show a coherent picture, as follows. Relatively simple cognitive mechanisms can lead to effective information pooling. Groups often face a trade-off between decision accuracy and speed, but appropriate fine-tuning of behavioural parameters could achieve high accuracy while maintaining reasonable speed. The right balance of interdependence and independence between animals is crucial for maintaining group cohesion and achieving high decision accuracy. In conflict situations, a high degree of decision-sharing between individuals is predicted, as well as transient leadership and leadership according to needs and physiological status. Animals often face crucial trade-offs between maintaining group cohesion and influencing the decision outcome in their own favour. Despite the great progress that has been made, there remains one big gap in our knowledge: how do animals make collective decisions in situations when information uncertainty and conflict of interest operate simultaneously? PMID:23565335

  13. Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

    NASA Astrophysics Data System (ADS)

    Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

    2016-04-01

    Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

  14. Polya’s bees: A model of decentralized decision-making

    PubMed Central

    Golman, Russell; Hagmann, David; Miller, John H.

    2015-01-01

    How do social systems make decisions with no single individual in control? We observe that a variety of natural systems, including colonies of ants and bees and perhaps even neurons in the human brain, make decentralized decisions using common processes involving information search with positive feedback and consensus choice through quorum sensing. We model this process with an urn scheme that runs until hitting a threshold, and we characterize an inherent tradeoff between the speed and the accuracy of a decision. The proposed common mechanism provides a robust and effective means by which a decentralized system can navigate the speed-accuracy tradeoff and make reasonably good, quick decisions in a variety of environments. Additionally, consensus choice exhibits systemic risk aversion even while individuals are idiosyncratically risk-neutral. This too is adaptive. The model illustrates how natural systems make decentralized decisions, illuminating a mechanism that engineers of social and artificial systems could imitate. PMID:26601255

  15. Presentation and explanation of medical decision models using the World Wide Web.

    PubMed Central

    Sanders, G. D.; Dembitzer, A. D.; Heidenreich, P. A.; McDonald, K. M.; Owens, D. K.

    1996-01-01

    We demonstrated the use of the World Wide Web for the presentation and explanation of a medical decision model. We put on the web a treatment model developed as part of the Cardiac Arrhythmia and Risk of Death Patient Outcomes Research Team (CARD PORT). To demonstrate the advantages of our web-based presentation, we critiqued both the conventional paper-based and the web-based formats of this decision-model presentation with reference to an accepted published guide to understanding clinical decision models. A web-based presentation provides a useful supplement to paper-based publications by allowing authors to present their model in greater detail, to link model inputs to the primary evidence, and to disseminate the model to peer investigators for critique and collaborative modeling. PMID:8947628

  16. An analytical framework to assist decision makers in the use of forest ecosystem model predictions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The predictions of most terrestrial ecosystem models originate from deterministic simulations. Relatively few uncertainty evaluation exercises in model outputs are performed by either model developers or users. This issue has important consequences for decision makers who rely on models to develop n...

  17. Analysis of a decision model in the context of equilibrium pricing and order book pricing

    NASA Astrophysics Data System (ADS)

    Wagner, D. C.; Schmitt, T. A.; Schäfer, R.; Guhr, T.; Wolf, D. E.

    2014-12-01

    An agent-based model for financial markets has to incorporate two aspects: decision making and price formation. We introduce a simple decision model and consider its implications in two different pricing schemes. First, we study its parameter dependence within a supply-demand balance setting. We find realistic behavior in a wide parameter range. Second, we embed our decision model in an order book setting. Here, we observe interesting features which are not present in the equilibrium pricing scheme. In particular, we find a nontrivial behavior of the order book volumes which reminds of a trend switching phenomenon. Thus, the decision making model alone does not realistically represent the trading and the stylized facts. The order book mechanism is crucial.

  18. The Integrated Medical Model: A Decision Support Tool for In-flight Crew Health Care

    NASA Technical Reports Server (NTRS)

    Butler, Doug

    2009-01-01

    This viewgraph presentation reviews the development of an Integrated Medical Model (IMM) decision support tool for in-flight crew health care safety. Clinical methods, resources, and case scenarios are also addressed.

  19. Sex differences in a rat model of risky decision making.

    PubMed

    Orsini, Caitlin A; Willis, Markie L; Gilbert, Ryan J; Bizon, Jennifer L; Setlow, Barry

    2016-02-01

    Many debilitating psychiatric conditions, including drug addiction, are characterized by poor decision making and maladaptive risk-taking. Recent research has begun to probe this relationship to determine how brain mechanisms mediating risk-taking become compromised after chronic drug use. Currently, however, the majority of work in this field has used male subjects. Given the well-established sex differences in drug addiction, it is conceivable that such differences are also evident in risk-based decision making. To test this possibility, male and female adult rats were trained in a risky decision making task (RDT), in which they chose between a small, "safe" food reward and a large, "risky" food reward accompanied by an increasing probability of mild footshock punishment. Consistent with findings in human subjects, females were more risk averse, choosing the large, risky reward significantly less than males. This effect was not due to differences in shock reactivity or body weight, and risk-taking in females was not modulated by estrous phase. Systemic amphetamine administration decreased risk-taking in both males and females; however, females exhibited greater sensitivity to amphetamine, suggesting that dopaminergic signaling may partially account for sex differences in risk-taking. Finally, although males displayed greater instrumental responding for food reward, reward choice in the RDT was not affected by satiation, indicating that differences in motivation to obtain food reward cannot fully account for sex differences in risk-taking. These results should prove useful for developing targeted treatments for psychiatric conditions in which risk-taking is altered and that are known to differentially affect males and females. PMID:26653713

  20. Decision analysis: a tool to guide the R and D selection of alternative energy sources

    SciTech Connect

    Kriz, T.

    1980-05-01

    The array of alternative energy sources which are vying for the federal government's R and D dollar is formidable when compared to the politically acceptable amount which can be used to fund the research. To guide how these funds should be dispersed, a rational, defensible procedure is needed which can repeatedly be applied as new technologies and new information become available. The procedure advanced in this paper is a decision analysis technique known as multi attribute decision analysis (MADA) and its use is illustrated in an evaluation and ranking of solar thermal electric power generating systems. Since the ultimate purchase decision is made in the market place, the preferences of potential users have been sampled and brought to bear on the ranking. The focus of this description is on the formulation of the problem structure and the decision model, the treatment of uncertainty, and how the results relate to the questions asked by and of the Department of Energy, which funded the study. A final note proposes how decision analysis can be used to address the broader questions of choice among competing technologies with cautions concerning misuse of the procedure.

  1. Emotion, Decision-Making and Substance Dependence: A Somatic-Marker Model of Addiction

    PubMed Central

    Verdejo-García, A; Pérez-García, M; Bechara, A

    2006-01-01

    Similar to patients with orbitofrontal cortex lesions, substance dependent individuals (SDI) show signs of impairments in decision-making, characterised by a tendency to choose the immediate reward at the expense of severe negative future consequences. The somatic-marker hypothesis proposes that decision-making depends in many important ways on neural substrates that regulate homeostasis, emotion and feeling. According to this model, there should be a link between abnormalities in experiencing emotions in SDI, and their severe impairments in decision-making in real-life. Growing evidence from neuroscientific studies suggests that core aspects of substance addiction may be explained in terms of abnormal emotional guidance of decision-making. Behavioural studies have revealed emotional processing and decision-making deficits in SDI. Combined neuropsychological and physiological assessment has demonstrated that the poorer decision-making of SDI is associated with altered reactions to reward and punishing events. Imaging studies have shown that impaired decision-making in addiction is associated with abnormal functioning of a distributed neural network critical for the processing of emotional information, including the ventromedial cortex, the amygdala, the striatum, the anterior cingulate cortex, and the insular/somato-sensory cortices, as well as non-specific neurotransmitter systems that modulate activities of neural processes involved in decision-making. The aim of this paper is to review this growing evidence, and to examine the extent of which these studies support a somatic-marker model of addiction. PMID:18615136

  2. A Multi Criteria Group Decision-Making Model for Teacher Evaluation in Higher Education Based on Cloud Model and Decision Tree

    ERIC Educational Resources Information Center

    Chang, Ting-Cheng; Wang, Hui

    2016-01-01

    This paper proposes a cloud multi-criteria group decision-making model for teacher evaluation in higher education which is involving subjectivity, imprecision and fuzziness. First, selecting the appropriate evaluation index depending on the evaluation objectives, indicating a clear structural relationship between the evaluation index and…

  3. Model of human collective decision-making in complex environments

    NASA Astrophysics Data System (ADS)

    Carbone, Giuseppe; Giannoccaro, Ilaria

    2015-12-01

    A continuous-time Markov process is proposed to analyze how a group of humans solves a complex task, consisting in the search of the optimal set of decisions on a fitness landscape. Individuals change their opinions driven by two different forces: (i) the self-interest, which pushes them to increase their own fitness values, and (ii) the social interactions, which push individuals to reduce the diversity of their opinions in order to reach consensus. Results show that the performance of the group is strongly affected by the strength of social interactions and by the level of knowledge of the individuals. Increasing the strength of social interactions improves the performance of the team. However, too strong social interactions slow down the search of the optimal solution and worsen the performance of the group. In particular, we find that the threshold value of the social interaction strength, which leads to the emergence of a superior intelligence of the group, is just the critical threshold at which the consensus among the members sets in. We also prove that a moderate level of knowledge is already enough to guarantee high performance of the group in making decisions.

  4. Dimension reduction of decision variables for multireservoir operation: A spectral optimization model

    NASA Astrophysics Data System (ADS)

    Chen, Duan; Leon, Arturo S.; Gibson, Nathan L.; Hosseini, Parnian

    2016-01-01

    Optimizing the operation of a multireservoir system is challenging due to the high dimension of the decision variables that lead to a large and complex search space. A spectral optimization model (SOM), which transforms the decision variables from time domain to frequency domain, is proposed to reduce the dimensionality. The SOM couples a spectral dimensionality-reduction method called Karhunen-Loeve (KL) expansion within the routine of Nondominated Sorting Genetic Algorithm (NSGA-II). The KL expansion is used to represent the decision variables as a series of terms that are deterministic orthogonal functions with undetermined coefficients. The KL expansion can be truncated into fewer significant terms, and consequently, fewer coefficients by a predetermined number. During optimization, operators of the NSGA-II (e.g., crossover) are conducted only on the coefficients of the KL expansion rather than the large number of decision variables, significantly reducing the search space. The SOM is applied to the short-term operation of a 10-reservoir system in the Columbia River of the United States. Two scenarios are considered herein, the first with 140 decision variables and the second with 3360 decision variables. The hypervolume index is used to evaluate the optimization performance in terms of convergence and diversity. The evaluation of optimization performance is conducted for both conventional optimization model (i.e., NSGA-II without KL) and the SOM with different number of KL terms. The results show that the number of decision variables can be greatly reduced in the SOM to achieve a similar or better performance compared to the conventional optimization model. For the scenario with 140 decision variables, the optimal performance of the SOM model is found with six KL terms. For the scenario with 3360 decision variables, the optimal performance of the SOM model is obtained with 11 KL terms.

  5. Application of the Viterbi Algorithm in Hidden Markov Models for Exploring Irrigation Decision Series

    NASA Astrophysics Data System (ADS)

    Andriyas, S.; McKee, M.

    2014-12-01

    Anticipating farmers' irrigation decisions can provide the possibility of improving the efficiency of canal operations in on-demand irrigation systems. Although multiple factors are considered during irrigation decision making, for any given farmer there might be one factor playing a major role. Identification of that biophysical factor which led to a farmer deciding to irrigate is difficult because of high variability of those factors during the growing season. Analysis of the irrigation decisions of a group of farmers for a single crop can help to simplify the problem. We developed a hidden Markov model (HMM) to analyze irrigation decisions and explore the factor and level at which the majority of farmers decide to irrigate. The model requires observed variables as inputs and the hidden states. The chosen model inputs were relatively easily measured, or estimated, biophysical data, including such factors (i.e., those variables which are believed to affect irrigation decision-making) as cumulative evapotranspiration, soil moisture depletion, soil stress coefficient, and canal flows. Irrigation decision series were the hidden states for the model. The data for the work comes from the Canal B region of the Lower Sevier River Basin, near Delta, Utah. The main crops of the region are alfalfa, barley, and corn. A portion of the data was used to build and test the model capability to explore that factor and the level at which the farmer takes the decision to irrigate for future irrigation events. Both group and individual level behavior can be studied using HMMs. The study showed that the farmers cannot be classified into certain classes based on their irrigation decisions, but vary in their behavior from irrigation-to-irrigation across all years and crops. HMMs can be used to analyze what factor and, subsequently, what level of that factor on which the farmer most likely based the irrigation decision. The study shows that the HMM is a capable tool to study a process

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

    PubMed

    Bornstein, Aaron M; Daw, Nathaniel D

    2013-01-01

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

  7. Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model

    PubMed Central

    2016-01-01

    The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694

  8. Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

    PubMed

    Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

    2016-01-01

    The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results. PMID:26871694

  9. A generalized quantum-inspired decision making model for intelligent agent.

    PubMed

    Hu, Yuhuang; Loo, Chu Kiong

    2014-01-01

    A novel decision making for intelligent agent using quantum-inspired approach is proposed. A formal, generalized solution to the problem is given. Mathematically, the proposed model is capable of modeling higher dimensional decision problems than previous researches. Four experiments are conducted, and both empirical experiments results and proposed model's experiment results are given for each experiment. Experiments showed that the results of proposed model agree with empirical results perfectly. The proposed model provides a new direction for researcher to resolve cognitive basis in designing intelligent agent. PMID:24778580

  10. Combined monitoring, decision and control model for the human operator in a command and control desk

    NASA Technical Reports Server (NTRS)

    Muralidharan, R.; Baron, S.

    1978-01-01

    A report is given on the ongoing efforts to mode the human operator in the context of the task during the enroute/return phases in the ground based control of multiple flights of remotely piloted vehicles (RPV). The approach employed here uses models that have their analytical bases in control theory and in statistical estimation and decision theory. In particular, it draws heavily on the modes and the concepts of the optimal control model (OCM) of the human operator. The OCM is being extended into a combined monitoring, decision, and control model (DEMON) of the human operator by infusing decision theoretic notions that make it suitable for application to problems in which human control actions are infrequent and in which monitoring and decision-making are the operator's main activities. Some results obtained with a specialized version of DEMON for the RPV control problem are included.

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

    PubMed

    Yılmaz Balaman, Şebnem; Selim, Hasan

    2015-09-01

    The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures. PMID:25983228

  12. Optimizing Negotiation Conflict in the Cloud Service Negotiation Framework Using Probabilistic Decision Making Model

    PubMed Central

    Rajavel, Rajkumar; Thangarathinam, Mala

    2015-01-01

    Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework. PMID:26543899

  13. Optimizing Negotiation Conflict in the Cloud Service Negotiation Framework Using Probabilistic Decision Making Model.

    PubMed

    Rajavel, Rajkumar; Thangarathinam, Mala

    2015-01-01

    Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework. PMID:26543899

  14. Graphical representation of life paths to better convey results of decision models to patients.

    PubMed

    Rubrichi, Stefania; Rognoni, Carla; Sacchi, Lucia; Parimbelli, Enea; Napolitano, Carlo; Mazzanti, Andrea; Quaglini, Silvana

    2015-04-01

    The inclusion of patients' perspectives in clinical practice has become an important matter for health professionals, in view of the increasing attention to patient-centered care. In this regard, this report illustrates a method for developing a visual aid that supports the physician in the process of informing patients about a critical decisional problem. In particular, we focused on interpretation of the results of decision trees embedding Markov models implemented with the commercial tool TreeAge Pro. Starting from patient-level simulations and exploiting some advanced functionalities of TreeAge Pro, we combined results to produce a novel graphical output that represents the distributions of outcomes over the lifetime for the different decision options, thus becoming a more informative decision support in a context of shared decision making. The training example used to illustrate the method is a decision tree for thromboembolism risk prevention in patients with nonvalvular atrial fibrillation. PMID:25589524

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  16. Modeling Integrated Water-User Decisions with Intermittent Supplies

    NASA Astrophysics Data System (ADS)

    Lund, J. R.; Rosenberg, D.

    2006-12-01

    We present an economic-engineering method to estimate urban water use demands with intermittent water supplies. A two-stage, probabilistic optimization formulation includes a wide variety of water supply enhancement and conservation actions that individual households can adopt to meet multiple water quality uses with uncertain water availability. We embed the optimization in Monte-Carlo simulations to show aggregate effects at a utility (citywide) scale for a population of user conditions and decisions. Parametric analysis provides derivations of supply curves to subsidize conservation, demand responses to alternative pricing, and customer willingness-to-pay to avoid shortages. Results show a good empirical fit for the average and distribution of billed residential water use in Amman, Jordan. Additional outputs give likely market penetration rates for household conservation actions, associated water savings, and subsidies required to entice further adoption. We discuss new insights to size, target, market, and finance conservation programs and interpret a demand curve with block pricing.

  17. An Empirical Investigation of Integrated Multicriteria Group Decision Models in a Simulation/Gaming Context.

    ERIC Educational Resources Information Center

    Affisco, John F.; Chanin, Michael N.

    1990-01-01

    Presents two models of group decision making that integrate mathematical, multicriteria models with behavioral problem-solving concepts. The results of an empirical test that used the Business Management Laboratory simulation game are reported, and the performance of the two integrated models is compared with the performance of a nonintegrated…

  18. APPLICATIONS OF DECISION THEORY TECHNIQUES IN AIR POLLUTION MODELING

    EPA Science Inventory

    The study applies methods of operations research to two basic areas of air pollution modeling: (1) the generation of wind fields for use in models of regional scale transport, diffusion and chemistry; and (2) the application of models in studies of optimal pollution control strat...

  19. Consistency and consensus models for group decision-making with uncertain 2-tuple linguistic preference relations

    NASA Astrophysics Data System (ADS)

    Zhang, Zhen; Guo, Chonghui

    2016-08-01

    Due to the uncertainty of the decision environment and the lack of knowledge, decision-makers may use uncertain linguistic preference relations to express their preferences over alternatives and criteria. For group decision-making problems with preference relations, it is important to consider the individual consistency and the group consensus before aggregating the preference information. In this paper, consistency and consensus models for group decision-making with uncertain 2-tuple linguistic preference relations (U2TLPRs) are investigated. First of all, a formula which can construct a consistent U2TLPR from the original preference relation is presented. Based on the consistent preference relation, the individual consistency index for a U2TLPR is defined. An iterative algorithm is then developed to improve the individual consistency of a U2TLPR. To help decision-makers reach consensus in group decision-making under uncertain linguistic environment, the individual consensus and group consensus indices for group decision-making with U2TLPRs are defined. Based on the two indices, an algorithm for consensus reaching in group decision-making with U2TLPRs is also developed. Finally, two examples are provided to illustrate the effectiveness of the proposed algorithms.

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

    NASA Astrophysics Data System (ADS)

    Huang, Kuailin; Bai, Zhiyong

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

  1. Identifying the decision to be supported: a review of papers from environmental modelling and software

    USGS Publications Warehouse

    Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

    2012-01-01

    Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for

  2. Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing.

    PubMed

    Tsalatsanis, Athanasios; Hozo, Iztok; Kumar, Ambuj; Djulbegovic, Benjamin

    2015-01-01

    Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice. PMID:26244571

  3. Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing

    PubMed Central

    Tsalatsanis, Athanasios; Hozo, Iztok; Kumar, Ambuj; Djulbegovic, Benjamin

    2015-01-01

    Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called “threshold probability” at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today’s clinical practice. PMID:26244571

  4. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  5. Modelling human decision-making in coupled human and natural systems

    NASA Astrophysics Data System (ADS)

    Feola, G.

    2012-12-01

    A solid understanding of human decision-making is essential to analyze the complexity of coupled human and natural systems (CHANS) and inform policies to promote resilience in the face of environmental change. Human decisions drive and/or mediate the interactions and feedbacks, and contribute to the heterogeneity and non-linearity that characterize CHANS. However, human decision-making is usually over-simplistically modeled, whereby human agents are represented deterministically either as dumb or clairvoyant decision-makers. Decision-making models fall short in the integration of both environmental and human behavioral drivers, and concerning the latter, tend to focus on only one category, e.g. economic, cultural, or psychological. Furthermore, these models render a linear decision-making process and therefore fail to account for the recursive co-evolutionary dynamics in CHANS. As a result, these models constitute only a weak basis for policy-making. There is therefore scope and an urgent need for better approaches to human decision-making, to produce the knowledge that can inform vulnerability reduction policies in the face of environmental change. This presentation synthesizes the current state-of-the-art of modelling human decision-making in CHANS, with particular reference to agricultural systems, and delineates how the above mentioned shortcomings can be overcome. Through examples from research on pesticide use and adaptation to climate change, both based on the integrative agent-centered framework (Feola and Binder, 2010), the approach for an improved understanding of human agents in CHANS are illustrated. This entails: integrative approach, focus on behavioral dynamics more than states, feedbacks between individual and system levels, and openness to heterogeneity.

  6. Building a maintenance policy through a multi-criterion decision-making model

    NASA Astrophysics Data System (ADS)

    Faghihinia, Elahe; Mollaverdi, Naser

    2012-08-01

    A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.

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

    PubMed

    Ratcliff, Roger; Frank, Michael J

    2012-05-01

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

  8. A case study of high school teachers' decision making models for planning and teaching science

    NASA Astrophysics Data System (ADS)

    Duschl, Richard A.; Wright, Emmett

    The focus of this study was to investigate the manner and the degree to which science teachers consider the nature of the subject matter in their decision making addressing the planning and the delivery of instructional tasks. An assumption of the study is that considerations for the nature of the subject matter should be a factor in a teacher's decision making about what to teach and how to teach. Relevant research literature reviewed includes (1) human decision making and the development of cognitive models of reality, (2) modern philosophies of science, and (3) philosophy of science and science education. Methods of data collection and of data analysis followed Spradley's Developmental Research Sequence guidelines for conducting ethnographic research. Validity of research findings was established from the triangulation of observations, interviews, and documents and surveys. The goal of the research was the development of grounded hypotheses about science TEACHERS' pedagogical decision making. Based on the results of this study it is hypothesized that science TEACHERS' decision-making models of reality for the selection, implementation, and development of instructional tasks are dominated by considerations for (a) student development, (b) curriculum guide objectives, and (c) pressures of accountability. Little, if any, consideration is given to the nature of the subject matter by the science teachers in decision making. Implications exist for the disenfranchisement of teachers from the task of making decisions concerning what to teach.

  9. An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

    PubMed

    Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

    2015-07-15

    The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. PMID:25829290

  10. CO2-PENS: A CO2 Sequestration Systems Model Supporting Risk-Based Decisions

    NASA Astrophysics Data System (ADS)

    Stauffer, P. H.; Viswanathan, H. S.; Guthrie, G. D.; Pawar, R. J.; Kaszuba, J. P.; Carey, J. W.; Lichtner, P. C.; Ziock, H. J.; Dubey, M. K.; Olsen, S. C.; Chipera, S. J.; Fessenden-Rahn, J. E.

    2005-12-01

    The Zero Emissions Research and Technology (ZERT) project at the Los Alamos National Laboratory is studying the injection of CO2 into geologic repositories. We are formulating the problem as science based decision framework that can address issues of risk, cost, and technical requirements at all stages of the sequestration process. The framework is implemented in a system model that is capable of performing stochastic simulations to address uncertainty in different geologic sequestration scenarios, including injection into poorly characterized brine aquifers. Processes level laboratory experiments, field experiments, modeling, economic data, and risk theory are used to support the system level model that will be the basis for decision making. The current system model, CO2-PENS, is already proving to be useful in showing complex interactions between the different components of the framework. The system model also provides a consistent platform to document decisions made during the site selection, implementation, and closure periods.

  11. Using ILOG OPL-CPLEX and ILOG Optimization Decision Manager (ODM) to Develop Better Models

    NASA Astrophysics Data System (ADS)

    2008-10-01

    This session will provide an in-depth overview on building state-of-the-art decision support applications and models. You will learn how to harness the full power of the ILOG OPL-CPLEX-ODM Development System (ODMS) to develop optimization models and decision support applications that solve complex problems ranging from near real-time scheduling to long-term strategic planning. We will demonstrate how to use ILOG's Open Programming Language (OPL) to quickly model problems solved by ILOG CPLEX, and how to use ILOG ODM to gain further insight about the model. By the end of the session, attendees will understand how to take advantage of the powerful combination of ILOG OPL (to describe an optimization model) and ILOG ODM (to understand the relationships between data, decision variables and constraints).

  12. Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

    NASA Technical Reports Server (NTRS)

    Tavana, Madjid

    1995-01-01

    The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

  13. Using the Benner intuitive-humanistic decision-making model in action: a case study.

    PubMed

    Blum, Cynthia Ann

    2010-09-01

    Nurse educators make decisions that affect students in profound ways. This decision-making process may follow an intuitive-humanistic decision-making model. The author most connected with developing the intuitive model and the distinction between theoretical knowledge and experiential knowledge in the discipline of nursing is Patricia Benner (Thompson, 1999). Educators use intuition in forming judgments regarding educational planning. The educator may not be aware of subtleties that influence the decision but rely on a 'gut' instinct as they determine the appropriate action. Utilizing six key concepts identified by Dreyfus and Dreyfus (Benner and Tanner, 1987) this process utilizes what is known to the educator from previous situations to determine a course of action appropriate for the given situation. This paper describes a method one nursing educator used and identifies outcomes that could impact the career path for the student when determining if they were safe to continue in a practice based course. PMID:20202908

  14. Ecosystem services: Challenges and opportunities for hydrologic modeling to support decision making

    NASA Astrophysics Data System (ADS)

    Guswa, Andrew J.; Brauman, Kate A.; Brown, Casey; Hamel, Perrine; Keeler, Bonnie L.; Sayre, Susan Stratton

    2014-05-01

    Ecosystem characteristics and processes provide significant value to human health and well-being, and there is growing interest in quantifying those values. Of particular interest are water-related ecosystem services and the incorporation of their value into local and regional decision making. This presents multiple challenges and opportunities to the hydrologic-modeling community. To motivate advances in water-resources research, we first present three common decision contexts that draw upon an ecosystem-service framework: scenario analysis, payments for watershed services, and spatial planning. Within these contexts, we highlight the particular challenges to hydrologic modeling, and then present a set of opportunities that arise from ecosystem-service decisions. The paper concludes with a set of recommendations regarding how we can prioritize our work to support decisions based on ecosystem-service valuation.

  15. Journey of Excellence: Implementing a Shared Decision-Making Model.

    PubMed

    Murray, Karen; Yasso, Sabrina; Schomburg, Roberta; Terhune, Molly; Beidelschies, Marissa; Bowers, Devin; Goodyear-Bruch, Caryl

    2016-04-01

    Research has shown that nurses who participate in shared decision making (SDM) have more control over their practice and greater job satisfaction, and hospitals that have instituted SDM have lower rates of nurse turnover and better patient outcomes. The purpose of this article is to describe the implementation of an SDM structure at a pediatric hospital. The hospital's chief nurse officer charged a group of nurses with developing SDM guidelines to outline the purpose, structure, and function of unit councils. A targeted, multifaceted approach to the implementation of these guidelines led to the successful standardization of nine existing unit councils and the expansion of the SDM unit council structure to all other hospital units. Work continues with guideline refinement in response to the real-life circumstances nurses encounter on the units, and the original group of nurses continues to review literature on SDM best practices. In addition, professions other than nursing, including multidisciplinary teams in dialysis, cardiovascular surgery, respiratory therapy, and child life, have adopted the guidelines for use in their departments. PMID:27011138

  16. Relevance of behavioral and social models to the study of consumer energy decision making and behavior

    SciTech Connect

    Burns, B.A.

    1980-11-01

    This report reviews social and behavioral science models and techniques for their possible use in understanding and predicting consumer energy decision making and behaviors. A number of models and techniques have been developed that address different aspects of the decision process, use different theoretical bases and approaches, and have been aimed at different audiences. Three major areas of discussion were selected: (1) models of adaptation to social change, (2) decision making and choice, and (3) diffusion of innovation. Within these three areas, the contributions of psychologists, sociologists, economists, marketing researchers, and others were reviewed. Five primary components of the models were identified and compared. The components are: (1) situational characteristics, (2) product characteristics, (3) individual characteristics, (4) social influences, and (5) the interaction or decision rules. The explicit use of behavioral and social science models in energy decision-making and behavior studies has been limited. Examples are given of a small number of energy studies which applied and tested existing models in studying the adoption of energy conservation behaviors and technologies, and solar technology.

  17. Application of decision tree model for the ground subsidence hazard mapping near abandoned underground coal mines.

    PubMed

    Lee, Saro; Park, Inhye

    2013-09-30

    Subsidence of ground caused by underground mines poses hazards to human life and property. This study analyzed the hazard to ground subsidence using factors that can affect ground subsidence and a decision tree approach in a geographic information system (GIS). The study area was Taebaek, Gangwon-do, Korea, where many abandoned underground coal mines exist. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 50/50 for training and validation of the models. A data-mining classification technique was applied to the GSH mapping, and decision trees were constructed using the chi-squared automatic interaction detector (CHAID) and the quick, unbiased, and efficient statistical tree (QUEST) algorithms. The frequency ratio model was also applied to the GSH mapping for comparing with probabilistic model. The resulting GSH maps were validated using area-under-the-curve (AUC) analysis with the subsidence area data that had not been used for training the model. The highest accuracy was achieved by the decision tree model using CHAID algorithm (94.01%) comparing with QUEST algorithms (90.37%) and frequency ratio model (86.70%). These accuracies are higher than previously reported results for decision tree. Decision tree methods can therefore be used efficiently for GSH analysis and might be widely used for prediction of various spatial events. PMID:23702378

  18. Software Tools For Building Decision-support Models For Flood Emergency Situations

    NASA Astrophysics Data System (ADS)

    Garrote, L.; Molina, M.; Ruiz, J. M.; Mosquera, J. C.

    The SAIDA decision-support system was developed by the Spanish Ministry of the Environment to provide assistance to decision-makers during flood situations. SAIDA has been tentatively implemented in two test basins: Jucar and Guadalhorce, and the Ministry is currently planning to have it implemented in all major Spanish basins in a few years' time. During the development cycle of SAIDA, the need for providing as- sistance to end-users in model definition and calibration was clearly identified. System developers usually emphasise abstraction and generality with the goal of providing a versatile software environment. End users, on the other hand, require concretion and specificity to adapt the general model to their local basins. As decision-support models become more complex, the gap between model developers and users gets wider: Who takes care of model definition, calibration and validation?. Initially, model developers perform these tasks, but the scope is usually limited to a few small test basins. Before the model enters operational stage, end users must get involved in model construction and calibration, in order to gain confidence in the model recommendations. However, getting the users involved in these activities is a difficult task. The goal of this re- search is to develop representation techniques for simulation and management models in order to define, develop and validate a mechanism, supported by a software envi- ronment, oriented to provide assistance to the end-user in building decision models for the prediction and management of river floods in real time. The system is based on three main building blocks: A library of simulators of the physical system, an editor to assist the user in building simulation models, and a machine learning method to calibrate decision models based on the simulation models provided by the user.

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

    EPA Science Inventory

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

  20. A Decision Model for Evaluating Potential Change in Instructional Programs.

    ERIC Educational Resources Information Center

    Amor, J. P.; Dyer, J. S.

    A statistical model designed to assist elementary school principals in the process of selection educational areas which should receive additional emphasis is presented. For each educational area, the model produces an index number which represents the expected "value" per dollar spent on an instructional program appropriate for strengthening that…

  1. Validation of numerical ground water models used to guide decision making.

    PubMed

    Hassan, Ahmed E

    2004-01-01

    Many sites of ground water contamination rely heavily on complex numerical models of flow and transport to develop closure plans. This complexity has created a need for tools and approaches that can build confidence in model predictions and provide evidence that these predictions are sufficient for decision making. Confidence building is a long-term, iterative process and the author believes that this process should be termed model validation. Model validation is a process, not an end result. That is, the process of model validation cannot ensure acceptable prediction or quality of the model. Rather, it provides an important safeguard against faulty models or inadequately developed and tested models. If model results become the basis for decision making, then the validation process provides evidence that the model is valid for making decisions (not necessarily a true representation of reality). Validation, verification, and confirmation are concepts associated with ground water numerical models that not only do not represent established and generally accepted practices, but there is not even widespread agreement on the meaning of the terms as applied to models. This paper presents a review of model validation studies that pertain to ground water flow and transport modeling. Definitions, literature debates, previously proposed validation strategies, and conferences and symposia that focused on subsurface model validation are reviewed and discussed. The review is general and focuses on site-specific, predictive ground water models used for making decisions regarding remediation activities and site closure. The aim is to provide a reasonable starting point for hydrogeologists facing model validation for ground water systems, thus saving a significant amount of time, effort, and cost. This review is also aimed at reviving the issue of model validation in the hydrogeologic community and stimulating the thinking of researchers and practitioners to develop practical and

  2. Scale (in)variance in a unified diffusion model of decision making and timing.

    PubMed

    Simen, Patrick; Vlasov, Ksenia; Papadakis, Samantha

    2016-03-01

    Weber's law is the canonical scale-invariance law in psychology: when the intensities of 2 stimuli are scaled by any value k, the just-noticeable-difference between them also scales by k. A diffusion model that approximates a spike-counting process accounts for Weber's law (Link, 1992), but there exist surprising corollaries of this account that have not yet been described or tested. We show that (a) this spike-counting diffusion model predicts time-scale invariant decision time distributions in perceptual decision making, and time-scale invariant response time (RT) distributions in interval timing; (b) for 2-choice perceptual decisions, the model predicts equal accuracy but faster responding for stimulus pairs with equally scaled-up intensities; (c) the coefficient of variation (CV) of decision times should remain constant across average intensity scales, but should otherwise decrease as a specific function of stimulus discriminability and speed-accuracy trade-off; and (d) for timing tasks, RT CVs should be constant for all durations, and RT skewness should always equal 3 times the CV. We tested these predictions using visual, auditory and vibrotactile decision tasks and visual interval timing tasks in humans. The data conformed closely to the predictions in all modalities. These results support a unified theory of decision making and timing in terms of a common, underlying spike-counting process, compactly represented as a diffusion process. (PsycINFO Database Record PMID:26461957

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

    PubMed

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

    2016-01-01

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

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

    PubMed

    Chen, Li; Huepe, Cristián; Gross, Thilo

    2016-08-01

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

  5. From Process Models to Decision Making: The Use of Data Mining Techniques for Developing Effect Decision Support Systems

    NASA Astrophysics Data System (ADS)

    Conrads, P. A.; Roehl, E. A.

    2010-12-01

    Natural-resource managers face the difficult problem of controlling the interactions between hydrologic and man-made systems in ways that preserve resources while optimally meeting the needs of disparate stakeholders. Finding success depends on obtaining and employing detailed scientific knowledge about the cause-effect relations that govern the physics of these hydrologic systems. This knowledge is most credible when derived from large field-based datasets that encompass the wide range of variability in the parameters of interest. The means of converting data into knowledge of the hydrologic system often involves developing computer models that predict the consequences of alternative management practices to guide resource managers towards the best path forward. Complex hydrologic systems are typically modeled using computer programs that implement traditional, generalized, physical equations, which are calibrated to match the field data as closely as possible. This type of model commonly is limited in terms of demonstrable predictive accuracy, development time, and cost. The science of data mining presents a powerful complement to physics-based models. Data mining is a relatively new science that assists in converting large databases into knowledge and is uniquely able to leverage the real-time, multivariate data now being collected for hydrologic systems. In side-by-side comparisons with state-of-the-art physics-based hydrologic models, the authors have found data-mining solutions have been substantially more accurate, less time consuming to develop, and embeddable into spreadsheets and sophisticated decision support systems (DSS), making them easy to use by regulators and stakeholders. Three data-mining applications will be presented that demonstrate how data-mining techniques can be applied to existing environmental databases to address regional concerns of long-term consequences. In each case, data were transformed into information, and ultimately, into

  6. An analytical framework to assist decision makers in the use of forest ecosystem model predictions

    USGS Publications Warehouse

    Larocque, Guy R.; Bhatti, Jagtar S.; Ascough, J.C.; Liu, J.; Luckai, N.; Mailly, D.; Archambault, L.; Gordon, Andrew M.

    2011-01-01

    The predictions from most forest ecosystem models originate from deterministic simulations. However, few evaluation exercises for model outputs are performed by either model developers or users. This issue has important consequences for decision makers using these models to develop natural resource management policies, as they cannot evaluate the extent to which predictions stemming from the simulation of alternative management scenarios may result in significant environmental or economic differences. Various numerical methods, such as sensitivity/uncertainty analyses, or bootstrap methods, may be used to evaluate models and the errors associated with their outputs. However, the application of each of these methods carries unique challenges which decision makers do not necessarily understand; guidance is required when interpreting the output generated from each model. This paper proposes a decision flow chart in the form of an analytical framework to help decision makers apply, in an orderly fashion, different steps involved in examining the model outputs. The analytical framework is discussed with regard to the definition of problems and objectives and includes the following topics: model selection, identification of alternatives, modelling tasks and selecting alternatives for developing policy or implementing management scenarios. Its application is illustrated using an on-going exercise in developing silvicultural guidelines for a forest management enterprise in Ontario, Canada. ?? 2010.

  7. Non-thermal transitions in a model inspired by moral decisions

    NASA Astrophysics Data System (ADS)

    Alamino, Roberto C.

    2016-08-01

    This work introduces a model in which agents of a network act upon one another according to three different kinds of moral decisions. These decisions are based on an increasing level of sophistication in the empathy capacity of the agent, a hierarchy which we name Piaget’s ladder. The decision strategy of the agents is non-rational, in the sense they are arbitrarily fixed, and the model presents quenched disorder given by the distribution of its defining parameters. An analytical solution for this model is obtained in the large system limit as well as a leading order correction for finite-size systems which shows that typical realisations of the model develop a phase structure with both continuous and discontinuous non-thermal transitions.

  8. Issues in Developing a Normative Descriptive Model for Dyadic Decision Making

    NASA Technical Reports Server (NTRS)

    Serfaty, D.; Kleinman, D. L.

    1984-01-01

    Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.

  9. Customer Decision Making in Web Services with an Integrated P6 Model

    NASA Astrophysics Data System (ADS)

    Sun, Zhaohao; Sun, Junqing; Meredith, Grant

    Customer decision making (CDM) is an indispensable factor for web services. This article examines CDM in web services with a novel P6 model, which consists of the 6 Ps: privacy, perception, propensity, preference, personalization and promised experience. This model integrates the existing 6 P elements of marketing mix as the system environment of CDM in web services. The new integrated P6 model deals with the inner world of the customer and incorporates what the customer think during the DM process. The proposed approach will facilitate the research and development of web services and decision support systems.

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

    NASA Astrophysics Data System (ADS)

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

    2011-07-01

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

  11. Neural mechanisms regulating different forms of risk-related decision-making: Insights from animal models.

    PubMed

    Orsini, Caitlin A; Moorman, David E; Young, Jared W; Setlow, Barry; Floresco, Stan B

    2015-11-01

    Over the past 20 years there has been a growing interest in the neural underpinnings of cost/benefit decision-making. Recent studies with animal models have made considerable advances in our understanding of how different prefrontal, striatal, limbic and monoaminergic circuits interact to promote efficient risk/reward decision-making, and how dysfunction in these circuits underlies aberrant decision-making observed in numerous psychiatric disorders. This review will highlight recent findings from studies exploring these questions using a variety of behavioral assays, as well as molecular, pharmacological, neurophysiological, and translational approaches. We begin with a discussion of how neural systems related to decision subcomponents may interact to generate more complex decisions involving risk and uncertainty. This is followed by an overview of interactions between prefrontal-amygdala-dopamine and habenular circuits in regulating choice between certain and uncertain rewards and how different modes of dopamine transmission may contribute to these processes. These data will be compared with results from other studies investigating the contribution of some of these systems to guiding decision-making related to rewards vs. punishment. Lastly, we provide a brief summary of impairments in risk-related decision-making associated with psychiatric disorders, highlighting recent translational studies in laboratory animals. PMID:26072028

  12. A Model of Supervisor Decision-Making in the Accommodation of Workers with Low Back Pain.

    PubMed

    Williams-Whitt, Kelly; Kristman, Vicki; Shaw, William S; Soklaridis, Sophie; Reguly, Paula

    2016-09-01

    Purpose To explore supervisors' perspectives and decision-making processes in the accommodation of back injured workers. Methods Twenty-three semi-structured, in-depth interviews were conducted with supervisors from eleven Canadian organizations about their role in providing job accommodations. Supervisors were identified through an on-line survey and interviews were recorded, transcribed and entered into NVivo software. The initial analyses identified common units of meaning, which were used to develop a coding guide. Interviews were coded, and a model of supervisor decision-making was developed based on the themes, categories and connecting ideas identified in the data. Results The decision-making model includes a process element that is described as iterative "trial and error" decision-making. Medical restrictions are compared to job demands, employee abilities and available alternatives. A feasible modification is identified through brainstorming and then implemented by the supervisor. Resources used for brainstorming include information, supervisor experience and autonomy, and organizational supports. The model also incorporates the experience of accommodation as a job demand that causes strain for the supervisor. Accommodation demands affect the supervisor's attitude, brainstorming and monitoring effort, and communication with returning employees. Resources and demands have a combined effect on accommodation decision complexity, which in turn affects the quality of the accommodation option selected. If the employee is unable to complete the tasks or is reinjured during the accommodation, the decision cycle repeats. More frequent iteration through the trial and error process reduces the likelihood of return to work success. Conclusion A series of propositions is developed to illustrate the relationships among categories in the model. The model and propositions show: (a) the iterative, problem solving nature of the RTW process; (b) decision resources necessary

  13. Modelling Vague Knowledge for Decision Support in Planning Archaeological Prospections

    NASA Astrophysics Data System (ADS)

    Boos, S.; Hornung, S.; Müller, H.

    2012-07-01

    Most archaeological predictive models lack significance because fuzziness of data and uncertainty in knowledge about human behaviour and natural processes are hardly ever considered. One possibility to cope with such uncertainties is utilization of probability based approaches like Bayes Theorem or Dempster-Shafer-Theory. We analyzed an area of 50 km2 in Rhineland Palatinate (Germany) near a Celtic oppidum by use of Dempster-Shafer's theory of evidence for predicting spatial probability distribution of archaeological sites. This technique incorporates uncertainty by assigning various weights of evidence to defined variables, in that way estimating the probability for supporting a specific hypothesis (in our case the hypothesis presence or absence of a site). Selection of variables for our model relied both on assumptions about settlement patterns and on statistically tested relationships between known archaeological sites and environmental factors. The modelling process was conducted in a Geographic Information System (GIS) by generating raster-based likelihood surfaces. The corresponding likelihood surfaces were aggregated to a final weight of evidence surface, which resulted in a likelihood value for every single cell of being a site or a non-site. Finally the result was tested against a database of known archaeological sites for evaluating the gain of the model. For the purpose of enhancing the gain of our model and sharpening our criteria we used a two-step approach to improve the modelling of former settlement strategies in our study area. Applying the developed model finally yielded a 100 percent success rate of known archaeological sites located in predicted high potential areas.

  14. Ecological models supporting environmental decision making: a strategy for the future

    USGS Publications Warehouse

    Schmolke, Amelie; Thorbek, Pernille; DeAngelis, Donald L.; Grimm, Volker

    2010-01-01

    Ecological models are important for environmental decision support because they allow the consequences of alternative policies and management scenarios to be explored. However, current modeling practice is unsatisfactory. A literature review shows that the elements of good modeling practice have long been identified but are widely ignored. The reasons for this might include lack of involvement of decision makers, lack of incentives for modelers to follow good practice, and the use of inconsistent terminologies. As a strategy for the future, we propose a standard format for documenting models and their analyses: transparent and comprehensive ecological modeling (TRACE) documentation. This standard format will disclose all parts of the modeling process to scrutiny and make modeling itself more efficient and coherent.

  15. Modeling the Occupational/Career Decision-Making Processes of Intellectually Gifted Adolescents: A Competing Models Strategy

    ERIC Educational Resources Information Center

    Jung, Jae Yup

    2014-01-01

    This study developed and empirically tested two related models of the occupational/career decision-making processes of gifted adolescents using a competing models strategy. The two models that guided the study, which acknowledged cultural orientations, social influences from the family, occupational/career values, and characteristics of…

  16. Computer-Aided Decisions in Human Services: Expert Systems and Multivariate Models.

    ERIC Educational Resources Information Center

    Sicoly, Fiore

    1989-01-01

    This comparison of two approaches to the development of computerized supports for decision making--expert systems and multivariate models--focuses on computerized systems that assist professionals with tasks related to diagnosis or classification in human services. Validation of both expert systems and statistical models is emphasized. (39…

  17. Decision Models for Admission into Teacher Preparation: An Application of Regression Analysis.

    ERIC Educational Resources Information Center

    Garcia, Ricardo A.; Denton, Jon J.

    This investigation explores the feasibility of constructing regression models for predicting teaching success and classroom behavior utilizing various measures of attitudes, personality, and psychological factors as predictors. The purpose of the study is to devise decision models that predict a candidate's success in student teaching as…

  18. Deciding about Decision Models of Remember and Know Judgments: A Reply to Murdock (2006)

    ERIC Educational Resources Information Center

    Macmillan, Neil A.; Rotello, Caren M.

    2006-01-01

    B. B. Murdock (2006; see record 2006-08257-009) has interpreted remember-know data within a decision space defined by item and associative information, the fundamental variables in his general recognition memory model TODAM (B. B. Murdock, 1982). He has related parameters of this extended model to stimulus characteristics for several classic…

  19. A Dual-Process Approach to Health Risk Decision Making: The Prototype Willingness Model

    ERIC Educational Resources Information Center

    Gerrard, Meg; Gibbons, Frederick X.; Houlihan, Amy E.; Stock, Michelle L.; Pomery, Elizabeth A.

    2008-01-01

    Although dual-process models in cognitive, personality, and social psychology have stimulated a large body of research about analytic and heuristic modes of decision making, these models have seldom been applied to the study of adolescent risk behaviors. In addition, the developmental course of these two kinds of information processing, and their…

  20. Curriculum Needs Assessment: A Model for Trade & Industrial Education Decision-Making.

    ERIC Educational Resources Information Center

    Wichowski, Chester

    A multi-dimensional needs assessment model has been developed to provide a research tool for the review of statewide curriculum needs in vocational education. The model provides for an integrated review of selected demographic, educational, and decision-making data to target vocational education program areas and occupational titles for additional…

  1. A Decision Model for Steady-State Choice in Concurrent Chains

    ERIC Educational Resources Information Center

    Christensen, Darren R.; Grace, Randolph C.

    2010-01-01

    Grace and McLean (2006) proposed a decision model for acquisition of choice in concurrent chains which assumes that after reinforcement in a terminal link, subjects make a discrimination whether the preceding reinforcer delay was short or long relative to a criterion. Their model was subsequently extended by Christensen and Grace (2008, 2009a,…

  2. A Model of Underlying Influences on Students' Decisions To Drop Out.

    ERIC Educational Resources Information Center

    McWilliams, Alfred E., Jr.; Everett, Patricia C.; Bass, Margaret L.

    2000-01-01

    Looked beyond socioeconomic indicators to seek underlying influences on rural high school seniors' dropout/completion decisions. Data came from school records and student surveys. Students were grouped by gender, and variables of Everett's (1996) model were analyzed. The predictor model for males had a 88.89 percent correct classification rate.…

  3. MODELS AS A COMPONENT OF DECISION-MAKING AT BROWNFIELDS SITES

    EPA Science Inventory

    Models have become an integral part of decision-making for many LUST and Brownfields sites if only because they form the basis of RCBA tiered assessments. Models, though, are based on a series of assumptions concerning how chemicals behave in the environment, how water flows thr...

  4. Book Review: Calibration and reliability in groundwater modeling: From uncertainty to decision making

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This is a review of the book “Calibration and Reliability in Groundwater Modeling: From Uncertainty to Decision Making” edited by M. F. P. Bierkens, J. C. Gehrels and K. Kovar. It is a collection of selected papers that dealt with advances in groundwater modeling, calibration techniques, and potenti...

  5. Decision Model of Flight Safety Based on Flight Event

    NASA Astrophysics Data System (ADS)

    Xiao-yu, Zhang; Jiu-sheng, Chen

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

  6. A conceptual and computational model of moral decision making in human and artificial agents.

    PubMed

    Wallach, Wendell; Franklin, Stan; Allen, Colin

    2010-07-01

    Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent's selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we

  7. An Intuitionistic Fuzzy Logic Models for Multicriteria Decision Making Under Uncertainty

    NASA Astrophysics Data System (ADS)

    Jana, Biswajit; Mohanty, Sachi Nandan

    2016-06-01

    The purpose of this paper is to enhance the applicability of the fuzzy sets for developing mathematical models for decision making under uncertainty, In general a decision making process consist of four stages, namely collection of information from various sources, compile the information, execute the information and finally take the decision/action. Only fuzzy sets theory is capable to quantifying the linguistic expression to mathematical form in complex situation. Intuitionistic fuzzy set (IFSs) which reflects the fact that the degree of non membership is not always equal to one minus degree of membership. There may be some degree of hesitation. Thus, there are some situations where IFS theory provides a more meaningful and applicable to cope with imprecise information present for solving multiple criteria decision making problem. This paper emphasis on IFSs, which is help for solving real world problem in uncertainty situation.

  8. Recasting Janis's Groupthink Model: The Key Role of Collective Efficacy in Decision Fiascoes.

    PubMed

    Whyte

    1998-02-01

    This paper advances an explanation for decision fiascoes that reflects recent theoretical trends and was developed in response to a growing body of research that has failed to substantiate the groupthink model (Janis, 1982). In this new framework, the lack of vigilance and preference for risk that characterizes groups contaminated by groupthink are attributed in large part to perceptions of collective efficacy that unduly exceed capability. High collective efficacy may also contribute to the negative framing of decisions and to certain administrative and structural organizational faults. In the making of critical decisions, these factors induce a preference for risk and a powerful concurrence seeking tendency that, facilitated by group polarization, crystallize around a decision option that is likely to fail. Implications for research and some evidence in support of this approach to the groupthink phenomenon are also discussed. Copyright 1998 Academic Press. PMID:9705802

  9. Organizational Models of Governance: Academic Deans' Decision Making Styles.

    ERIC Educational Resources Information Center

    McCarty, Donald J.; Reyes, Pedro

    1987-01-01

    This study examined the patterns of perceived management and leadership roles of academic deans as held by 55 departmental chairpersons at a major research institition. Four models of governance (organized anarchy, bureaucratic, collegial, and political) were presented for consideration. Results are discussed. (MT)

  10. Special Education Eligibility Decision Making in Response to Intervention Models

    ERIC Educational Resources Information Center

    Hoover, John J.

    2010-01-01

    The response to intervention model (RTI) represents a promising framework for the early identification and prevention of learning and behavior problems for students struggling in school. If RTI is properly implemented, it should reduce unnecessary referrals and placements into special education, and increase the accuracy of special education…

  11. A SPATIALLY REALISTIC MODEL FOR INFORMING FOREST MANAGEMENT DECISIONS

    EPA Science Inventory

    Spatially realistic population models (SRPMs) address a fundamental
    problem commonly confronted by wildlife managers - predicting the
    effects of landscape-scale habitat management on an animal population.
    SRPMs typically consist of three submodels: (1) a habitat submodel...

  12. Model-driven decision support for monitoring network design: methods and applications

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Harp, D. R.; Mishra, P. K.; Katzman, D.

    2012-12-01

    A crucial aspect of any decision-making process for environmental management of contaminated sites and protection of groundwater resources is the identification of scientifically defensible remediation scenarios. The selected scenarios are ranked based on both their protective and cost effectiveness. The decision-making process is facilitated by implementation of site-specific data- and model-driven analyses for decision support (DS) taking into account existing uncertainties to evaluate alternative characterization and remedial activities. However, due to lack of data and/or complex interdependent uncertainties (conceptual elements, model parameters, measurement/computational errors, etc.), the DS optimization problem is ill posed (non unique) and the model-prediction uncertainties are difficult to quantify. Recently, we have developed and implemented several novel theoretical approaches and computational algorithms for model-driven decision support. New and existing DS tools have been employed for model analyses of the fate and extent of a chromium plume in the regional aquifer at Sandia Canyon Site, LANL. Since 2007, we have performed three iterations of DS analyses implementing different models, decision-making tools, and data sets providing guidance on design of a subsurface monitoring network for (1) characterization of the flow and transports processes, and (2) protection of the water users. The monitoring network is augmented by new wells at locations where acquired new data can effectively reduce uncertainty in model predicted contaminant concentrations. A key component of the DS analyses is contaminant source identification. Due to data and conceptual uncertainties, subsurface processes controlling the contaminant arrival at the top of the regional aquifer are not well defined. Nevertheless, the model-based analyses of the existing data and conceptual knowledge, including respective uncertainties, provide constrained probabilistic estimates of the

  13. A decision model applied to alcohol effects on driver signal light behavior

    NASA Technical Reports Server (NTRS)

    Schwartz, S. H.; Allen, R. W.

    1978-01-01

    A decision model including perceptual noise or inconsistency is developed from expected value theory to explain driver stop and go decisions at signaled intersections. The model is applied to behavior in a car simulation and instrumented vehicle. Objective and subjective changes in driver decision making were measured with changes in blood alcohol concentration (BAC). Treatment levels averaged 0.00, 0.10 and 0.14 BAC for a total of 26 male subjects. Data were taken for drivers approaching signal lights at three timing configurations. The correlation between model predictions and behavior was highly significant. In contrast to previous research, analysis indicates that increased BAC results in increased perceptual inconsistency, which is the primary cause of increased risk taking at low probability of success signal lights.

  14. A model for amalgamation in group decision making

    NASA Technical Reports Server (NTRS)

    Cutello, Vincenzo; Montero, Javier

    1992-01-01

    In this paper we present a generalization of the model proposed by Montero, by allowing non-complete fuzzy binary relations for individuals. A degree of unsatisfaction can be defined in this case, suggesting that any democratic aggregation rule should take into account not only ethical conditions or some degree of rationality in the amalgamating procedure, but also a minimum support for the set of alternatives subject to the group analysis.

  15. Using Web Technology to Bridge the Gap Between Environmental Models and Decision Makers

    NASA Astrophysics Data System (ADS)

    Miller, D. A.; Bills, B.

    2011-12-01

    Expanding capabilities in web technology over the past decade have provided significant opportunities to create knowledge discovery tools and interfaces for a wide range of environmental modeling and management applications. The ubiquitous nature of the desktop web browser provides a potential solution to the gulf that currently exists between environmental modelers and geospatial technology experts on one side and environmental managers and decision makers on the other. By placing a map/model interface within the browser, and enabling this interface with highly-functional interactive capability focused on a specific set of management and decision needs, we are able to bridge the gap between the scientist and the decision maker. We have developed numerous web-based applications for bridging the model/decision maker gap using an evolving paradigm focused on highly interactive, easy-to-use interfaces created within the web browser. Based initially in FLASH and more recently in FLEX, these interfaces use web map server and object-relational database technology to create dynamic systems that can be used to facilitate query, exploration, and scenario analysis based on sophisticated underlying physical and biological processes models. Our presentation will focus on the growing suite of applications that we have developed in the past decade with a focus on the underlying principles and continuously evolving paradigm that underlie our approach to creating these decision environments. Examples include near-real time decision support tools in agriculture and a very recently developed and highly complex, agent-based model for the management of Interior Least Tern habitat on Southern Great Plains rivers.

  16. Effects of Practice on Task Architecture: Combined Evidence from Interference Experiments and Random-Walk Models of Decision Making

    ERIC Educational Resources Information Center

    Kamienkowski, Juan E.; Pashler, Harold; Dehaene, Stanislas; Sigman, Mariano

    2011-01-01

    Does extensive practice reduce or eliminate central interference in dual-task processing? We explored the reorganization of task architecture with practice by combining interference analysis (delays in dual-task experiment) and random-walk models of decision making (measuring the decision and non-decision contributions to RT). The main delay…

  17. A human performance modelling approach to intelligent decision support systems

    NASA Technical Reports Server (NTRS)

    Mccoy, Michael S.; Boys, Randy M.

    1987-01-01

    Manned space operations require that the many automated subsystems of a space platform be controllable by a limited number of personnel. To minimize the interaction required of these operators, artificial intelligence techniques may be applied to embed a human performance model within the automated, or semi-automated, systems, thereby allowing the derivation of operator intent. A similar application has previously been proposed in the domain of fighter piloting, where the demand for pilot intent derivation is primarily a function of limited time and high workload rather than limited operators. The derivation and propagation of pilot intent is presented as it might be applied to some programs.

  18. An agent-based model of group decision making in baboons.

    PubMed

    Sellers, W I; Hill, R A; Logan, B S

    2007-09-29

    We present an agent-based model of the key activities of a troop of chacma baboons (Papio hamadryas ursinus) based on the data collected at De Hoop Nature Reserve in South Africa. We analyse the predictions of the model in terms of how well it is able to duplicate the observed activity patterns of the animals and the relationship between the parameters that control the agent's decision procedure and the model's predictions. At the current stage of model development, we are able to show that across a wide range of decision parameter values, the baboons are able to achieve their energetic and social time requirements. The simulation results also show that decisions concerning movement (group action selection) have the greatest influence on the outcomes. Those cases where the model's predictions fail to agree with the observed activity patterns have highlighted key elements that were missing from the field data, and that would need to be collected in subsequent fieldwork. Based on our experience, we believe group decision making is a fertile field for future research, and agent-based modelling offers considerable scope for understanding group action selection. PMID:17428770

  19. 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.

  20. Tutorial in medical decision modeling incorporating waiting lines and queues using discrete event simulation.

    PubMed

    Jahn, Beate; Theurl, Engelbert; Siebert, Uwe; Pfeiffer, Karl-Peter

    2010-01-01

    In most decision-analytic models in health care, it is assumed that there is treatment without delay and availability of all required resources. Therefore, waiting times caused by limited resources and their impact on treatment effects and costs often remain unconsidered. Queuing theory enables mathematical analysis and the derivation of several performance measures of queuing systems. Nevertheless, an analytical approach with closed formulas is not always possible. Therefore, simulation techniques are used to evaluate systems that include queuing or waiting, for example, discrete event simulation. To include queuing in decision-analytic models requires a basic knowledge of queuing theory and of the underlying interrelationships. This tutorial introduces queuing theory. Analysts and decision-makers get an understanding of queue characteristics, modeling features, and its strength. Conceptual issues are covered, but the emphasis is on practical issues like modeling the arrival of patients. The treatment of coronary artery disease with percutaneous coronary intervention including stent placement serves as an illustrative queuing example. Discrete event simulation is applied to explicitly model resource capacities, to incorporate waiting lines and queues in the decision-analytic modeling example. PMID:20345550

  1. Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs

    NASA Astrophysics Data System (ADS)

    Mohleji, Nandita

    Convective weather and other constraints create uncertainty in air transportation, leading to costly delays. A Ground Delay Program (GDP) is a strategy to mitigate these effects. Systematic decision support can increase GDP efficacy, reduce delays, and minimize direct operating costs. In this study, a decision analysis (DA) model is constructed by combining a decision tree and Bayesian belief network. Through a study of three New York region airports, the DA model demonstrates that larger GDP scopes that include more flights in the program, along with longer lead times that provide stakeholders greater notice of a pending program, trigger the fewest average arrival delays. These findings are demonstrated to result in a savings of up to $1,850 per flight. Furthermore, when convective weather is predicted, forecast weather confidences remain the same level or greater at least 70% of the time, supporting more strategic decision making. The DA model thus enables quantification of uncertainties and insights on causal relationships, providing support for future GDP decisions.

  2. Geothermal-district-heating assessment model for decision making

    SciTech Connect

    Reisman, A.

    1981-11-01

    A methodology developed to assess the economic feasibility of district heating for any community in the United States is described. The overall philosophy which has guided its development is the conviction that district heating must be examined on a site-by-site basis. To support this approach, a set of extensive, in-house supporting data bases has been created and useful external data bases with national coverage have been identified. These data bases provide information at a sufficient level of detail to permit a first-cut examination of the district heating potential of a community without requiring outside data collection (allowing a substantial cost and time savings). The results of this blind look at a community permit a rapid, yet adequate estimate of district heating potential, costs, and energy savings. The data utilized in the initial examination can be supplemented or replaced by more detailed information obtained from on-site data collection, if the first results are promising. The fact that the data and methodology are computerized allows many locations within the community, alternate heat sources, ownership options, pipe technologies, etc. to be examined in a short period of time. The structure of the District Heating Model (DHM) (the methodology in computerized form) is described followed by a discussion of the application of the model to Provo, UT.

  3. Modelling the participation decision and duration of sporting activity in Scotland

    PubMed Central

    Eberth, Barbara; Smith, Murray D.

    2010-01-01

    Motivating individuals to actively engage in physical activity due to its beneficial health effects has been an integral part of Scotland's health policy agenda. The current Scottish guidelines recommend individuals participate in physical activity of moderate vigour for 30 min at least five times per week. For an individual contemplating the recommendation, decisions have to be made in regard of participation, intensity, duration and multiplicity. For the policy maker, understanding the determinants of each decision will assist in designing an intervention to effect the recommended policy. With secondary data sourced from the 2003 Scottish Health Survey (SHeS) we statistically model the combined decisions process, employing a copula approach to model specification. In taking this approach the model flexibly accounts for any statistical associations that may exist between the component decisions. Thus, we model the endogenous relationship between the decision of individuals to participate in sporting activities and, amongst those who participate, the duration of time spent undertaking their chosen activities. The main focus is to establish whether dependence exists between the two random variables assuming the vigour with which sporting activity is performed to be independent of the participation and duration decision. We allow for a variety of controls including demographic factors such as age and gender, economic factors such as income and educational attainment, lifestyle factors such as smoking, alcohol consumption, healthy eating and medical history. We use the model to compare the effect of interventions designed to increase the vigour with which individuals undertake their sport, relating it to obesity as a health outcome. PMID:20640033

  4. Shared Decision-Making Models Acknowledging an Interprofessional Approach: A Theory Analysis to Inform Nursing Practice.

    PubMed

    Lewis, Krystina B; Stacey, Dawn; Squires, Janet E; Carroll, Sandra

    2016-01-01

    Patient engagement in collaboration with health professionals is essential to deliver quality health care. A shared decision-making (SDM) approach requires that patients are involved in decisions regarding their health. SDM is expanding from the patient-physician dyad to incorporate an interprofessional perspective. Conceptual models can be used to better understand theoretical underpinnings for application in clinical practice. The aim of this article was to conduct a theory analysis of conceptual models using an interprofessional approach to SDM and discuss each model's relevance to nursing practice. Walker and Avant's theory analysis approach was used. Three conceptual models were eligible. For all models, the decision-making process was considered iterative. The development process was described for 1 model. All models were logical, parsimonious, and generalizable. One was supported by empirical testing. No model described how partnerships are enacted to achieve interprofessional SDM. Also, there was limited articulation as to how nurses' roles and contributions differ from other team members. This theory analysis highlights the need for a model that explains how partnerships among interprofessional team members are enacted to better understand the operationalization of interprofessional SDM. Implications for nursing practice at all system levels are offered and supported by the 3 models. PMID:27024998

  5. A conceptual model of emergency physician decision making for head computed tomography in mild head injury.

    PubMed

    Probst, Marc A; Kanzaria, Hemal K; Schriger, David L

    2014-06-01

    The use of computed tomographic scanning in blunt head trauma has increased dramatically in recent years without an accompanying rise in the prevalence of injury or hospital admission for serious conditions. Because computed tomography is neither harmless nor inexpensive, researchers have attempted to optimize utilization, largely through research that describes which clinical variables predict intracranial injury, and use this information to develop clinical decision instruments. Although such techniques may be useful when the benefits and harms of each strategy (neuroimaging vs observation) are quantifiable and amenable to comparison, the exact magnitude of these benefits and harms remains unknown in this clinical scenario. We believe that most clinical decision instrument development efforts are misguided insofar as they ignore critical, nonclinical factors influencing the decision to image. In this article, we propose a conceptual model to illustrate how clinical and nonclinical factors influence emergency physicians making this decision. We posit that elements unrelated to standard clinical factors, such as personality of the physician, fear of litigation and of missed diagnoses, patient expectations, and compensation method, may have equal or greater impact on actual decision making than traditional clinical factors. We believe that 3 particular factors deserve special consideration for further research: fear of error/malpractice, financial incentives, and patient engagement. Acknowledgement and study of these factors will be essential if we are to understand how emergency physicians truly make these decisions and how test-ordering behavior can be modified. PMID:24560384

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

    PubMed

    Joshi, Prashant

    2007-04-01

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

  7. HIV Treatment as Prevention: Models, Data, and Questions—Towards Evidence-Based Decision-Making

    PubMed Central

    2012-01-01

    Antiretroviral therapy (ART) for those infected with HIV can prevent onward transmission of infection, but biological efficacy alone is not enough to guide policy decisions about the role of ART in reducing HIV incidence. Epidemiology, economics, demography, statistics, biology, and mathematical modelling will be central in framing key decisions in the optimal use of ART. PLoS Medicine, with the HIV Modelling Consortium, has commissioned a set of articles that examine different aspects of HIV treatment as prevention with a forward-looking research agenda. Interlocking themes across these articles are discussed in this introduction. We hope that this article, and others in the collection, will provide a foundation upon which greater collaborations between disciplines will be formed, and will afford deeper insights into the key factors involved, to help strengthen the support for evidence-based decision-making in HIV prevention. PMID:22802739

  8. Simulation and modeling efforts to support decision making in healthcare supply chain management.

    PubMed

    AbuKhousa, Eman; Al-Jaroodi, Jameela; Lazarova-Molnar, Sanja; Mohamed, Nader

    2014-01-01

    Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges. PMID:24683333

  9. Simulation and Modeling Efforts to Support Decision Making in Healthcare Supply Chain Management

    PubMed Central

    Lazarova-Molnar, Sanja

    2014-01-01

    Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges. PMID:24683333

  10. A mathematical model for a T cell fate decision algorithm during immune response.

    PubMed

    Arias, Clemente F; Herrero, Miguel A; Acosta, Francisco J; Fernandez-Arias, Cristina

    2014-05-21

    We formulate and analyze an algorithm of cell fate decision that describes the way in which division vs. apoptosis choices are made by individual T cells during an infection. Such model involves a minimal number of known biochemical mechanisms: it basically relies on the interplay between cell division and cell death inhibitors on one hand, and membrane receptors on the other. In spite of its simplicity, the proposed decision algorithm is able to account for some significant facts in immune response. At the individual level, the existence of T cells that continue to replicate in the absence of antigen and the possible occurrence of T cell apoptosis in the presence of antigen are predicted by the model. Moreover, the latter is shown to yield an emergent collective behavior, the observed delay in clonal contraction with respect to the end of antigen stimulation, which is shown to arise just from individual T cell decisions made according to the proposed mechanism. PMID:24512913

  11. Toward an operational model of decision making, emotional regulation, and mental health impact.

    PubMed

    Collura, Thomas Francis; Zalaquett, Ronald P; Bonnstetter, Carlos Joyce; Chatters, Seria J

    2014-01-01

    Current brain research increasingly reveals the underlying mechanisms and processes of human behavior, cognition, and emotion. In addition to being of interest to a wide range of scientists, educators, and professionals, as well as laypeople, brain-based models are of particular value in a clinical setting. Psychiatrists, psychologists, counselors, and other mental health professionals are in need of operational models that integrate recent findings in the physical, cognitive, and emotional domains, and offer a common language for interdisciplinary understanding and communication. Based on individual traits, predispositions, and responses to stimuli, we can begin to identify emotional and behavioral pathways and mental processing patterns. The purpose of this article is to present a brain-path activation model to understand individual differences in decision making and psychopathology. The first section discusses the role of frontal lobe electroencephalography (EEG) asymmetry, summarizes state- and trait-based models of decision making, and provides a more complex analysis that supplements the traditional simple left-right brain model. Key components of the new model are the introduction of right hemisphere parallel and left hemisphere serial scanning in rendering decisions, and the proposition of pathways that incorporate both past experiences as well as future implications into the decision process. Main attributes of each decision-making mechanism are provided. The second section applies the model within the realm of clinical mental health as a tool to understand specific human behavior and pathology. Applications include general and chronic anxiety, depression, paranoia, risk taking, and the pathways employed when well-functioning operational integration is observed. Finally, specific applications such as meditation and mindfulness are offered to facilitate positive functioning. PMID:25590293

  12. Timed colored Petri nets and fuzzy-set-based model for decision making

    NASA Astrophysics Data System (ADS)

    Scopel Simoes, Marcos A.; Barretto, Marcos R. P.

    2000-10-01

    This work proposes the use of Timed Colored Petri nets as a formal base to a decision making tool for applications in industrial productive processes planning and programming. The Timed Colored Petri net is responsible for the transition of states in the decision process, establishing in time the use of resources and of heuristics that correspond to the more important managerial and operational actions for the planning activities and programming of the productive processes of an industrial plant. To negotiate with the uncertainties involved in a decision process, that in general takes care of the responsible specialist's knowledge for the routines involved in the productive system, we make use of the theory of fuzzy sets to suggest decisions logically consistent that obtain a viable solution just leading the viable states of the decision tree, that, in this case, is confused with the occurrence graph of the Petri net. As application example to the proposed model, we used a production system characterized by a port plant, whose model and simulation results are described at the end of this work.

  13. Decision models in the evaluation of psychotropic drugs : useful tool or useless toy?

    PubMed

    Barbui, Corrado; Lintas, Camilla

    2006-09-01

    A current contribution in the European Journal of Health Economics employs a decision model to compare health care costs of olanzapine and risperidone treatment for schizophrenia. The model suggests that a treatment strategy of first-line olanzapine is cost-saving over a 1-year period, with additional clinical benefits in the form of avoided relapses in the long-term. From a clinical perspective this finding is indubitably relevant, but can physicians and policy makers believe it? The study is presented in a balanced way, assumptions are based on data extracted from clinical trials published in major psychiatric journals, and the theoretical underpinnings of the model are reasonable. Despite these positive aspects, we believe that the methodology used in this study-the decision model approach-is an unsuitable and potentially misleading tool for evaluating psychotropic drugs. In this commentary, taking the olanzapine vs. risperidone model as an example, arguments are provided to support this statement. PMID:16862446

  14. A Descriptive Decision Process Model for Hierarchical Management of Interconnected Reservoir Systems

    NASA Astrophysics Data System (ADS)

    Adigüzel, R. Ä.°Lker; CoşKunoǧLu, Osman

    1984-07-01

    A significant limitation of prescriptive optimization models is that their formulation is disassociated from the behavioral and organizational attributes of the problem addressed. In an attempt to alleviate this limitation a decision process model is formulated directly within a framework of decision agents involved in integrated long- and short-term planning and management of multipurpose and multireservoir system operations. The resulting model is ierarchical, multilevel, multilayer, and decentralized. As such it is descriptive of a reservoir system managed and operated by geographically separated multiple agents with different authorities and responsibilities. Robustness and performance of the model is investigated by using the Shasta-Trinity system of California as an example. Results are encouraging for the descriptive as well as prescriptive relevance of the model.

  15. On diffusion processes with variable drift rates as models for decision making during learning

    NASA Astrophysics Data System (ADS)

    Eckhoff, P.; Holmes, P.; Law, C.; Connolly, P. M.; Gold, J. I.

    2008-01-01

    We investigate Ornstein Uhlenbeck and diffusion processes with variable drift rates as models of evidence accumulation in a visual discrimination task. We derive power-law and exponential drift-rate models and characterize how parameters of these models affect the psychometric function describing performance accuracy as a function of stimulus strength and viewing time. We fit the models to psychophysical data from monkeys learning the task to identify parameters that best capture performance as it improves with training. The most informative parameter was the overall drift rate describing the signal-to-noise ratio of the sensory evidence used to form the decision, which increased steadily with training. In contrast, secondary parameters describing the time course of the drift during motion viewing did not exhibit steady trends. The results indicate that relatively simple versions of the diffusion model can fit behavior over the course of training, thereby giving a quantitative account of learning effects on the underlying decision process.

  16. Paediatric models in motion: requirements for model-based decision support at the bedside.

    PubMed

    Barrett, Jeffrey S

    2015-01-01

    Optimal paediatric pharmacotherapy is reliant on a detailed understanding of the individual patient including their developmental status and disease state as well as the pharmaceutical agents he/she is receiving for treatment or management of side effects. Our appreciation for size and maturation effects on the pharmacokinetic/pharmacodynamic (PK/PD) phenomenon has improved to the point that we can develop predictive models that permit us to individualize therapy, especially in the situation where we are monitoring drug effects or therapeutic concentrations. The growth of efforts to guide paediatric pharmacotherapy via model-based decision support necessitates a coordinated and systematic approach to ensuring reliable and robust output to caregivers that represents the current standard of care and adheres to governance imposed by the host institution or coalition responsible. Model-based systems which guide caregivers on dosing paediatric patients in a more comprehensive manner are in development at several institutions. Care must be taken that these systems provide robust guidance with the current best practice. These systems must evolve as new information becomes available and ultimately are best constructed from diverse data representing global input on demographics, ethnic / racial diversity, diet and other lifestyle factors. Multidisciplinary involvement at the project team level is key to the ultimate clinical valuation. Likewise, early engagement of clinical champions is also critical for the success of model-based tools. Adherence to regulatory requirements as well as best practices with respect to software development and testing are essential if these tools are to be used as part of the routine standard of care. PMID:24251868

  17. Paediatric models in motion: requirements for model-based decision support at the bedside

    PubMed Central

    Barrett, Jeffrey S

    2015-01-01

    Optimal paediatric pharmacotherapy is reliant on a detailed understanding of the individual patient including their developmental status and disease state as well as the pharmaceutical agents he/she is receiving for treatment or management of side effects. Our appreciation for size and maturation effects on the pharmacokinetic/pharmacodynamic (PK/PD) phenomenon has improved to the point that we can develop predictive models that permit us to individualize therapy, especially in the situation where we are monitoring drug effects or therapeutic concentrations. The growth of efforts to guide paediatric pharmacotherapy via model-based decision support necessitates a coordinated and systematic approach to ensuring reliable and robust output to caregivers that represents the current standard of care and adheres to governance imposed by the host institution or coalition responsible. Model-based systems which guide caregivers on dosing paediatric patients in a more comprehensive manner are in development at several institutions. Care must be taken that these systems provide robust guidance with the current best practice. These systems must evolve as new information becomes available and ultimately are best constructed from diverse data representing global input on demographics, ethnic / racial diversity, diet and other lifestyle factors. Multidisciplinary involvement at the project team level is key to the ultimate clinical valuation. Likewise, early engagement of clinical champions is also critical for the success of model-based tools. Adherence to regulatory requirements as well as best practices with respect to software development and testing are essential if these tools are to be used as part of the routine standard of care. PMID:24251868

  18. Decision support model for evaluating biofuel development along the U.S.-Mexico border.

    SciTech Connect

    Tidwell, Vincent Carroll; Correa, Alberto; Maxwell, Paul; Malczynski, Leonard A.

    2010-04-01

    Recently, Sandia National Laboratories and General Motors cooperated on the development of the Biofuels Deployment Model (BDM) to assess the feasibility, implications, limitations, and enablers of producing 90 billion gallons of ethanol per year by 2030. Leveraging the past investment, a decision support model based on the BDM is being developed to assist investors, entrepreneurs, and decision makers in evaluating the costs and benefits associated with biofuels development in the U.S.-Mexico border region. Specifically, the model is designed to assist investors and entrepreneurs in assessing the risks and opportunities associated with alternative biofuels development strategies along the U.S.-Mexico border, as well as, assist local and regional decision makers in understanding the tradeoffs such development poses to their communities. The decision support model is developed in a system dynamics framework utilizing a modular architecture that integrates the key systems of feedstock production, transportation, and conversion. The model adopts a 30-year planning horizon, operating on an annual time step. Spatially the model is disaggregated at the county level on the U.S. side of the border and at the municipos level on the Mexican side. The model extent includes Luna, Hildalgo, Dona Anna, and Otero counties in New Mexico, El Paso and Hudspeth counties in Texas, and the four munipos along the U.S. border in Chihuahua. The model considers a variety of feedstocks; specifically, algae, gitropha, castor oil, and agricultural waste products from chili and pecans - identifying suitable lands for these feedstocks, possible yields, and required water use. The model also evaluates the carbon balance for each crop and provides insight into production costs including labor demands. Finally, the model is fitted with an interactive user interface comprised of a variety of controls (e.g., slider bars, radio buttons), descriptive text, and output graphics allowing stakeholders to

  19. Occupational Decision-Related Processes for Amotivated Adolescents: Confirmation of a Model

    ERIC Educational Resources Information Center

    Jung, Jae Yup; McCormick, John

    2011-01-01

    This study developed and (statistically) confirmed a new model of the occupational decision-related processes of adolescents, in terms of the extent to which they may be amotivated about choosing a future occupation. A theoretical framework guided the study. A questionnaire that had previously been administered to an Australian adolescent sample…

  20. The Integrated Medical Model - A Risk Assessment and Decision Support Tool for Human Space Flight Missions

    NASA Technical Reports Server (NTRS)

    Kerstman, Eric; Minard, Charles G.; Saile, Lynn; FreiredeCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

    2010-01-01

    The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission planners and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight.

  1. Reason, Intuition, and Social Justice: Elaborating on Parson's Career Decision-Making Model.

    ERIC Educational Resources Information Center

    Hartung, Paul J.; Blustein, David L.

    2002-01-01

    Nearly a century ago, Frank Parsons established the Vocation Bureau in Boston and spawned the development of the counseling profession. Elaborating on Parsons's socially responsible vision for counseling, the authors examine contemporary perspectives on career decision making that include both rational and alternative models and propose that these…

  2. OASIS: A GEOGRAPHICAL DECISION SUPPORT SYSTEM FOR GROUND-WATER CONTAMINANT MODELING

    EPA Science Inventory

    Three new software technologies were applied to develop an efficient and easy to use decision support system for ground-water contaminant modeling. Graphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces...

  3. The Cultural Mind: Environmental Decision Making and Cultural Modeling within and across Populations

    ERIC Educational Resources Information Center

    Atran, Scott; Medin, Douglas L.; Ross, Norbert O.

    2005-01-01

    This article describes cross-cultural research on the relation between how people conceptualize nature and how they act in it. Mental models of nature differ dramatically among populations living in the same area and engaged in similar activities. This has novel implications for environmental decision making and management, including commons…

  4. Conceptualizing the Identification of Learning Disabilities: A Decision-Making Model.

    ERIC Educational Resources Information Center

    Polloway, Edward A.; Patton, James R.

    1988-01-01

    A model for conceptualizing the identification process based on a broad view of the nature of learning disabilities is presented. Four decision-making points in the identification process are highlighted with emphasis on the role of team members at each of the four points. (Author/DB)

  5. FORBEEF: A Forage-Livestock System Computer Model Used as a Teaching Aid for Decision Making.

    ERIC Educational Resources Information Center

    Stringer, W. C.; And Others

    1987-01-01

    Describes the development of a computer simulation model of forage-beef production systems, which is intended to incorporate soil, forage, and animal decisions into an enterprise scenario. Produces a summary of forage production and livestock needs. Cites positive assessment of the program's value by participants in inservice training workshops.…

  6. Felony Investigation Decision Model: An Analysis of Investigative Elements of Information.

    ERIC Educational Resources Information Center

    Greenberg, Bernard; And Others

    The primary goal of research performed in Oakland, California was decision models for four felony classes--robbery, assault, with a deadly weapon, car theft, and rape--to determine cases having sufficient probability of clearance to warrant intensive investigation. A secondary objective, determination of personal-appearance and crime-event…

  7. Modeling Comparative Daily Enrollment Indicators To Aid Intelligent College Decisions. AIR 2001 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Lajubutu, Oyebanjo A.

    This paper shows how three critical enrollment indicators drawn from a relationship database were used to guide planning and management decisions. The paper discusses the guidelines for the development of the model, attributes needed, variables to be calculated, and other issues that may improve the effectiveness and efficiency of daily enrollment…

  8. The Use of Touch in Counseling: An Ethical Decision-Making Model

    ERIC Educational Resources Information Center

    Calmes, Stephanie A.; Piazza, Nick J.; Laux, John M.

    2013-01-01

    Although some counselors have advocated for the limited use of touch in counseling, others have argued that touch has no place within the counseling relationship. Despite the controversy, the use of touch has been shown to have a number of therapeutic benefits; however, there are few ethical decision-making models that are appropriate for…

  9. Developing a Decision Model of Sustainable Product Design and Development from Product Servicizing in Taiwan

    ERIC Educational Resources Information Center

    Huang, Yu-Chen; Tu, Jui-Che; Hung, So-Jeng

    2016-01-01

    In response to the global trend of low carbon and the concept of sustainable development, enterprises need to develop R&D for the manufacturing of energy-saving and sustainable products and low carbon products. Therefore, the purpose of this study was to construct a decision model for sustainable product design and development from product…

  10. Gaps of Decision Support Models for Pipeline Renewal and Recommendations for Improvement

    EPA Science Inventory

    In terms of the development of software for decision support for pipeline renewal, more attention to date has been paid to the development of asset management models that help an owner decide on which portions of a system to prioritize needed actions. There has been much less w...

  11. GAPS OF DECISION SUPPORT MODELS FOR PIPELINE RENEWAL AND RECOMMENDATIONS FOR IMPROVEMENT (SLIDE)

    EPA Science Inventory

    In terms of the development of software for decision support for pipeline renewal, more attention to date has been paid to the development of asset management models that help an owner decide on which portions of a system to prioritize needed actions. There has been much less wor...

  12. Modeling the College Application Decision Process in a Land-Grant Institution.

    ERIC Educational Resources Information Center

    DesJardins, Stephen L.; And Others

    This study used a logistic probability model to investigate the effects of variables relating student characteristics and institutional factors on the decision to apply to a large land-grant research university. The study used the entire data set from American College Testing (ACT) program test-takers in the fall of 1995 and institutional data on…

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

    ERIC Educational Resources Information Center

    Bauer, Scott C.; Bogotch, Ira E.

    2006-01-01

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

  14. Children Home Alone Unsupervised: Modeling Parental Decisions and Associated Factors in Botswana, Mexico, and Vietnam

    ERIC Educational Resources Information Center

    Ruiz-Casares, Monica; Heymann, Jody

    2009-01-01

    Objective: This paper examines different child care arrangements utilized by working families in countries undergoing major socio-economic transitions, with a focus on modeling parental decisions to leave children home alone. Method: The study interviewed 537 working caregivers attending government health clinics in Botswana, Mexico, and Vietnam.…

  15. Citizens' Perceptions of Flood Hazard Adjustments: An Application of the Protective Action Decision Model

    ERIC Educational Resources Information Center

    Terpstra, Teun; Lindell, Michael K.

    2013-01-01

    Although research indicates that adoption of flood preparations among Europeans is low, only a few studies have attempted to explain citizens' preparedness behavior. This article applies the Protective Action Decision Model (PADM) to explain flood preparedness intentions in the Netherlands. Survey data ("N" = 1,115) showed that…

  16. The Success of Linear Bootstrapping Models: Decision Domain-, Expertise-, and Criterion-Specific Meta-Analysis

    PubMed Central

    Kaufmann, Esther; Wittmann, Werner W.

    2016-01-01

    The success of bootstrapping or replacing a human judge with a model (e.g., an equation) has been demonstrated in Paul Meehl’s (1954) seminal work and bolstered by the results of several meta-analyses. To date, however, analyses considering different types of meta-analyses as well as the potential dependence of bootstrapping success on the decision domain, the level of expertise of the human judge, and the criterion for what constitutes an accurate decision have been missing from the literature. In this study, we addressed these research gaps by conducting a meta-analysis of lens model studies. We compared the results of a traditional (bare-bones) meta-analysis with findings of a meta-analysis of the success of bootstrap models corrected for various methodological artifacts. In line with previous studies, we found that bootstrapping was more successful than human judgment. Furthermore, bootstrapping was more successful in studies with an objective decision criterion than in studies with subjective or test score criteria. We did not find clear evidence that the success of bootstrapping depended on the decision domain (e.g., education or medicine) or on the judge’s level of expertise (novice or expert). Correction of methodological artifacts increased the estimated success of bootstrapping, suggesting that previous analyses without artifact correction (i.e., traditional meta-analyses) may have underestimated the value of bootstrapping models. PMID:27327085

  17. Problem-Solving Model for Decision Making with High-Incidence Disabilities: The Minneapolis Experience.

    ERIC Educational Resources Information Center

    Marston, Doug; Muyskens, Paul; Lau, Matthew; Canter, Andrea

    2003-01-01

    This article describes the problem-solving model (PSM) used in the Minneapolis Public Schools to guide decisions regarding intervention in general education, special education referral, and evaluation for special education eligibility for high-incidence disabilities. Program evaluation indicates students received special education services earlier…

  18. The Development of Individualised Educational Programmes Using a Decision-Making Model.

    ERIC Educational Resources Information Center

    Thomson, Kenneth; Bachor, Dan; Thomson, George

    2002-01-01

    A case study investigated the use of a decision-making model, characterized by partnerships between professionals and learners, in the development of Individualized Education Programs (IEP) for students with learning difficulties in Scotland. The student (age 13) and the teachers agreed that the development of an IEP collectively had been useful.…

  19. A cortical network model of cognitive and emotional influences in human decision making.

    PubMed

    Nazir, Azadeh Hassannejad; Liljenström, Hans

    2015-10-01

    Decision making (DM)(2) is a complex process that appears to involve several brain structures. In particular, amygdala, orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) seem to be essential in human decision making, where both emotional and cognitive aspects are taken into account. In this paper, we present a computational network model representing the neural information processing of DM, from perception to behavior. We model the population dynamics of the three neural structures (amygdala, OFC and LPFC), as well as their interaction. In our model, the neurodynamic activity of amygdala and OFC represents the neural correlates of secondary emotion, while the activity of certain neural populations in OFC alone represents the outcome expectancy of different options. The cognitive/rational aspect of DM is associated with LPFC. Our model is intended to give insights on the emotional and cognitive processes involved in DM under various internal and external contexts. Different options for actions are represented by the oscillatory activity of cell assemblies, which may change due to experience and learning. Knowledge and experience of the outcome of our decisions and actions can eventually result in changes in our neural structures, attitudes and behaviors. Simulation results may have implications for how we make decisions for our individual actions, as well as for societal choices, where we take examples from transport and its impact on CO2 emissions and climate change. PMID:26184761

  20. Commonalities between Perception and Practice in Models of School Decision-Making in Secondary Schools.

    ERIC Educational Resources Information Center

    Brown, Marie; Boyle, Bill; Boyle, Trudy

    1999-01-01

    Examines participation issues of (British) department heads in whole-school decision-making processes to determine whether such participation represents true empowerment. Three models emerged, with varied results. Collegiality offers many persuasive benefits but is difficult to attain. Hierarchical and horizontal structures' effectiveness needs…

  1. The Pre-Adult Health Decision-Making Model: Linking Decision-Making Directedness/Orientation to Adolescent Health-Related Attitudes and Behaviors.

    ERIC Educational Resources Information Center

    Langer, Lilly M.; Warheit, George J.

    1992-01-01

    Presents model for adolescent health behavior, Pre-Adult Health Decision-Making Model, which takes into account differential information processing from peers, parents, or through critical or reflexive self-analysis. Reviews psychological and sociological literature on adolescent development, adolescent health behaviors, and Acquired Immune…

  2. How can models better aid the decision processes for the management of water resources?

    NASA Astrophysics Data System (ADS)

    Brugnach, M.; Pahl-Wostl, C.

    2007-12-01

    Despite the long history of development and use of models in policy making, there is still a poor integration between modeling and the decision process. This is influenced by several factors, such as a lack of understanding of models from policy makers, limitations in the applicability and use of models, modeller's behaviour, and a lack of stakeholder involvement in the whole modelling process. But, most relevant of all, is the fact that models are perceived as non reliable tools for policy making, due to the uncertainty associated with them and the lack of confidence this uncertainty generates. Commonly, in fields like natural resource management, and in particular water management, models are build to predict, in space or time, the state of the system to be managed (e.g. real time flood forecasting). These models are then used by policy makers as a surrogate of a real system to inform their decisions. In this view, the efficacy of a model depends on how well it can approximate reality and how much confidence policy makers can have on model's results. However, even though predictive models can be used to convey scientific argumentation that can aid decision making, these models fall short in supporting the processes of negotiation, learning, and communication, which constitute the basis for policy making. In this presentation we explore and discuss the relationship between models used in water resource management and policy making: how models can be used and how uncertainty should be treated depending on the purpose models are supposed to serve. We identify four major modeling purposes that are important for understanding and managing complex environmental systems: prediction, exploratory analysis, communication and learning, and investigate the implications of the different purposes in dealing with uncertainty. In predictive models, the presence of uncertainty is understood as a critical constraint for decision making, and as such it ought to be eliminated or

  3. Spatial modelling and the prediction of Loa loa risk: decision making under uncertainty.

    PubMed

    Diggle, P J; Thomson, M C; Christensen, O F; Rowlingson, B; Obsomer, V; Gardon, J; Wanji, S; Takougang, I; Enyong, P; Kamgno, J; Remme, J H; Boussinesq, M; Molyneux, D H

    2007-09-01

    Health decision-makers working in Africa often need to act for millions of people over large geographical areas on little and uncertain information. Spatial statistical modelling and Bayesian inference have now been used to quantify the uncertainty in the predictions of a regional, environmental risk map for Loa loa (a map that is currently being used as an essential decision tool by the African Programme for Onchocerciasis Control). The methodology allows the expression of the probability that, given the data, a particular location does or does not exceed a predefined high-risk threshold for which a change in strategy for the delivery of the antihelmintic ivermectin is required. PMID:17716433

  4. A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

    PubMed

    Clark, Renee M; Besterfield-Sacre, Mary E

    2009-03-01

    We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk. PMID:19087232

  5. Integrating Client and Clinician Perspectives on Psychotropic Medication Decisions: Developing a Communication-Centered Epistemic Model of Shared Decision Making for Mental Health Contexts.

    PubMed

    Mikesell, Lisa; Bromley, Elizabeth; Young, Alexander S; Vona, Pamela; Zima, Bonnie

    2016-06-01

    Shared decision making (SDM) interventions aim to improve client autonomy, information sharing, and collaborative decision making, yet implementation of these interventions has been variably perceived. Using interviews and focus groups with clients and clinicians from mental health clinics, we explored experiences with and perceptions about decision support strategies aimed to promote SDM around psychotropic medication treatment. Using thematic analysis, we identified themes regarding beliefs about participant involvement, information management, and participants' broader understanding of their epistemic expertise. Clients and clinicians highly valued client-centered priorities such as autonomy and empowerment when making decisions. However, two frequently discussed themes revealed complex beliefs about what that involvement should look like in practice: (a) the role of communication and information exchange and (b) the value and stability of clinician and client epistemic expertise. Complex beliefs regarding these two themes suggested a dynamic and reflexive approach to information management. Situating these findings within the Theory of Motivated Information Management, we discuss implications for conceptualizing SDM in mental health services and adapt Siminoff and Step's Communication Model of Shared Decision Making (CMSDM) to propose a Communication-centered Epistemic Model of Shared Decision Making (CEM-SDM). PMID:26529605

  6. A decision support tool to prioritize risk management options for contaminated sites.

    PubMed

    Sorvari, Jaana; Seppälä, Jyri

    2010-03-15

    The decisions on risk management (RM) of contaminated sites in Finland have typically been driven by practical factors such as time and money. However, RM is a multifaceted task that generally involves several additional determinants, e.g. performance and environmental effects of remediation methods, psychological and social factors. Therefore, we adopted a multi-criteria decision analysis approach and developed a decision support tool (DST) that is viable in decision-making in such a complex situation. The basic components of the DST are based on the Dutch REC system. However, our DST is more case-specific and allows the consideration of the type, magnitude and scale of contamination, land use, environmental conditions and socio-cultural aspects (e.g. loss of cultural heritage, image aspects). The construction of the DST was started by structuring the decision problem using a value tree. Based on this work we adopted the Multi-Attribute Value Theory (MAVT) for data aggregation. The final DST was demonstrated by two model sites for which the RM alternatives and site-specific data were created on the basis of factual remediation projects and by interviewing experts. The demonstration of the DST was carried out in a workshop where representatives of different stakeholders were requested to rank and weight the decision criteria involved. To get information on the consistency of the ranking of the RM alternatives, we used different weighting techniques (ratio estimation and pair-wise weighting) and alternative ways to treat individual respondents' weights in calculating the preference scores for each RM alternative. These dissimilar approaches resulted in some differences in the preference order of the RM alternatives. The demonstration showed that attention has to be paid to the proper description of the site, the principles of the procedure and the decision criteria. Nevertheless, the procedure proved to enable efficient communication between different stakeholders

  7. Data-Mining-Based Coronary Heart Disease Risk Prediction Model Using Fuzzy Logic and Decision Tree

    PubMed Central

    Kim, Jaekwon; Lee, Jongsik

    2015-01-01

    Objectives The importance of the prediction of coronary heart disease (CHD) has been recognized in Korea; however, few studies have been conducted in this area. Therefore, it is necessary to develop a method for the prediction and classification of CHD in Koreans. Methods A model for CHD prediction must be designed according to rule-based guidelines. In this study, a fuzzy logic and decision tree (classification and regression tree [CART])-driven CHD prediction model was developed for Koreans. Datasets derived from the Korean National Health and Nutrition Examination Survey VI (KNHANES-VI) were utilized to generate the proposed model. Results The rules were generated using a decision tree technique, and fuzzy logic was applied to overcome problems associated with uncertainty in CHD prediction. Conclusions The accuracy and receiver operating characteristic (ROC) curve values of the propose systems were 69.51% and 0.594, proving that the proposed methods were more efficient than other models. PMID:26279953

  8. Dynamics of Entropy in Quantum-like Model of Decision Making

    NASA Astrophysics Data System (ADS)

    Basieva, Irina; Khrennikov, Andrei; Asano, Masanari; Ohya, Masanori; Tanaka, Yoshiharu

    2011-03-01

    We present a quantum-like model of decision making in games of the Prisoner's Dilemma type. By this model the brain processes information by using representation of mental states in complex Hilbert space. Driven by the master equation the mental state of a player, say Alice, approaches an equilibrium point in the space of density matrices. By using this equilibrium point Alice determines her mixed (i.e., probabilistic) strategy with respect to Bob. Thus our model is a model of thinking through decoherence of initially pure mental state. Decoherence is induced by interaction with memory and external environment. In this paper we study (numerically) dynamics of quantum entropy of Alice's state in the process of decision making. Our analysis demonstrates that this dynamics depends nontrivially on the initial state of Alice's mind on her own actions and her prediction state (for possible actions of Bob.)

  9. Contribution of the Multi-attribute Value Theory to conflict resolution in groundwater management. Application to the Mancha Oriental system (Spain)

    NASA Astrophysics Data System (ADS)

    Apperl, B.; Pulido-Velazquez, M.; Andreu, J.; Llopis-Albert, C.

    2012-04-01

    observed reactions: acceptance of more rigorous measures, on one hand, and a tendency to soft measures with the same cost, as a reaction to the decreased effectiveness of the alternatives. The implementation of the method to a very complex case study, with many conflicting objectives and alternatives and uncertain outcomes, including future scenarios (climate change) illustrate the potential of the method for supporting management decisions.

  10. A Family-Oriented Decision-Making Model for Human Research in Mainland China.

    PubMed

    Rui, Deng

    2015-08-01

    This essay argues that individual-oriented informed consent is inadequate to protect human research subjects in mainland China. The practice of family-oriented decision-making is better suited to guide moral research conduct. The family's role in medical decision-making originates from the mutual benevolence that exists among family members, and is in accordance with family harmony, which is the aim of Confucian society. I argue that the practice of informed consent for medical research on human subjects ought to remain family-oriented in mainland China. This essay explores the main features of this model of informed consent and demonstrates the proper authority of the family. The family's participation in decision-making as a whole does not negate or deny the importance of the individual who is the subject of the choice, but rather acts more fully to protect research subjects. PMID:26142439

  11. Econ's optimal decision model of wheat production and distribution-documentation

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The report documents the computer programs written to implement the ECON optical decision model. The programs were written in APL, an extremely compact and powerful language particularly well suited to this model, which makes extensive use of matrix manipulations. The algorithms used are presented and listings of and descriptive information on the APL programs used are given. Possible changes in input data are also given.

  12. A model of subjective report and objective discrimination as categorical decisions in a vast representational space.

    PubMed

    King, J-R; Dehaene, S

    2014-05-01

    Subliminal perception studies have shown that one can objectively discriminate a stimulus without subjectively perceiving it. We show how a minimalist framework based on Signal Detection Theory and Bayesian inference can account for this dissociation, by describing subjective and objective tasks with similar decision-theoretic mechanisms. Each of these tasks relies on distinct response classes, and therefore distinct priors and decision boundaries. As a result, they may reach different conclusions. By formalizing, within the same framework, forced-choice discrimination responses, subjective visibility reports and confidence ratings, we show that this decision model suffices to account for several classical characteristics of conscious and unconscious perception. Furthermore, the model provides a set of original predictions on the nonlinear profiles of discrimination performance obtained at various levels of visibility. We successfully test one such prediction in a novel experiment: when varying continuously the degree of perceptual ambiguity between two visual symbols presented at perceptual threshold, identification performance varies quasi-linearly when the stimulus is unseen and in an 'all-or-none' manner when it is seen. The present model highlights how conscious and non-conscious decisions may correspond to distinct categorizations of the same stimulus encoded by a high-dimensional neuronal population vector. PMID:24639577

  13. Using multi-species occupancy models in structured decision making on managed lands

    USGS Publications Warehouse

    Sauer, John R.; Blank, Peter J.; Zipkin, Elise F.; Fallon, Jane E.; Fallon, Frederick W.

    2013-01-01

    Land managers must balance the needs of a variety of species when manipulating habitats. Structured decision making provides a systematic means of defining choices and choosing among alternative management options; implementation of a structured decision requires quantitative approaches to predicting consequences of management on the relevant species. Multi-species occupancy models provide a convenient framework for making structured decisions when the management objective is focused on a collection of species. These models use replicate survey data that are often collected on managed lands. Occupancy can be modeled for each species as a function of habitat and other environmental features, and Bayesian methods allow for estimation and prediction of collective responses of groups of species to alternative scenarios of habitat management. We provide an example of this approach using data from breeding bird surveys conducted in 2008 at the Patuxent Research Refuge in Laurel, Maryland, evaluating the effects of eliminating meadow and wetland habitats on scrub-successional and woodland-breeding bird species using summed total occupancy of species as an objective function. Removal of meadows and wetlands decreased value of an objective function based on scrub-successional species by 23.3% (95% CI: 20.3–26.5), but caused only a 2% (0.5, 3.5) increase in value of an objective function based on woodland species, documenting differential effects of elimination of meadows and wetlands on these groups of breeding birds. This approach provides a useful quantitative tool for managers interested in structured decision making.

  14. Assessing the utility of the willingness/prototype model in predicting help-seeking decisions.

    PubMed

    Hammer, Joseph H; Vogel, David L

    2013-01-01

    Prior research on professional psychological help-seeking behavior has operated on the assumption that the decision to seek help is based on intentional and reasoned processes. However, research on the dual-process prototype/willingness model (PWM; Gerrard, Gibbons, Houlihan, Stock, & Pomery, 2008) suggests health-related decisions may also involve social reaction processes that influence one's spontaneous willingness (rather than planned intention) to seek help, given conducive circumstances. The present study used structural equation modeling to evaluate the ability of these 2 information-processing pathways (i.e., the reasoned pathway and the social reaction pathway) to predict help-seeking decisions among 182 college students currently experiencing clinical levels of psychological distress. Results indicated that when both pathways were modeled simultaneously, only the social reaction pathway independently accounted for significant variance in help-seeking decisions. These findings argue for the utility of the PWM framework in the context of professional psychological help seeking and hold implications for future counseling psychology research, prevention, and practice. PMID:23106820

  15. A model of subjective report and objective discrimination as categorical decisions in a vast representational space

    PubMed Central

    King, J-R.; Dehaene, S.

    2014-01-01

    Subliminal perception studies have shown that one can objectively discriminate a stimulus without subjectively perceiving it. We show how a minimalist framework based on Signal Detection Theory and Bayesian inference can account for this dissociation, by describing subjective and objective tasks with similar decision-theoretic mechanisms. Each of these tasks relies on distinct response classes, and therefore distinct priors and decision boundaries. As a result, they may reach different conclusions. By formalizing, within the same framework, forced-choice discrimination responses, subjective visibility reports and confidence ratings, we show that this decision model suffices to account for several classical characteristics of conscious and unconscious perception. Furthermore, the model provides a set of original predictions on the nonlinear profiles of discrimination performance obtained at various levels of visibility. We successfully test one such prediction in a novel experiment: when varying continuously the degree of perceptual ambiguity between two visual symbols presented at perceptual threshold, identification performance varies quasi-linearly when the stimulus is unseen and in an ‘all-or-none’ manner when it is seen. The present model highlights how conscious and non-conscious decisions may correspond to distinct categorizations of the same stimulus encoded by a high-dimensional neuronal population vector. PMID:24639577

  16. Modeling Protected Species Habitat and Assigning Risk to Inform Regulatory Decisions

    NASA Astrophysics Data System (ADS)

    Montgomery, Robert A.; Rubeck-Schurtz, C. Nichole; Millenbah, Kelly F.; Roloff, Gary J.; Whalon, Mark E.; Olsen, Larry G.

    2009-07-01

    In the United States, environmental regulatory agencies are required to use “best available” scientific information when making decisions on a variety of issues. However, agencies are often hindered by coarse or incomplete data, particularly as it pertains to threatened and endangered species protection. Stakeholders often agree that more resolute and integrated processes for decision-making are desirable. We demonstrate a process that uses species occurrence data for a federally endangered insect (Karner blue butterfly), a readily available habitat modeling tool, and spatially explicit information about an important Michigan commodity (tart cherries). This case study has characteristics of many protected species regulatory decisions in that species occurrence data were sparse and unequally distributed; regulatory decisions (on pesticide use) were required with potentially significant impacts on a viable agricultural industry; and stakeholder relations were diverse, misinformed, and, in some situations, unjustly contentious. Results from our process include a large-scale, empirically derived habitat suitability map for the focal species and a risk ranking of tart cherry orchards with risk based on the likelihood that pesticide applications will influence the focal protected species. Although the majority (77%) of pesticide-influence zones overlapped Karner blue butterfly habitat, risk scores associated with each orchard were low. Through our process we demonstrated that spatially explicit models can help stakeholders visualize and quantify potential protected species effects. In addition, model outputs can serve to guide field activities (e.g., species surveys and implementation of pesticide buffer zones) that help minimize future effects.

  17. Young adults' decision making surrounding heavy drinking: a multi-staged model of planned behaviour.

    PubMed

    Northcote, Jeremy

    2011-06-01

    This paper examines the real life contexts in which decisions surrounding heavy drinking are made by young adults (that is, on occasions when five or more alcoholic drinks are consumed within a few hours). It presents a conceptual model that views such decision making as a multi-faceted and multi-staged process. The mixed method study draws on purposive data gathered through direct observation of eight social networks consisting of 81 young adults aged between 18 and 25 years in Perth, Western Australia, including in-depth interviews with 31 participants. Qualitative and some basic quantitative data were gathered using participant observation and in-depth interviews undertaken over an eighteen month period. Participants explained their decision to engage in heavy drinking as based on a variety of factors. These elements relate to socio-cultural norms and expectancies that are best explained by the theory of planned behaviour. A framework is proposed that characterises heavy drinking as taking place in a multi-staged manner, with young adults having: 1. A generalised orientation to the value of heavy drinking shaped by wider influences and norms; 2. A short-term orientation shaped by situational factors that determines drinking intentions for specific events; and 3. An evaluative orientation shaped by moderating factors. The value of qualitative studies of decision making in real life contexts is advanced to complement the mostly quantitative research that dominates research on alcohol decision making. PMID:21632161

  18. 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

  19. Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use.

    PubMed

    Kerr, Kathleen F; Brown, Marshall D; Zhu, Kehao; Janes, Holly

    2016-07-20

    The decision curve is a graphical summary recently proposed for assessing the potential clinical impact of risk prediction biomarkers or risk models for recommending treatment or intervention. It was applied recently in an article in Journal of Clinical Oncology to measure the impact of using a genomic risk model for deciding on adjuvant radiation therapy for prostate cancer treated with radical prostatectomy. We illustrate the use of decision curves for evaluating clinical- and biomarker-based models for predicting a man's risk of prostate cancer, which could be used to guide the decision to biopsy. Decision curves are grounded in a decision-theoretical framework that accounts for both the benefits of intervention and the costs of intervention to a patient who cannot benefit. Decision curves are thus an improvement over purely mathematical measures of performance such as the area under the receiver operating characteristic curve. However, there are challenges in using and interpreting decision curves appropriately. We caution that decision curves cannot be used to identify the optimal risk threshold for recommending intervention. We discuss the use of decision curves for miscalibrated risk models. Finally, we emphasize that a decision curve shows the performance of a risk model in a population in which every patient has the same expected benefit and cost of intervention. If every patient has a personal benefit and cost, then the curves are not useful. If subpopulations have different benefits and costs, subpopulation-specific decision curves should be used. As a companion to this article, we released an R software package called DecisionCurve for making decision curves and related graphics. PMID:27247223

  20. Emergence of viral diseases: mathematical modeling as a tool for infection control, policy and decision making.

    PubMed

    Louz, Derrick; Bergmans, Hans E; Loos, Birgit P; Hoeben, Rob C

    2010-08-01

    Mathematical modeling can be used for the development and implementation of infection control policy to combat outbreaks and epidemics of communicable viral diseases. Here an outline is provided of basic concepts and approaches used in mathematical modeling and parameterization of disease transmission. The use of mathematical models is illustrated, using the 2001 UK foot-and-mouth disease (FMD) epidemic, the 2003 global severe acute respiratory syndrome (SARS) epidemic, and human influenza pandemics, as examples. This provides insights in the strengths, limitations, and weaknesses of the various models, and demonstrates their potential for supporting policy and decision making. PMID:20218764

  1. From complex questionnaire and interviewing data to intelligent Bayesian Network models for medical decision support

    PubMed Central

    Constantinou, Anthony Costa; Fenton, Norman; Marsh, William; Radlinski, Lukasz

    2016-01-01

    Objectives 1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; 2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; 3) To ensure the BN model can be used for interventional analysis; 4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available. Method The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the components of the method are based on established work, its novelty is that it provides a rigorous consolidated and generalised framework that addresses the whole life-cycle of BN model development. The method is based on two original and recent validated BN models in forensic psychiatry, known as DSVM-MSS and DSVM-P. Results When employed with the same datasets, the DSVM-MSS demonstrated competitive to superior predictive performance (AUC scores 0.708 and 0.797) against the state-of-the-art (AUC scores ranging from 0.527 to 0.705), and the DSVM-P demonstrated superior predictive performance (cross-validated AUC score of 0.78) against the state-of-the-art (AUC scores ranging from 0.665 to 0.717). More importantly, the resulting models go beyond improving predictive accuracy and into usefulness for risk management purposes through intervention, and enhanced decision support in terms of answering complex clinical questions that are based on unobserved evidence. Conclusions This development process is applicable to any application domain which involves large-scale decision analysis based on such complex information, rather than based on data with hard facts, and in conjunction with the incorporation of

  2. Effective Use of Models in the Decision Processes: Theory Grounded in Three Case Studies. AIR Forum 1982 Paper.

    ERIC Educational Resources Information Center

    Hinman, Martha M.; Kallio, Ruth E.

    The technical, social, and procedural phenomena that facilitate the effective utilization of analytic models in decision-making are examined. Attention is focused on the theoretical issues associated with: (1) selection and fit of the model to the needs of the decision setting; (2) human factors such as cognitive style and the political climate…

  3. The Ecological Model Web Concept: A Consultative Infrastructure for Decision Makers and Researchers

    NASA Astrophysics Data System (ADS)

    Geller, G.; Nativi, S.

    2011-12-01

    Rapid climate and socioeconomic changes may be outrunning society's ability to understand, predict, and respond to change effectively. Decision makers want better information about what these changes will be and how various resources will be affected, while researchers want better understanding of the components and processes of ecological systems, how they interact, and how they respond to change. Although there are many excellent models in ecology and related disciplines, there is only limited coordination among them, and accessible, openly shared models or model systems that can be consulted to gain insight on important ecological questions or assist with decision-making are rare. A "consultative infrastructure" that increased access to and sharing of models and model outputs would benefit decision makers, researchers, as well as modelers. Of course, envisioning such an ambitious system is much easier than building it, but several complementary approaches exist that could contribute. The one discussed here is called the Model Web. This is a concept for an open-ended system of interoperable computer models and databases based on making models and their outputs available as services ("model as a service"). Initially, it might consist of a core of several models from which it could grow gradually as new models or databases were added. However, a model web would not be a monolithic, rigidly planned and built system--instead, like the World Wide Web, it would grow largely organically, with limited central control, within a framework of broad goals and data exchange standards. One difference from the WWW is that a model web is much harder to create, and has more pitfalls, and thus is a long term vision. However, technology, science, observations, and models have advanced enough so that parts of an ecological model web can be built and utilized now, forming a framework for gradual growth as well as a broadly accessible infrastructure. Ultimately, the value of a model

  4. Collaborative modelling and integrated decision support system analysis of a developed terminal lake basin

    NASA Astrophysics Data System (ADS)

    Niswonger, Richard G.; Allander, Kip K.; Jeton, Anne E.

    2014-09-01

    A terminal lake basin in west-central Nevada, Walker Lake, has undergone drastic change over the past 90 yrs due to upstream water use for agriculture. Decreased inflows to the lake have resulted in 100 km2 decrease in lake surface area and a total loss of fisheries due to salinization. The ecologic health of Walker Lake is of great concern as the lake is a stopover point on the Pacific route for migratory birds from within and outside the United States. Stakeholders, water institutions, and scientists have engaged in collaborative modeling and the development of a decision support system that is being used to develop and analyze management change options to restore the lake. Here we use an integrated management and hydrologic model that relies on state-of-the-art simulation capabilities to evaluate the benefits of using integrated hydrologic models as components of a decision support system. Nonlinear feedbacks among climate, surface-water and groundwater exchanges, and water use present challenges for simulating realistic outcomes associated with management change. Integrated management and hydrologic modeling provides a means of simulating benefits associated with management change in the Walker River basin where drastic changes in the hydrologic landscape have taken place over the last century. Through the collaborative modeling process, stakeholder support is increasing and possibly leading to management change options that result in reductions in Walker Lake salt concentrations, as simulated by the decision support system.

  5. Modification of the Decision-Making Capability in the Social Force Model for the Evacuation Process

    NASA Astrophysics Data System (ADS)

    Zainuddin, Zarita; Shuaib, Mohammed

    2010-01-01

    The Social Force Model is one of the most successful microscopic pedestrian models that represent the well-organized phenomena of the pedestrian flow. The model has been modified for evacuation process by incorporating physical forces when contact exists, on one hand, and incorporating factors into the preferred velocity to govern the individual's behavior corresponding to the situation under consideration (normal or evacuation) on the other hand. The latter incorporation has enhanced the ability of the model to represent the decision-making process of pedestrians. However, the variety of pedestrian's abilities to make decisions in emergency situations has not been incorporated properly into the model. In this article we enhance the decision-making capability of the independent pedestrians first by improving the assessment process of selecting an exit from the set of exits available in the physical environment by considering a new factor (crowd at exits); and second, by incorporating following crowds as a new feature for those who are independent. A simulation of an emergency situation inside a room is performed to validate our work.

  6. Collaborative modelling and integrated decision support system analysis of a developed terminal lake basin

    USGS Publications Warehouse

    Niswonger, Richard; Allander, Kip K.; Jeton, Anne E.

    2014-01-01

    A terminal lake basin in west-central Nevada, Walker Lake, has undergone drastic change over the past 90 yrs due to upstream water use for agriculture. Decreased inflows to the lake have resulted in 100 km2 decrease in lake surface area and a total loss of fisheries due to salinization. The ecologic health of Walker Lake is of great concern as the lake is a stopover point on the Pacific route for migratory birds from within and outside the United States. Stakeholders, water institutions, and scientists have engaged in collaborative modeling and the development of a decision support system that is being used to develop and analyze management change options to restore the lake. Here we use an integrated management and hydrologic model that relies on state-of-the-art simulation capabilities to evaluate the benefits of using integrated hydrologic models as components of a decision support system. Nonlinear feedbacks among climate, surface-water and groundwater exchanges, and water use present challenges for simulating realistic outcomes associated with management change. Integrated management and hydrologic modeling provides a means of simulating benefits associated with management change in the Walker River basin where drastic changes in the hydrologic landscape have taken place over the last century. Through the collaborative modeling process, stakeholder support is increasing and possibly leading to management change options that result in reductions in Walker Lake salt concentrations, as simulated by the decision support system.

  7. The Attentional Drift-Diffusion Model Extends to Simple Purchasing Decisions

    PubMed Central

    Krajbich, Ian; Lu, Dingchao; Camerer, Colin; Rangel, Antonio

    2012-01-01

    How do we make simple purchasing decisions (e.g., whether or not to buy a product at a given price)? Previous work has shown that the attentional drift-diffusion model (aDDM) can provide accurate quantitative descriptions of the psychometric data for binary and trinary value-based choices, and of how the choice process is guided by visual attention. Here we extend the aDDM to the case of purchasing decisions, and test it using an eye-tracking experiment. We find that the model also provides a reasonably accurate quantitative description of the relationship between choice, reaction time, and visual fixations using parameters that are very similar to those that best fit the previous data. The only critical difference is that the choice biases induced by the fixations are about half as big in purchasing decisions as in binary choices. This suggests that a similar computational process is used to make binary choices, trinary choices, and simple purchasing decisions. PMID:22707945

  8. Developing and testing a decision model for predicting influenza vaccination compliance.

    PubMed Central

    Carter, W B; Beach, L R; Inui, T S; Kirscht, J P; Prodzinski, J C

    1986-01-01

    Influenza vaccination has long been recommended for elderly high-risk patients, yet national surveys indicate that vaccination compliance rates are remarkably low (20 percent). We conducted a study to model prospectively the flu shot decisions and subsequent behavior of an elderly and/or chronically diseased (at high risk for complications of influenza) ambulatory care population at the Seattle VA Medical Center. Prior to the 1980-81 flu shot season, a random (stratified by disease) sample of 63 patients, drawn from the total population of high-risk patients in the general medicine clinic, was interviewed to identify patient-defined concerns regarding flu shots. Six potential consequences of influenza and nine of vaccination were emphasized by patients and provided the content for a weighted hierarchical utility model questionnaire. The utility model provides an operational framework for (1) obtaining subjective value and relative importance judgments from patients; (2) combining these judgments to obtain a prediction of behavioral intention and behavior for each patient; and, if the model is valid (predictive of behavior), (3) identifying those factors which are most salient to patient's decisions and subsequent behavior. Prior to the 1981-82 flu season, the decision model questionnaire was administered to 350 other high-risk patients from the same general medicine clinic population. The decision model correctly predicted behavioral intention for 87 percent and vaccination behavior for 82 percent of this population and, more importantly, differentiated shot "takers" and "nontakers" along several attitudinal dimensions that suggest specific content areas for clinical compliance intervention strategies. PMID:3949541

  9. Developing a Hierarchical Decision Model to Evaluate Nuclear Power Plant Alternative Siting Technologies

    NASA Astrophysics Data System (ADS)

    Lingga, Marwan Mossa

    A strong trend of returning to nuclear power is evident in different places in the world. Forty-five countries are planning to add nuclear power to their grids and more than 66 nuclear power plants are under construction. Nuclear power plants that generate electricity and steam need to improve safety to become more acceptable to governments and the public. One novel practical solution to increase nuclear power plants' safety factor is to build them away from urban areas, such as offshore or underground. To date, Land-Based siting is the dominant option for siting all commercial operational nuclear power plants. However, the literature reveals several options for building nuclear power plants in safer sitings than Land-Based sitings. The alternatives are several and each has advantages and disadvantages, and it is difficult to distinguish among them and choose the best for a specific project. In this research, we recall the old idea of using the alternatives of offshore and underground sitings for new nuclear power plants and propose a tool to help in choosing the best siting technology. This research involved the development of a decision model for evaluating several potential nuclear power plant siting technologies, both those that are currently available and future ones. The decision model was developed based on the Hierarchical Decision Modeling (HDM) methodology. The model considers five major dimensions, social, technical, economic, environmental, and political (STEEP), and their related criteria and sub-criteria. The model was designed and developed by the author, and its elements' validation and evaluation were done by a large number of experts in the field of nuclear energy. The decision model was applied in evaluating five potential siting technologies and ranked the Natural Island as the best in comparison to Land-Based, Floating Plant, Artificial Island, and Semi-Embedded plant.

  10. Improved Decision Support in the Energy Sector Using NASA Spaceborne Observations and Models

    NASA Astrophysics Data System (ADS)

    Eckman, R. S.; Stackhouse, P. W.

    2006-12-01

    The NASA Applied Sciences Program Energy Management Program Element establishes partnerships with federal and private organizations to improve their decisions and assessments that impact the energy sector. These improvements are enabled by leveraging the knowledge generated from research resulting from spacecraft observations and model predictions conducted by NASA and providing these as inputs to the decision support and scenario assessment tools used by partner organizations. The Energy Management Program element focuses its efforts to provide for improved decisions and assessments for the following primary areas:, (1) Renewable energy & Energy efficiency, (2) Impacts of climate change on the energy sector, (3) Long-term energy modeling and forecasting, and (4) Supply and load forecasting/Distributed energy. The goals of the Program Element seek to maintain alignment and contribute to national and international priorities, specifically the Climate Change Science and Technology Programs, and the Group on Earth Observations (GEO). The approach of the Energy Management Program Element is to develop information pathways from NASA spacecraft observations and Earth system modeling to decision support tools (DST) supporting energy demand and availability in industry, government, and private entities. These entities require historical, near-real time, and forecasted environmental observations as inputs to the DST for management decisions and scenario assessments for policy. NASA works with its partners to identify the physical quantities provided by NASA observations and model predictions resulting from Earth science research, which are specifically selected, derived, and formatted to meet the needs of a specific DST. Specific case studies describing partnerships with the National Renewable Energy Laboratory and with the International Energy Agency resulting in the use of NASA measurements in renewable energy DSTs are presented. We also describe a partnership whereby

  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. A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

    NASA Astrophysics Data System (ADS)

    Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

    Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

  13. Enabling Real-time Water Decision Support Services Using Model as a Service

    NASA Astrophysics Data System (ADS)

    Zhao, T.; Minsker, B. S.; Lee, J. S.; Salas, F. R.; Maidment, D. R.; David, C. H.

    2014-12-01

    Through application of computational methods and an integrated information system, data and river modeling services can help researchers and decision makers more rapidly understand river conditions under alternative scenarios. To enable this capability, workflows (i.e., analysis and model steps) are created and published as Web services delivered through an internet browser, including model inputs, a published workflow service, and visualized outputs. The RAPID model, which is a river routing model developed at University of Texas Austin for parallel computation of river discharge, has been implemented as a workflow and published as a Web application. This allows non-technical users to remotely execute the model and visualize results as a service through a simple Web interface. The model service and Web application has been prototyped in the San Antonio and Guadalupe River Basin in Texas, with input from university and agency partners. In the future, optimization model workflows will be developed to link with the RAPID model workflow to provide real-time water allocation decision support services.

  14. Improving Water Management Decision Support Tools Using NASA Satellite and Modeling Data

    NASA Astrophysics Data System (ADS)

    Toll, D. L.; Arsenault, K.; Nigro, J.; Pinheiro, A.; Engman, E. T.; Triggs, J.; Cosgrove, B.; Alonge, C.; Boyle, D.; Allen, R.; Townsend, P.; Ni-Meister, W.

    2006-05-01

    One of twelve Applications of National priority within NASA's Applied Science Program, the Water Management Program Element addresses concerns and decision making related to water availability, water forecast and water quality. The goal of the Water Management Program Element is to encourage water management organizations to use NASA Earth science data, models products, technology and other capabilities in their decision support tools for problem solving. The Water Management Program Element partners with Federal agencies, academia, private firms, and may include international organizations. This paper further describes the Water Management Program with the objective of informing the applications community of the potential opportunities for using NASA science products for problem solving. We will illustrate some ongoing and application Water Management projects evaluating and benchmarking NASA data with partnering federal agencies and their decision support tools: 1) Environmental Protection Agency for water quality; 2) Bureau of Reclamation for water supply, demand and forecast; and 3) NOAA National Weather Service for improved weather prediction. Examples of the types of NASA contributions to the these agency decision support tools include: 1) satellite observations within models assist to estimate water storage, i.e., snow water equivalent, soil moisture, aquifer volumes, or reservoir storages; 2) model derived products, i.e., evapotranspiration, precipitation, runoff, ground water recharge, and other 4-dimensional data assimilation products; 3) improve water quality, assessments by using improved inputs from NASA models (precipitation, evaporation) and satellite observations (e.g., temperature, turbidity, land cover) to nonpoint source models; and 4) water (i.e., precipitation) and temperature predictions from days to decades over local, regional and global scales.

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

    PubMed

    Humphries Choptiany, John Michael; Pelot, Ronald

    2014-09-01

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

  16. Visual Attention Allocation Between Robotic Arm and Environmental Process Control: Validating the STOM Task Switching Model

    NASA Technical Reports Server (NTRS)

    Wickens, Christopher; Vieanne, Alex; Clegg, Benjamin; Sebok, Angelia; Janes, Jessica

    2015-01-01

    Fifty six participants time shared a spacecraft environmental control system task with a realistic space robotic arm control task in either a manual or highly automated version. The former could suffer minor failures, whose diagnosis and repair were supported by a decision aid. At the end of the experiment this decision aid unexpectedly failed. We measured visual attention allocation and switching between the two tasks, in each of the eight conditions formed by manual-automated arm X expected-unexpected failure X monitoring- failure management. We also used our multi-attribute task switching model, based on task attributes of priority interest, difficulty and salience that were self-rated by participants, to predict allocation. An un-weighted model based on attributes of difficulty, interest and salience accounted for 96 percent of the task allocation variance across the 8 different conditions. Task difficulty served as an attractor, with more difficult tasks increasing the tendency to stay on task.

  17. A case mix simulation decision support system model for negotiating hospital rates.

    PubMed

    Hatcher, M E; Connelly, C

    1988-12-01

    The institution of prospective payment systems by many health care insurers has drawn increased attention to case-based financial planning in hospitals. When hospital revenues are directly linked to patient diagnoses rather than to the types and quantities of services supplied to patients, managers must be aware of the financial implications of different case mixes and must be prepared to influence insurers' price structures. A case-based financial planning model is presented here for the purpose of assisting managerial decision making in the strategic areas of case mix planning and pricing. The computerized model characterizes hospitals as product manufacturers, the product being discharged patients. Diagnosis serves to differentiate the "products"; however, diagnoses are grouped by payor and similar treatment cost experiences to create a limited set of managerially meaningful case types. Diagnostic and treatment costs are also aggregated to facilitate the modeling of the hospital production process. The computerized model projects the number of patients of each case-type and total patient volume, based on estimated patient volume growth rates. The model also projects prices and contribution margins for each case-type, as well as total contribution to hospital overhead. Testing the model with a hypothetical example of a hospital strategic planning problem demonstrates the model's potential as a decision-making aid in case mix planning and case-type pricing. It also reveals several model shortcomings that require further developmental effort. PMID:3148679

  18. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    PubMed Central

    Zhang, Dezhi; Li, Shuangyan

    2014-01-01

    This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209

  19. A spiking Basal Ganglia model of synchrony, exploration and decision making

    PubMed Central

    Mandali, Alekhya; Rengaswamy, Maithreye; Chakravarthy, V. Srinivasa; Moustafa, Ahmed A.

    2015-01-01

    To make an optimal decision we need to weigh all the available options, compare them with the current goal, and choose the most rewarding one. Depending on the situation an optimal decision could be to either “explore” or “exploit” or “not to take any action” for which the Basal Ganglia (BG) is considered to be a key neural substrate. In an attempt to expand this classical picture of BG function, we had earlier hypothesized that the Indirect Pathway (IP) of the BG could be the subcortical substrate for exploration. In this study we build a spiking network model to relate exploration to synchrony levels in the BG (which are a neural marker for tremor in Parkinson's disease). Key BG nuclei such as the Sub Thalamic Nucleus (STN), Globus Pallidus externus (GPe) and Globus Pallidus internus (GPi) were modeled as Izhikevich spiking neurons whereas the Striatal output was modeled as Poisson spikes. The model is cast in reinforcement learning framework with the dopamine signal representing reward prediction error. We apply the model to two decision making tasks: a binary action selection task (similar to one used by Humphries et al., 2006) and an n-armed bandit task (Bourdaud et al., 2008). The model shows that exploration levels could be controlled by STN's lateral connection strength which also influenced the synchrony levels in the STN-GPe circuit. An increase in STN's lateral strength led to a decrease in exploration which can be thought as the possible explanation for reduced exploratory levels in Parkinson's patients. Our simulations also show that on complete removal of IP, the model exhibits only Go and No-Go behaviors, thereby demonstrating the crucial role of IP in exploration. Our model provides a unified account for synchronization, action section, and explorative behavior. PMID:26074761

  20. Optimal inventories for overhaul of repairable redundant systems - A Markov decision model

    NASA Technical Reports Server (NTRS)

    Schaefer, M. K.

    1984-01-01

    A Markovian decision model was developed to calculate the optimal inventory of repairable spare parts for an avionics control system for commercial aircraft. Total expected shortage costs, repair costs, and holding costs are minimized for a machine containing a single system of redundant parts. Transition probabilities are calculated for each repair state and repair rate, and optimal spare parts inventory and repair strategies are determined through linear programming. The linear programming solutions are given in a table.

  1. Research of a continuous time model of the decentralized decision-making

    NASA Astrophysics Data System (ADS)

    Fang, Xu

    2013-07-01

    A continuous time model is proposed in this paper, dealing with the decentralized decision-making of multi-products promotion, under the condition of moral hazard. The main result is that when the revenue function and the movement law satisfy certain conditions, the optimal efforts level of the division in continuous time is the same with that in the static case, even though both are distorted compared with the optimal efforts level under complete information.

  2. Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats

    PubMed Central

    Hales, Claire A.; Robinson, Emma S. J.; Houghton, Conor J.

    2016-01-01

    Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142), and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward. PMID:27023442

  3. Multi-phase intelligent decision model for reservoir real-time flood control during typhoons

    NASA Astrophysics Data System (ADS)

    Hsu, Nien-Sheng; Huang, Chien-Lin; Wei, Chih-Chiang

    2015-03-01

    This study applies an Adaptive Network-based Fuzzy Inference System (ANFIS) and a Real-Time Recurrent Learning Neural Network (RTRLNN) with an optimized reservoir release hydrograph using Mixed Integer Linear Programming (MILP) from historical typhoon events to develop a multi-phase intelligent real-time reservoir operation model for flood control. The flood control process is divided into three stages: (1) before flood (Stage I); (2) before peak flow (Stage II); and (3) after peak flow (Stage III). The models are then constructed with either three phase modules (ANFIS-3P and RTRLNN-3P) or two phase (Stage I + II and Stage III) modules (ANFIS-2P and RTRLNN-2P). The multi-phase modules are developed with consideration of the difference in operational decision mechanisms, decision information, release functions, and targets between each flood control stage to solve the problem of time-consuming computation and difficult system integration of MILP. In addition, the model inputs include the coupled short lead time and total reservoir inflow forecast information that are developed using radar- and satellite-based meteorological monitoring techniques, forecasted typhoon tracks, meteorological image similarity analysis, ANFIS and RTRLNN. This study uses the Tseng-Wen Reservoir basin as the study area, and the model results showed that RTRLNN outperformed ANFIS in the simulated outcomes from the optimized hydrographs. This study also applies the models to Typhoons Kalmaegi and Morakot to compare the simulations to historical operations. From the operation results, the RTRLNN-3P model is better than RTRLNN-2P and historical operations. Further, because the RTRLNN-3P model combines the innovative multi-phase module with monitored and forecasted decision information, the operation can simultaneously, effectively and automatically achieve the dual goals of flood detention at peak flow periods and water supply at the end of a typhoon event.

  4. Reservoir Operations and Flow Modeling to Support Decision Making in the Delaware River Basin

    NASA Astrophysics Data System (ADS)

    Quinodoz, H. A.

    2006-12-01

    About five percent of the US population depends on the waters from the Delaware River Basin for its water supply, including New York City and Philadelphia. Water management in the basin is governed by a compact signed in 1961 by the four basin states and the federal government. The compact created the Delaware River Basin Commission (DRBC) and gave it broad powers to plan, regulate, and manage the development of the basin water resources. The compact also recognized a pre-existing (1954) U.S. Supreme Court Decree that grants the City of New York the right to export up to 800 million gallons per day out of the basin, provided that a prescribed minimum flow is met at Montague, New Jersey for the use of the lower-basin states. The Delaware River Basin Compact also allows the DRBC to adjust the releases and diversions under the Decree, subject to the unanimous consent of the decree parties. This mechanism has been used several times over the last 30 years, to implement and modify rules governing drought operations, instream flows, minimum flow targets, and control of salinity intrusion. In every case, decision makers have relied upon extensive modeling of alternative proposals, using a basin-wide daily flow model. Often, stakeholders have modified and used the same model to test and refine their proposals prior to consideration by the decision makers. The flow model has been modified over the years, to simulate new features and processes in a river system partially controlled by more than ten reservoirs. The flow model has proved to be an adaptable tool, able to simulate the dynamics of a complex system driven by conflicting objectives. This presentation reviews the characteristics of the daily flow model in its current form, discuss how model simulations are used to inform the decision-making process, and provide a case study of a recent modification of the system-wide drought operating plan.

  5. Improved Hypoxia Modeling for Nutrient Control Decisions in the Gulf of Mexico

    NASA Technical Reports Server (NTRS)

    Habib, Shahid; Pickering, Ken; Tzortziou, Maria; Maninio, Antonio; Policelli, Fritz; Stehr, Jeff

    2011-01-01

    The Gulf of Mexico Modeling Framework is a suite of coupled models linking the deposition and transport of sediment and nutrients to subsequent bio-geo chemical processes and the resulting effect on concentrations of dissolved oxygen in the coastal waters of Louisiana and Texas. Here, we examine the potential benefits of using multiple NASA remote sensing data products within this Modeling Framework for increasing the accuracy of the models and their utility for nutrient control decisions in the Gulf of Mexico. Our approach is divided into three components: evaluation and improvement of (a) the precipitation input data (b) atmospheric constituent concentrations in EPA's air quality/deposition model and (c) the calculation of algal biomass, organic carbon and suspended solids within the water quality/eutrophication models of the framework.

  6. Computer models used to support cleanup decision-making at hazardous and radioactive waste sites

    SciTech Connect

    Moskowitz, P.D.; Pardi, R.; DePhillips, M.P.; Meinhold, A.F.

    1992-07-01

    Massive efforts are underway to cleanup hazardous and radioactive waste sites located throughout the US To help determine cleanup priorities, computer models are being used to characterize the source, transport, fate and effects of hazardous chemicals and radioactive materials found at these sites. Although, the US Environmental Protection Agency (EPA), the US Department of Energy (DOE), and the US Nuclear Regulatory Commission (NRC) have provided preliminary guidance to promote the use of computer models for remediation purposes, no Agency has produced directed guidance on models that must be used in these efforts. To identify what models are actually being used to support decision-making at hazardous and radioactive waste sites, a project jointly funded by EPA, DOE and NRC was initiated. The purpose of this project was to: (1) Identify models being used for hazardous and radioactive waste site assessment purposes; and (2) describe and classify these models. This report presents the results of this study.

  7. The decision of out-of-home placement in residential care after parental neglect: Empirically testing a psychosocial model.

    PubMed

    Rodrigues, Leonor; Calheiros, Manuela; Pereira, Cícero

    2015-11-01

    Out-of-home placement decisions in residential care are complex, ambiguous and full of uncertainty, especially in cases of parental neglect. Literature on this topic is so far unable to understand and demonstrate the source of errors involved in those decisions and still fails to focus on professional's decision making process. Therefore, this work intends to test a socio-psychological model of decision-making that is a more integrated, dualistic and ecological version of the Theory of Planned Behavior's model. It describes the process through which the decision maker takes into account personal, contextual and social factors of the Decision-Making Ecology in the definition of his/her decision threshold. One hundred and ninety-five professionals from different Children and Youth Protection Units, throughout the Portuguese territory, participated in this online study. After reading a vignette of a (psychological and physical) neglect case toward a one-year-old child, participants were presented with a group of questions that measured worker's assessment of risk, intention, attitude, subjective norm, behavior control and beliefs toward residential care placement decision, as well as worker's behavior experience, emotions and family/child-related-values involved in that decision. A set of structural equation modeling analyses have proven the good fit of the proposed model. The intention to propose a residential care placement decision was determined by cognitive, social, affective, value-laden and experience variables and the perceived risk. Altogether our model explained 61% of professional's decision toward a parental neglect case. The theoretical and practical implications of these results are discussed, namely the importance of raising awareness about the existence of these biased psychosocial determinants. PMID:25882668

  8. 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.

  9. A model study on the circuit mechanism underlying decision-making in Drosophila.

    PubMed

    Wu, Zhihua; Guo, Aike

    2011-05-01

    Previous elegant experiments in a flight simulator showed that conditioned Drosophila is able to make a clear-cut decision to avoid potential danger. When confronted with conflicting visual cues, the relative saliency of two competing cues is found to be a sensory ruler for flies to judge which cue should be used for decision-making. Further genetic manipulations and immunohistological analysis revealed that the dopamine system and mushroom bodies are indispensable for such a clear-cut or nonlinear decision. The neural circuit mechanism, however, is far from being clear. In this paper, we adopt a computational modeling approach to investigate how different brain areas and the dopamine system work together to drive a fly to make a decision. By developing a systems-level neural network, a two-pathway circuit is proposed. Besides a direct pathway from a feature binding area to the motor center, another connects two areas via the mushroom body, a target of dopamine release. A raised dopamine level is hypothesized to be induced by complex choice tasks and to enhance lateral inhibition and steepen the units' response gain in the mushroom body. Simulations show that training helps to assign values to formerly neutral features. For a circuit model with a blocked mushroom body, the direct pathway passes all alternatives to the motor center without changing original values, giving rise to a simple choice characterized by a linear choice curve. With respect to an intact circuit, enhanced lateral inhibition dependent on dopamine critically promotes competition between alternatives, turning the linear- into nonlinear choice behavior. Results account well for experimental data, supporting the reasonableness of model working hypotheses. Several testable predictions are made for future studies. PMID:21310589

  10. A micro-pool model for decision-related signals in visual cortical areas

    PubMed Central

    Parker, Andrew J.

    2013-01-01

    The study of sensory signaling in the visual cortex has been greatly advanced by the recording of neural activity simultaneously with the performance of a specific psychophysical task. Individual nerve cells may also increase their firing leading up to the particular choice or decision made on a single psychophysical trial. Understanding these signals is important because they have been taken as evidence that a particular nerve cell or group of nerve cells in the cortex is involved in the formation of the perceptual decision ultimately signaled by the organism. However, recent analyses show that the size of a decision-related change in firing in a particular neuron is not a secure basis for concluding anything about the contribution of a single neuron to the formation of a decision: rather the size of the decision-related firing is expected to be dominated by the extent to which the activation of a single neuron is correlated with the firing of the pool of neurons. The critical question becomes what defines membership of a population of neurons. This article presents the proposal that groups of neurons are naturally linked together by their connectivity, which in turn reflects the previous history of sensory stimulations. When a new psychophysical task is performed, a group of neurons relevant to the judgment becomes involved because the firing of some neurons in that group is strongly relevant to the task. This group of neurons is called a micro-pool. This article examines the consequences of such a proposal within the visual nervous system. The main focus is on the signals available from single neurons, but it argued that models of choice-related signals must scale up to larger numbers of neurons because MRI and MEG studies also show evidence of similar choice signals. PMID:23986690

  11. Creating a process for incorporating epidemiological modelling into outbreak management decisions.

    PubMed

    Akselrod, Hana; Mercon, Monica; Kirkeby Risoe, Petter; Schlegelmilch, Jeffrey; McGovern, Joanne; Bogucki, Sandy

    2012-01-01

    Modern computational models of infectious diseases greatly enhance our ability to understand new infectious threats and assess the effects of different interventions. The recently-released CDC Framework for Preventing Infectious Diseases calls for increased use of predictive modelling of epidemic emergence for public health preparedness. Currently, the utility of these technologies in preparedness and response to outbreaks is limited by gaps between modelling output and information requirements for incident management. The authors propose an operational structure that will facilitate integration of modelling capabilities into action planning for outbreak management, using the Incident Command System (ICS) and Synchronization Matrix framework. It is designed to be adaptable and scalable for use by state and local planners under the National Response Framework (NRF) and Emergency Support Function #8 (ESF-8). Specific epidemiological modelling requirements are described, and integrated with the core processes for public health emergency decision support. These methods can be used in checklist format to align prospective or real-time modelling output with anticipated decision points, and guide strategic situational assessments at the community level. It is anticipated that formalising these processes will facilitate translation of the CDC's policy guidance from theory to practice during public health emergencies involving infectious outbreaks. PMID:22948107

  12. Bayesian decision-network modeling of multiple stakeholders for reef ecosystem restoration in the coral triangle.

    PubMed

    Varkey, Divya A; Pitcher, Tony J; McAllister, Murdoch K; Sumaila, Rashid S

    2013-06-01

    Proposals for marine conservation measures have proliferated in the last 2 decades due to increased reports of fishery declines and interest in conservation. Fishers and fisheries managers have often disagreed strongly when discussing controls on fisheries. In such situations, ecosystem-based models and fisheries-stock assessment models can help resolve disagreements by highlighting the trade-offs that would be made under alternative management scenarios. We extended the analytical framework for modeling such trade-offs by including additional stakeholders whose livelihoods and the value they place on conservation depend on the condition of the marine ecosystem. To do so, we used Bayesian decision-network models (BDNs) in a case study of an Indonesian coral reef fishery. Our model included interests of the fishers and fishery managers; individuals in the tourism industry; conservation interests of the state, nongovernmental organizations, and the local public; and uncertainties in ecosystem status, projections of fisheries revenues, tourism growth, and levels of interest in conservation. We calculated the total utility (i.e., value) of a range of restoration scenarios. Restricting net fisheries and live-fish fisheries appeared to be the best compromise solutions under several combinations of settings of modeled variables. Results of our case study highlight the implications of alternate formulations for coral reef stakeholder utility functions and discount rates for the calculation of the net benefits of alternative fisheries management options. This case study may also serve as a useful example for other decision analyses with multiple stakeholders. PMID:23530881

  13. The combined analysis of uncertainty and patient heterogeneity in medical decision models.

    PubMed

    Groot Koerkamp, Bas; Stijnen, Theo; Weinstein, Milton C; Hunink, M G Myriam

    2011-01-01

    The analysis of both patient heterogeneity and parameter uncertainty in decision models is increasingly recommended. In addition, the complexity of current medical decision models commonly requires simulating individual subjects, which introduces stochastic uncertainty. The combined analysis of uncertainty and heterogeneity often involves complex nested Monte Carlo simulations to obtain the model outcomes of interest. In this article, the authors distinguish eight model types, each dealing with a different combination of patient heterogeneity, parameter uncertainty, and stochastic uncertainty. The analyses that are required to obtain the model outcomes are expressed in equations, explained in stepwise algorithms, and demonstrated in examples. Patient heterogeneity is represented by frequency distributions and analyzed with Monte Carlo simulation. Parameter uncertainty is represented by probability distributions and analyzed with 2nd-order Monte Carlo simulation (aka probabilistic sensitivity analysis). Stochastic uncertainty is analyzed with 1st-order Monte Carlo simulation (i.e., trials or random walks). This article can be used as a reference for analyzing complex models with more than one type of uncertainty and patient heterogeneity. PMID:20974904

  14. The Keirsey Temperament Model: A Model for Helping Educational Administrators Facilitate Ethical Decision Making

    ERIC Educational Resources Information Center

    Mills, Roxanne

    2006-01-01

    Administrators in any field are often called upon to make decisions involving ethical considerations, but are not always well prepared or prone to do so. This situation of being faced with ethical concerns is perhaps more true for educational administrators than for leaders in other arenas. Not only are administrators at school, since they deal…

  15. A software development and evolution model based on decision-making

    NASA Technical Reports Server (NTRS)

    Wild, J. Christian; Dong, Jinghuan; Maly, Kurt

    1991-01-01

    Design is a complex activity whose purpose is to construct an artifact which satisfies a set of constraints and requirements. However the design process is not well understood. The software design and evolution process is the focus of interest, and a three dimensional software development space organized around a decision-making paradigm is presented. An initial instantiation of this model called 3DPM(sub p) which was partly implemented, is presented. Discussion of the use of this model in software reuse and process management is given.

  16. Coupled hydrological, ecological, decision and economic models for monetary valuation of riparian ecosystem services

    NASA Astrophysics Data System (ADS)

    Goodrich, D. C.; Brookshire, D.; Broadbent, C.; Dixon, M. D.; Brand, L. A.; Thacher, J.; Benedict, K. K.; Lansey, K. E.; Stromberg, J. C.; Stewart, S.; McIntosh, M.

    2011-12-01

    Water is a critical component for sustaining both natural and human systems. Yet the value of water for sustaining ecosystem services is not well quantified in monetary terms. Ideally decisions involving water resource management would include an apples-to-apples comparison of the costs and benefits in dollars of both market and non-market goods and services - human and ecosystem. To quantify the value of non-market ecosystem services, scientifically defensible relationships must be developed that link the effect of a decision (e.g. human growth) to the change in ecosystem attributes from current conditions. It is this linkage that requires the "poly-disciplinary" coupling of knowledge and models from the behavioral, physical, and ecological sciences. In our experience another key component of making this successful linkage is development of a strong poly-disciplinary scientific team that can readily communicate complex disciplinary knowledge to non-specialists outside their own discipline. The time to build such a team that communicates well and has a strong sense of trust should not be underestimated. The research described in the presentation incorporated hydrologic, vegetation, avian, economic, and decision models into an integrated framework to determine the value of changes in ecological systems that result from changes in human water use. We developed a hydro-bio-economic framework for the San Pedro River Region in Arizona that considers groundwater, stream flow, and riparian vegetation, as well as abundance, diversity, and distribution of birds. In addition, we developed a similar framework for the Middle Rio Grande of New Mexico. There are six research components for this project: (1) decision support and scenario specification, (2) regional groundwater model, (3) the riparian vegetation model, (4) the avian model, (5) methods for displaying the information gradients in the valuation survey instruments (Choice Modeling and Contingent Valuation), and (6

  17. Modeling and Analysis in Support of Decision Making for Technological Investment

    SciTech Connect

    Lenhart, S

    2003-06-11

    Engineering design, resource allocation, military operations, and investment strategies share a major common trait, which is, to a large extent, independent of their different origins, specific features, and intended goals. The unifying trait is the fact that, in any of these endeavors, one has to make reasonable choices, at multiple levels of decision making, among various possible and sometimes competing prospective solutions to an important and consequential practical problem. While the specifics of the problem depend on application, context, additional constraints, etc., the ultimate--albeit imprecise--goal in all these activities is to ''optimize performance,'' which is to have maximal success/profit/return with minimal time/effort/investment. In general, the underlying system is ruled by complex and often unknown dynamics, and affected by various uncertainties, which are unknown as well; on the other hand, there are numerous levels of decision making, which result in a hierarchical structure in the decision process (tree) that is both asynchronous and non-deterministic. Usually, indifferent of the specific application, as one lowers the level of decision making, alternatives depend on fewer independent variables and models become more detailed and physics/engineering based. On the contrary, at higher levels, various components aggregate and decision making is based more on fuzzier criteria instead of readily quantifiable physics/engineering details. Moreover, decisions are strongly influenced by the educational and personal biases of the people who take them. In some instances, this may blur, if not totally obfuscate objective comparisons between various options. Therefore, a crucial point in decision-making is properly understanding and quantifying the tradeoffs, including all their future relevant consequences. Since the interaction between various choices is an intricate nonlinear process, the focus shifts from the dynamics itself to the overall

  18. Early Prostate Cancer: Hedonic Prices Model of Provider-Patient Interactions and Decisions

    SciTech Connect

    Jani, Ashesh B. Hellman, Samuel

    2008-03-15

    Purpose: To determine the relative influence of treatment features and treatment availabilities on final treatment decisions in early prostate cancer. Methods and Materials: We describe and apply a model, based on hedonic prices, to understand provider-patient interactions in prostate cancer. This model included four treatments (observation, external beam radiotherapy, brachytherapy, and prostatectomy) and five treatment features (one efficacy and four treatment complication features). We performed a literature search to estimate (1) the intersections of the 'bid' functions and 'offer' functions with the price function along different treatment feature axes, and (2) the treatments actually rendered in different patient subgroups based on age. We performed regressions to determine the relative weight of each feature in the overall interaction and the relative availability of each treatment modality to explain differences between observed vs. predicted use of different modalities in different patient subpopulations. Results: Treatment efficacy and potency preservation are the major factors influencing decisions for young patients, whereas preservation of urinary and rectal function is much more important for very elderly patients. Referral patterns seem to be responsible for most of the deviations of observed use of different treatments from those predicted by idealized provider-patient interactions. Specifically, prostatectomy is used far more commonly in young patients and radiotherapy and observation used far more commonly in elderly patients than predicted by a uniform referral pattern. Conclusions: The hedonic prices approach facilitated identifying the relative importance of treatment features and quantification of the impact of the prevailing referral pattern on prostate cancer treatment decisions.

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

    PubMed Central

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

    2015-01-01

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

  20. Design model of computerized personal decision aid for youth: An expert review

    NASA Astrophysics Data System (ADS)

    Sarif, Siti Mahfuzah; Ibrahim, Norfiza; Shiratuddin, Norshuhada

    2016-08-01

    This paper provides a structured review of a design model of a computerized personal decision aid that is intended for youth, named as YouthPDA Design Model. The proposed design model was examined by experts in related areas to ensure the appropriateness of the proposed components and elements, relevancy of the terminologies used, logic of the flow, usability, and practicality of the design model towards development of YouthPDA application. Seven experts from related areas were involved in the evaluation. Discussions on the findings obtained from the expert review are included in this paper. Finally, a revised design model of YouthPDA is proposed as main guidance to develop YouthPDA application.

  1. Multidisciplinary Modelling of Symptoms and Signs with Archetypes and SNOMED-CT for Clinical Decision Support.

    PubMed

    Marco-Ruiz, Luis; Maldonado, J Alberto; Karlsen, Randi; Bellika, Johan G

    2015-01-01

    Clinical Decision Support Systems (CDSS) help to improve health care and reduce costs. However, the lack of knowledge management and modelling hampers their maintenance and reuse. Current EHR standards and terminologies can allow the semantic representation of the data and knowledge of CDSS systems boosting their interoperability, reuse and maintenance. This paper presents the modelling process of respiratory conditions' symptoms and signs by a multidisciplinary team of clinicians and information architects with the help of openEHR, SNOMED and clinical information modelling tools for a CDSS. The information model of the CDSS was defined by means of an archetype and the knowledge model was implemented by means of an SNOMED-CT based ontology. PMID:25991115

  2. Counseling for Decisions

    ERIC Educational Resources Information Center

    Smaby, Marlowe H.; Tamminen, Armas W.

    1978-01-01

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

  3. Multiscale Modelling and Analysis of Collective Decision Making in Swarm Robotics

    PubMed Central

    Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

    2014-01-01

    We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable. PMID:25369026

  4. Integrating Decision Tree and Hidden Markov Model (HMM) for Subtype Prediction of Human Influenza A Virus

    NASA Astrophysics Data System (ADS)

    Attaluri, Pavan K.; Chen, Zhengxin; Weerakoon, Aruna M.; Lu, Guoqing

    Multiple criteria decision making (MCDM) has significant impact in bioinformatics. In the research reported here, we explore the integration of decision tree (DT) and Hidden Markov Model (HMM) for subtype prediction of human influenza A virus. Infection with influenza viruses continues to be an important public health problem. Viral strains of subtype H3N2 and H1N1 circulates in humans at least twice annually. The subtype detection depends mainly on the antigenic assay, which is time-consuming and not fully accurate. We have developed a Web system for accurate subtype detection of human influenza virus sequences. The preliminary experiment showed that this system is easy-to-use and powerful in identifying human influenza subtypes. Our next step is to examine the informative positions at the protein level and extend its current functionality to detect more subtypes. The web functions can be accessed at http://glee.ist.unomaha.edu/.

  5. Multiscale modelling and analysis of collective decision making in swarm robotics.

    PubMed

    Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

    2014-01-01

    We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable. PMID:25369026

  6. Impact of Uncertainty in SWAT Model Simulations on Consequent Decisions on Optimal Crop Management Practices

    NASA Astrophysics Data System (ADS)

    Krishnan, N.; Sudheer, K. P.; Raj, C.; Chaubey, I.

    2015-12-01

    The diminishing quantities of non-renewable forms of energy have caused an increasing interest in the renewable sources of energy, such as biofuel, in the recent years. However, the demand for biofuel has created a concern for allocating grain between the fuel and food industry. Consequently, appropriate regulations that limit grain based ethanol production have been developed and are put to practice, which resulted in cultivating perennial grasses like Switch grass and Miscanthus to meet the additional cellulose demand. A change in cropping and management practice, therefore, is essential to cater the conflicting requirement for food and biofuel, which has a long-term impact on the downstream water quality. Therefore it is essential to implement optimal cropping practices to reduce the pollutant loadings. Simulation models in conjunction with optimization procedures are useful in developing efficient cropping practices in such situations. One such model is the Soil and Water Assessment Tool (SWAT), which can simulate both the water and the nutrient cycle, as well as quantify long-term impacts of changes in management practice in the watershed. It is envisaged that the SWAT model, along with an optimization algorithm, can be used to identify the optimal cropping pattern that achieves the minimum guaranteed grain production with less downstream pollution, while maximizing the biomass production for biofuel generation. However, the SWAT simulations do have a certain level of uncertainty that needs to be accounted for before making decisions. Therefore, the objectives of this study are twofold: (i) to understand how model uncertainties influence decision-making, and (ii) to develop appropriate management scenarios that account the uncertainty. The simulation uncertainty of the SWAT model is assessed using Shuffled Complex Evolutionary Metropolis Algorithm (SCEM). With the data collected from St. Joseph basin, IN, USA, the preliminary results indicate that model

  7. A Critical Meta-Analysis of Lens Model Studies in Human Judgment and Decision-Making

    PubMed Central

    Kaufmann, Esther; Reips, Ulf-Dietrich; Wittmann, Werner W.

    2013-01-01

    Achieving accurate judgment (‘judgmental achievement’) is of utmost importance in daily life across multiple domains. The lens model and the lens model equation provide useful frameworks for modeling components of judgmental achievement and for creating tools to help decision makers (e.g., physicians, teachers) reach better judgments (e.g., a correct diagnosis, an accurate estimation of intelligence). Previous meta-analyses of judgment and decision-making studies have attempted to evaluate overall judgmental achievement and have provided the basis for evaluating the success of bootstrapping (i.e., replacing judges by linear models that guide decision making). However, previous meta-analyses have failed to appropriately correct for a number of study design artifacts (e.g., measurement error, dichotomization), which may have potentially biased estimations (e.g., of the variability between studies) and led to erroneous interpretations (e.g., with regards to moderator variables). In the current study we therefore conduct the first psychometric meta-analysis of judgmental achievement studies that corrects for a number of study design artifacts. We identified 31 lens model studies (N = 1,151, k = 49) that met our inclusion criteria. We evaluated overall judgmental achievement as well as whether judgmental achievement depended on decision domain (e.g., medicine, education) and/or the level of expertise (expert vs. novice). We also evaluated whether using corrected estimates affected conclusions with regards to the success of bootstrapping with psychometrically-corrected models. Further, we introduce a new psychometric trim-and-fill method to estimate the effect sizes of potentially missing studies correct psychometric meta-analyses for effects of publication bias. Comparison of the results of the psychometric meta-analysis with the results of a traditional meta-analysis (which only corrected for sampling error) indicated that artifact correction leads to a) an

  8. Prediction of Antimicrobial Activity of Synthetic Peptides by a Decision Tree Model

    PubMed Central

    Lira, Felipe; Perez, Pedro S.; Baranauskas, José A.

    2013-01-01

    Antimicrobial resistance is a persistent problem in the public health sphere. However, recent attempts to find effective substitutes to combat infections have been directed at identifying natural antimicrobial peptides in order to circumvent resistance to commercial antibiotics. This study describes the development of synthetic peptides with antimicrobial activity, created in silico by site-directed mutation modeling using wild-type peptides as scaffolds for these mutations. Fragments of antimicrobial peptides were used for modeling with molecular modeling computational tools. To analyze these peptides, a decision tree model, which indicated the action range of peptides on the types of microorganisms on which they can exercise biological activity, was created. The decision tree model was processed using physicochemistry properties from known antimicrobial peptides available at the Antimicrobial Peptide Database (APD). The two most promising peptides were synthesized, and antimicrobial assays showed inhibitory activity against Gram-positive and Gram-negative bacteria. Colossomin C and colossomin D were the most inhibitory peptides at 5 μg/ml against Staphylococcus aureus and Escherichia coli. The methods described in this work and the results obtained are useful for the identification and development of new compounds with antimicrobial activity through the use of computational tools. PMID:23455341

  9. Dual Processes in Decision Making and Developmental Neuroscience: A Fuzzy-Trace Model

    PubMed Central

    Reyna, Valerie F.; Brainerd, Charles J.

    2011-01-01

    From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals—that reasoning biases emerge with development —have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts both improvement and developmental reversals in reasoning and decision making. Drawing on research on logical and quantitative reasoning, as well as on risky decision making in the laboratory and in life, we illustrate how the same small set of theoretical principles apply to typical neurodevelopment, encompassing childhood, adolescence, and adulthood, and to neurological conditions such as autism and Alzheimer's disease. For example, framing effects—that risk preferences shift when the same decisions are phrases in terms of gains versus losses—emerge in early adolescence as gist-based intuition develops. In autistic individuals, who rely less on gist-based intuition and more on verbatim-based analysis, framing biases are attenuated (i.e., they outperform typically developing control subjects). In adults, simple manipulations based on fuzzy-trace theory can make framing effects appear and disappear depending on whether gist-based intuition or verbatim-based analysis is induced. These theoretical principles are summarized and integrated in a new mathematical model that specifies how dual modes of reasoning combine to produce predictable variability in performance. In particular, we show how the most popular and extensively studied model of decision making—prospect theory—can be derived from fuzzy-trace theory by combining analytical (verbatim-based) and intuitive (gist-based) processes. PMID:22096268

  10. Improving Computational Efficiency of Model Predictive Control Genetic Algorithms for Real-Time Decision Support

    NASA Astrophysics Data System (ADS)

    Minsker, B. S.; Zimmer, A. L.; Ostfeld, A.; Schmidt, A.

    2014-12-01

    Enabling real-time decision support, particularly under conditions of uncertainty, requires computationally efficient algorithms that can rapidly generate recommendations. In this paper, a suite of model predictive control (MPC) genetic algorithms are developed and tested offline to explore their value for reducing CSOs during real-time use in a deep-tunnel sewer system. MPC approaches include the micro-GA, the probability-based compact GA, and domain-specific GA methods that reduce the number of decision variable values analyzed within the sewer hydraulic model, thus reducing algorithm search space. Minimum fitness and constraint values achieved by all GA approaches, as well as computational times required to reach the minimum values, are compared to large population sizes with long convergence times. Optimization results for a subset of the Chicago combined sewer system indicate that genetic algorithm variations with coarse decision variable representation, eventually transitioning to the entire range of decision variable values, are most efficient at addressing the CSO control problem. Although diversity-enhancing micro-GAs evaluate a larger search space and exhibit shorter convergence times, these representations do not reach minimum fitness and constraint values. The domain-specific GAs prove to be the most efficient and are used to test CSO sensitivity to energy costs, CSO penalties, and pressurization constraint values. The results show that CSO volumes are highly dependent on the tunnel pressurization constraint, with reductions of 13% to 77% possible with less conservative operational strategies. Because current management practices may not account for varying costs at CSO locations and electricity rate changes in the summer and winter, the sensitivity of the results is evaluated for variable seasonal and diurnal CSO penalty costs and electricity-related system maintenance costs, as well as different sluice gate constraint levels. These findings indicate

  11. Improved Hypoxia Modeling for Nutrient Control Decisions in the Gulf of Mexico

    NASA Technical Reports Server (NTRS)

    Habib, Shaid; Pickering, Ken; Tzortziou, Maria; Maninio, Antonio; Policelli, Fritz

    2010-01-01

    As required by the Harmful Algal Bloom and Hypoxia Research Control Act of 1998, the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force issued the 2001 Gulf Hypoxia Action Plan (updated in 2008). In response to the Gulf Hypoxia Action Plan of 2001 (updated in 2008), the EPA Gulf of Mexico Hypoxia Modeling and Monitoring Project has established a detailed model for the Mississippi-Attchafalaya River Basin which provides a capability to forecast the multi-source nutrient loading to the Gulf and the subsequent bio-geochemical processes leading to hypoxic conditions and subsequent effects on Gulf habitats and fisheries. The primary purpose of the EPA model is to characterize the impacts of nutrient management actions, or proposed actions on the spatial and temporal characteristics of the Gulf hypoxic zone. The model is expected to play a significant role in determining best practices and improved strategies for incentivizing nutrient reduction strategies, including installation of on-farm structures to reduce sediment and nutrient runoff, use of cover crops and other agricultural practices, restoration of wetlands and riparian buffers, improved waste water treatment and decreased industrial nitrogen emissions. These decisions are currently made in a fragmented way by federal, state, and local agencies, using a variety of small scale models and limited data. During the past three years, EPA has collected an enormous amount of in-situ data to be used in the model. We believe that the use of NASA satellite data products in the model and for long term validation of the model has the potential to significantly increase the accuracy and therefore the utility of the model for the decision making described above. This proposal addresses the Gulf of Mexico Alliance (GOMA) priority issue of reductions in nutrient inputs to coastal ecosystem. It further directly relates to water quality for healthy beaches and shellfish beds and wetland and coastal conservation

  12. Flash Flood Risks and Warning Decisions: A Mental Models Study of Forecasters, Public Officials, and Media Broadcasters in Boulder, Colorado.

    PubMed

    Morss, Rebecca E; Demuth, Julie L; Bostrom, Ann; Lazo, Jeffrey K; Lazrus, Heather

    2015-11-01

    Timely warning communication and decision making are critical for reducing harm from flash flooding. To help understand and improve extreme weather risk communication and management, this study uses a mental models research approach to investigate the flash flood warning system and its risk decision context. Data were collected in the Boulder, Colorado area from mental models interviews with forecasters, public officials, and media broadcasters, who each make important interacting decisions in the warning system, and from a group modeling session with forecasters. Analysis of the data informed development of a decision-focused model of the flash flood warning system that integrates the professionals' perspectives. Comparative analysis of individual and group data with this model characterizes how these professionals conceptualize flash flood risks and associated uncertainty; create and disseminate flash flood warning information; and perceive how warning information is (and should be) used in their own and others' decisions. The analysis indicates that warning system functioning would benefit from professionals developing a clearer, shared understanding of flash flood risks and the warning system, across their areas of expertise and job roles. Given the challenges in risk communication and decision making for complex, rapidly evolving hazards such as flash floods, another priority is development of improved warning content to help members of the public protect themselves when needed. Also important is professional communication with members of the public about allocation of responsibilities for managing flash flood risks, as well as improved system-wide management of uncertainty in decisions. PMID:25988286

  13. Decision analysis and risk models for land development affecting infrastructure systems.

    PubMed

    Thekdi, Shital A; Lambert, James H

    2012-07-01

    Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development. PMID:22050390

  14. Web-based environmental simulation: bridging the gap between scientific modeling and decision-making.

    PubMed

    Buytaert, Wouter; Baez, Selene; Bustamante, Macarena; Dewulf, Art

    2012-02-21

    Data availability in environmental sciences is growing rapidly. Conventional monitoring systems are collecting data at increasing spatial and temporal resolutions; satellites provide a constant stream of global observations, and citizen scientist generate local data with electronic gadgets and cheap devices. There is a need to process this stream of heterogeneous data into useful information, both for science and for decision-making. Advances in networking and computer technologies increasingly enable accessing, combining, processing, and visualizing these data. This Feature reflects upon the role of environmental models in this process. We consider models as the primary tool for data processing, pattern identification, and scenario analysis. As such, they are an essential element of science-based decision-making. The new technologies analyzed here have the potential to turn the typical top-down flow of information from scientists to users into a much more direct, interactive approach. This may accelerate the dissemination of environmental information to a larger community of users. It may also facilitate harvesting feedback, and evaluating simulations and predictions from different perspectives. However, the evolution poses challenges, not only to model development but also to the communication of model results and their assumptions, shortcomings, and errors. PMID:22260091

  15. Evaluating areas of high conservation value in Western Oregon with a decision-support model.

    PubMed

    Staus, Nancy L; Strittholt, James R; Dellasala, Dominick A

    2010-06-01

    The Northwest Forest Plan was implemented in 1994 to protect habitat for species associated with old-growth forests, including Northern Spotted Owls (Strix occidentailis caurina) in Washington, Oregon, and northern California (U.S.A.). Nevertheless, 10-year monitoring data indicate mixed success in meeting the ecological goals of the plan. We used the ecosystem management decision-support model to evaluate terrestrial and aquatic habitats across the landscape on the basis of ecological objectives of the Northwest Forest Plan, which included maintenance of late-successional and old-growth forest, recovery, and maintenance of Pacific salmon (Oncorhynchus spp.), and viability of Northern Spotted Owls. Areas of the landscape that contained habitat characteristics that supported these objectives were considered of high conservation value. We used the model to evaluate ecological condition of each of the 36, 180 township and range sections of the study area. Eighteen percent of the study area was identified as habitat of high conservation value. These areas were mostly on public lands. Many of the sections that contained habitat of exceptional conservation value were on Bureau of Land Management land that has been considered for management-plan revisions to increase timber harvests. The results of our model can be used to guide future land management in the Northwest Forest Plan area, and illustrate how decision-support models can help land managers develop strategies to better meet their goals. PMID:20184658

  16. Development of dynamical downscaling for regional climate modeling and decision aid applications

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

    Current General Circulation Models (GCMs) provide a valuable estimate of both natural and anthropogenic climate changes and variability on global scales. At the same time, future climate projections calculated with GCMs are not of sufficient spatial resolution to address regional needs. There is a growing interest from various industry sectors such as health, energy, agriculture, transportation and water planning in incorporating climate change into their strategic and development plans. To address current deficiencies in local planning and decision making with respect to regional climate change, our research is focused on developing a dynamical downscaling capability with the Weather Research and Forecasting (WRF) model and developing decision aids that translate the regional climate data into actionable information for users. Our methodology involves detailed analysis of ensemble runs performed with the WRF model initialized with the NCEP-NCAR reanalysis data and the ECHAM5 GCM. The WRF model is also run with different physical schemes and spatial resolutions, and compared with ground-based observations to delineate the uncertainties associated with the use of different initial conditions, grid sizes and physical parameterizations.

  17. A decision support for an integrated multi-scale analysis of irrigation: DSIRR.

    PubMed

    Bazzani, Guido M

    2005-12-01

    The paper presents a decision support designed to conduct an economic-environmental assessment of the agricultural activity focusing on irrigation called 'Decision Support for IRRigated Agriculture' (DSIRR). The program describes the effect at catchment scale of choices taken at micro scale by independent actors, the farmers, by simulating their decision process. The decision support (DS) has been thought of as a support tool for participatory water policies as requested by the Water Framework Directive and it aims at analyzing alternatives in production and technology, according to different market, policy and climate conditions. The tool uses data and models, provides a graphical user interface and can incorporate the decision makers' own insights. Heterogeneity in preferences is admitted since it is assumed that irrigators try to optimize personal multi-attribute utility functions, subject to a set of constraints. Consideration of agronomic and engineering aspects allows an accurate description of irrigation. Mathematical programming techniques are applied to find solutions. The program has been applied in the river Po basin (northern Italy) to analyze the impact of a pricing policy in a context of irrigation technology innovation. Water demand functions and elasticity to water price have been estimated. Results demonstrate how different areas and systems react to the same policy in quite a different way. While in the annual cropping system pricing seems effective to save the resource at the cost of impeding Water Agencies cost recovery, the same policy has an opposite effect in the perennial fruit system which shows an inelastic response to water price. The multidimensional assessment conducted clarified the trades-off among conflicting economic-social-environmental objectives, thus generating valuable information to design a more tailored mix of measures. PMID:16288826

  18. Modelling Dynamic Decision Making with the ACT-R Cognitive Architecture

    NASA Astrophysics Data System (ADS)

    Peebles, David; Banks, Adrian

    2010-12-01

    This paper describes a model of dynamic decision making in the Dynamic Stocks and Flows (DSF) task, developed using the ACT-R cognitive architecture. This task is a simple simulation of a water tank in which the water level must be kept constant whilst the inflow and outflow changes at varying rates. The basic functions of the model are based around three steps. Firstly, the model predicts the water level in the next cycle by adding the current water level to the predicted net inflow of water. Secondly, based on this projection, the net outflow of the water is adjusted to bring the water level back to the target. Thirdly, the predicted net inflow of water is adjusted to improve its accuracy in the future. If the prediction has overestimated net inflow then it is reduced, if it has underestimated net inflow it is increased. The model was entered into a model comparison competition—the Dynamic Stocks and Flows Challenge—to model human performance on four conditions of the DSF task and then subject the model to testing on five unseen transfer conditions. The model reproduced the main features of the development data reasonably well but did not reproduce human performance well under the transfer conditions. This suggests that the principles underlying human performance across the different conditions differ considerably despite their apparent similarity. Further lessons for the future development of our model and model comparison challenges are considered.

  19. Model selection for a medical diagnostic decision support system: a breast cancer detection case.

    PubMed

    West, D; West, V

    2000-11-01

    There are a number of different quantitative models that can be used in a medical diagnostic decision support system (MDSS) including parametric methods (linear discriminant analysis or logistic regression), non-parametric models (K nearest neighbor, or kernel density) and several neural network models. The complexity of the diagnostic task is thought to be one of the prime determinants of model selection. Unfortunately, there is no theory available to guide model selection. Practitioners are left to either choose a favorite model or to test a small subset using cross validation methods. This paper illustrates the use of a self-organizing map (SOM) to guide model selection for a breast cancer MDSS. The topological ordering properties of the SOM are used to define targets for an ideal accuracy level similar to a Bayes optimal level. These targets can then be used in model selection, variable reduction, parameter determination, and to assess the adequacy of the clinical measurement system. These ideas are applied to a successful model selection for a real-world breast cancer database. Diagnostic accuracy results are reported for individual models, for ensembles of neural networks, and for stacked predictors. PMID:10998586

  20. The Decision Making Ecology of placing a child into foster care: A structural equation model.

    PubMed

    Graham, J Christopher; Dettlaff, Alan J; Baumann, Donald J; Fluke, John D

    2015-11-01

    The Decision Making Ecology provided a framework for empirically testing the impact of Case, Caseworker and Organizational factors on the decision to place children in out-of-home care. The structural equation model we developed fit the data extremely well, indicating a complex relationship between the variables. The main findings indicate that Case factors, even as aggregated to the worker level, were of most importance: Percent Removed was increased in part by greater average Risk being assessed and more families on a worker's caseload being Low Income. Furthermore, removal rates were increased by lower proportions of Hispanic families on the caseload, as well as lower organizational support, and a perception of manageable workload and sufficient resources. Individual factors, i.e., variables characterizing the caseworkers themselves, were not found to directly influence the placement decision, including workers' own race/ethnicity, though various orders of mediated effects were indicated, and these are detailed. Interrelationships between variables that affect case, caseworker and organizational factors are discussed along with implications for practice. PMID:25861871

  1. Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

    PubMed

    Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W

    2016-01-01

    Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness. PMID:27618082

  2. Grambling State University's Planning/Budgeting Model: An Integral Component of a Decision Support System. SAIR Conference Paper.

    ERIC Educational Resources Information Center

    Lundy, Harold W.

    The development of a planning/budgeting model as an integral component of a decision support system is described. The case study approach is used to describe how Grambling State University (GSU) developed the model to improve its financial planning and budgeting processes. The model can be used for tactical and/or strategic planning. The model is…

  3. TIME Impact - a new user-friendly tuberculosis (TB) model to inform TB policy decisions.

    PubMed

    Houben, R M G J; Lalli, M; Sumner, T; Hamilton, M; Pedrazzoli, D; Bonsu, F; Hippner, P; Pillay, Y; Kimerling, M; Ahmedov, S; Pretorius, C; White, R G

    2016-01-01

    Tuberculosis (TB) is the leading cause of death from infectious disease worldwide, predominantly affecting low- and middle-income countries (LMICs), where resources are limited. As such, countries need to be able to choose the most efficient interventions for their respective setting. Mathematical models can be valuable tools to inform rational policy decisions and improve resource allocation, but are often unavailable or inaccessible for LMICs, particularly in TB. We developed TIME Impact, a user-friendly TB model that enables local capacity building and strengthens country-specific policy discussions to inform support funding applications at the (sub-)national level (e.g. Ministry of Finance) or to international donors (e.g. the Global Fund to Fight AIDS, Tuberculosis and Malaria).TIME Impact is an epidemiological transmission model nested in TIME, a set of TB modelling tools available for free download within the widely-used Spectrum software. The TIME Impact model reflects key aspects of the natural history of TB, with additional structure for HIV/ART, drug resistance, treatment history and age. TIME Impact enables national TB programmes (NTPs) and other TB policymakers to better understand their own TB epidemic, plan their response, apply for funding and evaluate the implementation of the response.The explicit aim of TIME Impact's user-friendly interface is to enable training of local and international TB experts towards independent use. During application of TIME Impact, close involvement of the NTPs and other local partners also builds critical understanding of the modelling methods, assumptions and limitations inherent to modelling. This is essential to generate broad country-level ownership of the modelling data inputs and results. In turn, it stimulates discussions and a review of the current evidence and assumptions, strengthening the decision-making process in general.TIME Impact has been effectively applied in a variety of settings. In South Africa, it

  4. Data Model for Multi Hazard Risk Assessment Spatial Support Decision System

    NASA Astrophysics Data System (ADS)

    Andrejchenko, Vera; Bakker, Wim; van Westen, Cees

    2014-05-01

    The goal of the CHANGES Spatial Decision Support System is to support end-users in making decisions related to risk reduction measures for areas at risk from multiple hydro-meteorological hazards. The crucial parts in the design of the system are the user requirements, the data model, the data storage and management, and the relationships between the objects in the system. The implementation of the data model is carried out entirely with an open source database management system with a spatial extension. The web application is implemented using open source geospatial technologies with PostGIS as the database, Python for scripting, and Geoserver and javascript libraries for visualization and the client-side user-interface. The model can handle information from different study areas (currently, study areas from France, Romania, Italia and Poland are considered). Furthermore, the data model handles information about administrative units, projects accessible by different types of users, user-defined hazard types (floods, snow avalanches, debris flows, etc.), hazard intensity maps of different return periods, spatial probability maps, elements at risk maps (buildings, land parcels, linear features etc.), economic and population vulnerability information dependent on the hazard type and the type of the element at risk, in the form of vulnerability curves. The system has an inbuilt database of vulnerability curves, but users can also add their own ones. Included in the model is the management of a combination of different scenarios (e.g. related to climate change, land use change or population change) and alternatives (possible risk-reduction measures), as well as data-structures for saving the calculated economic or population loss or exposure per element at risk, aggregation of the loss and exposure using the administrative unit maps, and finally, producing the risk maps. The risk data can be used for cost-benefit analysis (CBA) and multi-criteria evaluation (SMCE). The

  5. SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

    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...

  6. MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

    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...

  7. MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

    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...

  8. Modeling spatial decisions with graph theory: logging roads and forest fragmentation in the Brazilian Amazon.

    PubMed

    Walker, Robert; Arima, Eugenio; Messina, Joe; Soares-Filho, Britaldo; Perz, Stephen; Vergara, Dante; Sales, Marcio; Pereira, Ritaumaria; Castro, Williams

    2013-01-01

    This article addresses the spatial decision-making of loggers and implications for forest fragmentation in the Amazon basin. It provides a behavioral explanation for fragmentation by modeling how loggers build road networks, typically abandoned upon removal of hardwoods. Logging road networks provide access to land, and the settlers who take advantage of them clear fields and pastures that accentuate their spatial signatures. In shaping agricultural activities, these networks organize emergent patterns of forest fragmentation, even though the loggers move elsewhere. The goal of the article is to explicate how loggers shape their road networks, in order to theoretically explain an important type of forest fragmentation found in the Amazon basin, particularly in Brazil. This is accomplished by adapting graph theory to represent the spatial decision-making of loggers, and by implementing computational algorithms that build graphs interpretable as logging road networks. The economic behavior of loggers is conceptualized as a profit maximization problem, and translated into spatial decision-making by establishing a formal correspondence between mathematical graphs and road networks. New computational approaches, adapted from operations research, are used to construct graphs and simulate spatial decision-making as a function of discount rates, land tenure, and topographic constraints. The algorithms employed bracket a range of behavioral settings appropriate for areas of terras de volutas, public lands that have not been set aside for environmental protection, indigenous peoples, or colonization. The simulation target sites are located in or near so-called Terra do Meio, once a major logging frontier in the lower Amazon Basin. Simulation networks are compared to empirical ones identified by remote sensing and then used to draw inferences about factors influencing the spatial behavior of loggers. Results overall suggest that Amazonia's logging road networks induce more

  9. Quality Assurance Decisions with Air Models: A Case Study of ImputatIon of Missing Input Data Using EPA's Multi-Layer Model

    EPA Science Inventory

    Abstract Environmental models are frequently used within regulatory and policy frameworks to estimate environmental metrics that are difficult or impossible to physically measure. As important decision tools, the uncertainty associated with the model outputs should impact their ...

  10. Modelling the learning of biomechanics and visual planning for decision-making of motor actions.

    PubMed

    Cos, Ignasi; Khamassi, Mehdi; Girard, Benoît

    2013-11-01

    Recent experiments showed that the bio-mechanical ease and end-point stability associated to reaching movements are predicted prior to movement onset, and that these factors exert a significant influence on the choice of movement. As an extension of these results, here we investigate whether the knowledge about biomechanical costs and their influence on decision-making are the result of an adaptation process taking place during each experimental session or whether this knowledge was learned at an earlier stage of development. Specifically, we analysed both the pattern of decision-making and its fluctuations during each session, of several human subjects making free choices between two reaching movements that varied in path distance (target relative distance), biomechanical cost, aiming accuracy and stopping requirement. Our main result shows that the effect of biomechanics is well established at the start of the session, and that, consequently, the learning of biomechanical costs in decision-making occurred at an earlier stage of development. As a means to characterise the dynamics of this learning process, we also developed a model-based reinforcement learning model, which generates a possible account of how biomechanics may be incorporated into the motor plan to select between reaching movements. Results obtained in simulation showed that, after some pre-training corresponding to a motor babbling phase, the model can reproduce the subjects' overall movement preferences. Although preliminary, this supports that the knowledge about biomechanical costs may have been learned in this manner, and supports the hypothesis that the fluctuations observed in the subjects' behaviour may adapt in a similar fashion. PMID:23973913

  11. Decisions on control of foot-and-mouth disease informed using model predictions.

    PubMed

    Halasa, T; Willeberg, P; Christiansen, L E; Boklund, A; Alkhamis, M; Perez, A; Enøe, C

    2013-11-01

    The decision on whether or not to change the control strategy, such as introducing emergency vaccination, is perhaps one of the most difficult decisions faced by the veterinary authorities during a foot-and-mouth disease (FMD) epidemic. A simple tool that may predict the epidemic outcome and consequences would be useful to assist the veterinary authorities in the decision-making process. A previously proposed simple quantitative tool based on the first 14 days outbreaks (FFO) of FMD was used with results from an FMD simulation exercise. Epidemic outcomes included the number of affected herds, epidemic duration, geographical size and costs. The first 14 days spatial spread (FFS) was also included to further support the prediction. The epidemic data was obtained from a Danish version (DTU-DADS) of a pre-existing FMD simulation model (Davis Animal Disease Spread - DADS) adapted to model the spread of FMD in Denmark. The European Union (EU) and Danish regulations for FMD control were used in the simulation. The correlations between FFO and FFS and the additional number of affected herds after day 14 following detection of the first infected herd were 0.66 and 0.82, respectively. The variation explained by the FFO at day 14 following detection was high (P-value<0.001). This indicates that the FFO may take a part in the decision of whether or not to intensify FMD control, for instance by introducing emergency vaccination and/or pre-emptive depopulation, which might prevent a "catastrophic situation". A significant part of the variation was explained by supplementing the model with the FFS (P-value<0.001). Furthermore, the type of the index-herd was also a significant predictor of the epidemic outcomes (P-value<0.05). The results of the current study suggest that national veterinary authorities should consider to model their national situation and to use FFO and FFS to help planning and updating their contingency plans and FMD emergency control strategies. PMID:24080392

  12. Modeling the Economics of Beach Nourishment Decisions in Response to Coastal Erosion

    NASA Astrophysics Data System (ADS)

    Ware, M.; Ashton, A. D.; Hoagland, P.; Jin, D.; Kite-Powell, H.; Lorenzo-Trueba, J.

    2012-12-01

    Beaches are constantly moving and changing. The dynamic transformations of beaches are mostly the result of the erosion of sand, which can occur through movements alongshore caused by waves, movements off-shore due to storms, or submersion due to sea-level rise. Predicted climate change impacts include potential changes in storminess and accelerated sea-level rise, which will lead to increased coastal erosion. At the same time, the number of people residing in coastal communities is increasing. The risks from eroding beaches (increased coastal flooding, damage to infrastructure, and displaced residents) are therefore increasing in number and scale; and coastal residents are taking actions to protect their homes. One such action is beach nourishment, where sand is added to a resident's property in order to widen the beach. We have developed an economic model of beach nourishment decision-making to investigate the relationship between the optimal volume and timing of beach nourishment and factors such as property value, erosion rate, and initial beach width. In this model, waterfront property owners nourish a beach when the losses in net rental income exceed the costs incurred from nourishing the beach. (Rental income is a function of property value, which in turn depends upon the width of the beach.) It is assumed that erosion and sea-level rise are related. We examine different nourishment scenarios, including one-time nourishment in the first year; constant annual nourishment; and a myopic decision process in which the homeowner nourishes the beach if property losses from erosion over the next five years are expected to exceed the cost of nourishment. One-time nourishment delays property flooding for both constant and accelerating sea level rise; however, this delay is more substantial under constant sea level rise. With continual nourishment, the beach can be maintained under constant sea-level rise, provided that the erosion rate is comparable to the additional

  13. Decision model in the laser scanning system for pavement crack detection

    NASA Astrophysics Data System (ADS)

    Sun, Xiaoming; Huang, Jianping; Liu, Wanyu

    2011-12-01

    Pavement crack detection plays an important role in the pavement maintaining and management. Recently, the laser scanning technique for pavement crack detection becomes more and more popular due to its ability of discriminating dark areas, which are not caused by pavement distress such as tire marks, oil spills, and shadows. However, this technique still bears some errors for pavement crack recognition errors, thus in the present work, the factors contributed to these errors in laser scanning system are first analyzed, and then a decision model for the laser scanning pavement crack detection system based on the hypothesis test is proposed. Experimental analyses and results show that this model not only allows us to build the relationship between the contribution factors and crack detection accuracy and to provide the criteria to compare the detection accuracy for the different roads, but also can be used to judge whether the crack exists with a reasonable number of deformed light stripes. Therefore, the proposed decision model can provide guidance on the pavement crack detection and has a practical value.

  14. Development of Decision Model for Selection of Appropriate Power Generation System Using Distance Based Approach Method

    NASA Astrophysics Data System (ADS)

    Widiyanto, Anugerah; Kato, Seizo; Maruyama, Naoki

    For solving decision problems in electric generation planning, a matrix operation based deterministic quantitative model called the Distance Based Approach (DBA) has been proposed for comparing the technical-economical and environmental features of various electric power plants. The customized computer code is developed to evaluate the overall function of alternative energy systems from the performance pattern corresponding to the selected energy attributes. For the purpose of exploring the applicability and the effectiveness of the proposed model, the model is applied to decision problems concerning the selection of energy sources for power generation in Japan. The set of nine energy alternatives includes conventional and new energy technologies of oil fired-, natural gas fired-, coal fired-, nuclear power, hydropower, geothermal, solar photovoltaic, wind power and solar thermal plants. Also, a set of criteria for optimized selection includes five areas of concern; energy economy, energy security, environmental protection, socio-economic development and technological aspects for electric power generation. The result will be a ranking of alternative sources of energy based on the Euclidean composite distance of each alternative to the designated optimal source of energy.

  15. Decision support system for optimal reservoir operation modeling within sediment deposition control.

    PubMed

    Hadihardaja, Iwan K

    2009-01-01

    Suspended sediment deals with surface runoff moving toward watershed affects reservoir sustainability due to the reduction of storage capacity. The purpose of this study is to introduce a reservoir operation model aimed at minimizing sediment deposition and maximizing energy production expected to obtain optimal decision policy for both objectives. The reservoir sediment-control operation model is formulated by using Non-Linear Programming with an iterative procedure based on a multi-objective measurement in order to achieve optimal decision policy that is established in association with the development of a relationship between stream inflow and sediment rate by utilizing the Artificial Neural Network. Trade off evaluation is introduced to generate a strategy for controlling sediment deposition at same level of target ratio while producing hydroelectric energy. The case study is carried out at the Sanmenxia Reservoir in China where redesign and reconstruction have been accomplished. However, this model deals only with the original design and focuses on a wet year operation. This study will also observe a five-year operation period to show the accumulation of sediment due to the impact of reservoir storage capacity. PMID:19214002

  16. Modeling the costs of clinical decision support for genomic precision medicine.

    PubMed

    Mathias, Patrick C; Tarczy-Hornoch, Peter; Shirts, Brian H

    2016-01-01

    Clinical decision support (CDS) within the electronic health record represents a promising mechanism to provide important genomic findings within clinical workflows. To better understand the current and possible future costs of genomic CDS, we leveraged our local CDS experience to assemble a simple model with inputs such as initial cost and numbers of patients, rules, and institutions. Our model assumed efficiencies of scale and allowed us to perform a one-way sensitivity analysis of the impact of each model input. The number of patients with genomic results per institution was the only single variable that could decrease the cost of CDS per useful alert below projected genomic sequencing costs. Because of the prohibitive upfront cost of sequencing large numbers of individuals, increasing the number of institutions using genomic CDS and improving the efficiency of sharing CDS infrastructure represent the most promising paths to making genomic CDS cost-effective. PMID:27570652

  17. Modeling the costs of clinical decision support for genomic precision medicine

    PubMed Central

    Mathias, Patrick C.; Tarczy-Hornoch, Peter; Shirts, Brian H.

    2016-01-01

    Clinical decision support (CDS) within the electronic health record represents a promising mechanism to provide important genomic findings within clinical workflows. To better understand the current and possible future costs of genomic CDS, we leveraged our local CDS experience to assemble a simple model with inputs such as initial cost and numbers of patients, rules, and institutions. Our model assumed efficiencies of scale and allowed us to perform a one-way sensitivity analysis of the impact of each model input. The number of patients with genomic results per institution was the only single variable that could decrease the cost of CDS per useful alert below projected genomic sequencing costs. Because of the prohibitive upfront cost of sequencing large numbers of individuals, increasing the number of institutions using genomic CDS and improving the efficiency of sharing CDS infrastructure represent the most promising paths to making genomic CDS cost-effective. PMID:27570652

  18. Interpreting Climate Model Projections of Extreme Weather Events for Decision Makers

    NASA Astrophysics Data System (ADS)

    Vavrus, S. J.; Notaro, M.

    2014-12-01

    The proliferation of output from climate model ensembles, such as CMIP3 and CMIP5, has greatly expanded access to future projections, but there is no accepted blueprint for how this data should be interpreted. Decision makers are thus faced with difficult questions when trying to utilize such information: How reliable are the multi-model mean projections? How should the changes simulated by outlier models be treated? How can raw projections of temperature and precipitation be translated into probabilities? The multi-model average is often regarded as the most accurate single estimate of future conditions, but higher-order moments representing the variance and skewness of the distribution of projections provide important information about uncertainty. We have analyzed a set of statistically downscaled climate model projections from the CMIP3 archive to conduct an assessment of extreme weather events at a level designed to be relevant for decision makers. Our analysis uses the distribution of 13 GCM projections to derive the inter-model standard deviation (and coefficient of variation, COV), skewness, and percentile ranges for simulated changes in extreme heat, cold, and precipitation during the middle and late 21st century for the A1B emissions scenario. These metrics help to establish the overall confidence level across the entire range of projections (via the inter-model COV), relative confidence in the simulated high-end versus low-end changes (via skewness), and probabilistic uncertainty bounds derived from a bootstrapping technique. Over our analysis domain centered on the United States Midwest, some primary findings include: (1) Greater confidence in projections of less extreme cold than more extreme heat and intense precipitation, (2) Greater confidence in the low-end than high-end projections of extreme heat, and (3) Higher spatial and temporal variability in the confidence of projected increases of heavy precipitation. In addition, our bootstrapping

  19. Urban Climate Resilience - Connecting climate models with decision support cyberinfrastructure using open standards

    NASA Astrophysics Data System (ADS)

    Bermudez, L. E.; Percivall, G.; Idol, T. A.

    2015-12-01

    Experts in climate modeling, remote sensing of the Earth, and cyber infrastructure must work together in order to make climate predictions available to decision makers. Such experts and decision makers worked together in the Open Geospatial Consortium's (OGC) Testbed 11 to address a scenario of population displacement by coastal inundation due to the predicted sea level rise. In a Policy Fact Sheet "Harnessing Climate Data to Boost Ecosystem & Water Resilience", issued by White House Office of Science and Technology (OSTP) in December 2014, OGC committed to increase access to climate change information using open standards. In July 2015, the OGC Testbed 11 Urban Climate Resilience activity delivered on that commitment with open standards based support for climate-change preparedness. Using open standards such as the OGC Web Coverage Service and Web Processing Service and the NetCDF and GMLJP2 encoding standards, Testbed 11 deployed an interoperable high-resolution flood model to bring climate model outputs together with global change assessment models and other remote sensing data for decision support. Methods to confirm model predictions and to allow "what-if-scenarios" included in-situ sensor webs and crowdsourcing. A scenario was in two locations: San Francisco Bay Area and Mozambique. The scenarios demonstrated interoperation and capabilities of open geospatial specifications in supporting data services and processing services. The resultant High Resolution Flood Information System addressed access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios examined the feasibility and capability of existing OGC geospatial Web service specifications in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Results of this testbed included identification of standards and best practices that help researchers and cities deal with climate-related issues

  20. Application of a plume model for decision makers' situation awareness during an outdoor airborne HAZMAT release.

    PubMed

    Meris, Ronald G; Barbera, Joseph A

    2014-01-01

    In a large-scale outdoor, airborne, hazardous materials (HAZMAT) incident, such as ruptured chlorine rail cars during a train derailment, the local Incident Commanders and HAZMAT emergency responders must obtain accurate information quickly to assess the situation and act promptly and appropriately. HAZMAT responders must have a clear understanding of key information and how to integrate it into timely and effective decisions for action planning. This study examined the use of HAZMAT plume modeling as a decision support tool during incident action planning in this type of extreme HAZMAT incident. The concept of situation awareness as presented by Endsley's dynamic situation awareness model contains three levels: perception, comprehension, and projection. It was used to examine the actions of incident managers related to adequate data acquisition, current situational understanding, and accurate situation projection. Scientists and engineers have created software to simulate and predict HAZMAT plume behavior, the projected hazard impact areas, and the associated health effects. Incorporating the use of HAZMAT plume projection modeling into an incident action plan may be a complex process. The present analysis used a mixed qualitative and quantitative methodological approach and examined the use and limitations of a "HAZMAT Plume Modeling Cycle" process that can be integrated into the incident action planning cycle. HAZMAT response experts were interviewed using a computer-based simulation. One of the research conclusions indicated the "HAZMAT Plume Modeling Cycle" is a critical function so that an individual/team can be tasked with continually updating the hazard plume model with evolving data, promoting more accurate situation awareness. PMID:25350360