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Sample records for multi-attribute decision model

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

    DTIC Science & Technology

    1983-08-01

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

  2. Applications of qualitative multi-attribute decision models in health care.

    PubMed

    Bohanec, M; Zupan, B; Rajkovic, V

    2000-09-01

    Hierarchical decision models are a general decision support methodology aimed at the classification or evaluation of options that occur in decision-making processes. They are also important for the analysis, simulation and explanation of options. Decision models are typically developed through the decomposition of complex decision problems into smaller and less complex subproblems; the result of such decomposition is a hierarchical structure that consists of attributes and utility functions. This article presents an approach to the development and application of qualitative hierarchical decision models that is based on DEX, an expert system shell for multi-attribute decision support. The distinguishing characteristics of DEX are the use of qualitative (symbolic) attributes, and 'if-then' decision rules. Also, DEX provides a number of methods for the analysis of models and options, such as selective explanation and what-if analysis. We demonstrate the applicability and flexibility of the approach presenting four real-life applications of DEX in health care: assessment of breast cancer risk, assessment of basic living activities in community nursing, risk assessment in diabetic foot care, and technical analysis of radiogram errors. In particular, we highlight and justify the importance of knowledge presentation and option analysis methods for practical decision-making. We further show that, using a recently developed data mining method called HINT, such hierarchical decision models can be discovered from retrospective patient data.

  3. Hierarchical multi-attribute decision models and their application in health care.

    PubMed

    Bohanec, M; Zupan, B; Rajkovic, V

    1999-01-01

    Hierarchical decision models are developed through decomposition of complex decision problems into smaller and less complex subproblems. They are aimed at the classification or evaluation of options and can be used for analysis, simulation and explanation. This paper presents a set of methods for the construction and application of qualitative hierarchical decision models in health care. We present the results of four ongoing projects in oncology, radiology, community nursing and diabetic foot treatment.

  4. Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

    PubMed

    Li, Yan

    2017-05-25

    The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

  5. A multi-attribute-utility-theory model that minimizes interview-data requirements: A consolidation of space launch decisions

    NASA Astrophysics Data System (ADS)

    Staats, Raymond W.

    1994-12-01

    This research uses multi-attribute utility theory (MAUT) to define a mathematical representation of a decision maker's utility associated with a satellite system. While developing the survey instrument, we focused on making it simpler to administer, primarily by eliminating the use of lottery questions. These simplifications enabled us to shorten our interview with the decision maker to under two hours for a rather complex model. The MAUT model gives National Air Intelligence Center (NAIC) analysts the ability to rank order satellite systems using the common measurement scale of 'utiles.' This tool allows a meaningful comparison of vastly different satellites. Properly prioritized launch of space assets will be key to maintaining our capabilities in the long term. The ordering methodology of this model was extended to a multi-criterion optimization (MCO) problem to demonstrate its potential use in prioritizing and scheduling limited launch resources. The results of these two case studies and the MCO application are combined to develop some characterizations of a theoretical group utility function. Most complex decisions are made by groups rather than by an individual. This research concludes with some insights on the impact of an individual's preferences on a decision that is ultimately made by the group.

  6. A Multi-Attribute-Utility-Theory Model that Minimizes Interview-Data Requirements: A Consolidation of Space Launch Decisions.

    DTIC Science & Technology

    1994-12-01

    acceptable. Satellite data was then added to the , mode ! to obhtali;n A c-Ardinni rnnk ,rderina nf the sateilites. The model rankings were then compared to...K-c is Cassini , NASA’s mission to Saturn, scheduled for take- off during October 1997. Launches K-d and K-e are typical payloads whose identities are...equivalence with the original utility function. We conclude tha;, in genera!. the sinmple r addii , mode ! is nelt appropriate to substitute for the

  7. Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection.

    PubMed

    Lin, Hui; Wang, Zhou-Jing

    2017-09-17

    Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice.

  8. Measuring Nursing Practice Models using Multi-Attribute Utility theory.

    PubMed

    Brennan, P F; Anthony, M K

    2000-10-01

    Nursing Practice Models (NPMs) represent the structural and contextual features that exist within any group practice of nursing. Currently, measurement of NPMs relies on costly and nonreproducible global judgments by experts. Quantitative measurement techniques are needed to provide a useful evaluation of nursing practice. Guided by Multi-Attribute Utility theory (MAU theory), an expert panel identified 24 factors representative of N PMs. The factors became elements in a computational index that, when summed, assigns a score to a given nursing unit reflecting the extent to which that unit's nursing practice model achieves the nursing professional ideal. Initial validation of the index and its elements consisted of comparing assessments of 40 nursing units generated by the index with a global evaluation provided by each of the expert panelists who proposed the model factors. Pearson correlations between the index-generated scores and the global assigned scores provided evidence supporting the preliminary validation of the index.

  9. 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.

  10. 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

  11. Multi-Attribute Decision Making (MADM) in Analysis of a Future Sensor Capability

    DTIC Science & Technology

    2014-11-17

    Excellence (MSCoE) Fort Leonard Wood , MO Approved for public release; distribution is unlimited. 1 Multi-Attribute Decision Making (MADM) in...Battle Lab (MSBL) Capabilities Development and Integration Directorate (CDID) Maneuver Support Center of Excellence (MSCoE) Fort Leonard Wood , MO 8...Backup Background • MSBL supports EN, MP, CM Schools and the Maneuver Support and Protection Warfighting Function (WfF). • MSBL manages a

  12. A multi-attribute model of prostate cancer patient's preferences for health states.

    PubMed

    Chapman, G B; Elstein, A S; Kuzel, T M; Nadler, R B; Sharifi, R; Bennett, C L

    1999-05-01

    Multi-attribute utility theory (MAUT) provides a way to model decisions involving trade-offs among different aspects or goals of a problem. We used MAUT to model prostate cancer patients' preferences for their own health state and we compared this model to patients' global judgments of health state utility. 57 patients with prostate cancer (mean age = 70) at two Chicago Veterans Administration health clinics were asked to evaluate health states described in terms of five health attributes affected by prostate cancer: pain, mood, sexual function, bladder and bowel function, and fatigue and energy. Each attribute had three levels that were used to form three clinically realistic health state descriptions (A = high, B = moderate, C = low). A fourth personalized health description (P) matched the patient's current health. We first measured patients' preferences using time trade-off (TTO) judgments for the three health states (A, B, and C) and for their own current health state (P). The TTO for the patient's own health state (P) was standardized by comparing it to TTO judgments for states A and C. We next constructed a multi-attribute model using the relative importance of the five attributes. The MAU scores were moderately correlated with the TTO preference judgments for the personalized state (Pearson r = 0.38, N = 57, p < 0.01). Thus, patients' preference judgments are moderately consistent and systematic. MAUT appears to be a potentially feasible method for evaluating preferences of prostate cancer patients and may prove helpful in assisting with patient decision making.

  13. [A multi-measure analysis of the similarity, attraction, and compromise effects in multi-attribute decision making].

    PubMed

    Tsuzuki, Takashi; Matsui, Hiroshi; Kikuchi, Manabu

    2012-12-01

    In multi-attribute decision making, the similarity, attraction, and compromise effects warrant specific investigation as they cause violations of principles in rational choice. In order to investigate these three effects simultaneously, we assigned 145 undergraduates to three context effect conditions. We requested them to solve the same 20 hypothetical purchase problems, each of which had three alternatives described along two attributes. We measured their choices, confidence ratings, and response times. We found that manipulating the third alternative had significant context effects for choice proportions and confidence ratings in all three conditions. Furthermore, the attraction effect was the most prominent with regard to choice proportions. In the compromise effect condition, although the choice proportion of the third alternative was high, the confidence rating was low and the response time was long. These results indicate that the relationship between choice proportions and confidence ratings requires further theoretical investigation. They also suggest that a combination of experimental and modeling studies is imperative to reveal the mechanisms underlying the context effects in multi-attribute, multi-alternative decision making.

  14. Multi-attribute, multi-alternative models of choice: Choice, reaction time, and process tracing.

    PubMed

    Cohen, Andrew L; Kang, Namyi; Leise, Tanya L

    2017-11-01

    The first aim of this research is to compare computational models of multi-alternative, multi-attribute choice when attribute values are explicit. The choice predictions of utility (standard random utility & weighted valuation), heuristic (elimination-by-aspects, lexicographic, & maximum attribute value), and dynamic (multi-alternative decision field theory, MDFT, & a version of the multi-attribute linear ballistic accumulator, MLBA) models are contrasted on both preferential and risky choice data. Using both maximum likelihood and cross-validation fit measures on choice data, the utility and dynamic models are preferred over the heuristic models for risky choice, with a slight overall advantage for the MLBA for preferential choice. The response time predictions of these models (except the MDFT) are then tested. Although the MLBA accurately predicts response time distributions, it only weakly accounts for stimulus-level differences. The other models completely fail to account for stimulus-level differences. Process tracing measures, i.e., eye and mouse tracking, were also collected. None of the qualitative predictions of the models are completely supported by that data. These results suggest that the models may not appropriately represent the interaction of attention and preference formation. To overcome this potential shortcoming, the second aim of this research is to test preference-formation assumptions, independently of attention, by developing the models of attentional sampling (MAS) model family which incorporates the empirical gaze patterns into a sequential sampling framework. An MAS variant that includes attribute values, but only updates the currently viewed alternative and does not contrast values across alternatives, performs well in both experiments. Overall, the results support the dynamic models, but point to the need to incorporate a framework that more accurately reflects the relationship between attention and the preference-formation process

  15. 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.

  16. 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

  17. Limitations of Exemplar Models of Multi-Attribute Probabilistic Inference

    ERIC Educational Resources Information Center

    Nosofsky, Robert M.; Bergert, F. Bryabn

    2007-01-01

    Observers were presented with pairs of objects varying along binary-valued attributes and learned to predict which member of each pair had a greater value on a continuously varying criterion variable. The predictions from exemplar models of categorization were contrasted with classic alternative models, including generalized versions of a…

  18. Multi-Attribute Utility Theory to Assist Top-Level Acquisition Decision-Making

    DTIC Science & Technology

    1981-12-01

    emphasize the judgment handling capability of MAUT by saying: Basing a capability measure on multiattribute utility theory capitalizes on the notion...NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS FMULTI-ATTRIBUTE UTILITY THEORY TO ASSIST TOP-LEVEL ACQUIS ITION DECIS ION-MKN by Ran Goreni...CATALOG MUMEU 4. TITL (1d S ufiDIO) . ?YoE 011 REPORT & PERIOD COVENEO Multi-Attribute Utility Theory to master’s thesis; Assist Top-Level Acquisition

  19. Informing vaccine decision-making: A strategic multi-attribute ranking tool for vaccines-SMART Vaccines 2.0.

    PubMed

    Knobler, Stacey; Bok, Karin; Gellin, Bruce

    2017-01-20

    SMART Vaccines 2.0 software is being developed to support decision-making among multiple stakeholders in the process of prioritizing investments to optimize the outcomes of vaccine development and deployment. Vaccines and associated vaccination programs are one of the most successful and effective public health interventions to prevent communicable diseases and vaccine researchers are continually working towards expanding targets for communicable and non-communicable diseases through preventive and therapeutic modes. A growing body of evidence on emerging vaccine technologies, trends in disease burden, costs associated with vaccine development and deployment, and benefits derived from disease prevention through vaccination and a range of other factors can inform decision-making and investment in new and improved vaccines and targeted utilization of already existing vaccines. Recognizing that an array of inputs influences these decisions, the strategic multi-attribute ranking method for vaccines (SMART Vaccines 2.0) is in development as a web-based tool-modified from a U.S. Institute of Medicine Committee effort (IOM, 2015)-to highlight data needs and create transparency to facilitate dialogue and information-sharing among decision-makers and to optimize the investment of resources leading to improved health outcomes. Current development efforts of the SMART Vaccines 2.0 framework seek to generate a weighted recommendation on vaccine development or vaccination priorities based on population, disease, economic, and vaccine-specific data in combination with individual preference and weights of user-selected attributes incorporating valuations of health, economics, demographics, public concern, scientific and business, programmatic, and political considerations. Further development of the design and utility of the tool is being carried out by the National Vaccine Program Office of the Department of Health and Human Services and the Fogarty International Center of the

  20. 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

  1. 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.

  2. 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.

  3. Attribute preference and selection in multi-attribute decision making: implications for unconscious and conscious thought.

    PubMed

    Srinivasan, Narayanan; Mukherjee, Sumitava

    2010-06-01

    Unconscious thought theory (UTT) states that all information is taken into account and the attributes are weighted optimally resulting in better decisions in complex decision problems during unconscious thought. Very few studies have investigated the actual amount of information processed in the unconscious thought condition. We hypothesized that only a small subset of information might be considered during unconscious thought (like conscious thought). To test this possibility and to explore the way attribute information is selected and combined, we performed computer simulations on the datasets used by previous researchers. The simulations showed that considering a small subset (3-4) of attributes, yields results comparable to previous studies. There is no need to posit infinite capacity in the unconscious thought condition. The results also suggest that weight information is used for attribute selection that could potentially explain the difficulties in replicating the deliberation-without-attention effect. 2010 Elsevier Inc. All rights reserved.

  4. 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.

  5. Deciding how to decide: ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making.

    PubMed

    Fellows, Lesley K

    2006-04-01

    Ventromedial frontal lobe (VMF) damage is associated with impaired decision making. Recent efforts to understand the functions of this brain region have focused on its role in tracking reward, punishment and risk. However, decision making is complex, and frontal lobe damage might be expected to affect it at other levels. This study used process-tracing techniques to explore the effect of VMF damage on multi-attribute decision making under certainty. Thirteen subjects with focal VMF damage were compared with 11 subjects with frontal damage that spared the VMF and 21 demographically matched healthy control subjects. Participants chose rental apartments in a standard information board task drawn from the literature on normal decision making. VMF subjects performed the decision making task in a way that differed markedly from all other groups, favouring an 'alternative-based' information acquisition strategy (i.e. they organized their information search around individual apartments). In contrast, both healthy control subjects and subjects with damage predominantly involving dorsal and/or lateral prefrontal cortex pursued primarily 'attribute-based' search strategies (in which information was acquired about categories such as rent and noise level across several apartments). This difference in the pattern of information acquisition argues for systematic differences in the underlying decision heuristics and strategies employed by subjects with VMF damage, which in turn may affect the quality of their choices. These findings suggest that the processes supported by ventral and medial prefrontal cortex need to be conceptualized more broadly, to account for changes in decision making under conditions of certainty, as well as uncertainty, following damage to these areas.

  6. 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.

  7. A Multi-Attribute Evaluation Model for Air Force Engineering Projects

    DTIC Science & Technology

    1992-05-01

    of Defense (DOD) are examining ways to utilize multiattribute decision models in the project and source selection processes. Results of some of these... multiattribute decision techniques have been examined by others in DOD to see how they may be utilized in various stages of the procurement process. The... Utility Theory (MAUT) and the AHP to determine how they could be applied to source selection in an Air Force system program office. 18 Additionally

  8. A Multi-Attributes Analysis Vignette For Warfighting Experiments

    DTIC Science & Technology

    2007-06-01

    elephants” – Harvard Business Review on Decision Making, 2001 By applying the Multi-Attributes Utility Theory to analysis of a modeled system...1976 8. US Army, “Guideline for Army Analysis”, 1999 9. Harvard Business Review on Decision Making, 2001 10. US Army, “Verification, Validation, and

  9. A Multi-Attributes Analysis Vignette for Warfighting Experiments

    DTIC Science & Technology

    2007-06-01

    elephants” – Harvard Business Review on Decision Making, 2001 By applying the Multi-Attributes Utility Theory to analysis of a modeled system...1976 8. US Army, “Guideline for Army Analysis”, 1999 9. Harvard Business Review on Decision Making, 2001 10. US Army, “Verification, Validation, and

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

    SciTech Connect

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

    1998-11-01

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

  11. Modeling recreation participants' willingness to substitute using multi-attribute indicators

    Treesearch

    Yung-Ping (Emilio) Tseng; Robert B. Ditton

    2008-01-01

    A logistic regression was used to predict anglers' resource-substitution decisions based on three dimensions of recreation specialization (behavior, skill and knowledge, and commitment), two dimensions of place attachment (place identity and place dependence), and three demographic indicators. Results indicated that place dependence was the most effective...

  12. Robust Sensitivity Analysis for Multi-Attribute Deterministic Hierarchical Value Models

    DTIC Science & Technology

    2002-03-01

    Method (Satisfying Method) Disjunctive Method Standart Level Elimination by Aspect Lexicograhic Semi order Lexicographic Method Ordinal Weigted Sum...framework for sensitivity analysis of hierarchical additive value models and standardizes the sensitivity analysis notation and terminology . Finally

  13. 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.

  14. Multi Stakeholders' Attitudes toward Bt rice in Southwest, Iran: Application of TPB and Multi Attribute Models.

    PubMed

    Ghoochani, Omid M; Ghanian, Mansour; Baradaran, Masoud; Azadi, Hossein

    2017-03-01

    Organisms that have been genetically engineered and modified (GM) are referred to as genetically modified organisms (GMOs). Bt crops are plants that have been genetically modified to produce certain proteins from the soil bacteria Bacillus thuringiensis (Bt), which makes these plants resistant to certain lepidopteran and coleopteran species. Genetically Modified (GM) rice was produced in 2006 by Iranian researchers from Tarom Mowla'ii and has since been called 'Bt rice'. As rice is an important source of food for over 3 billion inhabitants on Earth, this study aims to use a correlational survey in order to shed light on the predicting factors relating to the extent of stakeholders' behavioral intentions towards Bt rice. It is assumed and the results confirm that "attitudes toward GM crops" can be used as a bridge in the Attitude Model and the Behavioral Intention Model in order to establish an integrated model. To this end, a case study was made of the Southwest part of Iran in order to verify this research model. This study also revealed that as a part of the integrated research framework in the Behavior Intention Model both constructs of attitude and the subjective norm of the respondents serve as the predicting factors of stakeholders' intentions of working with Bt rice. In addition, the Attitude Model, as the other part of the integrated research framework, showed that the stakeholders' attitudes toward Bt rice can only be determined by the perceived benefits (e.g. positive outcomes) of Bt rice.

  15. A colored petri nets based workload evaluation model and its validation through Multi-Attribute Task Battery-II.

    PubMed

    Wang, Peng; Fang, Weining; Guo, Beiyuan

    2017-04-01

    This paper proposed a colored petri nets based workload evaluation model. A formal interpretation of workload was firstly introduced based on the process that reflection of petri nets components to task. A petri net based description of Multiple Resources theory was given by comprehending it from a new angle. A new application of VACP rating scales named V/A-C-P unit, and the definition of colored transitions were proposed to build a model of task process. The calculation of workload mainly has the following four steps: determine token's initial position and values; calculate the weight of directed arcs on the basis of the rules proposed; calculate workload from different transitions, and correct the influence of repetitive behaviors. Verify experiments were carried out based on Multi-Attribute Task Battery-II software. Our results show that there is a strong correlation between the model values and NASA -Task Load Index scores (r=0.9513). In addition, this method can also distinguish behavior characteristics between different people.

  16. A Three Stage Multi-attribute Procurement Auction: A Proposal for Department of Defense (DoD) Vendor Selection Decisions.

    DTIC Science & Technology

    2010-04-30

    Postgraduate School,Code 64,699 Dyer Rd,Monterey,CA,93943 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES...Graduate School of Business and Public Policy Naval Postgraduate School 555 Dyer Road, Room 332 Monterey, CA 93943-5103 Tel: (831) 656-2092 Fax...699 Dyer Rd. Monterey, CA 93943 fmelese@nps.edu Office: 831-656-2009 Jay Simon—Dr. Simon is an Assistant Professor of Decision Science at the

  17. Hierarchical competitions subserving multi-attribute choice

    PubMed Central

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

    2015-01-01

    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 competitive inhibition may occur in early valuation stages, before option selection. Here, we show 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 competition within-attribute, competition between attributes, and option selection. This multi-layered inhibition framework challenges the assumption that option values are computed before choice. Instead our results indicate a canonical competition mechanism throughout all stages of a processing hierarchy, not simply at a final choice stage. PMID:25306549

  18. 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…

  19. Multi-attribute utility function or statistical inference models: a comparison of health state valuation models using the HUI2 health state classification system.

    PubMed

    Stevens, Katherine; McCabe, Christopher; Brazier, John; Roberts, Jennifer

    2007-09-01

    A key issue in health state valuation modelling is the choice of functional form. The two most frequently used preference based instruments adopt different approaches; one based on multi-attribute utility theory (MAUT), the other on statistical analysis. There has been no comparison of these alternative approaches in the context of health economics. We report a comparison of these approaches for the health utilities index mark 2. The statistical inference model predicts more accurately than the one based on MAUT. We discuss possible explanations for the differences in performance, the importance of the findings, and implications for future research.

  20. Qualitatively Coherent Representation Makes Decision-Making Easier with Binary-Colored Multi-Attribute Tables: An Eye-Tracking Study

    PubMed Central

    Morii, Masahiro; Ideno, Takashi; Takemura, Kazuhisa; Okada, Mitsuhiro

    2017-01-01

    We aimed to identify the ways in which coloring cells affected decision-making in the context of binary-colored multi-attribute tables, using eye movement data. In our black-white attribute tables, the value of attributes was limited to two (with a certain threshold for each attribute) and each cell of the table was colored either black or white on the white background. We compared the two natural ways of systematic color assignment: “quantitatively coherent” ways and “qualitatively coherent” ways (namely, the ways in which the black-white distinction represented the quantitative amount distinction, and the ways in which the black-white distinction represented the quality distinction). The former consists of the following two types: (Type 1) “larger is black,” where the larger value-level was represented by black, and “smaller is white,” and (Type 2) “smaller is black.” The latter consisted of the following two types: (Type 3) “better is black,” and (Type 4) “worse is black.” We obtained the following two findings. [Result 1] The qualitatively coherent black-white tables (Types 3 and 4) made decision-making easier than the quantitatively coherent ones (Types 1 and 2). [Result 2] Among the two qualitatively coherent types, the “black is better” tables (Type 3) made decision making easier; in fact, the participants focused on the more important (black) cells in the case of “black is better” tables (Type 3) while they did not focus enough on the more important (white) ones in the case of the “white is better” tables (Type 4). We also examined some measures of eye movement patterns and showed that these measures supported our hypotheses. The data showed differences in the eye movement patterns between the first and second halves of each trial, which indicated the phased or combined decision strategies taken by the participants. PMID:28861020

  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. Selecting the Best Thermal Building Insulation Using a Multi-Attribute Decision Model

    DTIC Science & Technology

    2008-03-01

    34x 16" SOC 1/2" drywall )a Resistance to Infiltrationc Flame Spreada Smoke Generationa Owens Corning Fiberglass Batt (.82 lb/ft^3...13  Figure 2.2. Impact of temperature gradient on thermal resistance of loose-fill fiberglass ...R-value of loose-fill fiberglass was consistent with the rated R-value in the presence of a 22 degree Fahrenheit differential. However, a 53 degree

  3. Multi-attribute preference functions. Health Utilities Index.

    PubMed

    Torrance, G W; Furlong, W; Feeny, D; Boyle, M

    1995-06-01

    Multi-attribute utility theory, an extension of conventional utility theory, can be applied to model preference scores for health states defined by multi-attribute health status classification systems. The type of preference independence among the attributes determines the type of preference function required: additive, multiplicative or multilinear. In addition, the type of measurement instrument used determines the type of preference score obtained: value or utility. Multi-attribute utility theory has been applied to 2 recently developed multi-attribute health status classification systems, the Health Utilities Index (HUI) Mark II and Mark III systems. Results are presented for the Mark II system, and ongoing research is described for the Mark III system. The theory is also discussed in the context of other well known multi-attribute systems. The HUI system is an efficient method of determining a general public-based utility score for a specified health outcome or for the health status of an individual. In clinical populations, the scores can be used to provide a single summary measure of health-related quality of life. In cost-utility analyses, the scores can be used as quality weights for calculating quality-adjusted life years. In general populations, the measure can be used as quality weights for determining population health expectancy.

  4. 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.

  5. Graph Estimation From Multi-Attribute Data

    PubMed Central

    Kolar, Mladen; Liu, Han; Xing, Eric P.

    2014-01-01

    Undirected graphical models are important in a number of modern applications that involve exploring or exploiting dependency structures underlying the data. For example, they are often used to explore complex systems where connections between entities are not well understood, such as in functional brain networks or genetic networks. Existing methods for estimating structure of undirected graphical models focus on scenarios where each node represents a scalar random variable, such as a binary neural activation state or a continuous mRNA abundance measurement, even though in many real world problems, nodes can represent multivariate variables with much richer meanings, such as whole images, text documents, or multi-view feature vectors. In this paper, we propose a new principled framework for estimating the structure of undirected graphical models from such multivariate (or multi-attribute) nodal data. The structure of a graph is inferred through estimation of non-zero partial canonical correlation between nodes. Under a Gaussian model, this strategy is equivalent to estimating conditional independencies between random vectors represented by the nodes and it generalizes the classical problem of covariance selection (Dempster, 1972). We relate the problem of estimating non-zero partial canonical correlations to maximizing a penalized Gaussian likelihood objective and develop a method that efficiently maximizes this objective. Extensive simulation studies demonstrate the effectiveness of the method under various conditions. We provide illustrative applications to uncovering gene regulatory networks from gene and protein profiles, and uncovering brain connectivity graph from positron emission tomography data. Finally, we provide sufficient conditions under which the true graphical structure can be recovered correctly. PMID:25620892

  6. Clinical decision modeling system

    PubMed Central

    Shi, Haiwen; Lyons-Weiler, James

    2007-01-01

    Background Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified. Methods We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer. Results Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to

  7. You Only Die Once: Accounting for Multi-Attributable Mortality Risks in Multi-Disease Models for Health-Economic Analyses.

    PubMed

    Hoogenveen, Rudolf T; Boshuizen, Hendriek C; Engelfriet, Peter M; van Baal, Pieter Hm

    2016-07-12

    Mortality rates in Markov models, as used in health economic studies, are often estimated from summary statistics that allow limited adjustment for confounders. If interventions are targeted at multiple diseases and/or risk factors, these mortality rates need to be combined in a single model. This requires them to be mutually adjusted to avoid 'double counting' of mortality. We present a mathematical modeling approach to describe the joint effect of mutually dependent risk factors and chronic diseases on mortality in a consistent manner. Most importantly, this approach explicitly allows the use of readily available external data sources. An additional advantage is that existing models can be smoothly expanded to encompass more diseases/risk factors. To illustrate the usefulness of this method and how it should be implemented, we present a health economic model that links risk factors for diseases to mortality from these diseases, and describe the causal chain running from these risk factors (e.g., obesity) through to the occurrence of disease (e.g., diabetes, CVD) and death. Our results suggest that these adjustment procedures may have a large impact on estimated mortality rates. An improper adjustment of the mortality rates could result in an underestimation of disease prevalence and, therefore, disease costs.

  8. 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

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

    USDA-ARS?s Scientific Manuscript database

    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...

  10. Trusted Advisors, Decision Models and Other Keys to Communicating Science to Decision Makers

    NASA Astrophysics Data System (ADS)

    Webb, E.

    2006-12-01

    Water resource management decisions often involve multiple parties engaged in contentious negotiations that try to navigate through complex combinations of legal, social, hydrologic, financial, and engineering considerations. The standard approach for resolving these issues is some form of multi-party negotiation, a formal court decision, or a combination of the two. In all these cases, the role of the decision maker(s) is to choose and implement the best option that fits the needs and wants of the community. However, each path to a decision carries the risk of technical and/or financial infeasibility as well as the possibility of unintended consequences. To help reduce this risk, decision makers often rely on some type of predictive analysis from which they can evaluate the projected consequences of their decisions. Typically, decision makers are supported in the analysis process by trusted advisors who engage in the analysis as well as the day to day tasks associated with multi-party negotiations. In the case of water resource management, the analysis is frequently a numerical model or set of models that can simulate various management decisions across multiple systems and output results that illustrate the impact on areas of concern. Thus, in order to communicate scientific knowledge to the decision makers, the quality of the communication between the analysts, the trusted advisor, and the decision maker must be clear and direct. To illustrate this concept, a multi-attribute decision analysis matrix will be used to outline the value of computer model-based collaborative negotiation approaches to guide water resources decision making and communication with decision makers. In addition, the critical role of the trusted advisor and other secondary participants in the decision process will be discussed using examples from recent water negotiations.

  11. Design of a Seismic Reflection Multi-Attribute Workflow for Delineating Karst Pore Systems Using Neural Networks and Statistical Dimensionality Reduction Techniques

    NASA Astrophysics Data System (ADS)

    Ebuna, D. R.; Kluesner, J.; Cunningham, K. J.; Edwards, J. H.

    2016-12-01

    An effective method for determining the approximate spatial extent of karst pore systems is critical for hydrological modeling in such environments. When using geophysical techniques, karst features are especially challenging to constrain due to their inherent heterogeneity and complex seismic signatures. We present a method for mapping these systems using three-dimensional seismic reflection data by combining applications of machine learning and modern data science. Supervised neural networks (NN) have been successfully implemented in seismic reflection studies to produce multi-attributes (or meta-attributes) for delineating faults, chimneys, salt domes, and slumps. Using a seismic reflection dataset from southeast Florida, we develop an objective multi-attribute workflow for mapping karst in which potential interpreter bias is minimized by applying linear and non-linear data transformations for dimensionality reduction. This statistical approach yields a reduced set of input seismic attributes to the NN by eliminating irrelevant and overly correlated variables, while still preserving the vast majority of the observed data variance. By initiating the supervised NN from an eigenspace that maximizes the separation between classes, the convergence time and accuracy of the computations are improved since the NN only needs to recognize small perturbations to the provided decision boundaries. We contend that this 3D seismic reflection, data-driven method for defining the spatial bounds of karst pore systems provides great value as a standardized preliminary step for hydrological characterization and modeling in these complex geological environments.

  12. 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

  13. 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.

  14. A Checklist for Reporting Valuation Studies of Multi-Attribute Utility-Based Instruments (CREATE).

    PubMed

    Xie, Feng; Pickard, A Simon; Krabbe, Paul F M; Revicki, Dennis; Viney, Rosalie; Devlin, Nancy; Feeny, David

    2015-08-01

    Multi-attribute utility-based instruments (MAUIs) assess health status and provide an index score on the full health-dead scale, and are widely used to support reimbursement decisions for new healthcare interventions worldwide. A valuation study is a key part of the development of MAUIs, with the primary goal of developing a scoring algorithm through eliciting societal preferences. We developed the 21-item Checklist for REporting VAluaTion StudiEs (CREATE) by following a modified two-round Delphi panel approach plus an email survey. CREATE is intended to promote good reporting practice as well as guiding developers to thoroughly and carefully think through key methodological elements in designing valuation studies.

  15. Multi-attribute Regret-Based Dynamic Pricing

    NASA Astrophysics Data System (ADS)

    Jumadinova, Janyl; Dasgupta, Prithviraj

    In this paper, we consider the problem of dynamic pricing by a set of competing sellers in an information economy where buyers differentiate products along multiple attributes, and buyer preferences can change temporally. Previous research in this area has either focused on dynamic pricing along a limited number of (e.g. binary) attributes, or, assumes that each seller has access to private information such as preference distribution of buyers, and profit/price information of other sellers. However, in real information markets, private information about buyers and sellers cannot be assumed to be available a priori. Moreover, due to the competition between sellers, each seller faces a tradeoff between accuracy and rapidity of the pricing mechanism. In this paper, we describe a multi-attribute dynamic pricing algorithm based on minimax regret that can be used by a seller's agent called a pricebot, to maximize the seller's utility. Our simulation results show that the minimax regret based dynamic pricing algorithm performs significantly better than other algorithms for rapidly and dynamically tracking consumer attributes without using any private information from either buyers or sellers.

  16. 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

  17. Multi Criteria Decision Support Model for the Turkish Air Force Personnel Course/Education Planning System

    DTIC Science & Technology

    2011-03-01

    Making, Multiattribute Utility Theory : The Next Ten Years”. Management Science, 38(5):645–654, 1992. Fulop, Janos. “Introduction to Decision Making... Utility Theory . . . . . . . . . . . . . . . . . 21 2.2.4 ELECTRE Method . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2.5 PROMETHEE Method...10 DSS Decision Support Systems . . . . . . . . . . . . . . . . . . . . 16 MAUT Multi-Attribute Utility Theory

  18. Decision technology.

    PubMed

    Edwards, W; Fasolo, B

    2001-01-01

    This review is about decision technology-the rules and tools that help us make wiser decisions. First, we review the three rules that are at the heart of most traditional decision technology-multi-attribute utility, Bayes' theorem, and subjective expected utility maximization. Since the inception of decision research, these rules have prescribed how we should infer values and probabilities and how we should combine them to make better decisions. We suggest how to make best use of all three rules in a comprehensive 19-step model. The remainder of the review explores recently developed tools of decision technology. It examines the characteristics and problems of decision-facilitating sites on the World Wide Web. Such sites now provide anyone who can use a personal computer with access to very sophisticated decision-aiding tools structured mainly to facilitate consumer decision making. It seems likely that the Web will be the mode by means of which decision tools will be distributed to lay users. But methods for doing such apparently simple things as winnowing 3000 options down to a more reasonable number, like 10, contain traps for unwary decision technologists. The review briefly examines Bayes nets and influence diagrams-judgment and decision-making tools that are available as computer programs. It very briefly summarizes the state of the art of eliciting probabilities from experts. It concludes that decision tools will be as important in the 21st century as spreadsheets were in the 20th.

  19. A depression network of functionally connected regions discovered via multi-attribute canonical correlation graphs.

    PubMed

    Kang, Jian; Bowman, F DuBois; Mayberg, Helen; Liu, Han

    2016-11-01

    To establish brain network properties associated with major depressive disorder (MDD) using resting-state functional magnetic resonance imaging (Rs-fMRI) data, we develop a multi-attribute graph model to construct a region-level functional connectivity network that uses all voxel level information. For each region pair, we define the strength of the connectivity as the kernel canonical correlation coefficient between voxels in the two regions; and we develop a permutation test to assess the statistical significance. We also construct a network based classifier for making predictions on the risk of MDD. We apply our method to Rs-fMRI data from 20 MDD patients and 20 healthy control subjects in the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study. Using this method, MDD patients can be distinguished from healthy control subjects based on significant differences in the strength of regional connectivity. We also demonstrate the performance of the proposed method using simulationstudies.

  20. Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

    PubMed

    Wichary, Szymon; Smolen, Tomasz

    2016-01-01

    In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

  1. Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model

    PubMed Central

    Wichary, Szymon; Smolen, Tomasz

    2016-01-01

    In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals. PMID:27877103

  2. Selection of Aluminum Alloys for U.S. Army Vehicles Using Multi-Attribute Utility Analysis

    DTIC Science & Technology

    1989-01-01

    maker’s preferences, it was determined that a n aluminum alloy, 2519-T87 (conforming to MIL-A-46192) shows great promisse-for replacing the currently used...MTLTR89- AD-A204 018 AD SELECTION OF ALUMINUM ALLOYS FOR U.S. ARMY VEHICLES USING MULTI-ATTRIBUTE UTILITY ANALYSIS STEVEN A. GEDEON and CHARLES T...TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED SELECTION OF ALUMINUM ALLOYS FOR U.S. ARMY Final Report VEHICLES USING MULTI-ATTRIBUTE UTILITY

  3. Spatial Database Organization for Multi-attribute Sensor Data Representation

    NASA Astrophysics Data System (ADS)

    Gouveia, Feliz R.; Barthes, Jean-Paul A.

    1990-03-01

    This paper surveys spatial database organization and modelling as it is becoming a crucial issue for an ever increasing number of geometric data manipulation systems. We are here interested in efficient representation and storage structures for rapid processing of large sets of geometric data, as required by robotics applications, Very Large Scale Integration (VLSI) layout design, cartography, Computer Aided Design (CAD), or geographic information systems (GIS), where frequent operations involve spatial reasoning over that data. Existing database systems lack expressiveness to store some kinds of information which are inherently present in a geometric reasoning process, such as metric information, e.g. proximity, parallelism; or topological information, e.g. inclusion, intersection, contiguity, crossing. Geometric databases (GDB) alleviate this problem by providing an explicit representation for the spatial layout of the world in terms of empty and occupied space, together with a complete description of each object in it. Access to the data is done in an associative manner, that is, by specifying values over some usually small (sub)set of attributes, e.g. the coordinates of physical space. Manipulating data in GDB systems involves often spatially localized operations, i.e., locations, and consequently objects, which are accessed in the present are likely to be accessed again in a near future; this locality of reference which Hegron [24] calls temporal coherence, is due mainly to real world physical constraints. Indeed if accesses are caused for example by a sensor module which inspects its surroundings, then it is reasonable to suppose that successive scanned territories are not very far apart.

  4. Decision Making for Pap Testing among Pacific Islander Women

    ERIC Educational Resources Information Center

    Weiss, Jie W.; Mouttapa, Michele; Sablan-Santos, Lola; DeGuzman Lacsamana, Jasmine; Quitugua, Lourdes; Park Tanjasiri, Sora

    2016-01-01

    This study employed a Multi-Attribute Utility (MAU) model to examine the Pap test decision-making process among Pacific Islanders (PI) residing in Southern California. A total of 585 PI women were recruited through social networks from Samoan and Tongan churches, and Chamorro family clans. A questionnaire assessed Pap test knowledge, beliefs and…

  5. Modeling Common-Sense Decisions

    NASA Astrophysics Data System (ADS)

    Zak, Michail

    This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

  6. 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…

  7. 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.

  8. A decision aid for intensity-modulated radiation-therapy plan selection in prostate cancer based on a prognostic Bayesian network and a Markov model

    PubMed Central

    Smith, Wade P; Doctor, Jason; Meyer, Jürgen; Kalet, Ira J; Phillips, Mark H

    2009-01-01

    Objective The prognosis of cancer patients treated with intensity modulated radiation therapy (IMRT) is inherently uncertain, depends on many decision variables, and requires that a physician balance competing objectives: maximum tumor control with minimal treatment complications. Methods In order to better deal with the complex and multiple objective nature of the problem we have combined a prognostic probabilistic model with multi-attribute decision theory which incorporates patient preferences for outcomes. Results The response to IMRT for prostate cancer was modeled. A Bayesian network was used for prognosis for each treatment plan. Prognoses included predicting local tumor control, regional spread, distant metastases, and normal tissue complications resulting from treatment. A Markov model was constructed and used to calculate a quality-adjusted life-expectancy which aids in the multi-attribute decision process. Conclusions Our method makes explicit the tradeoffs patients face between quality and quantity of life. This approach has advantages over current approaches because with our approach risks of health outcomes and patient preferences determine treatment decisions. PMID:19157811

  9. Multi Attribute Decision Analysis in Public Health - Analyzing Effectiveness of Alternate Modes of Dispensing

    DTIC Science & Technology

    2007-09-01

    by Chan and Mauborgne in the book, “ Blue Ocean Strategy ” it is difficult for any agency to create an operational plan from their strategic plan...Website: www.bt.cdc.gov/cri/facts.asp. Chan, W. & Mauborgne, R. (2005). Blue Ocean Strategy . Cambridge, MA: Harvard Business School Press. Cities

  10. 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…

  11. 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…

  12. 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.

  13. 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.

  14. Fire behavior modeling-a decision tool

    Treesearch

    Jack Cohen; Bill Bradshaw

    1986-01-01

    The usefulness of an analytical model as a fire management decision tool is determined by the correspondence of its descriptive capability to the specific decision context. Fire managers must determine the usefulness of fire models as a decision tool when applied to varied situations. Because the wildland fire phenomenon is complex, analytical fire spread models will...

  15. 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

  16. 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

  17. 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).

  18. 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.

  19. Single-process versus multiple-strategy models of decision making: evidence from an information intrusion paradigm.

    PubMed

    Söllner, Anke; Bröder, Arndt; Glöckner, Andreas; Betsch, Tilmann

    2014-02-01

    When decision makers are confronted with different problems and situations, do they use a uniform mechanism as assumed by single-process models (SPMs) or do they choose adaptively from a set of available decision strategies as multiple-strategy models (MSMs) imply? Both frameworks of decision making have gathered a lot of support, but only rarely have they been contrasted with each other. Employing an information intrusion paradigm for multi-attribute decisions from givens, SPM and MSM predictions on information search, decision outcomes, attention, and confidence judgments were derived and tested against each other in two experiments. The results consistently support the SPM view: Participants seemingly using a "take-the-best" (TTB) strategy do not ignore TTB-irrelevant information as MSMs would predict, but adapt the amount of information searched, choose alternative choice options, and show varying confidence judgments contingent on the quality of the "irrelevant" information. The uniformity of these findings underlines the adequacy of the novel information intrusion paradigm and comprehensively promotes the notion of a uniform decision making mechanism as assumed by single-process models. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

  20. Decision modeling for fire incident analysis

    Treesearch

    Donald G. MacGregor; Armando González-Cabán

    2009-01-01

    This paper reports on methods for representing and modeling fire incidents based on concepts and models from the decision and risk sciences. A set of modeling techniques are used to characterize key fire management decision processes and provide a basis for incident analysis. The results of these methods can be used to provide insights into the structure of fire...

  1. 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.

  2. 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.

  3. Application of multi-attribute utility theory to measure social preferences for health states.

    PubMed

    Torrance, G W; Boyle, M H; Horwood, S P

    1982-01-01

    A four-attribute health state classification system designed to uniquely categorize the health status of all individuals two years of age and over is presented. A social preference function defined over the health state classification system is required. Standard multi-attribute utility theory is investigated for the task, problems are identified and modifications to the standard method are proposed. The modified methods is field tested in a survey research project involving 112 home interviews. Results are presented and discussed in detail for both the social preference function and the performance of the modified method. A recommended social preference function is presented, complete with a range of uncertainty. The modified method is found to be applicable to the task--no insurmountable difficulties are encountered. Recommendations are presented, based on our experience, for other investigators who may be interested in reapplying the method in other studies.

  4. Formalising expert opinion through multi-attribute value functions: an application in landscape ecology.

    PubMed

    Geneletti, Davide

    2005-08-01

    One of the main objectives of landscape ecology is to orient land-use planning by providing indications of optimal ecosystem patterning to support nature conservation. A frequent limitation to the practical use of the findings of landscape ecological studies is that they tend to focus on the identification and computation of indicators rather than on their interpretation and assessment. This paper presents and discusses the use of a methodology to formalise expert opinion through the elicitation of multi-attribute value functions. In particular, the value functions aim at assessing spatial indicators so as to provide an overall judgment of the viability of different ecosystem patches. The result consisted of the ranking of the ecosystems according to their degree of viability and therefore their suitability for nature conservation. The method of formalising expert opinion and knowledge complements traditional analyses based on the measurement of spatial ecological indicators.

  5. 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.

  6. 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.

  7. 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…

  8. 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…

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

    NASA Astrophysics Data System (ADS)

    Xue-jun, Tang; Jia, Chen

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

  10. Nonstationary decision model for flood risk decision scaling

    NASA Astrophysics Data System (ADS)

    Spence, Caitlin M.; Brown, Casey M.

    2016-11-01

    Hydroclimatic stationarity is increasingly questioned as a default assumption in flood risk management (FRM), but successor methods are not yet established. Some potential successors depend on estimates of future flood quantiles, but methods for estimating future design storms are subject to high levels of uncertainty. Here we apply a Nonstationary Decision Model (NDM) to flood risk planning within the decision scaling framework. The NDM combines a nonstationary probability distribution of annual peak flow with optimal selection of flood management alternatives using robustness measures. The NDM incorporates structural and nonstructural FRM interventions and valuation of flows supporting ecosystem services to calculate expected cost of a given FRM strategy. A search for the minimum-cost strategy under incrementally varied representative scenarios extending across the plausible range of flood trend and value of the natural flow regime discovers candidate FRM strategies that are evaluated and compared through a decision scaling analysis (DSA). The DSA selects a management strategy that is optimal or close to optimal across the broadest range of scenarios or across the set of scenarios deemed most likely to occur according to estimates of future flood hazard. We illustrate the decision framework using a stylized example flood management decision based on the Iowa City flood management system, which has experienced recent unprecedented high flow episodes. The DSA indicates a preference for combining infrastructural and nonstructural adaptation measures to manage flood risk and makes clear that options-based approaches cannot be assumed to be "no" or "low regret."

  11. 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 ...

  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. Use of Information Technology Tools in Source Selection Decision Making: A Study on USAF’s KC-X Tanker Replacement Program

    DTIC Science & Technology

    2008-06-01

    37 e. Compromise Programming (CP)............................................38 f. Multi-Attribute Utility Theory ( MAUT ...their assigned weights.87 f. Multi-Attribute Utility Theory ( MAUT ) Multi-attribute utility theory is another popular method for decision- making...and Roger Smith, “ Multiattribute Utility Theory ,” (technical report, University of Wisconsin), http://www.r2d2.uwm.edu/atoms/archive

  14. Models, Measurements, and Local Decisions: Assessing and ...

    EPA Pesticide Factsheets

    This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include either exposure or emissions reduction, and a host of stakeholders, including residents, academics, NGOs, local and federal agencies. This presentation includes results from the C-PORT modeling system, and from a citizen science project from the local area. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

  15. Towards the ecotourism: a decision support model for the assessment of sustainability of mountain huts in the Alps.

    PubMed

    Stubelj Ars, Mojca; Bohanec, Marko

    2010-12-01

    This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts' surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists.

  16. Job Aiding/Training Decision Process Model

    DTIC Science & Technology

    1992-09-01

    I[ -, . 1’, oo Ii AL-CR-i1992-0004 AD-A256 947lEE = IIEI ifl ll 1l I JOB AIDING/TRAINING DECISION PROCESS MODEL A R M John P. Zenyuh DTIC S Phillip C...March 1990 - April 1990 4. TITLE AND SUBTITLE S. FUNDING NUMBERS C - F33615-86-C-0545 Job Aiding/Training Decision Process Model PE - 62205F PR - 1121 6...Components to Process Model Decision and Selection Points ........... 32 13. Summary of Subject Recommendations for Aiding Approaches

  17. Participatory modeling and structured decision making

    USGS Publications Warehouse

    Robinson, Kelly F.; Fuller, Angela K.

    2016-01-01

    Structured decision making (SDM) provides a framework for making sound decisions even when faced with uncertainty, and is a transparent, defensible, and replicable method used to understand complex problems. A hallmark of SDM is the explicit incorporation of values and science, which often includes participation from multiple stakeholders, helping to garner trust and ultimately result in a decision that is more likely to be implemented. The core steps in the SDM process are used to structure thinking about natural resources management choices, and include: (1) properly defining the problem and the decision context, (2) determining the objectives that help describe the aspirations of the decision maker, (3) devising management actions or alternatives that can achieve those objectives, (4) evaluating the outcomes or consequences of each alternative on each of the objectives, (5) evaluating trade-offs, and (6) implementing the decision. Participatory modeling for SDM includes engaging stakeholders in some or all of the steps of the SDM process listed above. In addition, participatory modeling often is crucial for creating qualitative and quantitative models of how the system works, providing data for these models, and eliciting expert opinion when data are unavailable. In these ways, SDM provides a framework for decision making in natural resources management that includes participation from stakeholder groups throughout the process, including the modeling phase.

  18. 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…

  19. 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…

  20. A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

    PubMed Central

    Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

    2017-01-01

    With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

  1. 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.

  2. A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks.

    PubMed

    Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

    2017-03-08

    With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes' reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes' communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service.

  3. Multi-Attribute Task Battery - Applications in pilot workload and strategic behavior research

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

    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 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.

  4. 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...

  5. 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...

  6. Integrated seismic stochastic inversion and multi-attributes to delineate reservoir distribution: Case study MZ fields, Central Sumatra Basin

    NASA Astrophysics Data System (ADS)

    Haris, A.; Novriyani, M.; Suparno, S.; Hidayat, R.; Riyanto, A.

    2017-07-01

    This study presents the integration of seismic stochastic inversion and multi-attributes for delineating the reservoir distribution in term of lithology and porosity in the formation within depth interval between the Top Sihapas and Top Pematang. The method that has been used is a stochastic inversion, which is integrated with multi-attribute seismic by applying neural network Probabilistic Neural Network (PNN). Stochastic methods are used to predict the probability mapping sandstone as the result of impedance varied with 50 realizations that will produce a good probability. Analysis of Stochastic Seismic Tnversion provides more interpretive because it directly gives the value of the property. Our experiment shows that AT of stochastic inversion provides more diverse uncertainty so that the probability value will be close to the actual values. The produced AT is then used for an input of a multi-attribute analysis, which is used to predict the gamma ray, density and porosity logs. To obtain the number of attributes that are used, stepwise regression algorithm is applied. The results are attributes which are used in the process of PNN. This PNN method is chosen because it has the best correlation of others neural network method. Finally, we interpret the product of the multi-attribute analysis are in the form of pseudo-gamma ray volume, density volume and volume of pseudo-porosity to delineate the reservoir distribution. Our interpretation shows that the structural trap is identified in the southeastern part of study area, which is along the anticline.

  7. 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.

  8. Diffusion Decision Model: Current Issues and History

    PubMed Central

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

    2016-01-01

    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 article, we relate the models to both earlier and more recent research in psychology. PMID:26952739

  9. 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

  10. Computer models for economic and silvicultural decisions

    Treesearch

    Rosalie J. Ingram

    1989-01-01

    Computer systems can help simplify decisionmaking to manage forest ecosystems. We now have computer models to help make forest management decisions by predicting changes associated with a particular management action. Models also help you evaluate alternatives. To be effective, the computer models must be reliable and appropriate for your situation.

  11. 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.

  12. Climate modeling with decision makers in mind

    SciTech Connect

    Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

    2016-04-27

    The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

  13. Climate modeling with decision makers in mind

    DOE PAGES

    Jones, Andrew; Calvin, Katherine; Lamarque, Jean -Francois

    2016-04-27

    The need for regional- and local-scale climate information is increasing rapidly as decision makers seek to anticipate and manage a variety of context-specific climate risks over the next several decades. Furthermore, global climate models are not developed with these user needs in mind, and they typically operate at resolutions that are too coarse to provide information that could be used to support regional and local decisions.

  14. 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.

  15. Investigations of Naturalistic Decision Making and the Recognition-Primed Decision Model

    DTIC Science & Technology

    1990-07-01

    develop a Recognition-Primed Decision (RPD) model of decicion making . This model contrasts w-th current nor- mative and prescriptive models of decision...ARI Research Note 90-59 / .Lh FiLE COPY Investigations of Naturalistic Decision Making and the Recognition-Primed Decision Model Gary A. Klein and...exandria, VA 22333-5600 6110’_B 74F TITLE (include Security Classification) vestigations of Naturalistic Decision Making and the Recognition-Primed cision

  16. Decision-analytic models: current methodological challenges.

    PubMed

    Caro, J Jaime; Möller, Jörgen

    2014-10-01

    Modelers seeking to help inform decisions about insurance (public or private) coverage of the cost of pharmaceuticals or other health care interventions face various methodological challenges. In this review, which is not meant to be comprehensive, we cover those that in our experience are most vexing. The biggest challenge is getting decision makers to trust the model. This is a major problem because most models undergo only cursory validation; our field has lacked the motivation, time, and data to properly validate models intended to inform health care decisions. Without documented, adequate validation, there is little basis for decision makers to have confidence that the model's results are credible and should be used in a health technology appraisal. A fundamental problem for validation is that the models are very artificial and lack sufficient depth to adequately represent the reality they are simulating. Typically, modelers assume that all resources have infinite capacity so any patient needing care receives it immediately; there are no waiting times or queues, contrary to the common experience in actual practice. Moreover, all the patients enter the model simultaneously at time zero rather than over time as happens in actuality; differences between patients are ignored or minimized and structural modeling choices that make little sense (e.g., using states to represent events) are forced by commitment to a technique (and even to specific spreadsheet software!). The resulting structural uncertainty is rarely addressed, because methods are lacking and even probabilistic analysis of parameter uncertainty suffers from weak consideration of correlation and arbitrary distribution choices. Stakeholders must see to it that models are fit for the stated purpose and provide the best possible estimates given available data-the decisions at stake deserve nothing less.

  17. An Updated Version of the U.S. Air Force Multi-Attribute Task Battery (AF-MATB)

    DTIC Science & Technology

    2014-08-01

    assessing human performance in a controlled multitask environment. The most recent release of AF-MATB contains numerous improvements and additions...Strategic Behavior, MATB, Multitasking , Task Battery, Simulator, Multi-Attribute Task Battery, Automation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...performance and multitasking strategy. As a result, a specific Information Throughput (IT) Mode was designed to customize the task to fit the Human

  18. 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…

  19. 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…

  20. An EEG-based mental workload estimator trained on working memory task can work well under simulated multi-attribute task

    PubMed Central

    Ke, Yufeng; Qi, Hongzhi; He, Feng; Liu, Shuang; Zhao, Xin; Zhou, Peng; Zhang, Lixin; Ming, Dong

    2014-01-01

    Mental workload (MW)-based adaptive system has been found to be an effective approach to enhance the performance of human-machine interaction and to avoid human error caused by overload. However, MW estimated from the spontaneously generated electroencephalogram (EEG) was found to be task-specific. In existing studies, EEG-based MW classifier can work well under the task used to train the classifier (within-task) but crash completely when used to classify MW of a task that is similar to but not included in the training data (cross-task). The possible causes have been considered to be the task-specific EEG patterns, the mismatched workload across tasks and the temporal effects. In this study, cross-task performance-based feature selection (FS) and regression model were tried to cope with these challenges, in order to make EEG-based MW estimator trained on working memory tasks work well under a complex simulated multi-attribute task (MAT). The results show that the performance of regression model trained on working memory task and tested on multi-attribute task with the feature subset picked-out were significantly improved (correlation coefficient (COR): 0.740 ± 0.147 and 0.598 ± 0.161 for FS data and validation data respectively) when compared to the performance in the same condition with all features (chance level). It can be inferred that there do exist some MW-related EEG features can be picked out and there are something in common between MW of a relatively simple task and a complex task. This study provides a promising approach to measure MW across tasks. PMID:25249967

  1. An EEG-based mental workload estimator trained on working memory task can work well under simulated multi-attribute task.

    PubMed

    Ke, Yufeng; Qi, Hongzhi; He, Feng; Liu, Shuang; Zhao, Xin; Zhou, Peng; Zhang, Lixin; Ming, Dong

    2014-01-01

    Mental workload (MW)-based adaptive system has been found to be an effective approach to enhance the performance of human-machine interaction and to avoid human error caused by overload. However, MW estimated from the spontaneously generated electroencephalogram (EEG) was found to be task-specific. In existing studies, EEG-based MW classifier can work well under the task used to train the classifier (within-task) but crash completely when used to classify MW of a task that is similar to but not included in the training data (cross-task). The possible causes have been considered to be the task-specific EEG patterns, the mismatched workload across tasks and the temporal effects. In this study, cross-task performance-based feature selection (FS) and regression model were tried to cope with these challenges, in order to make EEG-based MW estimator trained on working memory tasks work well under a complex simulated multi-attribute task (MAT). The results show that the performance of regression model trained on working memory task and tested on multi-attribute task with the feature subset picked-out were significantly improved (correlation coefficient (COR): 0.740 ± 0.147 and 0.598 ± 0.161 for FS data and validation data respectively) when compared to the performance in the same condition with all features (chance level). It can be inferred that there do exist some MW-related EEG features can be picked out and there are something in common between MW of a relatively simple task and a complex task. This study provides a promising approach to measure MW across tasks.

  2. 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

  3. Modeling choice and valuation in decision experiments.

    PubMed

    Loomes, Graham

    2010-07-01

    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 participants to perceive probabilities and payoffs in a particular way. This model organizes more of the data than any other extant model and generates a number of novel testable implications which are examined with new data.

  4. Priority setting in health care using multi-attribute utility theory and programme budgeting and marginal analysis (PBMA).

    PubMed

    Peacock, Stuart J; Richardson, Jeff R J; Carter, Rob; Edwards, Diana

    2007-02-01

    Programme budgeting and marginal analysis (PBMA) is becoming an increasingly popular tool in setting health service priorities. This paper presents a novel multi-attribute utility (MAU) approach to setting health service priorities using PBMA. This approach includes identifying the attributes of the MAU function; describing and scaling attributes; quantifying trade-offs between attributes; and combining single conditional utility functions into the MAU function. We illustrate the MAU approach using a PBMA case study in mental health services from the Community Health Sector in metropolitan South Australia.

  5. Neurally Constrained Modeling of Perceptual Decision Making

    PubMed Central

    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 test alternative models of how evidence is combined in the accumulation process. The models were evaluated on their ability to predict both response time distributions and movement neuron activity observed in monkeys performing a visual search task. Models that assume gating of perceptual evidence to the accumulating units provide the best account of both behavioral and neural data. These results identify discrete stages of processing with anatomically distinct neural populations and rule out several alternative architectures. The results also illustrate the use of neurophysiological data as a model selection tool and establish a novel framework to bridge computational and neural levels of explanation. PMID:20822291

  6. 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.

  7. [Mathematical models of decision making and learning].

    PubMed

    Ito, Makoto; Doya, Kenji

    2008-07-01

    Computational models of reinforcement learning have recently been applied to analysis of brain imaging and neural recording data to identity neural correlates of specific processes of decision making, such as valuation of action candidates and parameters of value learning. However, for such model-based analysis paradigms, selecting an appropriate model is crucial. In this study we analyze the process of choice learning in rats using stochastic rewards. We show that "Q-learning," which is a standard reinforcement learning algorithm, does not adequately reflect the features of choice behaviors. Thus, we propose a generalized reinforcement learning (GRL) algorithm that incorporates the negative reward effect of reward loss and forgetting of values of actions not chosen. Using the Bayesian estimation method for time-varying parameters, we demonstrated that the GRL algorithm can predict an animal's choice behaviors as efficiently as the best Markov model. The results suggest the usefulness of the GRL for the model-based analysis of neural processes involved in decision making.

  8. 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.

  9. A decision-support model for evaluating changes in biopharmaceutical manufacturing processes.

    PubMed

    Chhatre, S; Francis, R; O'Donovan, K; Titchener-Hooker, N J; Newcombe, A R; Keshavarz-Moore, E

    2007-01-01

    A simulation is described that evaluates the impacts of altering bio-manufacturing processes. Modifications designed to improve production levels, times and costs were assessed, including increasing feed volumes/titres, replacing initial downstream stages with packed or expanded bed affinity steps and removing ion exchange steps. Options were evaluated for manufactured product mass, COG, batch times and development costs and timescales. Metrics were combined using multi-attribute-decision-making techniques generating a single assessment metric for each option. The utility of this approach was illustrated by application to an FDA-approved process manufacturing rattlesnake anti-venom (Protherics U.K.). Currently, ovine serum containing anti-venom IgG is purified by precipitation/centrifugation, prior to antibody proteolysis by papain. An ion exchanger removes F(C), before affinity chromatography yields the final anti-venom. An expanded bed affinity column operating with an 80% higher IgG titre, 66% higher feed volume and without the ion exchanger delivered the best multi-attribute-decision-making value, potentially providing the most desirable alternative.

  10. A Quadrupole Dalton-based multi-attribute method for product characterization, process development, and quality control of therapeutic proteins.

    PubMed

    Xu, Weichen; Jimenez, Rod Brian; Mowery, Rachel; Luo, Haibin; Cao, Mingyan; Agarwal, Nitin; Ramos, Irina; Wang, Xiangyang; Wang, Jihong

    2017-08-14

    During manufacturing and storage process, therapeutic proteins are subject to various post-translational modifications (PTMs), such as isomerization, deamidation, oxidation, disulfide bond modifications and glycosylation. Certain PTMs may affect bioactivity, stability or pharmacokinetics and pharmacodynamics profile and are therefore classified as potential critical quality attributes (pCQAs). Identifying, monitoring and controlling these PTMs are usually key elements of the Quality by Design (QbD) approach. Traditionally, multiple analytical methods are utilized for these purposes, which is time consuming and costly. In recent years, multi-attribute monitoring methods have been developed in the biopharmaceutical industry. However, these methods combine high-end mass spectrometry with complicated data analysis software, which could pose difficulty when implementing in a quality control (QC) environment. Here we report a multi-attribute method (MAM) using a Quadrupole Dalton (QDa) mass detector to selectively monitor and quantitate PTMs in a therapeutic monoclonal antibody. The result output from the QDa-based MAM is straightforward and automatic. Evaluation results indicate this method provides comparable results to the traditional assays. To ensure future application in the QC environment, this method was qualified according to the International Conference on Harmonization (ICH) guideline and applied in the characterization of drug substance and stability samples. The QDa-based MAM is shown to be an extremely useful tool for product and process characterization studies that facilitates facile understanding of process impact on multiple quality attributes, while being QC friendly and cost-effective.

  11. Comparison of potential method in analytic hierarchy process for multi-attribute of catering service companies

    NASA Astrophysics Data System (ADS)

    Mamat, Siti Salwana; Ahmad, Tahir; Awang, Siti Rahmah

    2017-08-01

    Analytic Hierarchy Process (AHP) is a method used in structuring, measuring and synthesizing criteria, in particular ranking of multiple criteria in decision making problems. On the other hand, Potential Method is a ranking procedure in which utilizes preference graph ς (V, A). Two nodes are adjacent if they are compared in a pairwise comparison whereby the assigned arc is oriented towards the more preferred node. In this paper Potential Method is used to solve problem on a catering service selection. The comparison of result by using Potential method is made with Extent Analysis. The Potential Method is found to produce the same rank as Extent Analysis in AHP.

  12. 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.

  13. 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.

  14. A multi-attribute methodology for the prioritisation of oil contaminated sites in the Niger Delta.

    PubMed

    Sam, Kabari; Coulon, Frédéric; Prpich, George

    2017-02-01

    The Ogoniland region of the Niger Delta contains a vast number of sites contaminated with petroleum hydrocarbons that originated from Nigeria's active oil sector. The United Nations Environment Programme (UNEP) reported on this widespread contamination in 2011, however, wide-scale action to clean-up these sites has yet to be initiated. A challenge for decision makers responsible for the clean-up of these sites has been the prioritisation of sites to enable appropriate allocation of scarce resources. In this study, a risk-based multi-criteria decision analysis framework was used to prioritise high-risk sites contaminated with petroleum hydrocarbons in the Ogoniland region of Nigeria. The prioritisation method used a set of risk-based attributes that took into account chemical and ecological impacts, as well as socio-economic impacts, providing a holistic assessment of the risk. Data for the analysis was taken from the UNEP Environmental Assessment of Ogoniland, where over 110 communities were assessed for oil-contamination. Results from our prioritisation show that the highest-ranking sites were not necessarily the sites with the highest observed level of hydrocarbon contamination. This differentiation was due to our use of proximity as a surrogate measure for likelihood of exposure. Composite measures of risk provide a more robust assessment, and can enrich discussions about risk management and the allocation of resources for the clean-up of affected sites.

  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. 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

  17. 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…

  18. Multi-Attribute Selection of Coal Center Location: A Case Study in Thailand

    NASA Astrophysics Data System (ADS)

    Kuakunrittiwong, T.; Ratanakuakangwan, S.

    2016-11-01

    Under Power Development Plan 2015, Thailand has to diversify its heavily gas-fired electricity generation. The main owner of electricity transmission grids is responsible to implement several coal-fired power plants with clean coal technology. To environmentally handle and economically transport unprecedented quantities of sub-bituminous and bituminous coal, a coal center is required. The location of such facility is an important strategic decision and a paramount to the success of the energy plan. As site selection involves many criteria, Fuzzy Analytical Hierarchy Process or Fuzzy-AHP is applied to select the most suitable location among three candidates. Having analyzed relevant criteria and the potential alternatives, the result reveals that engineering and socioeconomic are important criteria and Map Ta Phut is the most suitable site for the coal center.

  19. Constructing Retrocausal Models: Decision Points and Pitfalls

    NASA Astrophysics Data System (ADS)

    Wharton, Ken

    2011-11-01

    The scattered efforts to construct retrocausal models of quantum phenomena have utilized different conceptual and mathematical frameworks; in most cases a framework is assumed without explicit discussion or particular justification. Some of these frameworks are arguably internally inconsistent, and others incorporate standard quantum concepts that become problematic or unnecessary when used in a time-symmetric manner. With this in mind, I will examine the big-picture choices facing a theorist who wishes to construct a coherent retrocausal model. These decisions include whether or not to couch the theory in a single "block universe"; the role (if any) of hidden variables; the implementation of boundary constraints; the use of conditional probability vs. joint probability; and the choice between Newtonian and Lagrangian approaches.

  20. Decision Making, Models of Mind, and the New Cognitive Science.

    ERIC Educational Resources Information Center

    Evers, Colin W.

    1998-01-01

    Explores implications for understanding educational decision making from a cognitive science perspective. Examines three models of mind providing the methodological framework for decision-making studies. The "absent mind" embodies the behaviorist research tradition. The "functionalist mind" underwrites traditional cognitivism…

  1. Decision Making, Models of Mind, and the New Cognitive Science.

    ERIC Educational Resources Information Center

    Evers, Colin W.

    1998-01-01

    Explores implications for understanding educational decision making from a cognitive science perspective. Examines three models of mind providing the methodological framework for decision-making studies. The "absent mind" embodies the behaviorist research tradition. The "functionalist mind" underwrites traditional cognitivism…

  2. Subjective modelling decisions significantly impact the simulation of hydrological extremes

    NASA Astrophysics Data System (ADS)

    Melsen, Lieke; Teuling, Adriaan; Torfs, Paul; Zappa, Massimiliano; Mizukami, Naoki; Mendoza, Pablo; Clark, Martyn; Uijlenhoet, Remko

    2017-04-01

    It is generally acknowledged in the environmental sciences that the choice of a computational model impacts the research results. We have showed, with an example of hydrological modelling of floods and drought, that modelling decisions during the model configuration, beyond the model choice, also impact the model results. In our carefully designed experiment we investigated four modelling decisions in ten nested basins: the spatial resolution of the model, the spatial representation of the forcing data, the calibration period, and the performance metric. The simulation of both hydrological extremes was affected by the four modelling decisions, with differing significance and magnitude. The flood characteristics were mainly affected by the performance metric, whereas the drought characteristics were mainly affected by the calibration period. Modelling decisions during model configuration introduce subjectivity from the modeller. Multiple working hypotheses during model configuration can provide insights on the impact of such subjective modelling decisions.

  3. 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.

  4. Modelling elderly cardiac patients decision making using Cognitive Work Analysis: identifying requirements for patient decision aids.

    PubMed

    Dhukaram, Anandhi Vivekanandan; Baber, Chris

    2015-06-01

    Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  5. 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.

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

    PubMed

    Golder, W

    2000-01-01

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

  7. 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.

  8. 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

  9. 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…

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. Dynamic decision modeling in medicine: a critique of existing formalisms.

    PubMed Central

    Leong, T. Y.

    1993-01-01

    Dynamic decision models are frameworks for modeling and solving decision problems that take into explicit account the effects of time. These formalisms are based on structural and semantical extensions of conventional decision models, e.g., decision trees and influence diagrams, with the mathematical definitions of finite-state semi-Markov processes. This paper identifies the common theoretical basis of existing dynamic decision modeling formalisms, and compares and contrasts their applicability and efficiency. It also argues that a subclass of such dynamic decision problems can be formulated and solved more effectively with non-graphical techniques. Some insights gained from this exercise on automating the dynamic decision making process are summarized. PMID:8130519

  16. Multiview coding mode decision with hybrid optimal stopping model.

    PubMed

    Zhao, Tiesong; Kwong, Sam; Wang, Hanli; Wang, Zhou; Pan, Zhaoqing; Kuo, C-C Jay

    2013-04-01

    In a generic decision process, optimal stopping theory aims to achieve a good tradeoff between decision performance and time consumed, with the advantages of theoretical decision-making and predictable decision performance. In this paper, optimal stopping theory is employed to develop an effective hybrid model for the mode decision problem, which aims to theoretically achieve a good tradeoff between the two interrelated measurements in mode decision, as computational complexity reduction and rate-distortion degradation. The proposed hybrid model is implemented and examined with a multiview encoder. To support the model and further promote coding performance, the multiview coding mode characteristics, including predicted mode probability and estimated coding time, are jointly investigated with inter-view correlations. Exhaustive experimental results with a wide range of video resolutions reveal the efficiency and robustness of our method, with high decision accuracy, negligible computational overhead, and almost intact rate-distortion performance compared to the original encoder.

  17. 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

  18. Psychological Screening for Weapons Use Suitability: A Formal Decision Model,

    DTIC Science & Technology

    Psychological tests, *Military personnel, *Performance(Human), *Models, *Decision making, Scoring, Ratings, Data bases, Standardization, Personality ...tests, Psychology , Questionnaires, factor analysis, Diagnosis(General), Symposia

  19. 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.

  20. 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…

  1. Venture Theory: A Model of Decision Weights.

    DTIC Science & Technology

    1988-01-01

    restrictions are important in that nonadditive decision weights can be used to "explain" many anomalies of standard choice theory . Implications. There are...1974). On utility functions. Theory and Decision, 5, 205-242. Chew, S. H., & MacCrimmon, K. R. Alpha-nu choice theory : A generalization of expected

  2. 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…

  3. 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.

  4. A review of clinical decision making: models and current research.

    PubMed

    Banning, Maggi

    2008-01-01

    The aim of this paper was to review the current literature clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information-processing model, the intuitive-humanist model and the clinical decision-making model. Clinical decision making is a unique process that involves the interplay between knowledge of pre-existing pathological conditions, explicit patient information, nursing care and experiential learning. Historically, two models of clinical decision making are recognized from the literature; the information-processing model and the intuitive-humanist model. The usefulness and application of both models has been examined in relation the provision of nursing care and care related outcomes. More recently a third model of clinical decision making has been proposed. This new multidimensional model contains elements of the information-processing model but also examines patient specific elements that are necessary for cue and pattern recognition. Literature review. Evaluation of the literature generated from MEDLINE, CINAHL, OVID, PUBMED and EBESCO systems and the Internet from 1980 to November 2005. The characteristics of the three models of decision making were identified and the related research discussed. Three approaches to clinical decision making were identified, each having its own attributes and uses. The most recent addition to the clinical decision making is a theoretical, multidimensional model which was developed through an evaluation of current literature and the assessment of a limited number of research studies that focused on the clinical decision-making skills of inexperienced nurses in pseudoclinical settings. The components of this model and the relative merits to clinical practice are discussed. It is proposed that clinical decision making improves as the nurse gains experience of

  5. Clinical inferences and decisions--III. Utility assessment and the Bayesian decision model.

    PubMed

    Aspinall, P A; Hill, A R

    1984-01-01

    It is accepted that errors of misclassifications, however small, can occur in clinical decisions but it cannot be assumed that the importance associated with false positive errors is the same as that for false negatives. The relative importance of these two types of error is frequently implied by a decision maker in the different weighting factors or utilities he assigns to the alternative consequences of his decisions. Formal procedures are available by which it is possible to make explicit in numerical form the value or worth of the outcome of a decision process. The two principal methods are described for generating utilities as associated with clinical decisions. The concept and application of utility is then expanded from a unidimensional to a multidimensional problem where, for example, one variable may be state of health and another monetary assets. When combined with the principles of subjective probability and test criterion selection outlined in Parts I and II of this series, the consequent use of utilities completes the framework upon which the general Bayesian model of clinical decision making is based. The five main stages in this general decision making model are described and applications of the model are illustrated with clinical examples from the field of ophthalmology. These include examples for unidimensional and multidimensional problems which are worked through in detail to illustrate both the principles and methodology involved in a rationalized normative model of clinical decision making behaviour.

  6. [Decision modeling for economic evaluation of health technologies].

    PubMed

    de Soárez, Patrícia Coelho; Soares, Marta Oliveira; Novaes, Hillegonda Maria Dutilh

    2014-10-01

    Most economic evaluations that participate in decision-making processes for incorporation and financing of technologies of health systems use decision models to assess the costs and benefits of the compared strategies. Despite the large number of economic evaluations conducted in Brazil, there is a pressing need to conduct an in-depth methodological study of the types of decision models and their applicability in our setting. The objective of this literature review is to contribute to the knowledge and use of decision models in the national context of economic evaluations of health technologies. This article presents general definitions about models and concerns with their use; it describes the main models: decision trees, Markov chains, micro-simulation, simulation of discrete and dynamic events; it discusses the elements involved in the choice of model; and exemplifies the models addressed in national economic evaluation studies of diagnostic and therapeutic preventive technologies and health programs.

  7. 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.

  8. 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.

  9. 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.

  10. Clinical models of decision making in addiction.

    PubMed

    Koffarnus, Mikhail N; Kaplan, Brent A

    2017-08-26

    As research on decision making in addiction accumulates, it is increasingly clear that decision-making processes are dysfunctional in addiction and that this dysfunction may be fundamental to the initiation and maintenance of addictive behavior. How drug-dependent individuals value and choose among drug and nondrug rewards is consistently different from non-dependent individuals. The present review focuses on the assessment of decision-making in addiction. We cover the common behavioral tasks that have shown to be fruitful in decision-making research and highlight analytical and graphical considerations, when available, to facilitate comparisons within and among studies. Delay discounting tasks, drug demand tasks, drug choice tasks, the Iowa Gambling Task, and the Balloon Analogue Risk Task are included. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. 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. © 2014 Society for Risk Analysis.

  12. Clinical model for ethical cardiopulmonary resuscitation decision-making.

    PubMed

    Hayes, B

    2013-01-01

    Decisions to withhold cardiopulmonary resuscitation (CPR) for future cardiac arrest continue to be problematic, with a lack of consistency in how doctors approach this decision. To develop a clinical model that can be used in education to improve consistency in CPR decision-making. A qualitative study, using semistructured interviews with a total of 33 senior doctors, junior doctors and nurses from two Melbourne hospitals explored how decisions to withhold CPR are made. Interviews explored: issues arising; how doctors learn to make these decisions; how they deal with disagreement and their experiences of performing CPR. The transcripts were coded and analysed thematically. Three major themes were identified: CPR as a life-and-death decision; good and bad dying; and trust. The research also defined the two elements to a CPR decision: (i) technical and (ii) ethical. Applying ethical principles commonly used in medicine, a model for ethical CPR decision-making has been developed that identifies four patient groups, each with a different discussion aim. This approach simplifies the complexities of the CPR decision, providing a structured way to teach CPR decision-making to doctors and thereby achieve greater consistency in the decisions made. © 2012 The Author; Internal Medicine Journal © 2012 Royal Australasian College of Physicians.

  13. A Review of the Development and Application of Generic Multi-Attribute Utility Instruments for Paediatric Populations.

    PubMed

    Chen, Gang; Ratcliffe, Julie

    2015-10-01

    Multi-attribute utility instruments (MAUIs) are increasingly being used as a means of quantifying utility for the calculation of quality-adjusted life-years within the context of cost utility analysis. Traditionally, MAUIs have been developed and applied in adult populations. However, increasingly, researchers in health economics and other disciplines are recognising the importance of the measurement and valuation of health in both children and adolescents. Presently, there are nine generic MAUIs available internationally that have been used in paediatric populations: the Quality of Well-Being Scale (QWB), the Health Utility Index Mark 2 (HUI2), the HUI3, the Sixteen-dimensional measure of health-related quality of life (HRQoL) (16D), the Seventeen-dimensional measure of HRQoL (17D), the Assessment of Quality of Life 6-Dimension (AQoL-6D) Adolescent, the Child Health Utility 9D (CHU9D), the EQ-5D Youth version (EQ-5D-Y) and the Adolescent Health Utility Measure (AHUM). This paper critically reviews the development and application of the above nine MAUIs and discusses the specific challenges of health utility measurement in children and adolescents. Areas for further research relating to the development and application of generic MAUIs in paediatric populations are highlighted.

  14. 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

  15. 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,…

  16. 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…

  17. A Model for Evidence Accumulation in the Lexical Decision Task

    ERIC Educational Resources Information Center

    Wagenmakers, Eric-Jan; Steyvers, Mark; Raaijmakers, Jeroen G. W.; Shiffrin, Richard M.; van Rijn, Hedderik; Zeelenberg, Rene

    2004-01-01

    We present a new model for lexical decision, REM-LD, that is based on REM theory (e.g., Shiffrin & Steyvers, 1997). REM-LD uses a principled (i.e., Bayes' rule) decision process that simultaneously considers the diagnosticity of the evidence for the 'WORD' response and the 'NONWORD' response. The model calculates the odds ratio that the presented…

  18. A Diffusion Model Account of the Lexical Decision Task

    ERIC Educational Resources Information Center

    Ratcliff, Roger; Gomez, Pablo; McKoon, Gail

    2004-01-01

    The diffusion model for 2-choice decisions (R. Ratcliff, 1978) was applied to data from lexical decision experiments in which word frequency, proportion of high- versus low-frequency words, and type of nonword were manipulated. The model gave a good account of all of the dependent variables--accuracy, correct and error response times, and their…

  19. A Diffusion Model Account of the Lexical Decision Task

    ERIC Educational Resources Information Center

    Ratcliff, Roger; Gomez, Pablo; McKoon, Gail

    2004-01-01

    The diffusion model for 2-choice decisions (R. Ratcliff, 1978) was applied to data from lexical decision experiments in which word frequency, proportion of high- versus low-frequency words, and type of nonword were manipulated. The model gave a good account of all of the dependent variables--accuracy, correct and error response times, and their…

  20. Reviewing model application to support animal health decision making.

    PubMed

    Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann

    2011-04-01

    Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated.

  1. Implications of the KONVERGENCE Model for Difficult Cleanup Decisions

    SciTech Connect

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

    2002-08-04

    Abstract—Some cleanup decisions, such as cleanup of intractable contaminated sites or disposal of spent nuclear fuel, have proven difficult to make. Such decisions face high resistance to agreement from stakeholders possibly because they do not trust the decision makers, view the consequences of being wrong as too high, etc. Our project’s goal is to improve sciencebased cleanup decision-making. This includes diagnosing intractable situations, as a step to identifying a path toward sustainable solutions. Companion papers describe the underlying philosophy of the KONVERGENCE Model for Sustainable Decisions,1 and the overall framework and process steps.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. For intractable cases, serious consideration of the adaptable class of alternatives is warranted – if properly implemented and packaged.

  2. Individualizing generic decision models using assessments as evidence.

    PubMed

    Scott, George C; Shachter, Ross D

    2005-08-01

    Complex decision models in expert systems often depend upon a number of utilities and subjective probabilities for an individual. Although these values can be estimated for entire populations or demographic subgroups, a model should be customized to the individual's specific parameter values. This process can be onerous and inefficient for practical decisions. We propose an interactive approach for incrementally improving our knowledge about a specific individual's parameter values, including utilities and probabilities, given a decision model and a prior joint probability distribution over the parameter values. We define the concept of value of elicitation and use it to determine dynamically the next most informative elicitation for a given individual. We evaluated the approach using an example model and demonstrate that we can improve the decision quality by focusing on those parameter values most material to the decision.

  3. Revisiting the Relationship Between Data, Models, and Decision-Making.

    PubMed

    Ferré, Ty P A

    2017-09-01

    We hydrologists can do a better job of supporting water-resources decision-making. I will argue that we can do this by recognizing that decision makers use qualitative, multiple-narrative approaches. So, rather than providing single-model predictions with quantitative uncertainties, we should develop teams of rival models that inform decision makers about what is known, what is possible, and what is unknown. This requires that we build ensembles of models that include biased, advocacy models that directly represent stakeholders' interests or concerns. From this inclusive platform, we can speak objectively and clearly about the risks that drive stakeholders' decisions. Furthermore, we will be promoting more appropriate use of the scientific method in making informed water-resources decisions. © 2017, National Ground Water Association.

  4. A conditional model of evidence-based decision making.

    PubMed

    Falzer, Paul R; Garman, Melissa D

    2009-12-01

    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. 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. Twenty-one volunteers from a psychiatric residency programme responded to 64 case vignettes, 16 in each of the 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. Clinicians used 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. 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.

  5. Advanced Technology Multiple Criteria Decision Model.

    DTIC Science & Technology

    1981-11-01

    significantly impact upon this decision. Initial cost would also certainly impact upon the economic feasibility of a particular weapon system. 1 It is also...SHUTDOON TIME Es56P LIABILITY .7 PAINT. AND OPER. *S6 LIFETIME THERMAL ENERGY .2 VOLUU LIZE .3 WEIGHT FUEL USED GROuTH POTENTIAL .2 ENVIPON. CONSTR. .3

  6. Validating Multivariate Decision Modeling for Educational Planning.

    ERIC Educational Resources Information Center

    Wholeben, Brent Edward

    Complex decision-making environments often demand that a range of alternative strategies be identified and compared for their shared value in achieving desired ends. Simple parametric statistical procedures such as analysis of variance and discriminant function analysis can be used in such situations to compare (using selected criteria) the value…

  7. Cognitive Modeling and Robust Decision Making

    DTIC Science & Technology

    2012-03-05

    Uncertainty • Causal Reasoning and Bayesian /Machine Learning Algorithms • Neural Basis of Cognition and Decision • Computational Cognitive...EECS) The Scientific Challenge: The Holy Grail of Neuroscience - What is the neural code ? - Can we “reconstruct” cognition from neural spiking...statistical inference, etc. Neuroscience: implementing the solution by the neural architecture (including hardware and currency). Behavior

  8. 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.

  9. 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.

  10. Open parallel cooperative and competitive decision processes: a potential provenance for quantum probability decision models.

    PubMed

    Fuss, Ian G; Navarro, Daniel J

    2013-10-01

    In recent years quantum probability models have been used to explain many aspects of human decision making, and as such quantum models have been considered a viable alternative to Bayesian models based on classical probability. One criticism that is often leveled at both kinds of models is that they lack a clear interpretation in terms of psychological mechanisms. In this paper we discuss the mechanistic underpinnings of a quantum walk model of human decision making and response time. The quantum walk model is compared to standard sequential sampling models, and the architectural assumptions of both are considered. In particular, we show that the quantum model has a natural interpretation in terms of a cognitive architecture that is both massively parallel and involves both co-operative (excitatory) and competitive (inhibitory) interactions between units. Additionally, we introduce a family of models that includes aspects of the classical and quantum walk models.

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

    PubMed

    Lee, George; 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.

  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. Four Factors of Clinical Decision Making: A Teaching Model.

    ERIC Educational Resources Information Center

    Leist, James C.; Konen, Joseph C.

    1996-01-01

    Four factors of clinical decision making identified by medical students include quality of care, cost, ethics, and legal concerns. This paper argues that physicians have two responsibilities in the clinical decision-making model: to be the primary advocate for quality health care and to ensure balance among the four factors, working in partnership…

  15. Ethnographic Decision Tree Modeling: A Research Method for Counseling Psychology.

    ERIC Educational Resources Information Center

    Beck, Kirk A.

    2005-01-01

    This article describes ethnographic decision tree modeling (EDTM; C. H. Gladwin, 1989) as a mixed method design appropriate for counseling psychology research. EDTM is introduced and located within a postpositivist research paradigm. Decision theory that informs EDTM is reviewed, and the 2 phases of EDTM are highlighted. The 1st phase, model…

  16. 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.…

  17. Validation of a transparent decision model to rate drug interactions

    PubMed Central

    2012-01-01

    Background Multiple databases provide ratings of drug-drug interactions. The ratings are often based on different criteria and lack background information on the decision making process. User acceptance of rating systems could be improved by providing a transparent decision path for each category. Methods We rated 200 randomly selected potential drug-drug interactions by a transparent decision model developed by our team. The cases were generated from ward round observations and physicians’ queries from an outpatient setting. We compared our ratings to those assigned by a senior clinical pharmacologist and by a standard interaction database, and thus validated the model. Results The decision model rated consistently with the standard database and the pharmacologist in 94 and 156 cases, respectively. In two cases the model decision required correction. Following removal of systematic model construction differences, the DM was fully consistent with other rating systems. Conclusion The decision model reproducibly rates interactions and elucidates systematic differences. We propose to supply validated decision paths alongside the interaction rating to improve comprehensibility and to enable physicians to interpret the ratings in a clinical context. PMID:22950884

  18. A spiral model of musical decision-making

    PubMed Central

    Bangert, Daniel; Schubert, Emery; Fabian, Dorottya

    2014-01-01

    This paper describes a model of how musicians make decisions about performing notated music. The model builds on psychological theories of decision-making and was developed from empirical studies of Western art music performance that aimed to identify intuitive and deliberate processes of decision-making, a distinction consistent with dual-process theories of cognition. The model proposes that the proportion of intuitive (Type 1) and deliberate (Type 2) decision-making processes changes with increasing expertise and conceptualizes this change as movement along a continually narrowing upward spiral where the primary axis signifies principal decision-making type and the vertical axis marks level of expertise. The model is intended to have implications for the development of expertise as described in two main phases. The first is movement from a primarily intuitive approach in the early stages of learning toward greater deliberation as analytical techniques are applied during practice. The second phase occurs as deliberate decisions gradually become automatic (procedural), increasing the role of intuitive processes. As a performer examines more issues or reconsiders decisions, the spiral motion toward the deliberate side and back to the intuitive is repeated indefinitely. With increasing expertise, the spiral tightens to signify greater control over decision type selection. The model draws on existing theories, particularly Evans’ (2011) Intervention Model of dual-process theories, Cognitive Continuum Theory Hammond et al. (1987), Hammond (2007), Baylor’s (2001) U-shaped model for the development of intuition by level of expertise. By theorizing how musical decision-making operates over time and with increasing expertise, this model could be used as a framework for future research in music performance studies and performance science more generally. PMID:24795673

  19. 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…

  20. 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…

  1. 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.

  2. 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.

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

    PubMed Central

    Rao, Rajesh P. N.

    2010-01-01

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

  4. Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage.

    PubMed

    Watson, Samuel I; Chen, Yen-Fu; Nguyen-Van-Tam, Jonathan S; Myles, Puja R; Venkatesan, Sudhir; Zambon, Maria; Uthman, Olalekan; Chilton, Peter J; Lilford, Richard J

    2016-01-01

    Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence. Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling. Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile. Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule.

  5. Evidence synthesis and decision modelling to support complex decisions: stockpiling neuraminidase inhibitors for pandemic influenza usage

    PubMed Central

    Watson, Samuel I.; Chen, Yen-Fu; Nguyen-Van-Tam, Jonathan S.; Myles, Puja R.; Venkatesan, Sudhir; Zambon, Maria; Uthman, Olalekan; Chilton, Peter J.; Lilford, Richard J.

    2017-01-01

    Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence. Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling. Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile. Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule. PMID:28413608

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

    NASA Astrophysics Data System (ADS)

    Rodríguez, Rosa M.; Martínez, Luis

    2013-01-01

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

  7. An integrated ethical decision-making model for nurses.

    PubMed

    Park, Eun-Jun

    2012-01-01

    The study reviewed 20 currently-available structured ethical decision-making models and developed an integrated model consisting of six steps with useful questions and tools that help better performance each step: (1) the identification of an ethical problem; (2) the collection of additional information to identify the problem and develop solutions; (3) the development of alternatives for analysis and comparison; (4) the selection of the best alternatives and justification; (5) the development of diverse, practical ways to implement ethical decisions and actions; and (6) the evaluation of effects and development of strategies to prevent a similar occurrence. From a pilot-test of the model, nursing students reported positive experiences, including being satisfied with having access to a comprehensive review process of the ethical aspects of decision making and becoming more confident in their decisions. There is a need for the model to be further tested and refined in both the educational and practical environments.

  8. Business models for health care decision support.

    PubMed

    Gaughan, Phil

    2003-01-01

    CareScience, Inc. is a public company (NASDAQ: CARE) that originated ten years ago to commercialize risk adjustment and complication predictions developed by the Wharton School of Business and the University of Pennsylvania School of Medicine. Over the past decade, the company has grown to approximately 200 clients and 150 employees. Among the "firsts" recorded by the company, CareScience was the first to offer a clinical decision support system as an Application Service Provider (ASP), the first to offer peer-to-peer clinical data sharing among health care provider organizations and practitioners (Santa Barbara Care Data Exchange), and the first to provide a care management outsourcing arrangement.

  9. Application of seismic multi-attribute fusion method based on D-S evidence theory in prediction of CBM-enriched area

    NASA Astrophysics Data System (ADS)

    Qi, Xue-Mei; Zhang, Shao-Cong

    2012-03-01

    D-S evidence theory provides a good approach to fuse uncertain information. In this article, we introduce seismic multi-attribute fusion based on D-S evidence theory to predict the coalbed methane (CBM) concentrated areas. First, we choose seismic attributes that are most sensitive to CBM content changes with the guidance of CBM content measured at well sites. Then the selected seismic attributes are fused using D-S evidence theory and the fusion results are used to predict CBM-enriched area. The application shows that the predicted CBM content and the measured values are basically consistent. The results indicate that using D-S evidence theory in seismic multi-attribute fusion to predict CBM-enriched areas is feasible.

  10. Saccadic brightness decisions do not use a difference model.

    PubMed

    Liston, Dorion B; Stone, Leland S

    2013-07-01

    Eye movements are the most frequent (∼3 per second), shortest-latency (∼150-250 ms), and biomechanically simplest (1 joint, no inertial complexities) voluntary motor behavior in primates, providing a model sensorimotor decision-making system. Current computational "difference" models of choice behavior utilize a single decision variable encoding the difference between two alternate signals, often implemented as a log-likelihood ratio. Alternatively, the oculomotor literature describes a "race" mechanism, in which two separate decision variables encoding the two alternate signals race against one another independently. These two models make two qualitatively distinct predictions, which can be tested empirically with a two-alternative forced-choice task. Unlike the race model, a decision variable based upon a differencing operation predicts strong mirror image correlations between response time (RT) and the signal strengths of the selected and unselected stimuli (because differencing creates equal and opposite correlations). In a saccadic brightness discrimination task, we observed positive correlations between response rate (1/RT) and the strength of both the selected and unselected stimulus, a simple qualitative prediction of race models that applies to any 2AFC task but which is fundamentally at odds with the most basic prediction of any difference model. Our data are, however, qualitatively consistent with a mechanism in which two competing motor plans co-exist and their two corresponding neural decision variables race to a threshold to drive the saccadic decision.

  11. 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.

  12. Fatigue models as practical tools: diagnostic accuracy and decision thresholds.

    PubMed

    Raslear, Thomas G; Coplen, Michael

    2004-03-01

    Human fatigue models are increasingly being used in a variety of industrial settings, both civilian and military. Current uses include education, awareness, and analysis of individual or group work schedules. Perhaps the ultimate and potentially most beneficial use of human fatigue models is to diagnose if an individual is sufficiently rested to perform a period of duty safely or effectively. When used in this way, two important questions should be asked: 1) What is the accuracy of the diagnosis for duty-specific performance in this application; and 2) What decision threshold is appropriate for this application (i.e., how "fatigued" does an individual have to be to be considered "not safe"). In the simplest situation, a diagnostic fatigue test must distinguish between two states: "fatigued" and "not fatigued," and the diagnostic decisions are "safe" (or "effective") and "not safe" (or "not effective"). The resulting four decision outcomes include diagnostic errors because diagnostic tests are not perfectly accurate. Moreover, since all outcomes have costs and benefits associated with them that differ between applications, the choice of a decision criterion is extremely important. Signal Detection Theory (SDT) has demonstrated usefulness in measuring the accuracy of diagnostic tests and optimizing diagnostic decisions. This paper describes how SDT can be applied to foster the development of fatigue models as practical diagnostic and decision-making tools. By clarifying the difference between accuracy (or sensitivity) and decision criterion (or bias) in the use of fatigue models as diagnostic and decision-making tools, the SDT framework focuses on such critical issues as duty-specific performance, variability (model and performance), and model sensitivity, efficacy, and utility. As fatigue models become increasingly used in a variety of different applications, it is important that end-users understand the interplay of these factors for their particular application.

  13. 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

  14. 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.

  15. 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.

  16. Incorporating risk attitude into Markov-process decision models: importance for individual decision making.

    PubMed

    Cher, D J; Miyamoto, J; Lenert, L A

    1997-01-01

    Most decision models published in the medical literature take a risk-neutral perspective. Under risk neutrality, the utility of a gamble is equivalent to its expected value and the marginal utility of living a given unit of time is the same regardless of when it occurs. Most patients, however, are not risk-neutral. Not only does risk aversion affect decision analyses when tradeoffs between short- and long-term survival are involved, it also affects the interpretation of time-tradeoff measures of health-state utility. The proportional time tradeoff under- or overestimates the disutility of an inferior health state, depending on whether the patient is risk-seeking or risk-averse (it is unbiased if the patient is risk-neutral). The authors review how risk attitude with respect to gambles for survival duration can be incorporated into decision models using the framework of risk-adjusted quality-adjusted life years (RA-QALYs). They present a simple extension of this framework that allows RA-QALYs to be calculated for Markov-process decision models. Using a previously published Markov-process model of surgical vs expectant treatment for benign prostatic hypertrophy (BPH), they show how attitude towards risk affects the expected number of QALYs calculated by the model. In this model, under risk neutrality, surgery was the preferred option. Under mild risk aversion, expectant treatment was the preferred option. Risk attitude is an important aspect of preferences that should be incorporated into decision models where one treatment option has upfront risks of morbidity or mortality.

  17. A Decision Model for Locating Controversial Facilities

    ERIC Educational Resources Information Center

    Mumphrey, Anthony J.; And Others

    1971-01-01

    Locating controversial public facilities, such as highways or airports, that generate significant public opposition requires a more sophisticated methodology than the traditional least cost" procedures for minimizing physical costs. Two models--a short-run political placation" model and a long-run welfare distribution" model--evaluate the…

  18. 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

  19. Evaluating Child Welfare policies with decision-analytic simulation models

    PubMed Central

    Goldhaber-Fiebert, Jeremy D.; Bailey, Stephanie L.; Hurlburt, Michael S.; Zhang, Jinjin; Snowden, Lonnie R.; Wulczyn, Fred; Landsverk, John; Horwitz, Sarah M.

    2013-01-01

    The objective was to demonstrate decision-analytic modeling in support of Child Welfare policymakers considering implementing evidence-based interventions. Outcomes included permanency (e.g., adoptions) and stability (e.g., foster placement changes). Analyses of a randomized trial of KEEP -- a foster parenting intervention -- and NSCAW-1 estimated placement change rates and KEEP's effects. A microsimulation model generalized these findings to other Child Welfare systems. The model projected that KEEP could increase permanency and stability, identifying strategies targeting higher-risk children and geographical regions that achieve benefits efficiently. Decision-analytic models enable planners to gauge the value of potential implementations. PMID:21861204

  20. Making Invasion models useful for decision makers; incorporating uncertainty, knowledge gaps, and decision-making preferences

    Treesearch

    Denys Yemshanov; Frank H Koch; Mark Ducey

    2015-01-01

    Uncertainty is inherent in model-based forecasts of ecological invasions. In this chapter, we explore how the perceptions of that uncertainty can be incorporated into the pest risk assessment process. Uncertainty changes a decision maker’s perceptions of risk; therefore, the direct incorporation of uncertainty may provide a more appropriate depiction of risk. Our...

  1. Decision making in the transtheoretical model of behavior change.

    PubMed

    Prochaska, James O

    2008-01-01

    Decision making is an integral part of the transtheoretical model of behavior change. Stage of change represents a temporal dimension for behavior change and has been the key dimension for integrating principles and processes of change from across leading theories of psychotherapy and behavior change. The decision-making variables representing the pros and cons of changing have been found to have systematic relationships across the stages of change for 50 health-related behaviors. Implications of these patterns of relationships are discussed in the context of helping patients make more effective decisions to decrease health risk behaviors and increase health-enhancing behaviors.

  2. Creating operations research models to guide RHIO decision making

    PubMed Central

    Ferris, Michael; Brennan, Patricia Flatley; Tang, Lisa; Marquard, Jenna; Robinson, Stephen; Wright, Stephen

    2007-01-01

    Eight years of progress towards the creation of a national health information network has resulted in a plethora of health data exchange relationships, most commonly called regional health information organizations (RHIOs). Various network types reflect both governance decisions and practical aspects, such as the need for a variety of information sharing pathways between and among organizations. Applying systematic business planning approaches will help ensure that decisions about structure, governance, pricing and incentives lead to RHIO arrangements that meet both the RHIOs’ and the participants’ business goals. This paper describes the model formulation stage of an ongoing project that applies operations research methods to RHIO participation decisions. PMID:18693834

  3. Creating operations research models to guide RHIO decision making.

    PubMed

    Ferris, Michael; Brennan, Patricia Flatley; Tang, Lisa; Marquard, Jenna; Robinson, Stephen; Wright, Stephen

    2007-10-11

    Eight years of progress towards the creation of a national health information network has resulted in a plethora of health data exchange relationships, most commonly called regional health information organizations (RHIOs). Various network types reflect both governance decisions and practical aspects, such as the need for a variety of information sharing pathways between and among organizations. Applying systematic business planning approaches will help ensure that decisions about structure, governance, pricing and incentive lead to RHIO arrangements that meet both the RHIOs' and the participants' business goals. This paper describes the model formulation stage of an ongoing project that applies operations research methods to RHIO participation decisions.

  4. The DO ART Model: An Ethical Decision-Making Model Applicable to Art Therapy

    ERIC Educational Resources Information Center

    Hauck, Jessica; Ling, Thomson

    2016-01-01

    Although art therapists have discussed the importance of taking a positive stance in terms of ethical decision making (Hinz, 2011), an ethical decision-making model applicable for the field of art therapy has yet to emerge. As the field of art therapy continues to grow, an accessible, theoretically grounded, and logical decision-making model is…

  5. The DO ART Model: An Ethical Decision-Making Model Applicable to Art Therapy

    ERIC Educational Resources Information Center

    Hauck, Jessica; Ling, Thomson

    2016-01-01

    Although art therapists have discussed the importance of taking a positive stance in terms of ethical decision making (Hinz, 2011), an ethical decision-making model applicable for the field of art therapy has yet to emerge. As the field of art therapy continues to grow, an accessible, theoretically grounded, and logical decision-making model is…

  6. Patient participation in collective healthcare decision making: the Dutch model.

    PubMed

    van de Bovenkamp, Hester M; Trappenburg, Margo J; Grit, Kor J

    2010-03-01

    To study whether the Dutch participation model is a good model of participation. Patient participation is on the agenda, both on the individual and the collective level. In this study, we focus on the latter by looking at the Dutch model in which patient organizations are involved in many formal decision-making processes. This model can be described as neo-corporatist. We did 52 interviews with actors in the healthcare field, 35 of which were interviews with representatives of patient organizations and 17 with actors that involved patient organizations in their decision making. Dutch patient organizations have many opportunities to participate in formal healthcare decision making and, as a result, have become institutionalized. Although there were several examples identified in which patient organizations were able to influence decision making, patient organizations remain in a dependent position, which they try to overcome through professionalization. Although this model of participation gives patient organizations many opportunities to participate, it also causes important tensions. Many organizations cannot cope with all the participation possibilities attributed to them. This participation abundance can therefore cause redistribution effects. Furthermore, their dependent position leads to the danger of being put to instrumental use. Moreover, professionalization causes tensions concerning empowerment possibilities and representativeness. Conclusion Although the Dutch model tries to make patient organizations an equal party in healthcare decision making, this goal is not reached in practice. It is therefore important to study more closely which subjects patients can and should contribute to, and in what way.

  7. Multialternative decision field theory: a dynamic connectionist model of decision making.

    PubMed

    Roe, R M; Busemeyer, J R; Townsend, J T

    2001-04-01

    The authors interpret decision field theory (J. R. Busemeyer & J. T. Townsend, 1993) as a connectionist network and extend it to accommodate multialternative preferential choice situations. This article shows that the classic weighted additive utility model (see R. L. Keeney & H. Raiffa, 1976) and the classic Thurstone preferential choice model (see L. L. Thurstone, 1959) are special cases of this new multialternative decision field theory (MDFT), which also can emulate the search process of the popular elimination by aspects (EBA) model (see A. Tversky, 1969). The new theory is unique in its ability to explain several central empirical results found in the multialternative preference literature with a common set of principles. These empirical results include the similarity effect, the attraction effect, and the compromise effect, and the complex interactions among these three effects. The dynamic nature of the model also implies strong testable predictions concerning the moderating effect of time pressure on these three effects.

  8. Development of a Multi-Attribute Utility Analysis Model for Selecting Aquatic Plant Restoration Sites in Reservoirs

    DTIC Science & Technology

    2009-07-01

    efforts. Finally, the water grouping included water clarity as measured by Secchi disk and water flow, which has been shown to interfere greatly with...gradient to the 3-ft depth contour, turbidity (as measured by Secchi disk ), and fetch, among others. In addition to probabilities, importance was assigned...species. Light penetration is determined by using a standard Secchi disk with depth measured in inches. Secchi disk depth (in) measured at 3

  9. A pseudo-sequential choice model for valuing multi-attribute environmental policies or programs in contingent valuation applications

    Treesearch

    Dmitriy Volinskiy; John C Bergstrom; Christopher M Cornwell; Thomas P Holmes

    2010-01-01

    The assumption of independence of irrelevant alternatives in a sequential contingent valuation format should be questioned. Statistically, most valuation studies treat nonindependence as a consequence of unobserved individual effects. Another approach is to consider an inferential process in which any particular choice is part of a general choosing strategy of a survey...

  10. Decision modeling for analyzing fire action outcomes

    Treesearch

    Donald MacGregor; Armando Gonzalez-Caban

    2008-01-01

    A methodology for incident decomposition and reconstruction is developed based on the concept of an "event-frame model." The event-frame model characterizes a fire incident in terms of (a) environmental events that pertain to the fire and the fire context (e.g., fire behavior, weather, fuels) and (b) management events that represent responses to the fire...

  11. Linking process and measurement models of recognition-based decisions.

    PubMed

    Heck, Daniel W; Erdfelder, Edgar

    2017-07-01

    When making inferences about pairs of objects, one of which is recognized and the other is not, the recognition heuristic states that participants choose the recognized object in a noncompensatory way without considering any further knowledge. In contrast, information-integration theories such as parallel constraint satisfaction (PCS) assume that recognition is merely one of many cues that is integrated with further knowledge in a compensatory way. To test both process models against each other without manipulating recognition or further knowledge, we include response times into the r-model, a popular multinomial processing tree model for memory-based decisions. Essentially, this response-time-extended r-model allows to test a crucial prediction of PCS, namely, that the integration of recognition-congruent knowledge leads to faster decisions compared to the consideration of recognition only-even though more information is processed. In contrast, decisions due to recognition-heuristic use are predicted to be faster than decisions affected by any further knowledge. Using the classical German-cities example, simulations show that the novel measurement model discriminates between both process models based on choices, decision times, and recognition judgments only. In a reanalysis of 29 data sets including more than 400,000 individual trials, noncompensatory choices of the recognized option were estimated to be slower than choices due to recognition-congruent knowledge. This corroborates the parallel information-integration account of memory-based decisions, according to which decisions become faster when the coherence of the available information increases. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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)

  17. 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…

  18. A Modular Decision Model for Higher Education Institutions.

    ERIC Educational Resources Information Center

    Ozatalay, Savas; Golin, Myron

    1982-01-01

    In order to provide flexibility in mid-range financial planning in higher education institutions, a predictive modular decision-making model is prepared. Simple computational procedure and a small external information requirement will enable small institutions to utilize the model. (Author/MLW)

  19. Manuals for Editors and Authors: A Decision Model.

    ERIC Educational Resources Information Center

    Kirschner, Paul A.

    A series of eight manuals dealing with the triad text characteristics--learning processes--learning outcomes are being prepared for use by authors and editors as an aid in the design and writing of educational texts. These manuals are based upon a model for the functioning of text characteristics which in turn is part of a decision model for the…

  20. Computer Simulation of Small Group Decisions: Model Three.

    ERIC Educational Resources Information Center

    Hare, A.P.; Scheiblechner, Hartmann

    In a test of three computer models to simulate group decisions, data were used from 31 American and Austrian groups on a total of 307 trials. The task for each group was to predict a series of answers of an unknown subject on a value-orientation questionnaire, after being given a sample of his typical responses. The first model, used the mean of…

  1. 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.

  2. 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

  3. Bayesian Networks for Modeling Dredging Decisions

    DTIC Science & Technology

    2011-10-01

    comments and discussions on modeling of dredging activities. Dr . Andrew F. Casper of the Aquatic Ecology and Invasive Species Branch, Ecosystem Evaluation...report was written by Dr . Martin T. Schultz, Environmental Risk Assessment Branch, Environmental Processes and Engineering Division (EPED...Environmental Laboratory (EL); Thomas D. Borrowman, Environmental Engineering Branch, EPED, EL; and Dr . Mitchell J. Small, Department of Civil and Environmental

  4. Decision Support System for Resource Allocation Model

    DTIC Science & Technology

    1989-04-01

    by Presutti and Trepp in their paper "Much Ado about EOQ." [2) The constraints used in the stock fund model are total stock fund dollars and limits on...Jersey, 1963. 2. Presutti, Victor J., Jr. and Trepp , Richard C., More Ado About Economic Order Ouantities (EOO), Operations Analysis Office

  5. 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.

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

    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.

  8. 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

  9. 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.

  10. A neuro-computational model of economic decisions

    PubMed Central

    Rustichini, Aldo

    2015-01-01

    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

  11. 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.

  12. Uncertainty and validation of health economic decision models.

    PubMed

    Kim, Lois G; Thompson, Simon G

    2010-01-01

    Health economic decision models are based on specific assumptions relating to model structure and parameter estimation. Validation of these models is recommended as an indicator of reliability, but is not commonly reported. Furthermore, models derived from different data and employing different assumptions may produce a variety of results.A Markov model for evaluating the long-term cost-effectiveness of screening for abdominal aortic aneurysm is described. Internal, prospective and external validations are carried out using individual participant data from two randomised trials. Validation is assessed in terms of total numbers and timings of key events, and total costs and life-years. Since the initial model validates well only internally, two further models are developed that better fit the prospective and external validation data. All three models are then extrapolated to a life-time horizon, producing cost-effectiveness estimates ranging from pound1600 to pound4200 per life-year gained.Parameter uncertainty is now commonly addressed in health economic decision modelling. However, the derivation of models from different data sources adds another level of uncertainty. This extra uncertainty should be recognised in practical decision-making and, where possible, specifically investigated through independent model validation.

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

    DTIC Science & Technology

    1981-12-01

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

  14. A new decision support model for preanesthetic evaluation.

    PubMed

    Sobrie, Olivier; Lazouni, Mohammed El Amine; Mahmoudi, Saïd; Mousseau, Vincent; Pirlot, Marc

    2016-09-01

    The principal challenges in the field of anesthesia and intensive care consist of reducing both anesthetic risks and mortality rate. The ASA score plays an important role in patients' preanesthetic evaluation. In this paper, we propose a methodology to derive simple rules which classify patients in a category of the ASA scale on the basis of their medical characteristics. This diagnosis system is based on MR-Sort, a multiple criteria decision analysis model. The proposed method intends to support two steps in this process. The first is the assignment of an ASA score to the patient; the second concerns the decision to accept-or not-the patient for surgery. In order to learn the model parameters and assess its effectiveness, we use a database containing the parameters of 898 patients who underwent preanesthesia evaluation. The accuracy of the learned models for predicting the ASA score and the decision of accepting the patient for surgery is assessed and proves to be better than that of other machine learning methods. Furthermore, simple decision rules can be explicitly derived from the learned model. These are easily interpretable by doctors, and their consistency with medical knowledge can be checked. The proposed model for assessing the ASA score produces accurate predictions on the basis of the (limited) set of patient attributes in the database available for the tests. Moreover, the learned MR-Sort model allows for easy interpretation by providing human-readable classification rules. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  15. 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.

  16. 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.

  17. Dual processing model of medical decision-making

    PubMed Central

    2012-01-01

    Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical

  18. 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.

  19. Assessing the Reliability and Validity of Multi-Attribute Utility Procedures: An Application of the Theory of Generalizability

    DTIC Science & Technology

    1975-07-01

    of the effect of diversion on recidivism among I,os Angeles area juvenile delinquents, and evaluation of the effects of decriminali/.ation of status...ponsor interest. At present (Spring, 1975), SSRI has four programs: Criminal justice ami juvenile delinquency. Typical projects include studies... offenders . Decision analysis and social program evaluation. Typical projects include study of elicitation methods for continuous probability

  20. 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

  1. 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…

  2. 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…

  3. Managing health care decisions and improvement through simulation modeling.

    PubMed

    Forsberg, Helena Hvitfeldt; Aronsson, Håkan; Keller, Christina; Lindblad, Staffan

    2011-01-01

    Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.

  4. Climate Modeling and Analysis with Decision Makers in Mind

    NASA Astrophysics Data System (ADS)

    Jones, A. D.; Jagannathan, K.; Calvin, K. V.; Lamarque, J. F.; Ullrich, P. A.

    2016-12-01

    There is a growing need for information about future climate conditions to support adaptation planning across a wide range of sectors and stakeholder communities. However, our principal tools for understanding future climate - global Earth system models - were not developed with these user needs in mind, nor have we developed transparent methods for evaluating and communicating the credibility of various climate information products with respect to the climate characteristics that matter most to decision-makers. Several recent community engagements have identified a need for "co-production" of knowledge among stakeholders and scientists. Here we highlight some of the barriers to communication and collaboration that must be overcome to improve the dialogue among researchers and climate adaptation practitioners in a meaningful way. Solutions to this challenge are two-fold: 1) new institutional arrangements and collaborative mechanisms designed to improve coordination and understanding among communities, and 2) a research agenda that explicitly incorporates stakeholder needs into model evaluation, development, and experimental design. We contrast the information content in global-scale model evaluation exercises with that required for in specific decision contexts, such as long-term agricultural management decisions. Finally, we present a vision for advancing the science of model evaluation in the context of predicting decision-relevant hydroclimate regime shifts in North America.

  5. A Decision-Making Model Applied to Career Counseling.

    ERIC Educational Resources Information Center

    Olson, Christine; And Others

    1990-01-01

    A four-component model for career decision-making counseling relates each component to assessment questions and appropriate intervention strategies. The components are (1) conceptualization (definition of the problem); (2) enlargement of response repertoire (generation of alternatives); (3) identification of discriminative stimuli (consequences of…

  6. The Integrated Decision Modeling System (IDMS) User’s Manual

    DTIC Science & Technology

    1991-05-01

    AL-TP-1 991-0009 AD-A23 6 033 THE INTEGRATED DECISION MODELING SYSTEM (IDMS) USER’S MANUAL IJonathan C. Fast John N. Taylor Metrica , Incorporated...Looper 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) . PERFORMING ORGANIZATION REPORT NUMBER Metrica , Incorporated 8301 Broadway, Suite 215 San

  7. A Cognitive-Motivational Model of Decision Satisfaction.

    ERIC Educational Resources Information Center

    Small, Ruth V.; Venkatesh, Murali

    2000-01-01

    Introduces the Cognitive-Motivational Model of Decision Satisfaction that extends work on closure and the motivational aspects of instruction and learning. Recognizes the importance of information processing in judgmental tasks and specifies confidence as a major contributing factor to learning satisfaction. Suggests potential applications to…

  8. Modeling Human Decision Processes in Command and Control

    DTIC Science & Technology

    1983-02-14

    1982. 32. Simon, H.A., "Rational Decision Making in Business Organizations," maerican Economic Review, Volume 69, Number 4, 1979, pp. 493-513. 1, " 59...MADISOS NC BW A. 0 61749734)66 83~ 023𔃾 S. . . ... . ,. ..- ,,,- ,.-*.,-4 ALPHATECH, INC. % 1 TR-137 MODELING HUMAN DECISION PROCESSES IN COMMAND AND...THIS PAGE~tSebO Vale A.1tot t ALPHATECH, INC. II lCONTENTS 1. Introduction.. .. **0 S*......... 1.1 Net:hodological framework. .0 •.•. 1 ŕ.2 Human

  9. Rigorously testing multialternative decision field theory against random utility models.

    PubMed

    Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg

    2014-06-01

    Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions.

  10. Dynamical crossover in a stochastic model of cell fate decision

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Hiroki; Kawaguchi, Kyogo; Sagawa, Takahiro

    2017-07-01

    We study the asymptotic behaviors of stochastic cell fate decision between proliferation and differentiation. We propose a model of a self-replicating Langevin system, where cells choose their fate (i.e., proliferation or differentiation) depending on local cell density. Based on this model, we propose a scenario for multicellular organisms to maintain the density of cells (i.e., homeostasis) through finite-ranged cell-cell interactions. Furthermore, we numerically show that the distribution of the number of descendant cells changes over time, thus unifying the previously proposed two models regarding homeostasis: the critical birth death process and the voter model. Our results provide a general platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical mechanics.

  11. 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.

  12. Sinkhole hazard assessment in Minnesota using a decision tree model

    NASA Astrophysics Data System (ADS)

    Gao, Yongli; Alexander, E. Calvin

    2008-05-01

    An understanding of what influences sinkhole formation and the ability to accurately predict sinkhole hazards is critical to environmental management efforts in the karst lands of southeastern Minnesota. Based on the distribution of distances to the nearest sinkhole, sinkhole density, bedrock geology and depth to bedrock in southeastern Minnesota and northwestern Iowa, a decision tree model has been developed to construct maps of sinkhole probability in Minnesota. The decision tree model was converted as cartographic models and implemented in ArcGIS to create a preliminary sinkhole probability map in Goodhue, Wabasha, Olmsted, Fillmore, and Mower Counties. This model quantifies bedrock geology, depth to bedrock, sinkhole density, and neighborhood effects in southeastern Minnesota but excludes potential controlling factors such as structural control, topographic settings, human activities and land-use. The sinkhole probability map needs to be verified and updated as more sinkholes are mapped and more information about sinkhole formation is obtained.

  13. Differential Weighting in Multi-Attribute Utility Measurement: When it Should Not and When it does make a Difference

    DTIC Science & Technology

    1976-08-01

    RESEARCH PROJECTS AGENCY Office of Naval Research • Engineering Psychology Programs DI N STATEM A Approvedl for public relaseD~st4c Uniedes The objective...the Office of Naval Research - Engineering Psychology Programs. Participants in the program are: Decisions and Designs, Incorporated The Oregon...should be addressed to: Dr. Martin A. Tolcott Director, Engineering Psychology Programs Office of Naval Research 800 North Quincy Street Arlington

  14. 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…

  15. 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…

  16. 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.

  17. Decision Support Model for Optimal Management of Coastal Gate

    NASA Astrophysics Data System (ADS)

    Ditthakit, Pakorn; Chittaladakorn, Suwatana

    2010-05-01

    The coastal areas are intensely settled by human beings owing to their fertility of natural resources. However, at present those areas are facing with water scarcity problems: inadequate water and poor water quality as a result of saltwater intrusion and inappropriate land-use management. To solve these problems, several measures have been exploited. The coastal gate construction is a structural measure widely performed in several countries. This manner requires the plan for suitably operating coastal gates. Coastal gate operation is a complicated task and usually concerns with the management of multiple purposes, which are generally conflicted one another. This paper delineates the methodology and used theories for developing decision support modeling for coastal gate operation scheduling. The developed model was based on coupling simulation and optimization model. The weighting optimization technique based on Differential Evolution (DE) was selected herein for solving multiple objective problems. The hydrodynamic and water quality models were repeatedly invoked during searching the optimal gate operations. In addition, two forecasting models:- Auto Regressive model (AR model) and Harmonic Analysis model (HA model) were applied for forecasting water levels and tide levels, respectively. To demonstrate the applicability of the developed model, it was applied to plan the operations for hypothetical system of Pak Phanang coastal gate system, located in Nakhon Si Thammarat province, southern part of Thailand. It was found that the proposed model could satisfyingly assist decision-makers for operating coastal gates under various environmental, ecological and hydraulic conditions.

  18. 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.

  19. A decision model for community nurses providing bereavement care.

    PubMed

    Brownhill, Suzanne; Chang, Esther; Bidewell, John; Johnson, Amanda

    2013-03-01

    Community (district) nurses play a significant role in assisting and supporting bereaved informal carers (family members and friends) of recently decease clients of palliative care. Bereavement care demands a wide range of competencies including clinical decision-making. To date, little has been known about the decision-making role of community nurses in Australia. The aim of this study was to conduct in-depth examination of an existing data set generated from semi-structured interviews of 10 community nurses providing follow-up bereavement care home visits within an area health service of a metropolitan region of Sydney, Australia. A grounded theory approach to data analysis generated a model, which highlights an interaction between 'the relationship','the circumstances' (surrounding the bereavement),'the psychosocial variant', 'the mix of nurses', 'the workload', and 'the support' available for the bereaved and for community nurses, and elements of 'the visit' (central to bereavement care). The role of community nurses in bereavement care is complex, particularly where decision-making is discretionary and contingent on multiple variables that effect the course of the family's grief. The decision model has the potential to inform community nurses in their support of informal carers, to promote reflective practice and professional accountability, ensuring continuing competence in bereavement care.

  20. Patient participation in collective healthcare decision making: the Dutch model

    PubMed Central

    Van De Bovenkamp, Hester M.; Trappenburg, Margo J.; Grit, Kor J.

    2009-01-01

    Abstract Objective  To study whether the Dutch participation model is a good model of participation. Background  Patient participation is on the agenda, both on the individual and the collective level. In this study, we focus on the latter by looking at the Dutch model in which patient organizations are involved in many formal decision‐making processes. This model can be described as neo‐corporatist. Design  We did 52 interviews with actors in the healthcare field, 35 of which were interviews with representatives of patient organizations and 17 with actors that involved patient organizations in their decision making. Results  Dutch patient organizations have many opportunities to participate in formal healthcare decision making and, as a result, have become institutionalized. Although there were several examples identified in which patient organizations were able to influence decision making, patient organizations remain in a dependent position, which they try to overcome through professionalization. Discussion  Although this model of participation gives patient organizations many opportunities to participate, it also causes important tensions. Many organizations cannot cope with all the participation possibilities attributed to them. This participation abundance can therefore cause redistribution effects. Furthermore, their dependent position leads to the danger of being put to instrumental use. Moreover, professionalization causes tensions concerning empowerment possibilities and representativeness. Conclusion  Although the Dutch model tries to make patient organizations an equal party in healthcare decision making, this goal is not reached in practice. It is therefore important to study more closely which subjects patients can and should contribute to, and in what way. PMID:19719537

  1. Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making.

    PubMed

    Hatfield, Laura A; Baugh, Christine M; Azzone, Vanessa; Normand, Sharon-Lise T

    2017-07-01

    Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score-based decisions, even when the loss functions or hierarchical models are misspecified. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.

  2. Operator Decision-Making Characteristics.

    DTIC Science & Technology

    1979-11-01

    functions for possible outcomes. Multi-Attribute Utility Theory ( MAUT ) MAUT involves a conjoint worth measurement in an uncertain environ- ment. The utility ...pp. 460-81. VonWnterfeldt, D., and G. W. Fischer. " Multiattribute Utility Theory : Models and Assessment Procedures," in apt ?’,o’a’f,, , i I Hwman IX...48 Utility Theory ....... ............................... 49 Operator Performance .......... .................... 53

  3. A System Dynamics Model for Integrated Decision Making ...

    EPA Pesticide Factsheets

    EPA’s Sustainable and Healthy Communities Research Program (SHC) is conducting transdisciplinary research to inform and empower decision-makers. EPA tools and approaches are being developed to enable communities to effectively weigh and integrate human health, socioeconomic, environmental, and ecological factors into their decisions to promote community sustainability. To help achieve this goal, EPA researchers have developed systems approaches to account for the linkages among resources, assets, and outcomes managed by a community. System dynamics (SD) is a member of the family of systems approaches and provides a framework for dynamic modeling that can assist with assessing and understanding complex issues across multiple dimensions. To test the utility of such tools when applied to a real-world situation, the EPA has developed a prototype SD model for community sustainability using the proposed Durham-Orange Light Rail Project (D-O LRP) as a case study.The EPA D-O LRP SD modeling team chose the proposed D-O LRP to demonstrate that an integrated modeling approach could represent the multitude of related cross-sectoral decisions that would be made and the cascading impacts that could result from a light rail transit system connecting Durham and Chapel Hill, NC. In keeping with the SHC vision described above, the proposal for the light rail is a starting point solution for the more intractable problems of population growth, unsustainable land use, environmenta

  4. A System Dynamics Model for Integrated Decision Making ...

    EPA Pesticide Factsheets

    EPA’s Sustainable and Healthy Communities Research Program (SHC) is conducting transdisciplinary research to inform and empower decision-makers. EPA tools and approaches are being developed to enable communities to effectively weigh and integrate human health, socioeconomic, environmental, and ecological factors into their decisions to promote community sustainability. To help achieve this goal, EPA researchers have developed systems approaches to account for the linkages among resources, assets, and outcomes managed by a community. System dynamics (SD) is a member of the family of systems approaches and provides a framework for dynamic modeling that can assist with assessing and understanding complex issues across multiple dimensions. To test the utility of such tools when applied to a real-world situation, the EPA has developed a prototype SD model for community sustainability using the proposed Durham-Orange Light Rail Project (D-O LRP) as a case study.The EPA D-O LRP SD modeling team chose the proposed D-O LRP to demonstrate that an integrated modeling approach could represent the multitude of related cross-sectoral decisions that would be made and the cascading impacts that could result from a light rail transit system connecting Durham and Chapel Hill, NC. In keeping with the SHC vision described above, the proposal for the light rail is a starting point solution for the more intractable problems of population growth, unsustainable land use, environmenta

  5. 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.

  6. Limitations of multimedia models for use in environmental decision making.

    PubMed

    Travis, C C; Obenshain, K R; Regens, J L; Whipple, C G

    2001-09-01

    The United States currently is engaged in a complex, multi-billion dollar effort to cleanup a legacy of both privately- and federally-owned hazardous waste sites. Decisions regarding the best approach for remediation of these sites often are based on the analysis of potential risks to human health and the environment. A cornerstone of such analysis is the frequent use of computerized multimedia environmental transport models, to evaluate the large quantities of information necessary to understand the present and future implications of contamination at a site. One barrier to wide-spread use of this analytical procedure is the view that results obtained using computer models are highly dependent on user input, and therefore, subject to manipulation. It is widely recognized that for decisions to be both credible and implementable, the public must have confidence in both the scientific basis for judgments involved and the decision processes employed (NRC, 1983). Our purpose in this article is to overview the difficulties associated with application of multimedia models to real world problems and the contribution these models can make to technically sound estimates of exposure and risk.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. CSL Model Checking of Biochemical Networks with Interval Decision Diagrams

    NASA Astrophysics Data System (ADS)

    Schwarick, Martin; Heiner, Monika

    This paper presents an Interval Decision Diagram based approach to symbolic CSL model checking of Continuous Time Markov Chains which are derived from stochastic Petri nets. Matrix-vector and vector-matrix multiplication are the major tasks of exact analysis. We introduce a simple, but powerful algorithm which uses explicitly the Petri net structure and allows for parallelisation. We present results demonstrating the efficiency of our first prototype implementation when applied to biochemical network models, specifically with increasing token numbers. Our tool currently supports CSL model checking of time-bounded operators and the Next operator for ordinary stochastic Petri nets.

  12. 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.

  13. Development of a robust space power system decision model

    NASA Astrophysics Data System (ADS)

    Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert

    2001-02-01

    NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .

  14. Integrated models to support multiobjective ecological restoration decisions.

    PubMed

    Fraser, Hannah; Rumpff, Libby; Yen, Jian D L; Robinson, Doug; Wintle, Brendan A

    2017-03-24

    Many objectives motivate ecological restoration including improving vegetation condition, increasing the range and abundance of threatened species, and improving aggregate measures of biodiversity such as richness and diversity. While ecological models have been used to examine the outcomes of ecological restoration, there are few attempts to develop models to account for multiple, potentially competing objectives. We develop the first predictive model that integrates a vegetation-focused state-and-transition model with species distribution models for birds. We demonstrate how this integrated model can be used to identify effective restoration options for vegetation and bird species under a constrained budget. For example, using a typical agricultural land management scenario from south-eastern Australia, we demonstrate how the optimal management actions for promoting the occurrence of the Brown Treecreeper, an iconic threatened species, may be suboptimal for meeting vegetation condition objectives. This highlights that any 'preferred' management decision depends on the value assigned to the different objectives. An exploration of sensitivity to value weightings highlighted that 'no management' or 'weed control' were most likely to be the best management options to meet multiple objectives in the scenario we explored. We thus illustrate an approach to using the model outputs to explore trade-offs between bird and vegetation objectives. Our approach to exploring management outcomes and trade-offs using integrated modelling and structured decision support approaches has wide application for conservation management problems in which trade-offs exist between competing objectives. This article is protected by copyright. All rights reserved.

  15. [Comparative analysis of the promoting blood effects of the combination of different proportions of danggui and honghua by the principal component analysis and multi-attribute comprehensive index methods].

    PubMed

    Li, Shu-Jiao; Li, Wei-Xia; Tang, Yu-Ping; Shen, Juan; Shang, Er-Xin; Guo, Jian-Ming; Duan, Jin-Ao

    2014-09-01

    The combination of Danggui and Honghua (GH) is a popular herb pair commonly used in clinic for the treatment of blood stasis syndrome in China. To evaluate the activating blood circulation and dissipating blood stasis effects of the combination of different proportions of Danggui and Honghua on acute blood stasis rats, and optimize the proportion of GH to have the best activating blood circulation and dissipating blood stasis effect. Acute blood stasis rat model was induced by subcutaneous injection of adrenaline and ice water bath. The blood stasis rats were administrated intragastrically with GH (1 : 0, 4 : 1, 2 : 1, 3 : 2, 1 : 1, 2 : 3, 1: 2, 1 : 4 and 0 : 1) extracts. The whole blood viscosity (WBV), plasma viscosity (PV), and high shear whole blood relative index (HSWBRI), low shear whole blood relative index (LSWBRI), and erythrocyte aggregation index (EAI) were tested to observe the effects of GH on hemorheology of blood stasis rats. And the maximum aggregation induced by adenosine diphosphate (ADP) was tested to observe the effect of GH on platelet aggregation index of blood stasis rats. In addition, the prothrombin time (PT), thrombin time (TT), activated partial thromboplastin time (APTT) and plasma fibrinogen (FIB) were tested to observe the effects of GH on blood coagulation function of blood stasis rats. Then principal component analysis and multi-attribute comprehensive index methods were both used to comprehensively evaluate the total activating blood circulation and dissipating blood stasis effects of GH. The results showed that the hemorheological indexes and coagulation parameters of model group both had significant differences with normal group. Compared with model group, GH (1 : 0, 4 : 1, 2: 1, 3 : 2, 1 : 1, 2 : 3, 1 : 2, 1 : 4 and 0 : 1) could improve all the blood hemorheology indexes and regulate part indexes of blood coagulation function and platelet aggregation in acute blood stasis rats. Based on principal component analysis and multi-attribute

  16. 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.

  17. 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.

  18. 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

  19. Combining decision support and image processing: a PROforma model.

    PubMed

    Sordo, M; Fox, J; Blum, C; Taylor, P; Lee, R; Alberdi, E

    2001-01-01

    This paper addresses two important problems in medical image interpretation:(1) integration of numeric and symbolic information, (2) access to external sources of medical knowledge. We have developed a prototype in which image processing algorithms are combined with symbolic representations for reasoning, decision making and task management in an integrated, platform-independent system for the differential diagnosis of abnormalities in mammograms. The prototype is based on PROforma, a generic technology for building decision support systems based on clinical guidelines. The PROforma language defines a set of tasks, one of which, the enquiry, is used as means of interaction with the outside world. However, the current enquiry model has proved to be too limited for our purposes. In this paper we outline a more general model, which can be used as an interface between symbolic functions and image or other signal data.

  20. 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

  1. A Signal Detection Model of Compound Decision Tasks

    DTIC Science & Technology

    2006-12-01

    A signal detection model of compound decision tasks Matthew Duncan Defence R& D Canada Technical Report DRDC Toronto TR 2006-256 December 2006...tasks Matthew Duncan Defence R& D Canada – Toronto Technical Report DRDC Toronto TR 2006-256 December 2006 Author Original approved by...la prise de décision, il faut une méthode formelle pour distinguer (clarifier) les effets des divers facteurs, et pour simplifier l’évaluation des

  2. 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.

  3. Effects of stochastic interest rates in decision making under risk: A Markov decision process model for forest management

    Treesearch

    Mo Zhou; Joseph Buongiorno

    2011-01-01

    Most economic studies of forest decision making under risk assume a fixed interest rate. This paper investigated some implications of this stochastic nature of interest rates. Markov decision process (MDP) models, used previously to integrate stochastic stand growth and prices, can be extended to include variable interest rates as well. This method was applied to...

  4. Modeling Reaction Time and Accuracy of Multiple-Alternative Decisions

    PubMed Central

    Leite, Fábio P.; Ratcliff, Roger

    2009-01-01

    Several sequential sampling models using racing diffusion processes for multiple-alternative decisions were evaluated using data from two perceptual discrimination experiments. The structures of the models differed on a number of dimensions, including whether there was lateral inhibition between accumulators, whether there was decay in evidence, whether evidence could be negative, and whether there was variability in starting points. Data were collected from a letter discrimination task in which stimulus difficulty and probability of the response alternatives were varied along with number of response alternatives. Model fitting results ruled out a large number of model classes in favor of a smaller number of specific models, most of which showed a moderate to high degree of mimicking. The best-fitting models had zero to moderate values of decay, no inhibition, and assumed that the addition of alternatives either affected the subprocesses contributing to the nondecisional time, the degree of caution, or the quality of evidence extracted from stimuli. PMID:20045893

  5. Boosting alternating decision trees modeling of disease trait information.

    PubMed

    Liu, Kuang-Yu; Lin, Jennifer; Zhou, Xiaobo; Wong, Stephen T C

    2005-12-30

    We applied the alternating decision trees (ADTrees) method to the last 3 replicates from the Aipotu, Danacca, Karangar, and NYC populations in the Problem 2 simulated Genetic Analysis Workshop dataset. Using information from the 12 binary phenotypes and sex as input and Kofendrerd Personality Disorder disease status as the outcome of ADTrees-based classifiers, we obtained a new quantitative trait based on average prediction scores, which was then used for genome-wide quantitative trait linkage (QTL) analysis. ADTrees are machine learning methods that combine boosting and decision trees algorithms to generate smaller and easier-to-interpret classification rules. In this application, we compared four modeling strategies from the combinations of two boosting iterations (log or exponential loss functions) coupled with two choices of tree generation types (a full alternating decision tree or a classic boosting decision tree). These four different strategies were applied to the founders in each population to construct four classifiers, which were then applied to each study participant. To compute average prediction score for each subject with a specific trait profile, such a process was repeated with 10 runs of 10-fold cross validation, and standardized prediction scores obtained from the 10 runs were averaged and used in subsequent expectation-maximization Haseman-Elston QTL analyses (implemented in GENEHUNTER) with the approximate 900 SNPs in Hardy-Weinberg equilibrium provided for each population. Our QTL analyses on the basis of four models (a full alternating decision tree and a classic boosting decision tree paired with either log or exponential loss function) detected evidence for linkage (Z >or= 1.96, p < 0.01) on chromosomes 1, 3, 5, and 9. Moreover, using average iteration and abundance scores for the 12 phenotypes and sex as their relevancy measurements, we found all relevant phenotypes for all four populations except phenotype b for the Karangar population

  6. 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

  7. Markov chain decision model for urinary incontinence procedures.

    PubMed

    Kumar, Sameer; Ghildayal, Nidhi; Ghildayal, Neha

    2017-03-13

    Purpose Urinary incontinence (UI) is a common chronic health condition, a problem specifically among elderly women that impacts quality of life negatively. However, UI is usually viewed as likely result of old age, and as such is generally not evaluated or even managed appropriately. Many treatments are available to manage incontinence, such as bladder training and numerous surgical procedures such as Burch colposuspension and Sling for UI which have high success rates. The purpose of this paper is to analyze which of these popular surgical procedures for UI is effective. Design/methodology/approach This research employs randomized, prospective studies to obtain robust cost and utility data used in the Markov chain decision model for examining which of these surgical interventions is more effective in treating women with stress UI based on two measures: number of quality adjusted life years (QALY) and cost per QALY. Treeage Pro Healthcare software was employed in Markov decision analysis. Findings Results showed the Sling procedure is a more effective surgical intervention than the Burch. However, if a utility greater than certain utility value, for which both procedures are equally effective, is assigned to persistent incontinence, the Burch procedure is more effective than the Sling procedure. Originality/value This paper demonstrates the efficacy of a Markov chain decision modeling approach to study the comparative effectiveness analysis of available treatments for patients with UI, an important public health issue, widely prevalent among elderly women in developed and developing countries. This research also improves upon other analyses using a Markov chain decision modeling process to analyze various strategies for treating UI.

  8. 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.

  9. LATEST: A model of saccadic decisions in space and time.

    PubMed

    Tatler, Benjamin W; Brockmole, James R; Carpenter, R H S

    2017-04-01

    Many of our actions require visual information, and for this it is important to direct the eyes to the right place at the right time. Two or three times every second, we must decide both when and where to direct our gaze. Understanding these decisions can reveal the moment-to-moment information priorities of the visual system and the strategies for information sampling employed by the brain to serve ongoing behavior. Most theoretical frameworks and models of gaze control assume that the spatial and temporal aspects of fixation point selection depend on different mechanisms. We present a single model that can simultaneously account for both when and where we look. Underpinning this model is the theoretical assertion that each decision to move the eyes is an evaluation of the relative benefit expected from moving the eyes to a new location compared with that expected by continuing to fixate the current target. The eyes move when the evidence that favors moving to a new location outweighs that favoring staying at the present location. Our model provides not only an account of when the eyes move, but also what will be fixated. That is, an analysis of saccade timing alone enables us to predict where people look in a scene. Indeed our model accounts for fixation selection as well as (and often better than) current computational models of fixation selection in scene viewing. (PsycINFO Database Record

  10. 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.

  11. 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.

  12. 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.

  13. Pavement maintenance optimization model using Markov Decision Processes

    NASA Astrophysics Data System (ADS)

    Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

    2017-09-01

    This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

  14. Why do multi-attribute utility instruments produce different utilities: the relative importance of the descriptive systems, scale and 'micro-utility' effects.

    PubMed

    Richardson, Jeff; Iezzi, Angelo; Khan, Munir A

    2015-08-01

    Health state utilities measured by the major multi-attribute utility instruments differ. Understanding the reasons for this is important for the choice of instrument and for research designed to reconcile these differences. This paper investigates these reasons by explaining pairwise differences between utilities derived from six multi-attribute utility instruments in terms of (1) their implicit measurement scales; (2) the structure of their descriptive systems; and (3) 'micro-utility effects', scale-adjusted differences attributable to their utility formula. The EQ-5D-5L, SF-6D, HUI 3, 15D and AQoL-8D were administered to 8,019 individuals. Utilities and unweighted values were calculated using each instrument. Scale effects were determined by the linear relationship between utilities, the effect of the descriptive system by comparison of scale-adjusted values and 'micro-utility effects' by the unexplained difference between utilities and values. Overall, 66 % of the differences between utilities was attributable to the descriptive systems, 30.3 % to scale effects and 3.7 % to micro-utility effects. Results imply that the revision of utility algorithms will not reconcile differences between instruments. The dominating importance of the descriptive system highlights the need for researchers to select the instrument most capable of describing the health states relevant for a study. Reconciliation of inconsistent utilities produced by different instruments must focus primarily upon the content of the descriptive system. Utility weights primarily determine the measurement scale. Other differences, attributable to utility formula, are comparatively unimportant.

  15. A spiking network model of decision making employing rewarded STDP.

    PubMed

    Skorheim, Steven; Lonjers, Peter; 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.

  16. The Dutch model for legalizing end-of-life decisions.

    PubMed

    Kater, Loes

    2003-01-01

    The Dutch experience with euthanasia is used as a model for other countries for regulating end-of-life decisions. Several elements of the Dutch debate, for example the definition of euthanasia, are copied and imported to other debates. This paper studies the specific Dutch construction of regulating euthanasia and the concept of the requirements of prudent practice. The requirements of prudent practice embody the conditions for careful medical management in end-of-life decisions. It is argued that the requirements of prudent practice are a relatively acceptable way of regulating the Dutch practice of euthanasia as they are embedded in an elaborate network of relations, standards and values. As a consequence of this local character and the way the requirements of prudent practice relate to the Dutch practice of euthanasia it is difficult to simply transport them to other countries in order to regulate euthanasia.

  17. Prospective decision analysis modeling indicates that clinical decisions in vascular surgery often fail to maximize patient expected utility.

    PubMed

    Brothers, Thomas E; Cox, Montgomery H; Robison, Jacob G; Elliott, Bruce M; Nietert, Paul

    2004-08-01

    Applied prospectively to patients with peripheral arterial disease, individualized decision analysis has the potential to improve the surgeon's ability to optimize patient outcome. A prospective, randomized trial comparing Markov surgical decision analysis to standard decision-making was performed in 206 patients with symptomatic lower extremity arterial disease. Utility assessment and quality of life were determined from individual patients prior to treatment. Vascular surgeons provided estimates of probability of treatment outcome, intended and actual treatment plans, and assessment of comfort with the decision (PDPI). Treatment plans and PDPI evaluations were repeated after each surgeon was made aware of model predictions for half of the patients in a randomized manner. Optimal treatments predicted by decision analysis differed significantly from the surgeon's initial plan and consisted of bypass for 30 versus 29%, respectively, angioplasty for 28 versus 11%, amputation for 31 versus 6%, and medical management for 34 versus 54% (agreement 50%, kappa 0.28). Surgeon awareness of the decision model results did not alter the verbalized final plan, but did trend toward less frequent use of bypass. Patients for whom the model agreed with the surgeon's initial plan were less likely to undergo bypass (13 versus 30%, P < 0.01). Greater surgeon comfort was present when the initial plan and model agreed (PDPI score 47.5 versus 45.6, P < 0.005). Individualized application of a decision model to patients with peripheral arterial disease suggests that arterial bypass is frequently recommended even when it may not maximize patient expected utility.

  18. Implications of Modeling Uncertainty for Water Quality Decision Making

    NASA Astrophysics Data System (ADS)

    Shabman, L.

    2002-05-01

    The report, National Academy of Sciences report, "Assessing the TMDL Approach to Water Quality Management" endorsed the "watershed" and "ambient water quality focused" approach" to water quality management called for in the TMDL program. The committee felt that available data and models were adequate to move such a program forward, if the EPA and all stakeholders better understood the nature of the scientific enterprise and its application to the TMDL program. Specifically, the report called for a greater acknowledgement of model prediction uncertinaity in making and implementing TMDL plans. To assure that such uncertinaity was addressed in water quality decision making the committee called for a commitment to "adaptive implementation" of water quality management plans. The committee found that the number and complexity of the interactions of multiple stressors, combined with model prediction uncertinaity means that we need to avoid the temptation to make assurances that specific actions will result in attainment of particular water quality standards. Until the work on solving a water quality problem begins, analysts and decision makers cannot be sure what the correct solutions are, or even what water quality goals a community should be seeking. In complex systems we need to act in order to learn; adaptive implementation is a concurrent process of action and learning. Learning requires (1) continued monitoring of the waterbody to determine how it responds to the actions taken and (2) carefully designed experiments in the watershed. If we do not design learning into what we attempt we are not doing adaptive implementation. Therefore, there needs to be an increased commitment to monitoring and experiments in watersheds that will lead to learning. This presentation will 1) explain the logic for adaptive implementation; 2) discuss the ways that water quality modelers could characterize and explain model uncertinaity to decision makers; 3) speculate on the implications

  19. Quantum-Like Bayesian Networks for Modeling Decision Making.

    PubMed

    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.

  20. 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

  1. Alternative Approaches to Modeling the Individual Enlistment Decision: A Literature Review

    DTIC Science & Technology

    1987-05-01

    the NRS, ARI has been working on explora- tory development of new quantitative instruments for measuring the factors involved in the career decision ...social and psychological factors influencing young adults’ enlistment decisions . Procedure: The following decision theories/models were reviewed: De...be given to prospective recruits to assess how cognitive, social, and affective components influence the individual enlistment decision process . The

  2. A value model for evaluating homeland security decisions.

    PubMed

    Keeney, Ralph L; von Winterfeldt, Detlof

    2011-09-01

    One of the most challenging tasks of homeland security policymakers is to allocate their limited resources to reduce terrorism risks cost effectively. To accomplish this task, it is useful to develop a comprehensive set of homeland security objectives, metrics to measure each objective, a utility function, and value tradeoffs relevant for making homeland security investments. Together, these elements form a homeland security value model. This article develops a homeland security value model based on literature reviews, a survey, and experience with building value models. The purposes of the article are to motivate the use of a value model for homeland security decision making and to illustrate its use to assess terrorism risks, assess the benefits of countermeasures, and develop a severity index for terrorism attacks. © 2011 Society for Risk Analysis.

  3. 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.

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

    PubMed Central

    Heathcote, Andrew

    2016-01-01

    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

  5. Modeling decision support rule interactions in a clinical setting.

    PubMed

    Sordo, Margarita; Rocha, Beatriz H; Morales, Alfredo A; Maviglia, Saverio M; Oglio, Elisa Dell'Oglio; Fairbanks, Amanda; Aroy, Teal; Dubois, David; Bouyer-Ferullo, Sharon; Rocha, Roberto A

    2013-01-01

    Traditionally, rule interactions are handled at implementation time through rule task properties that control the order in which rules are executed. By doing so, knowledge about the behavior and interactions of decision rules is not captured at modeling time. We argue that this is important knowledge that should be integrated in the modeling phase. In this project, we build upon current work on a conceptual schema to represent clinical knowledge for decision support in the form of if then rules. This schema currently captures provenance of the clinical content, context where such content is actionable (i.e. constraints) and the logic of the rule itself. For this project, we borrowed concepts from both the Semantic Web (i.e., Ontologies) and Complex Adaptive Systems (CAS), to explore a conceptual approach for modeling rule interactions in an enterprise-wide clinical setting. We expect that a more comprehensive modeling will facilitate knowledge authoring, editing and update; foster consistency in rules implementation and maintenance; and develop authoritative knowledge repositories to promote quality, safety and efficacy of healthcare.

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

    PubMed

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

    2017-01-03

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

  7. Structural Uncertainties in Numerical Induction Models

    DTIC Science & Technology

    2006-07-01

    Fuzzy Cognitive Mapping MAUT: Multi-Attribute Utility Theory MCDM: Multi-Criteria Decision Making MOE: Measure of Effectiveness OWA...these decision theoretics can be found in texts such as [1,31,33,40,42,45,62,87,94,100]. 6.4.1 Multi-Attribute Utility Theory (MAUT) This is a...Neumann and Morganstern [89] axiomatised expected utility theory and thus laid the foundations of MAUT, as applied to econometrics. Accordingly, the

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. Early diagnosis model for meningitis supports public health decision making.

    PubMed

    Close, Rebecca M; Ejidokun, Oluwatoyin O; Verlander, Neville Q; Fraser, Graham; Meltzer, Margie; Rehman, Yasmin; Muir, Peter; Ninis, Nelly; Stuart, James M

    2011-07-01

    To develop a predictive model for rapid differential diagnosis of meningitis and meningococcal septicaemia to support public health decisions on chemoprophylaxis for contacts. Prospective study of suspected cases of acute meningitis and meningococcal septicaemia admitted to hospitals in the South West, West Midlands and London Regions of England from July 2008 to June 2009. Epidemiological, clinical and laboratory variables on admission were recorded. Logistic regression was used to derive a predictive model. Of the 719 suspect cases reported, 385 confirmed cases were included in analysis. Peripheral blood polymorphonuclear count of >16 × 10(9)/l, serum C-reactive protein of >100 mg/l and haemorrhagic rash were strongly and independently associated with diagnosis of bacterial meningitis and meningococcal septicaemia. Using a simple scoring system, the presence of any one of these factors gave a probability of >95% in predicting the final diagnosis. We have developed a model using laboratory and clinical factors, but not dependent on availability of CSF, for differentiating acute bacterial from viral meningitis within a few hours of admission to hospital. This scoring system is recommended in public health management of suspected cases of meningitis and meningococcal septicaemia to inform decisions on chemoprophylaxis. Copyright © 2011 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

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

    PubMed

    Ito, Makoto; Doya, Kenji

    2009-08-05

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

  14. An Evaluation of the Decision-Making Capacity Assessment Model.

    PubMed

    Brémault-Phillips, Suzette C; Parmar, Jasneet; Friesen, Steven; Rogers, Laura G; Pike, Ashley; Sluggett, Bryan

    2016-09-01

    The Decision-Making Capacity Assessment (DMCA) Model includes a best-practice process and tools to assess DMCA, and implementation strategies at the organizational and assessor levels to support provision of DMCAs across the care continuum. A Developmental Evaluation of the DMCA Model was conducted. A mixed methods approach was used. Survey (N = 126) and focus group (N = 49) data were collected from practitioners utilizing the Model. Strengths of the Model include its best-practice and implementation approach, applicability to independent practitioners and inter-professional teams, focus on training/mentoring to enhance knowledge/skills, and provision of tools/processes. Post-training, participants agreed that they followed the Model's guiding principles (90%), used problem-solving (92%), understood discipline-specific roles (87%), were confident in their knowledge of DMCAs (75%) and pertinent legislation (72%), accessed consultative services (88%), and received management support (64%). Model implementation is impeded when role clarity, physician engagement, inter-professional buy-in, accountability, dedicated resources, information sharing systems, and remuneration are lacking. Dedicated resources, job descriptions inclusive of DMCAs, ongoing education/mentoring supports, access to consultative services, and appropriate remuneration would support implementation. The DMCA Model offers practitioners, inter-professional teams, and organizations a best-practice and implementation approach to DMCAs. Addressing barriers and further contextualizing the Model would be warranted.

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

    PubMed

    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.

  16. 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

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

    PubMed

    Dolan, James G

    2010-01-01

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

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

    PubMed Central

    Dolan, James G.

    2010-01-01

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

  19. 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.

  20. 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.

  1. 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).

  2. 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).

  3. An Evaluation of the Decision-Making Capacity Assessment Model

    PubMed Central

    Brémault-Phillips, Suzette C.; Parmar, Jasneet; Friesen, Steven; Rogers, Laura G.; Pike, Ashley; Sluggett, Bryan

    2016-01-01

    Background The Decision-Making Capacity Assessment (DMCA) Model includes a best-practice process and tools to assess DMCA, and implementation strategies at the organizational and assessor levels to support provision of DMCAs across the care continuum. A Developmental Evaluation of the DMCA Model was conducted. Methods A mixed methods approach was used. Survey (N = 126) and focus group (N = 49) data were collected from practitioners utilizing the Model. Results Strengths of the Model include its best-practice and implementation approach, applicability to independent practitioners and inter-professional teams, focus on training/mentoring to enhance knowledge/skills, and provision of tools/processes. Post-training, participants agreed that they followed the Model’s guiding principles (90%), used problem-solving (92%), understood discipline-specific roles (87%), were confident in their knowledge of DMCAs (75%) and pertinent legislation (72%), accessed consultative services (88%), and received management support (64%). Model implementation is impeded when role clarity, physician engagement, inter-professional buy-in, accountability, dedicated resources, information sharing systems, and remuneration are lacking. Dedicated resources, job descriptions inclusive of DMCAs, ongoing education/mentoring supports, access to consultative services, and appropriate remuneration would support implementation. Conclusions The DMCA Model offers practitioners, inter-professional teams, and organizations a best-practice and implementation approach to DMCAs. Addressing barriers and further contextualizing the Model would be warranted. PMID:27729947

  4. 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.

  5. Implementation of Dynamic Smart Decision Model for Vertical Handoff

    NASA Astrophysics Data System (ADS)

    Sahni, Nidhi

    2010-11-01

    International Mobile Telecommunications-Advanced (IMT Advanced), better known as 4G is the next level of evolution in the field of wireless communications. 4G Wireless networks enable users to access information anywhere, anytime, with a seamless connection to a wide range of information and services, and receiving a large volume of information, data, pictures, video and thus increasing the demand for High Bandwidth and Signal Strength. The mobility among various networks is achieved through Vertical Handoff. Vertical handoffs refer to the automatic failover from one technology to another in order to maintain communication. The heterogeneous co-existence of access technologies with largely different characteristics creates a decision problem of determining the "best" available network at "best" time for handoff. In this paper, we implemented the proposed Dynamic and Smart Decision model to decide the "best" network interface and "best" time moment to handoff. The proposed model implementation not only demonstrates the individual user needs but also improve the whole system performance i.e. Quality of Service by reducing the unnecessary handoffs and maintain mobility.

  6. 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

  7. 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.

  8. Decision Support Model for Municipal Solid Waste Management at Department of Defense Installations.

    DTIC Science & Technology

    1995-12-01

    This research focuses on the development of a decision support model to identify the preferred strategy for managing municipal solid waste using the...principles of decision analysis theory. The model provides an effective decision making tool to evaluate and compare different municipal solid waste management

  9. Alternative Approaches to Modeling the Individual Enlistment Decision: A Literature Review. Technical Report 738.

    ERIC Educational Resources Information Center

    Zirk, Deborah A.; And Others

    Findings of previous scientific decision-making literature are reviewed in an effort to specify a model depicting the many facets of the individual military enlistment decision. Theories and/or models reviewed include decision theory, social judgment theory, information integration theory, conjoint measurement/unfolding theory, cognitive decision…

  10. Decision-Making among Emergency Room Residents: Preliminary Observations and a Decision Model.

    ERIC Educational Resources Information Center

    Quick, Jonathan D.; And Others

    1983-01-01

    The social process in clinical decision-making in emergency rooms was studied. Data from interviews and direct observation at two large urban general hospitals with busy emergency rooms staffed by medical and surgical residents are presented. Situations call for individual, consultive, or consensual patterns in making decisions. (Author/MSE)

  11. The Development of a Normative Acquisition Decision Making Model Incorporating Decision Analysis Principles

    DTIC Science & Technology

    1987-09-01

    school of management represented a shift from the workshop orientation of Frederick Taylor to an entire organization perspective ( Hellriegel & Slocum...of information can vitally affect organizational and individual performance" ( Hellriegel and Slocum, 1974: 266). The communication process determines...principles of decision analysis (Matheson & Howard, 1983: 25). To make rational decisions, the following are required ( Hellriegel & Slocum, 1974: 152): 1

  12. Application of Grey Relational Analysis to Decision-Making during Product Development

    ERIC Educational Resources Information Center

    Hsiao, Shih-Wen; Lin, Hsin-Hung; Ko, Ya-Chuan

    2017-01-01

    A multi-attribute decision-making (MADM) approach was proposed in this study as a prediction method that differs from the conventional production and design methods for a product. When a client has different dimensional requirements, this approach can quickly provide a company with design decisions for each product. The production factors of a…

  13. 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.

  14. 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.

  15. Health system re-engineering: a CPRS economic decision model.

    PubMed Central

    Diehl, M.

    1995-01-01

    The fundamental problem with the health care delivery system remains too little health delivered for too great a cost. Information essential to sound clinical and administrative decision making is too frequently missing at the time and place of decision. Automated systems offer opportunities both to improve health and to reduce cost through effective and efficient information management. Information systems are the enabling technology for those business practice changes which improve the benefit-cost profile of a re-engineered delivery system. The Computer-based Patient Record (CPR) is the organizing framework of an enterprise-wide health information system. Since information management is a core function of the health care enterprise, evaluation of the CPR should include its impact on the value of health outcomes and contribution to the organizational mission, rather than solely by benefits which accrue within the delivery system. This paper proposes a model to measure the impact of information technology and specifically a CPR on a re-engineered health care delivery system. PMID:8563375

  16. 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.

  17. Perceptual decision making: drift-diffusion model is equivalent to a Bayesian model

    PubMed Central

    Bitzer, Sebastian; Park, Hame; Blankenburg, Felix; Kiebel, Stefan J.

    2014-01-01

    Behavioral data obtained with perceptual decision making experiments are typically analyzed with the drift-diffusion model. This parsimonious model accumulates noisy pieces of evidence toward a decision bound to explain the accuracy and reaction times of subjects. Recently, Bayesian models have been proposed to explain how the brain extracts information from noisy input as typically presented in perceptual decision making tasks. It has long been known that the drift-diffusion model is tightly linked with such functional Bayesian models but the precise relationship of the two mechanisms was never made explicit. Using a Bayesian model, we derived the equations which relate parameter values between these models. In practice we show that this equivalence is useful when fitting multi-subject data. We further show that the Bayesian model suggests different decision variables which all predict equal responses and discuss how these may be discriminated based on neural correlates of accumulated evidence. In addition, we discuss extensions to the Bayesian model which would be difficult to derive for the drift-diffusion model. We suggest that these and other extensions may be highly useful for deriving new experiments which test novel hypotheses. PMID:24616689

  18. 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

  19. Air quality modeling and decisions for ozone reduction strategies.

    PubMed

    Roth, Philip M; Reynolds, Steven D; Tesche, Thomas W

    2005-10-01

    Despite the widespread application of photochemical air quality models (AQMs) in U.S. state implementation planning (SIP) for attainment of the ambient ozone standard, documentation for the reliability of projections has remained highly subjective. An "idealized" evaluation framework is proposed that provides a means for assessing reliability. Applied to 18 cases of regulatory modeling in the early 1990s in North America, a comparative review of these applications is reported. The intercomparisons suggest that more than two thirds of these AQM applications suffered from having inadequate air quality and meteorological databases. Emissions representations often were unreliable; uncertainties were too high. More than two thirds of the performance evaluation efforts were judged to be substandard compared with idealized goals. Meteorological conditions chosen according regulatory guidelines were limited to one or two cases and tended to be similar, thus limiting the extent to which public policy makers could be confident that the emission controls adopted would yield attainment for a broad range of adverse atmospheric conditions. More than half of the studies reviewed did not give sufficient attention to addressing the potential for compensating errors. Corroborative analyses were conducted in only one of the 18 studies reviewed. Insufficient attention was given to the estimation of model and/or input database errors, uncertainties, or variability in all of the cases examined. However, recent SIP and policy-related regional modeling provides evidence of substantial improvements in the underlying science and available modeling systems used for regulatory decision making. Nevertheless, the availability of suitable databases to support increasingly sophisticated modeling continues to be a concern for many locations. Thus, AQM results may still be subject to significant uncertainties. The evaluative process used here provides a framework for modelers and public policy

  20. Impact of modellers' decisions on hydrological a priori predictions

    NASA Astrophysics Data System (ADS)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2014-06-01

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Modeling integrated water user decisions in intermittent supply systems

    NASA Astrophysics Data System (ADS)

    Rosenberg, David E.; Tarawneh, Tarek; Abdel-Khaleq, Rania; Lund, Jay R.

    2007-07-01

    We apply systems analysis to estimate household water use in an intermittent supply system considering numerous interdependent water user behaviors. Some 39 household actions include conservation; improving local storage or water quality; and accessing sources having variable costs, availabilities, reliabilities, and qualities. A stochastic optimization program with recourse decisions identifies the infrastructure investments and short-term coping actions a customer can adopt to cost-effectively respond to a probability distribution of piped water availability. Monte Carlo simulations show effects for a population of customers. Model calibration reproduces the distribution of billed residential water use in Amman, Jordan. Parametric analyses suggest economic and demand responses to increased availability and alternative pricing. It also suggests potential market penetration for conservation actions, associated water savings, and subsidies to entice further adoption. We discuss new insights to size, target, and finance conservation.

  6. 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.

  7. Impact of modellers' decisions on hydrological a priori predictions

    NASA Astrophysics Data System (ADS)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2013-07-01

    The purpose of this paper is to stimulate a re-thinking of how we, the catchment hydrologists, could become reliable forecasters. A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek) without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1) for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments). They did not obtain time series of stream flow, soil moisture or groundwater response. (2) Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3) For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step 1. Here, we detail the modeller's decisions in accounting for the various processes based on what they learned during the field visit (step 2) and add the final outcome of step 3 when the modellers made use of additional data. We document the prediction progress as well as the learning process resulting from the availability of added information. For the 2nd and 3rd step, the progress in prediction quality could be evaluated in relation to individual modelling experience and costs of added information. We learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing

  8. Decentralized optimization across independent decision makers with incomplete models

    NASA Astrophysics Data System (ADS)

    Inalhan, Gokhan

    Following the advances in electronics and communications technology in the last three decades, a new paradigm for large-scale dynamic systems emerged. In this paradigm, groups of independent dynamic systems, such as unmanned air vehicles or spacecraft, act as a cooperative unit for a diverse set of applications in remote sensing, exploration, and imaging. These systems have been envisioned to provide highly flexible and reconfigurable structures that use individual autonomy to respond to changing environments and operations. The main aim of this research has been to design methods and algorithms to enable efficient operations for such large-scale dynamic systems when a centralized decision-maker cannot or does not exist. Towards this end, a decentralized optimization method and a coordination algorithm have been developed. The decentralized optimization framework exploits a structure inherent in the problem formulation in which each decision maker has a mathematical model that captures the local dynamics and interconnecting constraints. A globally convergent algorithm based on sequential local optimizations is presented. Under the assumptions of differentiability and the linear independence constraint qualification, we show that the method results in global convergence to feasible Nash solutions that satisfy the Kuhn-Tucker necessary conditions for Pareto-optimality. Analysis of the second order sufficiency conditions provide insight to structures and solutions with strong local convexity or weak interconnections which guarantee local Pareto-optimality. This methodology is applied to decentralized coordination problems from the aerospace and the operations research fields. We demonstrate the algorithm numerically via a multiple unmanned air vehicle system, with kinematic aircraft models, coordinating in a common airspace with separation requirements between the aircraft. In addition, analytic solutions are provided for decentralized inventory control in simple

  9. Is there a need for hydrological modelling in decision support systems for nuclear emergencies.

    PubMed

    Raskob, W; Heling, R; Zheleznyak, M

    2004-01-01

    This paper discusses the role of hydrological modelling in decision support systems for nuclear emergencies. In particular, most recent developments such as, the radionuclide transport models integrated in to the decision support system RODOS will be explored. Recent progress in the implementation of physically-based distributed hydrological models for operational forecasting in national and supranational centres, may support a closer cooperation between national hydrological services and therefore, strengthen the use of hydrological and radiological models implemented in decision support systems.

  10. Intelligent Model Management in a Forest Ecosystem Management Decision Support System

    Treesearch

    Donald Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mark Twery; H. Michael Rauscher; Peter Knopp; Scott Thomasma; Mayukh Dass; Hajime Uchiyama

    2002-01-01

    Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard...

  11. 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…

  12. Ensemble modelling and structured decision-making to support Emergency Disease Management.

    PubMed

    Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

    2017-03-01

    Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application.

  13. Fuzzy Naive Bayesian model for medical diagnostic decision support.

    PubMed

    Wagholikar, Kavishwar B; Vijayraghavan, Sundararajan; Deshpande, Ashok W

    2009-01-01

    This work relates to the development of computational algorithms to provide decision support to physicians. The authors propose a Fuzzy Naive Bayesian (FNB) model for medical diagnosis, which extends the Fuzzy Bayesian approach proposed by Okuda. A physician's interview based method is described to define a orthogonal fuzzy symptom information system, required to apply the model. For the purpose of elaboration and elicitation of characteristics, the algorithm is applied to a simple simulated dataset, and compared with conventional Naive Bayes (NB) approach. As a preliminary evaluation of FNB in real world scenario, the comparison is repeated on a real fuzzy dataset of 81 patients diagnosed with infectious diseases. The case study on simulated dataset elucidates that FNB can be optimal over NB for diagnosing patients with imprecise-fuzzy information, on account of the following characteristics - 1) it can model the information that, values of some attributes are semantically closer than values of other attributes, and 2) it offers a mechanism to temper exaggerations in patient information. Although the algorithm requires precise training data, its utility for fuzzy training data is argued for. This is supported by the case study on infectious disease dataset, which indicates optimality of FNB over NB for the infectious disease domain. Further case studies on large datasets are required to establish utility of FNB.

  14. 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

  15. A Reinforcement Learning Model of Precommitment in Decision Making

    PubMed Central

    Kurth-Nelson, Zeb; Redish, A. David

    2010-01-01

    Addiction and many other disorders are linked to impulsivity, where a suboptimal choice is preferred when it is immediately available. One solution to impulsivity is precommitment: constraining one's future to avoid being offered a suboptimal choice. A form of impulsivity can be measured experimentally by offering a choice between a smaller reward delivered sooner and a larger reward delivered later. Impulsive subjects are more likely to select the smaller-sooner choice; however, when offered an option to precommit, even impulsive subjects can precommit to the larger-later choice. To precommit or not is a decision between two conditions: (A) the original choice (smaller-sooner vs. larger-later), and (B) a new condition with only larger-later available. It has been observed that precommitment appears as a consequence of the preference reversal inherent in non-exponential delay-discounting. Here we show that most models of hyperbolic discounting cannot precommit, but a distributed model of hyperbolic discounting does precommit. Using this model, we find (1) faster discounters may be more or less likely than slow discounters to precommit, depending on the precommitment delay, (2) for a constant smaller-sooner vs. larger-later preference, a higher ratio of larger reward to smaller reward increases the probability of precommitment, and (3) precommitment is highly sensitive to the shape of the discount curve. These predictions imply that manipulations that alter the discount curve, such as diet or context, may qualitatively affect precommitment. PMID:21179584

  16. 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…

  17. Fiscal Viability, Conjunctive and Compensatory Models, and Career-Ladder Decisions: An Empirical Investigation.

    ERIC Educational Resources Information Center

    Mehrens, William A.; And Others

    A study was undertaken to explore cost-effective ways of making career ladder teacher evaluation system decisions based on fewer measures, assessing the relationship of observational variables to other data and final decisions, and comparison of compensatory and conjunctive decision models. Data included multiple scores from eight data sources in…

  18. A mixed integer program to model spatial wildfire behavior and suppression placement decisions

    Treesearch

    Erin J. Belval; Yu Wei; Michael. Bevers

    2015-01-01

    Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

  19. 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…

  20. 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…

  1. 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…

  2. 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…

  3. Brain networks for exploration decisions utilizing distinct modeled information types during contextual learning.

    PubMed

    Wang, Jane X; Voss, Joel L

    2014-06-04

    Exploration permits acquisition of the most relevant information during learning. However, the specific information needed, the influences of this information on decision making, and the relevant neural mechanisms remain poorly understood. We modeled distinct information types available during contextual association learning and used model-based fMRI in conjunction with manipulation of exploratory decision making to identify neural activity associated with information-based decisions. We identified hippocampal-prefrontal contributions to advantageous decisions based on immediately available novel information, distinct from striatal contributions to advantageous decisions based on the sum total available (accumulated) information. Furthermore, network-level interactions among these regions during exploratory decision making were related to learning success. These findings link strategic exploration decisions during learning to quantifiable information and advance understanding of adaptive behavior by identifying the distinct and interactive nature of brain-network contributions to decisions based on distinct information types.

  4. 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

  5. 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.

  6. The professional medical ethics model of decision making under conditions of clinical uncertainty.

    PubMed

    McCullough, Laurence B

    2013-02-01

    The professional medical ethics model of decision making may be applied to decisions clinicians and patients make under the conditions of clinical uncertainty that exist when evidence is low or very low. This model uses the ethical concepts of medicine as a profession, the professional virtues of integrity and candor and the patient's virtue of prudence, the moral management of medical uncertainty, and trial of intervention. These features combine to justifiably constrain clinicians' and patients' autonomy with the goal of preventing nondeliberative decisions of patients and clinicians. To prevent biased recommendations by the clinician that promote such nondeliberative decisions, medically reasonable alternatives supported by low or very low evidence should be offered but not recommended. The professional medical ethics model of decision making aims to improve the quality of decisions by reducing the unacceptable variation that can result from nondeliberative decision making by patients and clinicians when evidence is low or very low.

  7. 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.

  8. A novel medical information management and decision model for uncertain demand optimization.

    PubMed

    Bi, Ya

    2015-01-01

    Accurately planning the procurement volume is an effective measure for controlling the medicine inventory cost. Due to uncertain demand it is difficult to make accurate decision on procurement volume. As to the biomedicine sensitive to time and season demand, the uncertain demand fitted by the fuzzy mathematics method is obviously better than general random distribution functions. To establish a novel medical information management and decision model for uncertain demand optimization. A novel optimal management and decision model under uncertain demand has been presented based on fuzzy mathematics and a new comprehensive improved particle swarm algorithm. The optimal management and decision model can effectively reduce the medicine inventory cost. The proposed improved particle swarm optimization is a simple and effective algorithm to improve the Fuzzy interference and hence effectively reduce the calculation complexity of the optimal management and decision model. Therefore the new model can be used for accurate decision on procurement volume under uncertain demand.

  9. 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…

  10. Models and theories of prescribing decisions: A review and suggested a new model

    PubMed Central

    Mohaidin, Zurina

    2017-01-01

    To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the ‘persuasion theory - elaboration likelihood model’, the stimuli–response marketing model’, the ‘agency theory’, the theory of planned behaviour,’ and ‘social power theory,’ in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research. PMID:28690701

  11. Event Prediction for Modeling Mental Simulation in Naturalistic Decision Making

    DTIC Science & Technology

    2005-12-01

    the ingenious decisions made by great generals or admirals, but also to conventional and small-scale decisions as well. One of the differences...popular advanced- control theory. And in other industries as well — power plants, petroleum refineries, food processing, automotive , and aerospace

  12. 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…

  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. 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.

  15. 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.

  16. 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

  17. 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.

  18. A Model for Comparing Game Theory and Artificial Intelligence Decision Making Processes

    DTIC Science & Technology

    1989-12-01

    Matrix 7.5 Summary This chapter discussed an initial comparison of the game theory and artiicial intelligence decision techniques. The measure of...00 DTIC V ELECTE INJ DEC 15 1989 ID A MODEL FOR COMPARING C;.GME THEORY AND ARTIFICIAL INTELLIGENCE DECISION MAKING PROCESSES THESIS ’A Paul R. Andr...lic release: distribution unlii ted A F IT/;SO/ENS,/89D- 1 A MODEL FOR COMPARING GAME THEORY AND ARTIFICIAL INTELLIGENCE DECISION MAKING PROCESSES

  19. 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.

  20. Development of a model to guide decision making in amyotrophic lateral sclerosis multidisciplinary care.

    PubMed

    Hogden, Anne; Greenfield, David; Nugus, Peter; Kiernan, Matthew C

    2015-10-01

    Patients with amyotrophic lateral sclerosis (ALS) face numerous decisions for symptom management and quality of life. Models of decision making in chronic disease and cancer care are insufficient for the complex and changing needs of patients with ALS . The aim was to examine the question: how can decision making that is both effective and patient-centred be enacted in ALS multidisciplinary care? Fifty-four respondents (32 health professionals, 14 patients and eight carers) from two specialized ALS multidisciplinary clinics participated in semi-structured interviews. Interviews were transcribed, coded and analysed thematically. Comparison of stakeholder perspectives revealed six key themes of ALS decision making. These were the decision-making process; patient-centred focus; timing and planning; information sources; engagement with specialized ALS services; and access to non-specialized services. A model, embedded in the specialized ALS multidisciplinary clinic, was derived to guide patient decision making. The model is cyclic, with four stages: 'Participant Engagement'; 'Option Information'; 'Option Deliberation'; and 'Decision Implementation'. Effective and patient-centred decision making is enhanced by the structure of the specialized ALS clinic, which promotes patients' symptom management and quality of life goals. However, patient and carer engagement in ALS decision making is tested by the dynamic nature of ALS, and patient and family distress. Our model optimizes patient-centred decision making, by incorporating patients' cyclic decision-making patterns and facilitating carer inclusion in decision processes. The model captures the complexities of patient-centred decision making in ALS. The framework can assist patients and carers, health professionals, researchers and policymakers in this challenging disease environment. © 2013 John Wiley & Sons Ltd.

  1. 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

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

    PubMed

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

    2014-01-01

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

  3. A Survey of Enterprise Architecture Analysis Using Multi Criteria Decision Making Models (MCDM)

    NASA Astrophysics Data System (ADS)

    Zia, Mehmooda Jabeen; Azam, Farooque; Allauddin, Maria

    System design becomes really important for software production due to continuous increase in size and complexity of software systems. It is a complex design activity to build architecture for the systems like large enterprises. Thus it is a critical issue to select the correct architecture in software engineering domain. Moreover, in enterprise architecture selection different goals and objectives must be taken into consideration as it is a multi-criteria decision making problem. Generally this field of enterprise architecture analysis has progressed from the application of linear weighting, through integer programming and linear programming to multi-criteria decision making (MCDM) models. In this paper we survey two multi-criteria decision making models (AHP, ANP) to determine that to what extent they have been used in making powerful decisions in complex enterprise architecture analysis. We have found that by using ANP model, decision makers of an enterprise can make more precise and suitable decisions in selection of enterprise architecture styles.

  4. Simulation modeling to derive the value-of-information for risky animal disease-import decisions.

    PubMed

    Disney, W Terry; Peters, Mark A

    2003-11-12

    Simulation modeling can be used in aiding decision-makers in deciding when to invest in additional research and when the risky animal disease-import decision should go forward. Simulation modeling to evaluate value-of-information (VOI) techniques provides a robust, objective and transparent framework for assisting decision-makers in making risky animal and animal product decisions. In this analysis, the hypothetical risk from poultry disease in chicken-meat imports was modeled. Economic criteria were used to quantify alternative confidence-increasing decisions regarding potential import testing and additional research requirements. In our hypothetical example, additional information about poultry disease in the exporting country (either by requiring additional export-flock surveillance that results in no sign of disease, or by conducting additional research into lack of disease transmittal through chicken-meat ingestion) captured >75% of the value-of-information attainable regarding the chicken-meat-import decision.

  5. 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

  6. 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

  7. 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.

  8. 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…

  9. 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…

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

    USDA-ARS?s Scientific Manuscript database

    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...

  11. 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…

  12. The role of decision analytic modeling in the health economic assessment of spinal intervention.

    PubMed

    Edwards, Natalie C; Skelly, Andrea C; Ziewacz, John E; Cahill, Kevin; McGirt, Matthew J

    2014-10-15

    Narrative review. To review the common tenets, strengths, and weaknesses of decision modeling for health economic assessment and to review the use of decision modeling in the spine literature to date. For the majority of spinal interventions, well-designed prospective, randomized, pragmatic cost-effectiveness studies that address the specific decision-in-need are lacking. Decision analytic modeling allows for the estimation of cost-effectiveness based on data available to date. Given the rising demands for proven value in spine care, the use of decision analytic modeling is rapidly increasing by clinicians and policy makers. This narrative review discusses the general components of decision analytic models, how decision analytic models are populated and the trade-offs entailed, makes recommendations for how users of spine intervention decision models might go about appraising the models, and presents an overview of published spine economic models. A proper, integrated, clinical, and economic critical appraisal is necessary in the evaluation of the strength of evidence provided by a modeling evaluation. As is the case with clinical research, all options for collecting health economic or value data are not without their limitations and flaws. There is substantial heterogeneity across the 20 spine intervention health economic modeling studies summarized with respect to study design, models used, reporting, and general quality. There is sparse evidence for populating spine intervention models. Results mostly showed that interventions were cost-effective based on $100,000/quality-adjusted life-year threshold. Spine care providers, as partners with their health economic colleagues, have unique clinical expertise and perspectives that are critical to interpret the strengths and weaknesses of health economic models. Health economic models must be critically appraised for both clinical validity and economic quality before altering health care policy, payment strategies, or

  13. A Four-Phase Model of the Evolution of Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    Background A large body of evidence over many years suggests that clinical decision support systems can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. However, to this day, clinical decision support systems are not widely used outside of a small number of sites. One reason why decision support systems are not widely used is the relative difficulty of integrating such systems into clinical workflows and computer systems. Purpose To review and synthesize the history of clinical decision support systems, and to propose a model of various architectures for integrating clinical decision support systems with clinical systems. Methods The authors conducted an extensive review of the clinical decision support literature since 1959, sequenced the systems and developed a model. Results The model developed consists of four phases: standalone decision support systems, decision support integrated into clinical systems, standards for sharing clinical decision support content and service models for decision support. These four phases have not heretofore been identified, but they track remarkably well with the chronological history of clinical decision support, and show evolving and increasingly sophisticated attempts to ease integrating decision support systems into clinical workflows and other clinical systems. Conclusions Each of the four evolutionary approaches to decision support architecture has unique advantages and disadvantages. A key lesson was that there were common limitations that almost all the approaches faced, and no single approach has been able to entirely surmount: 1) fixed knowledge representation systems inherently circumscribe the type of knowledge that can be represented in them, 2) there are serious terminological issues, 3) patient data may be spread across several sources with no single source having a complete view of the patient, and 4) major difficulties exist in transferring successful interventions from one

  14. A multicriteria decision making model for assessment and selection of an ERP in a logistics context

    NASA Astrophysics Data System (ADS)

    Pereira, Teresa; Ferreira, Fernanda A.

    2017-07-01

    The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  16. Decision analytic modeling in spinal surgery: a methodologic overview with review of current published literature.

    PubMed

    McAnany, Steven J; Anwar, Muhammad A F; Qureshi, Sheeraz A

    2015-10-01

    In recent years, there has been an increase in the number of decision analysis studies in the spine literature. Although there are several published reviews on the different types of decision analysis (cost-effectiveness, cost-benefit, cost-utility), there is limited information in the spine literature regarding the mathematical models used in these studies (decision tree, Markov modeling, Monte Carlo simulation). The purpose of this review was to provide an overview of the types of decision analytic models used in spine surgery. A secondary aim was to provide a systematic overview of the most cited studies in the spine literature. This is a systematic review of the available information from all sources regarding decision analytics and economic modeling in spine surgery. A systematic search of PubMed, Embase, and Cochrane review was performed to identify the most relevant peer-reviewed literature of decision analysis/cost-effectiveness analysis (CEA) models including decisions trees, Markov models, and Monte Carlo simulations. Additionally, CEA models based on investigational drug exemption studies were reviewed in particular detail, as these studies are prime candidates for economic modeling. The initial review of the literature resulted in 712 abstracts. After two reviewer-assessment of abstract relevance and methodologic quality, 19 studies were selected: 12 with decision tree constructs and 7 with Markov models. Each study was assessed for methodologic quality and a review of the overall results of the model. A generalized overview of the mathematical construction and methodology of each type of model was also performed. Limitations, strengths, and potential applications to spine research were further explored. Decision analytic modeling represents a powerful tool both in the assessment of competing treatment options and potentially in the formulation of policy and reimbursement. Our review provides a generalized overview and a conceptual framework to help

  17. 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…

  18. Decision making under uncertainty in a spiking neural network model of the basal ganglia.

    PubMed

    Héricé, Charlotte; Khalil, Radwa; Moftah, Marie; Boraud, Thomas; Guthrie, Martin; Garenne, André

    2016-12-01

    The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbic modalities of decision-making. We have used these properties to develop and extend a connectionist model at a spiking neuron level based on a previous rate model approach. This model is demonstrated on decision-making tasks that have been studied in primates and the electrophysiology interpreted to show that the decision is made in two steps. To model this, we have used two parallel loops, each of which performs decision-making based on interactions between positive and negative feedback pathways. This model is able to perform two-level decision-making as in primates. We show here that, before learning, synaptic noise is sufficient to drive the decision-making process and that, after learning, the decision is based on the choice that has proven most likely to be rewarded. The model is then submitted to lesion tests, reversal learning and extinction protocols. We show that, under these conditions, it behaves in a consistent manner and provides predictions in accordance with observed experimental data.

  19. 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.

  20. 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

  1. Improving decision quality in healthcare with an Error Prevention Model (EPM).

    PubMed

    Chio, David T S; Kushniruk, Andre; Borycki, Elizabeth

    2013-01-01

    Human factors involved in decision quality are critical issues in healthcare. In this paper, issues related to the impact of human factors on decision quality in healthcare are considered. Specifically, the focus is on the issue of reducing human error as well as improving decision quality. An Error Prevention Model (EPM) is presented for considering tools and techniques that can be used to analyze complex errors that may be considered latent.

  2. Towards a relational model of decision-making in midwifery care.

    PubMed

    Noseworthy, D Ann; Phibbs, Suzanne R; Benn, Cheryl A

    2013-07-01

    current individualistic ideas of autonomy and decision making do not fit within the context of decision-making in the midwife-woman relationship. This article critically explores current issues around decision-making and proposes a relational decision-making model for midwifery care. qualitative prenatal and postnatal interviews around decision-making within childbirth in general, and the third stage of labour in particular. eight midwife-woman pairs in urban settings in New Zealand. a range of relational, social and political factors that are not present within existing decision-making models were highlighted. The themes included ontological and philosophical influences on decision-making; uncertainty, vulnerability and relational trust; and socio-political and cultural influences. Inconsistencies in knowledge arising from social, cultural and familial considerations as well as identities, beliefs, values, conversations, and practices were found to produce uncertainties around potential courses of action, expected consequences and outcomes. 'Unplanned' birth experiences decreased client autonomy and increased vulnerability thereby intensifying relational trust within decision-making. The political context may also open up or close down possibilities for decision-making at both national and local levels. decision-making for women and midwives is influenced by complex human, contextual and political factors. This study supports a relational model of decision-making that is embedded in understandings of choice as 'entangled'. A relational model enables consideration of how factors such as identity projects, individual practices, the organisation of maternity care, local hospital cultures, medicalised childbirth, workforce shortages, funding cuts and poverty shape the way in which care decisions are made. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. 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.

  4. Effects of modeling decisions on cold region hydrological model performance: snow, soil and streamflow

    NASA Astrophysics Data System (ADS)

    Musselman, Keith; Clark, Martyn; Endalamaw, Abraham; Bolton, W. Robert; Nijssen, Bart; Arnold, Jeffrey

    2017-04-01

    Cold regions are characterized by intense spatial gradients in climate, vegetation and soil properties that determine the complex spatiotemporal patterns of snowpack evolution, frozen soil dynamics, catchment connectivity, and streamflow. These spatial gradients pose unique challenges for hydrological models, including: 1) how the spatial variability of the physical processes are best represented across a hierarchy of scales, and 2) what algorithms and parameter sets best describe the biophysical and hydrological processes at the spatial scale of interest. To address these topics, we apply the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to simulate hydrological processes at the Caribou - Poker Creeks Research Watershed in the Alaskan sub-arctic Boreal forest. The site is characterized by numerous gauged headwater catchments ranging in size from 5 sq. km to 106 sq. km with varying extents (3% to 53%) of discontinuous permafrost that permits a multi-scale paired watershed analysis of the hydrological impacts of frozen soils. We evaluate the effects of model decisions on the skill of SUMMA to simulate observed snow and soil dynamics, and the spatial integration of these processes as catchment streamflow. Decisions such as the number of soil layers, total soil column depth, and vertical soil discretization are shown to have profound impacts on the simulation of seasonal active layer dynamics. Decisions on the spatial organization (lateral connectivity, representation of riparian response units, and the spatial discretization of the hydrological landscape) are shown to be as important as accurate snowpack and soil process representation in the simulation of streamflow. The work serves to better inform hydrological model decisions for cold region hydrologic evaluation and to improve predictive capacity for water resource planning.

  5. 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.

  6. 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

  7. A Threshold Rule Applied to the Retrieval Decision Model

    ERIC Educational Resources Information Center

    Kraft, Donald H.

    1978-01-01

    A threshold rule is analyzed and compared to the Neyman-Pearson procedure, indicating that the threshold rule provides a necessary but not sufficient measure of the minimal performance of a retrieval system, whereas Neyman-Pearson yields a better apriori decision for retrieval. (Author/MBR)

  8. 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…

  9. 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…

  10. Prisoner's Dilemma as a Model for Understanding Decisions.

    ERIC Educational Resources Information Center

    Larsen, Janet D.

    1987-01-01

    Describes two classroom demonstrations, based on the prisoner's dilemma, which illustrate some elements of decision making. Examines how students either cooperate or take advantage of one another, and discusses the use of this activity as an introduction to various concepts in psychology and other social sciences. (GEA)

  11. Decision Making in the School: A Participatory Model.

    ERIC Educational Resources Information Center

    Massialas, Byron G.; Simone, Martha W.

    Described is a project intended to help junior high school students gain understanding and experience in political decision making. The hypothesis is that students will show an increase in political efficacy, interest, trust, and social integration when they become involved in the political functioning of their schools. This hypothesis is in…

  12. 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…

  13. Decision support for sustainable forestry: enhancing the basic rational model.

    Treesearch

    H.R. Ekbia; K.M. Reynolds

    2007-01-01

    Decision-support systems (DSS) have been extensively used in the management of natural resources for nearly two decades. However, practical difficulties with the application of DSS in real-world situations have become increasingly apparent. Complexities of decisionmaking, encountered in the context of ecosystem management, are equally present in sustainable forestry....

  14. 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…

  15. 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…

  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. 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

  18. 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.

  19. A modelling approach to support dynamic decision-making in the control of FMD epidemics.

    PubMed

    Ge, Lan; Mourits, Monique C M; Kristensen, Anders R; Huirne, Ruud B M

    2010-07-01

    Most studies on control strategies for contagious diseases such as foot-and-mouth disease (FMD) evaluate pre-defined control strategies and imply static decision-making during epidemic control. Such a static approach contradicts the dynamic nature of the decision-making process during epidemic control. This paper presents an integrated epidemic-economic modelling approach to support dynamic decision-making in controlling FMD epidemics. This new modelling approach reflects ongoing uncertainty about epidemic growth during epidemic control and provides information required by a dynamic decision process. As demonstrated for a Dutch FMD-case, the modelling approach outperforms static evaluation of pre-fixed control strategies by: (1) providing guidance to decision-making during the entire control process; and (2) generating more realistic estimation of the costs of overreacting or underreacting in choosing control options.

  20. Decision-analytic modeling studies: An overview for clinicians using multiple myeloma as an example.

    PubMed

    Rochau, U; Jahn, B; Qerimi, V; Burger, E A; Kurzthaler, C; Kluibenschaedl, M; Willenbacher, E; Gastl, G; Willenbacher, W; Siebert, U

    2015-05-01

    The purpose of this study was to provide a clinician-friendly overview of decision-analytic models evaluating different treatment strategies for multiple myeloma (MM). We performed a systematic literature search to identify studies evaluating MM treatment strategies using mathematical decision-analytic models. We included studies that were published as full-text articles in English, and assessed relevant clinical endpoints, and summarized methodological characteristics (e.g., modeling approaches, simulation techniques, health outcomes, perspectives). Eleven decision-analytic modeling studies met our inclusion criteria. Five different modeling approaches were adopted: decision-tree modeling, Markov state-transition modeling, discrete event simulation, partitioned-survival analysis and area-under-the-curve modeling. Health outcomes included survival, number-needed-to-treat, life expectancy, and quality-adjusted life years. Evaluated treatment strategies included novel agent-based combination therapies, stem cell transplantation and supportive measures. Overall, our review provides a comprehensive summary of modeling studies assessing treatment of MM and highlights decision-analytic modeling as an important tool for health policy decision making. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  1. 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…

  2. 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…

  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.

    PubMed

    Park, Guihyun; Deshon, Richard P

    2010-09-01

    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 simulated airport security-screening task, we demonstrate that team learning goal orientation influences the confidence of minority opinion holders and team discussion. Team discussion, in turn, relates to minority influence, greater decision quality, and team satisfaction. Implications for managing decision-making teams in organizations are discussed.

  5. 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…

  6. 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…

  7. 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…

  8. Models, Measurements, and Local Decisions: Assessing and Addressing Impacts from Port Expansion and Traffic Activity

    EPA Science Inventory

    This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include ...

  9. Reward optimization in the primate brain: a probabilistic model of decision making under uncertainty.

    PubMed

    Huang, Yanping; Rao, Rajesh P N

    2013-01-01

    A key problem in neuroscience is understanding how the brain makes decisions under uncertainty. Important insights have been gained using tasks such as the random dots motion discrimination task in which the subject makes decisions based on noisy stimuli. A descriptive model known as the drift diffusion model has previously been used to explain psychometric and reaction time data from such tasks but to fully explain the data, one is forced to make ad-hoc assumptions such as a time-dependent collapsing decision boundary. We show that such assumptions are unnecessary when decision making is viewed within the framework of partially observable Markov decision processes (POMDPs). We propose an alternative model for decision making based on POMDPs. We show that the motion discrimination task reduces to the problems of (1) computing beliefs (posterior distributions) over the unknown direction and motion strength from noisy observations in a bayesian manner, and (2) selecting actions based on these beliefs to maximize the expected sum of future rewards. The resulting optimal policy (belief-to-action mapping) is shown to be equivalent to a collapsing decision threshold that governs the switch from evidence accumulation to a discrimination decision. We show that the model accounts for both accuracy and reaction time as a function of stimulus strength as well as different speed-accuracy conditions in the random dots task.

  10. 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…

  11. Models, Measurements, and Local Decisions: Assessing and Addressing Impacts from Port Expansion and Traffic Activity

    EPA Science Inventory

    This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include ...

  12. 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…

  13. 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…

  14. 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…

  15. 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…

  16. 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.

  17. Parental Vaccine Acceptance: A Logistic Regression Model Using Previsit Decisions.

    PubMed

    Lee, Sara; Riley-Behringer, Maureen; Rose, Jeanmarie C; Meropol, Sharon B; Lazebnik, Rina

    2016-10-26

    This study explores how parents' intentions regarding vaccination prior to their children's visit were associated with actual vaccine acceptance. A convenience sample of parents accompanying 6-week-old to 17-year-old children completed a written survey at 2 pediatric practices. Using hierarchical logistic regression, for hospital-based participants (n = 216), vaccine refusal history (P < .01) and vaccine decision made before the visit (P < .05) explained 87% of vaccine refusals. In community-based participants (n = 100), vaccine refusal history (P < .01) explained 81% of refusals. Over 1 in 5 parents changed their minds about vaccination during the visit. Thirty parents who were previous vaccine refusers accepted current vaccines, and 37 who had intended not to vaccinate choose vaccination. Twenty-nine parents without a refusal history declined vaccines, and 32 who did not intend to refuse before the visit declined vaccination. Future research should identify key factors to nudge parent decision making in favor of vaccination.

  18. Advanced Modeling Reconciles Counterintuitive Decisions in Lead Optimization.

    PubMed

    Fernández, Ariel; Scott, L Ridgway

    2017-01-06

    Lead optimization (LO) is essential to fulfill the efficacy and safety requirements of drug-based targeted therapy. The ease with which water may be locally removed from around the target protein crucially influences LO decisions. However, inferred binding sites often defy intuition and the resulting LO decisions are often counterintuitive, with nonpolar groups in the drug placed next to polar groups in the target. We first introduce biophysical advances to reconcile these apparent mismatches. We incorporate three-body energy terms that account for the net stabilization of preformed target structures upon removal of interfacial water concurrent with drug binding. These unexplored drug-induced environmental changes enhancing the target electrostatics are validated against drug-target affinity data, yielding superior computational accuracy required to improve drug design.

  19. The Role of Mental Models in Dynamic Decision-Making

    DTIC Science & Technology

    2009-03-01

    wholesaler, and the factory to brews and supplies beer to distributor. The object of the game is to minimize inventory and avoid backorder while...dynamic decision-making situations. Fu and Gonzalez (2006) used a simplified supply chain system in a microworld platform called The Beer Game. In...this game, a single retailer supplies beer to the consumer, a single wholesaler supplies beer to the retailer, the distributor supplies beer to the

  20. A Model of Reenlistment Decisions of Army National Guardsmen

    DTIC Science & Technology

    1982-10-01

    to enlist employer support appear to be directed at an important problem. Employer attitudes matter when reenlistment decisions are considered. The...previous military experience and circumstances of original enlistment proved important determinaits of reenlistment. Individuals with low draft lottery...noncombat jobs. This difference probably reflects the risk and other characteristics of combat jobs, the nontransferabi•ity of skills, and the poorer futurs

  1. 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.

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

    PubMed

    Conradt, Larissa

    2012-04-06

    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?

  3. 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.

  4. Factors affecting the decision of nursing students in Taiwan to be vaccinated against hepatitis B infection.

    PubMed

    Lin, W C; Ball, C

    1997-04-01

    Compliance with Hepatitis B vaccination for nurses has been reported to be low in Taiwan. Therefore, a study of nursing students' view was conducted in Taiwan to discover possible reasons. As complex decision-making was involved in taking the vaccine, a four-level utility decision model underpinned by the Multi-Attribute Utility theory was proposed to ascertain the relative contribution of the specific components of attitude and beliefs to the final decision and experience of being vaccinated against Hepatitis B infection. Results indicated that the 'personal value of Hepatitis B vaccination', in particular for 'concern about the efficacy of the Hepatitis B vaccine', 'fear of pain from repeated injections', 'time' and 'money', were the main determinants in relation to the uptake of the Hepatitis B vaccination. Such results were consistent with earlier findings based on the Health Belief Model. It appears that the greater the experience gained in nursing care the lower the rate of vaccination; the important items under the concept of 'Personal value of Hepatitis B vaccination' varied by 'experience in nursing care'. The overall predictive validity was 67%, based on the utility decision model. When stratified by 'experience in nursing care', the prediction improved, ranging from 89% to 100%. Based on these findings, a specific intervention programme should be provided to change behaviour and improve the vaccination rate.

  5. A conceptual model of the role of communication in surrogate decision making for hospitalized adults.

    PubMed

    Torke, Alexia M; Petronio, Sandra; Sachs, Greg A; Helft, Paul R; Purnell, Christianna

    2012-04-01

    To build a conceptual model of the role of communication in decision making, based on literature from medicine, communication studies and medical ethics. We proposed a model and described each construct in detail. We review what is known about interpersonal and patient-physician communication, described literature about surrogate-clinician communication, and discussed implications for our developing model. The communication literature proposes two major elements of interpersonal communication: information processing and relationship building. These elements are composed of constructs such as information disclosure and emotional support that are likely to be relevant to decision making. We propose these elements of communication impact decision making, which in turn affects outcomes for both patients and surrogates. Decision making quality may also mediate the relationship between communication and outcomes. Although many elements of the model have been studied in relation to patient-clinician communication, there is limited data about surrogate decision making. There is evidence of high surrogate distress associated with decision making that may be alleviated by communication-focused interventions. More research is needed to test the relationships proposed in the model. Good communication with surrogates may improve both the quality of medical decisions and outcomes for the patient and surrogate. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  6. A Conceptual Model of the Role of Communication in Surrogate Decision Making for Hospitalized Adults

    PubMed Central

    Torke, Alexia M.; Petronio, Sandra; Sachs, Greg A.; Helft, Paul R.; Purnell, Christianna

    2011-01-01

    Objective To build a conceptual model of the role of communication in decision making, based on literature from medicine, communication studies and medical ethics. Methods We propose a model and describe each construct in detail. We review what is known about interpersonal and patient-physician communication, describe literature about surrogate-clinician communication, and discuss implications for our developing model. Results The communication literature proposes two major elements of interpersonal communication: information processing and relationship building. These elements are composed of constructs such as information disclosure and emotional support that are likely to be relevant to decision making. We propose these elements of communication impact decision making, which in turn affects outcomes for both patients and surrogates. Decision making quality may also mediate the relationship between communication and outcomes. Conclusion Although many elements of the model have been studied in relation to patient-clinician communication, there is limited data about surrogate decision making. There is evidence of high surrogate distress associated with decision making that may be alleviated by communication–focused interventions. More research is needed to test the relationships proposed in the model. Practice Implications Good communication with surrogates may improve both the quality of medical decisions and outcomes for the patient and surrogate. PMID:21889865

  7. 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

  8. 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.

  9. Automatically updating predictive modeling workflows support decision-making in drug design.

    PubMed

    Muegge, Ingo; Bentzien, Jörg; Mukherjee, Prasenjit; Hughes, Robert O

    2016-09-01

    Using predictive models for early decision-making in drug discovery has become standard practice. We suggest that model building needs to be automated with minimum input and low technical maintenance requirements. Models perform best when tailored to answering specific compound optimization related questions. If qualitative answers are required, 2-bin classification models are preferred. Integrating predictive modeling results with structural information stimulates better decision making. For in silico models supporting rapid structure-activity relationship cycles the performance deteriorates within weeks. Frequent automated updates of predictive models ensure best predictions. Consensus between multiple modeling approaches increases the prediction confidence. Combining qualified and nonqualified data optimally uses all available information. Dose predictions provide a holistic alternative to multiple individual property predictions for reaching complex decisions.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  11. 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.

  12. Evaluation of Weather Service Heat Indices Using the USARIEM Heat Strain Decision Aid (HSDA) Model

    DTIC Science & Technology

    2003-06-01

    and Canadian indices differ. The U.S. uses the Heat Index (HI) based on Steadman’s model. Canada uses Humidex (HD). Our comparison used the USARIEM Heat Strain Decision Aid (HSDA) to evaluate both indices.

  13. Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges.

    PubMed

    Klabunde, Anna; Willekens, Frans

    We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.

  14. A Diffusion Model Account of Criterion Shifts in the Lexical Decision Task

    PubMed Central

    Wagenmakers, Eric-Jan; Ratcliff, Roger; Gomez, Pablo; McKoon, Gail

    2008-01-01

    Performance in the lexical decision task is highly dependent on decision criteria. These criteria can be influenced by speed versus accuracy instructions and word/nonword proportions. Experiment 1 showed that error responses speed up relative to correct responses under instructions to respond quickly. Experiment 2 showed that that responses to less probable stimuli are slower and less accurate than responses to more probable stimuli. The data from both experiments support the diffusion model for lexical decision (Ratcliff, Gomez, & McKoon, 2004). At the same time, the data provide evidence against the popular deadline model for lexical decision. The deadline model assumes that “nonword” responses are given only after the “word” response has timed out – consequently, the deadline model cannot account for the data from experimental conditions in which “nonword” responses are systematically faster than “word” responses. PMID:19122740

  15. Modeling Confidence Judgments, Response Times, and Multiple Choices in Decision Making: Recognition Memory and Motion Discrimination

    PubMed Central

    Ratcliff, Roger; Starns, Jeffrey J.

    2014-01-01

    Confidence in judgments is a fundamental aspect of decision making, and tasks that collect confidence judgments are an instantiation of multiple-choice decision making. We present a model for confidence judgments in recognition memory tasks that uses a multiple-choice diffusion decision process with separate accumulators of evidence for the different confidence choices. The accumulator that first reaches its decision boundary determines which choice is made. Five algorithms for accumulating evidence were compared, and one of them produced proportions of responses for each of the choices and full response time distributions for each choice that closely matched empirical data. With this algorithm, an increase in the evidence in one accumulator is accompanied by a decrease in the others so that the total amount of evidence in the system is constant. Application of the model to the data from an earlier experiment (Ratcliff, McKoon, & Tindall, 1994) uncovered a relationship between the shapes of z-transformed receiver operating characteristics and the behavior of response time distributions. Both are explained in the model by the behavior of the decision boundaries. For generality, we also applied the decision model to a 3-choice motion discrimination task and found it accounted for data better than a competing class of models. The confidence model presents a coherent account of confidence judgments and response time that cannot be explained with currently popular signal detection theory analyses or dual-process models of recognition. PMID:23915088

  16. Service Level Decision-making in Rural Physiotherapy: Development of Conceptual Models.

    PubMed

    Adams, Robyn; Jones, Anne; Lefmann, Sophie; Sheppard, Lorraine

    2016-06-01

    Understanding decision-making about health service provision is increasingly important in an environment of increasing demand and constrained resources. Multiple factors are likely to influence decisions about which services will be provided, yet workforce is the most noted factor in the rural physiotherapy literature. This paper draws together results obtained from exploration of service level decision-making (SLDM) to propose 'conceptual' models of rural physiotherapy SLDM. A prioritized qualitative approach enabled exploration of participant perspectives about rural physiotherapy decision-making. Stakeholder perspectives were obtained through surveys and in-depth interviews. Interviews were transcribed verbatim and reviewed by participants. Participant confidentiality was maintained by coding both participants and sites. A system theory-case study heuristic provided a framework for exploration across sites within the investigation area: a large area of one Australian state with a mix of regional, rural and remote communities. Thirty-nine surveys were received from participants in 11 communities. Nineteen in-depth interviews were conducted with physiotherapists and key decision-makers. Results reveal the complexity of factors influencing rural physiotherapy service provision and the value of a systems approach when exploring decision-making about rural physiotherapy service provision. Six key features were identified that formed the rural physiotherapy SLDM system: capacity and capability; contextual influences; layered decision-making; access issues; value and beliefs; and tensions and conflict. Rural physiotherapy SLDM is not a one-dimensional process but results from the complex interaction of clusters of systems issues. Decision-making about physiotherapy service provision is influenced by both internal and external factors. Similarities in influencing factors and the iterative nature of decision-making emerged, which enabled linking physiotherapy SLDM with

  17. Sex Differences in a Rat Model of Risky Decision Making

    PubMed Central

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

    2015-01-01

    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

  18. [Contribution of mathematical modeling to vaccination decision making. Examples from varicella, rotavirus and papillomavirus vaccinations].

    PubMed

    Lévy-Bruhl, Daniel

    2010-11-01

    The decision to add a new vaccine to the immunization schedule is a complex and multidisciplinary process based on the risk-benefit balance and, increasingly, on the cost- effectiveness ratio. Such decisions now use mathematical models that can predict the indirect, and potentially detrimental, effects of mass vaccination on the epidemiology of the target disease. The adjunction of an economic component to the modeling process ensures that vaccination represents an efficient allocation of available financial resources in an increasingly constrained environment.

  19. Modeling information flows in clinical decision support: key insights for enhancing system effectiveness.

    PubMed

    Medlock, Stephanie; Wyatt, Jeremy C; Patel, Vimla L; Shortliffe, Edward H; Abu-Hanna, Ameen

    2016-09-01

    A fundamental challenge in the field of clinical decision support is to determine what characteristics of systems make them effective in supporting particular types of clinical decisions. However, we lack such a theory of decision support itself and a model to describe clinical decisions and the systems to support them. This article outlines such a framework. We present a two-stream model of information flow within clinical decision-support systems (CDSSs): reasoning about the patient (the clinical stream), and reasoning about the user (the cognitive-behavioral stream). We propose that CDSS "effectiveness" be measured not only in terms of a system's impact on clinical care, but also in terms of how (and by whom) the system is used, its effect on work processes, and whether it facilitates appropriate decisions by clinicians and patients. Future research into which factors improve the effectiveness of decision support should not regard CDSSs as a single entity, but should instead differentiate systems based on their attributes, users, and the decision being supported. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  20. 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

  1. 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…

  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. 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.

  4. 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

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

    PubMed Central

    Bornstein, Aaron M.; Daw, Nathaniel D.

    2013-01-01

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

  6. 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.

  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. Modeling crisis decision-making for children in state custody.

    PubMed

    He, Xiaoxing Z; Lyons, John S; Heinemann, Allen W

    2004-01-01

    We studied 1492 children in state custody over a 6-month period to investigate the relationship between children's hospital admissions and the crisis workers' clinical assessment. A 27-item standardized decision-support tool [the Childhood Severity of Psychiatric Illness (CSPI)] was used to evaluate the symptoms, risk factors, functioning, comorbidity, and system characteristics. The CSPI has been shown to have a reliability range from 0.70 to 0.80 using intraclass correlations. Logistic regression was used to calculate age-adjusted odds ratios (AOR) of hospitalization, their 95% confidence intervals, and corresponding P values. The results showed that risk factors, symptoms, functioning, comorbidities, and system characteristics were all associated with hospital admissions. Children with a recent suicide attempt, severe danger to others, or history of running away from home/treatment settings were more likely to be hospitalized (respective AOR=12.7, P<.0001; AOR=32.3, P<.0001; AOR=3.0, P=.001). In addition, hospitalization was inversely associated with caregiver knowledge of children (AOR=0.2, P=.01) and multisystem needs (AOR=0.3, P=.04). The decision to hospitalize children psychiatrically appears to be complex. As predicted, risk behaviors and severe symptoms were independent predictors of children's hospital admissions. Interestingly, the capacity of the caregiver and the children's involvement in multiple systems also predict children's hospital admissions.

  9. 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.

  10. A Generalized Quantum-Inspired Decision Making Model for Intelligent Agent

    PubMed Central

    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

  11. Groundwater modelling in decision support: reflections on a unified conceptual framework

    NASA Astrophysics Data System (ADS)

    Doherty, John; Simmons, Craig T.

    2013-11-01

    Groundwater models are commonly used as basis for environmental decision-making. There has been discussion and debate in recent times regarding the issue of model simplicity and complexity. This paper contributes to this ongoing discourse. The selection of an appropriate level of model structural and parameterization complexity is not a simple matter. Although the metrics on which such selection should be based are simple, there are many competing, and often unquantifiable, considerations which must be taken into account as these metrics are applied. A unified conceptual framework is introduced and described which is intended to underpin groundwater modelling in decision support with a direct focus on matters regarding model simplicity and complexity.

  12. 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.

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

    PubMed

    Yılmaz Balaman, Şebnem; Selim, Hasan

    2015-09-01

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

  14. 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.

  15. 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

  16. 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.

  17. A Primer of Social Decision Scheme Theory: Models of Group Influence, Competitive Model-Testing, and Prospective Modeling.

    PubMed

    Stasser

    1999-10-01

    The basic elements of social decision scheme (SDS) theory are individual preferences, group preference compositions (distinguishable distributions), patterns of group influence (decision schemes, social combination rules), and collective responses (group decisions, judgments, solutions, and the like). The theory provides a framework for addressing two fundamental questions in the study of group performance: How are individual resources combined to yield a group response (the individual-into-group problem)? What are the implications of empirical observations under one set of circumstances for other conditions where data do not exist (the sparse data problem)? Several prescriptions for how to conduct fruitful group research are contained in the SDS tradition: make precise theoretical statements, provide strong and competitive tests of theories, and interpret empirical findings in the context of robust process models. Copyright 1999 Academic Press.

  18. 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.

  19. 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

  20. Using participatory agent-based models to measure flood managers' decision thresholds in extreme event response

    NASA Astrophysics Data System (ADS)

    Metzger, A.; Douglass, E.; Gray, S. G.

    2016-12-01

    Extreme flooding impacts to coastal cities are not only a function of storm characteristics, but are heavily influenced by decision-making and preparedness in event-level response. While recent advances in climate and hydrological modeling make it possible to predict the influence of climate change on storm and flooding patterns, flood managers still face a great deal of uncertainty related to adapting organizational responses and decision thresholds to these changing conditions. Some decision thresholds related to mitigation of extreme flood impacts are well-understood and defined by organizational protocol, but others are difficult to quantify due to reliance on contextual expert knowledge, experience, and complexity of information necessary to make certain decisions. Our research attempts to address this issue by demonstrating participatory modeling methods designed to help flood managers (1) better understand and parameterize local decision thresholds in extreme flood management situations, (2) collectively learn about scaling management decision thresholds to future local flooding scenarios and (3) identify effective strategies for adaptating flood mitigation actions and organizational response to climate change-intensified flooding. Our agent-based system dynamic models rely on expert knowledge from local flood managers and sophisticated, climate change-informed hydrological models to simulate current and future flood scenarios. Local flood managers from interact with these models by receiving dynamic information and making management decisions as a flood scenario progresses, allowing parametrization of decision thresholds under different scenarios. Flooding impacts are calculated in each iteration as a means of discussing effectiveness of responses and prioritizing response alternatives. We discuss the findings of this participatory modeling and educational process from a case study of Boston, MA, and discuss transferability of these methods to other types