Sample records for decision models constructing
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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.
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Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning
2018-03-05
This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.
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Optimal allocation model of construction land based on two-level system optimization theory
NASA Astrophysics Data System (ADS)
Liu, Min; Liu, Yanfang; Xia, Yuping; Lei, Qihong
2007-06-01
The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.
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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.
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The Constructive Role of Decisions: Implications from a quantum Approach
2016-12-01
objectives. The first was to explore the nature of constructive influences in decision making . The second concerned understanding decision making in...Prisoner’s Dilemma. **First objective; constructive judgments. This is the idea that sometimes making a decision can alter the underlying relevant mental...the performance of the agent. 15. SUBJECT TERMS EOARD, Quantum Probability, Human Modeling, Human Decision Making 16. SECURITY CLASSIFICATION OF
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From guideline modeling to guideline execution: defining guideline-based decision-support services.
Tu, S. W.; Musen, M. A.
2000-01-01
We describe our task-based approach to defining the guideline-based decision-support services that the EON system provides. We categorize uses of guidelines in patient-specific decision support into a set of generic tasks--making of decisions, specification of work to be performed, interpretation of data, setting of goals, and issuance of alert and reminders--that can be solved using various techniques. Our model includes constructs required for representing the knowledge used by these techniques. These constructs form a toolkit from which developers can select modeling solutions for guideline task. Based on the tasks and the guideline model, we define a guideline-execution architecture and a model of interactions between a decision-support server and clients that invoke services provided by the server. These services use generic interfaces derived from guideline tasks and their associated modeling constructs. We describe two implementations of these decision-support services and discuss how this work can be generalized. We argue that a well-defined specification of guideline-based decision-support services will facilitate sharing of tools that implement computable clinical guidelines. PMID:11080007
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He, Y J; Li, X T; Fan, Z Q; Li, Y L; Cao, K; Sun, Y S; Ouyang, T
2018-01-23
Objective: To construct a dynamic enhanced MR based predictive model for early assessing pathological complete response (pCR) to neoadjuvant therapy in breast cancer, and to evaluate the clinical benefit of the model by using decision curve. Methods: From December 2005 to December 2007, 170 patients with breast cancer treated with neoadjuvant therapy were identified and their MR images before neoadjuvant therapy and at the end of the first cycle of neoadjuvant therapy were collected. Logistic regression model was used to detect independent factors for predicting pCR and construct the predictive model accordingly, then receiver operating characteristic (ROC) curve and decision curve were used to evaluate the predictive model. Results: ΔArea(max) and Δslope(max) were independent predictive factors for pCR, OR =0.942 (95% CI : 0.918-0.967) and 0.961 (95% CI : 0.940-0.987), respectively. The area under ROC curve (AUC) for the constructed model was 0.886 (95% CI : 0.820-0.951). Decision curve showed that in the range of the threshold probability above 0.4, the predictive model presented increased net benefit as the threshold probability increased. Conclusions: The constructed predictive model for pCR is of potential clinical value, with an AUC>0.85. Meanwhile, decision curve analysis indicates the constructed predictive model has net benefit from 3 to 8 percent in the likely range of probability threshold from 80% to 90%.
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Devaluation and sequential decisions: linking goal-directed and model-based behavior
Friedel, Eva; Koch, Stefan P.; Wendt, Jean; Heinz, Andreas; Deserno, Lorenz; Schlagenhauf, Florian
2014-01-01
In experimental psychology different experiments have been developed to assess goal–directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans. PMID:25136310
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NASA Astrophysics Data System (ADS)
Marović, Ivan; Hanak, Tomaš
2017-10-01
In the management of construction projects special attention should be given to the planning as the most important phase of decision-making process. Quality decision-making based on adequate and comprehensive collaboration of all involved stakeholders is crucial in project’s early stages. Fundamental reasons for existence of this problem arise from: specific conditions of construction industry (final products are inseparable from the location i.e. location has a strong influence of building design and its structural characteristics as well as technology which will be used during construction), investors’ desires and attitudes, and influence of socioeconomic and environment aspects. Considering all mentioned reasons one can conclude that selection of adequate construction site location for future investment is complex, low structured and multi-criteria problem. To take into account all the dimensions, the proposed model for selection of adequate site location is devised. The model is based on AHP (for designing the decision-making hierarchy) and PROMETHEE (for pairwise comparison of investment locations) methods. As a result of mixing basis feature of both methods, operational synergies can be achieved in multi-criteria decision analysis. Such gives the decision-maker a sense of assurance, knowing that if the procedure proposed by the presented model has been followed, it will lead to a rational decision, carefully and systematically thought out.
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Deriving the expected utility of a predictive model when the utilities are uncertain.
Cooper, Gregory F; Visweswaran, Shyam
2005-01-01
Predictive models are often constructed from clinical databases with the goal of eventually helping make better clinical decisions. Evaluating models using decision theory is therefore natural. When constructing a model using statistical and machine learning methods, however, we are often uncertain about precisely how the model will be used. Thus, decision-independent measures of classification performance, such as the area under an ROC curve, are popular. As a complementary method of evaluation, we investigate techniques for deriving the expected utility of a model under uncertainty about the model's utilities. We demonstrate an example of the application of this approach to the evaluation of two models that diagnose coronary artery disease.
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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…
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A business planning model to identify new safety net clinic locations.
Langabeer, James; Helton, Jeffrey; DelliFraine, Jami; Dotson, Ebbin; Watts, Carolyn; Love, Karen
2014-01-01
Community health clinics serving the poor and underserved are geographically expanding due to changes in U.S. health care policy. This paper describes the experience of a collaborative alliance of health care providers in a large metropolitan area who develop a conceptual and mathematical decision model to guide decisions on expanding its network of community health clinics. Community stakeholders participated in a collaborative process that defined constructs they deemed important in guiding decisions on the location of community health clinics. This collaboration also defined key variables within each construct. Scores for variables within each construct were then totaled and weighted into a community-specific optimal space planning equation. This analysis relied entirely on secondary data available from published sources. The model built from this collaboration revolved around the constructs of demand, sustainability, and competition. It used publicly available data defining variables within each construct to arrive at an optimal location that maximized demand and sustainability and minimized competition. This is a model that safety net clinic planners and community stakeholders can use to analyze demographic and utilization data to optimize capacity expansion to serve uninsured and Medicaid populations. Communities can use this innovative model to develop a locally relevant clinic location-planning framework.
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ERIC Educational Resources Information Center
Luecht, Richard M.
2003-01-01
This article contends that the necessary links between constructs and test scores/decisions in language assessment must be established through principled design procedures that align three models: (1) a theoretical construct model; (2) a test development model; and (3) a psychometric scoring model. The theoretical construct model articulates the…
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NASA Astrophysics Data System (ADS)
Lee, K. David; Colony, Mike
2011-06-01
Modeling and simulation has been established as a cost-effective means of supporting the development of requirements, exploring doctrinal alternatives, assessing system performance, and performing design trade-off analysis. The Army's constructive simulation for the evaluation of equipment effectiveness in small combat unit operations is currently limited to representation of situation awareness without inclusion of the many uncertainties associated with real world combat environments. The goal of this research is to provide an ability to model situation awareness and decision process uncertainties in order to improve evaluation of the impact of battlefield equipment on ground soldier and small combat unit decision processes. Our Army Probabilistic Inference and Decision Engine (Army-PRIDE) system provides this required uncertainty modeling through the application of two critical techniques that allow Bayesian network technology to be applied to real-time applications. (Object-Oriented Bayesian Network methodology and Object-Oriented Inference technique). In this research, we implement decision process and situation awareness models for a reference scenario using Army-PRIDE and demonstrate its ability to model a variety of uncertainty elements, including: confidence of source, information completeness, and information loss. We also demonstrate that Army-PRIDE improves the realism of the current constructive simulation's decision processes through Monte Carlo simulation.
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A Conceptual Model of the Role of Communication in Surrogate Decision Making for Hospitalized Adults
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
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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.
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Robust Bayesian decision theory applied to optimal dosage.
Abraham, Christophe; Daurès, Jean-Pierre
2004-04-15
We give a model for constructing an utility function u(theta,d) in a dose prescription problem. theta and d denote respectively the patient state of health and the dose. The construction of u is based on the conditional probabilities of several variables. These probabilities are described by logistic models. Obviously, u is only an approximation of the true utility function and that is why we investigate the sensitivity of the final decision with respect to the utility function. We construct a class of utility functions from u and approximate the set of all Bayes actions associated to that class. Then, we measure the sensitivity as the greatest difference between the expected utilities of two Bayes actions. Finally, we apply these results to weighing up a chemotherapy treatment of lung cancer. This application emphasizes the importance of measuring robustness through the utility of decisions rather than the decisions themselves. Copyright 2004 John Wiley & Sons, Ltd.
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Evolutionary fuzzy modeling human diagnostic decisions.
Peña-Reyes, Carlos Andrés
2004-05-01
Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.
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1990-09-01
following two chapters. 28 V. COCOMO MODEL A. OVERVIEW The COCOMO model which stands for COnstructive COst MOdel was developed by Barry Boehm and is...estimation model which uses an expert system to automate the Intermediate COnstructive Cost Estimation MOdel (COCOMO), developed by Barry W. Boehm and...cost estimation model which uses an expert system to automate the Intermediate COnstructive Cost Estimation MOdel (COCOMO), developed by Barry W
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Attention and choice: a review on eye movements in decision making.
Orquin, Jacob L; Mueller Loose, Simone
2013-09-01
This paper reviews studies on eye movements in decision making, and compares their observations to theoretical predictions concerning the role of attention in decision making. Four decision theories are examined: rational models, bounded rationality, evidence accumulation, and parallel constraint satisfaction models. Although most theories were confirmed with regard to certain predictions, none of the theories adequately accounted for the role of attention during decision making. Several observations emerged concerning the drivers and down-stream effects of attention on choice, suggesting that attention processes plays an active role in constructing decisions. So far, decision theories have largely ignored the constructive role of attention by assuming that it is entirely determined by heuristics, or that it consists of stochastic information sampling. The empirical observations reveal that these assumptions are implausible, and that more accurate assumptions could have been made based on prior attention and eye movement research. Future decision making research would benefit from greater integration with attention research. Copyright © 2013 Elsevier B.V. All rights reserved.
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Ristić, Vladica; Maksin, Marija; Nenković-Riznić, Marina; Basarić, Jelena
2018-01-15
The process of making decisions on sustainable development and construction begins in spatial and urban planning when defining the suitability of using land for sustainable construction in a protected area (PA) and its immediate and regional surroundings. The aim of this research is to propose and assess a model for evaluating land-use suitability for sustainable construction in a PA and its surroundings. The methodological approach of Multi-Criteria Decision Analysis was used in the formation of this model and adapted for the research; it was combined with the adapted Analytical hierarchy process and the Delphi process, and supported by a geographical information system (GIS) within the framework of ESRI ArcGIS software - Spatial analyst. The model is applied to the case study of Sara mountain National Park in Kosovo. The result of the model is a "map of integrated assessment of land-use suitability for sustainable construction in a PA for the natural factor". Copyright © 2017 Elsevier Ltd. All rights reserved.
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Delva, Wim; Wilson, David P.; Abu-Raddad, Laith; Gorgens, Marelize; Wilson, David; Hallett, Timothy B.; Welte, Alex
2012-01-01
Public health responses to HIV epidemics have long relied on epidemiological modelling analyses to help prospectively project and retrospectively estimate the impact, cost-effectiveness, affordability, and investment returns of interventions, and to help plan the design of evaluations. But translating model output into policy decisions and implementation on the ground is challenged by the differences in background and expectations of modellers and decision-makers. As part of the PLoS Medicine Collection “Investigating the Impact of Treatment on New HIV Infections”—which focuses on the contribution of modelling to current issues in HIV prevention—we present here principles of “best practice” for the construction, reporting, and interpretation of HIV epidemiological models for public health decision-making on all aspects of HIV. Aimed at both those who conduct modelling research and those who use modelling results, we hope that the principles described here will become a shared resource that facilitates constructive discussions about the policy implications that emerge from HIV epidemiology modelling results, and that promotes joint understanding between modellers and decision-makers about when modelling is useful as a tool in quantifying HIV epidemiological outcomes and improving prevention programming. PMID:22802729
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A Model for Estimating the Reliability and Validity of Criterion-Referenced Measures.
ERIC Educational Resources Information Center
Edmonston, Leon P.; Randall, Robert S.
A decision model designed to determine the reliability and validity of criterion referenced measures (CRMs) is presented. General procedures which pertain to the model are discussed as to: Measures of relationship, Reliability, Validity (content, criterion-oriented, and construct validation), and Item Analysis. The decision model is presented in…
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An Intelligent Decision Support System for Workforce Forecast
2011-01-01
ARIMA ) model to forecast the demand for construction skills in Hong Kong. This model was based...Decision Trees ARIMA Rule Based Forecasting Segmentation Forecasting Regression Analysis Simulation Modeling Input-Output Models LP and NLP Markovian...data • When results are needed as a set of easily interpretable rules 4.1.4 ARIMA Auto-regressive, integrated, moving-average ( ARIMA ) models
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ERIC Educational Resources Information Center
Svetina, Dubravka; Gorin, Joanna S.; Tatsuoka, Kikumi K.
2011-01-01
As a construct definition, the current study develops a cognitive model describing the knowledge, skills, and abilities measured by critical reading test items on a high-stakes assessment used for selection decisions in the United States. Additionally, in order to establish generalizability of the construct meaning to other similarly structured…
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ERIC Educational Resources Information Center
Ho, Esther Sui Chu; Sum, Kwok Wing
2018-01-01
This study aims to construct and validate the Career and Educational Decision Self-Efficacy Inventory for Secondary Students (CEDSIS) by using a sample of 2,631 students in Hong Kong. Principal component analysis yielded a three-factor structure, which demonstrated good model fit in confirmatory factor analysis. High reliability was found for the…
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Accelerated bridge construction (ABC) decision making and economic modeling tool.
DOT National Transportation Integrated Search
2011-12-01
In this FHWA-sponsored pool funded study, a set of decision making tools, based on the Analytic Hierarchy Process (AHP) was developed. This tool set is prepared for transportation specialists and decision-makers to determine if ABC is more effective ...
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Uncertainty quantification and optimal decisions
2017-01-01
A mathematical model can be analysed to construct policies for action that are close to optimal for the model. If the model is accurate, such policies will be close to optimal when implemented in the real world. In this paper, the different aspects of an ideal workflow are reviewed: modelling, forecasting, evaluating forecasts, data assimilation and constructing control policies for decision-making. The example of the oil industry is used to motivate the discussion, and other examples, such as weather forecasting and precision agriculture, are used to argue that the same mathematical ideas apply in different contexts. Particular emphasis is placed on (i) uncertainty quantification in forecasting and (ii) how decisions are optimized and made robust to uncertainty in models and judgements. This necessitates full use of the relevant data and by balancing costs and benefits into the long term may suggest policies quite different from those relevant to the short term. PMID:28484343
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Fischer, Katharina E
2012-08-02
Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare. Empirical approaches that applied PLS-PM to decision-making in healthcare were identified through a systematic literature search. PLS-PM was used as an estimation technique for a structural equation model that specified hypotheses between the components of decision processes and the reasonableness of decision-making in terms of medical, economic and other ethical criteria. The model was estimated for a sample of 55 coverage decisions on the extension of newborn screening programmes in Europe. Results were evaluated by standard reliability and validity measures for PLS-PM. After modification by dropping two indicators that showed poor measures in the measurement models' quality assessment and were not meaningful for newborn screening, the structural equation model estimation produced plausible results. The presence of three influences was supported: the links between both stakeholder participation or transparency and the reasonableness of decision-making; and the effect of transparency on the degree of scientific rigour of assessment. Reliable and valid measurement models were obtained to describe the composites of 'transparency', 'participation', 'scientific rigour' and 'reasonableness'. The structural equation model was among the first applications of PLS-PM to coverage decision-making. It allowed testing of hypotheses in situations where there are links between several non-observable constructs. PLS-PM was compatible in accounting for the complexity of coverage decisions to obtain a more realistic perspective for empirical analysis. The model specification can be used for hypothesis testing by using larger sample sizes and for data in the full domain of health technologies.
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Personalized Modeling for Prediction with Decision-Path Models
Visweswaran, Shyam; Ferreira, Antonio; Ribeiro, Guilherme A.; Oliveira, Alexandre C.; Cooper, Gregory F.
2015-01-01
Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three personalized methods that derive personalized decision-path models. We compared the performance of these methods to that of Classification And Regression Tree (CART) that is a population decision tree to predict seven different outcomes in five medical datasets. Two of the three personalized methods performed statistically significantly better on area under the ROC curve (AUC) and Brier skill score compared to CART. The personalized approach of learning decision path models is a new approach for predictive modeling that can perform better than a population approach. PMID:26098570
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Chen, Hai; Liang, Xiaoying; Li, Rui
2013-01-01
Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.
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Couple Consensus during Marital Joint Decision-Making: A Context, Process, Outcome Model.
ERIC Educational Resources Information Center
Godwin, Deborah D.; Scanzoni, John
1989-01-01
Tested conceptual model of context, processes, and outcomes of joint marital decision making of married couples (N=188) which specified spouses' process variables as individual-level measures and partners' consensus as a couple construct. Found context factor of spouses' emotional interdependence influenced both partners' coerciveness and degree…
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Shi, Huilan; Jia, Junya; Li, Dong; Wei, Li; Shang, Wenya; Zheng, Zhenfeng
2018-02-09
Precise renal histopathological diagnosis will guide therapy strategy in patients with lupus nephritis. Blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI) has been applicable noninvasive technique in renal disease. This current study was performed to explore whether BOLD MRI could contribute to diagnose renal pathological pattern. Adult patients with lupus nephritis renal pathological diagnosis were recruited for this study. Renal biopsy tissues were assessed based on the lupus nephritis ISN/RPS 2003 classification. The Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) was used to obtain functional magnetic resonance parameter, R2* values. Several functions of R2* values were calculated and used to construct algorithmic models for renal pathological patterns. In addition, the algorithmic models were compared as to their diagnostic capability. Both Histopathology and BOLD MRI were used to examine a total of twelve patients. Renal pathological patterns included five classes III (including 3 as class III + V) and seven classes IV (including 4 as class IV + V). Three algorithmic models, including decision tree, line discriminant, and logistic regression, were constructed to distinguish the renal pathological pattern of class III and class IV. The sensitivity of the decision tree model was better than that of the line discriminant model (71.87% vs 59.48%, P < 0.001) and inferior to that of the Logistic regression model (71.87% vs 78.71%, P < 0.001). The specificity of decision tree model was equivalent to that of the line discriminant model (63.87% vs 63.73%, P = 0.939) and higher than that of the logistic regression model (63.87% vs 38.0%, P < 0.001). The Area under the ROC curve (AUROCC) of the decision tree model was greater than that of the line discriminant model (0.765 vs 0.629, P < 0.001) and logistic regression model (0.765 vs 0.662, P < 0.001). BOLD MRI is a useful non-invasive imaging technique for the evaluation of lupus nephritis. Decision tree models constructed using functions of R2* values may facilitate the prediction of renal pathological patterns.
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A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.
Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe
2011-05-30
Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.
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Research on Bidding Decision-making of International Public-Private Partnership Projects
NASA Astrophysics Data System (ADS)
Hu, Zhen Yu; Zhang, Shui Bo; Liu, Xin Yan
2018-06-01
In order to select the optimal quasi-bidding project for an investment enterprise, a bidding decision-making model for international PPP projects was established in this paper. Firstly, the literature frequency statistics method was adopted to screen out the bidding decision-making indexes, and accordingly the bidding decision-making index system for international PPP projects was constructed. Then, the group decision-making characteristic root method, the entropy weight method, and the optimization model based on least square method were used to set the decision-making index weights. The optimal quasi-bidding project was thus determined by calculating the consistent effect measure of each decision-making index value and the comprehensive effect measure of each quasi-bidding project. Finally, the bidding decision-making model for international PPP projects was further illustrated by a hypothetical case. This model can effectively serve as a theoretical foundation and technical support for the bidding decision-making of international PPP projects.
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Analysis of the decision-making process of nurse managers: a collective reflection.
Eduardo, Elizabete Araujo; Peres, Aida Maris; de Almeida, Maria de Lourdes; Roglio, Karina de Dea; Bernardino, Elizabeth
2015-01-01
to analyze the decision-making model adopted by nurses from the perspective of some decision-making process theories. qualitative approach, based on action research. Semi-structured questionnaires and seminars were conducted from April to June 2012 in order to understand the nature of decisions and the decision-making process of nine nurses in position of managers at a public hospital in Southern Brazil. Data were subjected to content analysis. data were classified in two categories: the current situation of decision-making, which showed a lack of systematization; the construction and collective decision-making, which emphasizes the need to develop a decision-making model. the decision-making model used by nurses is limited because it does not consider two important factors: the limits of human rationality, and the external and internal organizational environments that influence and determine right decisions.
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2012-01-01
Background Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare. Methods Empirical approaches that applied PLS-PM to decision-making in healthcare were identified through a systematic literature search. PLS-PM was used as an estimation technique for a structural equation model that specified hypotheses between the components of decision processes and the reasonableness of decision-making in terms of medical, economic and other ethical criteria. The model was estimated for a sample of 55 coverage decisions on the extension of newborn screening programmes in Europe. Results were evaluated by standard reliability and validity measures for PLS-PM. Results After modification by dropping two indicators that showed poor measures in the measurement models’ quality assessment and were not meaningful for newborn screening, the structural equation model estimation produced plausible results. The presence of three influences was supported: the links between both stakeholder participation or transparency and the reasonableness of decision-making; and the effect of transparency on the degree of scientific rigour of assessment. Reliable and valid measurement models were obtained to describe the composites of ‘transparency’, ‘participation’, ‘scientific rigour’ and ‘reasonableness’. Conclusions The structural equation model was among the first applications of PLS-PM to coverage decision-making. It allowed testing of hypotheses in situations where there are links between several non-observable constructs. PLS-PM was compatible in accounting for the complexity of coverage decisions to obtain a more realistic perspective for empirical analysis. The model specification can be used for hypothesis testing by using larger sample sizes and for data in the full domain of health technologies. PMID:22856325
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ERIC Educational Resources Information Center
Su, Chiu Hung; Tzeng, Gwo-Hshiung; Hu, Shu-Kung
2016-01-01
The purpose of this study was to address this problem by applying a new hybrid fuzzy multiple criteria decision-making model including (a) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to construct the fuzzy scope influential network relationship map (FSINRM) and determine the fuzzy influential weights of the…
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USDA-ARS?s Scientific Manuscript database
Decision support systems/models for agriculture are varied in target application and complexity, ranging from simple worksheets to near real-time forecast systems requiring significant computational and manpower resources. Until recently, most such decision support systems have been constructed with...
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Demographics of reintroduced populations: estimation, modeling, and decision analysis
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.
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NASA Astrophysics Data System (ADS)
Utama, D. N.; Triana, Y. S.; Iqbal, M. M.; Iksal, M.; Fikri, I.; Dharmawan, T.
2018-03-01
Mosque, for Muslim, is not only a place for daily worshipping, however as a center of culture as well. It is an important and valuable building to be well managed. For a responsible department or institution (such as Religion or Plan Department in Indonesia), to practically manage a lot of mosques is not simple task to handle. The challenge is in relation to data number and characteristic problems tackled. Specifically for renovating and rehabilitating the damaged mosques, a decision to determine the first damaged mosque priority to be renovated and rehabilitated is problematic. Through two types of optimization method, simulated-annealing and hill-climbing, a decision support model for mosque renovation and rehabilitation was systematically constructed. The method fuzzy-logic was also operated to establish the priority of eleven selected parameters. The constructed model is able to simulate an efficiency comparison between two optimization methods used and suggest the most objective decision coming from 196 generated alternatives.
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Modelling the risk-benefit impact of H1N1 influenza vaccines.
Phillips, Lawrence D; Fasolo, Barbara; Zafiropoulous, Nikolaos; Eichler, Hans-Georg; Ehmann, Falk; Jekerle, Veronika; Kramarz, Piotr; Nicoll, Angus; Lönngren, Thomas
2013-08-01
Shortly after the H1N1 influenza virus reached pandemic status in June 2009, the benefit-risk project team at the European Medicines Agency recognized this presented a research opportunity for testing the usefulness of a decision analysis model in deliberations about approving vaccines soon based on limited data or waiting for more data. Undertaken purely as a research exercise, the model was not connected to the ongoing assessment by the European Medicines Agency, which approved the H1N1 vaccines on 25 September 2009. A decision tree model constructed initially on 1 September 2009, and slightly revised subsequently as new data were obtained, represented an end-of-September or end-of-October approval of vaccines. The model showed combinations of uncertain events, the severity of the disease and the vaccines' efficacy and safety, leading to estimates of numbers of deaths and serious disabilities. The group based their probability assessments on available information and background knowledge about vaccines and similar pandemics in the past. Weighting the numbers by their joint probabilities for all paths through the decision tree gave a weighted average for a September decision of 216 500 deaths and serious disabilities, and for a decision delayed to October of 291 547, showing that an early decision was preferable. The process of constructing the model facilitated communications among the group's members and led to new insights for several participants, while its robustness built confidence in the decision. These findings suggest that models might be helpful to regulators, as they form their preferences during the process of deliberation and debate, and more generally, for public health issues when decision makers face considerable uncertainty.
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NASA Astrophysics Data System (ADS)
Li, Pai; Huang, Yuehui; Jia, Yanbing; Liu, Jichun; Niu, Yi
2018-02-01
Abstract . This article has studies on the generation investment decision in the background of global energy interconnection. Generation investment decision model considering the multiagent benefit is proposed. Under the back-ground of global energy Interconnection, generation investors in different clean energy base not only compete with other investors, but also facing being chosen by the power of the central area, therefor, constructing generation investment decision model considering multiagent benefit can be close to meet the interests demands. Using game theory, the complete information game model is adopted to solve the strategies of different subjects in equilibrium state.
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A communication model of shared decision making: accounting for cancer treatment decisions.
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.
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ERIC Educational Resources Information Center
Davis, Carolyn D.
2013-01-01
This paper describes research in progress concerning the development and use of a newly created tool, the Decision-Making Grid, which was designed to teach undergraduate management students to develop and use metacognitive regulation skills to improve decision-making by requiring students to construct improved decision-making models in a boundedly…
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Alkhatib, Omar J
2017-12-01
The construction industry is typically characterized as a fragmented, multi-organizational setting in which members from different technical backgrounds and moral values join together to develop a particular business or project. The most challenging obstacle in the construction process is to achieve a successful practice and to identify and apply an ethical framework to manage the behavior of involved specialists and contractors and to ensure the quality of all completed construction activities. The framework should reflect a common moral ground for myriad people involved in this process to survive and compete ethically in today's turbulent construction market. This study establishes a framework for moral judgment of behavior and actions conducted in the construction process. The moral framework provides the basis of judging actions as "moral" or "immoral" based on three levels of moral accountability: personal, professional, and social. The social aspect of the proposed framework is developed primarily from the essential attributes of normative business decision-making models identified in the literature review and subsequently incorporates additional attributes related to professional and personal moral values. The normative decision-making models reviewed are based primarily on social attributes as related to moral theories (e.g., utilitarianism, duty, rights, virtue, etc.). The professional and moral attributes are established by identifying a set of common moral values recognized by professionals in the construction industry and required to prevent common construction breaches. The moral framework presented here is the complementary part of the ethical framework developed in Part I of this article and is based primarily on the personal behavior or the moral aspect of professional responsibility. The framework can be implemented as a form of preventive personal ethics, which would help avoid ethical dilemmas and moral implications in the first place. Furthermore, the moral framework can be considered as a decision-making model to guide actions and improve the moral reasoning process, which would help individuals think through possible implications and the consequences of ethical and moral issues in the construction industry.
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SketchBio: a scientist's 3D interface for molecular modeling and animation.
Waldon, Shawn M; Thompson, Peter M; Hahn, Patrick J; Taylor, Russell M
2014-10-30
Because of the difficulties involved in learning and using 3D modeling and rendering software, many scientists hire programmers or animators to create models and animations. This both slows the discovery process and provides opportunities for miscommunication. Working with multiple collaborators, a tool was developed (based on a set of design goals) to enable them to directly construct models and animations. SketchBio is presented, a tool that incorporates state-of-the-art bimanual interaction and drop shadows to enable rapid construction of molecular structures and animations. It includes three novel features: crystal-by-example, pose-mode physics, and spring-based layout that accelerate operations common in the formation of molecular models. Design decisions and their consequences are presented, including cases where iterative design was required to produce effective approaches. The design decisions, novel features, and inclusion of state-of-the-art techniques enabled SketchBio to meet all of its design goals. These features and decisions can be incorporated into existing and new tools to improve their effectiveness.
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An experimental paradigm for team decision processes
NASA Technical Reports Server (NTRS)
Serfaty, D.; Kleinman, D. L.
1986-01-01
The study of distributed information processing and decision making is presently hampered by two factors: (1) The inherent complexity of the mathematical formulation of decentralized problems has prevented the development of models that could be used to predict performance in a distributed environment; and (2) The lack of comprehensive scientific empirical data on human team decision making has hindered the development of significant descriptive models. As a part of a comprehensive effort to find a new framework for multihuman decision making problems, a novel experimental research paradigm was developed involving human terms in decision making tasks. Attempts to construct parts of an integrated model with ideas from queueing networks, team theory, distributed estimation and decentralized resource management are described.
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Virtual Beach version 3 (VB3) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) concentrations at recreational beaches. VB3 is primarily designed for beach managers responsible for making decisions regarding beac...
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Research on Radar Importance with Decision Matrix
NASA Astrophysics Data System (ADS)
Meng, Lingjie; Du, Yu; Wang, Liuheng
2017-12-01
Considering the characteristic of radar, constructed the evaluation index system of radar importance, established the comprehensive evaluation model based on decision matrix. Finally, by means of an example, the methods of this evaluation on radar importance was right and feasibility.
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Collaborative deliberation: a model for patient care.
Elwyn, Glyn; Lloyd, Amy; May, Carl; van der Weijden, Trudy; Stiggelbout, Anne; Edwards, Adrian; Frosch, Dominick L; Rapley, Tim; Barr, Paul; Walsh, Thom; Grande, Stuart W; Montori, Victor; Epstein, Ronald
2014-11-01
Existing theoretical work in decision making and behavior change has focused on how individuals arrive at decisions or form intentions. Less attention has been given to theorizing the requirements that might be necessary for individuals to work collaboratively to address difficult decisions, consider new alternatives, or change behaviors. The goal of this work was to develop, as a forerunner to a middle range theory, a conceptual model that considers the process of supporting patients to consider alternative health care options, in collaboration with clinicians, and others. Theory building among researchers with experience and expertise in clinician-patient communication, using an iterative cycle of discussions. We developed a model composed of five inter-related propositions that serve as a foundation for clinical communication processes that honor the ethical principles of respecting individual agency, autonomy, and an empathic approach to practice. We named the model 'collaborative deliberation.' The propositions describe: (1) constructive interpersonal engagement, (2) recognition of alternative actions, (3) comparative learning, (4) preference construction and elicitation, and (5) preference integration. We believe the model underpins multiple suggested approaches to clinical practice that take the form of patient centered care, motivational interviewing, goal setting, action planning, and shared decision making. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
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Capacity expansion model of wind power generation based on ELCC
NASA Astrophysics Data System (ADS)
Yuan, Bo; Zong, Jin; Wu, Shengyu
2018-02-01
Capacity expansion is an indispensable prerequisite for power system planning and construction. A reasonable, efficient and accurate capacity expansion model (CEM) is crucial to power system planning. In most current CEMs, the capacity of wind power generation is considered as boundary conditions instead of decision variables, which may lead to curtailment or over construction of flexible resource, especially at a high renewable energy penetration scenario. This paper proposed a wind power generation capacity value(CV) calculation method based on effective load-carrying capability, and a CEM that co-optimizes wind power generation and conventional power sources. Wind power generation is considered as decision variable in this model, and the model can accurately reflect the uncertainty nature of wind power.
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Ben-Assuli, Ofir; Leshno, Moshe
2016-09-01
In the last decade, health providers have implemented information systems to improve accuracy in medical diagnosis and decision-making. This article evaluates the impact of an electronic health record on emergency department physicians' diagnosis and admission decisions. A decision analytic approach using a decision tree was constructed to model the admission decision process to assess the added value of medical information retrieved from the electronic health record. Using a Bayesian statistical model, this method was evaluated on two coronary artery disease scenarios. The results show that the cases of coronary artery disease were better diagnosed when the electronic health record was consulted and led to more informed admission decisions. Furthermore, the value of medical information required for a specific admission decision in emergency departments could be quantified. The findings support the notion that physicians and patient healthcare can benefit from implementing electronic health record systems in emergency departments. © The Author(s) 2015.
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ERIC Educational Resources Information Center
Huang, Yu-Chen; Tu, Jui-Che; Hung, So-Jeng
2016-01-01
In response to the global trend of low carbon and the concept of sustainable development, enterprises need to develop R&D for the manufacturing of energy-saving and sustainable products and low carbon products. Therefore, the purpose of this study was to construct a decision model for sustainable product design and development from product…
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Ertefaie, Ashkan; Shortreed, Susan; Chakraborty, Bibhas
2016-06-15
Q-learning is a regression-based approach that uses longitudinal data to construct dynamic treatment regimes, which are sequences of decision rules that use patient information to inform future treatment decisions. An optimal dynamic treatment regime is composed of a sequence of decision rules that indicate how to optimally individualize treatment using the patients' baseline and time-varying characteristics to optimize the final outcome. Constructing optimal dynamic regimes using Q-learning depends heavily on the assumption that regression models at each decision point are correctly specified; yet model checking in the context of Q-learning has been largely overlooked in the current literature. In this article, we show that residual plots obtained from standard Q-learning models may fail to adequately check the quality of the model fit. We present a modified Q-learning procedure that accommodates residual analyses using standard tools. We present simulation studies showing the advantage of the proposed modification over standard Q-learning. We illustrate this new Q-learning approach using data collected from a sequential multiple assignment randomized trial of patients with schizophrenia. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Advanced Decision-Support for Coastal Beach Health: Virtual Beach 3.0
Virtual Beach is a free decision-support system designed to help beach managers and researchers construct, evaluate, and operate site-specific statistical models that can predict levels of fecal indicator bacteria (FIB) based on environmental conditions that are more readily mea...
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Plant, Katherine L; Stanton, Neville A
2015-01-01
The perceptual cycle model (PCM) has been widely applied in ergonomics research in domains including road, rail and aviation. The PCM assumes that information processing occurs in a cyclical manner drawing on top-down and bottom-up influences to produce perceptual exploration and actions. However, the validity of the model has not been addressed. This paper explores the construct validity of the PCM in the context of aeronautical decision-making. The critical decision method was used to interview 20 helicopter pilots about critical decision-making. The data were qualitatively analysed using an established coding scheme, and composite PCMs for incident phases were constructed. It was found that the PCM provided a mutually exclusive and exhaustive classification of the information-processing cycles for dealing with critical incidents. However, a counter-cycle was also discovered which has been attributed to skill-based behaviour, characteristic of experts. The practical applications and future research questions are discussed. Practitioner Summary: This paper explores whether information processing, when dealing with critical incidents, occurs in the manner anticipated by the perceptual cycle model. In addition to the traditional processing cycle, a reciprocal counter-cycle was found. This research can be utilised by those who use the model as an accident analysis framework.
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The application of a decision tree to establish the parameters associated with hypertension.
Tayefi, Maryam; Esmaeili, Habibollah; Saberi Karimian, Maryam; Amirabadi Zadeh, Alireza; Ebrahimi, Mahmoud; Safarian, Mohammad; Nematy, Mohsen; Parizadeh, Seyed Mohammad Reza; Ferns, Gordon A; Ghayour-Mobarhan, Majid
2017-02-01
Hypertension is an important risk factor for cardiovascular disease (CVD). The goal of this study was to establish the factors associated with hypertension by using a decision-tree algorithm as a supervised classification method of data mining. Data from a cross-sectional study were used in this study. A total of 9078 subjects who met the inclusion criteria were recruited. 70% of these subjects (6358 cases) were randomly allocated to the training dataset for the constructing of the decision-tree. The remaining 30% (2720 cases) were used as the testing dataset to evaluate the performance of decision-tree. Two models were evaluated in this study. In model I, age, gender, body mass index, marital status, level of education, occupation status, depression and anxiety status, physical activity level, smoking status, LDL, TG, TC, FBG, uric acid and hs-CRP were considered as input variables and in model II, age, gender, WBC, RBC, HGB, HCT MCV, MCH, PLT, RDW and PDW were considered as input variables. The validation of the model was assessed by constructing a receiver operating characteristic (ROC) curve. The prevalence rates of hypertension were 32% in our population. For the decision-tree model I, the accuracy, sensitivity, specificity and area under the ROC curve (AUC) value for identifying the related risk factors of hypertension were 73%, 63%, 77% and 0.72, respectively. The corresponding values for model II were 70%, 61%, 74% and 0.68, respectively. We have developed a decision tree model to identify the risk factors associated with hypertension that maybe used to develop programs for hypertension management. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Predicting species distributions for conservation decisions
Guisan, Antoine; Tingley, Reid; Baumgartner, John B; Naujokaitis-Lewis, Ilona; Sutcliffe, Patricia R; Tulloch, Ayesha I T; Regan, Tracey J; Brotons, Lluis; McDonald-Madden, Eve; Mantyka-Pringle, Chrystal; Martin, Tara G; Rhodes, Jonathan R; Maggini, Ramona; Setterfield, Samantha A; Elith, Jane; Schwartz, Mark W; Wintle, Brendan A; Broennimann, Olivier; Austin, Mike; Ferrier, Simon; Kearney, Michael R; Possingham, Hugh P; Buckley, Yvonne M
2013-01-01
Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. PMID:24134332
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Stephens, Peggy C; Sloboda, Zili; Stephens, Richard C; Teasdale, Brent; Grey, Scott F; Hawthorne, Richard D; Williams, Joseph
2009-06-01
We examined the relationships among targeted constructs of social influences and competence enhancement prevention curricula and cigarette, alcohol and marijuana use outcomes in a diverse sample of high school students. We tested the causal relationships of normative beliefs, perceptions of harm, attitudes toward use of these substances and refusal, communication, and decision-making skills predicting the self-reported use of each substance. In addition, we modeled the meditation of these constructs through the intentions to use each substance and tested the moderating effects of the skills variables on the relationships between intentions to use and self-reported use of each of these substances. Logistic regression path models were constructed for each of the drug use outcomes. Models were run using the Mplus 5.0 statistical application using the complex sample function to control for the sampling design of students nested within schools; full information maximum likelihood estimates (FIML) were utilized to address missing data. Relationships among targeted constructs and outcomes differed for each of the drugs with communication skills having a potentially iatrogenic effect on alcohol use. Program targets were mediated through the intentions to use these substances. Finally, we found evidence of a moderating effect of decision-making skills on perceptions of harm and attitudes toward use, depending upon the outcome. Prevention curricula may need to target specific drugs. In addition to normative beliefs, perceptions of harm, and refusal and decision-making skills, programs should directly target constructs proximal to behavioral outcomes such as attitudes and intentions. Finally, more research on the effects of communication skills on adolescent substance use should be examined.
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Virtual Beach (VB) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) at recreational beaches. Although primarily designed for making decisions regarding beach closures or issuance of swimming advisories based on...
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Virtual Beach (VB) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) at locations of exposure. Although primarily designed for making decisions regarding beach closures or issuance of swimming advisories based on...
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Technological innovations in the development of cardiovascular clinical information systems.
Hsieh, Nan-Chen; Chang, Chung-Yi; Lee, Kuo-Chen; Chen, Jeen-Chen; Chan, Chien-Hui
2012-04-01
Recent studies have shown that computerized clinical case management and decision support systems can be used to assist surgeons in the diagnosis of disease, optimize surgical operation, aid in drug therapy and decrease the cost of medical treatment. Therefore, medical informatics has become an extensive field of research and many of these approaches have demonstrated potential value for improving medical quality. The aim of this study was to develop a web-based cardiovascular clinical information system (CIS) based on innovative techniques, such as electronic medical records, electronic registries and automatic feature surveillance schemes, to provide effective tools and support for clinical care, decision-making, biomedical research and training activities. The CIS developed for this study contained monitoring, surveillance and model construction functions. The monitoring layer function provided a visual user interface. At the surveillance and model construction layers, we explored the application of model construction and intelligent prognosis to aid in making preoperative and postoperative predictions. With the use of the CIS, surgeons can provide reasonable conclusions and explanations in uncertain environments.
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Rowlinson, Steve; Jia, Yunyan Andrea
2014-04-01
Existing heat stress risk management guidelines recommended by international standards are not practical for the construction industry which needs site supervision staff to make instant managerial decisions to mitigate heat risks. The ability of the predicted heat strain (PHS) model [ISO 7933 (2004). Ergonomics of the thermal environment analytical determination and interpretation of heat stress using calculation of the predicted heat strain. Geneva: International Standard Organisation] to predict maximum allowable exposure time (D lim) has now enabled development of localized, action-triggering and threshold-based guidelines for implementation by lay frontline staff on construction sites. This article presents a protocol for development of two heat stress management tools by applying the PHS model to its full potential. One of the tools is developed to facilitate managerial decisions on an optimized work-rest regimen for paced work. The other tool is developed to enable workers' self-regulation during self-paced work.
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Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs
NASA Astrophysics Data System (ADS)
Mohleji, Nandita
Convective weather and other constraints create uncertainty in air transportation, leading to costly delays. A Ground Delay Program (GDP) is a strategy to mitigate these effects. Systematic decision support can increase GDP efficacy, reduce delays, and minimize direct operating costs. In this study, a decision analysis (DA) model is constructed by combining a decision tree and Bayesian belief network. Through a study of three New York region airports, the DA model demonstrates that larger GDP scopes that include more flights in the program, along with longer lead times that provide stakeholders greater notice of a pending program, trigger the fewest average arrival delays. These findings are demonstrated to result in a savings of up to $1,850 per flight. Furthermore, when convective weather is predicted, forecast weather confidences remain the same level or greater at least 70% of the time, supporting more strategic decision making. The DA model thus enables quantification of uncertainties and insights on causal relationships, providing support for future GDP decisions.
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Gutnik, Lily A; Hakimzada, A Forogh; Yoskowitz, Nicole A; Patel, Vimla L
2006-12-01
Models of decision-making usually focus on cognitive, situational, and socio-cultural variables in accounting for human performance. However, the emotional component is rarely addressed within these models. This paper reviews evidence for the emotional aspect of decision-making and its role within a new framework of investigation, called neuroeconomics. The new approach aims to build a comprehensive theory of decision-making, through the unification of theories and methods from economics, psychology, and neuroscience. In this paper, we review these integrative research methods and their applications to issues of public health, with illustrative examples from our research on young adults' safe sex practices. This approach promises to be valuable as a comprehensively descriptive and possibly, better predictive model for construction and customization of decision support tools for health professionals and consumers.
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Hu, Wenfa; He, Xinhua
2014-01-01
The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated.
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Rennke, Stephanie; Yuan, Patrick; Monash, Brad; Blankenburg, Rebecca; Chua, Ian; Harman, Stephanie; Sakai, Debbie S; Khan, Adeena; Hilton, Joan F; Shieh, Lisa; Satterfield, Jason
2017-12-01
Patient engagement through shared decision-making (SDM) is increasingly seen as a key component for patient safety, patient satisfaction, and quality of care. Current SDM models do not adequately account for medical and environmental contexts, which may influence medical decisions in the hospital. We identified leading SDM models and reviews to inductively construct a novel SDM model appropriate for the inpatient setting. A team of medicine and pediatric hospitalists reviewed the literature to integrate core SDM concepts and processes and iteratively constructed a synthesized draft model. We then solicited broad SDM expert feedback on the draft model for validation and further refinement. The SDM 3 Circle Model identifies 3 core categories of variables that dynamically interact within an "environmental frame." The resulting Venn diagram includes overlapping circles for (1) patient/family, (2) provider/team, and (3) medical context. The environmental frame includes all external, contextual factors that may influence any of the 3 circles. Existing multistep SDM process models were then rearticulated and contextualized to illustrate how a shared decision might be made. The SDM 3 Circle Model accounts for important environmental and contextual characteristics that vary across settings. The visual emphasis generated by each "circle" and by the environmental frame direct attention to often overlooked interactive forces and has the potential to more precisely define, promote, and improve SDM. This model provides a framework to develop interventions to improve quality and patient safety through SDM and patient engagement for hospitalists. © 2017 Society of Hospital Medicine.
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DOT National Transportation Integrated Search
2007-05-01
This paper evaluates impact of various I-15 reconstruction closure scenarios on the travelers in Ogden area. The purpose of the research was to investigate impact of the scenarios and facilitate decision about future maintenance of traffic during the...
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ERIC Educational Resources Information Center
Stewart, Neil; Chater, Nick; Brown, Gordon D. A.
2006-01-01
We present a theory of decision by sampling (DbS) in which, in contrast with traditional models, there are no underlying psychoeconomic scales. Instead, we assume that an attribute's subjective value is constructed from a series of binary, ordinal comparisons to a sample of attribute values drawn from memory and is its rank within the sample. We…
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Establishing the effectiveness of patient decision aids: key constructs and measurement instruments
2013-01-01
Background Establishing the effectiveness of patient decision aids (PtDA) requires evidence that PtDAs improve the quality of the decision-making process and the quality of the choice made, or decision quality. The aim of this paper is to review the theoretical and empirical evidence for PtDA effectiveness and discuss emerging practical and research issues in the measurement of effectiveness. Methods This updated overview incorporates: a) an examination of the instruments used to measure five key decision-making process constructs (i.e., recognize decision, feel informed about options and outcomes, feel clear about goals and preferences, discuss goals and preferences with health care provider, and be involved in decisions) and decision quality constructs (i.e., knowledge, realistic expectations, values-choice agreement) within the 86 trials in the Cochrane review; and b) a summary of the 2011 Cochrane Collaboration’s review of PtDAs for these key constructs. Data on the constructs and instruments used were extracted independently by two authors from the 86 trials and any disagreements were resolved by discussion, with adjudication by a third party where required. Results The 86 studies provide considerable evidence that PtDAs improve the decision-making process and decision quality. A majority of the studies (76/86; 88%) measured at least one of the key decision-making process or decision quality constructs. Seventeen different measurement instruments were used to measure decision-making process constructs, but no single instrument covered all five constructs. The Decisional Conflict Scale was most commonly used (n = 47), followed by the Control Preference Scale (n = 9). Many studies reported one or more constructs of decision quality, including knowledge (n = 59), realistic expectation of risks and benefits (n = 21), and values-choice agreement (n = 13). There was considerable variability in how values-choice agreement was defined and determined. No study reported on all key decision-making process and decision quality constructs. Conclusions Evidence of PtDA effectiveness in improving the quality of the decision-making process and decision quality is strong and growing. There is not, however, consensus or standardization of measurement for either the decision-making process or decision quality. Additional work is needed to develop and evaluate measurement instruments and further explore theoretical issues to advance future research on PtDA effectiveness. PMID:24625035
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Establishing the effectiveness of patient decision aids: key constructs and measurement instruments.
Sepucha, Karen R; Borkhoff, Cornelia M; Lally, Joanne; Levin, Carrie A; Matlock, Daniel D; Ng, Chirk Jenn; Ropka, Mary E; Stacey, Dawn; Joseph-Williams, Natalie; Wills, Celia E; Thomson, Richard
2013-01-01
Establishing the effectiveness of patient decision aids (PtDA) requires evidence that PtDAs improve the quality of the decision-making process and the quality of the choice made, or decision quality. The aim of this paper is to review the theoretical and empirical evidence for PtDA effectiveness and discuss emerging practical and research issues in the measurement of effectiveness. This updated overview incorporates: a) an examination of the instruments used to measure five key decision-making process constructs (i.e., recognize decision, feel informed about options and outcomes, feel clear about goals and preferences, discuss goals and preferences with health care provider, and be involved in decisions) and decision quality constructs (i.e., knowledge, realistic expectations, values-choice agreement) within the 86 trials in the Cochrane review; and b) a summary of the 2011 Cochrane Collaboration's review of PtDAs for these key constructs. Data on the constructs and instruments used were extracted independently by two authors from the 86 trials and any disagreements were resolved by discussion, with adjudication by a third party where required. The 86 studies provide considerable evidence that PtDAs improve the decision-making process and decision quality. A majority of the studies (76/86; 88%) measured at least one of the key decision-making process or decision quality constructs. Seventeen different measurement instruments were used to measure decision-making process constructs, but no single instrument covered all five constructs. The Decisional Conflict Scale was most commonly used (n = 47), followed by the Control Preference Scale (n = 9). Many studies reported one or more constructs of decision quality, including knowledge (n = 59), realistic expectation of risks and benefits (n = 21), and values-choice agreement (n = 13). There was considerable variability in how values-choice agreement was defined and determined. No study reported on all key decision-making process and decision quality constructs. Evidence of PtDA effectiveness in improving the quality of the decision-making process and decision quality is strong and growing. There is not, however, consensus or standardization of measurement for either the decision-making process or decision quality. Additional work is needed to develop and evaluate measurement instruments and further explore theoretical issues to advance future research on PtDA effectiveness.
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Simulation-Based Prediction of Equivalent Continuous Noises during Construction Processes
Zhang, Hong; Pei, Yun
2016-01-01
Quantitative prediction of construction noise is crucial to evaluate construction plans to help make decisions to address noise levels. Considering limitations of existing methods for measuring or predicting the construction noise and particularly the equivalent continuous noise level over a period of time, this paper presents a discrete-event simulation method for predicting the construction noise in terms of equivalent continuous level. The noise-calculating models regarding synchronization, propagation and equivalent continuous level are presented. The simulation framework for modeling the noise-affected factors and calculating the equivalent continuous noise by incorporating the noise-calculating models into simulation strategy is proposed. An application study is presented to demonstrate and justify the proposed simulation method in predicting the equivalent continuous noise during construction. The study contributes to provision of a simulation methodology to quantitatively predict the equivalent continuous noise of construction by considering the relevant uncertainties, dynamics and interactions. PMID:27529266
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Simulation-Based Prediction of Equivalent Continuous Noises during Construction Processes.
Zhang, Hong; Pei, Yun
2016-08-12
Quantitative prediction of construction noise is crucial to evaluate construction plans to help make decisions to address noise levels. Considering limitations of existing methods for measuring or predicting the construction noise and particularly the equivalent continuous noise level over a period of time, this paper presents a discrete-event simulation method for predicting the construction noise in terms of equivalent continuous level. The noise-calculating models regarding synchronization, propagation and equivalent continuous level are presented. The simulation framework for modeling the noise-affected factors and calculating the equivalent continuous noise by incorporating the noise-calculating models into simulation strategy is proposed. An application study is presented to demonstrate and justify the proposed simulation method in predicting the equivalent continuous noise during construction. The study contributes to provision of a simulation methodology to quantitatively predict the equivalent continuous noise of construction by considering the relevant uncertainties, dynamics and interactions.
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Using Trust to Establish a Secure Routing Model in Cognitive Radio Network.
Zhang, Guanghua; Chen, Zhenguo; Tian, Liqin; Zhang, Dongwen
2015-01-01
Specific to the selective forwarding attack on routing in cognitive radio network, this paper proposes a trust-based secure routing model. Through monitoring nodes' forwarding behaviors, trusts of nodes are constructed to identify malicious nodes. In consideration of that routing selection-based model must be closely collaborative with spectrum allocation, a route request piggybacking available spectrum opportunities is sent to non-malicious nodes. In the routing decision phase, nodes' trusts are used to construct available path trusts and delay measurement is combined for making routing decisions. At the same time, according to the trust classification, different responses are made specific to their service requests. By adopting stricter punishment on malicious behaviors from non-trusted nodes, the cooperation of nodes in routing can be stimulated. Simulation results and analysis indicate that this model has good performance in network throughput and end-to-end delay under the selective forwarding attack.
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Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems
NASA Astrophysics Data System (ADS)
Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen
Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.
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Aligning ERP systems with companies' real needs: an `Operational Model Based' method
NASA Astrophysics Data System (ADS)
Mamoghli, Sarra; Goepp, Virginie; Botta-Genoulaz, Valérie
2017-02-01
Enterprise Resource Planning (ERP) systems offer standard functionalities that have to be configured and customised by a specific company depending on its own requirements. A consistent alignment is therefore an essential success factor of ERP projects. To manage this alignment, an 'Operational Model Based' method is proposed. It is based on the design and the matching of models, and conforms to the modelling views and constructs of the ISO 19439 and 19440 enterprise-modelling standards. It is characterised by: (1) a predefined design and matching order of the models; (2) the formalisation, in terms of modelling constructs, of alignment and misalignment situations; and (3) their association with a set of decisions in order to mitigate the misalignment risk. Thus, a comprehensive understanding of the alignment management during ERP projects is given. Unlike existing methods, this one includes decisions related to the organisational changes an ERP system can induce, as well as criteria on which the best decision can be based. In this way, it provides effective support and guidance to companies implementing ERP systems, as the alignment process is detailed and structured. The method is applied on the ERP project of a Small and Medium Enterprise, showing that it can be used even in contexts where the ERP project expertise level is low.
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2016-09-01
Military Construction Decisions Report to Congressional Requesters September 2016 GAO-16-853 United States Government Accountability Office...ANALYSIS COMPLEX DOD Partially Used Best Practices for Analyzing Alternatives and Should Do So Fully for Future Military Construction Decisions What...a set of AOA best practices for military construction decisions. Without guidance for using AOA best practices during certain military construction
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High-rise construction in the Russian economy: modeling of management decisions
NASA Astrophysics Data System (ADS)
Miroshnikova, Tatyana; Taskaeva, Natalia
2018-03-01
The growth in the building industry, particularly in residential high-rise construction, is having considerable influence on the country's economic development. The scientific hypothesis of the research is that the execution of town-planning programs of high-rise construction depends to a large extent on the management of the provision of material resources for the construction of a millionth city, while the balance model is the most important tool for establishing and determining the ratio between supply and demand for material resources. In order to improve the efficiency of high-rise building management, it is proposed to develop a methodology for managing the provision of construction of large cities with material resources.
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Vastamäki, Heidi; Vastamäki, Martti; Laimi, Katri; Saltychev, Michail
2017-07-01
Poorly functioning work environments may lead to dissatisfaction for the employees and financial loss for the employers. The Job Content Questionnaire (JCQ) was designed to measure social and psychological characteristics of work environments. To investigate the factor construct of the Finnish 14-item version of JCQ when applied to professional orchestra musicians. In a cross-sectional survey, the questionnaire was sent by mail to 1550 orchestra musicians and students. 630 responses were received. Full data were available for 590 respondents (response rate 38%).The questionnaire also contained questions on demographics, job satisfaction, health status, health behaviors, and intensity of playing music. Confirmatory factor analysis of the 2-factor model of JCQ was conducted. Of the 5 estimates, JCQ items in the "job demand" construct, the "conflicting demands" (question 5) explained most of the total variance in this construct (79%) demonstrating almost perfect correlation of 0.63. In the construct of "job control," "opinions influential" (question 10) demonstrated a perfect correlation index of 0.84 and the items "little decision freedom" (question 14) and "allows own decisions" (question 6) showed substantial correlations of 0.77 and 0.65. The 2-factor model of the Finnish 14-item version of JCQ proposed in this study fitted well into the observed data. The "conflicting demands," "opinions influential," "little decision freedom," and "allows own decisions" items demonstrated the strongest correlations with latent factors suggesting that in a population similar to the studied one, especially these items should be taken into account when observed in the response of a population.
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Sensitivity Analysis in Sequential Decision Models.
Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet
2017-02-01
Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.
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Hamilton, Kyra; Spinks, Teagan; White, Katherine M; Kavanagh, David J; Walsh, Anne M
2016-05-01
Preschool-aged children spend substantial amounts of time engaged in screen-based activities. As parents have considerable control over their child's health behaviours during the younger years, it is important to understand those influences that guide parents' decisions about their child's screen time behaviours. A prospective design with two waves of data collection, 1 week apart, was adopted. Parents (n = 207) completed a Theory of Planned Behaviour (TPB)-based questionnaire, with the addition of parental role construction (i.e., parents' expectations and beliefs of responsibility for their child's behaviour) and past behaviour. A number of underlying beliefs identified in a prior pilot study were also assessed. The model explained 77% (with past behaviour accounting for 5%) of the variance in intention and 50% (with past behaviour accounting for 3%) of the variance in parental decisions to limit child screen time. Attitude, subjective norms, perceived behavioural control, parental role construction, and past behaviour predicted intentions, and intentions and past behaviour predicted follow-up behaviour. Underlying screen time beliefs (e.g., increased parental distress, pressure from friends, inconvenience) were also identified as guiding parents' decisions. Results support the TPB and highlight the importance of beliefs for understanding parental decisions for children's screen time behaviours, as well as the addition of parental role construction. This formative research provides necessary depth of understanding of sedentary lifestyle behaviours in young children which can be adopted in future interventions to test the efficacy of the TPB mechanisms in changing parental behaviour for their child's health. What is already known on this subject? Identifying determinants of child screen time behaviour is vital to the health of young people. Social-cognitive and parental role constructions are key influences of parental decision-making. Little is known about the processes guiding parents' decisions to limit their child's screen time. What does this study add? Parental role construction and TPB social-cognitive factors influence parental decisions. The beliefs of parents for their child's behaviour were identified. A range of beliefs guide parents' decisions for their child's screen time viewing. © 2015 The British Psychological Society.
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Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J
2015-03-15
This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Seismic slope-performance analysis: from hazard map to decision support system
Miles, Scott B.; Keefer, David K.; Ho, Carlton L.
1999-01-01
In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.
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A Model Framework for Course Materials Construction (Second Edition).
ERIC Educational Resources Information Center
Schlenker, Richard M.
Designed for use by Coast Guard course writers, curriculum developers, course coordinators, and instructors as a decision-support system, this publication presents a model that translates the Intraservices Procedures for Instructional Systems Development curriculum design model into materials usable by classroom teachers and students. Although…
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Introduction: Occam’s Razor (SOT - Fit for Purpose workshop introduction)
Mathematical models provide important, reproducible, and transparent information for risk-based decision making. However, these models must be constructed to fit the needs of the problem to be solved. A “fit for purpose” model is an abstraction of a complicated problem that allow...
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ERIC Educational Resources Information Center
Keaten, James A.
This paper offers a model that integrates chaos theory and cybernetics, which can be used to describe the structure of decision making within small groups. The paper begins with an overview of cybernetics and chaos. Definitional characteristics of cybernetics are reviewed along with salient constructs, such as goal-seeking, feedback, feedback…
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2014-01-01
The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated. PMID:24672351
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Identifying pollution sources and predicting urban air quality using ensemble learning methods
NASA Astrophysics Data System (ADS)
Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali
2013-12-01
In this study, principal components analysis (PCA) was performed to identify air pollution sources and tree based ensemble learning models were constructed to predict the urban air quality of Lucknow (India) using the air quality and meteorological databases pertaining to a period of five years. PCA identified vehicular emissions and fuel combustion as major air pollution sources. The air quality indices revealed the air quality unhealthy during the summer and winter. Ensemble models were constructed to discriminate between the seasonal air qualities, factors responsible for discrimination, and to predict the air quality indices. Accordingly, single decision tree (SDT), decision tree forest (DTF), and decision treeboost (DTB) were constructed and their generalization and predictive performance was evaluated in terms of several statistical parameters and compared with conventional machine learning benchmark, support vector machines (SVM). The DT and SVM models discriminated the seasonal air quality rendering misclassification rate (MR) of 8.32% (SDT); 4.12% (DTF); 5.62% (DTB), and 6.18% (SVM), respectively in complete data. The AQI and CAQI regression models yielded a correlation between measured and predicted values and root mean squared error of 0.901, 6.67 and 0.825, 9.45 (SDT); 0.951, 4.85 and 0.922, 6.56 (DTF); 0.959, 4.38 and 0.929, 6.30 (DTB); 0.890, 7.00 and 0.836, 9.16 (SVR) in complete data. The DTF and DTB models outperformed the SVM both in classification and regression which could be attributed to the incorporation of the bagging and boosting algorithms in these models. The proposed ensemble models successfully predicted the urban ambient air quality and can be used as effective tools for its management.
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A software development and evolution model based on decision-making
NASA Technical Reports Server (NTRS)
Wild, J. Christian; Dong, Jinghuan; Maly, Kurt
1991-01-01
Design is a complex activity whose purpose is to construct an artifact which satisfies a set of constraints and requirements. However the design process is not well understood. The software design and evolution process is the focus of interest, and a three dimensional software development space organized around a decision-making paradigm is presented. An initial instantiation of this model called 3DPM(sub p) which was partly implemented, is presented. Discussion of the use of this model in software reuse and process management is given.
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On the use of Bayesian decision theory for issuing natural hazard warnings
NASA Astrophysics Data System (ADS)
Economou, T.; Stephenson, D. B.; Rougier, J. C.; Neal, R. A.; Mylne, K. R.
2016-10-01
Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.
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On the use of Bayesian decision theory for issuing natural hazard warnings.
Economou, T; Stephenson, D B; Rougier, J C; Neal, R A; Mylne, K R
2016-10-01
Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.
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On the use of Bayesian decision theory for issuing natural hazard warnings
Stephenson, D. B.; Rougier, J. C.; Neal, R. A.; Mylne, K. R.
2016-01-01
Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings. PMID:27843399
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NASA Astrophysics Data System (ADS)
Zai, Wenjiao; Wang, Bo; Liu, Jichun; Shi, Haobo; Zeng, Pingliang
2018-02-01
The investment decision model of trans-regional transmission network in the context of Global Energy Internet was studied in this paper. The key factors affecting the trans-regional transmission network investment income: the income tax rate, the loan interest rate, the expected return on investment of the investment subject, the per capita GDP and so on were considered in the transmission network investment income model. First, according to the principle of system dynamics, the causality diagram of key factors was constructed. Then, the dynamic model of transmission investment decision was established. A case study of the power transmission network between China and Mongolia, through the simulation of the system dynamic model, the influence of the above key factors on the investment returns was analyzed, and the feasibility and effectiveness of the model was proved.
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Modeling Human-Computer Decision Making with Covariance Structure Analysis.
ERIC Educational Resources Information Center
Coovert, Michael D.; And Others
Arguing that sufficient theory exists about the interplay between human information processing, computer systems, and the demands of various tasks to construct useful theories of human-computer interaction, this study presents a structural model of human-computer interaction and reports the results of various statistical analyses of this model.…
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Dalyander, P Soupy; Meyers, Michelle; Mattsson, Brady; Steyer, Gregory; Godsey, Elizabeth; McDonald, Justin; Byrnes, Mark; Ford, Mark
2016-12-01
Coastal ecosystem management typically relies on subjective interpretation of scientific understanding, with limited methods for explicitly incorporating process knowledge into decisions that must meet multiple, potentially competing stakeholder objectives. Conversely, the scientific community lacks methods for identifying which advancements in system understanding would have the highest value to decision-makers. A case in point is barrier island restoration, where decision-makers lack tools to objectively use system understanding to determine how to optimally use limited contingency funds when project construction in this dynamic environment does not proceed as expected. In this study, collaborative structured decision-making (SDM) was evaluated as an approach to incorporate process understanding into mid-construction decisions and to identify priority gaps in knowledge from a management perspective. The focus was a barrier island restoration project at Ship Island, Mississippi, where sand will be used to close an extensive breach that currently divides the island. SDM was used to estimate damage that may occur during construction, and guide repair decisions within the confines of limited availability of sand and funding to minimize adverse impacts to project objectives. Sand was identified as more limiting than funds, and unrepaired major breaching would negatively impact objectives. Repairing minor damage immediately was determined to be generally more cost effective (depending on the longshore extent) than risking more damage to a weakened project. Key gaps in process-understanding relative to project management were identified as the relationship of island width to breach formation; the amounts of sand lost during breaching, lowering, or narrowing of the berm; the potential for minor breaches to self-heal versus developing into a major breach; and the relationship between upstream nourishment and resiliency of the berm to storms. This application is a prototype for using structured decision-making in support of engineering projects in dynamic environments where mid-construction decisions may arise; highlights uncertainty about barrier island physical processes that limit the ability to make robust decisions; and demonstrates the potential for direct incorporation of process-based models in a formal adaptive management decision framework. Published by Elsevier Ltd.
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Dalyander, P. Soupy; Meyers, Michelle B.; Mattsson, Brady; Steyer, Gregory; Godsey, Elizabeth; McDonald, Justin; Byrnes, Mark R.; Ford, Mark
2016-01-01
Coastal ecosystem management typically relies on subjective interpretation of scientific understanding, with limited methods for explicitly incorporating process knowledge into decisions that must meet multiple, potentially competing stakeholder objectives. Conversely, the scientific community lacks methods for identifying which advancements in system understanding would have the highest value to decision-makers. A case in point is barrier island restoration, where decision-makers lack tools to objectively use system understanding to determine how to optimally use limited contingency funds when project construction in this dynamic environment does not proceed as expected. In this study, collaborative structured decision-making (SDM) was evaluated as an approach to incorporate process understanding into mid-construction decisions and to identify priority gaps in knowledge from a management perspective. The focus was a barrier island restoration project at Ship Island, Mississippi, where sand will be used to close an extensive breach that currently divides the island. SDM was used to estimate damage that may occur during construction, and guide repair decisions within the confines of limited availability of sand and funding to minimize adverse impacts to project objectives. Sand was identified as more limiting than funds, and unrepaired major breaching would negatively impact objectives. Repairing minor damage immediately was determined to be generally more cost effective (depending on the longshore extent) than risking more damage to a weakened project. Key gaps in process-understanding relative to project management were identified as the relationship of island width to breach formation; the amounts of sand lost during breaching, lowering, or narrowing of the berm; the potential for minor breaches to self-heal versus developing into a major breach; and the relationship between upstream nourishment and resiliency of the berm to storms. This application is a prototype for using structured decision-making in support of engineering projects in dynamic environments where mid-construction decisions may arise; highlights uncertainty about barrier island physical processes that limit the ability to make robust decisions; and demonstrates the potential for direct incorporation of process-based models in a formal adaptive management decision framework.
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How High School Students Construct Decision-Making Strategies for Choosing Colleges
ERIC Educational Resources Information Center
Govan, George V.; Patrick, Sondra; Yen, Cherng-Jyn
2006-01-01
This study examined how high school seniors construct decision-making strategies for choosing a college to attend. To comprehend their decision-making strategies, we chose to examine this process through the theoretical lens of bounded rationality, which brings to light the complexity in constructing a college choice decision-making strategy…
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A study on specialist or special disease clinics based on big data.
Fang, Zhuyuan; Fan, Xiaowei; Chen, Gong
2014-09-01
Correlation analysis and processing of massive medical information can be implemented through big data technology to find the relevance of different factors in the life cycle of a disease and to provide the basis for scientific research and clinical practice. This paper explores the concept of constructing a big medical data platform and introduces the clinical model construction. Medical data can be collected and consolidated by distributed computing technology. Through analysis technology, such as artificial neural network and grey model, a medical model can be built. Big data analysis, such as Hadoop, can be used to construct early prediction and intervention models as well as clinical decision-making model for specialist and special disease clinics. It establishes a new model for common clinical research for specialist and special disease clinics.
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Fung, Ivan W H; Lo, Tommy Y; Tung, Karen C F
2012-09-01
Since the safety professionals are the key decision makers dealing with project safety and risk assessment in the construction industry, their perceptions of safety risk would directly affect the reliability of risk assessment. The safety professionals generally tend to heavily rely on their own past experiences to make subjective decisions on risk assessment without systematic decision making. Indeed, understanding of the underlying principles of risk assessment is significant. In this study, the qualitative analysis on the safety professionals' beliefs of risk assessment and their perceptions towards risk assessment, including their recognitions of possible accident causes, the degree of differentiations on their perceptions of risk levels of different trades of works, recognitions of the occurrence of different types of accidents, and their inter-relationships with safety performance in terms of accident rates will be explored in the Stage 1. At the second stage, the deficiencies of the current general practice for risk assessment can be sorted out firstly. Based on the findings from Stage 1 and the historical accident data from 15 large-scaled construction projects in 3-year average, a risk evaluation model prioritizing the risk levels of different trades of works and which cause different types of site accident due to various accident causes will be developed quantitatively. With the suggested systematic accident recording techniques, this model can be implemented in the construction industry at both project level and organizational level. The model (Q(2)REM) not only act as a useful supplementary guideline of risk assessment for the construction safety professionals, but also assists them to pinpoint the potential risks on site for the construction workers under respective trades of works through safety trainings and education. It, in turn, arouses their awareness on safety risk. As the Q(2)REM can clearly show the potential accident causes leading to different types of accident by trade of works, it helps the concerned safety professionals and parties to plan effective accident prevention measures with reference to the priority of the risk levels. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Linguistic Analysis of Constructed Student Responses in CAI.
ERIC Educational Resources Information Center
Simmons, Robert F.
Protosynthex III (PSIII) is a language processing system developed as an (as yet inadequate) experimental vehicle for testing student responses, with a view to constructing a model of an automated tutor. A version of the PLANIT system was modified so that a human tutor could be used to make instructional decisions in response to students'…
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1998-04-28
be discussed. 2.1 ECONOMIC REPLACEMENT THEORY Decisions about heavy equipment should be made based on sound economic principles , not emotions...Life) will be less than L*. The converse is also true. 2.1.3 The Repair Limit Theory A different way of looking at the economic replacement decision...Summary Three different economic models have been reviewed in this section. The output of each is distinct. One seeks to minimize costs, one seeks to
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Hyde, Melissa K; White, Katherine M
2014-01-01
Understanding people's organ donation decisions may narrow the gap between organ supply and demand. In two studies, participants who had not recorded their posthumous organ donation decision (Study 1, N = 210; Study 2, N = 307) completed items assessing prototype/willingness model (PWM; attitude, subjective norm, donor prototype favorability and similarity, willingness) constructs. Attitude, subjective norm, and prototype similarity predicted willingness to donate. Prototype favorability and a Prototype Favorability × Similarity interaction predicted willingness (Study 2). These findings provide support for the PWM in altruistic health contexts, highlighting the importance of people's perceptions about organ donors in their donation decisions.
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Hyde, Melissa K; White, Katherine M
2014-06-09
Understanding people's organ donation decisions may narrow the gap between organ supply and demand. In two studies, participants who had not recorded their posthumous organ donation decision (Study 1 N = 210; Study 2 N = 307) completed items assessing Prototype/Willingness Model (PWM) (attitude, subjective norm, donor prototype favorability and similarity, willingness) constructs. Attitude, subjective norm, and prototype similarity predicted willingness to donate. Prototype favorability and a prototype favorability x similarity interaction predicted willingness (Study 2). These findings provide support for the PWM in altruistic health contexts, highlighting the importance of people's perceptions about organ donors in their donation decisions.
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Shreffler-Grant, Jean; Nichols, Elizabeth; Weinert, Clarann; Ide, Bette
2016-01-01
This article aims to present and describe a model of complementary and alternative medicine (CAM) health literacy. The model is the conceptual basis for CAM health literacy, which is operationally defined as the information about CAM needed to make informed self-management decisions regarding health. Improving health literacy is a national priority, and widespread use of CAM has added to the complexity of this task. There are no currently available models or measures of health literacy regarding CAM. The authors developed the model using an iterative process of deriving concepts, constructs, and empirical indicators from the literature and the author’s prior work, review and critique by experts, and revision. The model of CAM health literacy can serve as the basis for future research on the use and efficacy of CAM and the constructs and concepts within it can be used to identify points of intervention for research or for clinical practice. It is anticipated that the model will have scientific and clinical application for assessing health literacy in other self care decision-making situations. PMID:23889542
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Shreffler-Grant, Jean; Nichols, Elizabeth; Weinert, Clarann; Ide, Bette
2013-01-01
This article aims to present and describe a model of complementary and alternative medicine (CAM) health literacy. The model is the conceptual basis for CAM health literacy, which is operationally defined as the information about CAM needed to make informed self-management decisions regarding health. Improving health literacy is a national priority, and widespread use of CAM has added to the complexity of this task. There are no currently available models or measures of health literacy regarding CAM. The authors developed the model using an iterative process of deriving concepts, constructs, and empirical indicators from the literature and the author's prior work, review and critique by experts, and revision. The model of CAM health literacy can serve as the basis for future research on the use and efficacy of CAM and the constructs and concepts within it can be used to identify points of intervention for research or for clinical practice. It is anticipated that the model will have scientific and clinical application for assessing health literacy in other self care decision-making situations.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Kyong Ju, E-mail: kjkim@cau.ac.kr; Yun, Won Gun, E-mail: ogun78@naver.com; Cho, Namho, E-mail: nhc51@cau.ac.kr
The late rise in global concern for environmental issues such as global warming and air pollution is accentuating the need for environmental assessments in the construction industry. Promptly evaluating the environmental loads of the various design alternatives during the early stages of a construction project and adopting the most environmentally sustainable candidate is therefore of large importance. Yet, research on the early evaluation of a construction project's environmental load in order to aid the decision making process is hitherto lacking. In light of this dilemma, this study proposes a model for estimating the environmental load by employing only the mostmore » basic information accessible during the early design phases of a project for the pre-stressed concrete (PSC) beam bridge, the most common bridge structure. Firstly, a life cycle assessment (LCA) was conducted on the data from 99 bridges by integrating the bills of quantities (BOQ) with a life cycle inventory (LCI) database. The processed data was then utilized to construct a case based reasoning (CBR) model for estimating the environmental load. The accuracy of the estimation model was then validated using five test cases; the model's mean absolute error rates (MAER) for the total environmental load was calculated as 7.09%. Such test results were shown to be superior compared to those obtained from a multiple-regression based model and a slab area base-unit analysis model. Henceforth application of this model during the early stages of a project is expected to highly complement environmentally friendly designs and construction by facilitating the swift evaluation of the environmental load from multiple standpoints. - Highlights: • This study is to develop the model of assessing the environmental impacts on LCA. • Bills of quantity from completed designs of PSC Beam were linked with the LCI DB. • Previous cases were used to estimate the environmental load of new case by CBR model. • CBR model produces more accurate estimations (7.09%) than other conventional models. • This study supports decision making process in the early stage of a new construction case.« less
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AdViSHE: A Validation-Assessment Tool of Health-Economic Models for Decision Makers and Model Users.
Vemer, P; Corro Ramos, I; van Voorn, G A K; Al, M J; Feenstra, T L
2016-04-01
A trade-off exists between building confidence in health-economic (HE) decision models and the use of scarce resources. We aimed to create a practical tool providing model users with a structured view into the validation status of HE decision models, to address this trade-off. A Delphi panel was organized, and was completed by a workshop during an international conference. The proposed tool was constructed iteratively based on comments from, and the discussion amongst, panellists. During the Delphi process, comments were solicited on the importance and feasibility of possible validation techniques for modellers, their relevance for decision makers, and the overall structure and formulation in the tool. The panel consisted of 47 experts in HE modelling and HE decision making from various professional and international backgrounds. In addition, 50 discussants actively engaged in the discussion at the conference workshop and returned 19 questionnaires with additional comments. The final version consists of 13 items covering all relevant aspects of HE decision models: the conceptual model, the input data, the implemented software program, and the model outcomes. Assessment of the Validation Status of Health-Economic decision models (AdViSHE) is a validation-assessment tool in which model developers report in a systematic way both on validation efforts performed and on their outcomes. Subsequently, model users can establish whether confidence in the model is justified or whether additional validation efforts should be undertaken. In this way, AdViSHE enhances transparency of the validation status of HE models and supports efficient model validation.
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Stochastic Simulation Using @ Risk for Dairy Business Investment Decisions
USDA-ARS?s Scientific Manuscript database
A dynamic, stochastic, mechanistic simulation model of a dairy business was developed to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting fram...
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Sun, Wei; Zhang, Xiaorui; Peeta, Srinivas; He, Xiaozheng; Li, Yongfu; Zhu, Senlai
2015-01-01
To improve the effectiveness and robustness of fatigue driving recognition, a self-adaptive dynamic recognition model is proposed that incorporates information from multiple sources and involves two sequential levels of fusion, constructed at the feature level and the decision level. Compared with existing models, the proposed model introduces a dynamic basic probability assignment (BPA) to the decision-level fusion such that the weight of each feature source can change dynamically with the real-time fatigue feature measurements. Further, the proposed model can combine the fatigue state at the previous time step in the decision-level fusion to improve the robustness of the fatigue driving recognition. An improved correction strategy of the BPA is also proposed to accommodate the decision conflict caused by external disturbances. Results from field experiments demonstrate that the effectiveness and robustness of the proposed model are better than those of models based on a single fatigue feature and/or single-source information fusion, especially when the most effective fatigue features are used in the proposed model. PMID:26393615
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Multiple Subtypes among Vocationally Undecided College Students: A Model and Assessment Instrument.
ERIC Educational Resources Information Center
Jones, Lawrence K.; Chenery, Mary Faeth
1980-01-01
A model of vocational decision status was developed, and an instrument was constructed and used to assess its three dimensions. Results demonstrated the utility of the model, supported the reliability and validity of the instrument, and illustrated the value of viewing vocationally undecided students as multiple subtypes. (Author)
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Valder, Joshua F.; Delzer, Gregory C.; Carter, Janet M.; Smith, Bruce D.; Smith, David V.
2016-09-28
The city of Sioux Falls is the fastest growing community in South Dakota. In response to this continued growth and planning for future development, Sioux Falls requires a sustainable supply of municipal water. Planning and managing sustainable groundwater supplies requires a thorough understanding of local groundwater resources. The Big Sioux aquifer consists of glacial outwash sands and gravels and is hydraulically connected to the Big Sioux River, which provided about 90 percent of the city’s source-water production in 2015. Managing sustainable groundwater supplies also requires an understanding of groundwater availability. An effective mechanism to inform water management decisions is the development and utilization of a groundwater-flow model. A groundwater-flow model provides a quantitative framework for synthesizing field information and conceptualizing hydrogeologic processes. These groundwater-flow models can support decision making processes by mapping and characterizing the aquifer. Accordingly, the city of Sioux Falls partnered with the U.S. Geological Survey to construct a groundwater-flow model. Model inputs will include data from advanced geophysical techniques, specifically airborne electromagnetic methods.
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Federal Register 2010, 2011, 2012, 2013, 2014
2013-08-16
... Garrison, Hawai`i, (USAG-HI) announce the decision to construct and operate a new Infantry Platoon Battle... decision allows the Army to construct and operate an IPBC that will meet Army training requirements and... with alternatives to construct and operate the IPBC. In the Final EIS published in the Federal Register...
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Warfighter decision making performance analysis as an investment priority driver
NASA Astrophysics Data System (ADS)
Thornley, David J.; Dean, David F.; Kirk, James C.
2010-04-01
Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.
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NASA Technical Reports Server (NTRS)
Uschold, Michael
1992-01-01
We are concerned with two important issues in simulation modelling: model comprehension and model construction. Model comprehension is limited because many important choices taken during the modelling process are not documented. This makes it difficult for models to be modified or used by others. A key factor hindering model construction is the vast modelling search space which must be navigated. This is exacerbated by the fact that many modellers are unfamiliar with the terms and concepts catered to by current tools. The root of both problems is the lack of facilities for representing or reasoning about domain concepts in current simulation technology. The basis for our achievements in both of these areas is the development of a language with two distinct levels; one for representing domain information, and the other for representing the simulation model. Of equal importance, is the fact that we make formal connections between these two levels. The domain we are concerned with is ecological modelling. This language, called Elklogic, is based on the typed lambda calculus. Important features include a rich type structure, the use of various higher order functions, and semantics. This enables complex expressions to be constructed from relatively few primitives. The meaning of each expression can be determined in terms of the domain, the simulation model, or the relationship between the two. We describe a novel representation for sets and substructure, and a variety of other general concepts that are especially useful in the ecological domain. We use the type structure in a novel way: for controlling the modelling search space, rather than a proof search space. We facilitate model comprehension by representing modelling decisions that are embodied in the simulation model. We represent the simulation model separately from, but in terms of a domain mode. The explicit links between the two models constitute the modelling decisions. The semantics of Elklogic enables English text to be generated to explain the simulation model in domain terms.
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Using simplifications of reality in the real world: Robust benefits of models for decision making
NASA Astrophysics Data System (ADS)
Hunt, R. J.
2008-12-01
Models are by definition simplifications of reality; the degree and nature of simplification, however, is debated. One view is "the world is 3D, heterogeneous, and transient, thus good models are too" - the more a model directly simulates the complexity of the real world the better it is considered to be. An alternative view is to only use simple models up front because real-world complexity can never be truly known. A third view is construct and calibrate as many models as predictions. A fourth is to build highly parameterized models and either look at an ensemble of results, or use mathematical regularization to identify an optimal most reasonable parameter set and fit. Although each view may have utility for a given decision-making process, there are common threads that perhaps run through all views. First, the model-construction process itself can help the decision-making process because it raises the discussion of opposing parties from one of contrasting professional opinions to discussion of reasonable types and ranges of model inputs and processes. Secondly, no matter what view is used to guide the model building, model predictions for the future might be expected to perform poorly in the future due to unanticipated future changes and stressors to the underlying system simulated. Although this does not reduce the obligation of the modeler to build representative tools for the system, it should serve to temper expectations of model performance. Finally, perhaps the most under-appreciated utility of models is for calculating the reduction in prediction uncertainty resulting from different data collection strategies - an attractive feature separate from the calculation and minimization of absolute prediction uncertainty itself. This type of model output facilitates focusing on efficient use of current and future monitoring resources - something valued by many decision-makers regardless of background, system managed, and societal context.
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Variables, Decisions, and Scripting in Construct
2009-09-01
grounded in sociology and cognitive science which seeks to model the processes and situations by which humans interact and share information...Construct is an embodiment of constructuralism (Carley 1986), a theory which posits that human social structures and cognitive structures co-evolve so that...human cognition reflects human social behavior, and that human social behavior simultaneously influences cognitive processes. Recent work with
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3D methodology for evaluating rail crossing roughness : vehicle dynamic modeling.
DOT National Transportation Integrated Search
2015-09-28
In order for the results of the approach to be useful in decision making, one must consider that the accelerations (modeled or measured) at a rail crossing location can derive from either condition or construction of the crossing. That is to say, a c...
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Miller, W B; Pasta, D J
2001-01-01
In this study we develop and then test a couple model of contraceptive method choice decision-making following a pregnancy scare. The central constructs in our model are satisfaction with one's current method and confidence in the use of it. Downstream in the decision sequence, satisfaction and confidence predict desires and intentions to change methods. Upstream they are predicted by childbearing motivations, contraceptive attitudes, and the residual effects of the couples' previous method decisions. We collected data from 175 mostly unmarried and racially/ethnically diverse couples who were seeking pregnancy tests. We used LISREL and its latent variable capacity to estimate a structural equation model of the couple decision-making sequence leading to a change (or not) in contraceptive method. Results confirm most elements in our model and demonstrate a number of important cross-partner effects. Almost one-half of the sample had positive pregnancy tests and the base model fitted to this subsample indicates less accuracy in partner perception and greater influence of the female partner on method change decision-making. The introduction of some hypothesis-generating exogenous variables to our base couple model, together with some unexpected findings for the contraceptive attitude variables, suggest interesting questions that require further exploration.
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[Shared decision-making and communication theory: grounding the tango].
Kasper, Jürgen; Légaré, France; Scheibler, Fülöp; Geiger, Friedemann
2010-01-01
Shared decision-making (SDM) has the potential to overcome outdated social role models in the health care system. The concept, however, adheres to archaic epistemological assumptions as can be inferred from the rudimentary stage of the measurement methods used and from the information monopoly that the physician still holds in this concept. Advantages of an up-to-date model of knowledge for understanding and operationalising SDM are outlined. To this purpose, essential definitions of the concept are reflected in terms of epistemology. Accordingly, information emerges through a process of social construction. Likewise, interpersonal relations do not represent a static condition; rather, they develop anew with each interaction. Therefore, constructs suitable to focus on dyadic interaction processes can be used as indicators of sharing in SDM. Theories and methods of the interpersonal paradigm are advocated. Copyright © 2010. Published by Elsevier GmbH.
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Decision Through Optimism: The North Peruvian Pipeline.
1987-05-01
corporations. Another factor, optimism, is more intangible, but influenced the decision strongly. This paper discusses the need for, construction of...decision, the construction effort, and financing to accomplish this endeavor. Finally, it notes Peru’s oil situation after completion of the pipeline and...decision strongly. This paper discusses the need for, construction of, and results of building the Northern Peru Oil Pipeline. The paper reviews the
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de Visser, Leonie; Homberg, Judith R.; Mitsogiannis, Manuela; Zeeb, Fiona D.; Rivalan, Marion; Fitoussi, Aurélie; Galhardo, Vasco; van den Bos, Ruud; Winstanley, Catherine A.; Dellu-Hagedorn, Françoise
2011-01-01
Impaired decision-making is a core problem in several psychiatric disorders including attention-deficit/hyperactivity disorder, schizophrenia, obsessive–compulsive disorder, mania, drug addiction, eating disorders, and substance abuse as well as in chronic pain. To ensure progress in the understanding of the neuropathophysiology of these disorders, animal models with good construct and predictive validity are indispensable. Many human studies aimed at measuring decision-making capacities use the Iowa gambling task (IGT), a task designed to model everyday life choices through a conflict between immediate gratification and long-term outcomes. Recently, new rodent models based on the same principle have been developed to investigate the neurobiological mechanisms underlying IGT-like decision-making on behavioral, neural, and pharmacological levels. The comparative strengths, as well as the similarities and differences between these paradigms are discussed. The contribution of these models to elucidate the neurobehavioral factors that lead to poor decision-making and to the development of better treatments for psychiatric illness is considered, along with important future directions and potential limitations. PMID:22013406
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Smith, Wade P; Doctor, Jason; Meyer, Jürgen; Kalet, Ira J; Phillips, Mark H
2009-06-01
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. 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. 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. 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.
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Valdes, Gilmer; Simone, Charles B; Chen, Josephine; Lin, Alexander; Yom, Sue S; Pattison, Adam J; Carpenter, Colin M; Solberg, Timothy D
2017-12-01
Clinical decision support systems are a growing class of tools with the potential to impact healthcare. This study investigates the construction of a decision support system through which clinicians can efficiently identify which previously approved historical treatment plans are achievable for a new patient to aid in selection of therapy. Treatment data were collected for early-stage lung and postoperative oropharyngeal cancers treated using photon (lung and head and neck) and proton (head and neck) radiotherapy. Machine-learning classifiers were constructed using patient-specific feature-sets and a library of historical plans. Model accuracy was analyzed using learning curves, and historical treatment plan matching was investigated. Learning curves demonstrate that for these datasets, approximately 45, 60, and 30 patients are needed for a sufficiently accurate classification model for radiotherapy for early-stage lung, postoperative oropharyngeal photon, and postoperative oropharyngeal proton, respectively. The resulting classification model provides a database of previously approved treatment plans that are achievable for a new patient. An exemplary case, highlighting tradeoffs between the heart and chest wall dose while holding target dose constant in two historical plans is provided. We report on the first artificial-intelligence based clinical decision support system that connects patients to past discrete treatment plans in radiation oncology and demonstrate for the first time how this tool can enable clinicians to use past decisions to help inform current assessments. Clinicians can be informed of dose tradeoffs between critical structures early in the treatment process, enabling more time spent on finding the optimal course of treatment for individual patients. Copyright © 2017. Published by Elsevier B.V.
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Li, Ke; Zhang, Peng; Crittenden, John C; Guhathakurta, Subhrajit; Chen, Yongsheng; Fernando, Harindra; Sawhney, Anil; McCartney, Peter; Grimm, Nancy; Kahhat, Ramzy; Joshi, Himanshu; Konjevod, Goran; Choi, Yu-Jin; Fonseca, Ernesto; Allenby, Braden; Gerrity, Daniel; Torrens, Paul M
2007-07-15
To encourage sustainable development, engineers and scientists need to understand the interactions among social decision-making, development and redevelopment, land, energy and material use, and their environmental impacts. In this study, a framework that connects these interactions was proposed to guide more sustainable urban planning and construction practices. Focusing on the rapidly urbanizing setting of Phoenix, Arizona, complexity models and deterministic models were assembled as a metamodel, which is called Sustainable Futures 2100 and were used to predict land use and development, to quantify construction material demands, to analyze the life cycle environmental impacts, and to simulate future ground-level ozone formation.
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2015-01-01
Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN) model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project. PMID:26339227
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Shin, Yoonseok
2015-01-01
Among the recent data mining techniques available, the boosting approach has attracted a great deal of attention because of its effective learning algorithm and strong boundaries in terms of its generalization performance. However, the boosting approach has yet to be used in regression problems within the construction domain, including cost estimations, but has been actively utilized in other domains. Therefore, a boosting regression tree (BRT) is applied to cost estimations at the early stage of a construction project to examine the applicability of the boosting approach to a regression problem within the construction domain. To evaluate the performance of the BRT model, its performance was compared with that of a neural network (NN) model, which has been proven to have a high performance in cost estimation domains. The BRT model has shown results similar to those of NN model using 234 actual cost datasets of a building construction project. In addition, the BRT model can provide additional information such as the importance plot and structure model, which can support estimators in comprehending the decision making process. Consequently, the boosting approach has potential applicability in preliminary cost estimations in a building construction project.
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NASA Astrophysics Data System (ADS)
Kolkman, M. J.; Kok, M.; van der Veen, A.
The solution of complex, unstructured problems is faced with policy controversy and dispute, unused and misused knowledge, project delay and failure, and decline of public trust in governmental decisions. Mental model mapping (also called concept mapping) is a technique to analyse these difficulties on a fundamental cognitive level, which can reveal experiences, perceptions, assumptions, knowledge and subjective beliefs of stakeholders, experts and other actors, and can stimulate communication and learning. This article presents the theoretical framework from which the use of mental model mapping techniques to analyse this type of problems emerges as a promising technique. The framework consists of the problem solving or policy design cycle, the knowledge production or modelling cycle, and the (computer) model as interface between the cycles. Literature attributes difficulties in the decision-making process to communication gaps between decision makers, stakeholders and scientists, and to the construction of knowledge within different paradigm groups that leads to different interpretation of the problem situation. Analysis of the decision-making process literature indicates that choices, which are made in all steps of the problem solving cycle, are based on an individual decision maker’s frame of perception. This frame, in turn, depends on the mental model residing in the mind of the individual. Thus we identify three levels of awareness on which the decision process can be analysed. This research focuses on the third level. Mental models can be elicited using mapping techniques. In this way, analysing an individual’s mental model can shed light on decision-making problems. The steps of the knowledge production cycle are, in the same manner, ultimately driven by the mental models of the scientist in a specific discipline. Remnants of this mental model can be found in the resulting computer model. The characteristics of unstructured problems (complexity, uncertainty and disagreement) can be positioned in the framework, as can the communities of knowledge construction and valuation involved in the solution of these problems (core science, applied science, and professional consultancy, and “post-normal” science). Mental model maps, this research hypothesises, are suitable to analyse the above aspects of the problem. This hypothesis is tested for the case of the Zwolle storm surch barrier. Analysis can aid integration between disciplines, participation of public stakeholders, and can stimulate learning processes. Mental model mapping is recommended to visualise the use of knowledge, to analyse difficulties in problem solving process, and to aid information transfer and communication. Mental model mapping help scientists to shape their new, post-normal responsibilities in a manner that complies with integrity when dealing with unstructured problems in complex, multifunctional systems.
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A stochastic discrete optimization model for designing container terminal facilities
NASA Astrophysics Data System (ADS)
Zukhruf, Febri; Frazila, Russ Bona; Burhani, Jzolanda Tsavalista
2017-11-01
As uncertainty essentially affect the total transportation cost, it remains important in the container terminal that incorporates several modes and transshipments process. This paper then presents a stochastic discrete optimization model for designing the container terminal, which involves the decision of facilities improvement action. The container terminal operation model is constructed by accounting the variation of demand and facilities performance. In addition, for illustrating the conflicting issue that practically raises in the terminal operation, the model also takes into account the possible increment delay of facilities due to the increasing number of equipment, especially the container truck. Those variations expectantly reflect the uncertainty issue in the container terminal operation. A Monte Carlo simulation is invoked to propagate the variations by following the observed distribution. The problem is constructed within the framework of the combinatorial optimization problem for investigating the optimal decision of facilities improvement. A new variant of glow-worm swarm optimization (GSO) is thus proposed for solving the optimization, which is rarely explored in the transportation field. The model applicability is tested by considering the actual characteristics of the container terminal.
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A dynamic simulation model is constructed to compare benefit-cost ratios of riparian restoration options for the Middle Rio Grande riparian corridor in Albuquerque, New Mexico, USA. The model is built from original choice experiment valuation data, regional benefit-transfer studi...
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The Living Arrangement Dynamics of Sick, Elderly Individuals
ERIC Educational Resources Information Center
Dostie, Benoit; Leger, Pierre Thomas
2005-01-01
We model the dynamics associated with living-arrangement decisions of sick elderly individuals. Using the Panel Study of Income Dynamics? Parental Health Supplement, we construct the complete living-arrangement histories of elderly individuals in need of care. We use a simultaneous random-effects competing-risks model to analyze the impact of…
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Assessment and Decision-Making in Early Childhood Education and Intervention
ERIC Educational Resources Information Center
Strand, Paul S.; Cerna, Sandra; Skucy, Jim
2007-01-01
Assessment within the fields of early childhood education and early childhood intervention is guided by the "deductive-psychometric model", which is a framework for legitimizing constructs that arise from theories. An alternative approach, termed the "inductive-experimental model", places significantly more restrictions on what constitutes a…
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Koriat, Asher; Sorka, Hila
2015-01-01
The classification of objects to natural categories exhibits cross-person consensus and within-person consistency, but also some degree of between-person variability and within-person instability. What is more, the variability in categorization is also not entirely random but discloses systematic patterns. In this study, we applied the Self-Consistency Model (SCM, Koriat, 2012) to category membership decisions, examining the possibility that confidence judgments and decision latency track the stable and variable components of categorization responses. The model assumes that category membership decisions are constructed on the fly depending on a small set of clues that are sampled from a commonly shared population of pertinent clues. The decision and confidence are based on the balance of evidence in favor of a positive or a negative response. The results confirmed several predictions derived from SCM. For each participant, consensual responses to items were more confident than non-consensual responses, and for each item, participants who made the consensual response tended to be more confident than those who made the nonconsensual response. The difference in confidence between consensual and nonconsensual responses increased with the proportion of participants who made the majority response for the item. A similar pattern was observed for response speed. The pattern of results obtained for cross-person consensus was replicated by the results for response consistency when the responses were classified in terms of within-person agreement across repeated presentations. These results accord with the sampling assumption of SCM, that confidence and response speed should be higher when the decision is consistent with what follows from the entire population of clues than when it deviates from it. Results also suggested that the context for classification can bias the sample of clues underlying the decision, and that confidence judgments mirror the effects of context on categorization decisions. The model and results offer a principled account of the stable and variable contributions to categorization behavior within a decision-making framework. Copyright © 2014 Elsevier B.V. All rights reserved.
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Classification images reveal decision variables and strategies in forced choice tasks
Pritchett, Lisa M.; Murray, Richard F.
2015-01-01
Despite decades of research, there is still uncertainty about how people make simple decisions about perceptual stimuli. Most theories assume that perceptual decisions are based on decision variables, which are internal variables that encode task-relevant information. However, decision variables are usually considered to be theoretical constructs that cannot be measured directly, and this often makes it difficult to test theories of perceptual decision making. Here we show how to measure decision variables on individual trials, and we use these measurements to test theories of perceptual decision making more directly than has previously been possible. We measure classification images, which are estimates of templates that observers use to extract information from stimuli. We then calculate the dot product of these classification images with the stimuli to estimate observers' decision variables. Finally, we reconstruct each observer's “decision space,” a map that shows the probability of the observer’s responses for all values of the decision variables. We use this method to examine decision strategies in two-alternative forced choice (2AFC) tasks, for which there are several competing models. In one experiment, the resulting decision spaces support the difference model, a classic theory of 2AFC decisions. In a second experiment, we find unexpected decision spaces that are not predicted by standard models of 2AFC decisions, and that suggest intrinsic uncertainty or soft thresholding. These experiments give new evidence regarding observers’ strategies in 2AFC tasks, and they show how measuring decision variables can answer long-standing questions about perceptual decision making. PMID:26015584
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An Investment Behavior Analysis using by Brain Computer Interface
NASA Astrophysics Data System (ADS)
Suzuki, Kyoko; Kinoshita, Kanta; Miyagawa, Kazuhiro; Shiomi, Shinichi; Misawa, Tadanobu; Shimokawa, Tetsuya
In this paper, we will construct a new Brain Computer Interface (BCI), for the purpose of analyzing human's investment decision makings. The BCI is made up of three functional parts which take roles of, measuring brain information, determining market price in an artificial market, and specifying investment decision model, respectively. When subjects make decisions, their brain information is conveyed to the part of specifying investment decision model through the part of measuring brain information, whereas, their decisions of investment order are sent to the part of artificial market to form market prices. Both the support vector machine and the 3 layered perceptron are used to assess the investment decision model. In order to evaluate our BCI, we conduct an experiment in which subjects and a computer trader agent trade shares of stock in the artificial market and test how the computer trader agent can forecast market price formation and investment decision makings from the brain information of subjects. The result of the experiment shows that the brain information can improve the accuracy of forecasts, and so the computer trader agent can supply market liquidity to stabilize market volatility without his loss.
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Constructing food choice decisions.
Sobal, Jeffery; Bisogni, Carole A
2009-12-01
Food choice decisions are frequent, multifaceted, situational, dynamic, and complex and lead to food behaviors where people acquire, prepare, serve, give away, store, eat, and clean up. Many disciplines and fields examine decision making. Several classes of theories are applicable to food decision making, including social behavior, social facts, and social definition perspectives. Each offers some insights but also makes limiting assumptions that prevent fully explaining food choice decisions. We used constructionist social definition perspectives to inductively develop a food choice process model that organizes a broad scope of factors and dynamics involved in food behaviors. This food choice process model includes (1) life course events and experiences that establish a food choice trajectory through transitions, turning points, timing, and contexts; (2) influences on food choices that include cultural ideals, personal factors, resources, social factors, and present contexts; and (3) a personal system that develops food choice values, negotiates and balances values, classifies foods and situations, and forms/revises food choice strategies, scripts, and routines. The parts of the model dynamically interact to make food choice decisions leading to food behaviors. No single theory can fully explain decision making in food behavior. Multiple perspectives are needed, including constructionist thinking.
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Web-based decision support system to predict risk level of long term rice production
NASA Astrophysics Data System (ADS)
Mukhlash, Imam; Maulidiyah, Ratna; Sutikno; Setiyono, Budi
2017-09-01
Appropriate decision making in risk management of rice production is very important in agricultural planning, especially for Indonesia which is an agricultural country. Good decision would be obtained if the supporting data required are satisfied and using appropriate methods. This study aims to develop a Decision Support System that can be used to predict the risk level of rice production in some districts which are central of rice production in East Java. Web-based decision support system is constructed so that the information can be easily accessed and understood. Components of the system are data management, model management, and user interface. This research uses regression models of OLS and Copula. OLS model used to predict rainfall while Copula model used to predict harvested area. Experimental results show that the models used are successfully predict the harvested area of rice production in some districts which are central of rice production in East Java at any given time based on the conditions and climate of a region. Furthermore, it can predict the amount of rice production with the level of risk. System generates prediction of production risk level in the long term for some districts that can be used as a decision support for the authorities.
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2012-01-01
Abstract Recent progress in stem cell biology, notably cell fate conversion, calls for novel theoretical understanding for cell differentiation. The existing qualitative concept of Waddington’s “epigenetic landscape” has attracted particular attention because it captures subsequent fate decision points, thus manifesting the hierarchical (“tree-like”) nature of cell fate diversification. Here, we generalized a recent work and explored such a developmental landscape for a two-gene fate decision circuit by integrating the underlying probability landscapes with different parameters (corresponding to distinct developmental stages). The change of entropy production rate along the parameter changes indicates which parameter changes can represent a normal developmental process while other parameters’ change can not. The transdifferentiation paths over the landscape under certain conditions reveal the possibility of a direct and reversible phenotypic conversion. As the intensity of noise increases, we found that the landscape becomes flatter and the dominant paths more straight, implying the importance of biological noise processing mechanism in development and reprogramming. We further extended the landscape of the one-step fate decision to that for two-step decisions in central nervous system (CNS) differentiation. A minimal network and dynamic model for CNS differentiation was firstly constructed where two three-gene motifs are coupled. We then implemented the SDEs (Stochastic Differentiation Equations) simulation for the validity of the network and model. By integrating the two landscapes for the two switch gene pairs, we constructed the two-step development landscape for CNS differentiation. Our work provides new insights into cellular differentiation and important clues for better reprogramming strategies. PMID:23300518
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ERIC Educational Resources Information Center
Zuo, Jiping
2008-01-01
This study examines marital construction of family power among male-out-migrant couples in a Chinese village in Guangxi Province. In-depth interviews show that male-out-migrant couples prefer joint decision making. When couples are in disputes, power tends to go to the ones who shoulder greater household-based responsibilities; in this case, they…
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Data to Decisions: Creating a Culture of Model-Driven Drug Discovery.
Brown, Frank K; Kopti, Farida; Chang, Charlie Zhenyu; Johnson, Scott A; Glick, Meir; Waller, Chris L
2017-09-01
Merck & Co., Inc., Kenilworth, NJ, USA, is undergoing a transformation in the way that it prosecutes R&D programs. Through the adoption of a "model-driven" culture, enhanced R&D productivity is anticipated, both in the form of decreased attrition at each stage of the process and by providing a rational framework for understanding and learning from the data generated along the way. This new approach focuses on the concept of a "Design Cycle" that makes use of all the data possible, internally and externally, to drive decision-making. These data can take the form of bioactivity, 3D structures, genomics, pathway, PK/PD, safety data, etc. Synthesis of high-quality data into models utilizing both well-established and cutting-edge methods has been shown to yield high confidence predictions to prioritize decision-making and efficiently reposition resources within R&D. The goal is to design an adaptive research operating plan that uses both modeled data and experiments, rather than just testing, to drive project decision-making. To support this emerging culture, an ambitious information management (IT) program has been initiated to implement a harmonized platform to facilitate the construction of cross-domain workflows to enable data-driven decision-making and the construction and validation of predictive models. These goals are achieved through depositing model-ready data, agile persona-driven access to data, a unified cross-domain predictive model lifecycle management platform, and support for flexible scientist-developed workflows that simplify data manipulation and consume model services. The end-to-end nature of the platform, in turn, not only supports but also drives the culture change by enabling scientists to apply predictive sciences throughout their work and over the lifetime of a project. This shift in mindset for both scientists and IT was driven by an early impactful demonstration of the potential benefits of the platform, in which expert-level early discovery predictive models were made available from familiar desktop tools, such as ChemDraw. This was built using a workflow-driven service-oriented architecture (SOA) on top of the rigorous registration of all underlying model entities.
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Capturing a Commander's decision making style
NASA Astrophysics Data System (ADS)
Santos, Eugene; Nguyen, Hien; Russell, Jacob; Kim, Keumjoo; Veenhuis, Luke; Boparai, Ramnjit; Stautland, Thomas Kristoffer
2017-05-01
A Commander's decision making style represents how he weighs his choices and evaluates possible solutions with regards to his goals. Specifically, in the naval warfare domain, it relates the way he processes a large amount of information in dynamic, uncertain environments, allocates resources, and chooses appropriate actions to pursue. In this paper, we describe an approach to capture a Commander's decision style by creating a cognitive model that captures his decisionmaking process and evaluate this model using a set of scenarios using an online naval warfare simulation game. In this model, we use the Commander's past behaviors and generalize Commander's actions across multiple problems and multiple decision making sequences in order to recommend actions to a Commander in a manner that he may have taken. Our approach builds upon the Double Transition Model to represent the Commander's focus and beliefs to estimate his cognitive state. Each cognitive state reflects a stage in a Commander's decision making process, each action reflects the tasks that he has taken to move himself closer to a final decision, and the reward reflects how close he is to achieving his goal. We then use inverse reinforcement learning to compute a reward for each of the Commander's actions. These rewards and cognitive states are used to compare between different styles of decision making. We construct a set of scenarios in the game where rational, intuitive and spontaneous decision making styles will be evaluated.
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Project Delivery System Mode Decision Based on Uncertain AHP and Fuzzy Sets
NASA Astrophysics Data System (ADS)
Kaishan, Liu; Huimin, Li
2017-12-01
The project delivery system mode determines the contract pricing type, project management mode and the risk allocation among all participants. Different project delivery system modes have different characteristics and applicable scope. For the owners, the selection of the delivery mode is the key point to decide whether the project can achieve the expected benefits, it relates to the success or failure of project construction. Under the precondition of comprehensively considering the influence factors of the delivery mode, the model of project delivery system mode decision was set up on the basis of uncertain AHP and fuzzy sets, which can well consider the uncertainty and fuzziness when conducting the index evaluation and weight confirmation, so as to rapidly and effectively identify the most suitable delivery mode according to project characteristics. The effectiveness of the model has been verified via the actual case analysis in order to provide reference for the construction project delivery system mode.
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Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.
Yang, Zhongliang; Huang, Yongfeng; Jiang, Yiran; Sun, Yuxi; Zhang, Yu-Jin; Luo, Pengcheng
2018-04-20
Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67% accuracy and 96.02% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.
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Risk Decision Making Model for Reservoir Floodwater resources Utilization
NASA Astrophysics Data System (ADS)
Huang, X.
2017-12-01
Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.
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Preference, resistance to change, and the cumulative decision model.
Grace, Randolph C
2018-01-01
According to behavioral momentum theory (Nevin & Grace, 2000a), preference in concurrent chains and resistance to change in multiple schedules are independent measures of a common construct representing reinforcement history. Here I review the original studies on preference and resistance to change in which reinforcement variables were manipulated parametrically, conducted by Nevin, Grace and colleagues between 1997 and 2002, as well as more recent research. The cumulative decision model proposed by Grace and colleagues for concurrent chains is shown to provide a good account of both preference and resistance to change, and is able to predict the increased sensitivity to reinforcer rate and magnitude observed with constant-duration components. Residuals from fits of the cumulative decision model to preference and resistance to change data were positively correlated, supporting the prediction of behavioral momentum theory. Although some questions remain, the learning process assumed by the cumulative decision model, in which outcomes are compared against a criterion that represents the average outcome value in the current context, may provide a plausible model for the acquisition of differential resistance to change. © 2018 Society for the Experimental Analysis of Behavior.
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Yan, Qing
2010-01-01
Bioinformatics is the rational study at an abstract level that can influence the way we understand biomedical facts and the way we apply the biomedical knowledge. Bioinformatics is facing challenges in helping with finding the relationships between genetic structures and functions, analyzing genotype-phenotype associations, and understanding gene-environment interactions at the systems level. One of the most important issues in bioinformatics is data integration. The data integration methods introduced here can be used to organize and integrate both public and in-house data. With the volume of data and the high complexity, computational decision support is essential for integrative transporter studies in pharmacogenomics, nutrigenomics, epigenetics, and systems biology. For the development of such a decision support system, object-oriented (OO) models can be constructed using the Unified Modeling Language (UML). A methodology is developed to build biomedical models at different system levels and construct corresponding UML diagrams, including use case diagrams, class diagrams, and sequence diagrams. By OO modeling using UML, the problems of transporter pharmacogenomics and systems biology can be approached from different angles with a more complete view, which may greatly enhance the efforts in effective drug discovery and development. Bioinformatics resources of membrane transporters and general bioinformatics databases and tools that are frequently used in transporter studies are also collected here. An informatics decision support system based on the models presented here is available at http://www.pharmtao.com/transporter . The methodology developed here can also be used for other biomedical fields.
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Soft context clustering for F0 modeling in HMM-based speech synthesis
NASA Astrophysics Data System (ADS)
Khorram, Soheil; Sameti, Hossein; King, Simon
2015-12-01
This paper proposes the use of a new binary decision tree, which we call a soft decision tree, to improve generalization performance compared to the conventional `hard' decision tree method that is used to cluster context-dependent model parameters in statistical parametric speech synthesis. We apply the method to improve the modeling of fundamental frequency, which is an important factor in synthesizing natural-sounding high-quality speech. Conventionally, hard decision tree-clustered hidden Markov models (HMMs) are used, in which each model parameter is assigned to a single leaf node. However, this `divide-and-conquer' approach leads to data sparsity, with the consequence that it suffers from poor generalization, meaning that it is unable to accurately predict parameters for models of unseen contexts: the hard decision tree is a weak function approximator. To alleviate this, we propose the soft decision tree, which is a binary decision tree with soft decisions at the internal nodes. In this soft clustering method, internal nodes select both their children with certain membership degrees; therefore, each node can be viewed as a fuzzy set with a context-dependent membership function. The soft decision tree improves model generalization and provides a superior function approximator because it is able to assign each context to several overlapped leaves. In order to use such a soft decision tree to predict the parameters of the HMM output probability distribution, we derive the smoothest (maximum entropy) distribution which captures all partial first-order moments and a global second-order moment of the training samples. Employing such a soft decision tree architecture with maximum entropy distributions, a novel speech synthesis system is trained using maximum likelihood (ML) parameter re-estimation and synthesis is achieved via maximum output probability parameter generation. In addition, a soft decision tree construction algorithm optimizing a log-likelihood measure is developed. Both subjective and objective evaluations were conducted and indicate a considerable improvement over the conventional method.
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Prediction of the compression ratio for municipal solid waste using decision tree.
Heshmati R, Ali Akbar; Mokhtari, Maryam; Shakiba Rad, Saeed
2014-01-01
The compression ratio of municipal solid waste (MSW) is an essential parameter for evaluation of waste settlement and landfill design. However, no appropriate model has been proposed to estimate the waste compression ratio so far. In this study, a decision tree method was utilized to predict the waste compression ratio (C'c). The tree was constructed using Quinlan's M5 algorithm. A reliable database retrieved from the literature was used to develop a practical model that relates C'c to waste composition and properties, including dry density, dry weight water content, and percentage of biodegradable organic waste using the decision tree method. The performance of the developed model was examined in terms of different statistical criteria, including correlation coefficient, root mean squared error, mean absolute error and mean bias error, recommended by researchers. The obtained results demonstrate that the suggested model is able to evaluate the compression ratio of MSW effectively.
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Wulff, M B; Steitz, J A
1999-06-01
Utilizing a path model, this study investigated the relationship between Androgyny and career decision-making among 91 high school girls. The constructs included in the model were Androgyny as assessed by the Bem Sex-role Inventory, Self-esteem as assessed by the Rosenberg Self-esteem Scale, Self-efficacy as assessed by the Wulff-Steitz Career Self-efficacy Scale, and Career Indecision as assessed by the Osipow Career Decision Scale. The results indicated that Androgyny scores were significantly associated with those on Self-esteem, Self-esteem with Self-efficacy, and Self-efficacy with Career Indecision. The results are discussed in terms of the usefulness of path models in clarifying complex interrelationships.
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Operational Plan Ontology Model for Interconnection and Interoperability
NASA Astrophysics Data System (ADS)
Long, F.; Sun, Y. K.; Shi, H. Q.
2017-03-01
Aiming at the assistant decision-making system’s bottleneck of processing the operational plan data and information, this paper starts from the analysis of the problem of traditional expression and the technical advantage of ontology, and then it defines the elements of the operational plan ontology model and determines the basis of construction. Later, it builds up a semi-knowledge-level operational plan ontology model. Finally, it probes into the operational plan expression based on the operational plan ontology model and the usage of the application software. Thus, this paper has the theoretical significance and application value in the improvement of interconnection and interoperability of the operational plan among assistant decision-making systems.
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Creative Construction of Mathematics and Science Concepts in Early Childhood.
ERIC Educational Resources Information Center
Gallenstein, Nancy L.
Noting that effective teaching models that emphasize critical thinking in mathematics and science are used less often in early childhood classrooms than in those for older students, this book provides early childhood educators with an explanation of teaching models that promote 3- to 8-year-olds critical thinking, problem solving, decision making,…
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Constructive Engineering of Simulations
NASA Technical Reports Server (NTRS)
Snyder, Daniel R.; Barsness, Brendan
2011-01-01
Joint experimentation that investigates sensor optimization, re-tasking and management has far reaching implications for Department of Defense, Interagency and multinational partners. An adaption of traditional human in the loop (HITL) Modeling and Simulation (M&S) was one approach used to generate the findings necessary to derive and support these implications. Here an entity-based simulation was re-engineered to run on USJFCOM's High Performance Computer (HPC). The HPC was used to support the vast number of constructive runs necessary to produce statistically significant data in a timely manner. Then from the resulting sensitivity analysis, event designers blended the necessary visualization and decision making components into a synthetic environment for the HITL simulations trials. These trials focused on areas where human decision making had the greatest impact on the sensor investigations. Thus, this paper discusses how re-engineering existing M&S for constructive applications can positively influence the design of an associated HITL experiment.
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USMC Inventory Control Using Optimization Modeling and Discrete Event Simulation
2016-09-01
release. Distribution is unlimited. USMC INVENTORY CONTROL USING OPTIMIZATION MODELING AND DISCRETE EVENT SIMULATION by Timothy A. Curling...USING OPTIMIZATION MODELING AND DISCRETE EVENT SIMULATION 5. FUNDING NUMBERS 6. AUTHOR(S) Timothy A. Curling 7. PERFORMING ORGANIZATION NAME(S...optimization and discrete -event simulation. This construct can potentially provide an effective means in improving order management decisions. However
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NASA Astrophysics Data System (ADS)
Bognot, J. R.; Candido, C. G.; Blanco, A. C.; Montelibano, J. R. Y.
2018-05-01
Monitoring the progress of building's construction is critical in construction management. However, measuring the building construction's progress are still manual, time consuming, error prone, and impose tedious process of analysis leading to delays, additional costings and effort. The main goal of this research is to develop a methodology for building construction progress monitoring based on 3D as-built model of the building from unmanned aerial system (UAS) images, 4D as-planned model (with construction schedule integrated) and, GIS analysis. Monitoring was done by capturing videos of the building with a camera-equipped UAS. Still images were extracted, filtered, bundle-adjusted, and 3D as-built model was generated using open source photogrammetric software. The as-planned model was generated from digitized CAD drawings using GIS. The 3D as-built model was aligned with the 4D as-planned model of building formed from extrusion of building elements, and integration of the construction's planned schedule. The construction progress is visualized via color-coding the building elements in the 3D model. The developed methodology was conducted and applied from the data obtained from an actual construction site. Accuracy in detecting `built' or `not built' building elements ranges from 82-84 % and precision of 50-72 %. Quantified progress in terms of the number of building elements are 21.31% (November 2016), 26.84 % (January 2017) and 44.19 % (March 2017). The results can be used as an input for progress monitoring performance of construction projects and improving related decision-making process.
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The Galaxen model--a concept for rehabilitation and prevention in the construction industry.
Stenlund, Berndt
2005-01-01
The Galaxen model was developed during the late 1980s to provide rehabilitation and prevention activities in the construction industry. It handles around 1200 workers with long-term sick leave or partial disabilities annually, some 10% of whom annually leave Galaxen for an ordinary job without a wage subsidy. The model includes a decision by a rehabilitation board of representatives from the employers, the trade union, and the regional employment office, a rehabilitation plan, allotment of a case manager, wage subsidies from the State to the company, a search for a suitable job in relation to the partial disability. It also includes a preventive program with emphasis on practical ergonomics. The Galaxen model has proved to be a suitable means of rehabilitating construction workers and returning them to the workforce. The model was developed within the Swedish social security system but could well be adjusted to other contexts.
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NASA Technical Reports Server (NTRS)
Horvitz, Eric; Ruokangas, Corinne; Srinivas, Sampath; Barry, Matthew
1993-01-01
We describe a collaborative research and development effort between the Palo Alto Laboratory of the Rockwell Science Center, Rockwell Space Operations Company, and the Propulsion Systems Section of NASA JSC to design computational tools that can manage the complexity of information displayed to human operators in high-stakes, time-critical decision contexts. We shall review an application from NASA Mission Control and describe how we integrated a probabilistic diagnostic model and a time-dependent utility model, with techniques for managing the complexity of computer displays. Then, we shall describe the behavior of VPROP, a system constructed to demonstrate promising display-management techniques. Finally, we shall describe our current research directions on the Vista 2 follow-on project.
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Losses due to weather phenomena in the bituminous concrete construction industry in Wisconsin
NASA Technical Reports Server (NTRS)
Kuhn, H. A. J.
1973-01-01
The losses (costs) due to weather phenomena as they affect the bituminous concrete industry in Wisconsin were studied. The bituminous concrete industry's response to precipitation, in the form of rain, is identified through the use of a model, albeit crude, which identifies a typical industry decision-response mechanism. Using this mechanism, historical weather data and 1969 construction activity, dollar losses resulting from rain occurrences were developed.
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Cognitive/Information Processing Psychology and Instruction: Reviewing Recent Theory and Practice.
ERIC Educational Resources Information Center
Gallagher, John P.
1979-01-01
Discusses recent developments in instructional psychology relative to cognitive task analysis, individual difference variables, and cognitive models of interactive instructional decision making, which use constructs developed within the field of cognitive/information processing psychology. (Author/WBC)
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Neuroeconomics: cross-currents in research on decision-making.
Sanfey, Alan G; Loewenstein, George; McClure, Samuel M; Cohen, Jonathan D
2006-03-01
Despite substantial advances, the question of how we make decisions and judgments continues to pose important challenges for scientific research. Historically, different disciplines have approached this problem using different techniques and assumptions, with few unifying efforts made. However, the field of neuroeconomics has recently emerged as an inter-disciplinary effort to bridge this gap. Research in neuroscience and psychology has begun to investigate neural bases of decision predictability and value, central parameters in the economic theory of expected utility. Economics, in turn, is being increasingly influenced by a multiple-systems approach to decision-making, a perspective strongly rooted in psychology and neuroscience. The integration of these disparate theoretical approaches and methodologies offers exciting potential for the construction of more accurate models of decision-making.
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Monte Carlo Simulation of Effective Coordination Mechanisms for e-Commerce
NASA Astrophysics Data System (ADS)
Sakas, D. P.; Vlachos, D. S.; Simos, T. E.
2008-11-01
Making decisions in a dynamic environment is considered extremely important in today's market. Decision trees which can be used to model these systems, are not easily constructed and solved, especially in the case of infinite sets of consequences (for example, consider the case where only the mean and the variance of an outcome is known). In this work, discrete approximation and Monte Carlo techniques are used to overcome the aforementioned difficulties.
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Aminbakhsh, Saman; Gunduz, Murat; Sonmez, Rifat
2013-09-01
The inherent and unique risks on construction projects quite often present key challenges to contractors. Health and safety risks are among the most significant risks in construction projects since the construction industry is characterized by a relatively high injury and death rate compared to other industries. In construction project management, safety risk assessment is an important step toward identifying potential hazards and evaluating the risks associated with the hazards. Adequate prioritization of safety risks during risk assessment is crucial for planning, budgeting, and management of safety related risks. In this paper, a safety risk assessment framework is presented based on the theory of cost of safety (COS) model and the analytic hierarchy process (AHP). The main contribution of the proposed framework is that it presents a robust method for prioritization of safety risks in construction projects to create a rational budget and to set realistic goals without compromising safety. The framework provides a decision tool for the decision makers to determine the adequate accident/injury prevention investments while considering the funding limits. The proposed safety risk framework is illustrated using a real-life construction project and the advantages and limitations of the framework are discussed. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.
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Banks, Victoria A; Stanton, Neville A
2015-01-01
Automated assistance in driving emergencies aims to improve the safety of our roads by avoiding or mitigating the effects of accidents. However, the behavioural implications of such systems remain unknown. This paper introduces the driver decision-making in emergencies (DDMiEs) framework to investigate how the level and type of automation may affect driver decision-making and subsequent responses to critical braking events using network analysis to interrogate retrospective verbalisations. Four DDMiE models were constructed to represent different levels of automation within the driving task and its effects on driver decision-making. Findings suggest that whilst automation does not alter the decision-making pathway (e.g. the processes between hazard detection and response remain similar), it does appear to significantly weaken the links between information-processing nodes. This reflects an unintended yet emergent property within the task network that could mean that we may not be improving safety in the way we expect. This paper contrasts models of driver decision-making in emergencies at varying levels of automation using the Southampton University Driving Simulator. Network analysis of retrospective verbalisations indicates that increasing the level of automation in driving emergencies weakens the link between information-processing nodes essential for effective decision-making.
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Multicriteria decision model for retrofitting existing buildings
NASA Astrophysics Data System (ADS)
Bostenaru Dan, B.
2003-04-01
In this paper a model to decide which buildings from an urban area should be retrofitted is presented. The model has been cast into existing ones by choosing the decision rule, criterion weighting and decision support system types most suitable for the spatial problem of reducing earthquake risk in urban areas, considering existing spatial multiatributive and multiobjective decision methods and especially collaborative issues. Due to the participative character of the group decision problem "retrofitting existing buildings" the decision making model is based on interactivity. Buildings have been modeled following the criteria of spatial decision support systems. This includes identifying the corresponding spatial elements of buildings according to the information needs of actors from different sphaeres like architects, construction engineers and economists. The decision model aims to facilitate collaboration between this actors. The way of setting priorities interactivelly will be shown, by detailing the two phases: judgemental and computational, in this case site analysis, collection and evaluation of the unmodified data and converting survey data to information with computational methods using additional expert support. Buildings have been divided into spatial elements which are characteristic for the survey, present typical damages in case of an earthquake and are decisive for a better seismic behaviour in case of retrofitting. The paper describes the architectural and engineering characteristics as well as the structural damage for constuctions of different building ages on the example of building types in Bucharest, Romania in compressible and interdependent charts, based on field observation, reports from the 1977 earthquake and detailed studies made by the author together with a local engineer for the EERI Web Housing Encyclopedia. On this base criteria for setting priorities flow into the expert information contained in the system.
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A Model For Change: An Approach for Forecasting Well-Being ...
Every community decision incorporates a "forecasting" strategy (whether formal or implicit) to help visualize expected results and evaluate the potential “feelings” that people living in that community may have about those results. With more communities seeking to make decisions based on sustainable alternatives, forecasting efforts that examine potential impacts of decisions on overall community well-being may prove to be valuable for not only gaging future benefits and trade-offs, but also for recognizing a community’s affective response to the outcomes of those decisions. This paper describes a forecasting approach based on concepts introduced in the development of the U.S. Environmental Protection Agency’s (US EPA) Human Well-Being Index (HWBI) (Smith, et. al. 2014; Summers et al. 2014). The approach examines the relationships among selected economic, environmental and social services that can be directly impacted by community decisions and eight domains of human well-being. Using models developed from constructed- or fixed-effect step-wise and multiple regressions and eleven years of data (2000-2010), these relationship functions may be used to characterize likely direct impacts of decisions on future well-being as well as the possible intended and unintended secondary and tertiary effects relative to any main decision effects. This paper describes an approach to using HWBI in decision making models to characterize likely impacts of decisions on fut
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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 decentralized control laws for engineering applications from mobile sensor networks for environmental monitoring to collective construction robots. With this dissertation we hope to provide additional methodology and mathematical models for understanding the behavior and control of collective decision-making in multi-agent systems.
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Software Tools For Building Decision-support Models For Flood Emergency Situations
NASA Astrophysics Data System (ADS)
Garrote, L.; Molina, M.; Ruiz, J. M.; Mosquera, J. C.
The SAIDA decision-support system was developed by the Spanish Ministry of the Environment to provide assistance to decision-makers during flood situations. SAIDA has been tentatively implemented in two test basins: Jucar and Guadalhorce, and the Ministry is currently planning to have it implemented in all major Spanish basins in a few years' time. During the development cycle of SAIDA, the need for providing as- sistance to end-users in model definition and calibration was clearly identified. System developers usually emphasise abstraction and generality with the goal of providing a versatile software environment. End users, on the other hand, require concretion and specificity to adapt the general model to their local basins. As decision-support models become more complex, the gap between model developers and users gets wider: Who takes care of model definition, calibration and validation?. Initially, model developers perform these tasks, but the scope is usually limited to a few small test basins. Before the model enters operational stage, end users must get involved in model construction and calibration, in order to gain confidence in the model recommendations. However, getting the users involved in these activities is a difficult task. The goal of this re- search is to develop representation techniques for simulation and management models in order to define, develop and validate a mechanism, supported by a software envi- ronment, oriented to provide assistance to the end-user in building decision models for the prediction and management of river floods in real time. The system is based on three main building blocks: A library of simulators of the physical system, an editor to assist the user in building simulation models, and a machine learning method to calibrate decision models based on the simulation models provided by the user.
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Lee, Saro; Park, Inhye
2013-09-30
Subsidence of ground caused by underground mines poses hazards to human life and property. This study analyzed the hazard to ground subsidence using factors that can affect ground subsidence and a decision tree approach in a geographic information system (GIS). The study area was Taebaek, Gangwon-do, Korea, where many abandoned underground coal mines exist. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 50/50 for training and validation of the models. A data-mining classification technique was applied to the GSH mapping, and decision trees were constructed using the chi-squared automatic interaction detector (CHAID) and the quick, unbiased, and efficient statistical tree (QUEST) algorithms. The frequency ratio model was also applied to the GSH mapping for comparing with probabilistic model. The resulting GSH maps were validated using area-under-the-curve (AUC) analysis with the subsidence area data that had not been used for training the model. The highest accuracy was achieved by the decision tree model using CHAID algorithm (94.01%) comparing with QUEST algorithms (90.37%) and frequency ratio model (86.70%). These accuracies are higher than previously reported results for decision tree. Decision tree methods can therefore be used efficiently for GSH analysis and might be widely used for prediction of various spatial events. Copyright © 2013. Published by Elsevier Ltd.
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The Three Gorges Project: How sustainable?
NASA Astrophysics Data System (ADS)
Kepa Brian Morgan, Te Kipa; Sardelic, Daniel N.; Waretini, Amaria F.
2012-08-01
SummaryIn 1984 the Government of China approved the decision to construct the Three Gorges Dam Project, the largest project since the Great Wall. The project had many barriers to overcome, and the decision was made at a time when sustainability was a relatively unknown concept. The decision to construct the Three Gorges Project remains contentious today, especially since Deputy Director of the Three Gorges Project Construction Committee, Wang Xiaofeng, stated that "We absolutely cannot relax our guard against ecological and environmental security problems sparked by the Three Gorges Project" (Bristow, 2007; McCabe, 2007). The question therefore was posed: how sustainable is the Three Gorges Project? Conventional approaches to sustainability assessment tend to use monetary based assessment aligned to triple bottom line thinking. That is, projects are evaluated as trade-offs between economic, environmental and social costs and benefits. The question of sustainability is considered using such a traditional Cost-Benefit Analysis approach, as undertaken in 1988 by a CIPM-Yangtze Joint Venture, and the Mauri Model Decision Making Framework (MMDMF). The Mauri Model differs from other approaches in that sustainability performance indicators are considered independently from any particular stakeholder bias. Bias is then introduced subsequently as a sensitivity analysis on the raw results obtained. The MMDMF is unique in that it is based on the Māori concept of Mauri, the binding force between the physical and the spiritual attributes of something, or the capacity to support life in the air, soil, and water. This concept of Mauri is analogous to the Chinese concept of Qi, and there are many analogous concepts in other cultures. It is the universal relevance of Mauri that allows its use to assess sustainability. This research identified that the MMDMF was a strong complement to Cost-Benefit Analysis, which is not designed as a sustainability assessment tool in itself. The MMDMF does have relevance in identifying areas of conflict, and it can support the Cost-Benefit Analysis in assessing sustainability, as a Decision Support Tool. The research concluded that, based on both models, the Three Gorges Project as understood in 1988, and incorporating more recent sustainability analysis is contributing to enhanced sustainability.
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Decision problems in management of construction projects
NASA Astrophysics Data System (ADS)
Szafranko, E.
2017-10-01
In a construction business, one must oftentimes make decisions during all stages of a building process, from planning a new construction project through its execution to the stage of using a ready structure. As a rule, the decision making process is made more complicated due to certain conditions specific for civil engineering. With such diverse decision situations, it is recommended to apply various decision making support methods. Both, literature and hands-on experience suggest several methods based on analytical and computational procedures, some less and some more complex. This article presents the methods which can be helpful in supporting decision making processes in the management of civil engineering projects. These are multi-criteria methods, such as MCE, AHP or indicator methods. Because the methods have different advantages and disadvantages, whereas decision situations have their own specific nature, a brief summary of the methods alongside some recommendations regarding their practical applications has been given at the end of the paper. The main aim of this article is to review the methods of decision support and their analysis for possible use in the construction industry.
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Decision tree methods: applications for classification and prediction.
Song, Yan-Yan; Lu, Ying
2015-04-25
Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. This method classifies a population into branch-like segments that construct an inverted tree with a root node, internal nodes, and leaf nodes. The algorithm is non-parametric and can efficiently deal with large, complicated datasets without imposing a complicated parametric structure. When the sample size is large enough, study data can be divided into training and validation datasets. Using the training dataset to build a decision tree model and a validation dataset to decide on the appropriate tree size needed to achieve the optimal final model. This paper introduces frequently used algorithms used to develop decision trees (including CART, C4.5, CHAID, and QUEST) and describes the SPSS and SAS programs that can be used to visualize tree structure.
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Automating hypertext for decision support
NASA Technical Reports Server (NTRS)
Bieber, Michael
1990-01-01
A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.
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Modelling uncertainty with generalized credal sets: application to conjunction and decision
NASA Astrophysics Data System (ADS)
Bronevich, Andrey G.; Rozenberg, Igor N.
2018-01-01
To model conflict, non-specificity and contradiction in information, upper and lower generalized credal sets are introduced. Any upper generalized credal set is a convex subset of plausibility measures interpreted as lower probabilities whose bodies of evidence consist of singletons and a certain event. Analogously, contradiction is modelled in the theory of evidence by a belief function that is greater than zero at empty set. Based on generalized credal sets, we extend the conjunctive rule for contradictory sources of information, introduce constructions like natural extension in the theory of imprecise probabilities and show that the model of generalized credal sets coincides with the model of imprecise probabilities if the profile of a generalized credal set consists of probability measures. We give ways how the introduced model can be applied to decision problems.
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Interpersonal Administration: Overcoming the Pygmalion Effect.
ERIC Educational Resources Information Center
Brown, Alan F.
1982-01-01
Researchers used a cognitive-reflective-interactive model for administrator development to help school administrators recognize their own personal constructs (implicit assumptions that affect decision-making). This recognition brings a clarification of self-understanding which, in conjunction with reflection and interaction with colleagues,…
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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 decisions. In one case, we show the set of model building decisions has a low probability to correctly support the upgrade decision. In the other case, we show evidence suggesting another set of model building decisions has a high probability to correctly support the decision. The proposed DCT framework focuses on what model users typically care about: the management decision in question. The DCT framework will often be very strict and will produce easy to interpret results enabling clear unsuitability determinations. In the past, hydrologic modelling progress has necessarily meant new models and model building methods. Continued progress in hydrologic modelling requires finding clear evidence to motivate researchers to disregard unproductive models and methods and the DCT framework is built to produce this kind of evidence. References: Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry (2009), Crash tests for a standardized evaluation of hydrological models. Hydrology and Earth System Sciences, 13, 1757-1764. Klemeš, V. (1986), Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31 (1), 13-24.
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Integrated modelling of stormwater treatment systems uptake.
Castonguay, A C; Iftekhar, M S; Urich, C; Bach, P M; Deletic, A
2018-05-24
Nature-based solutions provide a variety of benefits in growing cities, ranging from stormwater treatment to amenity provision such as aesthetics. However, the decision-making process involved in the installation of such green infrastructure is not straightforward, as much uncertainty around the location, size, costs and benefits impedes systematic decision-making. We developed a model to simulate decision rules used by local municipalities to install nature-based stormwater treatment systems, namely constructed wetlands, ponds/basins and raingardens. The model was used to test twenty-four scenarios of policy-making, by combining four asset selection, two location selection and three budget constraint decision rules. Based on the case study of a local municipality in Metropolitan Melbourne, Australia, the modelled uptake of stormwater treatment systems was compared with attributes of real-world systems for the simulation period. Results show that the actual budgeted funding is not reliable to predict systems' uptake and that policy-makers are more likely to plan expenditures based on installation costs. The model was able to replicate the cumulative treatment capacity and the location of systems. As such, it offers a novel approach to investigate the impact of using different decision rules to provide environmental services considering biophysical and economic factors. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Tsoi, B; O'Reilly, D; Jegathisawaran, J; Tarride, J-E; Blackhouse, G; Goeree, R
2015-06-17
In constructing or appraising a health economic model, an early consideration is whether the modelling approach selected is appropriate for the given decision problem. Frameworks and taxonomies that distinguish between modelling approaches can help make this decision more systematic and this study aims to identify and compare the decision frameworks proposed to date on this topic area. A systematic review was conducted to identify frameworks from peer-reviewed and grey literature sources. The following databases were searched: OVID Medline and EMBASE; Wiley's Cochrane Library and Health Economic Evaluation Database; PubMed; and ProQuest. Eight decision frameworks were identified, each focused on a different set of modelling approaches and employing a different collection of selection criterion. The selection criteria can be categorized as either: (i) structural features (i.e. technical elements that are factual in nature) or (ii) practical considerations (i.e. context-dependent attributes). The most commonly mentioned structural features were population resolution (i.e. aggregate vs. individual) and interactivity (i.e. static vs. dynamic). Furthermore, understanding the needs of the end-users and stakeholders was frequently incorporated as a criterion within these frameworks. There is presently no universally-accepted framework for selecting an economic modelling approach. Rather, each highlights different criteria that may be of importance when determining whether a modelling approach is appropriate. Further discussion is thus necessary as the modelling approach selected will impact the validity of the underlying economic model and have downstream implications on its efficiency, transparency and relevance to decision-makers.
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End-of-life decision making is more than rational.
Eliott, Jaklin A; Olver, Ian N
2005-01-01
Most medical models of end-of-life decision making by patients assume a rational autonomous adult obtaining and deliberating over information to arrive at some conclusion. If the patient is deemed incapable of this, family members are often nominated as substitutes, with assumptions that the family are united and rational. These are problematic assumptions. We interviewed 23 outpatients with cancer about the decision not to resuscitate a patient following cardiopulmonary arrest and examined their accounts of decision making using discourse analytical techniques. Our analysis suggests that participants access two different interpretative repertoires regarding the construct of persons, invoking a 'modernist' repertoire to assert the appropriateness of someone, a patient or family, making a decision, and a 'romanticist' repertoire when identifying either a patient or family as ineligible to make the decision. In determining the appropriateness of an individual to make decisions, participants informally apply 'Sanity' and 'Stability' tests, assessing both an inherent ability to reason (modernist repertoire) and the presence of emotion (romanticist repertoire) which might impact on the decision making process. Failure to pass the tests respectively excludes or excuses individuals from decision making. The absence of the romanticist repertoire in dominant models of patient decision making has ethical implications for policy makers and medical practitioners dealing with dying patients and their families.
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A nonlinear bi-level programming approach for product portfolio management.
Ma, Shuang
2016-01-01
Product portfolio management (PPM) is a critical decision-making for companies across various industries in today's competitive environment. Traditional studies on PPM problem have been motivated toward engineering feasibilities and marketing which relatively pay less attention to other competitors' actions and the competitive relations, especially in mathematical optimization domain. The key challenge lies in that how to construct a mathematical optimization model to describe this Stackelberg game-based leader-follower PPM problem and the competitive relations between them. The primary work of this paper is the representation of a decision framework and the optimization model to leverage the PPM problem of leader and follower. A nonlinear, integer bi-level programming model is developed based on the decision framework. Furthermore, a bi-level nested genetic algorithm is put forward to solve this nonlinear bi-level programming model for leader-follower PPM problem. A case study of notebook computer product portfolio optimization is reported. Results and analyses reveal that the leader-follower bi-level optimization model is robust and can empower product portfolio optimization.
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ERIC Educational Resources Information Center
Lee, Scott Weng Fai
2013-01-01
The assessment of young children's thinking competence in task performances has typically followed the novice-to-expert regimen involving models of strategies that adults use when engaged in cognitive tasks such as problem-solving and decision-making. Socio-constructivists argue for a balanced pedagogical approach between the adult and child that…
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ERIC Educational Resources Information Center
Rhatigan, Deborah L.; Street, Amy E.
2005-01-01
This study explored the impact of violence exposure on investment-model constructs within a sample of college women involved in heterosexual dating relationships. Results generally supported the "common sense" hypothesis, suggesting that violence negatively impacts satisfaction for and commitment to one's relationship and is positively associated…
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Kiviniemi, Marc T.; Bennett, Alyssa; Zaiter, Marie; Marshall, James R.
2010-01-01
Compliance with colorectal cancer screening recommendations requires considerable conscious effort on the part of the individual patient, making an individual's decisions about engagement in screening an important contributor to compliance or noncompliance. The objective of this paper was to examine the effectiveness of individual-level behavior theories and their associated constructs in accounting for engagement in colorectal cancer screening behavior. We reviewed the literature examining constructs from formal models of individual-level health behavior as factors associated with compliance with screening for colorectal cancer. All published studies examining one or more constructs from the health belief model, theory of planned behavior, transtheoretical model, or social cognitive theory and their relation to screening behavior or behavioral intentions were included in the analysis. By and large, results of studies supported the theory-based predictions for the influence of constructs on cancer screening behavior. However, the evidence base for many of these relations, especially for models other than the health belief model, is quite limited. Suggestions are made for future research on individual-level determinants of colorectal cancer screening. PMID:21954045
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Chew, Keng Sheng; Kueh, Yee Cheng; Abdul Aziz, Adlihafizi
2017-03-21
Despite their importance on diagnostic accuracy, there is a paucity of literature on questionnaire tools to assess clinicians' awareness toward cognitive errors. A validation study was conducted to develop a questionnaire tool to evaluate the Clinician's Awareness Towards Cognitive Errors (CATChES) in clinical decision making. This questionnaire is divided into two parts. Part A is to evaluate the clinicians' awareness towards cognitive errors in clinical decision making while Part B is to evaluate their perception towards specific cognitive errors. Content validation for both parts was first determined followed by construct validation for Part A. Construct validation for Part B was not determined as the responses were set in a dichotomous format. For content validation, all items in both Part A and Part B were rated as "excellent" in terms of their relevance in clinical settings. For construct validation using exploratory factor analysis (EFA) for Part A, a two-factor model with total variance extraction of 60% was determined. Two items were deleted. Then, the EFA was repeated showing that all factor loadings are above the cut-off value of >0.5. The Cronbach's alpha for both factors are above 0.6. The CATChES questionnaire tool is a valid questionnaire tool aimed to evaluate the awareness among clinicians toward cognitive errors in clinical decision making.
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Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.
2015-01-01
The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318
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ERIC Educational Resources Information Center
Argon, Joe, Ed.; Spoor, Dana L.; Cox, Susan M.; Brown, Andrew; Ray, Jennifer
1998-01-01
Presents a series of articles that examine decision making in school construction and renovation projects. Topics include preparing for a construction project, purchasing windows that provide protection at a reasonable cost, choosing the best flooring and carpeting, and dealing with deregulation. An industry roundtable discussion on project…
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2009-03-01
making process (Skinner, 2001, 9). According to Clemen , before we can begin to apply any methodology to a specific decision problem, the analyst...it is possible to work with them to determine the values and objectives that relate to the decision in question ( Clemen , 2001, 21). Clemen ...value hierarchy is constructed, Clemen and Reilly suggest that a trade off is made between varying objectives. They introduce weights to determine
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Space market model space industry input-output model
NASA Technical Reports Server (NTRS)
Hodgin, Robert F.; Marchesini, Roberto
1987-01-01
The goal of the Space Market Model (SMM) is to develop an information resource for the space industry. The SMM is intended to contain information appropriate for decision making in the space industry. The objectives of the SMM are to: (1) assemble information related to the development of the space business; (2) construct an adequate description of the emerging space market; (3) disseminate the information on the space market to forecasts and planners in government agencies and private corporations; and (4) provide timely analyses and forecasts of critical elements of the space market. An Input-Output model of market activity is proposed which are capable of transforming raw data into useful information for decision makers and policy makers dealing with the space sector.
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Design and application of a CA-BDI model to determine farmers' land-use behavior.
Liang, Xiaoying; Chen, Hai; Wang, Yanni; Song, Shixiong
2016-01-01
The belief-desire-intention (BDI) model has been widely used to construct reasoning systems for complex tasks in dynamic environments. We have designed a capabilities and abilities (CA)-BDI farmer decision-making model, which is an extension of the BDI architecture and includes internal representations for farmer household Capabilities and Abilities. This model is used to explore farmer learning mechanisms and to simulate the bounded rational decisions made by farmer households. Our case study focuses on the Gaoqu Commune of Mizhi County, Shaanxi Province, China, where scallion is one of the main cash crops. After comparing the differences between actual land-use changes from 2007 to 2009 and the simulation results, we analyze the validity of the model and discuss the potential and limitations of the farmer land-use decision-making model under three scenarios. Based on the design and implementation of the model, the following conclusions can be drawn: (1) the CA-BDI framework is an appropriate model for exploring learning mechanisms and simulating bounded rational decisions; and (2) local governments should encourage scallion planting by assisting scallion farmer cooperatives and farmers to understand the market risk, standardize the rules of their cooperation, and supervise the contracts made between scallion cooperatives and farmers.
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DOT National Transportation Integrated Search
2010-09-01
Tools are proposed for carbon footprint estimation of transportation construction projects and decision support : for construction firms that must make equipment choice and usage decisions that affect profits, project duration : and greenhouse gas em...
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Goo, Yeong-Jia James; Shen, Zone-De
2014-01-01
As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%. PMID:25302338
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Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De
2014-01-01
As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.
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DOT National Transportation Integrated Search
2009-04-01
"The primary umbrella method used by the Oregon Department of Transportation (ODOT) to ensure on-time performance in standard construction contracting is liquidated damages. The assessment value is usually a matter of some judgment. In practice...
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Virtual Beach version 2.2 (VB 2.2) is a decision support tool. It is designed to construct site-specific Multi-Linear Regression (MLR) models to predict pathogen indicator levels (or fecal indicator bacteria, FIB) at recreational beaches. MLR analysis has outperformed persisten...
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Development of Interpretable Predictive Models for BPH and Prostate Cancer.
Bermejo, Pablo; Vivo, Alicia; Tárraga, Pedro J; Rodríguez-Montes, J A
2015-01-01
Traditional methods for deciding whether to recommend a patient for a prostate biopsy are based on cut-off levels of stand-alone markers such as prostate-specific antigen (PSA) or any of its derivatives. However, in the last decade we have seen the increasing use of predictive models that combine, in a non-linear manner, several predictives that are better able to predict prostate cancer (PC), but these fail to help the clinician to distinguish between PC and benign prostate hyperplasia (BPH) patients. We construct two new models that are capable of predicting both PC and BPH. An observational study was performed on 150 patients with PSA ≥3 ng/mL and age >50 years. We built a decision tree and a logistic regression model, validated with the leave-one-out methodology, in order to predict PC or BPH, or reject both. Statistical dependence with PC and BPH was found for prostate volume (P-value < 0.001), PSA (P-value < 0.001), international prostate symptom score (IPSS; P-value < 0.001), digital rectal examination (DRE; P-value < 0.001), age (P-value < 0.002), antecedents (P-value < 0.006), and meat consumption (P-value < 0.08). The two predictive models that were constructed selected a subset of these, namely, volume, PSA, DRE, and IPSS, obtaining an area under the ROC curve (AUC) between 72% and 80% for both PC and BPH prediction. PSA and volume together help to build predictive models that accurately distinguish among PC, BPH, and patients without any of these pathologies. Our decision tree and logistic regression models outperform the AUC obtained in the compared studies. Using these models as decision support, the number of unnecessary biopsies might be significantly reduced.
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The influences and neural correlates of past and present during gambling in humans.
Sacré, Pierre; Subramanian, Sandya; Kerr, Matthew S D; Kahn, Kevin; Johnson, Matthew A; Bulacio, Juan; González-Martínez, Jorge A; Sarma, Sridevi V; Gale, John T
2017-12-07
During financial decision-making tasks, humans often make "rational" decisions, where they maximize expected reward. However, this rationality may compete with a bias that reflects past outcomes. That is, if one just lost money or won money, this may impact future decisions. It is unclear how past outcomes influence future decisions in humans, and how neural circuits encode present and past information. In this study, six human subjects performed a financial decision-making task while we recorded local field potentials from multiple brain structures. We constructed a model for each subject characterizing bets on each trial as a function of present and past information. The models suggest that some patients are more influenced by previous trial outcomes (i.e., previous return and risk) than others who stick to more fixed decision strategies. In addition, past return and present risk modulated with the activity in the cuneus; while present return and past risk modulated with the activity in the superior temporal gyrus and the angular gyrus, respectively. Our findings suggest that these structures play a role in decision-making beyond their classical functions by incorporating predictions and risks in humans' decision strategy, and provide new insight into how humans link their internal biases to decisions.
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Pitcher, Brandon; Alaqla, Ali; Noujeim, Marcel; Wealleans, James A; Kotsakis, Georgios; Chrepa, Vanessa
2017-03-01
Cone-beam computed tomographic (CBCT) analysis allows for 3-dimensional assessment of periradicular lesions and may facilitate preoperative periapical cyst screening. The purpose of this study was to develop and assess the predictive validity of a cyst screening method based on CBCT volumetric analysis alone or combined with designated radiologic criteria. Three independent examiners evaluated 118 presurgical CBCT scans from cases that underwent apicoectomies and had an accompanying gold standard histopathological diagnosis of either a cyst or granuloma. Lesion volume, density, and specific radiologic characteristics were assessed using specialized software. Logistic regression models with histopathological diagnosis as the dependent variable were constructed for cyst prediction, and receiver operating characteristic curves were used to assess the predictive validity of the models. A conditional inference binary decision tree based on a recursive partitioning algorithm was constructed to facilitate preoperative screening. Interobserver agreement was excellent for volume and density, but it varied from poor to good for the radiologic criteria. Volume and root displacement were strong predictors for cyst screening in all analyses. The binary decision tree classifier determined that if the volume of the lesion was >247 mm 3 , there was 80% probability of a cyst. If volume was <247 mm 3 and root displacement was present, cyst probability was 60% (78% accuracy). The good accuracy and high specificity of the decision tree classifier renders it a useful preoperative cyst screening tool that can aid in clinical decision making but not a substitute for definitive histopathological diagnosis after biopsy. Confirmatory studies are required to validate the present findings. Published by Elsevier Inc.
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NASA Astrophysics Data System (ADS)
Yaakob, Mazri; Ali, Wan Nur Athirah Wan; Radzuan, Kamaruddin
2016-08-01
Building Information Modeling (BIM) is defined as existing from the earliest concept to demolition and it involves creating and using an intelligent 3D model to inform and communicate project decisions. This research aims to identify the critical success factors (CSFs) of BIM implementation in Malaysian construction industry. A literature review was done to explore previous BIM studies on definitions and history of BIM, construction issues, application of BIM in construction projects as well as benefits of BIM. A series of interviews with multidisciplinary Malaysian construction experts will be conducted purposely for data collection process guided by the research design and methodology approach of this study. The analysis of qualitative data from the process will be combined with criteria identified in the literature review in order to identify the CSFs. Finally, the CSFs of BIM implementation will be validated by further Malaysian industrialists during a workshop. The validated CSFs can be used as a term of reference for both Malaysian practitioners and academics towards measuring BIM effectiveness level in their organizations.
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NASA Astrophysics Data System (ADS)
Bagarello, F.; Haven, E.
2016-02-01
We discuss a non linear extension of a model of alliances in politics, recently proposed by one of us. The model is constructed in terms of operators, describing the interest of three parties to form, or not, some political alliance with the other parties. The time evolution of what we call the decision functions is deduced by introducing a suitable Hamiltonian, which describes the main effects of the interactions of the parties amongst themselves and with their environments, which are generated by their electors and by people who still have no clear idea for which party to vote (or even if to vote). The Hamiltonian contains some non-linear effects, which takes into account the role of a party in the decision process of the other two parties. Moreover, we show how the same Hamiltonian can also be used to construct a formal structure which can describe the dynamics of buying and selling financial assets (without however implying a specific price setting mechanism).
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2003-04-01
34action orientetion ". T^ks concerned pre-flight safety assessments for military combat aircraft and were performed 1^ Army Cobra aviators. Dependent...evaluations are vital during future assessments of team performance and especially for modeling purposes, as the literature lacks empirical...a similar scale, and then assign probabilities to likelihood’s for these in the future . Once completed, one can multiply expected feature values of
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A Decision Support System for Planning, Control and Auditing of DoD Software Cost Estimation.
1986-03-01
is frequently used in U. S. Air Force software cost estimates. Barry Boehm’s Constructive Cost Estimation Model (COCOMO) was recently selected for use...are considered basic to the proper development of software. Pressman , [Ref. 11], addresses these basic elements in a manner which attempts to integrate...H., Jr., and Carlson, Eric D., Building E fective Decision SUDDOrt Systems, Prentice-Hal, EnglewoodNJ, 1982 11. Pressman , Roger S., o A Practioner’s A
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NASA Astrophysics Data System (ADS)
Shiju, S.; Sumitra, S.
2017-12-01
In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.
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Intelligent reservoir operation system based on evolving artificial neural networks
NASA Astrophysics Data System (ADS)
Chaves, Paulo; Chang, Fi-John
2008-06-01
We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.
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NASA Astrophysics Data System (ADS)
Rains, D.; Dunipace, D.; Woo, C. K.
1981-02-01
Consumer motivations for choosing a solar energy equipped home when the nonsolar or conventional model was available were investigated. The approach was to test the relative importance of demographic, dwelling unit, and heating system characteristics in household decisions to purchase a home equipped with solar energy devices. Two statistical models were developed: one to examine the relationship between the types of home buyers (as an identifiable market segment) and the decision to purchase a solar home; and the other to compare the energy use of solar vs. conventional homes selected in the sample.
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Luebbe, Aaron M; Mancini, Kathryn J; Kiel, Elizabeth J; Spangler, Brooke R; Semlak, Julie L; Fussner, Lauren M
2016-08-24
The current study tests the underlying structure of a multidimensional construct of helicopter parenting (HP), assesses reliability of the construct, replicates past relations of HP to poor emotional functioning, and expands the literature to investigate links of HP to emerging adults' decision-making and academic functioning. A sample of 377 emerging adults (66% female; ages 17-30; 88% European American) were administered several items assessing HP as well as measures of other parenting behaviors, depression, anxiety, decision-making style, grade point average, and academic functioning. Exploratory factor analysis results suggested a four-factor, 23-item measure that encompassed varying levels of parental involvement in the personal and professional lives of their children. A bifactor model was also fit to the data and suggested the presence of a reliable overarching HP factor in addition to three reliable subfactors. The fourth subfactor was not reliable and item variances were subsumed by the general HP factor. HP was found to be distinct from, but correlated in expected ways with, other reports of parenting behavior. HP was also associated with poorer functioning in emotional functioning, decision making, and academic functioning. Parents' information-seeking behaviors, when done in absences of other HP behaviors, were associated with better decision making and academic functioning. © The Author(s) 2016.
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A structured analysis of uncertainty surrounding modeled impacts of groundwater-extraction rules
NASA Astrophysics Data System (ADS)
Guillaume, Joseph H. A.; Qureshi, M. Ejaz; Jakeman, Anthony J.
2012-08-01
Integrating economic and groundwater models for groundwater-management can help improve understanding of trade-offs involved between conflicting socioeconomic and biophysical objectives. However, there is significant uncertainty in most strategic decision-making situations, including in the models constructed to represent them. If not addressed, this uncertainty may be used to challenge the legitimacy of the models and decisions made using them. In this context, a preliminary uncertainty analysis was conducted of a dynamic coupled economic-groundwater model aimed at assessing groundwater extraction rules. The analysis demonstrates how a variety of uncertainties in such a model can be addressed. A number of methods are used including propagation of scenarios and bounds on parameters, multiple models, block bootstrap time-series sampling and robust linear regression for model calibration. These methods are described within the context of a theoretical uncertainty management framework, using a set of fundamental uncertainty management tasks and an uncertainty typology.
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Application of the Consumer Decision-Making Model to Hearing Aid Adoption in First-Time Users
Amlani, Amyn M.
2016-01-01
Since 1980, hearing aid adoption rates have remained essentially the same, increasing at a rate equal to the organic growth of the population. Researchers have used theoretical models from psychology and sociology to determine those factors or constructs that lead to the adoption of hearing aids by first-time impaired listeners entering the market. In this article, a theoretical model, the Consumer Decision-Making Model (CDM), premised on the neobehavioral approach that considers an individual's psychological and cognitive emphasis toward a product or service, is described. Three theoretical models (i.e., transtheoretical, social model of disability, Health Belief Model), and their relevant findings to the hearing aid market, are initially described. The CDM is then presented, along with supporting evidence of the model's various factors from the hearing aid literature. Future applications of the CDM to hearing health care also are discussed. PMID:27516718
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Application of the Consumer Decision-Making Model to Hearing Aid Adoption in First-Time Users.
Amlani, Amyn M
2016-05-01
Since 1980, hearing aid adoption rates have remained essentially the same, increasing at a rate equal to the organic growth of the population. Researchers have used theoretical models from psychology and sociology to determine those factors or constructs that lead to the adoption of hearing aids by first-time impaired listeners entering the market. In this article, a theoretical model, the Consumer Decision-Making Model (CDM), premised on the neobehavioral approach that considers an individual's psychological and cognitive emphasis toward a product or service, is described. Three theoretical models (i.e., transtheoretical, social model of disability, Health Belief Model), and their relevant findings to the hearing aid market, are initially described. The CDM is then presented, along with supporting evidence of the model's various factors from the hearing aid literature. Future applications of the CDM to hearing health care also are discussed.
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NASA Astrophysics Data System (ADS)
Leskens, Johannes
2015-04-01
In modern water management, often transdisciplinary work sessions are organized in which various stakeholders participate to jointly define problems, choose measures and divide responsibilities to take actions. Involved stakeholders are for example policy analysts or decision-makers from municipalities, water boards or provinces, representatives of pressure groups and researchers from knowledge institutes. Parallel to this increasing attention for transdisciplinary work sessions, we see a growing availability of interactive IT-tools that can be applied during these sessions. For example, dynamic flood risk maps have become recently available that allow users during a work sessions to instantaneously assess the impact of storm surges or dam breaches, displayed on digital maps. Other examples are serious games, realistic visualizations and participatory simulations. However, the question is if and how these interactive IT-tools contribute to better decision-making. To assess this, we take the process of knowledge construction during a work session as a measure for the quality of decision-making. Knowledge construction can be defined as the process in which ideas, perspectives and opinions of different stakeholders, all having their own expertise and experience, are confronted with each other and new shared meanings towards water management issues are created. We present an assessment method to monitor the process of knowledge construction during work sessions in water management in which interactive IT tools are being used. The assessment method is based on a literature review, focusing on studies in which knowledge construction was monitored in other contexts that water management. To test the applicability of the assessment method, we applied it during a multi-stakeholder work session in Westland, located in the southwest of the Netherlands. The discussions during the work session were observed by camera. All statements, expressed by the various members of a stakeholder session, were classified according to our assessment method. We can draw the following preliminary conclusions. First, the case study showed that the method was useful to show the knowledge construction process over time, in terms of content and cognitive level of statements and interaction, attention and response between stakeholders. It was observed that the various aspects of knowledge construction all were influenced by the use of the 3Di model. The model focused discussions on technical issues of flood risk management, non-flood specialists were able to participate in discussions and in suggesting solutions and more topics could be evaluated in respect to non-interactive flood maps. Second, the method is considered useful as a benchmark for different interactive IT tools. The method is also considered useful to gain insight in how to optimally set-up multi-stakeholder meetings in which interactive IT-tools are being used. Further, the method can provide model developers insight in how to better meet the technical requirements of interactive IT tools to support the knowledge construction process during multi-stakeholder meeting
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Real-life decision making in college students. II: Do individual differences show reliable effects?
Galotti, Kathleen M; Tandler, Jane M; Wiener, Hillary J D
2014-01-01
First-year undergraduates participated in a short-term longitudinal study of real-life decision making over their first 14 months of college. They were surveyed about 7 different decisions: choosing courses for upcoming terms (on 3 different occasions), choosing an academic major (twice), planning for the upcoming summer, and planning for sophomore-year housing. They also completed a survey of self-reported decision-making styles and the Need for Cognition survey (Cacioppo & Petty, 1982) to assess their focus on rationality and enjoyment of analytic thinking. Results showed few statistically significant correlations between stylistic measures and behavioral measures of decision making, in either the amount of information considered or the way in which the information integration tracked predictions of linear models of decision making applied to each participant's data. However, there were consistent correlations, across the 7 decisions, between stylistic measures and affective reactions to, or retrospective descriptions of, episodes of decision making. We suggest that decision-making styles instruments may better reflect the construction of narratives of self as a decision maker more than they do actual behavior during decision making.
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Adversarial reasoning and resource allocation: the LG approach
NASA Astrophysics Data System (ADS)
Stilman, Boris; Yakhnis, Vladimir; Umanskiy, Oleg; Boyd, Ron
2005-05-01
Many existing automated tools purporting to model the intelligent enemy utilize a fixed battle plan for the enemy while using flexible decisions of human players for the friendly side. According to the Naval Studies Board, "It is an open secret and a point of distress ... that too much of the substantive content of such M&S has its origin in anecdote, ..., or a narrow construction tied to stereotypical current practices of 'doctrinally correct behavior.'" Clearly, such runs lack objectivity by being heavily skewed in favor of the friendly forces. Presently, the military branches employ a variety of game-based simulators and synthetic environments, with manual (i.e., user-based) decision-making, for training and other purposes. However, without an ability to automatically generate the best strategies, tactics, and COA, the games serve mostly to display the current situation rather than form a basis for automated decision-making and effective training. We solve the problem of adversarial reasoning as a gaming problem employing Linguistic Geometry (LG), a new type of game theory demonstrating significant increase in size in gaming problems solvable in real and near-real time. It appears to be a viable approach for solving such practical problems as mission planning and battle management. Essentially, LG may be structured into two layers: game construction and game solving. Game construction includes construction of a game called an LG hypergame based on a hierarchy of Abstract Board Games (ABG). Game solving includes resource allocation for constructing an advantageous initial game state and strategy generation to reach a desirable final game state in the course of the game.
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Decisions with Uncertain Consequences—A Total Ordering on Loss-Distributions
König, Sandra; Schauer, Stefan
2016-01-01
Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action can be modeled by a random variable, then the decision problem boils down to comparing different effects (random variables) by comparing their distribution functions. Although the full space of probability distributions cannot be ordered, a properly restricted subset of distributions can be totally ordered in a practically meaningful way. We call these loss-distributions, since they provide a substitute for the concept of loss-functions in decision theory. This article introduces the theory behind the necessary restrictions and the hereby constructible total ordering on random loss variables, which enables decisions under uncertainty of consequences. Using data obtained from simulations, we demonstrate the practical applicability of our approach. PMID:28030572
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NASA Technical Reports Server (NTRS)
2002-01-01
Ames Research Center granted Reality Capture Technologies (RCT), Inc., a license to further develop NASA's Mars Map software platform. The company incorporated NASA#s innovation into software that uses the Virtual Plant Model (VPM)(TM) to structure, modify, and implement the construction sites of industrial facilities, as well as develop, validate, and train operators on procedures. The VPM orchestrates the exchange of information between engineering, production, and business transaction systems. This enables users to simulate, control, and optimize work processes while increasing the reliability of critical business decisions. Engineers can complete the construction process and test various aspects of it in virtual reality before building the actual structure. With virtual access to and simulation of the construction site, project personnel can manage, access control, and respond to changes on complex constructions more effectively. Engineers can also create operating procedures, training, and documentation. Virtual Plant Model(TM) is a trademark of Reality Capture Technologies, Inc.
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George, William H.; Davis, Kelly Cue; Masters, N. Tatiana; Kajumulo, Kelly F.; Stappenbeck, Cynthia A.; Norris, Jeanette; Heiman, Julia R.; Staples, Jennifer M.
2015-01-01
Highly intoxicated versus sober women were evaluated using multi-group path analyses to test the hypothesis that sexual victimization history would interact with partner pressure to forgo condom use, resulting in greater condom-decision abdication – letting the man decide whether or not to use a condom. After beverage administration, community women (n=408) projected themselves into a scenario depicting a male partner exerting high or low pressure for unprotected sex. Mood, anticipated negative reactions from the partner, and condom-decision abdication were assessed. In both control and alcohol models, high pressure increased anticipated negative partner reaction, and positive mood was associated with increased abdication. In the alcohol model, victimization predicted abdication via anticipated negative partner reaction, and pressure decreased positive mood and abdication. In the control model, under high pressure, victimization history severity was positively associated with abdication. Findings implicate condom-decision abdication as an important construct in understanding how women’s sexual victimization histories may exert sustained impact on sexual interactions. PMID:26340952
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Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid
2018-05-12
Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.
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Qi, Xiao-Wen; Zhang, Jun-Ling; Zhao, Shu-Ping; Liang, Chang-Yong
2017-10-02
In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager's prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches.
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Qi, Xiao-Wen; Zhang, Jun-Ling; Zhao, Shu-Ping; Liang, Chang-Yong
2017-01-01
In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager’s prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches. PMID:28974045
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Minimizing Project Cost by Integrating Subcontractor Selection Decisions with Scheduling
NASA Astrophysics Data System (ADS)
Biruk, Sławomir; Jaśkowski, Piotr; Czarnigowska, Agata
2017-10-01
Subcontracting has been a worldwide practice in the construction industry. It enables the construction enterprises to focus on their core competences and, at the same time, it makes complex project possible to be delivered. Since general contractors bear full responsibility for the works carried out by their subcontractors, it is their task and their risk to select a right subcontractor for a particular work. Although subcontractor management has been admitted to significantly affect the construction project’s performance, current practices and past research deal with subcontractor management and scheduling separately. The proposed model aims to support subcontracting decisions by integrating subcontractor selection with scheduling to enable the general contractor to select the optimal combination of subcontractors and own crews for all work packages of the project. The model allows for the interactions between the subcontractors and their impacts on the overall project performance in terms of cost and, indirectly, time and quality. The model is intended to be used at the general contractor’s bid preparation stage. The authors claim that the subcontracting decisions should be taken in a two-stage process. The first stage is a prequalification - provision of a short list of capable and reliable subcontractors; this stage is not the focus of the paper. The resulting pool of available resources is divided into two subsets: subcontractors, and general contractor’s in-house crews. Once it has been defined, the next stage is to assign them to the work packages that, bound by fixed precedence constraints, form the project’s network diagram. Each package is possible to be delivered by the general contractor’s crew or some of the potential subcontractors, at a specific time and cost. Particular crews and subcontractors can be contracted more than one package, but not at the same time. Other constraints include the predefined project completion date (the project is not allowed to take longer) and maximum total value of subcontracted work. The problem is modelled as a mixed binary linear program that minimizes project cost. It can be solved using universal solvers (e.g. LINGO, AIMMS, CPLEX, MATLAB and Optimization Toolbox, etc.). However, developing a dedicated decision-support tool would facilitate practical applications. To illustrate the idea of the model, the authors present a numerical example to find the optimal set of resources allocated to a project.
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Information and knowledge management for sustainable forestry
Alan J. Thomson; Michael Rauscher; Daniel L. Schmoldt; Harald Vacik
2007-01-01
Institutional information and knowledge management often involves a range of systems and technologies to aid decisions and produce reports. Construction of a knowledge system organizing hierarchy facilitates exploration of the interrelationships among knowledge management, inventory and monitoring, statistics and modeling, and policy. Two case studies illustrate these...
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DOT National Transportation Integrated Search
2009-04-01
The primary umbrella method used by the Oregon Department of Transportation (ODOT) to ensure on-time performance in standard construction contracting is liquidated damages. The assessment value is usually a matter of some judgment. In practice,...
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Blalock, Susan J.; Reyna, Valerie F.
2016-01-01
Objective Fuzzy-trace theory is a dual-process model of memory, reasoning, judgment, and decision making that contrasts with traditional expectancy-value approaches. We review the literature applying fuzzy-trace theory to health with three aims: evaluating whether the theory’s basic distinctions have been validated empirically in the domain of health; determining whether these distinctions are useful in assessing, explaining, and predicting health-related psychological processes; and determining whether the theory can be used to improve health judgments, decisions, or behaviors, especially in comparison to other approaches. Methods We conducted a literature review using PubMed, PsycInfo, and Web of Science to identify empirical peer-reviewed papers that applied fuzzy-trace theory, or central constructs of the theory, to investigate health judgments, decisions, or behaviors. Results 79 studies were identified, over half published since 2012, spanning a wide variety of conditions and populations. Study findings supported the prediction that verbatim and gist representations are distinct constructs that can be retrieved independently using different cues. Although gist-based reasoning was usually associated with improved judgment and decision making, four sources of bias that can impair gist reasoning were identified. Finally, promising findings were reported from intervention studies that used fuzzy-trace theory to improve decision making and decrease unhealthy risk taking. Conclusions Despite large gaps in the literature, most studies supported all three aims. By focusing on basic psychological processes that underlie judgment and decision making, fuzzy-trace theory provides insights into how individuals make decisions involving health risks and suggests innovative intervention approaches to improve health outcomes. PMID:27505197
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Monte Carlo decision curve analysis using aggregate data.
Hozo, Iztok; Tsalatsanis, Athanasios; Djulbegovic, Benjamin
2017-02-01
Decision curve analysis (DCA) is an increasingly used method for evaluating diagnostic tests and predictive models, but its application requires individual patient data. The Monte Carlo (MC) method can be used to simulate probabilities and outcomes of individual patients and offers an attractive option for application of DCA. We constructed a MC decision model to simulate individual probabilities of outcomes of interest. These probabilities were contrasted against the threshold probability at which a decision-maker is indifferent between key management strategies: treat all, treat none or use predictive model to guide treatment. We compared the results of DCA with MC simulated data against the results of DCA based on actual individual patient data for three decision models published in the literature: (i) statins for primary prevention of cardiovascular disease, (ii) hospice referral for terminally ill patients and (iii) prostate cancer surgery. The results of MC DCA and patient data DCA were identical. To the extent that patient data DCA were used to inform decisions about statin use, referral to hospice or prostate surgery, the results indicate that MC DCA could have also been used. As long as the aggregate parameters on distribution of the probability of outcomes and treatment effects are accurately described in the published reports, the MC DCA will generate indistinguishable results from individual patient data DCA. We provide a simple, easy-to-use model, which can facilitate wider use of DCA and better evaluation of diagnostic tests and predictive models that rely only on aggregate data reported in the literature. © 2017 Stichting European Society for Clinical Investigation Journal Foundation.
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Vallée-Tourangeau, Gaëlle; Promberger, Marianne; Moon, Karis; Wheelock, Ana; Sirota, Miroslav; Norton, Christine; Sevdalis, Nick
2017-09-25
Healthcare workers (HCWs) are an important priority group for vaccination against influenza, yet, flu vaccine uptake remains low among them. Psychosocial studies of HCWs' decisions to get vaccinated have commonly drawn on subjective expected utility models to assess predictors of vaccination, assuming HCWs' choices result from a rational information-weighing process. By contrast, we recast those decisions asa commitment to vaccination and we aimed to understand why HCWs may want to (rather than believe they need to) get vaccinated against the flu. This article outlines the development and validation of a 9-item measure of cognitive empowerment towards flu vaccination (MoVac-flu scale) and an 11-item measure of cognitive empowerment towards vaccination advocacy. Both scales were administered to 784 frontline NHS HCWs with direct patient contact between June 2014 and July 2015. The scales exhibited excellent reliability and a clear unidimensional factor structure. An examination of the nomological network of the cognitive empowerment construct in relation to HCWs' vaccination against the flu revealed that this construct was distinct from traditional measures of risk perception and the strongest predictor of HCWs' decisions to vaccinate. Similarly, cognitive empowerment in relation to vaccination advocacy was a strong predictor of HCWs' engagement with vaccination advocacy. These findings suggest that the cognitive empowerment construct has important implications for advancing our understanding of HCWs' decisions to vaccinate as well as their advocacy behavior. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Fischer, Sophia; Soyez, Katja; Gurtner, Sebastian
2015-05-01
Research testing the concept of decision-making styles in specific contexts such as health care-related choices is missing. Therefore, we examine the contextuality of Scott and Bruce's (1995) General Decision-Making Style Inventory with respect to patient choice situations. Scott and Bruce's scale was adapted for use as a patient decision-making style inventory. In total, 388 German patients who underwent elective joint surgery responded to a questionnaire about their provider choice. Confirmatory factor analyses within 2 independent samples assessed factorial structure, reliability, and validity of the scale. The final 4-dimensional, 13-item patient decision-making style inventory showed satisfactory psychometric properties. Data analyses supported reliability and construct validity. Besides the intuitive, dependent, and avoidant style, a new subdimension, called "comparative" decision-making style, emerged that originated from the rational dimension of the general model. This research provides evidence for the contextuality of decision-making style to specific choice situations. Using a limited set of indicators, this report proposes the patient decision-making style inventory as valid and feasible tool to assess patients' decision propensities. © The Author(s) 2015.
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Leveraging human decision making through the optimal management of centralized resources
NASA Astrophysics Data System (ADS)
Hyden, Paul; McGrath, Richard G.
2016-05-01
Combining results from mixed integer optimization, stochastic modeling and queuing theory, we will advance the interdisciplinary problem of efficiently and effectively allocating centrally managed resources. Academia currently fails to address this, as the esoteric demands of each of these large research areas limits work across traditional boundaries. The commercial space does not currently address these challenges due to the absence of a profit metric. By constructing algorithms that explicitly use inputs across boundaries, we are able to incorporate the advantages of using human decision makers. Key improvements in the underlying algorithms are made possible by aligning decision maker goals with the feedback loops introduced between the core optimization step and the modeling of the overall stochastic process of supply and demand. A key observation is that human decision-makers must be explicitly included in the analysis for these approaches to be ultimately successful. Transformative access gives warfighters and mission owners greater understanding of global needs and allows for relationships to guide optimal resource allocation decisions. Mastery of demand processes and optimization bottlenecks reveals long term maximum marginal utility gaps in capabilities.
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Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel
2008-01-01
With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.
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The cerebellum and decision making under uncertainty.
Blackwood, Nigel; Ffytche, Dominic; Simmons, Andrew; Bentall, Richard; Murray, Robin; Howard, Robert
2004-06-01
This study aimed to identify the neural basis of probabilistic reasoning, a type of inductive inference that aids decision making under conditions of uncertainty. Eight normal subjects performed two separate two-alternative-choice tasks (the balls in a bottle and personality survey tasks) while undergoing functional magnetic resonance imaging (fMRI). The experimental conditions within each task were chosen so that they differed only in their requirement to make a decision under conditions of uncertainty (probabilistic reasoning and frequency determination required) or under conditions of certainty (frequency determination required). The same visual stimuli and motor responses were used in the experimental conditions. We provide evidence that the neo-cerebellum, in conjunction with the premotor cortex, inferior parietal lobule and medial occipital cortex, mediates the probabilistic inferences that guide decision making under uncertainty. We hypothesise that the neo-cerebellum constructs internal working models of uncertain events in the external world, and that such probabilistic models subserve the predictive capacity central to induction. Copyright 2004 Elsevier B.V.
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Carney, Timothy Jay; Morgan, Geoffrey P.; Jones, Josette; McDaniel, Anna M.; Weaver, Michael; Weiner, Bryan; Haggstrom, David A.
2014-01-01
Our conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman’s Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability. PMID:24953241
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Individual vision and peak distribution in collective actions
NASA Astrophysics Data System (ADS)
Lu, Peng
2017-06-01
People make decisions on whether they should participate as participants or not as free riders in collective actions with heterogeneous visions. Besides of the utility heterogeneity and cost heterogeneity, this work includes and investigates the effect of vision heterogeneity by constructing a decision model, i.e. the revised peak model of participants. In this model, potential participants make decisions under the joint influence of utility, cost, and vision heterogeneities. The outcomes of simulations indicate that vision heterogeneity reduces the values of peaks, and the relative variance of peaks is stable. Under normal distributions of vision heterogeneity and other factors, the peaks of participants are normally distributed as well. Therefore, it is necessary to predict distribution traits of peaks based on distribution traits of related factors such as vision heterogeneity and so on. We predict the distribution of peaks with parameters of both mean and standard deviation, which provides the confident intervals and robust predictions of peaks. Besides, we validate the peak model of via the Yuyuan Incident, a real case in China (2014), and the model works well in explaining the dynamics and predicting the peak of real case.
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Niederhäuser, Simone K; Tepic, Slobodan; Weber, Urs T
2015-05-01
To evaluate the effect of screw position on strength and stiffness of a combination locking plate-rod construct in a synthetic feline femoral gap model. 30 synthetic long-bone models derived from beechwood and balsa wood. 3 constructs (2 locking plate-rod constructs and 1 locking plate construct; 10 specimens/construct) were tested in a diaphyseal bridge plating configuration by use of 4-point bending and torsion. Variables included screw position (near the fracture gap and far from the fracture gap) and application of an intramedullary pin. Constructs were tested to failure in each loading mode to determine strength and stiffness. Failure was defined as plastic deformation of the plate or breakage of the bone model or plate. Strength, yield angle, and stiffness were compared by use of a Wilcoxon test. Placement of screws near the fracture gap did not increase bending or torsional stiffness in the locking plate-rod constructs, assuming the plate was placed on the tension side of the bone. Addition of an intramedullary pin resulted in a significant increase in bending strength of the construct. Screw positioning did not have a significant effect on any torsion variables. Results of this study suggested that, in the investigated plate-rod construct, screw insertion adjacent to the fracture lacked mechanical advantages over screw insertion at the plate ends. For surgeons attempting to minimize soft tissue dissection, the decision to make additional incisions for screw placement should be considered with even more caution.
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2009-03-01
37 Figure 8 New Information Sharing Model from United States Intelligence Community Information Sharing...PRIDE while the Coast Guard has MISSLE and the newly constructed WATCHKEEPER. All these databases contain intelligence on incoming vessels...decisions making. Experts rely heavily on future projections as hallmarks of skilled performance." (Endsley et al. 2006) The SA model above
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NASA Astrophysics Data System (ADS)
Adeleke, Adeyinka
The construction project in the oil and gas industry covers the entire spectrum of hydrocarbon production from the wellhead (upstream) to downstream facilities. In each of these establishments, the activities in a construction project include: consulting, studies, front-end engineering, detail engineering, procurement, program management, construction, installation, commissioning and start-up. Efficient management of each of the activities involved in construction projects is one of the driving forces for the successful completion of the project. Optimizing the crucial factors in project management during each phase of a project in an oil and gas industry can assist managers to maximize the use of available resources and drive the project to successful conclusions. One of these factors is the decision-making process in the construction project. Current research effort investigated the relationship between decision-making processes and business strategy in oil and gas industry using employee surveys. I recruited employees of different races, age group, genders, and years of experience in order understand their influence on the implementation of the decision-making process in oil and gas industry through a quantitative survey. Decision-making was assessed using five decision measures: (a) rational, (b) intuitive, (c) dependent, (d) avoidant, and (e) spontaneous. The findings indicated gender, age, years of work experience and job titles as primary variables with a negative relationship with decision-making approach for employees working in a major oil and gas industry. The study results revealed that the two most likely decision-making methods in oil and gas industry include: making a decision in a logical and systematic way and seek assistance from others when making a decision. Additionally, the two leading management approaches to decision-making in the oil and gas industry include: decision analysis is part of organization culture and management is committed to the decision-making process. Some recommendations for future studies were presented based on the need to intensify the importance of the current study and enlarge the body of knowledge regarding decision-making process in oil and gas industry.
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Nanomaterials are extensively used in several industry sectors due to the improved properties they empower commercial products with. There is a pressing need to produce these materials more sustainably. This paper proposes a Multiple Criteria Decision Aiding (MCDA) approach to as...
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Student Observations: Introducing iPads into University Classrooms
ERIC Educational Resources Information Center
Wardley, Leslie J.; Mang, Colin F.
2016-01-01
This paper explores the growing trend of using mobile technology in university classrooms, exploring the use of tablets in particular, to identify learning benefits faced by students. Students, acting on their efficacy beliefs, make decisions regarding technology's influence in improving their education. We construct a theoretical model in which…
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Building Ecology & School Design. Technical Bulletin.
ERIC Educational Resources Information Center
Maryland State Dept. of Education, Baltimore.
To better understand construction's impact, an overview of building ecology as a concept and as a decision-making model for school systems is provided. "Building ecology" is defined as the interrelationships among people, the built environment, and the natural environment. It has special relevance for school design because most of the…
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Computational Models for Belief Revision, Group Decision-Making and Cultural Shifts
2010-10-25
34social" networks; the green numbers are pseudo-trees or artificial (non-social) constructions. The dashed blue line indicates the range of Erdos- Renyi ...non-social networks such as Erdos- Renyi random graphs or the more passive non-cognitive spreading of disease or information flow, As mentioned
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MATREX: A Unifying Modeling and Simulation Architecture for Live-Virtual-Constructive Applications
2007-05-23
Deployment Systems Acquisition Operations & Support B C Sustainment FRP Decision Review FOC LRIP/IOT& ECritical Design Review Pre-Systems...CMS2 – Comprehensive Munitions & Sensor Server • CSAT – C4ISR Static Analysis Tool • C4ISR – Command & Control, Communications, Computers
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Gaoua, Nadia; de Oliveira, Rita F; Hunter, Steve
2017-01-01
Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini) review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee's responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees' decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies.
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Gaoua, Nadia; de Oliveira, Rita F.; Hunter, Steve
2017-01-01
Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini) review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee’s responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees’ decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies. PMID:28912742
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Using the domain identification model to study major and career decision-making processes
NASA Astrophysics Data System (ADS)
Tendhar, Chosang; Singh, Kusum; Jones, Brett D.
2018-03-01
The purpose of this study was to examine the extent to which (1) a domain identification model could be used to predict students' engineering major and career intentions and (2) the MUSIC Model of Motivation components could be used to predict domain identification. The data for this study were collected from first-year engineering students. We used a structural equation model to test the hypothesised relationship between variables in the partial domain identification model. The findings suggested that engineering identification significantly predicted engineering major intentions and career intentions and had the highest effect on those two variables compared to other motivational constructs. Furthermore, results suggested that success, interest, and caring are plausible contributors to students' engineering identification. Overall, there is strong evidence that the domain identification model can be used as a lens to study career decision-making processes in engineering, and potentially, in other fields as well.
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Why we should talk about option generation in decision-making research
Kalis, Annemarie; Kaiser, Stefan; Mojzisch, Andreas
2013-01-01
Most empirical studies on decision-making start from a set of given options for action. However, in everyday life there is usually no one asking you to choose between A, B, and C. Recently, the question how people come up with options has been receiving growing attention. However, so far there has been neither a systematic attempt to define the construct of “option” nor an attempt to show why decision-making research really needs this construct. This paper aims to fill that void by developing definitions of “option” and “option generation” that can be used as a basis for decision-making research in a wide variety of decision-making settings, while clarifying how these notions relate to familiar psychological constructs. We conclude our analysis by arguing that there are indeed reasons to believe that option generation is an important and distinct aspect of human decision-making. PMID:23986737
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Why we should talk about option generation in decision-making research.
Kalis, Annemarie; Kaiser, Stefan; Mojzisch, Andreas
2013-01-01
Most empirical studies on decision-making start from a set of given options for action. However, in everyday life there is usually no one asking you to choose between A, B, and C. Recently, the question how people come up with options has been receiving growing attention. However, so far there has been neither a systematic attempt to define the construct of "option" nor an attempt to show why decision-making research really needs this construct. This paper aims to fill that void by developing definitions of "option" and "option generation" that can be used as a basis for decision-making research in a wide variety of decision-making settings, while clarifying how these notions relate to familiar psychological constructs. We conclude our analysis by arguing that there are indeed reasons to believe that option generation is an important and distinct aspect of human decision-making.
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Karmali, Shazia
2012-01-01
This paper explores differences in decision-making approaches between physician executives and nonphysician executives in a managerial setting. Fredrickson and Mitchell's (1984) conceptualization of the construct of comprehensiveness in strategic decision making is the central construct of this paper. Theories of professional identity, socialization, and institutional/dominant logics are applied to illustrate their impact on strategic decision-making approaches of physician and nonphysician executives. This paper proposes that high-status professionals, specifically physicians, occupying senior management roles are likely to approach decision making in a way that is consistent with their professional identity, and by extension, that departments led by physician executives are less likely to exhibit comprehensiveness in strategic decision-making processes than departments led by nonphysician executives. This paper provides conceptual evidence that physicians and nonphysicians approach management differently, and introduces the utility of comprehensiveness as a construct for strategic decision making in the context of health care management.
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Using Green Building As A Model For Making Health Promotion Standard In The Built Environment.
Trowbridge, Matthew J; Worden, Kelly; Pyke, Christopher
2016-11-01
The built environment-the constructed physical parts of the places where people live and work-is a powerful determinant of both individual and population health. Awareness of the link between place and health is growing within the public health sector and among built environment decision makers working in design, construction, policy, and both public and private finance. However, these decision makers lack the knowledge, tools, and capacity to ensure that health and well-being are routinely considered across all sectors of the built environment. The green building industry has successfully established environmental sustainability as a normative part of built environment practice, policy making, and investment. We explore the value of this industry's experience as a template for promoting health and well-being in the built environment. Project HOPE—The People-to-People Health Foundation, Inc.
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Hart, Andrew S.; Collins, Anne L.; Bernstein, Ilene L.; Phillips, Paul E. M.
2012-01-01
Alcohol use during adolescence has profound and enduring consequences on decision-making under risk. However, the fundamental psychological processes underlying these changes are unknown. Here, we show that alcohol use produces over-fast learning for better-than-expected, but not worse-than-expected, outcomes without altering subjective reward valuation. We constructed a simple reinforcement learning model to simulate altered decision making using behavioral parameters extracted from rats with a history of adolescent alcohol use. Remarkably, the learning imbalance alone was sufficient to simulate the divergence in choice behavior observed between these groups of animals. These findings identify a selective alteration in reinforcement learning following adolescent alcohol use that can account for a robust change in risk-based decision making persisting into later life. PMID:22615989
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Veksler, Vladislav D; Buchler, Norbou; Hoffman, Blaine E; Cassenti, Daniel N; Sample, Char; Sugrim, Shridat
2018-01-01
Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting.
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Alkhatib, Omar J; Abdou, Alaa
2018-04-01
The construction industry is usually characterized as a fragmented system of multiple-organizational entities in which members from different technical backgrounds and moral values join together to develop a particular business or project. The greatest challenge in the construction process for the achievement of a successful practice is the development of an outstanding reputation, which is built on identifying and applying an ethical framework. This framework should reflect a common ethical ground for myriad people involved in this process to survive and compete ethically in today's turbulent construction market. This study establishes a framework for ethical judgment of behavior and actions conducted in the construction process. The framework was primarily developed based on the essential attributes of business management identified in the literature review and subsequently incorporates additional attributes identified to prevent breaches in the construction industry and common ethical values related to professional engineering. The proposed judgment framework is based primarily on the ethical dimension of professional responsibility. The Ethical Judgment Framework consists of descriptive approaches involving technical, professional, administrative, and miscellaneous terms. The framework provides the basis for judging actions as either ethical or unethical. Furthermore, the framework can be implemented as a form of preventive ethics, which would help avoid ethical dilemmas and moral allegations. The framework can be considered a decision-making model to guide actions and improve the ethical reasoning process that would help individuals think through possible implications and consequences of ethical dilemmas in the construction industry.
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Brandeau, Margaret L.; McCoy, Jessica H.; Hupert, Nathaniel; Holty, Jon-Erik; Bravata, Dena M.
2013-01-01
Purpose Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. We examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models. Methods We reviewed a spectrum of published disaster response models addressing public health or healthcare delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. We developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making. Results We propose six recommendations for model construction and reporting, inspired by the most exemplary models: Health sector disaster response models should address real-world problems; be designed for maximum usability by response planners; strike the appropriate balance between simplicity and complexity; include appropriate outcomes, which extend beyond those considered in traditional cost-effectiveness analyses; and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models. Conclusions Quantitative models are critical tools for planning effective health sector responses to disasters. The recommendations we propose can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response. PMID:19605887
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Brandeau, Margaret L; McCoy, Jessica H; Hupert, Nathaniel; Holty, Jon-Erik; Bravata, Dena M
2009-01-01
Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. The authors examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models. . The authors reviewed a spectrum of published disaster response models addressing public health or health care delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. They developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making. . The authors propose 6 recommendations for model construction and reporting, inspired by the most exemplary models: health sector disaster response models should address real-world problems, be designed for maximum usability by response planners, strike the appropriate balance between simplicity and complexity, include appropriate outcomes that extend beyond those considered in traditional cost-effectiveness analyses, and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models. . Quantitative models are critical tools for planning effective health sector responses to disasters. The proposed recommendations can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response.
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Visualization of decision processes using a cognitive architecture
NASA Astrophysics Data System (ADS)
Livingston, Mark A.; Murugesan, Arthi; Brock, Derek; Frost, Wende K.; Perzanowski, Dennis
2013-01-01
Cognitive architectures are computational theories of reasoning the human mind engages in as it processes facts and experiences. A cognitive architecture uses declarative and procedural knowledge to represent mental constructs that are involved in decision making. Employing a model of behavioral and perceptual constraints derived from a set of one or more scenarios, the architecture reasons about the most likely consequence(s) of a sequence of events. Reasoning of any complexity and depth involving computational processes, however, is often opaque and challenging to comprehend. Arguably, for decision makers who may need to evaluate or question the results of autonomous reasoning, it would be useful to be able to inspect the steps involved in an interactive, graphical format. When a chain of evidence and constraint-based decision points can be visualized, it becomes easier to explore both how and why a scenario of interest will likely unfold in a particular way. In initial work on a scheme for visualizing cognitively-based decision processes, we focus on generating graphical representations of models run in the Polyscheme cognitive architecture. Our visualization algorithm operates on a modified version of Polyscheme's output, which is accomplished by augmenting models with a simple set of tags. We provide example visualizations and discuss properties of our technique that pose challenges for our representation goals. We conclude with a summary of feedback solicited from domain experts and practitioners in the field of cognitive modeling.
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NASA Astrophysics Data System (ADS)
Beedasy, Jaishree; Whyatt, Duncan
Mauritius is a small island (1865 km 2) in the Indian Ocean. Tourism is the third largest economic sector of the country, after manufacturing and agriculture. A limitation of space and the island's vulnerable ecosystem warrants a rational approach to tourism development. The main problems so far have been to manipulate and integrate all the factors affecting tourism planning and to match spatial data with their relevant attributes. A Spatial Decision Support System (SDSS) for sustainable tourism planning is therefore proposed. The proposed SDSS design would include a GIS as its core component. A first GIS model has already been constructed with available data. Supporting decision-making in a spatial context is implicit in the use of GIS. However the analytical capability of the GIS has to be enhanced to solve semi-structured problems, where subjective judgements come into play. The second part of the paper deals with the choice, implementation and customisation of a relevant model to develop a specialised SDSS. Different types of models and techniques are discussed, in particular a comparison of compensatory and non-compensatory approaches to multicriteria evaluation (MCE). It is concluded that compensatory multicriteria evaluation techniques increase the scope of the present GIS model as a decision-support tool. This approach gives the user or decision-maker the flexibility to change the importance of each criterion depending on relevant objectives.
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Perception and communication of risk in decision making by persons with dementia.
Stevenson, Mabel; Savage, Beverley; Taylor, Brian J
2017-01-01
Communication of risks must involve people with dementia meaningfully to ensure informed and inclusive decision-making processes. This qualitative study explored concepts of risk from the perspective of persons with dementia and their experiences of communicating risk with family members and professionals. Data was analysed using grounded theory. Seventeen people in Northern Ireland with mild-moderate dementia who had recently made a decision about their daily life or care involving consideration of risks were interviewed between November 2015 and November 2016. A wide range of actual or feared risks were identified relating to: daily activities; hobbies and socialising; mental health and medicines; and risks to and from others. 'Risk' often held emotional rather than probability connotations. Constructive communications to address issues were presented. Problem-solving models of both active and passive decision-making about risks were evident. Effective risk communication in informed decision-making processes about health and social care is discussed.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com; Gupta, Shikha
Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data,more » optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the constructed (c) DTB and (d) DTF regression models to predict the T. pyriformis toxicity of diverse chemicals. - Highlights: • Ensemble learning (EL) based models constructed for toxicity prediction of chemicals • Predictive models used a few simple non-quantum mechanical molecular descriptors. • EL-based DTB/DTF models successfully discriminated toxic and non-toxic chemicals. • DTB/DTF regression models precisely predicted toxicity of chemicals in multi-species. • Proposed EL based models can be used as tool to predict toxicity of new chemicals.« less
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Surgical Consultation as Social Process: Implications for Shared Decision Making.
Clapp, Justin T; Arriaga, Alexander F; Murthy, Sushila; Raper, Steven E; Schwartz, J Sanford; Barg, Frances K; Fleisher, Lee A
2017-12-12
This qualitative study examines surgical consultation as a social process and assesses its alignment with assumptions of the shared decision-making (SDM) model. SDM stresses the importance of patient preferences and rigorous discussion of therapeutic risks/benefits based on these preferences. However, empirical studies have highlighted discrepancies between SDM and realities of surgical decision making. Qualitative research can inform understanding of the decision-making process and allow for granular assessment of the nature and causes of these discrepancies. We observed consultations between 3 general surgeons and 45 patients considering undergoing 1 of 2 preference-sensitive elective operations: (1) hernia repair, or (2) cholecystectomy. These patients and surgeons also participated in semi-structured interviews. By the time of the consultation, patients and surgeons were predisposed toward certain decisions by preceding events occurring elsewhere. During the visit, surgeons had differential ability to arbitrate surgical intervention and construct the severity of patients' conditions. These upstream dynamics frequently displaced the centrality of the risk/benefit-based consent discussion. The influence of events preceding consultation suggests that decision-making models should account for broader spatiotemporal spans. Given surgeons' authority to define patients' conditions and control service provision, SDM may be premised on an overestimation of patients' power to alter the course of decision making once in a specialist's office. Considering the subordinate role of the risk/benefit discussion in many surgical decisions, it will be important to study if and how the social process of decision making is altered by SDM-oriented decision aids that foreground this discussion.
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Slade, Eric P.; Becker, Kimberly D.
2014-01-01
This paper discusses the steps and decisions involved in proximal-distal economic modeling, in which social, behavioral, and academic outcomes data for children may be used to inform projections of the economic consequences of interventions. Economic projections based on proximal-distal modeling techniques may be used in cost-benefit analyses when information is unavailable for certain long term outcomes data in adulthood or to build entire cost-benefit analyses. Although examples of proximal-distal economic analyses of preventive interventions exist in policy reports prepared for governmental agencies, such analyses have rarely been completed in conjunction with research trials. The modeling decisions on which these prediction models are based are often opaque to policymakers and other end-users. This paper aims to illuminate some of the key steps and considerations involved in constructing proximal-distal prediction models and to provide examples and suggestions that may help guide future proximal-distal analyses. PMID:24337979
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Development of a Knowledge-Based System Approach for Decision Making in Construction Projects
1992-05-01
a generic model for an administrative facility and medical facility with predefined fixed building systems based on Air Force criteria and past...MAINTENANCE HANGAR (MEDIUM BAY) CORROSION CONTROL HANGAR (HIGH BAY) FUEL SYSTEM MAINTENANCE HANGAR (MEDIUM BAY) MEDICAL MODEL 82 Table 5-1--continued...BUILDING SUPPORT MEDICAL LOGISTICS MEDICAL TOTAL 85 Table 5-2--continued MISSILE ASSEMBLY AND MAINTENANCE BUILDING TOTAL MISSILE LOADING AND UNLOADING
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An Environmental Management Maturity Model of Construction Programs Using the AHP-Entropy Approach.
Bai, Libiao; Wang, Hailing; Huang, Ning; Du, Qiang; Huang, Youdan
2018-06-23
The accelerating process of urbanization in China has led to considerable opportunities for the development of construction projects, however, environmental issues have become an important constraint on the implementation of these projects. To quantitatively describe the environmental management capabilities of such projects, this paper proposes a 2-dimensional Environmental Management Maturity Model of Construction Program (EMMMCP) based on an analysis of existing projects, group management theory and a management maturity model. In this model, a synergetic process was included to compensate for the lack of consideration of synergies in previous studies, and it was involved in the construction of the first dimension, i.e., the environmental management index system. The second dimension, i.e., the maturity level of environment management, was then constructed by redefining the hierarchical characteristics of construction program (CP) environmental management maturity. Additionally, a mathematical solution to this proposed model was derived via the Analytic Hierarchy Process (AHP)-entropy approach. To verify the effectiveness and feasibility of this proposed model, a computational experiment was conducted, and the results show that this approach could not only measure the individual levels of different processes, but also achieve the most important objective of providing a reference for stakeholders when making decisions on the environmental management of construction program, which reflects this model is reasonable for evaluating the level of environmental management maturity in CP. To our knowledge, this paper is the first study to evaluate the environmental management maturity levels of CP, which would fill the gap between project program management and environmental management and provide a reference for relevant management personnel to enhance their environmental management capabilities.
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Blalock, Susan J; Reyna, Valerie F
2016-08-01
Fuzzy-trace theory is a dual-process model of memory, reasoning, judgment, and decision making that contrasts with traditional expectancy-value approaches. We review the literature applying fuzzy-trace theory to health with 3 aims: evaluating whether the theory's basic distinctions have been validated empirically in the domain of health; determining whether these distinctions are useful in assessing, explaining, and predicting health-related psychological processes; and determining whether the theory can be used to improve health judgments, decisions, or behaviors, especially compared to other approaches. We conducted a literature review using PubMed, PsycINFO, and Web of Science to identify empirical peer-reviewed papers that applied fuzzy-trace theory, or central constructs of the theory, to investigate health judgments, decisions, or behaviors. Seventy nine studies (updated total is 94 studies; see Supplemental materials) were identified, over half published since 2012, spanning a wide variety of conditions and populations. Study findings supported the prediction that verbatim and gist representations are distinct constructs that can be retrieved independently using different cues. Although gist-based reasoning was usually associated with improved judgment and decision making, 4 sources of bias that can impair gist reasoning were identified. Finally, promising findings were reported from intervention studies that used fuzzy-trace theory to improve decision making and decrease unhealthy risk taking. Despite large gaps in the literature, most studies supported all 3 aims. By focusing on basic psychological processes that underlie judgment and decision making, fuzzy-trace theory provides insights into how individuals make decisions involving health risks and suggests innovative intervention approaches to improve health outcomes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology
NASA Astrophysics Data System (ADS)
Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli
2007-06-01
Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.
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Courtney, Kelly E.; Arellano, Ryan; Barkley-Levenson, Emily; Gálvan, Adriana; Poldrack, Russell A.; MacKillop, James; Jentsch, J. David; Ray, Lara A.
2011-01-01
Background Higher levels of impulsivity have been implicated in the development of alcohol use disorders. Recent findings suggest that impulsivity is not a unitary construct, highlighted by the diverse ways in which the various measures of impulsivity relate to alcohol use outcomes. This study simultaneously tested the following dimensions of impulsivity as determinants of alcohol use and alcohol problems: risky decision-making, self-reported risk attitudes, response inhibition, and impulsive decision-making. Method Participants were a community sample of non-treatment seeking problem drinkers (N = 158). Structural Equation Modeling (SEM) analyses employed behavioral measures of impulsive decision-making (Delay Discounting Task, DDT), response inhibition (Stop Signal Task, SST), and risky decision-making (Balloon Analogue Risk Task, BART), and a self-report measure of risk attitudes (Domain-specific Risk-attitude Scale, DOSPERT), as predictors of alcohol use and of alcohol-related problems in this sample. Results The model fit well, accounting for 38% of the variance in alcohol problems, and identified two impulsivity dimensions that significantly loaded onto alcohol outcomes: (1) impulsive decision-making, indexed by the DDT; and (2) risky decision-making, measured by the BART. Conclusions The impulsive decision-making dimension of impulsivity, indexed by the DDT, was the strongest predictor of alcohol use and alcohol pathology in this sample of problem drinkers. Unexpectedly, a negative relationship was found between risky decision-making and alcohol problems. The results highlight the importance of considering the distinct facets of impulsivity in order to elucidate their individual and combined effects on alcohol use initiation, escalation, and dependence. PMID:22091877
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Controversies in water management: Frames and mental models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kolkman, M.J.; Department of Civil Engineering and Management, Faculty of Engineering Technology; Veen, A. van der
Controversies in decision and policy-making processes can be analysed using frame reflection and mental model mapping techniques. The purpose of the method presented in this paper is to improve the quality of the information and interpretations available to decision makers, by surfacing and juxtaposing the different frames of decision makers, experts, and special interests groups. The research provides a new method to analyse frames. It defines a frame to consist of perspectives and a mental model, which are in close interaction (through second order learning processes). The mental model acts like a 'filter' through which the problem situation is observed.more » Five major perspective types guide the construction of meaning out of the information delivered by the mental model, and determine what actors see as their interests. The perspective types are related to an actor's institutional and personal position in the decision making process. The method was applied to a case, in order to test its viability. The case concerns the decision making process and environmental impact assessment procedure for the improvement of dike ring 53 in the Netherlands, which was initiated by the Dutch 'Flood Defences Act 1996'. In this specific case the perspectives and mental models of stakeholders were elicited to explain controversies. The case was analysed with regard to the conflicts emerging between stakeholders, on an individual level. The influence of institutional embedding of individuals on the use of information and the construction of meaning, and the limits of a participatory approach were analysed within the details of controversies that emerged during the case analysis. Complicating factor appeared to be the interaction between national dike safety norms (short term) and local water management problems (long term). Revealed controversies mainly concerned disputes between an organisational and a technical perspective. But also disputes on distribution of responsibilities between different institutes, on legal and political liability, and on funding issues, involving persons of both perspectives, were found. The case reveals a lack of possibilities to search for an integrated solution which involves all levels of authority, and a lack of possibilities to discuss the additional problems that were raised by the integrated approach in the initial phase of the case project. The complex and unstructured nature of the problem situation caused the traditional substantive approach to fail to deliver a good solution. Legal, socio-economic and institutional factors ultimately dominated the decision making process.« less
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Exploring the possibility of modeling a genetic counseling guideline using agile methodology.
Choi, Jeeyae
2013-01-01
Increased demand of genetic counseling services heightened the necessity of a computerized genetic counseling decision support system. In order to develop an effective and efficient computerized system, modeling of genetic counseling guideline is an essential step. Throughout this pilot study, Agile methodology with United Modeling Language (UML) was utilized to model a guideline. 13 tasks and 14 associated elements were extracted. Successfully constructed conceptual class and activity diagrams revealed that Agile methodology with UML was a suitable tool to modeling a genetic counseling guideline.
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Borderline Personality Traits and Disorder: Predicting Prospective Patient Functioning
ERIC Educational Resources Information Center
Hopwood, Christopher J.; Zanarini, Mary C.
2010-01-01
Objective: Decisions about the composition of personality assessment in the "Diagnostic and Statistical Manual of Mental Disorders" (5th ed.; DSM-V) will be heavily influenced by the clinical utility of candidate constructs. In this study, we addressed 1 aspect of clinical utility by testing the incremental validity of 5-factor model (FFM)…
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2006-03-01
1989) present an innovative approach to quantifying risk . Their approach is to utilize linguistic terms or words and to systematically assign a...Together, these 15 factors were a first step in the problem of quantifying risk . These factors, and the four categories within which they fall, are
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The Promise and the Caution of Resilience Models for Schools
ERIC Educational Resources Information Center
Doll, Beth; Jones, Kristin; Osborn, Allison; Dooley, Kadie; Turner, April
2011-01-01
Resilience is a very useful construct for framing school mental health services to children and is particularly applicable to mental health services in school settings. Still, resilience perspectives should not be overgeneralized to school mental health practice because risk and resilience wax and wane over time and daily decisions about students'…
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Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.
Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen
2014-01-01
Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.
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A Comparison of Juror Decision Making in Race-Based and Sexual Orientation-Based Hate Crime Cases.
Gamblin, Bradlee W; Kehn, Andre; Vanderzanden, Karen; Ruthig, Joelle C; Jones, Kelly M; Long, Brittney L
2018-05-01
Several constructs have been identified as relevant to the juror decision-making process in hate crime cases. However, there is a lack of research on the relationships between these constructs and their variable influence across victim group. The purpose of the current study was to reexamine factors relevant to the juror decision-making process in hate crime cases within a structural model, and across victim group, to gauge the relative strength and explanatory power of various predictors. In the current study, 313 participants sentenced a perpetrator found guilty of a hate crime committed against either a Black man or a gay man; participants also responded to individual difference measures relevant to mock juror hate crime decision making, including prejudice toward the victim's social group. Using path analysis, we explored the role of juror prejudice on sentencing decisions in hate crime cases as well as similarities and differences based on the victimized group. Results indicated that, when the victim was a Black man, modern racism influenced sentencing both directly and indirectly through perpetrator blame attributions, explaining 18% of the variance in sentencing. In contrast, when the victim was a gay man, modern homophobia did not directly predict sentencing, and the overall model explained only 4% of the variance in sentencing, suggesting variables beyond juror prejudice may be better suited to explain juror decision making in sexual orientation-based hate crimes. The current study suggests that the role of juror prejudice in hate crime cases varies as a function of the victimized group and raises questions about the importance of juror prejudice in the sentencing of hate crime cases, particularly antigay prejudice. The importance of blame attributions, social dominance orientation, and juror beliefs regarding penalty enhancements for hate crime cases, as well as policy implications, are also addressed.
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Using features of Arden Syntax with object-oriented medical data models for guideline modeling.
Peleg, M; Ogunyemi, O; Tu, S; Boxwala, A A; Zeng, Q; Greenes, R A; Shortliffe, E H
2001-01-01
Computer-interpretable guidelines (CIGs) can deliver patient-specific decision support at the point of care. CIGs base their recommendations on eligibility and decision criteria that relate medical concepts to patient data. CIG models use expression languages for specifying these criteria, and define models for medical data to which the expressions can refer. In developing version 3 of the GuideLine Interchange Format (GLIF3), we used existing standards as the medical data model and expression language. We investigated the object-oriented HL7 Reference Information Model (RIM) as a default data model. We developed an expression language, called GEL, based on Arden Syntax's logic grammar. Together with other GLIF constructs, GEL reconciles incompatibilities between the data models of Arden Syntax and the HL7 RIM. These incompatibilities include Arden's lack of support for complex data types and time intervals, and the mismatch between Arden's single primary time and multiple time attributes of the HL7 RIM.
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Corruption Early Prevention: Decision Support System for President of the Republic of Indonesia
NASA Astrophysics Data System (ADS)
Sasmoko; Widhoyoko, S. A.; Ariyanto, S.; Indrianti, Y.; Noerlina; Muqsith, A. M.; Alamsyah, M.
2017-01-01
Corruption is an extraordinary crime, and then the prevention must also be extraordinary, simultaneously (national) in the form of early warning that involves all elements; government, industry, and society. To realize it the system needs to be built which in this study is called the Corruption Early Prevention (CEP) as a Decision Support System for President of the Republic of Indonesia. This study aims to examine 1) how is the construct of the Corruption Early Prevention as a Decision Support System for President of the Republic of Indonesia?, and 2) how is the design form of the system of Corruption Early Prevention as a Decision Support System for President of Republic of Indonesia? The research method is using Neuro-Research which is the collaboration of qualitative and quantitative research methods and the model development of Information Technology (IT). The research found that: 1) the construct of CEP is theoretically feasible, valid and reliable by content to be developed in the context of the prevention of corruption in Indonesia as an early prevention system that diagnoses Indonesia simultaneously and in real time, and 2) the concept of system design and business process of CEP is predicted to be realized in the IT-based program.
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Decisive management in selecting locations for development of construction projects
NASA Astrophysics Data System (ADS)
Szafranko, E.; Pawłowicz, J. A.
2017-08-01
The location of an investment project is one of the most important decisions in the construction and land development business. The shape of a new building and aspects of its future use depend on making a good choice of a land plot where it will be constructed. There are many characteristics involved descriptions of land available for development. On the one hand, different buildings (with different envisaged use) fit differently to a given location. Residential homes, for example, require a location which will ensure a peaceful lifestyle, with places for walks and recreation, situated in a relatively quite setting. On the other hand, close proximity to schools, shops or a health clinic is another important consideration. Industrial buildings should be localized so as not to be a nuisance to others, and their location should facilitate efficient transport of raw materials and ready products. Yet other requirements are defined for public buildings. It is therefore evident that the characteristics included in an evaluation of the location of a planned building can be highly diverse and their diversity makes the evaluation difficult. Selection of a location can be supported by a variety of methods. For instance, an evaluation can rely on assigning points which indicate the fulfillment of certain criteria. This approach generates a complex evaluation in the form of tables and maps of usefulness. Another possibility is to make an assessment of the criteria that a given land parcels should satisfy in order to develop a specific type of a building. Having combined these two sets of information, we can create a system or a model for the management of land resources, which will easily help to support decision making processes pertaining to the choice of a location. This article shows a model approach for a specific building.
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Rasch Analysis of the 9-Item Shared Decision Making Questionnaire in Women With Breast Cancer.
Wu, Tzu-Yi; Chen, Cheng-Te; Huang, Yi-Jing; Hou, Wen-Hsuan; Wang, Jung-Der; Hsieh, Ching-Lin
2018-04-19
Shared decision making (SDM) is a best practice to help patients make optimal decisions by a process of healthcare, especially for women diagnosed with breast cancer and having heavy burden in long-term treatments. To promote successful SDM, it is crucial to assess the level of perceived involvement in SDM in women with breast cancer. The aims of this study were to apply Rasch analysis to examine the construct validity and person reliability of the 9-item Shared Decision Making Questionnaire (SDM-Q-9) in women with breast cancer. The construct validity of SDM-Q-9 was confirmed when the items fit the Rasch model's assumptions of unidimensionality: (1) infit and outfit mean square ranged from 0.6 to 1.4; (2) the unexplained variance of the first dimension of the principal component analysis was less than 20%. Person reliability was calculated. A total of 212 participants were recruited in this study. Item 1 did not fit the model's assumptions and was deleted. The unidimensionality of the remaining 8 items (SDM-Q-8) was supported with good item fit (infit and outfit mean square ranging from 0.6 to 1.3) and very low unexplained variance of the first dimension (5.3%) of the principal component analysis. The person reliability of the SDM-Q-8 was 0.90. The SDM-Q-8 was unidimensional and had good person reliability in women with breast cancer. The SDM-Q-8 has shown its potential for assessing the level of perceived involvement in SDM in women with breast cancer for both research and clinical purposes.
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A decision method based on uncertainty reasoning of linguistic truth-valued concept lattice
NASA Astrophysics Data System (ADS)
Yang, Li; Xu, Yang
2010-04-01
Decision making with linguistic information is a research hotspot now. This paper begins by establishing the theory basis for linguistic information processing and constructs the linguistic truth-valued concept lattice for a decision information system, and further utilises uncertainty reasoning to make the decision. That is, we first utilise the linguistic truth-valued lattice implication algebra to unify the different kinds of linguistic expressions; second, we construct the linguistic truth-valued concept lattice and decision concept lattice according to the concrete decision information system and third, we establish the internal and external uncertainty reasoning methods and talk about the rationality of them. We apply these uncertainty reasoning methods into decision making and present some generation methods of decision rules. In the end, we give an application of this decision method by an example.
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Improved decision making in construction using virtual site visits.
DOT National Transportation Integrated Search
2003-01-01
This study explored the dynamics of information exchange involving field issues relating to construction and the assistance that a virtual site visit can provide to the field decision-making process. Such a process can be used for inspection and surv...
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Martin, April; Bagdasarov, Zhanna; Connelly, Shane
2015-04-01
Although various models of ethical decision making (EDM) have implicitly called upon constructs governed by working memory capacity (WMC), a study examining this relationship specifically has not been conducted. Using a sense making framework of EDM, we examined the relationship between WMC and various sensemaking processes contributing to EDM. Participants completed an online assessment comprised of a demographic survey, intelligence test, various EDM measures, and the Automated Operation Span task to determine WMC. Results indicated that WMC accounted for unique variance above and beyond ethics education, exposure to ethical issues, and intelligence in several sensemaking processes. Additionally, a marginally significant effect of WMC was also found with reference to EDM. Individual differences in WMC appear likely to play an important role in the ethical decision-making process, and future researchers may wish to consider their potential influences.
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Chungkham, Holendro Singh; Ingre, Michael; Karasek, Robert; Westerlund, Hugo; Theorell, Töres
2013-01-01
To examine the factor structure and to evaluate the longitudinal measurement invariance of the demand-control-support questionnaire (DCSQ), using the Swedish Longitudinal Occupational Survey of Health (SLOSH). A confirmatory factor analysis (CFA) and multi-group confirmatory factor analysis (MGCFA) models within the framework of structural equation modeling (SEM) have been used to examine the factor structure and invariance across time. Four factors: psychological demand, skill discretion, decision authority and social support, were confirmed by CFA at baseline, with the best fit obtained by removing the item repetitive work of skill discretion. A measurement error correlation (0.42) between work fast and work intensively for psychological demands was also detected. Acceptable composite reliability measures were obtained except for skill discretion (0.68). The invariance of the same factor structure was established, but caution in comparing mean levels of factors over time is warranted as lack of intercept invariance was evident. However, partial intercept invariance was established for work intensively. Our findings indicate that skill discretion and decision authority represent two distinct constructs in the retained model. However removing the item repetitive work along with either work fast or work intensively would improve model fit. Care should also be taken while making comparisons in the constructs across time. Further research should investigate invariance across occupations or socio-economic classes.
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Chungkham, Holendro Singh; Ingre, Michael; Karasek, Robert; Westerlund, Hugo; Theorell, Töres
2013-01-01
Objectives To examine the factor structure and to evaluate the longitudinal measurement invariance of the demand-control-support questionnaire (DCSQ), using the Swedish Longitudinal Occupational Survey of Health (SLOSH). Methods A confirmatory factor analysis (CFA) and multi-group confirmatory factor analysis (MGCFA) models within the framework of structural equation modeling (SEM) have been used to examine the factor structure and invariance across time. Results Four factors: psychological demand, skill discretion, decision authority and social support, were confirmed by CFA at baseline, with the best fit obtained by removing the item repetitive work of skill discretion. A measurement error correlation (0.42) between work fast and work intensively for psychological demands was also detected. Acceptable composite reliability measures were obtained except for skill discretion (0.68). The invariance of the same factor structure was established, but caution in comparing mean levels of factors over time is warranted as lack of intercept invariance was evident. However, partial intercept invariance was established for work intensively. Conclusion Our findings indicate that skill discretion and decision authority represent two distinct constructs in the retained model. However removing the item repetitive work along with either work fast or work intensively would improve model fit. Care should also be taken while making comparisons in the constructs across time. Further research should investigate invariance across occupations or socio-economic classes. PMID:23950957
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Decision Support System for Reservoir Management and Operation in Africa
NASA Astrophysics Data System (ADS)
Navar, D. A.
2016-12-01
Africa is currently experiencing a surge in dam construction for flood control, water supply and hydropower production, but ineffective reservoir management has caused problems in the region, such as water shortages, flooding and loss of potential hydropower generation. Our research aims to remedy ineffective reservoir management by developing a novel Decision Support System(DSS) to equip water managers with a technical planning tool based on the state of the art in hydrological sciences. The DSS incorporates a climate forecast model, a hydraulic model of the watershed, and an optimization model to effectively plan for the operation of a system of cascade large-scale reservoirs for hydropower production, while treating water supply and flood control as constraints. Our team will use the newly constructed hydropower plants in the Omo Gibe basin of Ethiopia as the test case. Using the basic HIDROTERM software developed in Brazil, the General Algebraic Modeling System (GAMS) utilizes a combination of linear programing (LP) and non-linear programming (NLP) in conjunction with real time hydrologic and energy demand data to optimize the monthly and daily operations of the reservoir system. We compare the DSS model results with the current reservoir operating policy used by the water managers of that region. We also hope the DSS will eliminate the current dangers associated with the mismanagement of large scale water resources projects in Africa.
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Detection of fraudulent financial statements using the hybrid data mining approach.
Chen, Suduan
2016-01-01
The purpose of this study is to construct a valid and rigorous fraudulent financial statement detection model. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements between the years 2002 and 2013. In the first stage, two decision tree algorithms, including the classification and regression trees (CART) and the Chi squared automatic interaction detector (CHAID) are applied in the selection of major variables. The second stage combines CART, CHAID, Bayesian belief network, support vector machine and artificial neural network in order to construct fraudulent financial statement detection models. According to the results, the detection performance of the CHAID-CART model is the most effective, with an overall accuracy of 87.97 % (the FFS detection accuracy is 92.69 %).
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Ballesteros, Javier; Moral, Ester; Brieva, Luis; Ruiz-Beato, Elena; Prefasi, Daniel; Maurino, Jorge
2017-04-22
Shared decision-making is a cornerstone of patient-centred care. The 9-item Shared Decision-Making Questionnaire (SDM-Q-9) is a brief self-assessment tool for measuring patients' perceived level of involvement in decision-making related to their own treatment and care. Information related to the psychometric properties of the SDM-Q-9 for multiple sclerosis (MS) patients is limited. The objective of this study was to assess the performance of the items composing the SDM-Q-9 and its dimensional structure in patients with relapsing-remitting MS. A non-interventional, cross-sectional study in adult patients with relapsing-remitting MS was conducted in 17 MS units throughout Spain. A nonparametric item response theory (IRT) analysis was used to assess the latent construct and dimensional structure underlying the observed responses. A parametric IRT model, General Partial Credit Model, was fitted to obtain estimates of the relationship between the latent construct and item characteristics. The unidimensionality of the SDM-Q-9 instrument was assessed by confirmatory factor analysis. A total of 221 patients were studied (mean age = 42.1 ± 9.9 years, 68.3% female). Median Expanded Disability Status Scale score was 2.5 ± 1.5. Most patients reported taking part in each step of the decision-making process. Internal reliability of the instrument was high (Cronbach's α = 0.91) and the overall scale scalability score was 0.57, indicative of a strong scale. All items, except for the item 1, showed scalability indices higher than 0.30. Four items (items 6 through to 9) conveyed more than half of the SDM-Q-9 overall information (67.3%). The SDM-Q-9 was a good fit for a unidimensional latent structure (comparative fit index = 0.98, root-mean-square error of approximation = 0.07). All freely estimated parameters were statistically significant (P < 0.001). All items presented standardized parameter estimates with salient loadings (>0.40) with the exception of item 1 which presented the lowest loading (0.26). Items 6 through to 8 were the most relevant items for shared decision-making. The SDM-Q-9 presents appropriate psychometric properties and is therefore useful for assessing different aspects of shared decision-making in patients with multiple sclerosis.
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Sung, Ki Hyuk; Chung, Chin Youb; Lee, Kyoung Min; Lee, Seung Yeol; Choi, In Ho; Cho, Tae-Joon; Yoo, Won Joon; Park, Moon Seok
2014-01-01
This study aimed to determine the best treatment modality for coronal angular deformity of the knee joint in growing children using decision analysis. A decision tree was created to evaluate 3 treatment modalities for coronal angular deformity in growing children: temporary hemiepiphysiodesis using staples, percutaneous screws, or a tension band plate. A decision analysis model was constructed containing the final outcome score, probability of metal failure, and incomplete correction of deformity. The final outcome was defined as health-related quality of life and was used as a utility in the decision tree. The probabilities associated with each case were obtained by literature review, and health-related quality of life was evaluated by a questionnaire completed by 25 pediatric orthopedic experts. Our decision analysis model favored temporary hemiepiphysiodesis using a tension band plate over temporary hemiepiphysiodesis using percutaneous screws or stapling, with utilities of 0.969, 0.957, and 0.962, respectively. One-way sensitivity analysis showed that hemiepiphysiodesis using a tension band plate was better than temporary hemiepiphysiodesis using percutaneous screws, when the overall complication rate of hemiepiphysiodesis using a tension band plate was lower than 15.7%. Two-way sensitivity analysis showed that hemiepiphysiodesis using a tension band plate was more beneficial than temporary hemiepiphysiodesis using percutaneous screws. PMID:25276801
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The thinking of Cloud computing in the digital construction of the oil companies
NASA Astrophysics Data System (ADS)
CaoLei, Qizhilin; Dengsheng, Lei
In order to speed up digital construction of the oil companies and enhance productivity and decision-support capabilities while avoiding the disadvantages from the waste of the original process of building digital and duplication of development and input. This paper presents a cloud-based models for the build in the digital construction of the oil companies that National oil companies though the private network will join the cloud data of the oil companies and service center equipment integrated into a whole cloud system, then according to the needs of various departments to prepare their own virtual service center, which can provide a strong service industry and computing power for the Oil companies.
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The construct-behavior gap in behavioral decision research: A challenge beyond replicability.
Regenwetter, Michel; Robinson, Maria M
2017-10-01
Behavioral decision research compares theoretical constructs like preferences to behavior such as observed choices. Three fairly common links from constructs to behavior are (1) to tally, across participants and decision problems, the number of choices consistent with one predicted pattern of pairwise preferences; (2) to compare what most people choose in each decision problem against a predicted preference pattern; or (3) to enumerate the decision problems in which two experimental conditions generate a 1-sided significant difference in choice frequency 'consistent' with the theory. Although simple, these theoretical links are heuristics. They are subject to well-known reasoning fallacies, most notably the fallacy of sweeping generalization and the fallacy of composition. No amount of replication can alleviate these fallacies. On the contrary, reiterating logically inconsistent theoretical reasoning over and again across studies obfuscates science. As a case in point, we consider pairwise choices among simple lotteries and the hypotheses of overweighting or underweighting of small probabilities, as well as the description-experience gap. We discuss ways to avoid reasoning fallacies in bridging the conceptual gap between hypothetical constructs, such as, for example, "overweighting" to observable pairwise choice data. Although replication is invaluable, successful replication of hard-to-interpret results is not. Behavioral decision research stands to gain much theoretical and empirical clarity by spelling out precise and formally explicit theories of how hypothetical constructs translate into observable behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Building a Foreign Military Sales Construction Delivery Strategy Decision Support System
1991-09-01
DSS, formulates it into a computer model and produces solutions using information and expert heuristics. Using the Expert Systeic Process to Build a DSS...computer model . There are five stages in the development of an expert system. They are: 1) Identify and characterize the important aspects of the problem...and Steven A. Hidreth. U.S. Security Assistance: The Political Process. Massachusetts: Heath and Company, 1985. 19. Guirguis , Amir A., Program
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2012-09-01
supported by the National Science Foundation (NSF) IGERT 9972762, the Army Research Institute (ARI) W91WAW07C0063, the Army Research Laboratory (ARL/CTA...prediction models in AutoMap .................................................. 144 Figure 13: Decision Tree for prediction model selection in...generated for nationally funded initiatives and made available through the Linguistic Data Consortium (LDC). An overview of these datasets is provided in
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An Empirically Calibrated Model of Cell Fate Decision Following Viral Infection
NASA Astrophysics Data System (ADS)
Coleman, Seth; Igoshin, Oleg; Golding, Ido
The life cycle of the virus (phage) lambda is an established paradigm for the way genetic networks drive cell fate decisions. But despite decades of interrogation, we are still unable to theoretically predict whether the infection of a given cell will result in cell death or viral dormancy. The poor predictive power of current models reflects the absence of quantitative experimental data describing the regulatory interactions between different lambda genes. To address this gap, we are constructing a theoretical model that captures the known interactions in the lambda network. Model assumptions and parameters are calibrated using new single-cell data from our lab, describing the activity of lambda genes at single-molecule resolution. We began with a mean-field model, aimed at exploring the population averaged gene-expression trajectories under different initial conditions. Next, we will develop a stochastic formulation, to capture the differences between individual cells within the population. The eventual goal is to identify how the post-infection decision is driven by the interplay between network topology, initial conditions, and stochastic effects. The insights gained here will inform our understanding of cell fate choices in more complex cellular systems.
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Economic and environmental costs of regulatory uncertainty for coal-fired power plants.
Patiño-Echeverri, Dalia; Fischbeck, Paul; Kriegler, Elmar
2009-02-01
Uncertainty about the extent and timing of CO2 emissions regulations for the electricity-generating sector exacerbates the difficulty of selecting investment strategies for retrofitting or alternatively replacing existent coal-fired power plants. This may result in inefficient investments imposing economic and environmental costs to society. In this paper, we construct a multiperiod decision model with an embedded multistage stochastic dynamic program minimizing the expected total costs of plant operation, installations, and pollution allowances. We use the model to forecast optimal sequential investment decisions of a power plant operator with and without uncertainty about future CO2 allowance prices. The comparison of the two cases demonstrates that uncertainty on future CO2 emissions regulations might cause significant economic costs and higher air emissions.
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Dynamic Interplay of Value and Sensory Information in High-Speed Decision Making.
Afacan-Seref, Kivilcim; Steinemann, Natalie A; Blangero, Annabelle; Kelly, Simon P
2018-03-05
In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively [1-6], but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases are affected by starting the integrator closer to the more valuable bound. Here, we show significant departures from this account for humans making rapid sensory-instructed action choices. Behavior was best explained by a simple model in which the evidence representation-and hence, rate of accumulation-is itself biased by value and is non-stationary, increasing over the short decision time frame. Because the value bias initially dominates, the model uniquely predicts a dynamic "turn-around" effect on low-value cues, where the accumulator first launches toward the incorrect action but is then re-routed to the correct one. This was clearly exhibited in electrophysiological signals reflecting motor preparation and evidence accumulation. Finally, we construct an extended model that implements this dynamic effect through plausible sensory neural response modulations and demonstrate the correspondence between decision signal dynamics simulated from a behavioral fit of that model and the empirical decision signals. Our findings suggest that value and sensory information can exert simultaneous and dynamically countervailing influences on the trajectory of the accumulation-to-bound process, driving rapid, sensory-guided actions. Copyright © 2018 Elsevier Ltd. All rights reserved.
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McMeekin, Peter; Flynn, Darren; Ford, Gary A; Rodgers, Helen; Gray, Jo; Thomson, Richard G
2015-11-11
Individualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke. A decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data. The model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA. We have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.
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A dynamic dual process model of risky decision making.
Diederich, Adele; Trueblood, Jennifer S
2018-03-01
Many phenomena in judgment and decision making are often attributed to the interaction of 2 systems of reasoning. Although these so-called dual process theories can explain many types of behavior, they are rarely formalized as mathematical or computational models. Rather, dual process models are typically verbal theories, which are difficult to conclusively evaluate or test. In the cases in which formal (i.e., mathematical) dual process models have been proposed, they have not been quantitatively fit to experimental data and are often silent when it comes to the timing of the 2 systems. In the current article, we present a dynamic dual process model framework of risky decision making that provides an account of the timing and interaction of the 2 systems and can explain both choice and response-time data. We outline several predictions of the model, including how changes in the timing of the 2 systems as well as time pressure can influence behavior. The framework also allows us to explore different assumptions about how preferences are constructed by the 2 systems as well as the dynamic interaction of the 2 systems. In particular, we examine 3 different possible functional forms of the 2 systems and 2 possible ways the systems can interact (simultaneously or serially). We compare these dual process models with 2 single process models using risky decision making data from Guo, Trueblood, and Diederich (2017). Using this data, we find that 1 of the dual process models significantly outperforms the other models in accounting for both choices and response times. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Sa-Ngamuang, Chaitawat; Haddawy, Peter; Luvira, Viravarn; Piyaphanee, Watcharapong; Iamsirithaworn, Sopon; Lawpoolsri, Saranath
2018-06-18
Differentiating dengue patients from other acute febrile illness patients is a great challenge among physicians. Several dengue diagnosis methods are recommended by WHO. The application of specific laboratory tests is still limited due to high cost, lack of equipment, and uncertain validity. Therefore, clinical diagnosis remains a common practice especially in resource limited settings. Bayesian networks have been shown to be a useful tool for diagnostic decision support. This study aimed to construct Bayesian network models using basic demographic, clinical, and laboratory profiles of acute febrile illness patients to diagnose dengue. Data of 397 acute undifferentiated febrile illness patients who visited the fever clinic of the Bangkok Hospital for Tropical Diseases, Thailand, were used for model construction and validation. The two best final models were selected: one with and one without NS1 rapid test result. The diagnostic accuracy of the models was compared with that of physicians on the same set of patients. The Bayesian network models provided good diagnostic accuracy of dengue infection, with ROC AUC of 0.80 and 0.75 for models with and without NS1 rapid test result, respectively. The models had approximately 80% specificity and 70% sensitivity, similar to the diagnostic accuracy of the hospital's fellows in infectious disease. Including information on NS1 rapid test improved the specificity, but reduced the sensitivity, both in model and physician diagnoses. The Bayesian network model developed in this study could be useful to assist physicians in diagnosing dengue, particularly in regions where experienced physicians and laboratory confirmation tests are limited.
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Distributed collaborative environments for virtual capability-based planning
NASA Astrophysics Data System (ADS)
McQuay, William K.
2003-09-01
Distributed collaboration is an emerging technology that will significantly change how decisions are made in the 21st century. Collaboration involves two or more geographically dispersed individuals working together to share and exchange data, information, knowledge, and actions. The marriage of information, collaboration, and simulation technologies provides the decision maker with a collaborative virtual environment for planning and decision support. This paper reviews research that is focusing on the applying open standards agent-based framework with integrated modeling and simulation to a new Air Force initiative in capability-based planning and the ability to implement it in a distributed virtual environment. Virtual Capability Planning effort will provide decision-quality knowledge for Air Force resource allocation and investment planning including examining proposed capabilities and cost of alternative approaches, the impact of technologies, identification of primary risk drivers, and creation of executable acquisition strategies. The transformed Air Force business processes are enabled by iterative use of constructive and virtual modeling, simulation, and analysis together with information technology. These tools are applied collaboratively via a technical framework by all the affected stakeholders - warfighter, laboratory, product center, logistics center, test center, and primary contractor.
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Research on reverse logistics location under uncertainty environment based on grey prediction
NASA Astrophysics Data System (ADS)
Zhenqiang, Bao; Congwei, Zhu; Yuqin, Zhao; Quanke, Pan
This article constructs reverse logistic network based on uncertain environment, integrates the reverse logistics network and distribution network, and forms a closed network. An optimization model based on cost is established to help intermediate center, manufacturing center and remanufacturing center make location decision. A gray model GM (1, 1) is used to predict the product holdings of the collection points, and then prediction results are carried into the cost optimization model and a solution is got. Finally, an example is given to verify the effectiveness and feasibility of the model.
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Van Petegem, Stijn; Beyers, Wim; Brenning, Katrijn; Vansteenkiste, Maarten
2013-12-01
The present investigation focuses on the associations between adolescents' insecure attachment styles (i.e., anxiety and avoidance) and their autonomous functioning in family decision making. In line with recent insights in the construct of adolescent autonomy, we combined two perspectives on autonomy, differentiating between the degree of independent versus dependent functioning and the self-endorsed and pressuring motives underlying (in)dependent functioning. A longitudinal sample of 327 adolescents (age range = 13-20 years; 64 % girls) completed questionnaires on attachment to the mother and father and on both autonomy operationalisations on two measurement moments spanning a 1-year interval. Structural equation modeling showed that attachment avoidance generally was unrelated to the degree of independent decision making and the motives underlying independent decision making, but related to more pressuring motives for dependent decision making. Anxiety, on the other hand, was associated with a lower degree of independent decision making as well as with more pressuring motives for both independent and dependent decision making. Cross-lagged paths were generally in line with these findings. Theoretical implications are outlined in the discussion.
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Formal Representations of Eligibility Criteria: A Literature Review
Weng, Chunhua; Tu, Samson W.; Sim, Ida; Richesson, Rachel
2010-01-01
Standards-based, computable knowledge representations for eligibility criteria are increasingly needed to provide computer-based decision support for automated research participant screening, clinical evidence application, and clinical research knowledge management. We surveyed the literature and identified five aspects of eligibility criteria knowledge representations that contribute to the various research and clinical applications: the intended use of computable eligibility criteria, the classification of eligibility criteria, the expression language for representing eligibility rules, the encoding of eligibility concepts, and the modeling of patient data. We consider three of them (expression language, codification of eligibility concepts, and patient data modeling), to be essential constructs of a formal knowledge representation for eligibility criteria. The requirements for each of the three knowledge constructs vary for different use cases, which therefore should inform the development and choice of the constructs toward cost-effective knowledge representation efforts. We discuss the implications of our findings for standardization efforts toward sharable knowledge representation of eligibility criteria. PMID:20034594
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New perspectives for motivating better decisions in older adults
Strough, JoNell; de Bruin, Wändi Bruine; Peters, Ellen
2015-01-01
Decision-making competence in later adulthood is affected by declines in cognitive skills, and age-related changes in affect and experience can sometimes compensate. However, recent findings suggest that age-related changes in motivation also affect the extent to which adults draw from experience, affect, and deliberative skills when making decisions. To date, relatively little attention has been given to strategies for addressing age-related changes in motivation to promote better decisions in older adults. To address this limitation, we draw from diverse literatures to suggest promising intervention strategies for motivating older recipients’ motivation to make better decisions. We start by reviewing the life-span developmental literature, which suggests that older adults’ motivation to put effort into decisions depends on the perceived personal relevance of decisions as well as their self-efficacy (i.e., confidence in applying their ability and knowledge). Next, we discuss two approaches from the health intervention design literature, the mental models approach and the patient activation approach, which aim to improve motivation for decision making by improving personal relevance or by building self-efficacy or confidence to use new information and skills. Using examples from these literatures, we discuss how to construct interventions to motivate good decisions in later adulthood. PMID:26157398
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NASA Astrophysics Data System (ADS)
Sliva, Amy L.; Gorman, Joe; Voshell, Martin; Tittle, James; Bowman, Christopher
2016-05-01
The Dual Node Decision Wheels (DNDW) architecture concept was previously described as a novel approach toward integrating analytic and decision-making processes in joint human/automation systems in highly complex sociotechnical settings. In this paper, we extend the DNDW construct with a description of components in this framework, combining structures of the Dual Node Network (DNN) for Information Fusion and Resource Management with extensions on Rasmussen's Decision Ladder (DL) to provide guidance on constructing information systems that better serve decision-making support requirements. The DNN takes a component-centered approach to system design, decomposing each asset in terms of data inputs and outputs according to their roles and interactions in a fusion network. However, to ensure relevancy to and organizational fitment within command and control (C2) processes, principles from cognitive systems engineering emphasize that system design must take a human-centered systems view, integrating information needs and decision making requirements to drive the architecture design and capabilities of network assets. In the current work, we present an approach for structuring and assessing DNDW systems that uses a unique hybrid DNN top-down system design with a human-centered process design, combining DNN node decomposition with artifacts from cognitive analysis (i.e., system abstraction decomposition models, decision ladders) to provide work domain and task-level insights at different levels in an example intelligence, surveillance, and reconnaissance (ISR) system setting. This DNDW structure will ensure not only that the information fusion technologies and processes are structured effectively, but that the resulting information products will align with the requirements of human decision makers and be adaptable to different work settings .
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Overlapping Risky Decision-Making and Olfactory Processing Ability in HIV-Infected Individuals.
Jackson, Christopher; Rai, Narayan; McLean, Charlee K; Hipolito, Maria Mananita S; Hamilton, Flora Terrell; Kapetanovic, Suad; Nwulia, Evaristus A
2017-09-01
Given neuroimaging evidences of overlap in the circuitries for decision-making and olfactory processing, we examined the hypothesis that impairment in psychophysical tasks of olfaction would independently predict poor performances on Iowa Gambling Task (IGT), a laboratory task that closely mimics real-life decision-making, in a US cohort of HIV-infected (HIV+) individuals. IGT and psychophysical tasks of olfaction were administered to a Washington DC-based cohort of largely African American HIV+ subjects (N=100), and to a small number of demographically-matched non-HIV healthy controls (N=43) from a different study. Constructs of olfactory ability and decision-making were examined through confirmatory factor analysis (CFA). Structural equation models (SEMs) were used to evaluate the validity of the path relationship between these two constructs. The 100 HIV+ participants (56% female; 96% African Americans; median age = 48 years) had median CD4 count of 576 cells/μl and median HIV RNA viral load <48 copies per milliliter. Majority of HIV+ participants performed randomly throughout the course of IGT tasks, and failed to demonstrate a learning curve. Confirmatory factor analysis provided support for a unidimensional factor underlying poor performances on IGT. Nomological validity for correlations between olfactory ability and IGT performance was confirmed through SEM. Finally, factor scores of olfactory ability and IGT performance strongly predicted 6 months history of drug use, while olfaction additionally predicted hallucinogen use. This study suggests that combination of simple, office-based tasks of olfaction and decision-making may identify those HIV+ individuals who are more prone to risky decision-making. This finding may have significant clinical, public health value if joint impairments in olfaction and IGT task correlates with more decreased activity in brain regions relevant to decision-making.
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Veksler, Vladislav D.; Buchler, Norbou; Hoffman, Blaine E.; Cassenti, Daniel N.; Sample, Char; Sugrim, Shridat
2018-01-01
Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting. PMID:29867661
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A judgment and decision-making model for plant behavior.
Karban, Richard; Orrock, John L
2018-06-12
Recently plant biologists have documented that plants, like animals, engage in many activities that can be considered as behaviors, although plant biologists currently lack a conceptual framework to understand these processes. Borrowing the well-established framework developed by psychologists, we propose that plant behaviors can be constructively modeled by identifying four distinct components: 1) a cue or stimulus that provides information, 2) a judgment whereby the plant perceives and processes this informative cue, 3) a decision whereby the plant chooses among several options based on their relative costs and benefits, and 4) action. Judgment for plants can be determined empirically by monitoring signaling associated with electrical, calcium, or hormonal fluxes. Decision-making can be evaluated empirically by monitoring gene expression or differential allocation of resources. We provide examples of the utility of this judgment and decision-making framework by considering cases in which plants either successfully or unsuccessfully induced resistance against attacking herbivores. Separating judgment from decision-making suggests new analytical paradigms (i.e., Bayesian methods for judgment and economic utility models for decision-making). Following this framework, we propose an experimental approach to plant behavior that explicitly manipulates the stimuli provided to plants, uses plants that vary in sensory abilities, and examines how environmental context affects plant responses. The concepts and approaches that follow from the judgment and decision-making framework can shape how we study and understand plant-herbivore interactions, biological invasions, plant responses to climate change, and the susceptibility of plants to evolutionary traps. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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ERIC Educational Resources Information Center
Dou, Remy; Brewe, Eric; Zwolak, Justyna P.; Potvin, Geoff; Williams, Eric A.; Kramer, Laird H.
2016-01-01
The Modeling Instruction (MI) approach to introductory physics manifests significant increases in student conceptual understanding and attitudes toward physics. In light of these findings, we investigated changes in student self-efficacy while considering the construct's contribution to the career-decision making process. Students in the Fall 2014…
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ERIC Educational Resources Information Center
Lang, W. Steve; Wilkerson, Judy R.
2008-01-01
The construct of dispositions is defined in national standards, and colleges of education are required to assess candidate dispositions to meet accreditation requirements. Similarly, there is a need to review teacher dispositions in making hiring decisions about teachers, although this need may not yet be realized. Measurement is virtually…
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NASA Astrophysics Data System (ADS)
Yanchun, Wan; Qiucen, Chen
2017-11-01
Purchasing is an important part of export e-commerce of B2C, which plays an important role on risk and cost control in supply management. From the perspective of risk control, the paper construct a CVaR model for portfolio purchase. We select a heavy sales mobile power equipment from a typical B2C e-commerce export retailer as study sample. This study optimizes the purchasing strategy of this type of mobile power equipment. The research has some reference for similar enterprises in purchasing portfolio decision.
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AHP for Risk Management Based on Expected Utility Theory
NASA Astrophysics Data System (ADS)
Azuma, Rumiko; Miyagi, Hayao
This paper presents a model of decision-making considering the risk assessment. The conventional evaluation in AHP is considered to be a kind of utility. When dealing with the risk, however, it is necessary to consider the probability of damage. In order to take risk into decision-making problem, we construct AHP based on expected utility. The risk is considered as a related element of criterion rather than criterion itself. The expected utility is integrated, considering that satisfaction is positive utility and damage by risk is negative utility. Then, evaluation in AHP is executed using the expected utility.
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Models with Men and Women: Representing Gender in Dynamic Modeling of Social Systems.
Palmer, Erika; Wilson, Benedicte
2018-04-01
Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue.
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Patients' mental models and adherence to outpatient physical therapy home exercise programs.
Rizzo, Jon
2015-05-01
Within physical therapy, patient adherence usually relates to attending appointments, following advice, and/or undertaking prescribed exercise. Similar to findings for general medical adherence, patient adherence to physical therapy home exercise programs (HEP) is estimated between 35 and 72%. Adherence to HEPs is a multifactorial and poorly understood phenomenon, with no consensus regarding a common theoretical framework that best guides empirical or clinical efforts. Mental models, a construct used to explain behavior and decision-making in the social sciences, may serve as this framework. Mental models comprise an individual's tacit thoughts about how the world works. They include assumptions about new experiences and expectations for the future based on implicit comparisons between current and past experiences. Mental models play an important role in decision-making and guiding actions. This professional theoretical article discusses empirical research demonstrating relationships among mental models, prior experience, and adherence decisions in medical and physical therapy contexts. Specific issues related to mental models and physical therapy patient adherence are discussed, including the importance of articulation of patients' mental models, assessment of patients' mental models that relate to exercise program adherence, discrepancy between patient and provider mental models, and revision of patients' mental models in ways that enhance adherence. The article concludes with practical implications for physical therapists and recommendations for further research to better understand the role of mental models in physical therapy patient adherence behavior.
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Oladinrin, Olugbenga Timo; Ho, Christabel Man-Fong
2016-08-01
Several researchers have identified codes of ethics (CoEs) as tools that stimulate positive ethical behavior by shaping the organisational decision-making process, but few have considered the information needed for code implementation. Beyond being a legal and moral responsibility, ethical behavior needs to become an organisational priority, which requires an alignment process that integrates employee behavior with the organisation's ethical standards. This paper discusses processes for the responsible implementation of CoEs based on an extensive review of the literature. The internationally recognized European Foundation for Quality Management Excellence Model (EFQM model) is proposed as a suitable framework for assessing an organisation's ethical performance, including CoE embeddedness. The findings presented herein have both practical and research implications. They will encourage construction practitioners to shift their attention from ethical policies to possible enablers of CoE implementation and serve as a foundation for further research on ethical performance evaluation using the EFQM model. This is the first paper to discuss the model's use in the context of ethics in construction practice.
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Visual-spatial cognition in children using aided communication.
Stadskleiv, Kristine; Batorowicz, Beata; Massaro, Munique; van Balkom, Hans; von Tetzchner, Stephen
2018-03-01
Children with severe motor impairments are restricted in their manipulation and exploration of objects, but little is known about how such limitations influence cognitive development. This study investigated visual-constructional abilities in 75 children and adolescents, aged 5;0-15;11 (years;months), with severe speech impairments and no intellectual disabilities (aided group) and in 56 children and adolescents with typical development (reference group). Verbal comprehension, non-verbal reasoning, and visual-spatial perception were assessed with standardized tests. The task of the participants was to verbally instruct communication partners to make physical constructions identical to models that the partner could not see. In the aided group, 55.7% of the constructions were identical to the models participants described, compared to 91.3% in the reference group. In the aided group, test results explained 51.4% of the variance in construction errors. The results indicate that the participants' language skills were decisive for construction success. Visual-perceptual challenges were common among the aided communicators, and their instructions included little information about size and spatial relations. This may reflect less experience with object manipulation and construction than children with typical development, and using aided communication to instruct others to make three-dimensional constructions. The results imply a need for interventions that compensate for the lack of relevant experience.
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NASA Astrophysics Data System (ADS)
Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim
2017-10-01
Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.
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NASA Astrophysics Data System (ADS)
Spitulnik, Michele Wisnudel
Science education reforms advocate inquiry as a way to build explanations and make informed decisions. Based on this call this dissertation (1) defines flexible scientific understanding by elaborating on content, inquiry and epistemic understandings; (2) describes an inquiry based unit that integrates dynamic modeling software; (3) examines students' understandings as they construct models; and (4) identifies instructional strategies that support inquiry and model building. A curriculum unit was designed to engage students in inquiry by identifying problems and constructing models to represent, explain and predict phenomena. Ninth grade students in a public mid-western high school worked in teams of 2-3 to ask questions, find information and reflect on the purposes of models. Data sources including classroom video, observations, interviews, student models and handouts were used to formulate cases that examine how two groups construct understanding. A teacher case study identifies the teaching strategies that support understanding. Categories within content, inquiry and epistemic understandings were used to analyze student understandings and teaching supports. The findings demonstrate that students can build flexible understanding by constructing models. Students built: (1) content understanding by identifying key ideas and building relationships and explanations of phenomena; (2) inquiry understanding by defining problems, constructing models and developing positions; and (3) epistemic understanding by describing the purposes of models as generalizing phenomena, testing hypotheses and making predictions. However, students demonstrated difficulty in using evidence to defend scientific arguments. Strategies that support flexible understanding were also identified. Content supports include: setting expectations for explanations; using examples to illustrate explanations; modeling questions; and providing feedback that prompts detailed explanations. Supports for inquiry are setting expectations for data gathering; using examples that illustrate model building; modeling the development of an argument; and providing feedback to promote coherent models. Epistemic supports include: using examples to illustrate purposes and assumptions within models, and providing feedback as students evaluate their models. The dissertation demonstrates that teaching strategies impact student understanding but are challenging to implement. When strategies are not used, students do not necessarily construct desired outcomes such as, using evidence to support arguments.
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NASA Astrophysics Data System (ADS)
Ivanova, Nina; Ganzha, Olga
2017-10-01
In article the technique of adoption of the design decision on placement of eco-friendly routes for the purpose of use is proved by steady transport, the technique of the choice of the optimal solution of development of local bicycle network of routes is offered and developed structural model of the choice of options of placement of cycle routes in system of street road system and recreational zones in the conditions of sustainable development of the city. The theoretical and practical experience of construction of cycle routes in Russia and abroad is generalized; the method of the analysis of hierarchies which allows to carry out the choice of the design decision taking into account different groups of factors is used; the structural model at the choice of options of placement of bicycle tracks on the example of linear structure of the coastal city is developed; experimental design in the territory of streets of Volgograd is executed. The offered structural model is used in development of design offers of construction of bicycle tracks for the streets of Volgograd providing to inhabitants and city visitors more attractive, healthy and cheap option of movement to place of work, training, rest and entertainments.
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Potential of Progressive Construction Systems in Slovakia
NASA Astrophysics Data System (ADS)
Kozlovska, Maria; Spisakova, Marcela; Mackova, Daniela
2017-10-01
Construction industry is a sector with rapid development. Progressive technologies of construction and new construction materials also called modern methods of construction (MMC) are developed constantly. MMC represent the adoption of construction industrialisation and the use of prefabrication of components in building construction. One of these modern methods is also system Varianthaus, which is based on, insulated concrete forms principle and provides complete production plant for wall, ceiling and roof elements for a high thermal insulation house construction. Another progressive construction system is EcoB, which represents an insulated precast concrete panel based on combination of two layers, insulation and concrete, produced in a factory as a whole. Both modern methods of construction are not yet known and wide-spread in the Slovak construction market. The aim of this paper is focused on demonstration of MMC using potential in Slovakia. MMC potential is proved based on comparison of the selected parameters of construction process - construction costs and construction time. The subject of this study is family house modelled in three material variants - masonry construction (as a representative of traditional methods of construction), Varianthaus and EcoB (as the representatives of modern methods of construction). The results of this study provide the useful information in decision-making process for potential investors of construction.
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Barbieri, Christopher E; Cha, Eugene K; Chromecki, Thomas F; Dunning, Allison; Lotan, Yair; Svatek, Robert S; Scherr, Douglas S; Karakiewicz, Pierre I; Sun, Maxine; Mazumdar, Madhu; Shariat, Shahrokh F
2012-03-01
• To employ decision curve analysis to determine the impact of nuclear matrix protein 22 (NMP22) on clinical decision making in the detection of bladder cancer using data from a prospective trial. • The study included 1303 patients at risk for bladder cancer who underwent cystoscopy, urine cytology and measurement of urinary NMP22 levels. • We constructed several prediction models to estimate risk of bladder cancer. The base model was generated using patient characteristics (age, gender, race, smoking and haematuria); cytology and NMP22 were added to the base model to determine effects on predictive accuracy. • Clinical net benefit was calculated by summing the benefits and subtracting the harms and weighting these by the threshold probability at which a patient or clinician would opt for cystoscopy. • In all, 72 patients were found to have bladder cancer (5.5%). In univariate analyses, NMP22 was the strongest predictor of bladder cancer presence (predictive accuracy 71.3%), followed by age (67.5%) and cytology (64.3%). • In multivariable prediction models, NMP22 improved the predictive accuracy of the base model by 8.2% (area under the curve 70.2-78.4%) and of the base model plus cytology by 4.2% (area under the curve 75.9-80.1%). • Decision curve analysis revealed that adding NMP22 to other models increased clinical benefit, particularly at higher threshold probabilities. • NMP22 is a strong, independent predictor of bladder cancer. • Addition of NMP22 improves the accuracy of standard predictors by a statistically and clinically significant margin. • Decision curve analysis suggests that integration of NMP22 into clinical decision making helps avoid unnecessary cystoscopies, with minimal increased risk of missing a cancer. © 2011 THE AUTHORS. BJU INTERNATIONAL © 2011 BJU INTERNATIONAL.
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NASA Astrophysics Data System (ADS)
Meng, Fanyong
2018-02-01
Triangular fuzzy reciprocal preference relations (TFRPRs) are powerful tools to denoting decision-makers' fuzzy judgments, which permit the decision-makers to apply triangular fuzzy ratio rather than real numbers to express their judgements. Consistency analysis is one of the most crucial issues in preference relations that can guarantee the reasonable ranking order. However, all previous consistency concepts cannot well address this type of preference relations. Based on the operational laws on triangular fuzzy numbers, this paper introduces an additive consistency concept for TFRPRs by using quasi TFRPRs, which can be seen as a natural extension of the crisp case. Using this consistency concept, models to judging the additive consistency of TFRPRs and to estimating missing values in complete TFRPRs are constructed. Then, an algorithm to decision-making with TFRPRs is developed. Finally, two numerical examples are offered to illustrate the application of the proposed procedure, and comparison analysis is performed.
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Linking guidelines to Electronic Health Record design for improved chronic disease management.
Barretto, Sistine A; Warren, Jim; Goodchild, Andrew; Bird, Linda; Heard, Sam; Stumptner, Markus
2003-01-01
The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and workflow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR.
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Linking Guidelines to Electronic Health Record Design for Improved Chronic Disease Management
Barretto, Sistine A.; Warren, Jim; Goodchild, Andrew; Bird, Linda; Heard, Sam; Stumptner, Markus
2003-01-01
The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and work-flow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR. PMID:14728135
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Decisions on new product development under uncertainties
NASA Astrophysics Data System (ADS)
Huang, Yeu-Shiang; Liu, Li-Chen; Ho, Jyh-Wen
2015-04-01
In an intensively competitive market, developing a new product has become a valuable strategy for companies to establish their market positions and enhance their competitive advantages. Therefore, it is essential to effectively manage the process of new product development (NPD). However, since various problems may arise in NPD projects, managers should set up some milestones and subsequently construct evaluative mechanisms to assess their feasibility. This paper employed the approach of Bayesian decision analysis to deal with the two crucial uncertainties for NPD, which are the future market share and the responses of competitors. The proposed decision process can provide a systematic analytical procedure to determine whether an NPD project should be continued or not under the consideration of whether effective usage is being made of the organisational resources. Accordingly, the proposed decision model can assist the managers in effectively addressing the NPD issue under the competitive market.
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[Ethical issues in nursing leadership].
Wang, Shu-Fang; Hung, Chich-Hsiu
2005-10-01
Social transition causes shifts and changes in the relationship between health professionals and their patients. In their professional capacity, it is important today for nurses to handle ethical dilemmas properly, in a manner that fosters an ethical environment. This article investigates the ethical concerns and decision processes of nurses from a knowledge construction perspective, and examines such issues as patient needs, staff perceptions, organizational benefits, and professional image. The decision making methods commonly used when facing ethical dilemma explored in this study include the traditional problem solving, nursing process, MORAL model, and Murphy's methods. Although decision making for ethical dilemmas is governed by no universal rule, nurses are responsible to try to foster a trusting relationship between employee and employer, health care providers and patients, and the organization and colleagues. When decision making on ethical dilemmas is properly executed quality care will be delivered and malpractice can be reduced.
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Spatial decision support system to evaluate crop residue energy potential by anaerobic digestion.
Escalante, Humberto; Castro, Liliana; Gauthier-Maradei, Paola; Rodríguez De La Vega, Reynel
2016-11-01
Implementing anaerobic digestion (AD) in energy production from crop residues requires development of decision tools to assess its feasibility and sustainability. A spatial decision support system (SDSS) was constructed to assist decision makers to select appropriate feedstock according to biomethanation potential, identify the most suitable location for biogas facilities, determine optimum plant capacity and supply chain, and evaluate associated risks and costs. SDSS involves a spatially explicit analysis, fuzzy multi-criteria analysis, and statistical and optimization models. The tool was validated on seven crop residues located in Santander, Colombia. For example, fique bagasse generates about 0.21millionm(3)CH4year(-1) (0.329m(3)CH4kg(-1) volatile solids) with a minimum profitable plant of about 2000tonyear(-1) and an internal rate of return of 10.5%. SDSS can be applied to evaluate other biomass resources, availability periods, and co-digestion potential. Copyright © 2016. Published by Elsevier Ltd.
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Stratification of Recanalization for Patients with Endovascular Treatment of Intracranial Aneurysms
Ogilvy, Christopher S.; Chua, Michelle H.; Fusco, Matthew R.; Reddy, Arra S.; Thomas, Ajith J.
2015-01-01
Background With increasing utilization of endovascular techniques in the treatment of both ruptured and unruptured intracranial aneurysms, the issue of obliteration efficacy has become increasingly important. Objective Our goal was to systematically develop a comprehensive model for predicting retreatment with various types of endovascular treatment. Methods We retrospectively reviewed medical records that were prospectively collected for 305 patients who received endovascular treatment for intracranial aneurysms from 2007 to 2013. Multivariable logistic regression was performed on candidate predictors identified by univariable screening analysis to detect independent predictors of retreatment. A composite risk score was constructed based on the proportional contribution of independent predictors in the multivariable model. Results Size (>10 mm), aneurysm rupture, stent assistance, and post-treatment degree of aneurysm occlusion were independently associated with retreatment while intraluminal thrombosis and flow diversion demonstrated a trend towards retreatment. The Aneurysm Recanalization Stratification Scale was constructed by assigning the following weights to statistically and clinically significant predictors. Aneurysm-specific factors: Size (>10 mm), 2 points; rupture, 2 points; presence of thrombus, 2 points. Treatment-related factors: Stent assistance, -1 point; flow diversion, -2 points; Raymond Roy 2 occlusion, 1 point; Raymond Roy 3 occlusion, 2 points. This scale demonstrated good discrimination with a C-statistic of 0.799. Conclusion Surgical decision-making and patient-centered informed consent require comprehensive and accessible information on treatment efficacy. We have constructed the Aneurysm Recanalization Stratification Scale to enhance this decision-making process. This is the first comprehensive model that has been developed to quantitatively predict the risk of retreatment following endovascular therapy. PMID:25621984
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Cyterski, Mike; Brooks, Wesley; Galvin, Mike; Wolfe, Kurt; Carvin, Rebecca; Roddick, Tonia; Fienen, Mike; Corsi, Steve
2014-01-01
Virtual Beach version 3 (VB3) is a decision support tool that constructs site-specific statistical models to predict fecal indicator bacteria (FIB) concentrations at recreational beaches. VB3 is primarily designed for beach managers responsible for making decisions regarding beach closures or the issuance of swimming advisories due to pathogen contamination. However, researchers, scientists, engineers, and students interested in studying relationships between water quality indicators and ambient environmental conditions will find VB3 useful. VB3 reads input data from a text file or Excel document, assists the user in preparing the data for analysis, enables automated model selection using a wide array of possible model evaluation criteria, and provides predictions using a chosen model parameterized with new data. With an integrated mapping component to determine the geographic orientation of the beach, the software can automatically decompose wind/current/wave speed and magnitude information into along-shore and onshore/offshore components for use in subsequent analyses. Data can be examined using simple scatter plots to evaluate relationships between the response and independent variables (IVs). VB3 can produce interaction terms between the primary IVs, and it can also test an array of transformations to maximize the linearity of the relationship The software includes search routines for finding the "best" models from an array of possible choices. Automated censoring of statistical models with highly correlated IVs occurs during the selection process. Models can be constructed either using previously collected data or forecasted environmental information. VB3 has residual diagnostics for regression models, including automated outlier identification and removal using DFFITs or Cook's Distances.
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An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health
Mancy, Rebecca; Brock, Patrick M.; Kao, Rowland R.
2017-01-01
Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature. PMID:29021983
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An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health.
Mancy, Rebecca; Brock, Patrick M; Kao, Rowland R
2017-01-01
Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.
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Evolving optimised decision rules for intrusion detection using particle swarm paradigm
NASA Astrophysics Data System (ADS)
Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.
2012-12-01
The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.
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A critical narrative analysis of shared decision-making in acute inpatient mental health care.
Stacey, Gemma; Felton, Anne; Morgan, Alastair; Stickley, Theo; Willis, Martin; Diamond, Bob; Houghton, Philip; Johnson, Beverley; Dumenya, John
2016-01-01
Shared decision-making (SDM) is a high priority in healthcare policy and is complementary to the recovery philosophy in mental health care. This agenda has been operationalised within the Values-Based Practice (VBP) framework, which offers a theoretical and practical model to promote democratic interprofessional approaches to decision-making. However, these are limited by a lack of recognition of the implications of power implicit within the mental health system. This study considers issues of power within the context of decision-making and examines to what extent decisions about patients' care on acute in-patient wards are perceived to be shared. Focus groups were conducted with 46 mental health professionals, service users, and carers. The data were analysed using the framework of critical narrative analysis (CNA). The findings of the study suggested each group constructed different identity positions, which placed them as inside or outside of the decision-making process. This reflected their view of themselves as best placed to influence a decision on behalf of the service user. In conclusion, the discourse of VBP and SDM needs to take account of how differentials of power and the positioning of speakers affect the context in which decisions take place.
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Learning a Health Knowledge Graph from Electronic Medical Records.
Rotmensch, Maya; Halpern, Yoni; Tlimat, Abdulhakim; Horng, Steven; Sontag, David
2017-07-20
Demand for clinical decision support systems in medicine and self-diagnostic symptom checkers has substantially increased in recent years. Existing platforms rely on knowledge bases manually compiled through a labor-intensive process or automatically derived using simple pairwise statistics. This study explored an automated process to learn high quality knowledge bases linking diseases and symptoms directly from electronic medical records. Medical concepts were extracted from 273,174 de-identified patient records and maximum likelihood estimation of three probabilistic models was used to automatically construct knowledge graphs: logistic regression, naive Bayes classifier and a Bayesian network using noisy OR gates. A graph of disease-symptom relationships was elicited from the learned parameters and the constructed knowledge graphs were evaluated and validated, with permission, against Google's manually-constructed knowledge graph and against expert physician opinions. Our study shows that direct and automated construction of high quality health knowledge graphs from medical records using rudimentary concept extraction is feasible. The noisy OR model produces a high quality knowledge graph reaching precision of 0.85 for a recall of 0.6 in the clinical evaluation. Noisy OR significantly outperforms all tested models across evaluation frameworks (p < 0.01).
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Computational mate choice: theory and empirical evidence.
Castellano, Sergio; Cadeddu, Giorgia; Cermelli, Paolo
2012-06-01
The present review is based on the thesis that mate choice results from information-processing mechanisms governed by computational rules and that, to understand how females choose their mates, we should identify which are the sources of information and how they are used to make decisions. We describe mate choice as a three-step computational process and for each step we present theories and review empirical evidence. The first step is a perceptual process. It describes the acquisition of evidence, that is, how females use multiple cues and signals to assign an attractiveness value to prospective mates (the preference function hypothesis). The second step is a decisional process. It describes the construction of the decision variable (DV), which integrates evidence (private information by direct assessment), priors (public information), and value (perceived utility) of prospective mates into a quantity that is used by a decision rule (DR) to produce a choice. We make the assumption that females are optimal Bayesian decision makers and we derive a formal model of DV that can explain the effects of preference functions, mate copying, social context, and females' state and condition on the patterns of mate choice. The third step of mating decision is a deliberative process that depends on the DRs. We identify two main categories of DRs (absolute and comparative rules), and review the normative models of mate sampling tactics associated to them. We highlight the limits of the normative approach and present a class of computational models (sequential-sampling models) that are based on the assumption that DVs accumulate noisy evidence over time until a decision threshold is reached. These models force us to rethink the dichotomy between comparative and absolute decision rules, between discrimination and recognition, and even between rational and irrational choice. Since they have a robust biological basis, we think they may represent a useful theoretical tool for behavioural ecologist interested in integrating proximate and ultimate causes of mate choice. Copyright © 2012 Elsevier B.V. All rights reserved.
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Constructing graph models for software system development and analysis
NASA Astrophysics Data System (ADS)
Pogrebnoy, Andrey V.
2017-01-01
We propose a concept for creating the instrumentation for functional and structural decisions rationale during the software system (SS) development. We propose to develop SS simultaneously on two models - functional (FM) and structural (SM). FM is a source code of the SS. Adequate representation of the FM in the form of a graph model (GM) is made automatically and called SM. The problem of creating and visualizing GM is considered from the point of applying it as a uniform platform for the adequate representation of the SS source code. We propose three levels of GM detailing: GM1 - for visual analysis of the source code and for SS version control, GM2 - for resources optimization and analysis of connections between SS components, GM3 - for analysis of the SS functioning in dynamics. The paper includes examples of constructing all levels of GM.
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The use of cognitive ability measures as explanatory variables in regression analysis.
Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J
2012-12-01
Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.
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Hadi, Azlihanis Abdul; Naing, Nyi Nyi; Daud, Aziah; Nordin, Rusli
2006-11-01
This study was conducted to assess the reliability and construct validity of the Malay version of Job Content Questionnaire (JCQ) among secondary school teachers in Kota Bharu, Kelantan. A total of 68 teachers consented to participate in the study and were administered the Malay version of JCQ. Reliability was determined using Cronbach's alpha for internal consistency whilst construct validity was assessed using factor analysis. The results indicated that Cronbach's alpha coefficients revealed decision latitude (0.75), psychological job demand (0.50) and social support (0.84). Factor analysis showed three meaningful common factors that could explain the construct of Karasek's demand-control-social support model. The study suggests the JCQ scales are reliable and valid tools for assessing job stress in school teachers.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Greitzer, Frank L.; Podmore, Robin
2008-11-17
The focus of the present study is on improved training approaches to accelerate learning and improved methods for analyzing effectiveness of tools within a high-fidelity power grid simulated environment. A theory-based model has been developed to document and understand the mental processes that an expert power system operator uses when making critical decisions. The theoretical foundation for the method is based on the concepts of situation awareness, the methods of cognitive task analysis, and the naturalistic decision making (NDM) approach of Recognition Primed Decision Making. The method has been systematically explored and refined as part of a capability demonstration ofmore » a high-fidelity real-time power system simulator under normal and emergency conditions. To examine NDM processes, we analyzed transcripts of operator-to-operator conversations during the simulated scenario to reveal and assess NDM-based performance criteria. The results of the analysis indicate that the proposed framework can be used constructively to map or assess the Situation Awareness Level of the operators at each point in the scenario. We can also identify the mental models and mental simulations that the operators employ at different points in the scenario. This report documents the method, describes elements of the model, and provides appendices that document the simulation scenario and the associated mental models used by operators in the scenario.« less
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NASA Astrophysics Data System (ADS)
Sahul Hameed, Ruzanna; Thiruchelvam, Sivadass; Nasharuddin Mustapha, Kamal; Che Muda, Zakaria; Mat Husin, Norhayati; Ezanee Rusli, Mohd; Yong, Lee Choon; Ghazali, Azrul; Itam, Zarina; Hakimie, Hazlinda; Beddu, Salmia; Liyana Mohd Kamal, Nur
2016-03-01
This paper proposes a conceptual framework to compare criteria/factor that influence the supplier selection. A mixed methods approach comprising qualitative and quantitative survey will be used. The study intend to identify and define the metrics that key stakeholders at Public Works Department (PWD) believed should be used for supplier. The outcomes would foresee the possible initiatives to bring procurement in PWD to a strategic level. The results will provide a deeper understanding of drivers for supplier’s selection in the construction industry. The obtained output will benefit many parties involved in the supplier selection decision-making. The findings provides useful information and greater understanding of the perceptions that PWD executives hold regarding supplier selection and the extent to which these perceptions are consistent with findings from prior studies. The findings from this paper can be utilized as input for policy makers to outline any changes in the current procurement code of practice in order to enhance the degree of transparency and integrity in decision-making.
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Wheatley, Catherine M; Davies, Emma L; Dawes, Helen
2018-03-01
The health benefits of exercise in school are recognized, yet physical activity continues to decline during early adolescence despite numerous interventions. In this study, we investigated whether the prototype willingness model, an account of adolescent decision making that includes both reasoned behavioral choices and unplanned responses to social environments, might improve understanding of physical activity in school. We conducted focus groups with British pupils aged 12 to 13 years and used deductive thematic analysis to search for themes relating to the model. Participants described reasoned decisions about physical activity outside school and unplanned choices to be inactive during break, in response to social contexts described as more "judgmental" than in primary school. Social contexts appeared characterized by anxiety about competence, negative peer evaluation, and inactive playground norms. The prototype willingness model might more fully explain physical activity in school than reasoned behavioral models alone, indicating potential for interventions targeting anxieties about playground social environments.
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Application of Spatial Models in Making Location Decisions of Wind Power Plant in Poland
NASA Astrophysics Data System (ADS)
Płuciennik, Monika; Hełdak, Maria; Szczepański, Jakub; Patrzałek, Ciechosław
2017-10-01
In this paper,we explore the process of making decisions on the location of wind power plants in Poland in connection with a gradually increasing consumption of energy from renewable sources and the increase of impact problems of such facilities. The location of new wind power plants attracts much attention, and both positive and negative publicity. Visualisations can be of assistance when choosing the most advantageous location for a plant, as three-dimensional variants of the facility to be constructed can be prepared. This work involves terrestrial laser scanning of an existing wind power plant and 3D modelling followed by. The model could be subsequently used in visualisation of real terrain, with special purpose in local land development plan. This paper shows a spatial model of a wind power plant as a new element of a capital investment process in Poland. Next, we incorporate the model into an undeveloped site, intended for building a wind farm, subject to the requirements for location of power plants.
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Determinants of tetanus toxoid immunization in pregnancy in rural Bihar.
Thind, Amardeep
2005-04-01
In order to increase the uptake of tetanus toxoid (TT) vaccination, we need to understand the factors that underlie the decision of the pregnant woman to undergo vaccination, especially in rural areas, where 75% of India's population resides. This paper constructs a model from a data-set of 2398 women in order to understand the determinants ofTTvaccine immunization by women during their most recent pregnancy and applies it to the National Family Health Survey-2 data. The object of the model is to predict the likelyhood of a pregnant woman receiving the recommended two doses of TT vaccine subject to other factors such as birth order, maternal education, prenatal care provider, household standard of living, health-care-seeking decision-maker and service availability. Policy implications of these findings are discussed.
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2008-06-01
1. Input........................................................................................ 21 2. Team Knowledge Base Construction...awareness. Team cognition differs from individual cognition. To effectively perform as a team, each member must share knowledge and understand his/her...sufficient to achieve situational awareness for decision-making or creation of a product. Knowledge interoperability is the identification, collection
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Decision Model for Forecasting Projected Naval Enlisted Reserve Attainments
2008-12-01
Command CM Construction Mechanic CS Culinary Specialist CTA Cryptologic Technician - Administrative CTI Cryptologic Technician - Interpretive...services are utilized to compile databases of active duty and reserve accession and loss Category Arts and Photography Journalist (JO) Photographer’s...MM) Mineman (MN) Torpedoman’s Mate (TM) Food, Restaurant, and Lodging Culinary Specialist (CS) Human Resources Navy Counselor (NC) Personnelman (PN
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ERIC Educational Resources Information Center
Huang, Tony Cheng-Kui; Huang, Chih-Hong
2010-01-01
With advances in information and network technologies, lots of data have been digitized to reveal information for users by the construction of Web sites. Unfortunately, they are both overloading and overlapping in Internet so that users cannot distinguish their quality. To address this issue in education, Hwang, Huang, and Tseng proposed a group…
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Project Canada West. Canadian Urban Dynamics: A Model for Student Involvement in the Urban Setting.
ERIC Educational Resources Information Center
Western Curriculum Project on Canada Studies, Edmonton (Alberta).
This is a progress report of a project in the process of developing an interdisciplinary secondary school curriculum on the Canadian urban environment. The primary goal is to encourage constructive involvement in urban life and community decision-making, and develop a personal and social competence that will engender a greater commitment to the…
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ERIC Educational Resources Information Center
Gojkošek, Mihael; Sliško, Josip; Planinšic, Gorazd
2013-01-01
The transfer of knowledge is considered to be a fundamental goal of education; therefore, knowing and understanding the conditions that influence the efficiency of the transfer from learning activity to problem solving play a decisive role in the improvement of science education. In this article, the results of a study of 196 high school students'…
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Karmarkar, Taruja D; Maurer, Anne; Parks, Michael L; Mason, Thomas; Bejinez-Eastman, Ana; Harrington, Melvyn; Morgan, Randall; O'Connor, Mary I; Wood, James E; Gaskin, Darrell J
2017-12-01
Disparities in the presentation of knee osteoarthritis (OA) and in the utilization of treatment across sex, racial, and ethnic groups in the United States are well documented. We used a Markov model to calculate lifetime costs of knee OA treatment. We then used the model results to compute costs of disparities in treatment by race, ethnicity, sex, and socioeconomic status. We used the literature to construct a Markov Model of knee OA and publicly available data to create the model parameters and patient populations of interest. An expert panel of physicians, who treated a large number of patients with knee OA, constructed treatment pathways. Direct costs were based on the literature and indirect costs were derived from the Medical Expenditure Panel Survey. We found that failing to obtain effective treatment increased costs and limited benefits for all groups. Delaying treatment imposed a greater cost across all groups and decreased benefits. Lost income because of lower labor market productivity comprised a substantial proportion of the lifetime costs of knee OA. Population simulations demonstrated that as the diversity of the US population increases, the societal costs of racial and ethnic disparities in treatment utilization for knee OA will increase. Our results show that disparities in treatment of knee OA are costly. All stakeholders involved in treatment decisions for knee OA patients should consider costs associated with delaying and forgoing treatment, especially for disadvantaged populations. Such decisions may lead to higher costs and worse health outcomes.
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McKee, Gregory J; Goodhue, Rachael E; Zalom, Frank G; Carter, Colin A; Chalfant, James A
2009-01-01
In agriculture, relatively few efficacious control measures may be available for an invasive pest. In the case of a new insect pest, insecticide use decisions are affected by regulations associated with its registration, insect population dynamics, and seasonal market price cycles. We assess the costs and benefits of environmental regulations designed to regulate insecticide applications on an invasive species. We construct a bioeconomic model, based on detailed scientific data, of management decisions for a specific invasion: greenhouse whiteflies in California-grown strawberries. The empirical model integrates whitefly population dynamics, the effect of whitefly feeding on strawberry yields, and weekly strawberry price. We use the model to assess the optimality of alternative treatment programs on a simulated greenhouse whitefly population. Our results show that regulations may lead growers to "under-spray" when placed in an economic context, and provide some general lessons about the design of optimal invasive species control policies.
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TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees.
Muhlbacher, Thomas; Linhardt, Lorenz; Moller, Torsten; Piringer, Harald
2018-01-01
Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.
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Interval-valued distributed preference relation and its application to group decision making
Liu, Yin; Xue, Min; Chang, Wenjun; Yang, Shanlin
2018-01-01
As an important way to help express the preference relation between alternatives, distributed preference relation (DPR) can represent the preferred, non-preferred, indifferent, and uncertain degrees of one alternative over another simultaneously. DPR, however, is unavailable in some situations where a decision maker cannot provide the precise degrees of one alternative over another due to lack of knowledge, experience, and data. In this paper, to address this issue, we propose interval-valued DPR (IDPR) and present its properties of validity and normalization. Through constructing two optimization models, an IDPR matrix is transformed into a score matrix to facilitate the comparison between any two alternatives. The properties of the score matrix are analyzed. To guarantee the rationality of the comparisons between alternatives derived from the score matrix, the additive consistency of the score matrix is developed. In terms of these, IDPR is applied to model and solve multiple criteria group decision making (MCGDM) problem. Particularly, the relationship between the parameters for the consistency of the score matrix associated with each decision maker and those for the consistency of the score matrix associated with the group of decision makers is analyzed. A manager selection problem is investigated to demonstrate the application of IDPRs to MCGDM problems. PMID:29889871
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Phillips, Mark H., E-mail: markp@u.washington.ed; Smith, Wade P.; Parvathaneni, Upendra
2011-03-15
Purpose: To determine under what conditions positron emission tomography (PET) imaging will be useful in decisions regarding the use of radiotherapy for the treatment of clinically occult lymph node metastases in head-and-neck cancer. Methods and Materials: A decision model of PET imaging and its downstream effects on radiotherapy outcomes was constructed using an influence diagram. This model included the sensitivity and specificity of PET, as well as the type and stage of the primary tumor. These parameters were varied to determine the optimal strategy for imaging and therapy for different clinical situations. Maximum expected utility was the metric by whichmore » different actions were ranked. Results: For primary tumors with a low probability of lymph node metastases, the sensitivity of PET should be maximized, and 50 Gy should be delivered if PET is positive and 0 Gy if negative. As the probability for lymph node metastases increases, PET imaging becomes unnecessary in some situations, and the optimal dose to the lymph nodes increases. The model needed to include the causes of certain health states to predict current clinical practice. Conclusion: The model demonstrated the ability to reproduce expected outcomes for a range of tumors and provided recommendations for different clinical situations. The differences between the optimal policies and current clinical practice are likely due to a disparity between stated clinical decision processes and actual decision making by clinicians.« less
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Structure and Style in Career Decision Making.
ERIC Educational Resources Information Center
Kortas, Linda; And Others
1992-01-01
The Career Decision Scale, Assessment of Career Decision Making, and Cognitive Differentiation Grid were administered to 598 community college students. Results indicated a relationship between decision-making styles and vocational construct structure. Poorly developed vocational schemas predispose individuals toward dependent and intuitive…
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Schoorel, E N C; Vankan, E; Scheepers, H C J; Augustijn, B C C; Dirksen, C D; de Koning, M; van Kuijk, S M J; Kwee, A; Melman, S; Nijhuis, J G; Aardenburg, R; de Boer, K; Hasaart, T H M; Mol, B W J; Nieuwenhuijze, M; van Pampus, M G; van Roosmalen, J; Roumen, F J M E; de Vries, R; Wouters, M G A J; van der Weijden, T; Hermens, R P M G
2014-01-01
To develop a patient decision aid (PtDA) for mode of delivery after caesarean section that integrates personalised prediction of vaginal birth after caesarean (VBAC) with the elicitation of patient preferences and evidence-based information. A PtDA was developed and pilot tested using the International Patients Decision Aid Standards (IPDAS) criteria. Obstetric health care in the Netherlands. A multidisciplinary steering group, an expert panel, and 25 future users of the PtDA, i.e. women with a previous caesarean section. The development consisted of a construction phase (definition of scope and purpose, and selection of content, framework, and format) and a pilot testing phase by interview. The process was supervised by a multidisciplinary steering group. Usability, clarity, and relevance. The construction phase resulted in a booklet including unbiased balanced information on mode of birth after caesarean section, a preference elicitation exercise, and tailored risk information, including a prediction model for successful VBAC. During pilot testing, visualisation of risks and clarity formed the main basis for revisions. Pilot testing showed the availability of tailored structured information to be the main factor involving women in decision-making. The PtDA meets 39 out of 50 IPDAS criteria (78%): 23 out of 23 criteria for content (100%) and 16 out of 20 criteria for the development process (80%). Criteria for effectiveness (n = 7) were not evaluated. An evidence-based PtDA was developed, with the probability of successful VBAC and the availability of structured information as key items. It is likely that the PtDA enhances the quality of decision-making on mode of birth after caesarean section. © 2013 Royal College of Obstetricians and Gynaecologists.
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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.
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Integrating the social sciences to understand human-water dynamics
NASA Astrophysics Data System (ADS)
Carr, G.; Kuil, L., Jr.
2017-12-01
Many interesting and exciting socio-hydrological models have been developed in recent years. Such models often aim to capture the dynamic interplay between people and water for a variety of hydrological settings. As such, peoples' behaviours and decisions are brought into the models as drivers of and/or respondents to the hydrological system. To develop and run such models over a sufficiently long time duration to observe how the water-human system evolves the human component is often simplified according to one or two key behaviours, characteristics or decisions (e.g. a decision to move away from a drought or flood area; a decision to pump groundwater, or a decision to plant a less water demanding crop). To simplify the social component, socio-hydrological modellers often pull knowledge and understanding from existing social science theories. This requires them to negotiate complex territory, where social theories may be underdeveloped, contested, dynamically evolving, or case specific and difficult to generalise or upscale. A key question is therefore, how can this process be supported so that the resulting socio-hydrological models adequately describe the system and lead to meaningful understanding of how and why it behaves as it does? Collaborative interdisciplinary research teams that bring together social and natural scientists are likely to be critical. Joint development of the model framework requires specific attention to clarification to expose all underlying assumptions, constructive discussion and negotiation to reach agreement on the modelled system and its boundaries. Mutual benefits to social scientists can be highlighted, i.e. socio-hydrological work can provide insights for further exploring and testing social theories. Collaborative work will also help ensure underlying social theory is made explicit, and may identify ways to include and compare multiple theories. As socio-hydrology progresses towards supporting policy development, approaches that brings in stakeholders and non-scientist participants to develop the conceptual modelling framework will become essential. They are also critical for fully understanding human-water dynamics.
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Extension of Companion Modeling Using Classification Learning
NASA Astrophysics Data System (ADS)
Torii, Daisuke; Bousquet, François; Ishida, Toru
Companion Modeling is a methodology of refining initial models for understanding reality through a role-playing game (RPG) and a multiagent simulation. In this research, we propose a novel agent model construction methodology in which classification learning is applied to the RPG log data in Companion Modeling. This methodology enables a systematic model construction that handles multi-parameters, independent of the modelers ability. There are three problems in applying classification learning to the RPG log data: 1) It is difficult to gather enough data for the number of features because the cost of gathering data is high. 2) Noise data can affect the learning results because the amount of data may be insufficient. 3) The learning results should be explained as a human decision making model and should be recognized by the expert as being the result that reflects reality. We realized an agent model construction system using the following two approaches: 1) Using a feature selction method, the feature subset that has the best prediction accuracy is identified. In this process, the important features chosen by the expert are always included. 2) The expert eliminates irrelevant features from the learning results after evaluating the learning model through a visualization of the results. Finally, using the RPG log data from the Companion Modeling of agricultural economics in northeastern Thailand, we confirm the capability of this methodology.
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The complex contribution of sociodemographics to decision-making power in gay male couples
Perry, Nicholas S.; Huebner, David M.; Baucom, Brian R. W.; Hoff, Colleen C.
2016-01-01
Relationship power is an important dyadic construct in close relationships that is associated with relationship health and partner’s individual health. Understanding what predicts power in heterosexual couples has proven difficult, and even less is known about gay couples. Resource models of power posit that demographic characteristics associated with social status (e.g., age, income) confer power within the relationship, which in turn shapes relationship outcomes. We tested this model in a sample of gay male couples (N=566 couples), and extended it by examining race and HIV status. Multilevel modeling was used to test associations between demographic bases of power and decision-making power. We also examined relative associations among demographic bases and decision-making power with relationship satisfaction, given the literature on power imbalances and overall relationship functioning. Results showed that individual income was positively associated with decision-making power, as was participant’s HIV status, with HIV-positive men reporting greater power. Age differences within the relationship interacted with relationship length to predict decision-making power, but not satisfaction. HIV-concordant positive couples were less satisfied than concordant negative couples. Higher power partners were less satisfied than lower power partners. Demographic factors contributing to decision-making power among same-sex male couples appear to share some similarities with heterosexual couples (e.g., income is associated with power), as well as have unique features (e.g., HIV status influences power). However, these same demographics did not reliably predict relationship satisfaction in the manner that existing power theories suggest. Findings indicate important considerations for theories of power among same-sex male couples. PMID:27606937
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Dynamic remapping decisions in multi-phase parallel computations
NASA Technical Reports Server (NTRS)
Nicol, D. M.; Reynolds, P. F., Jr.
1986-01-01
The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.
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McRoberts, N; Hall, C; Madden, L V; Hughes, G
2011-06-01
Many factors influence how people form risk perceptions. Farmers' perceptions of risk and levels of risk aversion impact on decision-making about such things as technology adoption and disease management practices. Irrespective of the underlying factors that affect risk perceptions, those perceptions can be summarized by variables capturing impact and uncertainty components of risk. We discuss a new framework that has the subjective probability of disease and the cost of decision errors as its central features, which might allow a better integration of social science and epidemiology, to the benefit of plant disease management. By focusing on the probability and cost (or impact) dimensions of risk, the framework integrates research from the social sciences, economics, decision theory, and epidemiology. In particular, we review some useful properties of expected regret and skill value, two measures of expected cost that are particularly useful in the evaluation of decision tools. We highlight decision-theoretic constraints on the usefulness of decision tools that may partly explain cases of failure of adoption. We extend this analysis by considering information-theoretic criteria that link model complexity and relative performance and which might explain why users reject forecasters that impose even moderate increases in the complexity of decision making despite improvements in performance or accept very simple decision tools that have relatively poor performance.
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Feminist ethics and menopause: autonomy and decision-making in primary medical care.
Murtagh, Madeleine J; Hepworth, Julie
2003-04-01
The construction of menopause as a long-term risk to health and the adoption of discourses of prevention has made necessary a decision by women about medical treatment; specifically regarding the use of hormone replacement therapy. In a study of general practitioners' accounts of menopause and treatment in Australia, women's 'choice', 'informed decision-making' and 'empowerment' were key themes through which primary medical care for women at menopause was presented. These accounts create a position for women defined by the concept of individual choice and an ethic of autonomy. These data are a basis for theorising more generally in this paper. We critically examine the construct of 'informed decision-making' in relation to several approaches to ethics including bioethics and a range of feminist ethics. We identify the intensification of power relations produced by an ethic of autonomy and discuss the ways these considerations inform a feminist ethics of decision-making by women. We argue that an 'ethic of autonomy' and an 'offer of choice' in relation to health care for women at menopause, far from being emancipatory, serves to intensify power relations. The dichotomy of choice, to take or not to take hormone replacement therapy, is required to be a choice and is embedded in relations of power and bioethical discourse that construct meanings about what constitutes decision-making at menopause. The deployment of the principle of autonomy in medical practice limits decision-making by women precisely because it is detached from the construction of meaning and the self and makes invisible the relations of power of which it is a part.
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NASA Astrophysics Data System (ADS)
Sheehan, T.; Baker, B.; Degagne, R. S.
2015-12-01
With the abundance of data sources, analytical methods, and computer models, land managers are faced with the overwhelming task of making sense of a profusion of data of wildly different types. Luckily, fuzzy logic provides a method to work with different types of data using language-based propositions such as "the landscape is undisturbed," and a simple set of logic constructs. Just as many surveys allow different levels of agreement with a proposition, fuzzy logic allows values reflecting different levels of truth for a proposition. Truth levels fall within a continuum ranging from Fully True to Fully False. Hence a fuzzy logic model produces continuous results. The Environmental Evaluation Modeling System (EEMS) is a platform-independent, tree-based, fuzzy logic modeling framework. An EEMS model provides a transparent definition of an evaluation model and is commonly developed as a collaborative effort among managers, scientists, and GIS experts. Managers specify a set of evaluative propositions used to characterize the landscape. Scientists, working with managers, formulate functions that convert raw data values into truth values for the propositions and produce a logic tree to combine results into a single metric used to guide decisions. Managers, scientists, and GIS experts then work together to implement and iteratively tune the logic model and produce final results. We present examples of two successful EEMS projects that provided managers with map-based results suitable for guiding decisions: sensitivity and climate change exposure in Utah and the Colorado Plateau modeled for the Bureau of Land Management; and terrestrial ecological intactness in the Mojave and Sonoran region of southern California modeled for the Desert Renewable Energy Conservation Plan.
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Scholz, Stefan; Mittendorf, Thomas
2014-12-01
Rheumatoid arthritis (RA) is a chronic, inflammatory disease with severe effects on the functional ability of patients. Due to the prevalence of 0.5 to 1.0 percent in western countries, new treatment options are a major concern for decision makers with regard to their budget impact. In this context, cost-effectiveness analyses are a helpful tool to evaluate new treatment options for reimbursement schemes. To analyze and compare decision analytic modeling techniques and to explore their use in RA with regard to their advantages and shortcomings. A systematic literature review was conducted in PubMED and 58 studies reporting health economics decision models were analyzed with regard to the modeling technique used. From the 58 reviewed publications, we found 13 reporting decision tree-analysis, 25 (cohort) Markov models, 13 publications on individual sampling methods (ISM) and seven discrete event simulations (DES). Thereby 26 studies were identified as presenting independently developed models and 32 models as adoptions. The modeling techniques used were found to differ in their complexity and in the number of treatment options compared. Methodological features are presented in the article and a comprehensive overview of the cost-effectiveness estimates is given in Additional files 1 and 2. When compared to the other modeling techniques, ISM and DES have advantages in the coverage of patient heterogeneity and, additionally, DES is capable to model more complex treatment sequences and competing risks in RA-patients. Nevertheless, the availability of sufficient data is necessary to avoid assumptions in ISM and DES exercises, thereby enabling biased results. Due to the different settings, time frames and interventions in the reviewed publications, no direct comparison of modeling techniques was applicable. The results from other indications suggest that incremental cost-effective ratios (ICERs) do not differ significantly between Markov and DES models, but DES is able to report more outcome parameters. Given a sufficient data supply, DES is the modeling technique of choice when modeling cost-effectiveness in RA. Otherwise transparency on the data inputs is crucial for valid results and to inform decision makers about possible biases. With regard to ICERs, Markov models might provide similar estimates as more advanced modeling techniques.
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NASA Astrophysics Data System (ADS)
Skorupka, Dariusz; Duchaczek, Artur; Waniewska, Agnieszka; Kowacka, Magdalena
2017-07-01
Due to their properties unmanned aerial vehicles have huge number of possibilities for application in construction engineering. The nature and extent of construction works performedmakes the decision to purchase the right equipment significant for the possibility for its further use while monitoring the implementation of these works. Technical factors, such as the accuracy and quality of the applied measurement instruments are especially important when monitoring the realization of construction projects. The paper presents the optimization of the choice of unmanned aerial vehicles using the Bellinger method. The decision-making analysis takes into account criteria that are particularly crucial by virtue of the range of monitoring of ongoing construction works.
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Conceptualizing the Role of Research Literacy in Advancing Societal Health
Brody, Janet L.; Dalen, Jeanne; Annett, Robert D.; Scherer, David G.; Turner, Charles W.
2013-01-01
Purpose To provide a conceptual formulation for “research literacy” and preliminary evidence for the utility of the construct in enhancing knowledge of and ethical participation in research. Methods Examined the impact of a brief educational intervention on parents’ research knowledge and their research participation decisions. Results Research-related knowledge was improved. Parents with greater knowledge were more comfortable with their research participation decisions. Enhanced understanding of child volition increased parents’ willingness to enroll their children in research. Conclusion The proposed research literacy model identifies methods to enhance population knowledge and appreciation of research, strengthening links between scientific advancement and health. PMID:22021275
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Simulating motivated cognition
NASA Technical Reports Server (NTRS)
Gevarter, William B.
1991-01-01
A research effort to develop a sophisticated computer model of human behavior is described. A computer framework of motivated cognition was developed. Motivated cognition focuses on the motivations or affects that provide the context and drive in human cognition and decision making. A conceptual architecture of the human decision-making approach from the perspective of information processing in the human brain is developed in diagrammatic form. A preliminary version of such a diagram is presented. This architecture is then used as a vehicle for successfully constructing a computer program simulation Dweck and Leggett's findings that relate how an individual's implicit theories orient them toward particular goals, with resultant cognitions, affects, and behavior.
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A Digital Framework to Support Providers and Patients in Diabetes Related Behavior Modification.
Abidi, Samina; Vallis, Michael; Piccinini-Vallis, Helena; Imran, Syed Ali; Abidi, Syed Sibte Raza
2017-01-01
We present Diabetes Web-Centric Information and Support Environment (D-WISE) that features: (a) Decision support tool to assist family physicians to administer Behavior Modification (BM) strategies to patients; and (b) Patient BM application that offers BM strategies and motivational interventions to engage patients. We take a knowledge management approach, using semantic web technologies, to model the social cognition theory constructs, Canadian diabetes guidelines and BM protocols used locally, in terms of a BM ontology that drives the BM decision support to physicians and BM strategy adherence monitoring and messaging to patients. We present the qualitative analysis of D-WISE usability by both physicians and patients.
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Review of retrofit strategies decision system in historic perspective
NASA Astrophysics Data System (ADS)
Bostenaru Dan, M. D.
2004-06-01
Urban development is a process. In structuring and developing its phases different actors are implied, who act under different, sometimes opposite, dynamic conditions and within different reference systems. This paper aims to explore the contribution of participatism to disaster mitigation, when this concerns earthquake impact on urban settlements, through the support provided to multi-criteria decision in matters of retrofit. The research broadness in field of decision making on one side and the lack of a specific model for the retrofit of existing buildings on another side led to an extensive review of the state of the art in related models to address the issue. Core idea in the selection of existing models has been the preoccupation for collaborative issues, in other words, the consideration for the different actors implied in the planning process. The historic perspective on participative planning models is made from the view of two generations of citizen implication. The first approaches focus on the participation of the building owner/inhabitant in the planning process of building construction. As current strategies building rehabilitation and selection from alternative retrofit strategies are presented. New developments include innovative models using the internet or spatial databases. The investigated participation approaches show, that participation and communication as a more comprehensive term are an old topic in the field politics-democratisation-urbanism. In all cases it can be talked of "successful learning processes", of the improvement of the level of the professional debate. More than 30 years history of participation marked a transition in understanding the concept: from participation, based on a central decision process leading to a solution controlled and steered by the political-administrative system, to communication, characterised by simultaneous decision processes taking place outside politics and administration in co-operative procedures.
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A linear programming approach for placement of applicants to academic programs.
Kassa, Biniyam Asmare
2013-01-01
This paper reports a linear programming approach for placement of applicants to study programs developed and implemented at the college of Business & Economics, Bahir Dar University, Bahir Dar, Ethiopia. The approach is estimated to significantly streamline the placement decision process at the college by reducing required man hour as well as the time it takes to announce placement decisions. Compared to the previous manual system where only one or two placement criteria were considered, the new approach allows the college's management to easily incorporate additional placement criteria, if needed. Comparison of our approach against manually constructed placement decisions based on actual data for the 2012/13 academic year suggested that about 93 percent of the placements from our model concur with the actual placement decisions. For the remaining 7 percent of placements, however, the actual placements made by the manual system display inconsistencies of decisions judged against the very criteria intended to guide placement decisions by the college's program management office. Overall, the new approach proves to be a significant improvement over the manual system in terms of efficiency of the placement process and the quality of placement decisions.
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A template-finding algorithm and a comprehensive benchmark for homology modeling of proteins
Vallat, Brinda Kizhakke; Pillardy, Jaroslaw; Elber, Ron
2010-01-01
The first step in homology modeling is to identify a template protein for the target sequence. The template structure is used in later phases of the calculation to construct an atomically detailed model for the target. We have built from the Protein Data Bank a large-scale learning set that includes tens of millions of pair matches that can be either a true template or a false one. Discriminatory learning (learning from positive and negative examples) is employed to train a decision tree. Each branch of the tree is a mathematical programming model. The decision tree is tested on an independent set from PDB entries and on the sequences of CASP7. It provides significant enrichment of true templates (between 50-100 percent) when compared to PSI-BLAST. The model is further verified by building atomically detailed structures for each of the tentative true templates with modeller. The probability that a true match does not yield an acceptable structural model (within 6Å RMSD from the native structure), decays linearly as a function of the TM structural-alignment score. PMID:18300226
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Rethinking the Default Construction of Multimodel Climate Ensembles
Rauser, Florian; Gleckler, Peter; Marotzke, Jochem
2015-07-21
Here, we discuss the current code of practice in the climate sciences to routinely create climate model ensembles as ensembles of opportunity from the newest phase of the Coupled Model Intercomparison Project (CMIP). We give a two-step argument to rethink this process. First, the differences between generations of ensembles corresponding to different CMIP phases in key climate quantities are not large enough to warrant an automatic separation into generational ensembles for CMIP3 and CMIP5. Second, we suggest that climate model ensembles cannot continue to be mere ensembles of opportunity but should always be based on a transparent scientific decision process.more » If ensembles can be constrained by observation, then they should be constructed as target ensembles that are specifically tailored to a physical question. If model ensembles cannot be constrained by observation, then they should be constructed as cross-generational ensembles, including all available model data to enhance structural model diversity and to better sample the underlying uncertainties. To facilitate this, CMIP should guide the necessarily ongoing process of updating experimental protocols for the evaluation and documentation of coupled models. Finally, with an emphasis on easy access to model data and facilitating the filtering of climate model data across all CMIP generations and experiments, our community could return to the underlying idea of using model data ensembles to improve uncertainty quantification, evaluation, and cross-institutional exchange.« less
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Niedhammer, Isabelle; Milner, Allison; LaMontagne, Anthony D; Chastang, Jean-François
2018-03-08
The objectives of the study were to construct a job-exposure matrix (JEM) for psychosocial work factors of the job strain model, to evaluate its validity, and to compare the results over time. The study was based on national representative data of the French working population with samples of 46,962 employees (2010 SUMER survey) and 24,486 employees (2003 SUMER survey). Psychosocial work factors included the job strain model factors (Job Content Questionnaire): psychological demands, decision latitude, social support, job strain and iso-strain. Job title was defined by three variables: occupation and economic activity coded using standard classifications, and company size. A JEM was constructed using a segmentation method (Classification and Regression Tree-CART) and cross-validation. The best quality JEM was found using occupation and company size for social support. For decision latitude and psychological demands, there was not much difference using occupation and company size with or without economic activity. The validity of the JEM estimates was higher for decision latitude, job strain and iso-strain, and lower for social support and psychological demands. Differential changes over time were observed for psychosocial work factors according to occupation, economic activity and company size. This study demonstrated that company size in addition to occupation may improve the validity of JEMs for psychosocial work factors. These matrices may be time-dependent and may need to be updated over time. More research is needed to assess the validity of JEMs given that these matrices may be able to provide exposure assessments to study a range of health outcomes.
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Essays on competition in electricity markets
NASA Astrophysics Data System (ADS)
Bustos Salvagno, Ricardo Javier
The first chapter shows how technology decisions affect entry in commodity markets with oligopolistic competition, like the electricity market. I demonstrate an entry deterrence effect that works through cost uncertainty. Technology's cost uncertainty affects spot market expected profits through forward market trades. Therefore, incentives to engage in forward trading shape firms' decisions on production technologies. I show that high-cost but low-risk technologies are adopted by risk-averse incumbents to deter entry. Strategic technology adoption can end in a equilibrium where high-cost technologies prevail over low-cost but riskier ones. In the case of incumbents who are less risk-averse than entrants, entry deterrence is achieved by choosing riskier technologies. The main results do not depend on who chooses their technology first. Chapter two examines the Chilean experience on auctions for long-term supply contracts in electricity markets from 2006 to 2011. Using a divisible-good auction model, I provide a theoretical framework that explains bidding behavior in terms of expected spot prices and contracting positions. The model is extended to include potential strategic behavior on contracting decisions. Empirical estimations confirm the main determinants of bidding behavior and show heterogeneity in the marginal cost of over-contracting depending on size and incumbency. Chapter three analyzes the lag in capacity expansion in the Chilean electricity market from 2000 to 2004. Regarded as a result of regulatory uncertainty, the role of delays in the construction of a large hydro-power plant has been overlooked by the literature. We argue that those delays postponed projected investment and gave small windows of opportunity that only incumbents could take advantage of. We are able to retrace the history of investments through real-time information from the regulator's reports and a simple model enables us to explain the effect of those delays on suggested and under-construction investments.
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Zhou, Shang-Ming; Lyons, Ronan A.; Brophy, Sinead; Gravenor, Mike B.
2012-01-01
The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and this results in limited applicability in fields such as epidemiology or bioinformatics where the interaction of many variables must be considered. Here, we develop a new parsimonious TS rule system. We propose three statistics: R, L, and ω-values, to rank the importance of each TS rule, and a forward selection procedure to construct a final model. We use our method to predict how key components of childhood deprivation combine to influence educational achievement outcome. We show that a parsimonious TS model can be constructed, based on a small subset of rules, that provides an accurate description of the relationship between deprivation indices and educational outcomes. The selected rules shed light on the synergistic relationships between the variables, and reveal that the effect of targeting specific domains of deprivation is crucially dependent on the state of the other domains. Policy decisions need to incorporate these interactions, and deprivation indices should not be considered in isolation. The TS rule system provides a basis for such decision making, and has wide applicability for the identification of non-linear interactions in complex biomedical data. PMID:23272108
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Zhou, Shang-Ming; Lyons, Ronan A; Brophy, Sinead; Gravenor, Mike B
2012-01-01
The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and this results in limited applicability in fields such as epidemiology or bioinformatics where the interaction of many variables must be considered. Here, we develop a new parsimonious TS rule system. We propose three statistics: R, L, and ω-values, to rank the importance of each TS rule, and a forward selection procedure to construct a final model. We use our method to predict how key components of childhood deprivation combine to influence educational achievement outcome. We show that a parsimonious TS model can be constructed, based on a small subset of rules, that provides an accurate description of the relationship between deprivation indices and educational outcomes. The selected rules shed light on the synergistic relationships between the variables, and reveal that the effect of targeting specific domains of deprivation is crucially dependent on the state of the other domains. Policy decisions need to incorporate these interactions, and deprivation indices should not be considered in isolation. The TS rule system provides a basis for such decision making, and has wide applicability for the identification of non-linear interactions in complex biomedical data.
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NASA Astrophysics Data System (ADS)
Edlund, C. A.
2017-12-01
The Department of Defense (DoD) is planning over $500M in military construction on Eielson Air Force Base (AFB) within the next three fiscal years. This construction program will expand the footprint of facilities and change the storm water management scheme, which will have second order effects on the underlying permafrost layer. These changes in permafrost will drive engineering decision making at local and regional levels, and help shape the overall strategy for military readiness in the Arctic. Although many studies have attempted to predict climate change induced permafrost degradation, very little site-specific knowledge exists on the anthropogenic effects to permafrost at this location. In 2016, the permafrost degradation rates at Eielson AFB were modeled using the Geophysics Institute Permafrost Laboratory (GIPL) 2.1 model and limited available geotechnical and climate data. Model results indicated a degradation of the discontinuous permafrost layer at Eielson AFB of up to 7 meters in depth over the next century. To further refine an understanding of the geophysics at Eielson AFB and help engineers and commanders make more informed decisions on engineering and operations in the arctic, this project established two permafrost monitoring stations near the future construction sites. Installation of the stations occurred in July 2017. Permafrost was located and characterized using two Electrical Resistivity Tomography surveys, as well as direct frost probe measurements. Using this data, the research team optimized the placement location and depth of two long term ground temperature monitoring stations, and then installed the stations for data collection. The data set generated by these stations are the first of their kind at Eielson AFB, and represent the first systematic effort in the DoD to quantify permafrost condition before, during, and after construction and other anthropogenic activities in order to fully understand the effects of that activity in the future.
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NASA Technical Reports Server (NTRS)
Shih, Ann T.; Ancel, Ersin; Jones, Sharon M.
2012-01-01
The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.
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What You Should Know about Construction Disputes.
ERIC Educational Resources Information Center
Hohns, H. Murray
1979-01-01
A number of rules that will aid in the decision making of the individual confronted with the need to purchase construction services, administer a construction contract, or be responsible for the performance of those construction services. (Author)
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Optimal Contractor Selection in Construction Industry: The Fuzzy Way
NASA Astrophysics Data System (ADS)
Krishna Rao, M. V.; Kumar, V. S. S.; Rathish Kumar, P.
2018-02-01
A purely price-based approach to contractor selection has been identified as the root cause for many serious project delivery problems. Therefore, the capability of the contractor to execute the project should be evaluated using a multiple set of selection criteria including reputation, past performance, performance potential, financial soundness and other project specific criteria. An industry-wide questionnaire survey was conducted with the objective of identifying the important criteria for adoption in the selection process. In this work, a fuzzy set based model was developed for contractor prequalification/evaluation, by using effective criteria obtained from the percept of construction professionals, taking subjective judgments of decision makers also into consideration. A case study consisting of four alternatives (contractors in the present case) solicited from a public works department of Pondicherry in India, is used to illustrate the effectiveness of the proposed approach. The final selection of contractor is made based on the integrated score or Overall Evaluation Score of the decision alternative in prequalification as well as bid evaluation stages.
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Women's career choices in chemistry: Motivations, perceptions, and a conceptual model
NASA Astrophysics Data System (ADS)
Grunert, Megan L.
Statistics showing the under-representation of women at all levels within the physical sciences abound, particularly at the graduate and faculty levels. Women chemists choosing an academic career tend to select teaching institutions over research institutions. This study examined women at the graduate and faculty levels through interviews and the construction of participant narratives to better understand why many women opt out of a career in academic research. Specific attention was paid to women's decision-making processes and what motivates women to choose careers, the rewards and challenges associated with different careers, and the perception of different careers contribute to their decisions. The participant narratives were analyzed on a cross-case basis and constructivist grounded theory was used to develop a model about women's decision-making regarding their careers. Additionally, preliminary work has suggested that graduate students have inaccurate perceptions of careers in academia. Interviews with faculty at teaching and research institutions provided a clearer picture of what each type of career entails. Career-choice motivators, rewards, and challenges were identified for each of the faculty groups. It was found that graduate student women have inaccurate perceptions of academic research careers, which affects how they make career decisions. A model of career choice shows interactions between motivation and perception that guide the career decision-making process. By better understanding these women and their motivations, changes can be made to foster inclusion and accommodation for women and other underrepresented groups in academic chemistry.
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NASA Astrophysics Data System (ADS)
Simpson, Mike; Ives, Matthew; Hall, Jim
2016-04-01
There is an increasing body of evidence in support of the use of nature based solutions as a strategy to mitigate drought. Restored or constructed wetlands, grasslands and in some cases forests have been used with success in numerous case studies. Such solutions remain underused in the UK, where they are not considered as part of long-term plans for supply by water companies. An important step is the translation of knowledge on the benefits of nature based solutions at the upland/catchment scale into a model of the impact of these solutions on national water resource planning in terms of financial costs, carbon benefits and robustness to drought. Our project, 'A National Scale Model of Green Infrastructure for Water Resources', addresses this issue through development of a model that can show the costs and benefits associated with a broad roll-out of nature based solutions for water supply. We have developed generalised models of both the hydrological effects of various classes and implementations of nature-based approaches and their economic impacts in terms of construction costs, running costs, time to maturity, land use and carbon benefits. Our next step will be to compare this work with our recent evaluation of conventional water infrastructure, allowing a case to be made in financial terms and in terms of security of water supply. By demonstrating the benefits of nature based solutions under multiple possible climate and population scenarios we aim to demonstrate the potential value of using nature based solutions as a component of future long-term water resource plans. Strategies for decision making regarding the selection of nature based and conventional approaches, developed through discussion with government and industry, will be applied to the final model. Our focus is on keeping our work relevant to the requirements of decision-makers involved in conventional water planning. We propose to present the outcomes of our model for the evaluation of nature-based solutions at catchment scale and ongoing results of our national-scale model.
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The research on construction and application of machining process knowledge base
NASA Astrophysics Data System (ADS)
Zhao, Tan; Qiao, Lihong; Qie, Yifan; Guo, Kai
2018-03-01
In order to realize the application of knowledge in machining process design, from the perspective of knowledge in the application of computer aided process planning(CAPP), a hierarchical structure of knowledge classification is established according to the characteristics of mechanical engineering field. The expression of machining process knowledge is structured by means of production rules and the object-oriented methods. Three kinds of knowledge base models are constructed according to the representation of machining process knowledge. In this paper, the definition and classification of machining process knowledge, knowledge model, and the application flow of the process design based on the knowledge base are given, and the main steps of the design decision of the machine tool are carried out as an application by using the knowledge base.
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The Career Decision-Making Competence: A New Construct for the Career Realm
ERIC Educational Resources Information Center
Ceschi, Andrea; Costantini, Arianna; Phillips, Susan D.; Sartori, Riccardo
2017-01-01
Purpose: This paper aims to link findings from laboratory-based decision-making research and decision-making competence (DMC) aspects that may be central for career-related decision-making processes. Past research has identified individual differences in rational responses in decision situations, which the authors refer to as DMC. Although there…
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Decision-Making Style among Adolescents: Relationship with Sensation Seeking and Locus of Control
ERIC Educational Resources Information Center
Baiocco, Roberto; Laghi, Fiorenzo; D'Alessio, Maria
2009-01-01
The principal aim of the study was to examine the psychometric properties and construct validity of the General Decision-Making Scale (GDMS) in a sample of 700 adolescents (aged 15-19 years). Confirmatory and exploratory factor analyses provide evidence for a solid five-dimension structure reflecting the theorized construct: rational, intuitive,…
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ERIC Educational Resources Information Center
Byars, Alvin Gregg
The objectives of this investigation are to develop, describe, assess, and demonstrate procedures for constructing mastery tests to minimize errors of classification and to maximize decision reliability. The guidelines are based on conditions where item exchangeability is a reasonable assumption and the test constructor can control the number of…
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45 CFR 1309.12 - Timely decisions.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 45 Public Welfare 4 2010-10-01 2010-10-01 false Timely decisions. 1309.12 Section 1309.12 Public... PROGRAM HEAD START FACILITIES PURCHASE, MAJOR RENOVATION AND CONSTRUCTION Application Procedures § 1309.12 Timely decisions. The responsible HHS official shall promptly review and make final decisions regarding...
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Developing a database for pedestrians' earthquake emergency evacuation in indoor scenarios.
Zhou, Junxue; Li, Sha; Nie, Gaozhong; Fan, Xiwei; Tan, Jinxian; Li, Huayue; Pang, Xiaoke
2018-01-01
With the booming development of evacuation simulation software, developing an extensive database in indoor scenarios for evacuation models is imperative. In this paper, we conduct a qualitative and quantitative analysis of the collected videotapes and aim to provide a complete and unitary database of pedestrians' earthquake emergency response behaviors in indoor scenarios, including human-environment interactions. Using the qualitative analysis method, we extract keyword groups and keywords that code the response modes of pedestrians and construct a general decision flowchart using chronological organization. Using the quantitative analysis method, we analyze data on the delay time, evacuation speed, evacuation route and emergency exit choices. Furthermore, we study the effect of classroom layout on emergency evacuation. The database for indoor scenarios provides reliable input parameters and allows the construction of real and effective constraints for use in software and mathematical models. The database can also be used to validate the accuracy of evacuation models.
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Decision support system in an international-voice-services business company
NASA Astrophysics Data System (ADS)
Hadianti, R.; Uttunggadewa, S.; Syamsuddin, M.; Soewono, E.
2017-01-01
We consider a problem facing by an international telecommunication services company in maximizing its profit. From voice services by controlling cost and business partnership. The competitiveness in this industry is very high, so that any efficiency from controlling cost and business partnership can help the company to survive in the very high competitiveness situation. The company trades voice traffic with a large number of business partners. There are four trading schemes that can be chosen by this company, namely, flat rate, class tiering, volume commitment, and revenue capped. Each scheme has a specific characteristic on the rate and volume deal, where the last three schemes are regarded as strategic schemes to be offered to business partner to ensure incoming traffic volume for both parties. This company and each business partner need to choose an optimal agreement in a certain period of time that can maximize the company’s profit. In this agreement, both parties agree to use a certain trading scheme, rate and rate/volume/revenue deal. A decision support system is then needed in order to give a comprehensive information to the sales officers to deal with the business partners. This paper discusses the mathematical model of the optimal decision for incoming traffic volume control, which is a part of the analysis needed to build the decision support system. The mathematical model is built by first performing data analysis to see how elastic the incoming traffic volume is. As the level of elasticity is obtained, we then derive a mathematical modelling that can simulate the impact of any decision on trading to the revenue of the company. The optimal decision can be obtained from these simulations results. To evaluate the performance of the proposed method we implement our decision model to the historical data. A software tool incorporating our methodology is currently in construction.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Jiangjiang; Li, Weixuan; Lin, Guang
In decision-making for groundwater management and contamination remediation, it is important to accurately evaluate the probability of the occurrence of a failure event. For small failure probability analysis, a large number of model evaluations are needed in the Monte Carlo (MC) simulation, which is impractical for CPU-demanding models. One approach to alleviate the computational cost caused by the model evaluations is to construct a computationally inexpensive surrogate model instead. However, using a surrogate approximation can cause an extra error in the failure probability analysis. Moreover, constructing accurate surrogates is challenging for high-dimensional models, i.e., models containing many uncertain input parameters.more » To address these issues, we propose an efficient two-stage MC approach for small failure probability analysis in high-dimensional groundwater contaminant transport modeling. In the first stage, a low-dimensional representation of the original high-dimensional model is sought with Karhunen–Loève expansion and sliced inverse regression jointly, which allows for the easy construction of a surrogate with polynomial chaos expansion. Then a surrogate-based MC simulation is implemented. In the second stage, the small number of samples that are close to the failure boundary are re-evaluated with the original model, which corrects the bias introduced by the surrogate approximation. The proposed approach is tested with a numerical case study and is shown to be 100 times faster than the traditional MC approach in achieving the same level of estimation accuracy.« less
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Bayesian Networks for Modeling Dredging Decisions
2011-10-01
change scenarios. Arctic Expert elicitation Netica Bacon et al . 2002 Identify factors that might lead to a change in land use from farming to...tree) algorithms developed by Lauritzen and Spiegelhalter (1988) and Jensen et al . (1990). Statistical inference is simply the process of...causality when constructing a Bayesian network (Kjaerulff and Madsen 2008, Darwiche 2009, Marcot et al . 2006). A knowledge representation approach is the
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Some aspects of control of a large-scale dynamic system
NASA Technical Reports Server (NTRS)
Aoki, M.
1975-01-01
Techniques of predicting and/or controlling the dynamic behavior of large scale systems are discussed in terms of decentralized decision making. Topics discussed include: (1) control of large scale systems by dynamic team with delayed information sharing; (2) dynamic resource allocation problems by a team (hierarchical structure with a coordinator); and (3) some problems related to the construction of a model of reduced dimension.
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The Army Communications Objectives Measurement System (ACOMS): Annual Report, School Year 86/87
1988-04-01
assessments of advertising program effectiveness, assessments of advertising strategy efficiencies, management of the advertising program, and planning...market. ACOMS is being used for Army assessments of advertising program effectiveness, assessments of advertising strategy efficiencies, management of... advertising strategy and effectiveness and to begin the construction of an integrated model of the role of the Army’s advertising in the enlistment decision
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Collaboration and Synergy among Government, Industry and Academia in M&S Domain: Turkey’s Approach
2009-10-01
Analysis, Decision Support System Design and Implementation, Simulation Output Analysis, Statistical Data Analysis, Virtual Reality , Artificial... virtual and constructive visual simulation systems as well as integrated advanced analytical models. Collaboration and Synergy among Government...simulation systems that are ready to use, credible, integrated with C4ISR systems. Creating synthetic environments and/or virtual prototypes of concepts
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Légaré, France; Borduas, Francine; Freitas, Adriana; Jacques, André; Godin, Gaston; Luconi, Francesca; Grimshaw, Jeremy
2014-01-01
Decision-makers in organizations providing continuing professional development (CPD) have identified the need for routine assessment of its impact on practice. We sought to develop a theory-based instrument for evaluating the impact of CPD activities on health professionals' clinical behavioral intentions. Our multipronged study had four phases. 1) We systematically reviewed the literature for instruments that used socio-cognitive theories to assess healthcare professionals' clinically-oriented behavioral intentions and/or behaviors; we extracted items relating to the theoretical constructs of an integrated model of healthcare professionals' behaviors and removed duplicates. 2) A committee of researchers and CPD decision-makers selected a pool of items relevant to CPD. 3) An international group of experts (n = 70) reached consensus on the most relevant items using electronic Delphi surveys. 4) We created a preliminary instrument with the items found most relevant and assessed its factorial validity, internal consistency and reliability (weighted kappa) over a two-week period among 138 physicians attending a CPD activity. Out of 72 potentially relevant instruments, 47 were analyzed. Of the 1218 items extracted from these, 16% were discarded as improperly phrased and 70% discarded as duplicates. Mapping the remaining items onto the constructs of the integrated model of healthcare professionals' behaviors yielded a minimum of 18 and a maximum of 275 items per construct. The partnership committee retained 61 items covering all seven constructs. Two iterations of the Delphi process produced consensus on a provisional 40-item questionnaire. Exploratory factorial analysis following test-retest resulted in a 12-item questionnaire. Cronbach's coefficients for the constructs varied from 0.77 to 0.85. A 12-item theory-based instrument for assessing the impact of CPD activities on health professionals' clinical behavioral intentions showed adequate validity and reliability. Further studies could assess its responsiveness to behavior change following CPD activities and its capacity to predict health professionals' clinical performance.
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Légaré, France; Borduas, Francine; Freitas, Adriana; Jacques, André; Godin, Gaston; Luconi, Francesca; Grimshaw, Jeremy
2014-01-01
Background Decision-makers in organizations providing continuing professional development (CPD) have identified the need for routine assessment of its impact on practice. We sought to develop a theory-based instrument for evaluating the impact of CPD activities on health professionals' clinical behavioral intentions. Methods and Findings Our multipronged study had four phases. 1) We systematically reviewed the literature for instruments that used socio-cognitive theories to assess healthcare professionals' clinically-oriented behavioral intentions and/or behaviors; we extracted items relating to the theoretical constructs of an integrated model of healthcare professionals' behaviors and removed duplicates. 2) A committee of researchers and CPD decision-makers selected a pool of items relevant to CPD. 3) An international group of experts (n = 70) reached consensus on the most relevant items using electronic Delphi surveys. 4) We created a preliminary instrument with the items found most relevant and assessed its factorial validity, internal consistency and reliability (weighted kappa) over a two-week period among 138 physicians attending a CPD activity. Out of 72 potentially relevant instruments, 47 were analyzed. Of the 1218 items extracted from these, 16% were discarded as improperly phrased and 70% discarded as duplicates. Mapping the remaining items onto the constructs of the integrated model of healthcare professionals' behaviors yielded a minimum of 18 and a maximum of 275 items per construct. The partnership committee retained 61 items covering all seven constructs. Two iterations of the Delphi process produced consensus on a provisional 40-item questionnaire. Exploratory factorial analysis following test-retest resulted in a 12-item questionnaire. Cronbach's coefficients for the constructs varied from 0.77 to 0.85. Conclusion A 12-item theory-based instrument for assessing the impact of CPD activities on health professionals' clinical behavioral intentions showed adequate validity and reliability. Further studies could assess its responsiveness to behavior change following CPD activities and its capacity to predict health professionals' clinical performance. PMID:24643173
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Mei, Chao; Liu, Jiahong; Wang, Hao; Yang, Zhiyong; Ding, Xiangyi; Shao, Weiwei
2018-10-15
Green Infrastructure (GI) has become increasingly important in urban stormwater management because of the effects of climate change and urbanization. To mitigate severe urban water-related problems, China is implementing GI at the national scale under its Sponge City Program (SCP). The SCP is currently in a pilot period, however, little attention has been paid to the cost-effectiveness of GI implementation in China. In this study, an evaluation framework based on the Storm Water Management Model (SWMM) and life cycle cost analysis (LCCA) was applied to undertake integrated assessments of the development of GI for flood mitigation, to support robust decision making regarding sponge city construction in urbanized watersheds. A baseline scenario and 15 GI scenarios under six design rainfall events with recurrence intervals ranging from 2-100 years were simulated and assessed. Model simulation results confirmed the effectiveness of GI for flood mitigation. Nevertheless, even under the most beneficial scenario, the results showed the hydrological performance of GI was incapable of eliminating flooding. Analysis indicated the bioretention cell (BC) plus vegetated swale (VS) scenario was the most cost-effective GI option for unit investment under all rainfall events. However, regarding the maximum potential of the implementation areas of all GI scenarios, the porous pavement plus BC + VS strategy was considered most reasonable for the study area. Although the optimal combinations are influenced by uncertainties in both the model and the GI parameters, the main trends and key insights derived remain unaffected; therefore, the conclusions are relevant regarding sponge city construction within the study area. Copyright © 2018 Elsevier B.V. All rights reserved.
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Analysis of a mammography teaching program based on an affordance design model.
Luo, Ping; Eikman, Edward A; Kealy, William; Qian, Wei
2006-12-01
The wide use of computer technology in education, particularly in mammogram reading, asks for e-learning evaluation. The existing media comparative studies, learner attitude evaluations, and performance tests are problematic. Based on an affordance design model, this study examined an existing e-learning program on mammogram reading. The selection criteria include content relatedness, representativeness, e-learning orientation, image quality, program completeness, and accessibility. A case study was conducted to examine the affordance features, functions, and presentations of the selected software. Data collection and analysis methods include interviews, protocol-based document analysis, and usability tests and inspection. Also some statistics were calculated. The examination of PBE identified that this educational software designed and programmed some tools. The learner can use these tools in the process of optimizing displays, scanning images, comparing different projections, marking the region of interests, constructing a descriptive report, assessing one's learning outcomes, and comparing one's decisions with the experts' decisions. Further, PBE provides some resources for the learner to construct one's knowledge and skills, including a categorized image library, a term-searching function, and some teaching links. Besides, users found it easy to navigate and carry out tasks. The users also reacted positively toward PBE's navigation system, instructional aids, layout, pace and flow of information, graphics, and other presentation design. The software provides learners with some cognitive tools, supporting their perceptual problem-solving processes and extending their capabilities. Learners can internalize the mental models in mammogram reading through multiple perceptual triangulations, sensitization of related features, semantic description of mammogram findings, and expert-guided semantic report construction. The design of these cognitive tools and the software interface matches the findings and principles in human learning and instructional design. Working with PBE's case-based simulations and categorized gallery, learners can enrich and transfer their experience to their jobs.
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Mathematical Methods of System Analysis in Construction Materials
NASA Astrophysics Data System (ADS)
Garkina, Irina; Danilov, Alexander
2017-10-01
System attributes of construction materials are defined: complexity of an object, integrity of set of elements, existence of essential, stable relations between elements defining integrative properties of system, existence of structure, etc. On the basis of cognitive modelling (intensive and extensive properties; the operating parameters) materials (as difficult systems) and creation of the cognitive map the hierarchical modular structure of criteria of quality is under construction. It actually is a basis for preparation of the specification on development of material (the required organization and properties). Proceeding from a modern paradigm (model of statement of problems and their decisions) of development of materials, levels and modules are specified in structure of material. It when using the principles of the system analysis allows to considered technological process as the difficult system consisting of elements of the distinguished specification level: from atomic before separate process. Each element of system depending on an effective objective is considered as separate system with more detailed levels of decomposition. Among them, semantic and qualitative analyses of an object (are considered a research objective, decomposition levels, separate elements and communications between them come to light). Further formalization of the available knowledge in the form of mathematical models (structural identification) is carried out; communications between input and output parameters (parametrical identification) are defined. Hierarchical structures of criteria of quality are under construction for each allocated level. On her the relevant hierarchical structures of system (material) are under construction. Regularities of structurization and formation of properties, generally are considered at the levels from micro to a macrostructure. The mathematical model of material is represented as set of the models corresponding to private criteria by which separate modules and their levels (the mathematical description, a decision algorithm) are defined. Adequacy is established (compliance of results of modelling to experimental data; is defined by the level of knowledge of process and validity of the accepted assumptions). The global criterion of quality of material is considered as a set of private criteria (properties). Synthesis of material is carried out on the basis of one-criteria optimization on each of the chosen private criteria. Results of one-criteria optimization are used at multicriteria optimization. The methods of developing materials as single-purpose, multi-purpose, including contradictory, systems are indicated. The scheme of synthesis of composite materials as difficult systems is developed. The specified system approach effectively was used in case of synthesis of composite materials with special properties.
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Clinical decision support tool for Co-management signalling.
Horta, Alexandra Bayão; Salgado, Cátia; Fernandes, Marta; Vieira, Susana; Sousa, João M; Papoila, Ana Luísa; Xavier, Miguel
2018-05-01
Co-management between internists and surgeons of selected patients is becoming one of the pillars of modern clinical management in large hospitals. Defining the patients to be co-managed is essential. The aim of this study is to create a decision tool using real-world patient data collected in the preoperative period, to support the decision on which patients should have the co-management service offered. Data was collected from the electronic clinical health records of patients who had an International Classification of Diseases, 9th edition (ICD-9) code of colorectal surgery during the period between January 2012 and October 2014 in a 200 bed private teaching hospital in Lisbon. ICD-9 codes of colorectal surgery [48.5 and 48.6 (anterior rectal resection and abdominoperineal resection), 45.7 (partial colectomy), 45.8 (Total Colectomy), and 45.9 (Bowel Anastomosis)] were used. Only patients above 18 years old were considered. Patients with more than one procedure were excluded from the study. From these data the authors investigated the construction of predictive models using logistic regression and Takagi-Sugeno fuzzy modelling. Data contains information obtained from the clinical records of a cohort of 344 adult patients. Data from 398 emergent and elective surgeries were collected, from which 54 were excluded because they were second procedures for the same patients. Four preoperative variables were identified as being the most predictive of co-management, in multivariable regression analysis. The final model performed well after being internally validated (0.81 AUC, 77% accuracy, 74% sensitivity, 78% specificity, 93% negative predictive value). The results indicate that the decision process can be more objective and potentially automated. The authors developed a prediction model based on preoperative characteristics, in order to support the decision for the co-management of surgical patients in the postoperative ward setting. The model is a simple bedside decision tool that uses only four numerical variables. Copyright © 2018 Elsevier B.V. All rights reserved.
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Grünebaum, T; Bode, H
2004-01-01
Organised in public or private structures, wastewater services have to cope with different framework conditions as regards planning, construction, financing and operation. This leads quite often to different modes of management. In recent years there has been a push for privatisation on the water sector in general, the reasons for which are manifold, ranging from access to external know-how and capital to synergistic effects through integration of wastewater treatment into other tasks of similar or equal nature. Discussed are various models of public/private partnership (PPP) in wastewater treatment, encompassing for example the delegation of partial tasks or even the proportional or entire transfer of ownership of treatment facilities to private third parties. Decisive for high performance and efficiency is not the legal or organisational form, but rather the clear and unmistakable definition of tasks which are to be assigned to the different parties, customers and all other partners involved, as well as of clear-cut interfaces. On account of the (of course legitimate) profit-oriented perspective of the private sector, some decision-making processes in relation to project implementation (design and construction) and to operational aspects will differ from those typically found on the public sector. This does apply to decisions on investments, financing and on technical solutions too. On the other hand, core competencies in wastewater treatment should not be outsourced, but remain the public bodies' responsibility, even with 'far-reaching' privatisation models. Such core competencies are all efforts geared to sustainable wastewater treatment as life-supporting provision for the future or as contribution to the protection of health and the environment and to the development of infrastructure. Major areas of wastewater treatment and other related tasks are reviewed. The paper concludes with a list of questions on the issue of outsourcing.
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Ceschi, Andrea; Demerouti, Evangelia; Sartori, Riccardo; Weller, Joshua
2017-01-01
The present study aims to connect more the I/O and the decision-making psychological domains, by showing how some common components across jobs interfere with decision-making and affecting performance. Two distinct constructs that can contribute to positive workplace performance have been considered: decision-making competency (DMCy) and decision environment management (DEM). Both factors are presumed to involve self-regulatory mechanisms connected to decision processes by influencing performance in relation to work environment conditions. In the framework of the job demands-resources (JD-R) model, the present study tested how such components as job demands, job resources and exhaustion can moderate decision-making processes and performance, where high resources are advantageous for decision-making processes and performance at work, while the same effect happens with low job demands and/or low exhaustion. In line with the formulated hypotheses, results confirm the relations between both the decision-making competences, performance (i.e., in-role and extra-role) and moderators considered. In particular, employees with low levels of DMCy show to be more sensitive to job demands toward in-role performance, whereas high DEM levels increase the sensitivity of employees toward job resources and exhaustion in relation to extra-role performance. These findings indicate that decision-making processes, as well as work environment conditions, are jointly related to employee functioning. PMID:28529491
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Ceschi, Andrea; Demerouti, Evangelia; Sartori, Riccardo; Weller, Joshua
2017-01-01
The present study aims to connect more the I/O and the decision-making psychological domains, by showing how some common components across jobs interfere with decision-making and affecting performance. Two distinct constructs that can contribute to positive workplace performance have been considered: decision-making competency (DMCy) and decision environment management (DEM). Both factors are presumed to involve self-regulatory mechanisms connected to decision processes by influencing performance in relation to work environment conditions. In the framework of the job demands-resources (JD-R) model, the present study tested how such components as job demands, job resources and exhaustion can moderate decision-making processes and performance, where high resources are advantageous for decision-making processes and performance at work, while the same effect happens with low job demands and/or low exhaustion. In line with the formulated hypotheses, results confirm the relations between both the decision-making competences, performance (i.e., in-role and extra-role) and moderators considered. In particular, employees with low levels of DMCy show to be more sensitive to job demands toward in-role performance, whereas high DEM levels increase the sensitivity of employees toward job resources and exhaustion in relation to extra-role performance. These findings indicate that decision-making processes, as well as work environment conditions, are jointly related to employee functioning.
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Shared decision making and medication management in the recovery process.
Deegan, Patricia E; Drake, Robert E
2006-11-01
Mental health professionals commonly conceptualize medication management for people with severe mental illness in terms of strategies to increase compliance or adherence. The authors argue that compliance is an inadequate construct because it fails to capture the dynamic complexity of autonomous clients who must navigate decisional conflicts in learning to manage disorders over the course of years or decades. Compliance is rooted in medical paternalism and is at odds with principles of person-centered care and evidence-based medicine. Using medication is an active process that involves complex decision making and a chance to work through decisional conflicts. It requires a partnership between two experts: the client and the practitioner. Shared decision making provides a model for them to assess a treatment's advantages and disadvantages within the context of recovering a life after a diagnosis of a major mental disorder.
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Validation of a DICE Simulation Against a Discrete Event Simulation Implemented Entirely in Code.
Möller, Jörgen; Davis, Sarah; Stevenson, Matt; Caro, J Jaime
2017-10-01
Modeling is an essential tool for health technology assessment, and various techniques for conceptualizing and implementing such models have been described. Recently, a new method has been proposed-the discretely integrated condition event or DICE simulation-that enables frequently employed approaches to be specified using a common, simple structure that can be entirely contained and executed within widely available spreadsheet software. To assess if a DICE simulation provides equivalent results to an existing discrete event simulation, a comparison was undertaken. A model of osteoporosis and its management programmed entirely in Visual Basic for Applications and made public by the National Institute for Health and Care Excellence (NICE) Decision Support Unit was downloaded and used to guide construction of its DICE version in Microsoft Excel ® . The DICE model was then run using the same inputs and settings, and the results were compared. The DICE version produced results that are nearly identical to the original ones, with differences that would not affect the decision direction of the incremental cost-effectiveness ratios (<1% discrepancy), despite the stochastic nature of the models. The main limitation of the simple DICE version is its slow execution speed. DICE simulation did not alter the results and, thus, should provide a valid way to design and implement decision-analytic models without requiring specialized software or custom programming. Additional efforts need to be made to speed up execution.
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Randhawa, Gurprit K
2017-01-01
A conceptual model for exploring the relationship between end-user support (EUS) and electronic medical record (EMR) use by primary care physicians is presented. The model was developed following a review of conceptual and theoretical frameworks related to technology adoption/use and EUS. The model includes (a) one core construct (facilitating conditions), (b) four antecedents and one postcedent of facilitating conditions, and (c) four moderators. EMR use behaviour is the key outcome of the model. The proposed conceptual model should be tested. The model may be used to inform planning and decision-making for EMR implementations to increase EMR use for benefits realization.
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NASA Astrophysics Data System (ADS)
Loginov, E. L.; Raikov, A. N.
2015-04-01
The most large-scale accidents occurred as a consequence of network information attacks on the control systems of power facilities belonging to the United States' critical infrastructure are analyzed in the context of possibilities available in modern decision support systems. Trends in the development of technologies for inflicting damage to smart grids are formulated. A volume matrix of parameters characterizing attacks on facilities is constructed. A model describing the performance of a critical infrastructure's control system after an attack is developed. The recently adopted measures and legislation acts aimed at achieving more efficient protection of critical infrastructure are considered. Approaches to cognitive modeling and networked expertise of intricate situations for supporting the decision-making process, and to setting up a system of indicators for anticipatory monitoring of critical infrastructure are proposed.
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Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
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The use of cognitive ability measures as explanatory variables in regression analysis
Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J
2015-01-01
Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual’s wage, or a decision such as an individual’s education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score, constructed via standard psychometric practice from individuals’ responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a “mixed effects structural equations” (MESE) model, may be more appropriate in many circumstances. PMID:26998417
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76 FR 40367 - Federal Acquisition Regulation; Information Collection; Buy American Act-Construction
Federal Register 2010, 2011, 2012, 2013, 2014
2011-07-08
...; Information Collection; Buy American Act--Construction AGENCY: Department of Defense (DOD), General Services... approved information collection requirement concerning the Buy American Act--Construction (Grimberg..., American Act--Construction (Grimberg Decision), by any of the following methods: [[Page 40368
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NASA Astrophysics Data System (ADS)
Lingga, Marwan Mossa
A strong trend of returning to nuclear power is evident in different places in the world. Forty-five countries are planning to add nuclear power to their grids and more than 66 nuclear power plants are under construction. Nuclear power plants that generate electricity and steam need to improve safety to become more acceptable to governments and the public. One novel practical solution to increase nuclear power plants' safety factor is to build them away from urban areas, such as offshore or underground. To date, Land-Based siting is the dominant option for siting all commercial operational nuclear power plants. However, the literature reveals several options for building nuclear power plants in safer sitings than Land-Based sitings. The alternatives are several and each has advantages and disadvantages, and it is difficult to distinguish among them and choose the best for a specific project. In this research, we recall the old idea of using the alternatives of offshore and underground sitings for new nuclear power plants and propose a tool to help in choosing the best siting technology. This research involved the development of a decision model for evaluating several potential nuclear power plant siting technologies, both those that are currently available and future ones. The decision model was developed based on the Hierarchical Decision Modeling (HDM) methodology. The model considers five major dimensions, social, technical, economic, environmental, and political (STEEP), and their related criteria and sub-criteria. The model was designed and developed by the author, and its elements' validation and evaluation were done by a large number of experts in the field of nuclear energy. The decision model was applied in evaluating five potential siting technologies and ranked the Natural Island as the best in comparison to Land-Based, Floating Plant, Artificial Island, and Semi-Embedded plant.
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Code of Federal Regulations, 2013 CFR
2013-01-01
... 10 Energy 1 2013-01-01 2013-01-01 false Notice of hearing on application for early review of site... AGENCY RULES OF PRACTICE AND PROCEDURE Additional Procedures Applicable to Early Partial Decisions on... Early Partial Decisions on Site Suitability-Construction Permit § 2.604 Notice of hearing on application...
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Code of Federal Regulations, 2012 CFR
2012-01-01
... 10 Energy 1 2012-01-01 2012-01-01 false Notice of hearing on application for early review of site... Applicable to Early Partial Decisions on Site Suitability Issues in Connection With an Application for a... Limited Work Authorizations Early Partial Decisions on Site Suitability-Construction Permit § 2.604 Notice...
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Code of Federal Regulations, 2014 CFR
2014-01-01
... 10 Energy 1 2014-01-01 2014-01-01 false Notice of hearing on application for early review of site... AGENCY RULES OF PRACTICE AND PROCEDURE Additional Procedures Applicable to Early Partial Decisions on... Early Partial Decisions on Site Suitability-Construction Permit § 2.604 Notice of hearing on application...
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ERIC Educational Resources Information Center
Wood, J. Luke; Hilton, Adriel A.
2012-01-01
This article encourages community college leaders to employ ethical paradigms when constructing and considering alternative courses of action in decision-making processes. The authors discuss four previously articulated paradigms (e.g., ethic of justice, ethic of critique, ethic of care, and ethic of the profession) and propose an additional…
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Code of Federal Regulations, 2011 CFR
2011-01-01
... 10 Energy 1 2011-01-01 2011-01-01 false Notice of hearing on application for early review of site... Applicable to Early Partial Decisions on Site Suitability Issues in Connection With an Application for a... Limited Work Authorizations Early Partial Decisions on Site Suitability-Construction Permit § 2.604 Notice...
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Code of Federal Regulations, 2010 CFR
2010-01-01
... 10 Energy 1 2010-01-01 2010-01-01 false Notice of hearing on application for early review of site... Applicable to Early Partial Decisions on Site Suitability Issues in Connection With an Application for a... Limited Work Authorizations Early Partial Decisions on Site Suitability-Construction Permit § 2.604 Notice...
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ERIC Educational Resources Information Center
Killingsworth, Erin Elizabeth
2013-01-01
With the widespread use of classroom exams in nursing education there is a great need for research on current practices in nursing education regarding this form of assessment. The purpose of this study was to explore how nursing faculty members make decisions about using best practices in classroom test construction, item analysis, and revision in…
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Learning to Make Decisions Through Constructive Controversy.
ERIC Educational Resources Information Center
Tjosvold, Dean
Students must make decisions about their lifestyle, future careers, academic pursuits, and classroom and school issues. Learning to make effective decisions for themselves and for society is an important aspect of competence. They can learn decision making through interacting and solving problems with others. A central ingredient for successful…
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Shi, Ting-Ting; Zhang, Xiao-Bo; Guo, Lan-Ping; Huang, Lu-Qi
2017-11-01
The herbs used as the material for traditional Chinese medicine are always planted in the mountainous area where the natural environment is suitable. As the mountain terrain is complex and the distribution of planting plots is scattered, the traditional survey method is difficult to obtain accurate planting area. It is of great significance to provide decision support for the conservation and utilization of traditional Chinese medicine resources by studying the method of extraction of Chinese herbal medicine planting area based on remote sensing and realizing the dynamic monitoring and reserve estimation of Chinese herbal medicines. In this paper, taking the Panax notoginseng plots in Wenshan prefecture of Yunnan province as an example, the China-made GF-1multispectral remote sensing images with a 16 m×16 m resolution were obtained. Then, the time series that can reflect the difference of spectrum of P. notoginseng shed and the background objects were selected to the maximum extent, and the decision tree model of extraction the of P. notoginseng plots was constructed according to the spectral characteristics of the surface features. The results showed that the remote sensing classification method based on the decision tree model could extract P. notoginseng plots in the study area effectively. The method can provide technical support for extraction of P. notoginseng plots at county level. Copyright© by the Chinese Pharmaceutical Association.
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Incentive Control Strategies for Decision Problems with Parametric Uncertainties
NASA Astrophysics Data System (ADS)
Cansever, Derya H.
The central theme of this thesis is the design of incentive control policies in large scale systems with hierarchical decision structures, under the stipulation that the objective functionals of the agents at the lower level of the hierarchy are uncertain to the top-level controller (the leader). These uncertainties are modeled as a finite -dimensional parameter vector whose exact value constitutes private information to the relevant agent at the lower level. The approach we have adopted is to design incentive policies for the leader such that the dependence of the decision of the agents on the uncertain parameter is minimized. We have identified several classes of problems for which this approach is feasible. In particular, we have constructed policies whose performance is arbitrarily close to the solution of a version of the same problem that does not involve uncertainties. We have also shown that for a certain class of problem wherein the leader observes a linear combination of the agents' decisions, the leader can achieve the performance he would obtain if he had observed each decision separately.
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Clinical-decision support based on medical literature: A complex network approach
NASA Astrophysics Data System (ADS)
Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin
2016-10-01
In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.
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Beyeler, Michael; Dutt, Nikil D; Krichmar, Jeffrey L
2013-12-01
Understanding how the human brain is able to efficiently perceive and understand a visual scene is still a field of ongoing research. Although many studies have focused on the design and optimization of neural networks to solve visual recognition tasks, most of them either lack neurobiologically plausible learning rules or decision-making processes. Here we present a large-scale model of a hierarchical spiking neural network (SNN) that integrates a low-level memory encoding mechanism with a higher-level decision process to perform a visual classification task in real-time. The model consists of Izhikevich neurons and conductance-based synapses for realistic approximation of neuronal dynamics, a spike-timing-dependent plasticity (STDP) synaptic learning rule with additional synaptic dynamics for memory encoding, and an accumulator model for memory retrieval and categorization. The full network, which comprised 71,026 neurons and approximately 133 million synapses, ran in real-time on a single off-the-shelf graphics processing unit (GPU). The network was constructed on a publicly available SNN simulator that supports general-purpose neuromorphic computer chips. The network achieved 92% correct classifications on MNIST in 100 rounds of random sub-sampling, which is comparable to other SNN approaches and provides a conservative and reliable performance metric. Additionally, the model correctly predicted reaction times from psychophysical experiments. Because of the scalability of the approach and its neurobiological fidelity, the current model can be extended to an efficient neuromorphic implementation that supports more generalized object recognition and decision-making architectures found in the brain. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Research on strategy marine noise map based on i4ocean platform: Constructing flow and key approach
NASA Astrophysics Data System (ADS)
Huang, Baoxiang; Chen, Ge; Han, Yong
2016-02-01
Noise level in a marine environment has raised extensive concern in the scientific community. The research is carried out on i4Ocean platform following the process of ocean noise model integrating, noise data extracting, processing, visualizing, and interpreting, ocean noise map constructing and publishing. For the convenience of numerical computation, based on the characteristics of ocean noise field, a hybrid model related to spatial locations is suggested in the propagation model. The normal mode method K/I model is used for far field and ray method CANARY model is used for near field. Visualizing marine ambient noise data is critical to understanding and predicting marine noise for relevant decision making. Marine noise map can be constructed on virtual ocean scene. The systematic marine noise visualization framework includes preprocessing, coordinate transformation interpolation, and rendering. The simulation of ocean noise depends on realistic surface. Then the dynamic water simulation gird was improved with GPU fusion to achieve seamless combination with the visualization result of ocean noise. At the same time, the profile and spherical visualization include space, and time dimensionality were also provided for the vertical field characteristics of ocean ambient noise. Finally, marine noise map can be published with grid pre-processing and multistage cache technology to better serve the public.
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Role of the fibula in the stability of diaphyseal tibial fractures fixed by intramedullary nailing.
Galbraith, John G; Daly, Charles J; Harty, James A; Dailey, Hannah L
2016-10-01
For tibial fractures, the decision to fix a concomitant fibular fracture is undertaken on a case-by-case basis. To aid in this clinical decision-making process, we investigated whether loss of integrity of the fibula significantly destabilises midshaft tibial fractures, whether fixation of the fibula restores stability to the tibia, and whether removal of the fibula and interosseous membrane for expediency in biomechanical testing significantly influences tibial interfragmentary mechanics. Tibia/fibula pairs were harvested from six cadaveric donors with the interosseous membrane intact. A tibial osteotomy fracture was fixed by reamed intramedullary (IM) nailing. Axial, torsion, bending, and shear tests were completed for four models of fibular involvement: intact fibula, osteotomy fracture, fibular plating, and resected fibula and interosseous membrane. Overall construct stiffness decreased slightly with fibular osteotomy compared to intact bone, but this change was not statistically significant. Under low loads, the influence of the fibula on construct stability was only statistically significant in torsion (large effect size). Fibular plating stiffened the construct slightly, but this change was not statistically significant compared to the fibular osteotomy case. Complete resection of the fibula and interosseous membrane significantly decreased construct torsional stiffness only (large effect size). These results suggest that fixation of the fibula may not contribute significantly to the stability of diaphyseal tibial fractures and should not be undertaken unless otherwise clinically indicated. For testing purposes, load-sharing through the interosseous membrane contributes significantly to overall construct mechanics, especially in torsion, and we recommend preservation of these structures when possible. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Modeling the prediction of business intelligence system effectiveness.
Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I
2016-01-01
Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.
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Sivell, Stephanie; Edwards, Adrian; Elwyn, Glyn; Manstead, Antony S. R.
2010-01-01
Abstract Objective To describe the evidence about factors influencing breast cancer patients’ surgery choices and the implications for designing decision support in reference to an extended Theory of Planned Behaviour (TPB) and the Common Sense Model of Illness Representations (CSM). Background A wide range of factors are known to influence the surgery choices of women diagnosed with early breast cancer facing the choice of mastectomy or breast conservation surgery with radiotherapy. However, research does not always reflect the complexities of decision making and is often atheoretical. A theoretical approach, as provided by the CSM and the TPB, could help to identify and tailor support by focusing on patients’ representations of their breast cancer and predicting surgery choices. Design Literature search and narrative synthesis of data. Synthesis Twenty‐six studies reported women’s surgery choices to be influenced by perceived clinical outcomes of surgery, appearance and body image, treatment concerns, involvement in decision making and preferences of clinicians. These factors can be mapped onto the key constructs of both the TPB and CSM and used to inform the design and development of decision support interventions to ensure accurate information is provided in areas most important to patients. Conclusions The TPB and CSM have the potential to inform the design of decision support for breast cancer patients, with accurate and clear information that avoids leading patients to make decisions they may come to regret. Further research is needed examining how the components of the extended TPB and CSM account for patients’ surgery choices. PMID:20579123
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The complex contribution of sociodemographics to decision-making power in gay male couples.
Perry, Nicholas S; Huebner, David M; Baucom, Brian R W; Hoff, Colleen C
2016-12-01
Relationship power is an important dyadic construct in close relationships that is associated with relationship health and partner's individual health. Understanding what predicts power in heterosexual couples has proven difficult, and even less is known about gay couples. Resource models of power posit that demographic characteristics associated with social status (e.g., age, income) confer power within the relationship, which in turn shapes relationship outcomes. We tested this model in a sample of gay male couples (N = 566 couples) and extended it by examining race and HIV status. Multilevel modeling was used to test associations between demographic bases of power and decision-making power. We also examined relative associations among demographic bases and decision-making power with relationship satisfaction given the literature on power imbalances and overall relationship functioning. Results showed that individual income was positively associated with decision-making power, as was participant's HIV status, with HIV-positive men reporting greater power. Age differences within the relationship interacted with relationship length to predict decision-making power, but not satisfaction. HIV-concordant positive couples were less satisfied than concordant negative couples. Higher power partners were less satisfied than lower power partners. Demographic factors contributing to decision-making power among same-sex male couples appear to share some similarities with heterosexual couples (e.g., income is associated with power) and have unique features (e.g., HIV status influences power). However, these same demographics did not reliably predict relationship satisfaction in the manner that existing power theories suggest. Findings indicate important considerations for theories of power among same-sex male couples. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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NASA Astrophysics Data System (ADS)
Chang, Ni-Bin; Davila, Eric
2006-10-01
Solid waste management (SWM) is at the forefront of environmental concerns in the Lower Rio Grande Valley (LRGV), South Texas. The complexity in SWM drives area decision makers to look for innovative and forward-looking solutions to address various waste management options. In decision analysis, it is not uncommon for decision makers to go by an option that may minimize the maximum regret when some determinant factors are vague, ambiguous, or unclear. This article presents an innovative optimization model using the grey mini-max regret (GMMR) integer programming algorithm to outline an optimal regional coordination of solid waste routing and possible landfill/incinerator construction under an uncertain environment. The LRGV is an ideal location to apply the GMMR model for SWM planning because of its constant urban expansion, dwindling landfill space, and insufficient data availability signifying the planning uncertainty combined with vagueness in decision-making. The results give local decision makers hedged sets of options that consider various forms of systematic and event-based uncertainty. By extending the dimension of decision-making, this may lead to identifying a variety of beneficial solutions with efficient waste routing and facility siting for the time frame of 2005 through 2010 in LRGV. The results show the ability of the GMMR model to open insightful scenario planning that can handle situational and data-driven uncertainty in a way that was previously unavailable. Research findings also indicate that the large capital investment of incineration facilities makes such an option less competitive among municipal options for landfills. It is evident that the investment from a municipal standpoint is out of the question, but possible public-private partnerships may alleviate this obstacle.
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ANFIS multi criteria decision making for overseas construction projects: a methodology
NASA Astrophysics Data System (ADS)
Utama, W. P.; Chan, A. P. C.; Zulherman; Zahoor, H.; Gao, R.; Jumas, D. Y.
2018-02-01
A critical part when a company targeting a foreign market is how to make a better decision in connection with potential project selection. Since different attributes of information are often incomplete, imprecise and ill-defined in overseas projects selection, the process of decision making by relying on the experiences and intuition is a risky attitude. This paper aims to demonstrate a decision support method in deciding overseas construction projects (OCPs). An Adaptive Neuro-Fuzzy Inference System (ANFIS), the amalgamation of Neural Network and Fuzzy Theory, was used as decision support tool to decide to go or not go on OCPs. Root mean square error (RMSE) and coefficient of correlation (R) were employed to identify the ANFIS system indicating an optimum and efficient result. The optimum result was obtained from ANFIS network with two input membership functions, Gaussian membership function (gaussmf) and hybrid optimization method. The result shows that ANFIS may help the decision-making process for go/not go decision in OCPs.
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NASA Astrophysics Data System (ADS)
Forney, W.; Raunikar, R. P.; Bernknopf, R.; Mishra, S.
2012-12-01
A production possibilities frontier (PPF) is a graph comparing the production interdependencies for two commodities. In this case, the commodities are defined as the ecosystem services of agricultural production and groundwater quality. This presentation focuses on the refinement of techniques used in an application to estimate the value of remote sensing information. Value of information focuses on the use of uncertain and varying qualities of information within a specific decision-making context for a certain application, which in this case included land use, biogeochemical, hydrogeologic, economic and geospatial data and models. The refined techniques include deriving alternate patterns and processes of ecosystem functions, new estimates of ecosystem service values to construct a PPF, and the extension of this work into decision support systems. We have coupled earth observations of agricultural production with groundwater quality measurements to estimate the value of remote sensing information in northeastern Iowa to be 857M ± 198M (at the 2010 price level) per year. We will present an improved method for modeling crop rotation patterns to include multiple years of rotation, reduction in the assumptions associated with optimal land use allocations, and prioritized improvement of the resolution of input data (for example, soil resources and topography). The prioritization focuses on watersheds that were identified at a coarse-scale of analysis to have higher intensities of agricultural production and lower probabilities of groundwater survivability (in other words, remaining below a regulatory threshold for nitrate pollution) over time, and thus require finer-scaled modeling and analysis. These improved techniques and the simulation of certain scale-dependent policy and management actions, which trade-off the objectives of optimizing crop value versus maintaining potable groundwater, and provide new estimates for the empirical values of the PPF. The calculation of a PPF in this way provides a decision maker with a tool to consider the ramifications of different policies, management practices and regional objectives.
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NASA Astrophysics Data System (ADS)
Utomo, C.; Rahmawati, Y.; Pararta, D. L.; Ariesta, A.
2017-11-01
Readiness of infrastructure establishment is needed in the early phase of real estate development. To meet the needs of retail property in the form of traditional markets, the Government prepares to build a new 1300 units. Traditional market development requires infrastructure development. One of it is the preparation of sand material embankment as much as ± 200,000 m3. With a distance of 30 km, sand material can be delivered to the project site by dump trucks that can only be operated by 2 trip per day. The material is managed by using stockpile method. Decision of stockpile location requires multi person and multi criteria in a collaborative environment. The highest and the best use (HBU) criteria was used to construct a value-based decision hierarchy. Decision makers from five stakeholders analyzed the best of three locations by giving their own preference of development cost and HBU function. Analytical Hierarchy Process (AHP) based on satisfying options and cooperative game was applied for agreement options and coalition formation on collaborative decision. The result indicates that not all solutions become a possible location for the stockpile material. It shows the ‘best fit’ options process for all decision makers.
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Constructing an Urban Population Model for Medical Insurance Scheme Using Microsimulation Techniques
Xiong, Linping; Zhang, Lulu; Tang, Weidong; Ma, Yuqin
2012-01-01
China launched a pilot project of medical insurance reform in 79 cities in 2007 to cover urban nonworking residents. An urban population model was created in this paper for China's medical insurance scheme using microsimulation model techniques. The model made it clear for the policy makers the population distributions of different groups of people, the potential urban residents entering the medical insurance scheme. The income trends of units of individuals and families were also obtained. These factors are essential in making the challenging policy decisions when considering to balance the long-term financial sustainability of the medical insurance scheme. PMID:22481973
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A study of EMR-based medical knowledge network and its applications.
Zhao, Chao; Jiang, Jingchi; Xu, Zhiming; Guan, Yi
2017-05-01
Electronic medical records (EMRs) contain an amount of medical knowledge which can be used for clinical decision support. We attempt to integrate this medical knowledge into a complex network, and then implement a diagnosis model based on this network. The dataset of our study contains 992 records which are uniformly sampled from different departments of the hospital. In order to integrate the knowledge of these records, an EMR-based medical knowledge network (EMKN) is constructed. This network takes medical entities as nodes, and co-occurrence relationships between the two entities as edges. Selected properties of this network are analyzed. To make use of this network, a basic diagnosis model is implemented. Seven hundred records are randomly selected to re-construct the network, and the remaining 292 records are used as test records. The vector space model is applied to illustrate the relationships between diseases and symptoms. Because there may exist more than one actual disease in a record, the recall rate of the first ten results, and the average precision are adopted as evaluation measures. Compared with a random network of the same size, this network has a similar average length but a much higher clustering coefficient. Additionally, it can be observed that there are direct correlations between the community structure and the real department classes in the hospital. For the diagnosis model, the vector space model using disease as a base obtains the best result. At least one accurate disease can be obtained in 73.27% of the records in the first ten results. We constructed an EMR-based medical knowledge network by extracting the medical entities. This network has the small-world and scale-free properties. Moreover, the community structure showed that entities in the same department have a tendency to be self-aggregated. Based on this network, a diagnosis model was proposed. This model uses only the symptoms as inputs and is not restricted to a specific disease. The experiments conducted demonstrated that EMKN is a simple and universal technique to integrate different medical knowledge from EMRs, and can be used for clinical decision support. Copyright © 2017 Elsevier B.V. All rights reserved.
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Discrepancies between cognition and decision making in older adults
Boyle, Patricia A.; James, Bryan D.; Yu, Lei; Barnes, Lisa L.; Bennett, David A.
2015-01-01
Background and aims There is increasing clinical and legal interest in discrepancies between decision-making ability and cognition in old age, a stage of life when decisions have major ramifications. We investigated the frequency and correlates of such discrepancies in non-demented older adults participating in a large community-based cohort study of aging, the Rush Memory and Aging Project. Methods Participants [n = 689, mean age 81.8 (SD 7.6), mean education 15.2 (SD 3.1), 76.8 % female and 93.3 % white] completed a measure of financial and healthcare decision making (DM) and a battery of 19 neuropsychological tests from which a composite measure of global cognition (COG) was derived. Results Results indicated that 23.9 % of the sample showed a significant discrepancy between DM and COG abilities. Of these, 12.9 % showed DM < COG, while 11.0 % showed DM > COG. Logistic regression models showed older age, being non-white, greater temporal discounting, and greater risk aversion were associated with higher odds of being in the DM < COG group. Being male was associated with higher odds of being in the DM > COG group. Education, income, depressive symptoms, and impulsivity were not associated with a discrepancy. Only demographic associations (age, sex, and race) remained significant in a fully adjusted model with terms included for all factors. Conclusion These results support the consideration of decision making and cognition as potentially separate constructs. PMID:25995167
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Discrepancies between cognition and decision making in older adults.
Han, S Duke; Boyle, Patricia A; James, Bryan D; Yu, Lei; Barnes, Lisa L; Bennett, David A
2016-02-01
There is increasing clinical and legal interest in discrepancies between decision-making ability and cognition in old age, a stage of life when decisions have major ramifications. We investigated the frequency and correlates of such discrepancies in non-demented older adults participating in a large community-based cohort study of aging, the Rush Memory and Aging Project. Participants [n = 689, mean age 81.8 (SD 7.6), mean education 15.2 (SD 3.1), 76.8 % female and 93.3 % white] completed a measure of financial and healthcare decision making (DM) and a battery of 19 neuropsychological tests from which a composite measure of global cognition (COG) was derived. Results indicated that 23.9 % of the sample showed a significant discrepancy between DM and COG abilities. Of these, 12.9 % showed DM < COG, while 11.0 % showed DM > COG. Logistic regression models showed older age, being non-white, greater temporal discounting, and greater risk aversion were associated with higher odds of being in the DM < COG group. Being male was associated with higher odds of being in the DM > COG group. Education, income, depressive symptoms, and impulsivity were not associated with a discrepancy. Only demographic associations (age, sex, and race) remained significant in a fully adjusted model with terms included for all factors. These results support the consideration of decision making and cognition as potentially separate constructs.
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A model for interprovincial air pollution control based on futures prices.
Zhao, Laijun; Xue, Jian; Gao, Huaizhu Oliver; Li, Changmin; Huang, Rongbing
2014-05-01
Based on the current status of research on tradable emission rights futures, this paper introduces basic market-related assumptions for China's interprovincial air pollution control problem. The authors construct an interprovincial air pollution control model based on futures prices: the model calculated the spot price of emission rights using a classic futures pricing formula, and determined the identities of buyers and sellers for various provinces according to a partitioning criterion, thereby revealing five trading markets. To ensure interprovincial cooperation, a rational allocation result for the benefits from this model was achieved using the Shapley value method to construct an optimal reduction program and to determine the optimal annual decisions for each province. Finally, the Beijing-Tianjin-Hebei region was used as a case study, as this region has recently experienced serious pollution. It was found that the model reduced the overall cost of reducing SO2 pollution. Moreover, each province can lower its cost for air pollution reduction, resulting in a win-win solution. Adopting the model would therefore enhance regional cooperation and promote the control of China's air pollution. The authors construct an interprovincial air pollution control model based on futures prices. The Shapley value method is used to rationally allocate the cooperation benefit. Interprovincial pollution control reduces the overall reduction cost of SO2. Each province can lower its cost for air pollution reduction by cooperation.
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Angelis, Aris; Kanavos, Panos
2017-09-01
Escalating drug prices have catalysed the generation of numerous "value frameworks" with the aim of informing payers, clinicians and patients on the assessment and appraisal process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions. In this paper, a Multiple Criteria Decision Analysis (MCDA) methodological process, based on Multi Attribute Value Theory (MAVT), is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down "value-focused thinking" approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers' concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory. The resulting value tree (Advance Value Tree) consists of three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative treatment options, assigning relative weights of importance to the criteria, and combining scores and weights. Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a structured and transparent way. Given its flexibility to meet diverse requirements and become readily adaptable across different settings, the Advance Value Framework could be offered as a decision-support tool for evaluators and payers to aid coverage and reimbursement of new medicines. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
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NASA Astrophysics Data System (ADS)
Coopersmith, Evan Joseph
The techniques and information employed for decision-making vary with the spatial and temporal scope of the assessment required. In modern agriculture, the farm owner or manager makes decisions on a day-to-day or even hour-to-hour basis for dozens of fields scattered over as much as a fifty-mile radius from some central location. Following precipitation events, land begins to dry. Land-owners and managers often trace serpentine paths of 150+ miles every morning to inspect the conditions of their various parcels. His or her objective lies in appropriate resource usage -- is a given tract of land dry enough to be workable at this moment or would he or she be better served waiting patiently? Longer-term, these owners and managers decide upon which seeds will grow most effectively and which crops will make their operations profitable. At even longer temporal scales, decisions are made regarding which fields must be acquired and sold and what types of equipment will be necessary in future operations. This work develops and validates algorithms for these shorter-term decisions, along with models of national climate patterns and climate changes to enable longer-term operational planning. A test site at the University of Illinois South Farms (Urbana, IL, USA) served as the primary location to validate machine learning algorithms, employing public sources of precipitation and potential evapotranspiration to model the wetting/drying process. In expanding such local decision support tools to locations on a national scale, one must recognize the heterogeneity of hydroclimatic and soil characteristics throughout the United States. Machine learning algorithms modeling the wetting/drying process must address this variability, and yet it is wholly impractical to construct a separate algorithm for every conceivable location. For this reason, a national hydrological classification system is presented, allowing clusters of hydroclimatic similarity to emerge naturally from annual regime curve data and facilitate the development of cluster-specific algorithms. Given the desire to enable intelligent decision-making at any location, this classification system is developed in a manner that will allow for classification anywhere in the U.S., even in an ungauged basin. Daily time series data from 428 catchments in the MOPEX database are analyzed to produce an empirical classification tree, partitioning the United States into regions of hydroclimatic similarity. In constructing a classification tree based upon 55 years of data, it is important to recognize the non-stationary nature of climate data. The shifts in climatic regimes will cause certain locations to shift their ultimate position within the classification tree, requiring decision-makers to alter land usage, farming practices, and equipment needs, and algorithms to adjust accordingly. This work adapts the classification model to address the issue of regime shifts over larger temporal scales and suggests how land-usage and farming protocol may vary from hydroclimatic shifts in decades to come. Finally, the generalizability of the hydroclimatic classification system is tested with a physically-based soil moisture model calibrated at several locations throughout the continental United States. The soil moisture model is calibrated at a given site and then applied with the same parameters at other sites within and outside the same hydroclimatic class. The model's performance deteriorates minimally if the calibration and validation location are within the same hydroclimatic class, but deteriorates significantly if the calibration and validates sites are located in different hydroclimatic classes. These soil moisture estimates at the field scale are then further refined by the introduction of LiDAR elevation data, distinguishing faster-drying peaks and ridges from slower-drying valleys. The inclusion of LiDAR enabled multiple locations within the same field to be predicted accurately despite non-identical topography. This cross-application of parametric calibrations and LiDAR-driven disaggregation facilitates decision-support at locations without proximally-located soil moisture sensors.
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A Small Aircraft Transportation System (SATS) Demand Model
NASA Technical Reports Server (NTRS)
Long, Dou; Lee, David; Johnson, Jesse; Kostiuk, Peter; Yackovetsky, Robert (Technical Monitor)
2001-01-01
The Small Aircraft Transportation System (SATS) demand modeling is a tool that will be useful for decision-makers to analyze SATS demands in both airport and airspace. We constructed a series of models following the general top-down, modular principles in systems engineering. There are three principal models, SATS Airport Demand Model (SATS-ADM), SATS Flight Demand Model (SATS-FDM), and LMINET-SATS. SATS-ADM models SATS operations, by aircraft type, from the forecasts in fleet, configuration and performance, utilization, and traffic mixture. Given the SATS airport operations such as the ones generated by SATS-ADM, SATS-FDM constructs the SATS origin and destination (O&D) traffic flow based on the solution of the gravity model, from which it then generates SATS flights using the Monte Carlo simulation based on the departure time-of-day profile. LMINET-SATS, an extension of LMINET, models SATS demands at airspace and airport by all aircraft operations in US The models use parameters to provide the user with flexibility and ease of use to generate SATS demand for different scenarios. Several case studies are included to illustrate the use of the models, which are useful to identify the need for a new air traffic management system to cope with SATS.
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Kucukvar, Murat; Egilmez, Gokhan; Tatari, Omer
2014-06-01
Waste management in construction is critical for the sustainable treatment of building-related construction and demolition (C&D) waste materials, and recycling of these wastes has been considered as one of the best strategies in minimization of C&D debris. However, recycling of C&D materials may not always be a feasible strategy for every waste type and therefore recycling and other waste treatment strategies should be supported by robust decision-making models. With the aim of assessing the net carbon, energy, and water footprints of C&D recycling and other waste management alternatives, a comprehensive economic input-output-based hybrid life-cycle assessment model is developed by tracing all of the economy-wide supply-chain impacts of three waste management strategies: recycling, landfilling, and incineration. Analysis results showed that only the recycling of construction materials provided positive environmental footprint savings in terms of carbon, energy, and water footprints. Incineration is a better option as a secondary strategy after recycling for water and energy footprint categories, whereas landfilling is found to be as slightly better strategy when carbon footprint is considered as the main focus of comparison. In terms of construction materials' environmental footprint, nonferrous metals are found to have a significant environmental footprint reduction potential if recycled. © The Author(s) 2014.
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Deep Space Network (DSN), Network Operations Control Center (NOCC) computer-human interfaces
NASA Technical Reports Server (NTRS)
Ellman, Alvin; Carlton, Magdi
1993-01-01
The technical challenges, engineering solutions, and results of the NOCC computer-human interface design are presented. The use-centered design process was as follows: determine the design criteria for user concerns; assess the impact of design decisions on the users; and determine the technical aspects of the implementation (tools, platforms, etc.). The NOCC hardware architecture is illustrated. A graphical model of the DSN that represented the hierarchical structure of the data was constructed. The DSN spacecraft summary display is shown. Navigation from top to bottom is accomplished by clicking the appropriate button for the element about which the user desires more detail. The telemetry summary display and the antenna color decision table are also shown.
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As we enter the era of precision medicine, characterization of cancer genomes will directly influence therapeutic decisions in the clinic. Here we describe a platform enabling functionalization of rare gene mutations through their high-throughput construction, molecular barcoding and delivery to cancer models for in vivo tumour driver screens. We apply these technologies to identify oncogenic drivers of pancreatic ductal adenocarcinoma (PDAC).
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Decision Analysis of the Benefits and Costs of Screening for Prostate Cancer
2011-08-01
REPORT DATE: TYPE OF REPORT: Annual PREPARED FOR: U.S. Army Medical Research and Materiel Command...MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland...constructed and in men aged 55 to 75. Results of this model have been published in the Journal of the American Medical Association, presented at
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ERIC Educational Resources Information Center
Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying
2011-01-01
Monte Carlo methods can be used in data analytic situations (e.g., validity studies) to make decisions about sample size and to estimate power. The purpose of using Monte Carlo methods in a validity study is to improve the methodological approach within a study where the primary focus is on construct validity issues and not on advancing…
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ERIC Educational Resources Information Center
Buckland, M.K.; Woodburn, I.
A research project is being conducted to construct a mathematical model of the operations of an academic library to be used in making managerial decisions. As part of this project, this report examines Bradford's Law of Scattering and the fall-off of use of documents as they age. A series of mathematical analyses indicate how these two laws can be…
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Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jang, Minho, E-mail: minmin40@hanmail.net; Hong, Taehoon, E-mail: hong7@yonsei.ac.kr; Ji, Changyoon, E-mail: chnagyoon@yonsei.ac.kr
2015-01-15
The assessment of the embodied environmental impacts of buildings can help decision-makers plan environment-friendly buildings and reduce environmental impacts. For a more comprehensive assessment of the embodied environmental impacts of buildings, a hybrid life cycle assessment model was developed in this study. The developed model can assess the embodied environmental impacts (global warming, ozone layer depletion, acidification, eutrophication, photochemical ozone creation, abiotic depletion, and human toxicity) generated directly and indirectly in the material manufacturing, transportation, and construction phases. To demonstrate the application and validity of the developed model, the environmental impacts of an elementary school building were assessed using themore » developed model and compared with the results of a previous model used in a case study. The embodied environmental impacts from the previous model were lower than those from the developed model by 4.6–25.2%. Particularly, human toxicity potential (13 kg C{sub 6}H{sub 6} eq.) calculated by the previous model was much lower (1965 kg C{sub 6}H{sub 6} eq.) than what was calculated by the developed model. The results indicated that the developed model can quantify the embodied environmental impacts of buildings more comprehensively, and can be used by decision-makers as a tool for selecting environment-friendly buildings. - Highlights: • The model was developed to assess the embodied environmental impacts of buildings. • The model evaluates GWP, ODP, AP, EP, POCP, ADP, and HTP as environmental impacts. • The model presents more comprehensive results than the previous model by 4.6–100%. • The model can present the HTP of buildings, which the previous models cannot do. • Decision-makers can use the model for selecting environment-friendly buildings.« less
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Distribution Free Approach for Coordination of a Supply Chain with Consumer Return
NASA Astrophysics Data System (ADS)
Hu, Jinsong; Xu, Yuanji
Consumer return is considered in a coordination of a supply chain consisting of one manufacturer and one retailer. A distribution free approach is employed to deal with a centralized decision model and a decentralized model which are constructed under the situation with only knowing the demand function's mean and variance, respectively. A markdown money contract is designed to coordinate the supply chain, and it is also proved that the contract can make the supply chain perfectly coordinated. Several numerical examples are given at the end of this paper.
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Khosravi, Khabat; Pham, Binh Thai; Chapi, Kamran; Shirzadi, Ataollah; Shahabi, Himan; Revhaug, Inge; Prakash, Indra; Tien Bui, Dieu
2018-06-15
Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due to sudden change in climatic condition and manmade factors. However, prior identification of flood susceptible areas can be done with the help of machine learning techniques for proper timely management of flood hazards. In this study, we tested four decision trees based machine learning models namely Logistic Model Trees (LMT), Reduced Error Pruning Trees (REPT), Naïve Bayes Trees (NBT), and Alternating Decision Trees (ADT) for flash flood susceptibility mapping at the Haraz Watershed in the northern part of Iran. For this, a spatial database was constructed with 201 present and past flood locations and eleven flood-influencing factors namely ground slope, altitude, curvature, Stream Power Index (SPI), Topographic Wetness Index (TWI), land use, rainfall, river density, distance from river, lithology, and Normalized Difference Vegetation Index (NDVI). Statistical evaluation measures, the Receiver Operating Characteristic (ROC) curve, and Freidman and Wilcoxon signed-rank tests were used to validate and compare the prediction capability of the models. Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively. These techniques have proven successful in quickly determining flood susceptible areas. Copyright © 2018 Elsevier B.V. All rights reserved.
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Leitão, J P; Matos, J S; Gonçalves, A B; Matos, J L
2005-01-01
This paper presents the contributions of Geographic Information Systems (GIS) and location models towards planning regional wastewater systems (sewers and wastewater treatment plants) serving small agglomerations, i.e. agglomerations with less than 2,000 inhabitants. The main goal was to develop a decision support tool for tracing and locating regional wastewater systems. The main results of the model are expressed in terms of number, capacity and location of Wastewater Treatment Plants (WWTP) and the length of main sewers. The decision process concerning the location and capacity of wastewater systems has a number of parameters that can be optimized. These parameters include the total sewer length and number, capacity and location of WWTP. The optimization of parameters should lead to the minimization of construction and operation costs of the integrated system. Location models have been considered as tools for decision support, mainly when a geo-referenced database can be used. In these cases, the GIS may represent an important role for the analysis of data and results especially in the preliminary stage of planning and design. After selecting the spatial location model and the heuristics, two greedy algorithms were implemented in Visual Basic for Applications on the ArcGIS software environment. To illustrate the application of these algorithms a case study was developed, in a rural area located in the central part of Portugal.
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ERIC Educational Resources Information Center
Guay, Frederic
2005-01-01
The purpose of the present research was to develop and validate a measure of motivation toward career decision-making activities, the Career Decision-Making Autonomy Scale (CDMAS). The CDMAS is designed to assess the constructs of intrinsic motivation, identified regulation, introjected regulation, and external regulation. A longitudinal study was…
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Shi, Guo; Zhang, Shun-xiang
2013-03-01
To synthesize relevant data and to analyze the benefit-cost ratio on strategies related to preventing the maternal-infantile transmission of hepatitis B virus infection and to explore the optimal strategy. A decision tree model was constructed according to the strategies of hepatitis B immunization and a Markov model was conducted to simulate the complex disease progress after HBV infection. Parameters in the models were drawn from meta-analysis and information was collected from field study and review of literature. Economic evaluation was performed to calculate costs, benefit, and the benefit-cost ratio. Sensitivity analysis was also conducted and a tornado graph was drawn. In view of the current six possible strategies in preventing maternal-infantile transmission of hepatitis B virus infection, a multi-stage decision tree model was constructed to screen hepatitis B surface antigen (HBsAg) or screen for HBsAg then hepatitis B e antigen (HBeAg). Dose and the number of injections of HBIG and hepatitis B vaccine were taken into consideration in the model. All the strategies were considered to be cost-saving, while the strategy of screening for HBsAg and then offering hepatitis B vaccine of 10 µg×3 for all neonates with hepatitis B immunoglobulin (HBIG) of 100 IU×1 for the neonates born to mothers who tested positive for HBsAg appeared with most cost-saving. In the strategies, the benefit-cost ratio of using 100 IU HBIG was similar to 200 IU HBIG, and one shot of HBIG was superior to two shots. from sensitivity analysis suggested that the rates of immunization and the efficacy of the strategy in preventing maternal-infantile transmission were the main sensitive variables in the model. The passive-active immune-prophylaxis strategy that using 10 µg hepatitis B vaccine combined with 100 IU HBIG seemed to be the optimal strategy in preventing maternal-infantile transmission, while the rates of immunization and the efficacy of the strategy played the key roles in choosing the ideal strategy.
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NASA Astrophysics Data System (ADS)
Maharik, Michael
This thesis addresses the public perception of the risk of a technology not widely known to laypeople. Its aims were (1) to characterize public perceptions of the risk of using nuclear energy in space and decisions related to this risk, and (2) to extend the 'mental model' methodology to studying public perception of unfamiliar, risky technologies. A model of the physical processes capable of creating risks from using nuclear energy sources in space was first constructed. Then, knowledge and beliefs related to this topic were elicited from three different groups of people. The generality of the findings was examined in a constructive replication with environmentally-oriented people. The possibility of involving the public in decision-making processes related to engineering macro-design was then investigated. Finally, a communication regarding these risk processes was developed and evaluated in an experiment comparing it with communications produced by NASA. Although they included large portions of the expert model, people's beliefs also had gaps and misconceptions. Respondents often used scientific terms without a clear understanding of what they meant. Respondents' mental models sometimes contained scattered and inconsistent entries. The impact of pre-existing mental models was clearly seen. Different groups of people had different patterns of knowledge and beliefs. Nevertheless, respondents expressed reasonable and coherent opinions on choices among engineering options. The CMU brochure, derived from the study of readers' existing mental models, provided a better risk communication tool than NASA's material, reflecting primarily experts' perspective. The better performance of subjects reading either brochure generally reflected adding knowledge on issues that they had not previously known, rather than correcting wrong beliefs. The communication study confirmed a hypothesis that improving knowledge on risk processes related to the use of a technology causes a more favorable attitude towards that technology. Recommendations related to the design and targeting of risk communication, and to public participation in decision-making on using new and risky technologies, are derived. Additional studies that will elicit laypeople's definitions of risk related to specific technologies, and link their detailed understanding of risk-development processes to the perceived dimensions of risk, are suggested.
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Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention
Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise
2015-01-01
Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases. PMID:26295344
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Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.
Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise
2015-01-01
Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases.
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Davies, Kylie; Bulsara, Max K; Ramelet, Anne-Sylvie; Monterosso, Leanne
2018-05-01
To establish criterion-related construct validity and test-retest reliability for the Endotracheal Suction Assessment Tool© (ESAT©). Endotracheal tube suction performed in children can significantly affect clinical stability. Previously identified clinical indicators for endotracheal tube suction were used as criteria when designing the ESAT©. Content validity was reported previously. The final stages of psychometric testing are presented. Observational testing was used to measure construct validity and determine whether the ESAT© could guide "inexperienced" paediatric intensive care nurses' decision-making regarding endotracheal tube suction. Test-retest reliability of the ESAT© was performed at two time points. The researchers and paediatric intensive care nurse "experts" developed 10 hypothetical clinical scenarios with predetermined endotracheal tube suction outcomes. "Experienced" (n = 12) and "inexperienced" (n = 14) paediatric intensive care nurses were presented with the scenarios and the ESAT© guiding decision-making about whether to perform endotracheal tube suction for each scenario. Outcomes were compared with those predetermined by the "experts" (n = 9). Test-retest reliability of the ESAT© was measured at two consecutive time points (4 weeks apart) with "experienced" and "inexperienced" paediatric intensive care nurses using the same scenarios and tool to guide decision-making. No differences were observed between endotracheal tube suction decisions made by "experts" (n = 9), "inexperienced" (n = 14) and "experienced" (n = 12) nurses confirming the tool's construct validity. No differences were observed between groups for endotracheal tube suction decisions at T1 and T2. Criterion-related construct validity and test-retest reliability of the ESAT© were demonstrated. Further testing is recommended to confirm reliability in the clinical setting with the "inexperienced" nurse to guide decision-making related to endotracheal tube suction. The ESAT© is the first validated tool to systematically guide endotracheal nursing practice for the "inexperienced" nurse. © 2018 John Wiley & Sons Ltd.
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Scaglione, Nichole M.; Hultgren, Brittney A.; Reavy, Racheal; Mallett, Kimberly A.; Turrisi, Rob; Cleveland, Michael J.; Sell, Nichole M.
2015-01-01
Objective Recent studies suggest drinking protective behaviors (DPBs) and contextual protective behaviors (CPBs) can uniquely reduce alcohol-related sexual risk in college students. Few studies have examined CPBs independently, and even fewer have utilized theory to examine modifiable psychosocial predictors of students’ decisions to use CPBs. The current study used a prospective design to examine 1) rational and reactive pathways and psychosocial constructs predictive of CPB use, and 2) how gender might moderate these influences in a sample of college students. Method Students (n = 508) completed web-based baseline (mid-spring semester) and 1- and 6-month follow-up assessments of CPB use; psychosocial constructs (expectancies, normative beliefs, attitudes, and self-concept); and rational and reactive pathways (intentions and willingness). Regression was used to examine rational and reactive influences as proximal predictors of CPB use at the 6-month follow-up. Subsequent path analyses examined the effects of psychosocial constructs, as distal predictors of CPB use, mediated through the rational and reactive pathways. Results Both rational (intentions to use CPB) and reactive (willingness to use CPB) influences were significantly associated with increased CPB use. The examined distal predictors were found to effect CPB use differentially through the rational and reactive pathways. Gender did not significantly moderate any relationships within in the model. Discussion Findings suggest potential entry points for increasing CPB use that include both rational and reactive pathways. Overall, this study demonstrates the mechanisms underlying how to increase the use of CPBs in programs designed to reduce alcohol-related sexual consequences and victimization. PMID:26415062
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Scaglione, Nichole M; Hultgren, Brittney A; Reavy, Racheal; Mallett, Kimberly A; Turrisi, Rob; Cleveland, Michael J; Sell, Nichole M
2015-09-01
Recent studies suggest drinking protective behaviors (DPBs) and contextual protective behaviors (CPBs) can uniquely reduce alcohol-related sexual risk in college students. Few studies have examined CPBs independently, and even fewer have utilized theory to examine modifiable psychosocial predictors of students' decisions to use CPBs. The current study used a prospective design to examine (a) rational and reactive pathways and psychosocial constructs predictive of CPB use and (b) how gender might moderate these influences in a sample of college students. Students (n = 508) completed Web-based baseline (mid-Spring semester) and 1- and 6-month follow-up assessments of CPB use; psychosocial constructs (expectancies, normative beliefs, attitudes, and self-concept); and rational and reactive pathways (intentions and willingness). Regression was used to examine rational and reactive influences as proximal predictors of CPB use at the 6-month follow-up. Subsequent path analyses examined the effects of psychosocial constructs, as distal predictors of CPB use, mediated through the rational and reactive pathways. Both rational (intentions to use CPB) and reactive (willingness to use CPB) influences were significantly associated with increased CPB use. The examined distal predictors were found to effect CPB use differentially through the rational and reactive pathways. Gender did not significantly moderate any relationships within in the model. Findings suggest potential entry points for increasing CPB use that include both rational and reactive pathways. Overall, this study demonstrates the mechanisms underlying how to increase the use of CPBs in programs designed to reduce alcohol-related sexual consequences and victimization. (c) 2015 APA, all rights reserved).
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Patient participation in palliative care decisions: An ethnographic discourse analysis
Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert
2016-01-01
The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize decisions that shaped patients’ dying trajectories. Discourse analysis encourages awareness of the role of language in either promoting or hindering patient participation in decision-making. PMID:27882864
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Patient participation in palliative care decisions: An ethnographic discourse analysis.
Bélanger, Emmanuelle; Rodríguez, Charo; Groleau, Danielle; Légaré, France; MacDonald, Mary Ellen; Marchand, Robert
2016-01-01
The participation of patients in making decisions about their care is especially important towards the end of life because palliative care decisions involve extensive uncertainty and are heavily influenced by personal values. Yet, there is a scarcity of studies directly observing clinical interactions between palliative patients and their health care providers. In this study, we aimed to understand how patient participation in palliative care decisions is constructed through discourse in a community hospital-based palliative care team. This qualitative study combined ethnographic observations of a palliative care team with discourse analysis. Eighteen palliative care patients with cancer diagnoses, six family physicians, and two nurses were involved in the study. Multiple interactions were observed between each patient and health care providers over the course of 1 year, for a total of 101 consultations, 24 of which were audio-recorded. The analysis consisted in looking for the interpretive repertoires (i.e., familiar lines of argument used to justify actions) that were used to justify patient participation in decision-making during clinical interactions, as well as exploring their implications for decision roles and end-of-life care. Patients and their health care providers seldom addressed their decision-making roles explicitly. Rather, they constructed patient participation in palliative care decisions in a covert manner. Four interpretive repertoires were used to justify patient participation: (1) exposing uncertainty, (2) co-constructing patient preferences, (3) affirming patient autonomy, and finally (4) upholding the authority of health care providers. The results demonstrate how patients and health care providers used these arguments to negotiate their respective roles in decision-making. In conclusion, patients and health care providers used a variety of interpretive repertoires to covertly negotiate their roles in decision-making, and to legitimize decisions that shaped patients' dying trajectories. Discourse analysis encourages awareness of the role of language in either promoting or hindering patient participation in decision-making.
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The Space Environmental Impact System
NASA Astrophysics Data System (ADS)
Kihn, E. A.
2009-12-01
The Space Environmental Impact System (SEIS) is an operational tool for incorporating environmental data sets into DoD Modeling and Simulation (M&S) which allows for enhanced decision making regarding acquisitions, testing, operations and planning. The SEIS system creates, from the environmental archives and developed rule-base, a tool for describing the effects of the space environment on particular military systems, both historically and in real-time. The system uses data available over the web, and in particular data provided by NASA’s virtual observatory network, as well as modeled data generated specifically for this purpose. The rule base system developed to support SEIS is an open XML based model which can be extended to events from any environmental domain. This presentation will show how the SEIS tool allows users to easily and accurately evaluate the effect of space weather in terms that are meaningful to them as well as discuss the relevant standards used in its construction and go over lessons learned from fielding an operational environmental decision tool.
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Bobko, Philip; Barelka, Alex J; Hirshfield, Leanne M
2014-05-01
The objective was to review and integrate available research about the construct of state-level suspicion as it appears in social science literatures and apply the resulting findings to information technology (IT) contexts. Although the human factors literature is replete with articles about trust (and distrust) in automation, there is little on the related, but distinct, construct of "suspicion" (in either automated or IT contexts). The construct of suspicion--its precise definition, theoretical correlates, and role in such applications--deserves further study. Literatures that consider suspicion are reviewed and integrated. Literatures include communication, psychology, human factors, management, marketing, information technology, and brain/neurology. We first develop a generic model of state-level suspicion. Research propositions are then derived within IT contexts. Fundamental components of suspicion include (a) uncertainty, (b) increased cognitive processing (e.g., generation of alternative explanations for perceived discrepancies), and (c) perceptions of (mal)intent. State suspicion is defined as the simultaneous occurrence of these three components. Our analysis also suggests that trust inhibits suspicion, whereas distrust can be a catalyst of state-level suspicion. Based on a three-stage model of state-level suspicion, associated research propositions and questions are developed. These propositions and questions are intended to help guide future work on the measurement of suspicion (self-report and neurological), as well as the role of the construct of suspicion in models of decision making and detection of deception. The study of suspicion, including its correlates, antecedents, and consequences, is important. We hope that the social sciences will benefit from our integrated definition and model of state suspicion. The research propositions regarding suspicion in IT contexts should motivate substantial research in human factors and related fields.
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‘If you are good, I get better’: the role of social hierarchy in perceptual decision-making
Pannunzi, Mario; Ayneto, Alba; Deco, Gustavo; Sebastián-Gallés, Nuria
2014-01-01
So far, it was unclear if social hierarchy could influence sensory or perceptual cognitive processes. We evaluated the effects of social hierarchy on these processes using a basic visual perceptual decision task. We constructed a social hierarchy where participants performed the perceptual task separately with two covertly simulated players (superior, inferior). Participants were faster (better) when performing the discrimination task with the superior player. We studied the time course when social hierarchy was processed using event-related potentials and observed hierarchical effects even in early stages of sensory-perceptual processing, suggesting early top–down modulation by social hierarchy. Moreover, in a parallel analysis, we fitted a drift-diffusion model (DDM) to the results to evaluate the decision making process of this perceptual task in the context of a social hierarchy. Consistently, the DDM pointed to nondecision time (probably perceptual encoding) as the principal period influenced by social hierarchy. PMID:23946003
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Water flow algorithm decision support tool for travelling salesman problem
NASA Astrophysics Data System (ADS)
Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd
2016-08-01
This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.
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NASA Astrophysics Data System (ADS)
Kozlovská, Mária; Struková, Zuzana
2013-06-01
Several factors should be considered by the owner and general contractor in the process of contractors` and subcontractors` selection and evaluation. The paper reviews the recent models addressed to guide general contractors in subcontractors' selection process and in evaluation of different contractors during the execution of the project. Moreover the paper suggests the impact of different contractors' performance to the overall level of occupational health and safety culture at the sites. It deals with the factors influencing the safety performance of contractors during construction and analyses the methods for assessing the safety performance of construction contractors. The results of contractors' safety performance evaluation could be a useful tool in motivating contractors to achieve better safety outcomes or could have effect on owners` or general contractors' decision making about contractors suitability for future contracting works.
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Research-based-decision-making in Canadian health organizations: a behavioural approach.
Jbilou, Jalila; Amara, Nabil; Landry, Réjean
2007-06-01
Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment... These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build networks, develop partnerships between professionals locally, regionally and nationally, and also act as change agents in the dissemination and adoption of knowledge and innovations in health services. However, the research focused on knowledge use as a support to decision-making, further research is needed to identify and evaluate effective incentives and strategies to implement so as to enhance RBDM adoption among health decision makers and more theoretical development are to complete in this perspective.
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The influence of averaging and noisy decision strategies on the recognition memory ROC.
Malmberg, Kenneth J; Xu, Jing
2006-02-01
Many single- and dual-process models of recognition memory predict that the ratings and remember-know receiver operating characteristics (ROCs) are the same, but Rotello, Macmillan, and Reeder (2004) reported that the slopes of the remember-know and ratings z-transformed ROCs (zROCs) are different The authors show that averaging introduces nonlinearities to the form of the zROC and that ratings and remember-know zROCs are indistinguishable when constructed in a conventional manner. The authors show, further, that some nonoptimal decision strategies have a distinctive, nonlinear effect on the form of the single-process continuous-state zROC. The conclusion is that many factors having nothing to do with the nature of recognition memory can affect the shape of zROCs, and that therefore, the shape of the zROC does not, alone, characterize different memory models.
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Retirement and death in office of U.S. Supreme Court justices.
Stolzenberg, Ross M; Lindgren, James
2010-05-01
We construct demographic models of retirement and death in office of U.S. Supreme Court justices, a group that has gained demographic notice, evaded demographic analysis, and is said to diverge from expected retirement patterns. Models build on prior multistate labor force status studies, and data permit an unusually clear distinction between voluntary and "induced" retirement. Using data on every justice from 1789 through 2006, with robust, cluster-corrected, discrete-time, censored, event-history methods, we (1) estimate retirement effects of pension eligibility, age, health, and tenure on the timing of justices' retirements and deaths in office, (2) resolve decades of debate over the politicized departure hypothesis that justices tend to alter the timing of their retirements for the political benefit or detriment of the incumbent president, (3) reconsider the nature of rationality in retirement decisions, and (4) consider the relevance of organizational conditions as well as personal circumstances to retirement decisions. Methodological issues are addressed.
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Collaborative, Sequential and Isolated Decisions in Design
NASA Technical Reports Server (NTRS)
Lewis, Kemper; Mistree, Farrokh
1997-01-01
The Massachusetts Institute of Technology (MIT) Commission on Industrial Productivity, in their report Made in America, found that six recurring weaknesses were hampering American manufacturing industries. The two weaknesses most relevant to product development were 1) technological weakness in development and production, and 2) failures in cooperation. The remedies to these weaknesses are considered the essential twin pillars of CE: 1) improved development process, and 2) closer cooperation. In the MIT report, it is recognized that total cooperation among teams in a CE environment is rare in American industry, while the majority of the design research in mathematically modeling CE has assumed total cooperation. In this paper, we present mathematical constructs, based on game theoretic principles, to model degrees of collaboration characterized by approximate cooperation, sequential decision making and isolation. The design of a pressure vessel and a passenger aircraft are included as illustrative examples.
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NASA Technical Reports Server (NTRS)
Haldemann, Albert F. C.; Johnson, Jerome B.; Elphic, Richard C.; Boynton, William V.; Wetzel, John
2006-01-01
CRUX is a modular suite of geophysical and borehole instruments combined with display and decision support system (MapperDSS) tools to characterize regolith resources, surface conditions, and geotechnical properties. CRUX is a NASA-funded Technology Maturation Program effort to provide enabling technology for Lunar and Planetary Surface Operations (LPSO). The MapperDSS uses data fusion methods with CRUX instruments, and other available data and models, to provide regolith properties information needed for LPSO that cannot be determined otherwise. We demonstrate the data fusion method by showing how it might be applied to characterize the distribution and form of hydrogen using a selection of CRUX instruments: Borehole Neutron Probe and Thermal Evolved Gas Analyzer data as a function of depth help interpret Surface Neutron Probe data to generate 3D information. Secondary information from other instruments along with physical models improves the hydrogen distribution characterization, enabling information products for operational decision-making.
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[Chances and limitations of patients' advance decisions at the end of life].
Bauer, Axel W
2009-01-01
Death by "natural" causes is not appreciated in Western industrialized countries because it may be regarded as an obstacle against performance and consumption. In addition, life-saving therapies for patients with an infaust prognosis are often rather expensive and therefore classified as "futile". Utilitarian measures for the individual's quality of life (QALY's), which are allegedly objective, veil the fact that they can only reflect the parameters that have been considered during their construction. Caused by fear of a life in the nursing home, which is partially intensified by the media, many ethicists and lawyers propagate anticipating models of retaining patients' autonomy at the end of life. Apart from general considerations published by the former National Ethics Council in 2005, the German Parliament in 2009 will have to discuss three different bills concerning patients' advance decisions to refuse medical treatment. The illusion of "autonomous dying" is not a convincing model for the end of life debate.
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Stability and Hopf bifurcation for a business cycle model with expectation and delay
NASA Astrophysics Data System (ADS)
Liu, Xiangdong; Cai, Wenli; Lu, Jiajun; Wang, Yangyang
2015-08-01
According to rational expectation hypothesis, the government will take into account the future capital stock in the process of investment decision. By introducing anticipated capital stock into an economic model with investment delay, we construct a mixed functional differential system including delay and advanced variables. The system is converted to the one containing only delay by variable substitution. The equilibrium point of the system is obtained and its dynamical characteristics such as stability, Hopf bifurcation and its stability and direction are investigated by using the related theories of nonlinear dynamics. We carry out some numerical simulations to confirm these theoretical conclusions. The results indicate that both capital stock's anticipation and investment lag are the certain factors leading to the occurrence of cyclical fluctuations in the macroeconomic system. Moreover, the level of economic fluctuation can be dampened to some extent if investment decisions are made by the reasonable short-term forecast on capital stock.
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Flood risk assessment and robust management under deep uncertainty: Application to Dhaka City
NASA Astrophysics Data System (ADS)
Mojtahed, Vahid; Gain, Animesh Kumar; Giupponi, Carlo
2014-05-01
The socio-economic changes as well as climatic changes have been the main drivers of uncertainty in environmental risk assessment and in particular flood. The level of future uncertainty that researchers face when dealing with problems in a future perspective with focus on climate change is known as Deep Uncertainty (also known as Knightian uncertainty), since nobody has already experienced and undergone those changes before and our knowledge is limited to the extent that we have no notion of probabilities, and therefore consolidated risk management approaches have limited potential.. Deep uncertainty is referred to circumstances that analysts and experts do not know or parties to decision making cannot agree on: i) the appropriate models describing the interaction among system variables, ii) probability distributions to represent uncertainty about key parameters in the model 3) how to value the desirability of alternative outcomes. The need thus emerges to assist policy-makers by providing them with not a single and optimal solution to the problem at hand, such as crisp estimates for the costs of damages of natural hazards considered, but instead ranges of possible future costs, based on the outcomes of ensembles of assessment models and sets of plausible scenarios. Accordingly, we need to substitute optimality as a decision criterion with robustness. Under conditions of deep uncertainty, the decision-makers do not have statistical and mathematical bases to identify optimal solutions, while instead they should prefer to implement "robust" decisions that perform relatively well over all conceivable outcomes out of all future unknown scenarios. Under deep uncertainty, analysts cannot employ probability theory or other statistics that usually can be derived from observed historical data and therefore, we turn to non-statistical measures such as scenario analysis. We construct several plausible scenarios with each scenario being a full description of what may happen in future and based on a meaningful synthesis of parameters' values with control of their correlations for maintaining internal consistencies. This paper aims at incorporating a set of data mining and sampling tools to assess uncertainty of model outputs under future climatic and socio-economic changes for Dhaka city and providing a decision support system for robust flood management and mitigation policies. After constructing an uncertainty matrix to identify the main sources of uncertainty for Dhaka City, we identify several hazard and vulnerability maps based on future climatic and socio-economic scenarios. The vulnerability of each flood management alternative under different set of scenarios is determined and finally the robustness of each plausible solution considered is defined based on the above assessment.
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76 FR 65510 - Federal Acquisition Regulation; Submission for OMB Review; Buy American-Construction
Federal Register 2010, 2011, 2012, 2013, 2014
2011-10-21
...; Submission for OMB Review; Buy American--Construction AGENCIES: Department of Defense (DOD), General Services... requirement concerning the Buy American Act--Construction (Grimberg Decision). A notice was published in the...: Submit comments identified by Information Collection 9000- 0141, Buy American--Construction, by any of...
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Midoun, Miriam; Shangani, Sylvia; Mbete, Bibi; Babu, Shadrack; Hackman, Melissa; van der Elst, Elise; Sanders, Eduard J.; Smith, Adrian; Operario, Don
2016-01-01
Men who have sex with men are increasingly recognised as one of the most vulnerable HIV risk groups in Kenya. Se between men is highly stigmatised in Kenya, and efforts to provide sexual health services to men who have sex with men require a deeper understanding of their lived experiences; this includes how suchmen in Kenya construct their sexual identities, and how these constructions affect sexual decision-making. Adult self-identified men who have sex with men (n=26) in Malindi, Kenya participated in individual interviews to examine sociocultural processes influencing sexual identity construction and decision-making. Four key themes were identified: (i) tensions between perceptions of ‘homosexuality’ versus being ‘African’; (ii) gender-stereotyped beliefs about sexual positioning; (iii) socioeconomic status and limitations to personal agency; (iv) objectification and commodification of non-normative sexualities. Findings from this analysis emphasise the need to conceive of same-sex sexuality and HIV risk as context-dependent social phenomena. Multiple sociocultural axes were found to converge and shape sexual identity and sexual decision-making among this population. These axes and their interactive effects should be considered in the design of future interventions and other public health programmes for men who have sex with men in this region. PMID:26551761
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Midoun, Miriam; Shangani, Sylvia; Mbete, Bibi; Babu, Shadrack; Hackman, Melissa; van der Elst, Elise M; Sanders, Eduard J; Smith, Adrian D; Operario, Don
2016-01-01
Men who have sex with men are increasingly recognised as one of the most vulnerable HIV risk groups in Kenya. Sex between men is highly stigmatised in Kenya, and efforts to provide sexual health services to men who have sex with men require a deeper understanding of their lived experiences; this includes how such men in Kenya construct their sexual identities and how these constructions affect sexual decision-making. Adult self-identified men who have sex with men (n = 26) in Malindi, Kenya, participated in individual interviews to examine sociocultural processes influencing sexual identity construction and decision-making. Four key themes were identified: (1) tensions between perceptions of 'homosexuality' versus being 'African', (2) gender-stereotyped beliefs about sexual positioning, (3) socioeconomic status and limitations to personal agency and (4) objectification and commodification of non-normative sexualities. Findings from this analysis emphasise the need to conceive of same-sex sexuality and HIV risk as context-dependent social phenomena. Multiple sociocultural axes were found to converge and shape sexual identity and sexual decision-making among this population. These axes and their interactive effects should be considered in the design of future interventions and other public health programmes for men who have sex with men in this region.
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Yan, Wan-Sen; Zhang, Ran-Ran; Lan, Yan; Li, Zhi-Ming; Li, Yong-Hui
2018-01-01
Binge Eating Disorder (BED), considered a public health problem because of its impact on psychiatric, physical, and social functioning, merits much attention given its elevation to an independent diagnosis in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Similar with substance use disorders, some neuropsychological and personality constructs are potentially implicated in the onset and development of BED, in which poor decision-making has been suggested to facilitate overeating and BED. The objective of this study was to investigate the associations between decision-coping patterns, monetary decision-making, and binge-eating behavior in young adults. A sample of 1013 college students, equally divided into binge-eating and non-binge-eating groups according to the scores on the Binge Eating Scale (BES), were administered multiple measures of decision-making including the Melbourne Decision-Making Questionnaire (MDMQ), the Delay-discounting Test (DDT), and the Probability Discounting Test (PDT). Compared with the non-binge-eating group, the binge-eating group displayed elevated scores on maladaptive decision-making patterns including Procrastination, Buck-passing, and Hypervigilance. Logistic regression model revealed that only Procrastination positively predicted binge eating. These findings suggest that different dimensions of decision-making may be distinctly linked to binge eating among young adults, with Procrastination putatively identified as a risk trait in the development of overeating behavior, which might promote a better understanding of this disorder. PMID:29765343
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Decision Support Tool for Nighttime Construction and Air Quality - User’s Guide
DOT National Transportation Integrated Search
2017-11-01
The Texas Department of Transportation (TxDOT) Research Project 0-6864 Investigate the Air Quality Benefits of Nighttime Construction in Non-attainment Counties investigated the potential air quality benefits of shifting construction/maintenance acti...
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Killingsworth, Erin; Kimble, Laura P; Sudia, Tanya
2015-01-01
To explore the decision-making process of BSN faculty when determining which best practices to use for classroom testing. A descriptive, correlational study was conducted with a national sample (N = 127) of full-time BSN faculty. Participants completed a web-based survey incorporating instruments that measured beliefs about evaluation, decision-making, and best practices for item analysis and constructing and revising classroom tests. Study participants represented 31 states and were primarily middle-aged white women. In multiple linear regression analyses, faculty beliefs, contextual factors for decision-making, and decision-making processes accounted for statistically significant amounts of the variance in item analysis and test construction and revision. Strong faculty beliefs that rules were important when evaluating students was a significant predictor of increased use of best practices. Results support that understanding faculty beliefs around classroom testing is important in promoting the use of best practices.
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NASA Astrophysics Data System (ADS)
Chuan, Ngam Min; Thiruchelvam, Sivadass; Nasharuddin Mustapha, Kamal; Che Muda, Zakaria; Mat Husin, Norhayati; Yong, Lee Choon; Ghazali, Azrul; Ezanee Rusli, Mohd; Itam, Zarina Binti; Beddu, Salmia; Liyana Mohd Kamal, Nur
2016-03-01
This paper intends to fathom the current state of procurement system in Malaysia specifically in the construction industry in the aspect of supplier selection. This paper propose a comprehensive study on the supplier selection metrics for infrastructure building, weight the importance of each metrics assigned and to find the relationship between the metrics among initiators, decision makers, buyers and users. With the metrics hierarchy of criteria importance, a supplier selection process can be defined, repeated and audited with lesser complications or difficulties. This will help the field of procurement to improve as this research is able to develop and redefine policies and procedures that have been set in supplier selection. Developing this systematic process will enable optimization of supplier selection and thus increasing the value for every stakeholders as the process of selection is greatly simplified. With a new redefined policy and procedure, it does not only increase the company’s effectiveness and profit, but also make it available for the company to reach greater heights in the advancement of procurement in Malaysia.
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NASA Astrophysics Data System (ADS)
Del Vasto-Terrientes, L.; Kumar, V.; Chao, T.-C.; Valls, A.
2016-03-01
Global change refers to climate changes, but also demographic, technological and economic changes. Predicted water scarcity will be critical in the coastal Mediterranean region, especially for provision to mid-sized and large-sized cities. This paper studies the case of the city of Tarragona, located at the Mediterranean area of north-eastern Spain (Catalonia). Several scenarios have been constructed to evaluate different sectorial water allocation policies to mitigate the water scarcity induced by global change. Future water supply and demand predictions have been made for three time spans. The decision support system presented is based on the outranking model, which constructs a partial pre-order based on pairwise preference relations among all the possible actions. The system analyses a hierarchical structure of criteria, including environmental and economic criteria. We compare several adaptation measures including alternative water sources, inter-basin water transfer and sectorial demand management coming from industry, agriculture and domestic sectors. Results indicate that the most appropriate water allocation strategies depend on the severity of the global change effects.
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Liu, Kung-Ming; Lin, Sheng-Hau; Hsieh, Jing-Chzi; Tzeng, Gwo-Hshiung
2018-05-01
With the growth of population and the development of urbanization, waste management has always been a critical global issue. Recently, more and more countries have found that food waste constitutes the majority of municipal waste, if they are disposed of properly, will bring more benefits in sustainable development. Regarding the issue of selecting and improving the location to make the disposal facility towards achieving the aspiration level for sustainable development, since it involves multiple and complicated interaction factors about environment, society, and economy which have to be considered properly in the decision-making process of mutual influence relationship. It is basically a multiple attribute decision making (MADM) issue, a difficult problem which has been obsessing the governments of many countries is widely studied and discussed. This study uses the new hybrid modified MADM model, as follows, first to build an influential network relation map (INRM) via DEMATEL technique, next to confirm the influential weightings via DANP (DEMATEL-based ANP), and then to construct a decision-making model via a hybrid modified VIKOR method to improve and select the location for remaining the best disposal facilities. Finally, an empirical case study is illustrated to demonstrate that the proposed model can be effective and useful. In finding the process of decision making, environmental pollution is the main concern of many people in the area, but actually it is the resistance by the general public that has to be considered with first priority. Copyright © 2018. Published by Elsevier Ltd.
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Group decisions in biodiversity conservation: implications from game theory.
Frank, David M; Sarkar, Sahotra
2010-05-27
Decision analysis and game theory have proved useful tools in various biodiversity conservation planning and modeling contexts. This paper shows how game theory may be used to inform group decisions in biodiversity conservation scenarios by modeling conflicts between stakeholders to identify Pareto-inefficient Nash equilibria. These are cases in which each agent pursuing individual self-interest leads to a worse outcome for all, relative to other feasible outcomes. Three case studies from biodiversity conservation contexts showing this feature are modeled to demonstrate how game-theoretical representation can inform group decision-making. The mathematical theory of games is used to model three biodiversity conservation scenarios with Pareto-inefficient Nash equilibria: (i) a two-agent case involving wild dogs in South Africa; (ii) a three-agent raptor and grouse conservation scenario from the United Kingdom; and (iii) an n-agent fish and coral conservation scenario from the Philippines. In each case there is reason to believe that traditional mechanism-design solutions that appeal to material incentives may be inadequate, and the game-theoretical analysis recommends a resumption of further deliberation between agents and the initiation of trust--and confidence--building measures. Game theory can and should be used as a normative tool in biodiversity conservation contexts: identifying scenarios with Pareto-inefficient Nash equilibria enables constructive action in order to achieve (closer to) optimal conservation outcomes, whether by policy solutions based on mechanism design or otherwise. However, there is mounting evidence that formal mechanism-design solutions may backfire in certain cases. Such scenarios demand a return to group deliberation and the creation of reciprocal relationships of trust.
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Li, Qing; Qiao, Fengxiang; Yu, Lei; Shi, Junqing
2018-06-01
Vehicle interior noise functions at the dominant frequencies of 500 Hz below and around 800 Hz, which fall into the bands that may impair hearing. Recent studies demonstrated that freeway commuters are chronically exposed to vehicle interior noise, bearing the risk of hearing impairment. The interior noise evaluation process is mostly conducted in a laboratory environment. The test results and the developed noise models may underestimate or ignore the noise effects from dynamic traffic and road conditions and configuration. However, the interior noise is highly associated with vehicle maneuvering. The vehicle maneuvering on a freeway weaving segment is more complex because of its nature of conflicting areas. This research is intended to explore the risk of the interior noise exposure on freeway weaving segments for freeway commuters and to improve the interior noise estimation by constructing a decision tree learning-based noise exposure dose (NED) model, considering weaving segment designs and engine operation. On-road driving tests were conducted on 12 subjects on State Highway 288 in Houston, Texas. On-board Diagnosis (OBD) II, a smartphone-based roughness app, and a digital sound meter were used to collect vehicle maneuvering and engine information, International Roughness Index, and interior noise levels, respectively. Eleven variables were obtainable from the driving tests, including the length and type of a weaving segment, serving as predictors. The importance of the predictors was estimated by their out-of-bag-permuted predictor delta errors. The hazardous exposure level of the interior noise on weaving segments was quantified to hazard quotient, NED, and daily noise exposure level, respectively. Results showed that the risk of hearing impairment on freeway is acceptable; the interior noise level is the most sensitive to the pavement roughness and is subject to freeway configuration and traffic conditions. The constructed NED model shows high predictive power (R = 0.93, normalized root-mean-square error [NRMSE] < 6.7%). Vehicle interior noise is usually ignored in the public, and its modeling and evaluation are generally conducted in a laboratory environment, regardless of the interior noise effects from dynamic traffic, road conditions, and road configuration. This study quantified the interior exposure dose on freeway weaving segments, which provides freeway commuters with a sense of interior noise exposure risk. In addition, a bagged decision tree-based interior noise exposure dose model was constructed, considering vehicle maneuvering, vehicle engine operational information, pavement roughness, and weaving segment configuration. The constructed model could significantly improve the interior noise estimation for road engineers and vehicle manufactures.
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Validation of the AVM Blast Computational Modeling and Simulation Tool Set
2015-08-04
by-construction" methodology is powerful and would not be possible without high -level design languages to support validation and verification. [1,4...to enable the making of informed design decisions. Enable rapid exploration of the design trade-space for high -fidelity requirements tradeoffs...live-fire tests, the jump height of the target structure is recorded by using either high speed cameras or a string pot. A simple projectile motion
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Rehm, Markus; Prehn, Jochen H M
2013-06-01
Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters. Copyright © 2013 Elsevier Inc. All rights reserved.
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Mental maps and travel behaviour: meanings and models
NASA Astrophysics Data System (ADS)
Hannes, Els; Kusumastuti, Diana; Espinosa, Maikel León; Janssens, Davy; Vanhoof, Koen; Wets, Geert
2012-04-01
In this paper, the " mental map" concept is positioned with regard to individual travel behaviour to start with. Based on Ogden and Richards' triangle of meaning (The meaning of meaning: a study of the influence of language upon thought and of the science of symbolism. International library of psychology, philosophy and scientific method. Routledge and Kegan Paul, London, 1966) distinct thoughts, referents and symbols originating from different scientific disciplines are identified and explained in order to clear up the notion's fuzziness. Next, the use of this concept in two major areas of research relevant to travel demand modelling is indicated and discussed in detail: spatial cognition and decision-making. The relevance of these constructs to understand and model individual travel behaviour is explained and current research efforts to implement these concepts in travel demand models are addressed. Furthermore, these mental map notions are specified in two types of computational models, i.e. a Bayesian Inference Network (BIN) and a Fuzzy Cognitive Map (FCM). Both models are explained, and a numerical and a real-life example are provided. Both approaches yield a detailed quantitative representation of the mental map of decision-making problems in travel behaviour.
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Watershed models for decision support in the Yakima River basin, Washington
Mastin, M.C.; Vaccaro, J.J.
2002-01-01
A Decision Support System (DSS) is being developed by the U.S. Geological Survey and the Bureau of Reclamation as part of a long-term project, the Watershed and River Systems Management Program. The goal of the program is to apply the DSS to U.S. Bureau of Reclamation projects in the western United States. The DSS was applied to the Reclamation's Yakima Project in the Yakima River Basin in eastern Washington. An important component of the DSS is the physical hydrology modeling. For the application to the Yakima River Basin, the physical hydrology component consisted of constructing four watershed models using the U.S. Geological Survey's Precipitation-Runoff Modeling System within the Modular Modeling System. The implementation of these models is described. To facilitate calibration of the models, mean annual streamflow also was estimated for ungaged subbasins. The models were calibrated for water years 1950-94 and tested for water years 1995-98. The integration of the models in the DSS for real-time water-management operations using an interface termed the Object User Interface is also described. The models were incorporated in the DSS for use in long-term to short-term planning and have been used in a real-time operational mode since water year 1999.
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Child welfare organizations: Do specialization and service integration impact placement decisions?
Smith, Carrie; Fluke, John; Fallon, Barbara; Mishna, Faye; Decker Pierce, Barbara
2018-02-01
The objective of this study was to contribute to the understanding of the child welfare organization by testing the hypothesis that the characteristics of organizations influence decisions made by child protection staff for vulnerable children. The influence of two aspects of organizational structure on the decision to place a child in out-of-home care were examined: service integration and worker specialization. A theoretical framework that integrated the Decision-Making Ecology Framework (Baumann et al., 2011) and Yoo et al. (2007) conceptual framework of organizational constructs as predictors of service effectiveness was tested. Secondary data analysis of the Ontario Incidence Study of Reported Child Abuse and Neglect - 2013 (OIS-2013) was conducted. A subsample of 4949 investigations from 16 agencies was included in this study. Given the nested structure of the data, multi-level modelling was used to test the relative contribution of case and organizational factors to the decision to place. Despite the reported differences among child welfare organizations and research that has demonstrated variance in the placement decision as a result of organizational factors, the structure of the organization (i.e., worker specialization and service integration) showed no predictive power in the final models. The lack of variance may be explained by the relatively low frequency of placements during the investigation phase of service, the hierarchical impact of the factors of the DME and the limited information available regarding the structure of child welfare organizations in Ontario. Suggestions for future research are provided. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Gis-Based Site Selection for Underground Natural Resources Using Fuzzy Ahp-Owa
NASA Astrophysics Data System (ADS)
Sabzevari, A. R.; Delavar, M. R.
2017-09-01
Fuel consumption has significantly increased due to the growth of the population. A solution to address this problem is the underground storage of natural gas. The first step to reach this goal is to select suitable places for the storage. In this study, site selection for the underground natural gas reservoirs has been performed using a multi-criteria decision-making in a GIS environment. The "Ordered Weighted Average" (OWA) operator is one of the multi-criteria decision-making methods for ranking the criteria and consideration of uncertainty in the interaction among the criteria. In this paper, Fuzzy AHP_OWA (FAHP_OWA) is used to determine optimal sites for the underground natural gas reservoirs. Fuzzy AHP_OWA considers the decision maker's risk taking and risk aversion during the decision-making process. Gas consumption rate, temperature, distance from main transportation network, distance from gas production centers, population density and distance from gas distribution networks are the criteria used in this research. Results show that the northeast and west of Iran and the areas around Tehran (Tehran and Alborz Provinces) have a higher attraction for constructing a natural gas reservoir. The performance of the used method was also evaluated. This evaluation was performed using the location of the existing natural gas reservoirs in the country and the site selection maps for each of the quantifiers. It is verified that the method used in this study is capable of modeling different decision-making strategies used by the decision maker with about 88 percent of agreement between the modeling and test data.
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Nighttime construction: evaluation of construction operations : final report.
DOT National Transportation Integrated Search
2004-05-01
The different aspects that should be considered in making decisions on nighttime construction operations are identified and investigated in light of the current state of knowledge and practice. A state-of-the-art review was conducted of the current p...
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NASA Astrophysics Data System (ADS)
Neves de Campos, Thiago
This research examines the distortionary effects of a discovered and undeveloped sequential modular offshore project under five different designs for a production-sharing agreement (PSA). The model differs from previous research by looking at the effect of taxation from the perspective of a host government, where the objective is to maximize government utility over government revenue generated by the project and the non-pecuniary benefits to society. This research uses Modern Asset Pricing (MAP) theory, which is able to provide a good measure of the asset value accruing to various stakeholders in the project combined with the optimal decision rule for the development of the investment opportunity. Monte Carlo simulation was also applied to incorporate into the model the most important sources of risk associated with the project and to account for non-linearity in the cash flows. For a complete evaluation of how the fiscal system affects the project development, an investor's behavioral model was constructed, incorporating three operational decisions: investment timing, capacity size and early abandonment. The model considers four sources of uncertainty that affect the project value and the firm's optimal decision: the long run oil price and short-run deviations from that price, cost escalation and the reservoir recovery rate. The optimizations outcomes show that all fiscal systems evaluated produce distortion over the companies' optimal decisions, and companies adjust their choices to avoid taxation in different ways according to the fiscal system characteristics. Moreover, it is revealed that fiscal systems with tax provisions that try to capture additional project profits based on production profitability measures leads to stronger distortions in the project investment and output profile. It is also shown that a model based on a fixed percentage rate is the system that creates the least distortion. This is because companies will be subjected to the same government share of profit oil independently of any operational decision which they can make to change the production profile to evade taxation.
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Knowledge exchange for climate adaptation planning in western North America
NASA Astrophysics Data System (ADS)
Garfin, Gregg; Orr, Barron
2015-04-01
In western North America, the combination of sustained drought, rapid ecosystem changes, and land use changes associated with urban population growth has motivated concern among ecosystem managers about the implications of future climate changes for the landscapes which they manage. Through literature review, surveys, and workshop discussions, we assess the process of moving from concern, to planning, to action, with an emphasis on questions, such as: What are the roles of boundary organizations in facilitating knowledge exchange? Which practices lead to effective interactions between scientists, decision-makers, and knowledge brokers? While there is no "one size fits all" science communication method, the co-production of science and policy by research scientists, science translators, and decision-makers, as co-equals, is a resource intensive, but effective practice for moving adaptation planning forward. Constructive approaches make use of alliances with early adopters and opinion leaders, and make strong communication links between predictions, impacts and solutions. Resource managers need information on the basics of regional climate variability and global climate change, region-specific projections of climate changes and impacts, frank discussion of uncertainties, and opportunities for candid exploration of these topics with peers and subject experts. Research scientists play critical roles in adaptation planning discussions, because they assist resource managers in clarifying the cascade of interactions leading to potential impacts and, importantly, because decision-makers want to hear the information straight from the scientists conducting the research, which bolsters credibility. We find that uncertainty, formerly a topic to avoided, forms the foundation for constructive progress in adaptation planning. Candid exploration of the array of uncertainties, including those due to modeling, institutional, policy and economic factors, with practitioners, science translators, and subject experts, stimulates constructive thinking on adaptation strategies. Discussion support to explore multiple future scenarios and research nuances advances the discussion beyond "uncertainty paralysis."
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10 CFR 51.103 - Record of decision-general.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 10 Energy 2 2014-01-01 2014-01-01 false Record of decision-general. 51.103 Section 51.103 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) ENVIRONMENTAL PROTECTION REGULATIONS FOR DOMESTIC LICENSING AND... limited work authorization under 10 CFR 50.10 was issued, the Commission's decision on the construction...
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ERIC Educational Resources Information Center
Jonassen, David H.
2012-01-01
Decision making is the most common kind of problem solving. It is also an important component skill in other more ill-structured and complex kinds of problem solving, including policy problems and design problems. There are different kinds of decisions, including choices, acceptances, evaluations, and constructions. After describing the centrality…
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Zadeh, Rana; Sadatsafavi, Hessam; Xue, Ryan
2015-01-01
This study describes a vision and framework that can facilitate the implementation of evidence-based design (EBD), scientific knowledge base into the process of the design, construction, and operation of healthcare facilities and clarify the related safety and quality outcomes for the stakeholders. The proposed framework pairs EBD with value-driven decision making and aims to improve communication among stakeholders by providing a common analytical language. Recent EBD research indicates that the design and operation of healthcare facilities contribute to an organization's operational success by improving safety, quality, and efficiency. However, because little information is available about the financial returns of evidence-based investments, such investments are readily eliminated during the capital-investment decision-making process. To model the proposed framework, we used engineering economy tools to evaluate the return on investments in six successful cases, identified by a literature review, in which facility design and operation interventions resulted in reductions in hospital-acquired infections, patient falls, staff injuries, and patient anxiety. In the evidence-based cases, calculated net present values, internal rates of return, and payback periods indicated that the long-term benefits of interventions substantially outweighed the intervention costs. This article explained a framework to develop a research-based and value-based communication language on specific interventions along the planning, design and construction, operation, and evaluation stages. Evidence-based and value-based design frameworks can be applied to communicate the life-cycle costs and savings of EBD interventions to stakeholders, thereby contributing to more informed decision makings and the optimization of healthcare infrastructures. © The Author(s) 2015.
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Surrogate-based Analysis and Optimization
NASA Technical Reports Server (NTRS)
Queipo, Nestor V.; Haftka, Raphael T.; Shyy, Wei; Goel, Tushar; Vaidyanathan, Raj; Tucker, P. Kevin
2005-01-01
A major challenge to the successful full-scale development of modem aerospace systems is to address competing objectives such as improved performance, reduced costs, and enhanced safety. Accurate, high-fidelity models are typically time consuming and computationally expensive. Furthermore, informed decisions should be made with an understanding of the impact (global sensitivity) of the design variables on the different objectives. In this context, the so-called surrogate-based approach for analysis and optimization can play a very valuable role. The surrogates are constructed using data drawn from high-fidelity models, and provide fast approximations of the objectives and constraints at new design points, thereby making sensitivity and optimization studies feasible. This paper provides a comprehensive discussion of the fundamental issues that arise in surrogate-based analysis and optimization (SBAO), highlighting concepts, methods, techniques, as well as practical implications. The issues addressed include the selection of the loss function and regularization criteria for constructing the surrogates, design of experiments, surrogate selection and construction, sensitivity analysis, convergence, and optimization. The multi-objective optimal design of a liquid rocket injector is presented to highlight the state of the art and to help guide future efforts.
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From the experience of development of composite materials with desired properties
NASA Astrophysics Data System (ADS)
Garkina, I. A.; Danilov, A. M.
2017-04-01
Using the experience in the development of composite materials with desired properties is given the algorithm of construction materials synthesis on the basis of their representation in the form of a complex system. The possibility of creation of a composite and implementation of the technical task originally are defined at a stage of cognitive modeling. On the basis of development of the cognitive map hierarchical structures of criteria of quality are defined; according to them for each allocated large-scale level the corresponding block diagrams of system are specified. On the basis of the solution of problems of one-criteria optimization with use of the found optimum values formalization of a multi-criteria task and its decision is carried out (the optimum organization and properties of system are defined). The emphasis is on methodological aspects of mathematical modeling (construction of a generalized and partial models to optimize the properties and structure of materials, including those based on the concept of systemic homeostasis).
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Automated rule-base creation via CLIPS-Induce
NASA Technical Reports Server (NTRS)
Murphy, Patrick M.
1994-01-01
Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.
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Strategic advantages of high-rise construction
NASA Astrophysics Data System (ADS)
Yaskova, Natalya
2018-03-01
Traditional methods to assess the competitiveness of different types of real estate in the context of huge changes of new technological way of life don't provide building solutions that would be correct from a strategic perspective. There are many challenges due to changes in the consumers' behavior in the housing area. A multiplicity of life models, a variety of opportunities and priorities, traditions and new trends in construction should be assessed in terms of prospective benefits in the environment of the emerging new world order. At the same time, the mane discourse of high-rise construction mainly relates to its design features, technical innovations, and architectural accents. We need to clarify the criteria for economic evaluation of high-rise construction in order to provide decisions with clear and quantifiable contexts. The suggested approach to assessing the strategic advantage of high-rise construction and the prospects for capitalization of high-rise buildings poses new challenges for the economy to identify adequate quantitative assessment methods of the high-rise buildings economic efficiency, taking into account all stages of their life cycle.
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Lunar-base construction equipment and methods evaluation
NASA Technical Reports Server (NTRS)
Boles, Walter W.; Ashley, David B.; Tucker, Richard L.
1993-01-01
A process for evaluating lunar-base construction equipment and methods concepts is presented. The process is driven by the need for more quantitative, systematic, and logical methods for assessing further research and development requirements in an area where uncertainties are high, dependence upon terrestrial heuristics is questionable, and quantitative methods are seldom applied. Decision theory concepts are used in determining the value of accurate information and the process is structured as a construction-equipment-and-methods selection methodology. Total construction-related, earth-launch mass is the measure of merit chosen for mathematical modeling purposes. The work is based upon the scope of the lunar base as described in the National Aeronautics and Space Administration's Office of Exploration's 'Exploration Studies Technical Report, FY 1989 Status'. Nine sets of conceptually designed construction equipment are selected as alternative concepts. It is concluded that the evaluation process is well suited for assisting in the establishment of research agendas in an approach that is first broad, with a low level of detail, followed by more-detailed investigations into areas that are identified as critical due to high degrees of uncertainty and sensitivity.
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Dowding, Dawn; Lichtner, Valentina; Allcock, Nick; Briggs, Michelle; James, Kirstin; Keady, John; Lasrado, Reena; Sampson, Elizabeth L; Swarbrick, Caroline; José Closs, S
2016-01-01
The recognition, assessment and management of pain in hospital settings is suboptimal, and is a particular challenge in patients with dementia. The existing process guiding pain assessment and management in clinical settings is based on the assumption that nurses follow a sequential linear approach to decision making. In this paper we re-evaluate this theoretical assumption drawing on findings from a study of pain recognition, assessment and management in patients with dementia. To provide a revised conceptual model of pain recognition, assessment and management based on sense-making theories of decision making. The research we refer to is an exploratory ethnographic study using nested case sites. Patients with dementia (n=31) were the unit of data collection, nested in 11 wards (vascular, continuing care, stroke rehabilitation, orthopaedic, acute medicine, care of the elderly, elective and emergency surgery), located in four NHS hospital organizations in the UK. Data consisted of observations of patients at bedside (170h in total); observations of the context of care; audits of patient hospital records; documentary analysis of artefacts; semi-structured interviews (n=56) and informal open conversations with staff and carers (family members). Existing conceptualizations of pain recognition, assessment and management do not fully explain how the decision process occurs in clinical practice. Our research indicates that pain recognition, assessment and management is not an individual cognitive activity; rather it is carried out by groups of individuals over time and within a specific organizational culture or climate, which influences both health care professional and patient behaviour. We propose a revised theoretical model of decision making related to pain assessment and management for patients with dementia based on theories of sense-making, which is reflective of the reality of clinical decision making in acute hospital wards. The revised model recognizes the salience of individual cognition as well as acknowledging that decisions are constructed through social interaction and organizational context. The model will be used in further research to develop decision support interventions to assist with the assessment and management of patients with dementia in acute hospital settings. Copyright © 2015. Published by Elsevier Ltd.
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National-Scale Hydrologic Classification & Agricultural Decision Support: A Multi-Scale Approach
NASA Astrophysics Data System (ADS)
Coopersmith, E. J.; Minsker, B.; Sivapalan, M.
2012-12-01
Classification frameworks can help organize catchments exhibiting similarity in hydrologic and climatic terms. Focusing this assessment of "similarity" upon specific hydrologic signatures, in this case the annual regime curve, can facilitate the prediction of hydrologic responses. Agricultural decision-support over a diverse set of catchments throughout the United States depends upon successful modeling of the wetting/drying process without necessitating separate model calibration at every site where such insights are required. To this end, a holistic classification framework is developed to describe both climatic variability (humid vs. arid, winter rainfall vs. summer rainfall) and the draining, storing, and filtering behavior of any catchment, including ungauged or minimally gauged basins. At the national scale, over 400 catchments from the MOPEX database are analyzed to construct the classification system, with over 77% of these catchments ultimately falling into only six clusters. At individual locations, soil moisture models, receiving only rainfall as input, produce correlation values in excess of 0.9 with respect to observed soil moisture measurements. By deploying physical models for predicting soil moisture exclusively from precipitation that are calibrated at gauged locations, overlaying machine learning techniques to improve these estimates, then generalizing the calibration parameters for catchments in a given class, agronomic decision-support becomes available where it is needed rather than only where sensing data are located.lassifications of 428 U.S. catchments on the basis of hydrologic regime data, Coopersmith et al, 2012.
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An ethical framework for pharmacy management: balancing autonomy and other principles.
Glassman, Peter A; Schneider, Paul L; Good, Chester B
2014-04-01
Decisions to control pharmaceutical costs can cause conflicts as to what medications are covered. Such conflicts have ethical implications, however implicit, and given this fact, an ethical framework can help address them. In the following commentary, we discuss the more traditional, individual-level ethical considerations likely familiar to most clinicians. We, then, discuss population-level ethical constructs that clinicians may not as readily embrace. We also present a hypothetical cancer-care case to illustrate how imbalances in ethical foci between individual- and population-level constructs may lead to conflicts among health care actors and promote shifts in pharmaceutical decision making away from providers and toward payers, paradoxically reducing provider autonomy and hence patient autonomy. Finally, we propose a more comprehensive ethical framework to help converge individual, payer, and societal interests when making pharmaceutical use decisions. Pharmacists play a crucial role as pharmacy benefits managers and should be familiar with individual- and population-based ethical constructs.
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Construct Maps: A Tool to Organize Validity Evidence
ERIC Educational Resources Information Center
McClarty, Katie Larsen
2013-01-01
The construct map is a promising tool for organizing the data standard-setting panelists interpret. The challenge in applying construct maps to standard-setting procedures will be the judicious selection of data to include within this organizing framework. Therefore, this commentary focuses on decisions about what to include in the construct map.…
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Assessing hydrometeorological impacts with terrestrial and aerial Lidar data in Monterrey, México
NASA Astrophysics Data System (ADS)
Yepez Rincon, F.; Lozano Garcia, D.; Vela Coiffier, P.; Rivera Rivera, L.
2013-10-01
Light Detection Ranging (Lidar) is an efficient tool to gather points reflected from a terrain and store them in a xyz coordinate system, allowing the generation of 3D data sets to manage geoinformation. Translation of these coordinates, from an arbitrary system into a geographical base, makes data feasible and useful to calculate volumes and define topographic characteristics at different scales. Lidar technological advancement in topographic mapping enables the generation of highly accurate and densely sampled elevation models, which are in high demand by many industries like construction, mining and forestry. This study merges terrestrial and aerial Lidar data to evaluate the effectiveness of these tools assessing volumetric changes after a hurricane event of riverbeds and scour bridges The resulted information could be an optimal approach to improve hydrological and hydraulic models, to aid authorities in proper to decision making in construction, urban planning, and homeland security.
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Analysis and Comparison on the Flood Simulation in Typical Hilly & Semi-mountainous Region
NASA Astrophysics Data System (ADS)
Luan, Qinghua; Wang, Dong; Zhang, Xiang; Liu, Jiahong; Fu, Xiaoran; Zhang, Kun; Ma, Jun
2017-12-01
Water-logging and flood are both serious in hilly and semi-mountainous cities of China, but the related research is rare. Lincheng Economic Development Zone (EDZ) in Hebei Province as the typical city was selected and storm water management model (SWMM) was applied for flood simulation in this study. The regional model was constructed through calibrating and verifying the runoff coefficient of different flood processes. Different designed runoff processes in five-year, ten-year and twenty-year return periods in basic scenario and in the low impact development (LID) scenario, respectively, were simulated and compared. The result shows that: LID measures have effect on peak reduction in the study area, but the effectiveness is not significant; the effectiveness of lagging peak time is poor. These simulation results provide decision support for the rational construction of LID in the study area, and provide the references for regional rain flood management.
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NASA Astrophysics Data System (ADS)
Alkasem, Ameen; Liu, Hongwei; Zuo, Decheng; Algarash, Basheer
2018-01-01
The volume of data being collected, analyzed, and stored has exploded in recent years, in particular in relation to the activity on the cloud computing. While large-scale data processing, analysis, storage, and platform model such as cloud computing were previously and currently are increasingly. Today, the major challenge is it address how to monitor and control these massive amounts of data and perform analysis in real-time at scale. The traditional methods and model systems are unable to cope with these quantities of data in real-time. Here we present a new methodology for constructing a model for optimizing the performance of real-time monitoring of big datasets, which includes a machine learning algorithms and Apache Spark Streaming to accomplish fine-grained fault diagnosis and repair of big dataset. As a case study, we use the failure of Virtual Machines (VMs) to start-up. The methodology proposition ensures that the most sensible action is carried out during the procedure of fine-grained monitoring and generates the highest efficacy and cost-saving fault repair through three construction control steps: (I) data collection; (II) analysis engine and (III) decision engine. We found that running this novel methodology can save a considerate amount of time compared to the Hadoop model, without sacrificing the classification accuracy or optimization of performance. The accuracy of the proposed method (92.13%) is an improvement on traditional approaches.
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Gannon, Jill J.; Moore, Clinton T.; Shaffer, Terry L.; Flanders-Wanner, Bridgette
2011-01-01
Much of the native prairie managed by the U.S. Fish and Wildlife Service (Service) in the Prairie Pothole Region (PPR) is extensively invaded by the introduced cool-season grasses smooth brome (Bromus inermis) and Kentucky bluegrass (Poa pratensis). The central challenge to managers is selecting appropriate management actions in the face of biological and environmental uncertainties. We describe the technical components of a USGS management project, and explain how the components integrate and inform each other, how data feedback from individual cooperators serves to reduce uncertainty across the whole region, and how a successful adaptive management project is coordinated and maintained on a large scale. In partnership with the Service, the U.S. Geological Survey is developing an adaptive decision support framework to assist managers in selecting management actions under uncertainty and maximizing learning from management outcomes. The framework is built around practical constraints faced by refuge managers and includes identification of the management objective and strategies, analysis of uncertainty and construction of competing decision models, monitoring, and mechanisms for model feedback and decision selection. Nineteen Service field stations, spanning four states of the PPR, are participating in the project. They share a common management objective, available management strategies, and biological uncertainties. While the scope is broad, the project interfaces with individual land managers who provide refuge-specific information and receive updated decision guidance that incorporates understanding gained from the collective experience of all cooperators.
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Federal Register 2010, 2011, 2012, 2013, 2014
2012-03-28
...] Final Environmental Impact Statement and Record of Decision for Alabama Beach Mouse General Conservation... mouse (Peromyscus polionotus ammobates). For record of decision (ROD) availability, see DATES. DATES... beach mouse incidental to construction of up to 500 single-family developments potentially affecting an...
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Wang, Yanqing; Chong, Heap-Yih; Liao, Pin-Chao; Ren, Hantao
2017-09-25
Unsafe behavior is a leading factor in accidents, and the working environment significantly affects behaviors. However, few studies have focused on detailed mechanisms for addressing unsafe behaviors resulting from environmental constraints. This study aims to delineate these mechanisms using cognitive work analysis (CWA) for an elevator installation case study. Elevator installation was selected for study because it involves operations at heights: falls from heights remain a major cause of construction worker mortality. This study adopts a mixed research approach based on three research methodology stages. This research deconstructs the details of the working environment, the workers' decision-making processes, the strategies chosen given environmental conditions and the conceptual model for workers' behaviors, which jointly depict environment-behavior mechanisms at length. By applying CWA to the construction industry, environmental constraints can easily be identified, and targeted engineering suggestions can be generated.