Do individual differences in Iowa Gambling Task performance predict adaptive decision making for risky gains and losses?

PubMed

Weller, Joshua A; Levin, Irwin P; Bechara, Antoine

2010-02-01

We relate performance on the Iowa Gambling Task (IGT), a widely used, but complex, neuropsychological task of executive function in which mixed outcomes (gains and losses) are experienced together, to performance on a relatively simpler descriptive task, the Cups task, which isolates adaptive decision making for achieving gains and avoiding losses. We found that poor IGT performance was associated with suboptimal decision making on Cups, especially for risky losses, suggesting that losses are weighted more than gains in the IGT. These findings were significant beyond several notable gender differences in which men outperformed women. Implications for the neuropsychological study of risk are discussed.

WeightLifter: Visual Weight Space Exploration for Multi-Criteria Decision Making.

PubMed

Pajer, Stephan; Streit, Marc; Torsney-Weir, Thomas; Spechtenhauser, Florian; Muller, Torsten; Piringer, Harald

2017-01-01

A common strategy in Multi-Criteria Decision Making (MCDM) is to rank alternative solutions by weighted summary scores. Weights, however, are often abstract to the decision maker and can only be set by vague intuition. While previous work supports a point-wise exploration of weight spaces, we argue that MCDM can benefit from a regional and global visual analysis of weight spaces. Our main contribution is WeightLifter, a novel interactive visualization technique for weight-based MCDM that facilitates the exploration of weight spaces with up to ten criteria. Our technique enables users to better understand the sensitivity of a decision to changes of weights, to efficiently localize weight regions where a given solution ranks high, and to filter out solutions which do not rank high enough for any plausible combination of weights. We provide a comprehensive requirement analysis for weight-based MCDM and describe an interactive workflow that meets these requirements. For evaluation, we describe a usage scenario of WeightLifter in automotive engineering and report qualitative feedback from users of a deployed version as well as preliminary feedback from decision makers in multiple domains. This feedback confirms that WeightLifter increases both the efficiency of weight-based MCDM and the awareness of uncertainty in the ultimate decisions.

Mathematical model to select the optimal alternative for an integral plan to desertification and erosion control for the Chaco Area in Salta Province (Argentine)

NASA Astrophysics Data System (ADS)

Grau, J. B.; Anton, J. M.; Tarquis, A. M.; Colombo, F.; de Los Rios, L.; Cisneros, J. M.

2010-04-01

Multi-criteria Decision Analysis (MCDA) is concerned with identifying the values, uncertainties and other issues relevant in a given decision, its rationality, and the resulting optimal decision. These decisions are difficult because the complexity of the system or because of determining the optimal situation or behavior. This work will illustrate how MCDA is applied in practice to a complex problem to resolve such us soil erosion and degradation. Desertification is a global problem and recently it has been studied in several forums as ONU that literally says: "Desertification has a very high incidence in the environmental and food security, socioeconomic stability and world sustained development". Desertification is the soil quality loss and one of FAO's most important preoccupations as hunger in the world is increasing. Multiple factors are involved of diverse nature related to: natural phenomena (water and wind erosion), human activities linked to soil and water management, and others not related to the former. In the whole world this problem exists, but its effects and solutions are different. It is necessary to take into account economical, environmental, cultural and sociological criteria. A multi-criteria model to select among different alternatives to prepare an integral plan to ameliorate or/and solve this problem in each area has been elaborated taking in account eight criteria and six alternatives. Six sub zones have been established following previous studies and in each one the initial matrix and weights have been defined to apply on different criteria. Three Multicriteria Decision Methods have been used for the different sub zones: ELECTRE, PROMETHEE and AHP. The results show a high level of consistency among the three different multicriteria methods despite the complexity of the system studied. The methods are described for La Estrella sub zone, indicating election of weights, Initial Matrixes, the MATHCAD8 algorithms used for PROMETHEE, and the Graph of Expert Choice showing the results of AHP. A brief schema of the actions recommended for each of the six different sub zones is reported in Conclusions, with "We can combine Autochthonous and High Value Forest" for La Estrella.

An application of mathematical models to select the optimal alternative for an integral plan to desertification and erosion control (Chaco Area - Salta Province - Argentina)

NASA Astrophysics Data System (ADS)

Grau, J. B.; Antón, J. M.; Tarquis, A. M.; Colombo, F.; de Los Ríos, L.; Cisneros, J. M.

2010-11-01

Multi-criteria Decision Analysis (MCDA) is concerned with identifying the values, uncertainties and other issues relevant in a given decision, its rationality, and the resulting optimal decision. These decisions are difficult because the complexity of the system or because of determining the optimal situation or behaviour. This work will illustrate how MCDA is applied in practice to a complex problem to resolve such us soil erosion and degradation. Desertification is a global problem and recently it has been studied in several forums as ONU that literally says: "Desertification has a very high incidence in the environmental and food security, socioeconomic stability and world sustained development". Desertification is the soil quality loss and one of FAO's most important preoccupations as hunger in the world is increasing. Multiple factors are involved of diverse nature related to: natural phenomena (water and wind erosion), human activities linked to soil and water management, and others not related to the former. In the whole world this problem exists, but its effects and solutions are different. It is necessary to take into account economical, environmental, cultural and sociological criteria. A multi-criteria model to select among different alternatives to prepare an integral plan to ameliorate or/and solve this problem in each area has been elaborated taking in account eight criteria and five alternatives. Six sub zones have been established following previous studies and in each one the initial matrix and weights have been defined to apply on different criteria. Three multicriteria decision methods have been used for the different sub zones: ELECTRE, PROMETHEE and AHP. The results show a high level of consistency among the three different multicriteria methods despite the complexity of the system studied. The methods are fully described for La Estrella sub zone, indicating election of weights, Initial Matrixes, algorithms used for PROMETHEE, and the Graph of Expert Choice showing the AHP results. A brief schema of the actions recommended for each of the six different sub zones is discussed.

Obesity: which drug and when?

PubMed

Lean, M; Mullan, A

2007-09-01

Obesity, with all its consequences, is audaciously confronting medical professionals and health service providers worldwide. Diet and exercise intervention is an essential part of any weight management strategy, but may not succeed in isolation. Effective approaches for routine practice are more likely to involve affordable, efficacious and well-tolerated drug therapy than the more expensive, case selective approach of bariatric surgery. Advancement of pharmacotherapy is expanding the battery of available drugs; the clinician is faced with an increasingly complex therapeutic decision. Which drug to use, and when, is influenced by a range of factors, discussed here. There is a large body of high quality evidence in the literature to support the presently available drugs; however, many questions remain unanswered including duration of therapy and whether longer-term goals of improved morbidity and mortality are achievable. Clinician and patient awareness of these issues will provide a more informed therapeutic decision and ultimately improve the potential for reaching the weight management targets.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; An Iterative Decoding Algorithm for Linear Block Codes Based on a Low-Weight Trellis Search

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

For long linear block codes, maximum likelihood decoding based on full code trellises would be very hard to implement if not impossible. In this case, we may wish to trade error performance for the reduction in decoding complexity. Sub-optimum soft-decision decoding of a linear block code based on a low-weight sub-trellis can be devised to provide an effective trade-off between error performance and decoding complexity. This chapter presents such a suboptimal decoding algorithm for linear block codes. This decoding algorithm is iterative in nature and based on an optimality test. It has the following important features: (1) a simple method to generate a sequence of candidate code-words, one at a time, for test; (2) a sufficient condition for testing a candidate code-word for optimality; and (3) a low-weight sub-trellis search for finding the most likely (ML) code-word.

Evaluating supplier quality performance using analytical hierarchy process

NASA Astrophysics Data System (ADS)

Kalimuthu Rajoo, Shanmugam Sundram; Kasim, Maznah Mat; Ahmad, Nazihah

2013-09-01

This paper elaborates the importance of evaluating supplier quality performance to an organization. Supplier quality performance evaluation reflects the actual performance of the supplier exhibited at customer's end. It is critical in enabling the organization to determine the area of improvement and thereafter works with supplier to close the gaps. Success of the customer partly depends on supplier's quality performance. Key criteria as quality, cost, delivery, technology support and customer service are categorized as main factors in contributing to supplier's quality performance. 18 suppliers' who were manufacturing automotive application parts evaluated in year 2010 using weight point system. There were few suppliers with common rating which led to common ranking observed by few suppliers'. Analytical Hierarchy Process (AHP), a user friendly decision making tool for complex and multi criteria problems was used to evaluate the supplier's quality performance challenging the weight point system that was used for 18 suppliers'. The consistency ratio was checked for criteria and sub-criteria. Final results of AHP obtained with no overlap ratings, therefore yielded a better decision making methodology as compared to weight point rating system.

Choosing Psychiatry as a Career: Motivators and Deterrents at a Critical Decision-Making Juncture

PubMed Central

Wiesenfeld, Lesley; Abbey, Susan; Takahashi, Sue Glover; Abrahams, Caroline

2014-01-01

Objective To examine factors influencing the choice of psychiatry as a career between residency program application and ranking decision making. Methods: Using an online questionnaire, applicants to the largest Canadian psychiatry residency program were surveyed about the impact of various factors on their ultimate decision to enter psychiatry residency training. Results: Applicants reported that patient-related stigma was a motivator in considering psychiatry as a career, but that negative comments from colleagues, friends, and family about choosing psychiatry was a deterrent. Training program length, limited treatments, and insufficient clerkship exposure were noted as deterrents to choosing psychiatry, though future job prospects, the growing role of neuroscience, and diagnostic complexity positively influenced choosing psychiatry as a specialty. Research and elective time away opportunities were deemed relatively unimportant to ranking decisions, compared with more highly weighted factors, such as program flexibility, emphasis on psychotherapy, service– training balance, and training program location. Most applicants also reported continuing to fine tune ranking decisions between the application and ranking submission deadline. Conclusions: Stigma, exposure to psychiatry, diagnostic complexity, and an encouraging job market were highlighted as positive influences on the choice to enter psychiatry residency. Interview and information days represent opportunities for continued targeted recruitment activity for psychiatry residency programs. PMID:25161070

A simple way to unify multicriteria decision analysis (MCDA) and stochastic multicriteria acceptability analysis (SMAA) using a Dirichlet distribution in benefit-risk assessment.

PubMed

Saint-Hilary, Gaelle; Cadour, Stephanie; Robert, Veronique; Gasparini, Mauro

2017-05-01

Quantitative methodologies have been proposed to support decision making in drug development and monitoring. In particular, multicriteria decision analysis (MCDA) and stochastic multicriteria acceptability analysis (SMAA) are useful tools to assess the benefit-risk ratio of medicines according to the performances of the treatments on several criteria, accounting for the preferences of the decision makers regarding the relative importance of these criteria. However, even in its probabilistic form, MCDA requires the exact elicitations of the weights of the criteria by the decision makers, which may be difficult to achieve in practice. SMAA allows for more flexibility and can be used with unknown or partially known preferences, but it is less popular due to its increased complexity and the high degree of uncertainty in its results. In this paper, we propose a simple model as a generalization of MCDA and SMAA, by applying a Dirichlet distribution to the weights of the criteria and by making its parameters vary. This unique model permits to fit both MCDA and SMAA, and allows for a more extended exploration of the benefit-risk assessment of treatments. The precision of its results depends on the precision parameter of the Dirichlet distribution, which could be naturally interpreted as the strength of confidence of the decision makers in their elicitation of preferences. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Breast cancer and pregnancy: decision making and the point of view of the mother].

PubMed

Eisinger, François; Noizet, Agnès

2002-09-01

For the treatment of breast cancer, modifications of decision making related to pregnancy could be assessed through three questions. Why a decision had been chosen? In that case, the hypothesis is that decisions are based on the expected utility. The theory assumes weighting and computation of complete possibilities with their associated probabilities and values. However values exhibits a wide inter-individual variation range. Therefore the predictability of choice based on this model is indeed very low. Furthermore it is likely that the willingness of pregnancy after breast cancer contains besides classic constituents of appeals of motherhood, a specific meaning of recovery both of health and femininity. The second question: who is in charge of the decision? And under the paradigm of autonomy, women' decision is, merely by itself, the right decision. The last question is how? For some situations for which foreseeing is quiet complex, the value of the process in itself is increased and could help the end-oriented or self-determined decision. Casuistic analysis could therefore improve women' decisions. The issue is not only about decision but also related to patient-physician relationship, about an issue that is not only a biomedical problem.

The use of logistic regression to enhance risk assessment and decision making by mental health administrators.

PubMed

Menditto, Anthony A; Linhorst, Donald M; Coleman, James C; Beck, Niels C

2006-04-01

Development of policies and procedures to contend with the risks presented by elopement, aggression, and suicidal behaviors are long-standing challenges for mental health administrators. Guidance in making such judgments can be obtained through the use of a multivariate statistical technique known as logistic regression. This procedure can be used to develop a predictive equation that is mathematically formulated to use the best combination of predictors, rather than considering just one factor at a time. This paper presents an overview of logistic regression and its utility in mental health administrative decision making. A case example of its application is presented using data on elopements from Missouri's long-term state psychiatric hospitals. Ultimately, the use of statistical prediction analyses tempered with differential qualitative weighting of classification errors can augment decision-making processes in a manner that provides guidance and flexibility while wrestling with the complex problem of risk assessment and decision making.

Using an innovative criteria weighting tool for stakeholders involvement to rank MSW facility sites with the AHP.

PubMed

De Feo, Giovanni; De Gisi, Sabino

2010-11-01

The main aim of this study was to verify the efficacy of using an innovative criteria weighting tool (the "priority scale") for stakeholders involvement to rank a list of suitable municipal solid waste (MSW) facility sites with the multi-criteria decision-making (MCDM) technique known as analytic hierarchy process (AHP). One of the main objectives of the study was to verify the behaviour of the "priority scale" with both technical and non-technical decision-makers. All over the world, the siting of MSW treatment or disposal plants is a complex process involving politicians, technicians as well as citizens, where stakeholders who are not effectively involved strongly oppose (or even obstruct) the realization of new facilities. In this study, in order to pursue both the technical (select the best site) and social aims (all the stakeholders have to give their aware contribution), the use of the "priority scale" is suggested as a tool to easily collect non-contradictory criteria preferences by the various decision-makers. Every decision-maker filled in "priority scale", which was subsequently uploaded in the AHP tool in order to indirectly calculate the individual priority of alternatives given by each stakeholder (not using group aggregation techniques). The proposed method was applied to the siting of a composting plant in an area suffering from a serious MSW emergency, which has lasted for over 15 years, in the Campania Region, in Southern Italy. The best site (the "first choice") was taken as the one that appeared the most times at the first place of each decision-maker ranking list. The involved technical and non-technical decision-makers showed the same behaviour in (indirectly) selecting the best site as well as in terms of the most appraised criteria ("absence of areas of the highest value for natural habitats and species of plants and animals"). Moreover, they showed the same AHP inconsistency ratio as well as the same behaviour in comparison with a "balanced decision-maker" (who assigns identical weights to all the considered criteria). Therefore, the proposed criteria weighting tool could be widely as well as easily used for stakeholders involvement to rank MSW facility sites (or other kinds of alternatives) with the AHP or with other MCDM techniques, taking or not into consideration group aggregation methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Evaluating a multispecies adaptive management framework: Must uncertainty impede effective decision-making?

USGS Publications Warehouse

Smith, David R.; McGowan, Conor P.; Daily, Jonathan P.; Nichols, James D.; Sweka, John A.; Lyons, James E.

2013-01-01

Application of adaptive management to complex natural resource systems requires careful evaluation to ensure that the process leads to improved decision-making. As part of that evaluation, adaptive policies can be compared with alternative nonadaptive management scenarios. Also, the value of reducing structural (ecological) uncertainty to achieving management objectives can be quantified.A multispecies adaptive management framework was recently adopted by the Atlantic States Marine Fisheries Commission for sustainable harvest of Delaware Bay horseshoe crabs Limulus polyphemus, while maintaining adequate stopover habitat for migrating red knots Calidris canutus rufa, the focal shorebird species. The predictive model set encompassed the structural uncertainty in the relationships between horseshoe crab spawning, red knot weight gain and red knot vital rates. Stochastic dynamic programming was used to generate a state-dependent strategy for harvest decisions given that uncertainty. In this paper, we employed a management strategy evaluation approach to evaluate the performance of this adaptive management framework. Active adaptive management was used by including model weights as state variables in the optimization and reducing structural uncertainty by model weight updating.We found that the value of information for reducing structural uncertainty is expected to be low, because the uncertainty does not appear to impede effective management. Harvest policy responded to abundance levels of both species regardless of uncertainty in the specific relationship that generated those abundances. Thus, the expected horseshoe crab harvest and red knot abundance were similar when the population generating model was uncertain or known, and harvest policy was robust to structural uncertainty as specified.Synthesis and applications. The combination of management strategy evaluation with state-dependent strategies from stochastic dynamic programming was an informative approach to evaluate adaptive management performance and value of learning. Although natural resource decisions are characterized by uncertainty, not all uncertainty will cause decisions to be altered substantially, as we found in this case. It is important to incorporate uncertainty into the decision framing and evaluate the effect of reducing that uncertainty on achieving the desired outcomes

Dynamic Divisive Normalization Predicts Time-Varying Value Coding in Decision-Related Circuits

PubMed Central

LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W.

2014-01-01

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. PMID:25429145

Decision support system of e-book provider selection for library using Simple Additive Weighting

NASA Astrophysics Data System (ADS)

Ciptayani, P. I.; Dewi, K. C.

2018-01-01

Each library has its own criteria and differences in the importance of each criterion in choosing an e-book provider for them. The large number of providers and the different importance levels of each criterion make the problem of determining the e-book provider to be complex and take a considerable time in decision making. The aim of this study was to implement Decision support system (DSS) to assist the library in selecting the best e-book provider based on their preferences. The way of DSS works is by comparing the importance of each criterion and the condition of each alternative decision. SAW is one of DSS method that is quite simple, fast and widely used. This study used 9 criteria and 18 provider to demonstrate how SAW work in this study. With the DSS, then the decision-making time can be shortened and the calculation results can be more accurate than manual calculations.

On the Composition of Risk Preference and Belief

ERIC Educational Resources Information Center

Wakkar, Peter P.

2004-01-01

Prospect theory assumes nonadditive decision weights for preferences over risky gambles. Such decision weights generalize additive probabilities. This article proposes a decomposition of decision weights into a component reflecting risk attitude and a new component depending on belief. The decomposition is based on an observable preference…

Health decision making: lynchpin of evidence-based practice.

PubMed

Spring, Bonnie

2008-01-01

Health decision making is both the lynchpin and the least developed aspect of evidence-based practice. The evidence-based practice process requires integrating the evidence with consideration of practical resources and patient preferences and doing so via a process that is genuinely collaborative. Yet, the literature is largely silent about how to accomplish integrative, shared decision making. for evidence-based practice are discussed for 2 theories of clinician decision making (expected utility and fuzzy trace) and 2 theories of patient health decision making (transtheoretical model and reasoned action). Three suggestions are offered. First, it would be advantageous to have theory-based algorithms that weight and integrate the 3 data strands (evidence, resources, preferences) in different decisional contexts. Second, patients, not providers, make the decisions of greatest impact on public health, and those decisions are behavioral. Consequently, theory explicating how provider-patient collaboration can influence patient lifestyle decisions made miles from the provider's office is greatly needed. Third, although the preponderance of data on complex decisions supports a computational approach, such an approach to evidence-based practice is too impractical to be widely applied at present. More troublesomely, until patients come to trust decisions made computationally more than they trust their providers' intuitions, patient adherence will remain problematic. A good theory of integrative, collaborative health decision making remains needed.

Health Decision Making: Lynchpin of Evidence-Based Practice

PubMed Central

Spring, Bonnie

2008-01-01

Health decision making is both the lynchpin and the least developed aspect of evidence-based practice. The evidence-based practice process requires integrating the evidence with consideration of practical resources and patient preferences and doing so via a process that is genuinely collaborative. Yet, the literature is largely silent about how to accomplish integrative, shared decision making. Implications for evidence-based practice are discussed for 2 theories of clinician decision making (expected utility and fuzzy trace) and 2 theories of patient health decision making (transtheoretical model and reasoned action). Three suggestions are offered. First, it would be advantageous to have theory-based algorithms that weight and integrate the 3 data strands (evidence, resources, preferences) in different decisional contexts. Second, patients, not providers, make the decisions of greatest impact on public health, and those decisions are behavioral. Consequently, theory explicating how provider-patient collaboration can influence patient lifestyle decisions made miles from the provider's office is greatly needed. Third, although the preponderance of data on complex decisions supports a computational approach, such an approach to evidence-based practice is too impractical to be widely applied at present. More troublesomely, until patients come to trust decisions made computationally more than they trust their providers’ intuitions, patient adherence will remain problematic. A good theory of integrative, collaborative health decision making remains needed. PMID:19015288

Investigation of effective decision criteria for multiobjective optimization in IMRT.

PubMed

Holdsworth, Clay; Stewart, Robert D; Kim, Minsun; Liao, Jay; Phillips, Mark H

2011-06-01

To investigate how using different sets of decision criteria impacts the quality of intensity modulated radiation therapy (IMRT) plans obtained by multiobjective optimization. A multiobjective optimization evolutionary algorithm (MOEA) was used to produce sets of IMRT plans. The MOEA consisted of two interacting algorithms: (i) a deterministic inverse planning optimization of beamlet intensities that minimizes a weighted sum of quadratic penalty objectives to generate IMRT plans and (ii) an evolutionary algorithm that selects the superior IMRT plans using decision criteria and uses those plans to determine the new weights and penalty objectives of each new plan. Plans resulting from the deterministic algorithm were evaluated by the evolutionary algorithm using a set of decision criteria for both targets and organs at risk (OARs). Decision criteria used included variation in the target dose distribution, mean dose, maximum dose, generalized equivalent uniform dose (gEUD), an equivalent uniform dose (EUD(alpha,beta) formula derived from the linear-quadratic survival model, and points on dose volume histograms (DVHs). In order to quantatively compare results from trials using different decision criteria, a neutral set of comparison metrics was used. For each set of decision criteria investigated, IMRT plans were calculated for four different cases: two simple prostate cases, one complex prostate Case, and one complex head and neck Case. When smaller numbers of decision criteria, more descriptive decision criteria, or less anti-correlated decision criteria were used to characterize plan quality during multiobjective optimization, dose to OARs and target dose variation were reduced in the final population of plans. Mean OAR dose and gEUD (a = 4) decision criteria were comparable. Using maximum dose decision criteria for OARs near targets resulted in inferior populations that focused solely on low target variance at the expense of high OAR dose. Target dose range, (D(max) - D(min)), decision criteria were found to be most effective for keeping targets uniform. Using target gEUD decision criteria resulted in much lower OAR doses but much higher target dose variation. EUD(alpha,beta) based decision criteria focused on a region of plan space that was a compromise between target and OAR objectives. None of these target decision criteria dominated plans using other criteria, but only focused on approaching a different area of the Pareto front. The choice of decision criteria implemented in the MOEA had a significant impact on the region explored and the rate of convergence toward the Pareto front. When more decision criteria, anticorrelated decision criteria, or decision criteria with insufficient information were implemented, inferior populations are resulted. When more informative decision criteria were used, such as gEUD, EUD(alpha,beta), target dose range, and mean dose, MOEA optimizations focused on approaching different regions of the Pareto front, but did not dominate each other. Using simple OAR decision criteria and target EUD(alpha,beta) decision criteria demonstrated the potential to generate IMRT plans that significantly reduce dose to OARs while achieving the same or better tumor control when clinical requirements on target dose variance can be met or relaxed.

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

PubMed

Li, Lian-Hui; Mo, Rong

2015-01-01

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

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

PubMed Central

Li, Lian-hui; Mo, Rong

2015-01-01

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

Multicriteria Selection of Optimal Location of TCSC in a Competitive Energy Market

NASA Astrophysics Data System (ADS)

Alomoush, Muwaffaq I.

2010-05-01

The paper investigates selection of the best location of thyristor-controlled series compensator (TCSC) in a transmission system from many candidate locations in a competitive energy market such that the TCSC causes a net valuable impact on congestion management outcome, transmission utilization, transmission losses, voltage stability, degree of fulfillment of spot market contracts, and system security. The problem is treated as a multicriteria decision-making process such that the candidate locations of TCSC are the alternatives and the conflicting objectives are the outcomes of the dispatch process, which may have different importance weights. The paper proposes some performance indices that the dispatch decision-making entity can use to measure market dispatch outcomes of each alternative. Based on agreed-upon preferences, the measures presented may help the decision maker compare and rank dispatch scenarios to ultimately decide which location is the optimal one. To solve the multicriteria decision, we use the preference ranking organization method for enrichment evaluations (PROMETHEE), which is a multicriteria decision support method that can handle complex conflicting-objective decision-making processes.

An attentional drift diffusion model over binary-attribute choice.

PubMed

Fisher, Geoffrey

2017-11-01

In order to make good decisions, individuals need to identify and properly integrate information about various attributes associated with a choice. Since choices are often complex and made rapidly, they are typically affected by contextual variables that are thought to influence how much attention is paid to different attributes. I propose a modification of the attentional drift-diffusion model, the binary-attribute attentional drift diffusion model (baDDM), which describes the choice process over simple binary-attribute choices and how it is affected by fluctuations in visual attention. Using an eye-tracking experiment, I find the baDDM makes accurate quantitative predictions about several key variables including choices, reaction times, and how these variables are correlated with attention to two attributes in an accept-reject decision. Furthermore, I estimate an attribute-based fixation bias that suggests attention to an attribute increases its subjective weight by 5%, while the unattended attribute's weight is decreased by 10%. Copyright © 2017 Elsevier B.V. All rights reserved.

Prospect theory and body mass: characterizing psychological parameters for weight-related risk attitudes and weight-gain aversion.

PubMed

Lim, Seung-Lark; Bruce, Amanda S

2015-01-01

We developed a novel decision-making paradigm that allows us to apply prospect theory in behavioral economics to body mass. 67 healthy young adults completed self-report measures and two decision-making tasks for weight-loss, as well as for monetary rewards. We estimated risk-related preference and loss aversion parameters for each individual, separately for weight-loss and monetary rewards choice data. Risk-seeking tendency for weight-loss was positively correlated with body mass index in individuals who desired to lose body weight, whereas the risk-seeking for momentary rewards was not. Risk-seeking for weight-loss was correlated to excessive body shape preoccupations, while aversion to weight-gain was correlated with self-reports of behavioral involvement for successful weight-loss. We demonstrated that prospect theory can be useful in explaining the decision-making process related to body mass. Applying prospect theory is expected to advance our understanding of decision-making mechanisms in obesity, which might prove helpful for improving healthy choices.

Prospect theory and body mass: characterizing psychological parameters for weight-related risk attitudes and weight-gain aversion

PubMed Central

Lim, Seung-Lark; Bruce, Amanda S.

2015-01-01

We developed a novel decision-making paradigm that allows us to apply prospect theory in behavioral economics to body mass. 67 healthy young adults completed self-report measures and two decision-making tasks for weight-loss, as well as for monetary rewards. We estimated risk-related preference and loss aversion parameters for each individual, separately for weight-loss and monetary rewards choice data. Risk-seeking tendency for weight-loss was positively correlated with body mass index in individuals who desired to lose body weight, whereas the risk-seeking for momentary rewards was not. Risk-seeking for weight-loss was correlated to excessive body shape preoccupations, while aversion to weight-gain was correlated with self-reports of behavioral involvement for successful weight-loss. We demonstrated that prospect theory can be useful in explaining the decision-making process related to body mass. Applying prospect theory is expected to advance our understanding of decision-making mechanisms in obesity, which might prove helpful for improving healthy choices. PMID:25852628

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

PubMed

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

2009-04-01

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

Box codes of lengths 48 and 72

NASA Technical Reports Server (NTRS)

Solomon, G.; Jin, Y.

1993-01-01

A self-dual code length 48, dimension 24, with Hamming distance essentially equal to 12 is constructed here. There are only six code words of weight eight. All the other code words have weights that are multiples of four and have a minimum weight equal to 12. This code may be encoded systematically and arises from a strict binary representation of the (8,4;5) Reed-Solomon (RS) code over GF (64). The code may be considered as six interrelated (8,7;2) codes. The Mattson-Solomon representation of the cyclic decomposition of these codes and their parity sums are used to detect an odd number of errors in any of the six codes. These may then be used in a correction algorithm for hard or soft decision decoding. A (72,36;15) box code was constructed from a (63,35;8) cyclic code. The theoretical justification is presented herein. A second (72,36;15) code is constructed from an inner (63,27;16) Bose Chaudhuri Hocquenghem (BCH) code and expanded to length 72 using box code algorithms for extension. This code was simulated and verified to have a minimum distance of 15 with even weight words congruent to zero modulo four. The decoding for hard and soft decision is still more complex than the first code constructed above. Finally, an (8,4;5) RS code over GF (512) in the binary representation of the (72,36;15) box code gives rise to a (72,36;16*) code with nine words of weight eight, and all the rest have weights greater than or equal to 16.

Goal-Directed Decision Making with Spiking Neurons.

PubMed

Friedrich, Johannes; Lengyel, Máté

2016-02-03

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. Copyright © 2016 the authors 0270-6474/16/361529-18$15.00/0.

Goal-Directed Decision Making with Spiking Neurons

PubMed Central

Lengyel, Máté

2016-01-01

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. SIGNIFICANCE STATEMENT Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. PMID:26843636

Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay

USGS Publications Warehouse

McGowan, Conor P.; Smith, David R.; Nichols, James D.; Lyons, James E.; Sweka, John A.; Kalasz, Kevin; Niles, Lawrence J.; Wong, Richard; Brust, Jeffrey; Davis, Michelle C.; Spear, Braddock

2015-01-01

Decision analytic approaches have been widely recommended as well suited to solving disputed and ecologically complex natural resource management problems with multiple objectives and high uncertainty. However, the difference between theory and practice is substantial, as there are very few actual resource management programs that represent formal applications of decision analysis. We applied the process of structured decision making to Atlantic horseshoe crab harvest decisions in the Delaware Bay region to develop a multispecies adaptive management (AM) plan, which is currently being implemented. Horseshoe crab harvest has been a controversial management issue since the late 1990s. A largely unregulated horseshoe crab harvest caused a decline in crab spawning abundance. That decline coincided with a major decline in migratory shorebird populations that consume horseshoe crab eggs on the sandy beaches of Delaware Bay during spring migration. Our approach incorporated multiple stakeholders, including fishery and shorebird conservation advocates, to account for diverse management objectives and varied opinions on ecosystem function. Through consensus building, we devised an objective statement and quantitative objective function to evaluate alternative crab harvest policies. We developed a set of competing ecological models accounting for the leading hypotheses on the interaction between shorebirds and horseshoe crabs. The models were initially weighted based on stakeholder confidence in these hypotheses, but weights will be adjusted based on monitoring and Bayesian model weight updating. These models were used together to predict the effects of management actions on the crab and shorebird populations. Finally, we used a dynamic optimization routine to identify the state dependent optimal harvest policy for horseshoe crabs, given the possible actions, the stated objectives and our competing hypotheses about system function. The AM plan was reviewed, accepted and implemented by the Atlantic States Marine Fisheries Commission in 2012 and 2013. While disagreements among stakeholders persist, structured decision making enabled unprecedented progress towards a transparent and consensus driven management plan for crabs and shorebirds in Delaware Bay.

A rough set approach for determining weights of decision makers in group decision making.

PubMed

Yang, Qiang; Du, Ping-An; Wang, Yong; Liang, Bin

2017-01-01

This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs' decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member' decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs' evaluations and selections.

Heuristics in Managing Complex Clinical Decision Tasks in Experts’ Decision Making

PubMed Central

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2016-01-01

Background Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Conclusion Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design. PMID:27275019

Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

PubMed

Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

2014-09-01

Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

Does technique matter; a pilot study exploring weighting techniques for a multi-criteria decision support framework.

PubMed

van Til, Janine; Groothuis-Oudshoorn, Catharina; Lieferink, Marijke; Dolan, James; Goetghebeur, Mireille

2014-01-01

There is an increased interest in the use of multi-criteria decision analysis (MCDA) to support regulatory and reimbursement decision making. The EVIDEM framework was developed to provide pragmatic multi-criteria decision support in health care, to estimate the value of healthcare interventions, and to aid in priority-setting. The objectives of this study were to test 1) the influence of different weighting techniques on the overall outcome of an MCDA exercise, 2) the discriminative power in weighting different criteria of such techniques, and 3) whether different techniques result in similar weights in weighting the criteria set proposed by the EVIDEM framework. A sample of 60 Dutch and Canadian students participated in the study. Each student used an online survey to provide weights for 14 criteria with two different techniques: a five-point rating scale and one of the following techniques selected randomly: ranking, point allocation, pairwise comparison and best worst scaling. The results of this study indicate that there is no effect of differences in weights on value estimates at the group level. On an individual level, considerable differences in criteria weights and rank order occur as a result of the weight elicitation method used, and the ability of different techniques to discriminate in criteria importance. Of the five techniques tested, the pair-wise comparison of criteria has the highest ability to discriminate in weights when fourteen criteria are compared. When weights are intended to support group decisions, the choice of elicitation technique has negligible impact on criteria weights and the overall value of an innovation. However, when weights are used to support individual decisions, the choice of elicitation technique influences outcome and studies that use dissimilar techniques cannot be easily compared. Weight elicitation through pairwise comparison of criteria is preferred when taking into account its superior ability to discriminate between criteria and respondents' preferences.

Development of a Framework Based on Reflective MCDA to Support Patient-Clinician Shared Decision-Making: The Case of the Management of Gastroenteropancreatic Neuroendocrine Tumors (GEP-NET) in the United States.

PubMed

Wagner, Monika; Samaha, Dima; Khoury, Hanane; O'Neil, William M; Lavoie, Louis; Bennetts, Liga; Badgley, Danielle; Gabriel, Sylvie; Berthon, Anthony; Dolan, James; Kulke, Matthew H; Goetghebeur, Mireille

2018-01-01

Well- or moderately differentiated gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are often slow-growing, and some patients with unresectable, asymptomatic, non-functioning tumors may face the choice between watchful waiting (WW), or somatostatin analogues (SSA) to delay progression. We developed a comprehensive multi-criteria decision analysis (MCDA) framework to help patients and physicians clarify their values and preferences, consider each decision criterion, and support communication and shared decision-making. The framework was adapted from a generic MCDA framework (EVIDEM) with patient and clinician input. During a workshop, patients and clinicians expressed their individual values and preferences (criteria weights) and, on the basis of two scenarios (treatment vs WW; SSA-1 [lanreotide] vs SSA-2 [octreotide]) with evidence from a literature review, expressed how consideration of each criterion would impact their decision in favor of either option (score), and shared their knowledge and insights verbally and in writing. The framework included benefit-risk criteria and modulating factors, such as disease severity, quality of evidence, costs, and constraints. Overall and progression-free survival being most important, criteria weights ranged widely, highlighting variations in individual values and the need to share them. Scoring and considering each criterion prompted a rich exchange of perspectives and uncovered individual assumptions and interpretations. At the group level, type of benefit, disease severity, effectiveness, and quality of evidence favored treatment; cost aspects favored WW (scenario 1). For scenario 2, most criteria did not favor either option. Patients and clinicians consider many aspects in decision-making. The MCDA framework provided a common interpretive frame to structure this complexity, support individual reflection, and share perspectives. Ipsen Pharma.

Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game

DTIC Science & Technology

2010-03-01

separate LoA heuristic. If any of the examined heuristics produced competitive player , then the final measurement was a success . Barring that, a...if offline training actually results in a successful player . Whereas offline learning plays many games and then trains as many networks as desired...a competitive Lines of Action player , shedding light on the difficulty of developing a neural network to model such a large and complex solution

ELICIT: An alternative imprecise weight elicitation technique for use in multi-criteria decision analysis for healthcare.

PubMed

Diaby, Vakaramoko; Sanogo, Vassiki; Moussa, Kouame Richard

2016-01-01

In this paper, the readers are introduced to ELICIT, an imprecise weight elicitation technique for multicriteria decision analysis for healthcare. The application of ELICIT consists of two steps: the rank ordering of evaluation criteria based on decision-makers' (DMs) preferences using the principal component analysis; and the estimation of criteria weights and their descriptive statistics using the variable interdependent analysis and the Monte Carlo method. The application of ELICIT is illustrated with a hypothetical case study involving the elicitation of weights for five criteria used to select the best device for eye surgery. The criteria were ranked from 1-5, based on a strict preference relationship established by the DMs. For each criterion, the deterministic weight was estimated as well as the standard deviation and 95% credibility interval. ELICIT is appropriate in situations where only ordinal DMs' preferences are available to elicit decision criteria weights.

Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

PubMed

Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

2014-11-26

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

[The decision of an obese woman to have bariatric surgery: the social phenomenology].

PubMed

Oliveira, Deíse Moura de; Merighi, Miriam Aparecida Barbosa; Jesus, Maria Cristina Pinto de

2014-12-01

To understand the process by which an obese woman decides to have bariatric surgery. A qualitative survey with a social phenomenology approach, carried out in 2012, with 12 women, using the phenomenological interview. A woman bases the decision to have the surgery on: the inappropriateness of her eating habits; a physical appearance that is incompatible with an appearance that is standardized by society; the social prejudice that she has to live with; the limitations imposed by obesity; and her lack of success with previous attempts to lose weight. Outcomes that she hopes for from the decision to have the surgery include: restoring her health; achieving social inclusion; and entering the labor market. This study allows one to reflect that prescriptive actions do not give a satisfactory response to a complexity of the subjective questions involved in the decision to have surgery for obesity. For this, what is called for is a program of work based on an interdisciplinary approach, and training that gives value to the bio-psycho-social aspects involved in a decision in favor of surgical treatment.

The effect of sad facial expressions on weight judgment

PubMed Central

Weston, Trent D.; Hass, Norah C.; Lim, Seung-Lark

2015-01-01

Although the body weight evaluation (e.g., normal or overweight) of others relies on perceptual impressions, it also can be influenced by other psychosocial factors. In this study, we explored the effect of task-irrelevant emotional facial expressions on judgments of body weight and the relationship between emotion-induced weight judgment bias and other psychosocial variables including attitudes toward obese persons. Forty-four participants were asked to quickly make binary body weight decisions for 960 randomized sad and neutral faces of varying weight levels presented on a computer screen. The results showed that sad facial expressions systematically decreased the decision threshold of overweight judgments for male faces. This perceptual decision bias by emotional expressions was positively correlated with the belief that being overweight is not under the control of obese persons. Our results provide experimental evidence that task-irrelevant emotional expressions can systematically change the decision threshold for weight judgments, demonstrating that sad expressions can make faces appear more overweight than they would otherwise be judged. PMID:25914669

Modulating activity in the prefrontal cortex changes decision-making for risky gains and losses: a transcranial direct current stimulation study.

PubMed

Ye, Hang; Chen, Shu; Huang, Daqiang; Wang, Siqi; Luo, Jun

2015-06-01

When making choices under uncertainty, people usually consider both the risks and benefits of each option. Previous studies have found that weighing of risks and benefits during decision-making involves a complex neural network that includes the dorsolateral prefrontal cortex (DLPFC), but the causal effect of this network on risk decision-making has remained unclear. This experiment was based on a risk-measurement table designed to provide a direct measure of risk preference, with a weighted value of the choices (denoted as weighted risk aversion, WRA) as an index of the participant's degree of risk aversion. We studied whether bifrontal transcranial direct current stimulation (tDCS) applied over the right and left prefrontal cortex can change the balance of risky vs. safe responses under both gain frame and loss frame. A total of 60 volunteers performed risk tasks while receiving either anodal over the right with cathodal over the left DLPFC, anodal over the left with cathodal over the right DLPFC, or sham stimulation. The participants tended to choose more risky options in the gain frame and more safe options in the loss frame after the right anodal/left cathodal tDCS. We also found that right anodal/left cathodal tDCS significantly decreased the WRA values compared with those associated with sham stimulation. These findings extend the notion that DLPFC activity is critical for risk decision-making, indicating an asymmetric role of the right DLPFC in the gain frame vs. the loss frame of risk decision-making. Copyright © 2015 Elsevier B.V. All rights reserved.

Amplifying Each Patient's Voice: A Systematic Review of Multi-criteria Decision Analyses Involving Patients.

PubMed

Marsh, Kevin; Caro, J Jaime; Hamed, Alaa; Zaiser, Erica

2017-04-01

Qualitative methods tend to be used to incorporate patient preferences into healthcare decision making. However, for patient preferences to be given adequate consideration by decision makers they need to be quantified. Multi-criteria decision analysis (MCDA) is one way to quantify and capture the patient voice. The objective of this review was to report on existing MCDAs involving patients to support the future use of MCDA to capture the patient voice. MEDLINE and EMBASE were searched in June 2014 for English-language papers with no date restriction. The following search terms were used: 'multi-criteria decision*', 'multiple criteria decision*', 'MCDA', 'benefit risk assessment*', 'risk benefit assessment*', 'multicriteri* decision*', 'MCDM', 'multi-criteri* decision*'. Abstracts were included if they reported the application of MCDA to assess healthcare interventions where patients were the source of weights. Abstracts were excluded if they did not apply MCDA, such as discussions of how MCDA could be used; or did not evaluate healthcare interventions, such as MCDAs to assess the level of health need in a locality. Data were extracted on weighting method, variation in patient and expert preferences, and discussion on different weighting techniques. The review identified ten English-language studies that reported an MCDA to assess healthcare interventions and involved patients as a source of weights. These studies reported 12 applications of MCDA. Different methods of preference elicitation were employed: direct weighting in workshops; discrete choice experiment surveys; and the analytical hierarchy process using both workshops and surveys. There was significant heterogeneity in patient responses and differences between patients, who put greater weight on disease characteristics and treatment convenience, and experts, who put more weight on efficacy. The studies highlighted cognitive challenges associated with some weighting methods, though patients' views on their ability to undertake weighting tasks was positive. This review identified several recent examples of MCDA used to elicit patient preferences, which support the feasibility of using MCDA to capture the patient voice. Challenges identified included, how best to reflect the heterogeneity of patient preferences in decision making and how to manage the cognitive burden associated with some MCDA tasks.

Comparison AHP and SAW to promotion of head major department SMK Muhammadiyah 04 Medan

NASA Astrophysics Data System (ADS)

Saputra, M.; Sitompul, O. S.; Sihombing, P.

2018-04-01

Decision Support System (DSS) is a system that can help a person to make informed decisions about various types of choices that are performed accurately and in accordance with the desired goals. Many problems can be solved by using decision support systems. In this journal the decision support system is used to assist the Chief of Muhammadiyah Medan branch in the selection of the department chief. The criteria used for the election of department chiefs are: Loyalty, Job Performance, Responsibility, Obedience, Honesty, Cooperation, Education, and Leadership. The selection promotion process consists of Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The data were obtained through teacher assessment questionnaires by principals and colleagues. The results of this study used a comparison with two decision methods namely SAW method and AHP method so that the decision maker (principal) is more appropriate in the determination of candidates who will be elected head of department at school. The final result of this research is the first rank obtained by muhammad musa with weight value on AHP method (0.274) and weight value on SAW method (0.993), alvin syahrin with weight value on AHP method (0.241) and weight value on SAW method (0.883), noviyanti with weight value on AHP method (0.193) and weight value on SAW method (0.707). So the conclusion on the research that is by using SAW method the value of weight produced more accurate.

Inhibitory Control in the Cortico-Basal Ganglia-Thalamocortical Loop: Complex Regulation and Interplay with Memory and Decision Processes.

PubMed

Wei, Wei; Wang, Xiao-Jing

2016-12-07

We developed a circuit model of spiking neurons that includes multiple pathways in the basal ganglia (BG) and is endowed with feedback mechanisms at three levels: cortical microcircuit, corticothalamic loop, and cortico-BG-thalamocortical system. We focused on executive control in a stop signal task, which is known to depend on BG across species. The model reproduces a range of experimental observations and shows that the newly discovered feedback projection from external globus pallidus to striatum is crucial for inhibitory control. Moreover, stopping process is enhanced by the cortico-subcortical reverberatory dynamics underlying persistent activity, establishing interdependence between working memory and inhibitory control. Surprisingly, the stop signal reaction time (SSRT) can be adjusted by weights of certain connections but is insensitive to other connections in this complex circuit, suggesting novel circuit-based intervention for inhibitory control deficits associated with mental illness. Our model provides a unified framework for inhibitory control, decision making, and working memory. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2009-01-01

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

Application of the fuzzy topsis multi-attribute decision making method to determine scholarship recipients

NASA Astrophysics Data System (ADS)

Irvanizam, I.

2018-03-01

Some scholarships have been routinely offered by Ministry of Research, Technology and Higher Education of the Republic of Indonesia for students at Syiah Kuala University. In reality, the scholarship selection process is becoming subjective and highly complex problem. Multi-Attribute Decision Making (MADM) techniques can be a solution in order to solve scholarship selection problem. In this study, we demonstrated the application of a fuzzy TOPSIS as an MADM technique by using a numerical example in order to calculate a triangular fuzzy number for the fuzzy data onto a normalized weight. We then use this normalized value to construct the normalized fuzzy decision matrix. We finally use the fuzzy TOPSIS to rank alternatives in descending order based on the relative closeness to the ideal solution. The result in terms of final ranking shows slightly different from the previous work.

Augmented Hebbian reweighting accounts for accuracy and induced bias in perceptual learning with reverse feedback

PubMed Central

Liu, Jiajuan; Dosher, Barbara Anne; Lu, Zhong-Lin

2015-01-01

Using an asymmetrical set of vernier stimuli (−15″, −10″, −5″, +10″, +15″) together with reverse feedback on the small subthreshold offset stimulus (−5″) induces response bias in performance (Aberg & Herzog, 2012; Herzog, Eward, Hermens, & Fahle, 2006; Herzog & Fahle, 1999). These conditions are of interest for testing models of perceptual learning because the world does not always present balanced stimulus frequencies or accurate feedback. Here we provide a comprehensive model for the complex set of asymmetric training results using the augmented Hebbian reweighting model (Liu, Dosher, & Lu, 2014; Petrov, Dosher, & Lu, 2005, 2006) and the multilocation integrated reweighting theory (Dosher, Jeter, Liu, & Lu, 2013). The augmented Hebbian learning algorithm incorporates trial-by-trial feedback, when present, as another input to the decision unit and uses the observer's internal response to update the weights otherwise; block feedback alters the weights on bias correction (Liu et al., 2014). Asymmetric training with reversed feedback incorporates biases into the weights between representation and decision. The model correctly predicts the basic induction effect, its dependence on trial-by-trial feedback, and the specificity of bias to stimulus orientation and spatial location, extending the range of augmented Hebbian reweighting accounts of perceptual learning. PMID:26418382

Augmented Hebbian reweighting accounts for accuracy and induced bias in perceptual learning with reverse feedback.

PubMed

Liu, Jiajuan; Dosher, Barbara Anne; Lu, Zhong-Lin

2015-01-01

Using an asymmetrical set of vernier stimuli (-15″, -10″, -5″, +10″, +15″) together with reverse feedback on the small subthreshold offset stimulus (-5″) induces response bias in performance (Aberg & Herzog, 2012; Herzog, Eward, Hermens, & Fahle, 2006; Herzog & Fahle, 1999). These conditions are of interest for testing models of perceptual learning because the world does not always present balanced stimulus frequencies or accurate feedback. Here we provide a comprehensive model for the complex set of asymmetric training results using the augmented Hebbian reweighting model (Liu, Dosher, & Lu, 2014; Petrov, Dosher, & Lu, 2005, 2006) and the multilocation integrated reweighting theory (Dosher, Jeter, Liu, & Lu, 2013). The augmented Hebbian learning algorithm incorporates trial-by-trial feedback, when present, as another input to the decision unit and uses the observer's internal response to update the weights otherwise; block feedback alters the weights on bias correction (Liu et al., 2014). Asymmetric training with reversed feedback incorporates biases into the weights between representation and decision. The model correctly predicts the basic induction effect, its dependence on trial-by-trial feedback, and the specificity of bias to stimulus orientation and spatial location, extending the range of augmented Hebbian reweighting accounts of perceptual learning.

A rough set approach for determining weights of decision makers in group decision making

PubMed Central

Yang, Qiang; Du, Ping-an; Wang, Yong; Liang, Bin

2017-01-01

This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs’ decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member’ decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs’ evaluations and selections. PMID:28234974

Joint carrier phase and frequency-offset estimation with parallel implementation for dual-polarization coherent receiver.

PubMed

Lu, Jianing; Li, Xiang; Fu, Songnian; Luo, Ming; Xiang, Meng; Zhou, Huibin; Tang, Ming; Liu, Deming

2017-03-06

We present dual-polarization complex-weighted, decision-aided, maximum-likelihood algorithm with superscalar parallelization (SSP-DP-CW-DA-ML) for joint carrier phase and frequency-offset estimation (FOE) in coherent optical receivers. By pre-compensation of the phase offset between signals in dual polarizations, the performance can be substantially improved. Meanwhile, with the help of modified SSP-based parallel implementation, the acquisition time of FO and the required number of training symbols are reduced by transferring the complex weights of the filters between adjacent buffers, where differential coding/decoding is not required. Simulation results show that the laser linewidth tolerance of our proposed algorithm is comparable to traditional blind phase search (BPS), while a complete FOE range of ± symbol rate/2 can be achieved. Finally, performance of our proposed algorithm is experimentally verified under the scenario of back-to-back (B2B) transmission using 10 Gbaud DP-16/32-QAM formats.

Differences in SEM-AVS and ERM-ERL predictions of sediment impacts from metals in two US Virgin Islands marinas.

PubMed

Hinkey, Lynne M; Zaidi, Baqar R

2007-02-01

Two US Virgin Islands marinas were examined for potential metal impacts by comparing sediment chemistry data with two sediment quality guideline (SQG) values: the ratio of simultaneously extractable metals to acid volatile sulfides (SEM-AVS), and effects range-low and -mean (ERL-ERM) values. ERL-ERMs predicted the marina/boatyard complex (IBY: 2118 microg/g dry weight total metals, two exceeded ERMs) would have greater impacts than the marina with no boatyard (CBM: 231 microg/g dry weight total metals, no ERMs exceeded). The AVS-SEM method predicted IBY would have fewer effects due to high AVS-forming metal sulfide complexes, reducing trace metal bioavailability. These contradictory predictions demonstrate the importance of validating the results of either of these methods with other toxicity measures before making any management or regulatory decisions regarding boating and marina impacts. This is especially important in non-temperate areas where sediment quality guidelines have not been validated.

Individual Confidence-Weighting and Group Decision-Making.

PubMed

Marshall, James A R; Brown, Gavin; Radford, Andrew N

2017-09-01

Group-living species frequently pool individual information so as to reach consensus decisions such as when and where to move, or whether a predator is present. Such opinion-pooling has been demonstrated empirically, and theoretical models have been proposed to explain why group decisions are more reliable than individual decisions. Behavioural ecology theory frequently assumes that all individuals have equal decision-making abilities, but decision theory relaxes this assumption and has been tested in human groups. We summarise relevant theory and argue for its applicability to collective animal decisions. We consider selective pressure on confidence-weighting in groups of related and unrelated individuals. We also consider which species and behaviours may provide evidence of confidence-weighting, paying particular attention to the sophisticated vocal communication of cooperative breeders. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

PubMed Central

Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

Efficient iris recognition based on optimal subfeature selection and weighted subregion fusion.

PubMed

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; He, Fei; Wang, Hongye; Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, and MMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity.

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

Multi-Objective Programming for Lot-Sizing with Quantity Discount

NASA Astrophysics Data System (ADS)

Kang, He-Yau; Lee, Amy H. I.; Lai, Chun-Mei; Kang, Mei-Sung

2011-11-01

Multi-objective programming (MOP) is one of the popular methods for decision making in a complex environment. In a MOP, decision makers try to optimize two or more objectives simultaneously under various constraints. A complete optimal solution seldom exists, and a Pareto-optimal solution is usually used. Some methods, such as the weighting method which assigns priorities to the objectives and sets aspiration levels for the objectives, are used to derive a compromise solution. The ɛ-constraint method is a modified weight method. One of the objective functions is optimized while the other objective functions are treated as constraints and are incorporated in the constraint part of the model. This research considers a stochastic lot-sizing problem with multi-suppliers and quantity discounts. The model is transformed into a mixed integer programming (MIP) model next based on the ɛ-constraint method. An illustrative example is used to illustrate the practicality of the proposed model. The results demonstrate that the model is an effective and accurate tool for determining the replenishment of a manufacturer from multiple suppliers for multi-periods.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clayton, Daniel James; Lipinski, Ronald J.; Bechtel, Ryan D.

As compact and light weight power sources with reliable, long lives, Radioisotope Power Systems (RPSs) have made space missions to explore the solar system possible. Due to the hazardous material that can be released during a launch accident, the potential health risk of an accident must be quantified, so that appropriate launch approval decisions can be made. One part of the risk estimation involves modeling the response of the RPS to potential accident environments. Due to the complexity of modeling the full RPS response deterministically on dynamic variables, the evaluation is performed in a stochastic manner with a Monte Carlomore » simulation. The potential consequences can be determined by modeling the transport of the hazardous material in the environment and in human biological pathways. The consequence analysis results are summed and weighted by appropriate likelihood values to give a collection of probabilistic results for the estimation of the potential health risk. This information is used to guide RPS designs, spacecraft designs, mission architecture, or launch procedures to potentially reduce the risk, as well as to inform decision makers of the potential health risks resulting from the use of RPSs for space missions.« less

A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach.

PubMed

Varmazyar, Mohsen; Dehghanbaghi, Maryam; Afkhami, Mehdi

2016-10-01

Balanced Scorecard (BSC) is a strategic evaluation tool using both financial and non-financial indicators to determine the business performance of organizations or companies. In this paper, a new integrated approach based on the Balanced Scorecard (BSC) and multi-criteria decision making (MCDM) methods are proposed to evaluate the performance of research centers of research and technology organization (RTO) in Iran. Decision-Making Trial and Evaluation Laboratory (DEMATEL) are employed to reflect the interdependencies among BSC perspectives. Then, Analytic Network Process (ANP) is utilized to weight the indices influencing the considered problem. In the next step, we apply four MCDM methods including Additive Ratio Assessment (ARAS), Complex Proportional Assessment (COPRAS), Multi-Objective Optimization by Ratio Analysis (MOORA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking of alternatives. Finally, the utility interval technique is applied to combine the ranking results of MCDM methods. Weighted utility intervals are computed by constructing a correlation matrix between the ranking methods. A real case is presented to show the efficacy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Selection of remedial alternatives for mine sites: a multicriteria decision analysis approach.

PubMed

Betrie, Getnet D; Sadiq, Rehan; Morin, Kevin A; Tesfamariam, Solomon

2013-04-15

The selection of remedial alternatives for mine sites is a complex task because it involves multiple criteria and often with conflicting objectives. However, an existing framework used to select remedial alternatives lacks multicriteria decision analysis (MCDA) aids and does not consider uncertainty in the selection of alternatives. The objective of this paper is to improve the existing framework by introducing deterministic and probabilistic MCDA methods. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) methods have been implemented in this study. The MCDA analysis involves processing inputs to the PROMETHEE methods that are identifying the alternatives, defining the criteria, defining the criteria weights using analytical hierarchical process (AHP), defining the probability distribution of criteria weights, and conducting Monte Carlo Simulation (MCS); running the PROMETHEE methods using these inputs; and conducting a sensitivity analysis. A case study was presented to demonstrate the improved framework at a mine site. The results showed that the improved framework provides a reliable way of selecting remedial alternatives as well as quantifying the impact of different criteria on selecting alternatives. Copyright © 2013 Elsevier Ltd. All rights reserved.

ELICIT: An alternative imprecise weight elicitation technique for use in multi-criteria decision analysis for healthcare

PubMed Central

Diaby, Vakaramoko; Sanogo, Vassiki; Moussa, Kouame Richard

2015-01-01

Objective In this paper, the readers are introduced to ELICIT, an imprecise weight elicitation technique for multicriteria decision analysis for healthcare. Methods The application of ELICIT consists of two steps: the rank ordering of evaluation criteria based on decision-makers’ (DMs) preferences using the principal component analysis; and the estimation of criteria weights and their descriptive statistics using the variable interdependent analysis and the Monte Carlo method. The application of ELICIT is illustrated with a hypothetical case study involving the elicitation of weights for five criteria used to select the best device for eye surgery. Results The criteria were ranked from 1–5, based on a strict preference relationship established by the DMs. For each criterion, the deterministic weight was estimated as well as the standard deviation and 95% credibility interval. Conclusions ELICIT is appropriate in situations where only ordinal DMs’ preferences are available to elicit decision criteria weights. PMID:26361235

Using health outcomes data to inform decision-making: formulary committee perspective.

PubMed

Janknegt, R

2001-01-01

When healthcare resources are limited, decisions about the treatments to fund can be complex and difficult to make, involving the careful balancing of multiple factors. The decisions taken may have far-reaching consequences affecting many people. Clearly, decisions such as the choice of products on a formulary must be taken using a selection process that is fully transparent and that can be justified to all parties concerned. Although everyone would agree that drug selection should be a rational process that follows the guidelines of evidence-based medicine, many other factors may play a role in decision-making. Although some of these are explicit and rational, others are less clearly defined, and decision-makers may be unaware of the influence exerted by some of these factors. In order to facilitate transparent decision-making that makes rational use of health outcomes information, the System of Objectified Judgement Analysis (SOJA) has been developed by the author. SOJA includes interactive software that combines the quality advantages of the 'top-down' approach to drug selection, based on a thorough literature review, with the compliance advantages of a 'bottom-up' approach, where the final decision is made by the individual formulary committee and not by the authors of the review. The SOJA method, based on decision-making processes in economics, ensures that health outcomes information is given appropriate weight. Such approaches are valuable tools in discussions about product selection for formularies.

Relative body weight as a factor in the decision to abort.

PubMed

Thelen, T H; Alumbaugh, R V

1983-06-01

Abortion referral data of 692 pregnant women visiting a large urban planned parenthood clinic were analyzed to determine whether relative weight, as measured by an adiposity index, as well as other variables, were associated with a decision to terminate or not terminate a pregnancy. Relative weight, length of pregnancy, education, age, ethnicity, and marital status were found to be associated with the decision to abort. While most of these variables were previously shown to have been related to the decision to terminate or not terminate a pregnancy, a relationship between relative weight and abortion has not previously been reported. In the analyses of all the women in this study and of a subsample consisting only of those in the early stages of their pregnancies, increased relative weight was associated with a decrease in the likelihood of pregnancy termination. Possible reasons for this relationship and the evolutionary implications are discussed.

Performance on the Iowa gambling task is related to magnitude of weight loss and salivary cortisol in a diet-induced weight loss intervention in overweight women

USDA-ARS?s Scientific Manuscript database

The overall objective of this study was to examine the relationship between executive function, specifically decision making, and weight loss. We used the Iowa Gambling Task (IGT) to characterize decision making and compared performance on this task to weight loss in obese women (n=29) participatin...

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

PubMed

Dolan, James G

2010-01-01

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

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

PubMed Central

Dolan, James G.

2010-01-01

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

Linking Science and Management in an Interactive Geospatial, Mutli-Criterion, Structured Decision Support Framework: Use Case Studies of the "Future Forests Geo-visualization and Decision Support Tool

NASA Astrophysics Data System (ADS)

Pontius, J.; Duncan, J.

2017-12-01

Land managers are often faced with balancing management activities to accomplish a diversity of management objectives, in systems faced with many stress agents. Advances in ecosystem modeling provide a rich source of information to inform management. Coupled with advances in decision support techniques and computing capabilities, interactive tools are now accessible for a broad audience of stakeholders. Here we present one such tool designed to capture information on how climate change may impact forested ecosystems, and how that impact varies spatially across the landscape. This tool integrates empirical models of current and future forest structure and function in a structured decision framework that allows users to customize weights for multiple management objectives and visualize suitability outcomes across the landscape. Combined with climate projections, the resulting products allow stakeholders to compare the relative success of various management objectives on a pixel by pixel basis and identify locations where management outcomes are most likely to be met. Here we demonstrate this approach with the integration of several of the preliminary models developed to map species distributions, sugar maple health, forest fragmentation risk and hemlock vulnerability to hemlock woolly adelgid under current and future climate scenarios. We compare three use case studies with objective weightings designed to: 1) Identify key parcels for sugarbush conservation and management, 2) Target state lands that may serve as hemlock refugia from hemlock woolly adelgid induced mortality, and 3) Examine how climate change may alter the success of managing for both sugarbush and hemlock across privately owned lands. This tool highlights the value of flexible models that can be easily run with customized weightings in a dynamic, integrated assessment that allows users to hone in on their potentially complex management objectives, and to visualize and prioritize locations across the landscape. It also demonstrates the importance of including climate considerations for long-term management. This merging of scientific knowledge with the diversity of stakeholder needs is an important step towards using science to inform management and policy decisions.

Multi Criteria Decision Making to evaluate control strategies of contagious animal diseases.

PubMed

Mourits, M C M; van Asseldonk, M A P M; Huirne, R B M

2010-09-01

The decision on which strategy to use in the control of contagious animal diseases involves complex trade-offs between multiple objectives. This paper describes a Multi Criteria Decision Making (MCDM) application to illustrate its potential support to policy makers in choosing the control strategy that best meets all of the conflicting interests. The presented application focused on the evaluation of alternative strategies to control Classical Swine Fever (CSF) epidemics within the European Union (EU) according to the preferences of the European Chief Veterinary Officers (CVO). The performed analysis was centred on the three high-level objectives of epidemiology, economics and social ethics. The appraised control alternatives consisted of the EU compulsory control strategy, a pre-emptive slaughter strategy, a protective vaccination strategy and a suppressive vaccination strategy. Using averaged preference weights of the elicited CVOs, the preference ranking of the control alternatives was determined for six EU regions. The obtained results emphasized the need for EU region-specific control. Individual CVOs differed in their views on the relative importance of the various (sub)criteria by which the performance of the alternatives were judged. Nevertheless, the individual rankings of the control alternatives within a region appeared surprisingly similar. Based on the results of the described application it was concluded that the structuring feature of the MCDM technique provides a suitable tool in assisting the complex decision making process of controlling contagious animal diseases. 2010 Elsevier B.V. All rights reserved.

Comparison in decision-making between bulimia nervosa, anorexia nervosa, and healthy women: influence of mood status and pathological eating concerns.

PubMed

Matsumoto, Junko; Hirano, Yoshiyuki; Numata, Noriko; Matzuzawa, Daisuke; Murano, Shunichi; Yokote, Koutaro; Iyo, Masaomi; Shimizu, Eiji; Nakazato, Michiko

2015-01-01

Decision-making is reported to be impaired in anorexia nervosa (AN) and bulimia nervosa (BN), but the influence of mood status, pathophysiological eating, and weight concerns on the performance of decision-making ability between AN and BN is still unclear. The aims of this study were to investigate differential impairments in the decision-making process between AN, BN, and healthy controls (HC), and secondly, to explore the role of mood status, such as anxiety, depression, pathological eating, and weight concerns, in decision-making ability. Patients suffering from AN (n = 22), BN (n = 36) and age-matched HC (n = 51) were assessed for their decision-making abilities using the Iowa Gambling Task (IGT). Self-reported questionnaires including the Eating Disorder Examination Questionnaire (EDE-Q), the Bulimia Investigatory Test, Edinburgh (BITE), the Eating Disorders Inventory, the Maudsley Obsessive-Compulsive Inventory measuring obsessive-compulsive traits, the Hospital Anxiety and Depression Scale, and the Toronto Alexithymia Scale were used to assess pathological eating concerns and attitude to feelings. Significant differences in IGT performance were observed between BN and HC. Significant negative correlation was found between IGT performance and the BITE symptom subscale in AN. In BN, there was a negative correlation between the EDE-Q weight concerns subscale and IGT performance. It was also found that increased anxiety, depression, and eating/weight concerns predicted poorer decision-making. Different patterns of association between pathological eating concerns/behaviors and performances in decision-making ability were found between AN, BN, and HC. Anxiety, depressive mood status, and eating/weight concerns were related to decision-making ability.

Automatic Decision Support for Clinical Diagnostic Literature Using Link Analysis in a Weighted Keyword Network.

PubMed

Li, Shuqing; Sun, Ying; Soergel, Dagobert

2017-12-23

We present a novel approach to recommending articles from the medical literature that support clinical diagnostic decision-making, giving detailed descriptions of the associated ideas and principles. The specific goal is to retrieve biomedical articles that help answer questions of a specified type about a particular case. Based on the filtered keywords, MeSH(Medical Subject Headings) lexicon and the automatically extracted acronyms, the relationship between keywords and articles was built. The paper gives a detailed description of the process of by which keywords were measured and relevant articles identified based on link analysis in a weighted keywords network. Some important challenges identified in this study include the extraction of diagnosis-related keywords and a collection of valid sentences based on the keyword co-occurrence analysis and existing descriptions of symptoms. All data were taken from medical articles provided in the TREC (Text Retrieval Conference) clinical decision support track 2015. Ten standard topics and one demonstration topic were tested. In each case, a maximum of five articles with the highest relevance were returned. The total user satisfaction of 3.98 was 33% higher than average. The results also suggested that the smaller the number of results, the higher the average satisfaction. However, a few shortcomings were also revealed since medical literature recommendation for clinical diagnostic decision support is so complex a topic that it cannot be fully addressed through the semantic information carried solely by keywords in existing descriptions of symptoms. Nevertheless, the fact that these articles are actually relevant will no doubt inspire future research.

AdaBoost-based algorithm for network intrusion detection.

PubMed

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

Application of stochastic multiattribute analysis to assessment of single walled carbon nanotube synthesis processes.

PubMed

Canis, Laure; Linkov, Igor; Seager, Thomas P

2010-11-15

The unprecedented uncertainty associated with engineered nanomaterials greatly expands the need for research regarding their potential environmental consequences. However, decision-makers such as regulatory agencies, product developers, or other nanotechnology stakeholders may not find the results of such research directly informative of decisions intended to mitigate environmental risks. To help interpret research findings and prioritize new research needs, there is an acute need for structured decision-analytic aids that are operable in a context of extraordinary uncertainty. Whereas existing stochastic decision-analytic techniques explore uncertainty only in decision-maker preference information, this paper extends model uncertainty to technology performance. As an illustrative example, the framework is applied to the case of single-wall carbon nanotubes. Four different synthesis processes (arc, high pressure carbon monoxide, chemical vapor deposition, and laser) are compared based on five salient performance criteria. A probabilistic rank ordering of preferred processes is determined using outranking normalization and a linear-weighted sum for different weighting scenarios including completely unknown weights and four fixed-weight sets representing hypothetical stakeholder views. No single process pathway dominates under all weight scenarios, but it is likely that some inferior process technologies could be identified as low priorities for further research.

Decision Support Model for Introduction of Gamification Solution Using AHP

PubMed Central

2014-01-01

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

Decision support model for introduction of gamification solution using AHP.

PubMed

Kim, Sangkyun

2014-01-01

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

Multi-criteria decision making to support waste management: A critical review of current practices and methods.

PubMed

Goulart Coelho, Lineker M; Lange, Liséte C; Coelho, Hosmanny Mg

2017-01-01

Solid waste management is a complex domain involving the interaction of several dimensions; thus, its analysis and control impose continuous challenges for decision makers. In this context, multi-criteria decision-making models have become important and convenient supporting tools for solid waste management because they can handle problems involving multiple dimensions and conflicting criteria. However, the selection of the multi-criteria decision-making method is a hard task since there are several multi-criteria decision-making approaches, each one with a large number of variants whose applicability depends on information availability and the aim of the study. Therefore, to support researchers and decision makers, the objectives of this article are to present a literature review of multi-criteria decision-making applications used in solid waste management, offer a critical assessment of the current practices, and provide suggestions for future works. A brief review of fundamental concepts on this topic is first provided, followed by the analysis of 260 articles related to the application of multi-criteria decision making in solid waste management. These studies were investigated in terms of the methodology, including specific steps such as normalisation, weighting, and sensitivity analysis. In addition, information related to waste type, the study objective, and aspects considered was recorded. From the articles analysed it is noted that studies using multi-criteria decision making in solid waste management are predominantly addressed to problems related to municipal solid waste involving facility location or management strategy.

Towards generic online multicriteria decision support in patient-centred health care.

PubMed

Dowie, Jack; Kjer Kaltoft, Mette; Salkeld, Glenn; Cunich, Michelle

2015-10-01

To introduce a new online generic decision support system based on multicriteria decision analysis (MCDA), implemented in practical and user-friendly software (Annalisa©). All parties in health care lack a simple and generic way to picture and process the decisions to be made in pursuit of improved decision making and more informed choice within an overall philosophy of person- and patient-centred care. The MCDA-based system generates patient-specific clinical guidance in the form of an opinion as to the merits of the alternative options in a decision, which are all scored and ranked. The scores for each option combine, in a simple expected value calculation, the best estimates available now for the performance of those options on patient-determined criteria, with the individual patient's preferences, expressed as importance weightings for those criteria. The survey software within which the Annalisa file is embedded (Elicia©) customizes and personalizes the presentation and inputs. Principles relevant to the development of such decision-specific MCDA-based aids are noted and comparisons with alternative implementations presented. The necessity to trade-off practicality (including resource constraints) with normative rigour and empirical complexity, in both their development and delivery, is emphasized. The MCDA-/Annalisa-based decision support system represents a prescriptive addition to the portfolio of decision-aiding tools available online to individuals and clinicians interested in pursuing shared decision making and informed choice within a commitment to transparency in relation to both the evidence and preference bases of decisions. Some empirical data establishing its usability are provided. © 2013 The Authors. Health Expectations published by John Wiley & Sons Ltd.

Multi-criteria decision analysis and environmental risk assessment for nanomaterials

NASA Astrophysics Data System (ADS)

Linkov, Igor; Satterstrom, F. Kyle; Steevens, Jeffery; Ferguson, Elizabeth; Pleus, Richard C.

2007-08-01

Nanotechnology is a broad and complex discipline that holds great promise for innovations that can benefit mankind. Yet, one must not overlook the wide array of factors involved in managing nanomaterial development, ranging from the technical specifications of the material to possible adverse effects in humans. Other opportunities to evaluate benefits and risks are inherent in environmental health and safety (EHS) issues related to nanotechnology. However, there is currently no structured approach for making justifiable and transparent decisions with explicit trade-offs between the many factors that need to be taken into account. While many possible decision-making approaches exist, we believe that multi-criteria decision analysis (MCDA) is a powerful and scientifically sound decision analytical framework for nanomaterial risk assessment and management. This paper combines state-of-the-art research in MCDA methods applicable to nanotechnology with a hypothetical case study for nanomaterial management. The example shows how MCDA application can balance societal benefits against unintended side effects and risks, and how it can also bring together multiple lines of evidence to estimate the likely toxicity and risk of nanomaterials given limited information on physical and chemical properties. The essential contribution of MCDA is to link this performance information with decision criteria and weightings elicited from scientists and managers, allowing visualization and quantification of the trade-offs involved in the decision-making process.

Life cycle impact assessment weights to support environmentally preferable purchasing in the United States.

PubMed

Gloria, Thomas P; Lippiatt, Barbara C; Cooper, Jennifer

2007-11-01

LCA is a quantitative method for understanding the environmental impacts of a product, yet all product purchasing decisions are ultimately subjective. Weights are the nexus between the quantitative results of LCA and the values-based, subjective choices of decision makers. In May 2007, NIST introduced a new optional weight set in Version 4.0 of the BEES software. Three key points about this new optional weight set are the basis for discussion in this paper: The new weight set was created specifically in the context of BEES. It is intended to support a practical method to assist environmentally preferable purchasing in the United States based on LCIA results. This is in contrast to the weight sets currently in BEES, which are based on generalist perspectives. The new weight set was created by a multi-stakeholder panel via the AHP method, and is a synthesis of panelists' perspectives on the relative importance of each environmental impact category in BEES. The weight set draws on each panelist's personal and professional understanding of, and value attributed to, each impact category. While the synthesized weight set may not equally satisfy each panelist's view of impact importance, it does reflect contemporary values in applying LCAto real world decisions, and represents one approach others can learn from in producing weight sets. The new weight set offers BEES users an additional option for synthesizing and comparing the environmental performance of building products and making purchasing decisions. In so doing, it strengthens the decision-making process, which is important when making product comparisons in the public domain. The Weight Set: Across all panelists and with explicit consideration of all time horizons, anthropogenic contributions to global warming, weighted at 29%, was judged most important, yet not so important that decisions can be made solely on the basis of this impact. A strong tail of other concerns include fossil fuel depletion (10%), criteria air pollutants (9%), water intake/use (8%), human health cancerous effects (8%), ecological toxicity (7%), eutrophication of water bodies (6%), land use (6%), and human health noncancerous effects (5%). Also of interest are the identified impact areas of concern assigned the lowest weights: smog formation (4%), indoor air quality (3%), acidification (3%), and ozone depletion (2%). Their low weights may indicate that there is not as much immediate concern or that the remedial actions associated with the impact for the most part are underway.

Effect of Women's Decision-Making Autonomy on Infant's Birth Weight in Rural Bangladesh

PubMed Central

Sharma, Arpana

2013-01-01

Background. Low birth weight (LBW), an outcome of maternal undernutrition, is a major public health concern in Bangladesh where the problem is most prominent. Women's decision-making autonomy is likely an important factor influencing maternal and child health outcomes. The aim of the study was to assess the effect of women's decision-making autonomy on infant's birth weight (BW). Methods. The study included data of 2175 enrolled women (14–45 years of age) from the Maternal and Infant Nutritional Intervention in Matlab (MINIMat-study) in Bangladesh. Pearson's chi-square test, analysis of covariance (ANCOVA), and logistic regression analysis were applied at the collected data. Results. Women with lowest decision-making autonomy were significantly more likely to have a low birth weight (LBW) child, after controlling for maternal age, education (woman's and her husband's), socioeconomic status (SES) (odds ratio (OR) = 1.4; 95% confidence interval (CI) 1.0, 1.8). BW was decreased significantly among women with lowest decision making autonomy after adjusting for all confounders. Conclusion. Women's decision-making autonomy has an independent effect on BW and LBW outcome. In addition, there is a need for further exploration to identify sociocultural attributes and gender related determinants of women decision-making autonomy in this study setting. PMID:24575305

Construction of Early and Midlife Work Trajectories in Women and Their Association With Birth Weight

PubMed Central

Mutambudzi, Miriam

2014-01-01

Objectives. We derived trajectories of the substantive complexity (SC) of work across mid-adult life in women and determined their association with term birth weight. SC is a concept that encompasses decision latitude, active learning, and ability to use and expand one’s abilities at work. Methods. Using occupational data from the National Longitudinal Survey of Youth 1979 and O*NET work variables, we used growth mixture modeling (GMM) to construct longitudinal trajectories of work SC from the ages of 18 to 34 years. The association between work trajectories and birth weight of infants born to study participants was modeled using generalized estimating equations, adjusting for education, income, and relevant covariates. Results. GMM yielded a 5-class solution for work trajectories in women. Higher work trajectories were associated with higher term birth weight and were robust to the inclusion of both education and income. A work trajectory that showed a sharp rise after age 24 years was associated with marked improvement in birth weight. Conclusions. Longitudinal modeling of work characteristics might improve capacity to integrate occupation into a life-course model that examines antecedents and consequences for maternal and child health. PMID:24354827

Numeracy moderates the influence of task-irrelevant affect on probability weighting.

PubMed

Traczyk, Jakub; Fulawka, Kamil

2016-06-01

Statistical numeracy, defined as the ability to understand and process statistical and probability information, plays a significant role in superior decision making. However, recent research has demonstrated that statistical numeracy goes beyond simple comprehension of numbers and mathematical operations. On the contrary to previous studies that were focused on emotions integral to risky prospects, we hypothesized that highly numerate individuals would exhibit more linear probability weighting because they would be less biased by incidental and decision-irrelevant affect. Participants were instructed to make a series of insurance decisions preceded by negative (i.e., fear-inducing) or neutral stimuli. We found that incidental negative affect increased the curvature of the probability weighting function (PWF). Interestingly, this effect was significant only for less numerate individuals, while probability weighting in more numerate people was not altered by decision-irrelevant affect. We propose two candidate mechanisms for the observed effect. Copyright © 2016 Elsevier B.V. All rights reserved.

The relationship between work complexity and nurses' participation in decision making in hospitals.

PubMed

Bacon, Cynthia Thornton; Lee, Shoou-Yih Daniel; Mark, Barbara

2015-04-01

The aim of this study is to examine the relationship between work complexity and nurses' participation in decision making in hospital nursing units. Increasing nurses' participation in decision making has been used as a way to manage work complexity; however, the work of nurses in acute care hospitals has become highly complex, and strategies used to manage this complexity have not been fully explored. The relationship between work complexity and nurse participation in decision making was examined using data from the Outcomes Research in Nursing Administration project. The sample included 3,718 RNs in 278 medical-surgical units in 143 hospitals. When work complexity increased, nurses' participation in decision making decreased. When nurses have limited input into decision making, the information available to the care team may be incomplete. Barriers to nurses' participation in decision making should be explored and interventions developed so that nurses may be full participants in decision making affecting both patients and the work environment.

Dopaminergic Drug Effects on Probability Weighting during Risky Decision Making.

PubMed

Ojala, Karita E; Janssen, Lieneke K; Hashemi, Mahur M; Timmer, Monique H M; Geurts, Dirk E M; Ter Huurne, Niels P; Cools, Roshan; Sescousse, Guillaume

2018-01-01

Dopamine has been associated with risky decision-making, as well as with pathological gambling, a behavioral addiction characterized by excessive risk-taking behavior. However, the specific mechanisms through which dopamine might act to foster risk-taking and pathological gambling remain elusive. Here we test the hypothesis that this might be achieved, in part, via modulation of subjective probability weighting during decision making. Human healthy controls ( n = 21) and pathological gamblers ( n = 16) played a decision-making task involving choices between sure monetary options and risky gambles both in the gain and loss domains. Each participant played the task twice, either under placebo or the dopamine D 2 /D 3 receptor antagonist sulpiride, in a double-blind counterbalanced design. A prospect theory modelling approach was used to estimate subjective probability weighting and sensitivity to monetary outcomes. Consistent with prospect theory, we found that participants presented a distortion in the subjective weighting of probabilities, i.e., they overweighted low probabilities and underweighted moderate to high probabilities, both in the gain and loss domains. Compared with placebo, sulpiride attenuated this distortion in the gain domain. Across drugs, the groups did not differ in their probability weighting, although gamblers consistently underweighted losing probabilities in the placebo condition. Overall, our results reveal that dopamine D 2 /D 3 receptor antagonism modulates the subjective weighting of probabilities in the gain domain, in the direction of more objective, economically rational decision making.

Application of multi-criteria decision analysis in prediction of groundwater resources potential: A case of Oke-Ana, Ilesa Area Southwestern, Nigeria

NASA Astrophysics Data System (ADS)

Akinlalu, A. A.; Adegbuyiro, A.; Adiat, K. A. N.; Akeredolu, B. E.; Lateef, W. Y.

2017-06-01

Groundwater Potential of Oke-Ana area southwestern Nigeria have been evaluated using the integration of electrical resistivity method, remote sensing and geographic information systems. The effect of five hydrogeological indices, namely lineament density, drainage density, lithology, overburden thickness and aquifer layer resistivity on groundwater occurrence was established. Multi-criteria decision analysis technique was employed to assign weight to each of the index using the concept of analytical hierarchy process. The assigned weight was normalized and consistency ratio was established. In order to evaluate the groundwater potential of Oke-Ana, sixty-seven (67) vertical electrical sounding points were occupied. Ten curve types were delineated in the study area. The curve types vary from simple three layer A and H-type curves to the more complex four, five and six layer AA, HA, KH, QH, AKH, HKH, KHA and KHKH curves. Four subsurface geo-electric sequences of top soil, weathered layer, partially weathered/fractured basement and the fresh basement were delineated in the area. The analytical process assisted in classifying Oke-Ana into, low, medium and high groundwater potential zones. Validation of the model from well information and two aborted boreholes suggest 70% agreement.

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

PubMed

Lin, Hui; Wang, Zhou-Jing

2017-09-17

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

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

PubMed Central

Lin, Hui; Wang, Zhou-Jing

2017-01-01

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice. PMID:28926985

Music-evoked incidental happiness modulates probability weighting during risky lottery choices

PubMed Central

Schulreich, Stefan; Heussen, Yana G.; Gerhardt, Holger; Mohr, Peter N. C.; Binkofski, Ferdinand C.; Koelsch, Stefan; Heekeren, Hauke R.

2014-01-01

We often make decisions with uncertain consequences. The outcomes of the choices we make are usually not perfectly predictable but probabilistic, and the probabilities can be known or unknown. Probability judgments, i.e., the assessment of unknown probabilities, can be influenced by evoked emotional states. This suggests that also the weighting of known probabilities in decision making under risk might be influenced by incidental emotions, i.e., emotions unrelated to the judgments and decisions at issue. Probability weighting describes the transformation of probabilities into subjective decision weights for outcomes and is one of the central components of cumulative prospect theory (CPT) that determine risk attitudes. We hypothesized that music-evoked emotions would modulate risk attitudes in the gain domain and in particular probability weighting. Our experiment featured a within-subject design consisting of four conditions in separate sessions. In each condition, the 41 participants listened to a different kind of music—happy, sad, or no music, or sequences of random tones—and performed a repeated pairwise lottery choice task. We found that participants chose the riskier lotteries significantly more often in the “happy” than in the “sad” and “random tones” conditions. Via structural regressions based on CPT, we found that the observed changes in participants' choices can be attributed to changes in the elevation parameter of the probability weighting function: in the “happy” condition, participants showed significantly higher decision weights associated with the larger payoffs than in the “sad” and “random tones” conditions. Moreover, elevation correlated positively with self-reported music-evoked happiness. Thus, our experimental results provide evidence in favor of a causal effect of incidental happiness on risk attitudes that can be explained by changes in probability weighting. PMID:24432007

Music-evoked incidental happiness modulates probability weighting during risky lottery choices.

PubMed

Schulreich, Stefan; Heussen, Yana G; Gerhardt, Holger; Mohr, Peter N C; Binkofski, Ferdinand C; Koelsch, Stefan; Heekeren, Hauke R

2014-01-07

We often make decisions with uncertain consequences. The outcomes of the choices we make are usually not perfectly predictable but probabilistic, and the probabilities can be known or unknown. Probability judgments, i.e., the assessment of unknown probabilities, can be influenced by evoked emotional states. This suggests that also the weighting of known probabilities in decision making under risk might be influenced by incidental emotions, i.e., emotions unrelated to the judgments and decisions at issue. Probability weighting describes the transformation of probabilities into subjective decision weights for outcomes and is one of the central components of cumulative prospect theory (CPT) that determine risk attitudes. We hypothesized that music-evoked emotions would modulate risk attitudes in the gain domain and in particular probability weighting. Our experiment featured a within-subject design consisting of four conditions in separate sessions. In each condition, the 41 participants listened to a different kind of music-happy, sad, or no music, or sequences of random tones-and performed a repeated pairwise lottery choice task. We found that participants chose the riskier lotteries significantly more often in the "happy" than in the "sad" and "random tones" conditions. Via structural regressions based on CPT, we found that the observed changes in participants' choices can be attributed to changes in the elevation parameter of the probability weighting function: in the "happy" condition, participants showed significantly higher decision weights associated with the larger payoffs than in the "sad" and "random tones" conditions. Moreover, elevation correlated positively with self-reported music-evoked happiness. Thus, our experimental results provide evidence in favor of a causal effect of incidental happiness on risk attitudes that can be explained by changes in probability weighting.

Lost in search: (Mal-)adaptation to probabilistic decision environments in children and adults.

PubMed

Betsch, Tilmann; Lehmann, Anne; Lindow, Stefanie; Lang, Anna; Schoemann, Martin

2016-02-01

Adaptive decision making in probabilistic environments requires individuals to use probabilities as weights in predecisional information searches and/or when making subsequent choices. Within a child-friendly computerized environment (Mousekids), we tracked 205 children's (105 children 5-6 years of age and 100 children 9-10 years of age) and 103 adults' (age range: 21-22 years) search behaviors and decisions under different probability dispersions (.17; .33, .83 vs. .50, .67, .83) and constraint conditions (instructions to limit search: yes vs. no). All age groups limited their depth of search when instructed to do so and when probability dispersion was high (range: .17-.83). Unlike adults, children failed to use probabilities as weights for their searches, which were largely not systematic. When examining choices, however, elementary school children (unlike preschoolers) systematically used probabilities as weights in their decisions. This suggests that an intuitive understanding of probabilities and the capacity to use them as weights during integration is not a sufficient condition for applying simple selective search strategies that place one's focus on weight distributions. PsycINFO Database Record (c) 2016 APA, all rights reserved.

Equality bias impairs collective decision-making across cultures

PubMed Central

Mahmoodi, Ali; Bang, Dan; Olsen, Karsten; Zhao, Yuanyuan Aimee; Shi, Zhenhao; Broberg, Kristina; Safavi, Shervin; Han, Shihui; Nili Ahmadabadi, Majid; Frith, Chris D.; Roepstorff, Andreas; Rees, Geraint; Bahrami, Bahador

2015-01-01

We tend to think that everyone deserves an equal say in a debate. This seemingly innocuous assumption can be damaging when we make decisions together as part of a group. To make optimal decisions, group members should weight their differing opinions according to how competent they are relative to one another; whenever they differ in competence, an equal weighting is suboptimal. Here, we asked how people deal with individual differences in competence in the context of a collective perceptual decision-making task. We developed a metric for estimating how participants weight their partner’s opinion relative to their own and compared this weighting to an optimal benchmark. Replicated across three countries (Denmark, Iran, and China), we show that participants assigned nearly equal weights to each other’s opinions regardless of true differences in their competence—even when informed by explicit feedback about their competence gap or under monetary incentives to maximize collective accuracy. This equality bias, whereby people behave as if they are as good or as bad as their partner, is particularly costly for a group when a competence gap separates its members. PMID:25775532

Equality bias impairs collective decision-making across cultures.

PubMed

Mahmoodi, Ali; Bang, Dan; Olsen, Karsten; Zhao, Yuanyuan Aimee; Shi, Zhenhao; Broberg, Kristina; Safavi, Shervin; Han, Shihui; Nili Ahmadabadi, Majid; Frith, Chris D; Roepstorff, Andreas; Rees, Geraint; Bahrami, Bahador

2015-03-24

We tend to think that everyone deserves an equal say in a debate. This seemingly innocuous assumption can be damaging when we make decisions together as part of a group. To make optimal decisions, group members should weight their differing opinions according to how competent they are relative to one another; whenever they differ in competence, an equal weighting is suboptimal. Here, we asked how people deal with individual differences in competence in the context of a collective perceptual decision-making task. We developed a metric for estimating how participants weight their partner's opinion relative to their own and compared this weighting to an optimal benchmark. Replicated across three countries (Denmark, Iran, and China), we show that participants assigned nearly equal weights to each other's opinions regardless of true differences in their competence-even when informed by explicit feedback about their competence gap or under monetary incentives to maximize collective accuracy. This equality bias, whereby people behave as if they are as good or as bad as their partner, is particularly costly for a group when a competence gap separates its members.

A multidisciplinary weight of evidence approach for environmental risk assessment at the Costa Concordia wreck: Integrative indices from Mussel Watch.

PubMed

Regoli, Francesco; Pellegrini, David; Cicero, Anna Maria; Nigro, Marco; Benedetti, Maura; Gorbi, Stefania; Fattorini, Daniele; D'Errico, Giuseppe; Di Carlo, Marta; Nardi, Alessandro; Gaion, Andrea; Scuderi, Alice; Giuliani, Silvia; Romanelli, Giulia; Berto, Daniela; Trabucco, Benedetta; Guidi, Patrizia; Bernardeschi, Margherita; Scarcelli, Vittoria; Frenzilli, Giada

2014-05-01

A complex framework of chemical, biological and oceanographic activities was immediately activated after the Costa Concordia shipwreck, to assess possible contamination events and the environmental impact during both emergency and wreck removal operations. In the present paper, we describe the results obtained with caged mussels, Mytilus galloprovincialis, chosen as bioindicator organisms to detect variations of bioavailability and the early onset of molecular and cellular effects (biomarkers). Seven translocation experiments were carried out during the first year from the incident, with organisms deployed at 2 depths in 3 different sites. After 4-6 weeks, tissue concentrations were measured for the main classes of potentially released chemicals (trace metals, polycyclic aromatic hydrocarbons, volatile and aliphatic hydrocarbons, polychlorinated biphenyls, halogenated pesticides, organotin compounds, brominated flame retardants, anionic surfactants); a wide battery of biomarkers covered responses indicative of exposure, detoxification, oxidative stress, cell damage and genotoxic effects. Results excluded serious contamination events or a consistent increase of environmental pollution although some episodic spills with reversible effects were detected. Data were elaborated within a quantitative weight of evidence (WOE) model which provided synthetic hazard indices for each typology of data, before their overall integration in an environmental risk index, which generally ranged from slight to moderate. The proposed WOE model was confirmed a useful tool to summarize large datasets of complex data in integrative indices, and to simplify the interpretation for stakeholders and decision makers, thus supporting a more comprehensive process of "site-oriented" management decisions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Exaggerated risk: prospect theory and probability weighting in risky choice.

PubMed

Kusev, Petko; van Schaik, Paul; Ayton, Peter; Dent, John; Chater, Nick

2009-11-01

In 5 experiments, we studied precautionary decisions in which participants decided whether or not to buy insurance with specified cost against an undesirable event with specified probability and cost. We compared the risks taken for precautionary decisions with those taken for equivalent monetary gambles. Fitting these data to Tversky and Kahneman's (1992) prospect theory, we found that the weighting function required to model precautionary decisions differed from that required for monetary gambles. This result indicates a failure of the descriptive invariance axiom of expected utility theory. For precautionary decisions, people overweighted small, medium-sized, and moderately large probabilities-they exaggerated risks. This effect is not anticipated by prospect theory or experience-based decision research (Hertwig, Barron, Weber, & Erev, 2004). We found evidence that exaggerated risk is caused by the accessibility of events in memory: The weighting function varies as a function of the accessibility of events. This suggests that people's experiences of events leak into decisions even when risk information is explicitly provided. Our findings highlight a need to investigate how variation in decision content produces variation in preferences for risk.

Phenomenological theory of collective decision-making

NASA Astrophysics Data System (ADS)

Zafeiris, Anna; Koman, Zsombor; Mones, Enys; Vicsek, Tamás

2017-08-01

An essential task of groups is to provide efficient solutions for the complex problems they face. Indeed, considerable efforts have been devoted to the question of collective decision-making related to problems involving a single dominant feature. Here we introduce a quantitative formalism for finding the optimal distribution of the group members' competences in the more typical case when the underlying problem is complex, i.e., multidimensional. Thus, we consider teams that are aiming at obtaining the best possible answer to a problem having a number of independent sub-problems. Our approach is based on a generic scheme for the process of evaluating the proposed solutions (i.e., negotiation). We demonstrate that the best performing groups have at least one specialist for each sub-problem - but a far less intuitive result is that finding the optimal solution by the interacting group members requires that the specialists also have some insight into the sub-problems beyond their unique field(s). We present empirical results obtained by using a large-scale database of citations being in good agreement with the above theory. The framework we have developed can easily be adapted to a variety of realistic situations since taking into account the weights of the sub-problems, the opinions or the relations of the group is straightforward. Consequently, our method can be used in several contexts, especially when the optimal composition of a group of decision-makers is designed.

Ventromedial Frontal Lobe Damage Alters how Specific Attributes are Weighed in Subjective Valuation.

PubMed

Vaidya, Avinash R; Sefranek, Marcus; Fellows, Lesley K

2017-10-23

The concept of subjective value is central to current neurobiological views of economic decision-making. Much of this work has focused on signals in the ventromedial frontal lobe (VMF) that correlate with the subjective value of a variety of stimuli (e.g., food, monetary gambles), and are thought to support decision-making. However, the neural processes involved in assessing and integrating value information from the attributes of such complex options remain to be defined. Here, we tested the necessary role of VMF in weighting attributes of naturalistic stimuli during value judgments. We asked how distinct attributes of visual artworks influenced the subjective value ratings of subjects with VMF damage, compared to healthy participants and a frontal lobe damaged control group. Subjects with VMF damage were less influenced by the energy (emotion, complexity) and color radiance (warmth, saturation) of the artwork, while they were similar to control groups in considering saliency, balance and concreteness. These dissociations argue that VMF is critical for allowing certain affective content to influence subjective value, while sparing the influence of perceptual or representational information. These distinctions are important for better defining the often-underspecified concept of subjective value and developing more detailed models of the brain mechanisms underlying decision behavior. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Vulnerability assessment of urban ecosystems driven by water resources, human health and atmospheric environment

NASA Astrophysics Data System (ADS)

Shen, Jing; Lu, Hongwei; Zhang, Yang; Song, Xinshuang; He, Li

2016-05-01

As ecosystem management is a hotspot and urgent topic with increasing population growth and resource depletion. This paper develops an urban ecosystem vulnerability assessment method representing a new vulnerability paradigm for decision makers and environmental managers, as it's an early warning system to identify and prioritize the undesirable environmental changes in terms of natural, human, economic and social elements. The whole idea is to decompose a complex problem into sub-problem, and analyze each sub-problem, and then aggregate all sub-problems to solve this problem. This method integrates spatial context of Geographic Information System (GIS) tool, multi-criteria decision analysis (MCDA) method, ordered weighted averaging (OWA) operators, and socio-economic elements. Decision makers can find out relevant urban ecosystem vulnerability assessment results with different vulnerable attitude. To test the potential of the vulnerability methodology, it has been applied to a case study area in Beijing, China, where it proved to be reliable and consistent with the Beijing City Master Plan. The results of urban ecosystem vulnerability assessment can support decision makers in evaluating the necessary of taking specific measures to preserve the quality of human health and environmental stressors for a city or multiple cities, with identifying the implications and consequences of their decisions.

Implementation of the analytical hierarchy process with VBA in ArcGIS

NASA Astrophysics Data System (ADS)

Marinoni, Oswald

2004-07-01

Decisions on landuse have become progressively more difficult in the last decades. The main reasons for this development lie in the increasing population combined with an increasing demand for new land and resources and in the growing consciousness for sustainable land and resource use. The steady reduction of valuable land leads to an increase of conflicts in land use decision-making processes since more interests are being affected and therefore more stakeholders with different land use interests and different valuation criteria are being involved in the decision-making process. In the course of such a decision process all identified criteria are weighted according to their relative importance. But assigning weights to the relevant criteria quickly becomes a difficult task when a greater number of criteria are being considered, especially with regard to land use decisions where decision makers expect some kind of mapped result it is therefore useful to use procedures that not only help to derive criteria weights but also accelerate the visualisation and mapping of land use assessment results. Both aspects can easily be facilitated in a GIS. This paper focuses the development of an ArcGIS VBA macro which enables the user to derive criteria weights with the analytical hierarchy process and which allows a mapping of the land use assessment results by a weighted summation of GIS raster data sets. A dynamic link library for the calculation of the eigenvalues and eigenvectors of a square matrix is provided.

Dopaminergic Drug Effects on Probability Weighting during Risky Decision Making

PubMed Central

Timmer, Monique H. M.; ter Huurne, Niels P.

2018-01-01

Abstract Dopamine has been associated with risky decision-making, as well as with pathological gambling, a behavioral addiction characterized by excessive risk-taking behavior. However, the specific mechanisms through which dopamine might act to foster risk-taking and pathological gambling remain elusive. Here we test the hypothesis that this might be achieved, in part, via modulation of subjective probability weighting during decision making. Human healthy controls (n = 21) and pathological gamblers (n = 16) played a decision-making task involving choices between sure monetary options and risky gambles both in the gain and loss domains. Each participant played the task twice, either under placebo or the dopamine D2/D3 receptor antagonist sulpiride, in a double-blind counterbalanced design. A prospect theory modelling approach was used to estimate subjective probability weighting and sensitivity to monetary outcomes. Consistent with prospect theory, we found that participants presented a distortion in the subjective weighting of probabilities, i.e., they overweighted low probabilities and underweighted moderate to high probabilities, both in the gain and loss domains. Compared with placebo, sulpiride attenuated this distortion in the gain domain. Across drugs, the groups did not differ in their probability weighting, although gamblers consistently underweighted losing probabilities in the placebo condition. Overall, our results reveal that dopamine D2/D3 receptor antagonism modulates the subjective weighting of probabilities in the gain domain, in the direction of more objective, economically rational decision making. PMID:29632870

Taking a gamble or playing by the rules: Dissociable prefrontal systems implicated in probabilistic versus deterministic rule-based decisions

PubMed Central

Bhanji, Jamil P.; Beer, Jennifer S.; Bunge, Silvia A.

2014-01-01

A decision may be difficult because complex information processing is required to evaluate choices according to deterministic decision rules and/or because it is not certain which choice will lead to the best outcome in a probabilistic context. Factors that tax decision making such as decision rule complexity and low decision certainty should be disambiguated for a more complete understanding of the decision making process. Previous studies have examined the brain regions that are modulated by decision rule complexity or by decision certainty but have not examined these factors together in the context of a single task or study. In the present functional magnetic resonance imaging study, both decision rule complexity and decision certainty were varied in comparable decision tasks. Further, the level of certainty about which choice to make (choice certainty) was varied separately from certainty about the final outcome resulting from a choice (outcome certainty). Lateral prefrontal cortex, dorsal anterior cingulate cortex, and bilateral anterior insula were modulated by decision rule complexity. Anterior insula was engaged more strongly by low than high choice certainty decisions, whereas ventromedial prefrontal cortex showed the opposite pattern. These regions showed no effect of the independent manipulation of outcome certainty. The results disambiguate the influence of decision rule complexity, choice certainty, and outcome certainty on activity in diverse brain regions that have been implicated in decision making. Lateral prefrontal cortex plays a key role in implementing deterministic decision rules, ventromedial prefrontal cortex in probabilistic rules, and anterior insula in both. PMID:19781652

Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex and Dynamic Conditions

DTIC Science & Technology

2015-07-14

AFRL-OSR-VA-TR-2015-0202 Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex...Computational Modeling of Team Problem Solving for Decision Making Under Complex and Dynamic Conditions 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1...functioning as they solve complex problems, and propose the means to improve the performance of teams, under changing or adversarial conditions. By

Decision theory with resource-bounded agents.

PubMed

Halpern, Joseph Y; Pass, Rafael; Seeman, Lior

2014-04-01

There have been two major lines of research aimed at capturing resource-bounded players in game theory. The first, initiated by Rubinstein (), charges an agent for doing costly computation; the second, initiated by Neyman (), does not charge for computation, but limits the computation that agents can do, typically by modeling agents as finite automata. We review recent work on applying both approaches in the context of decision theory. For the first approach, we take the objects of choice in a decision problem to be Turing machines, and charge players for the "complexity" of the Turing machine chosen (e.g., its running time). This approach can be used to explain well-known phenomena like first-impression-matters biases (i.e., people tend to put more weight on evidence they hear early on) and belief polarization (two people with different prior beliefs, hearing the same evidence, can end up with diametrically opposed conclusions) as the outcomes of quite rational decisions. For the second approach, we model people as finite automata, and provide a simple algorithm that, on a problem that captures a number of settings of interest, provably performs optimally as the number of states in the automaton increases. Copyright © 2014 Cognitive Science Society, Inc.

Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence.

PubMed

Naso, David; Turchiano, Biagio

2005-04-01

In many manufacturing environments, automated guided vehicles are used to move the processed materials between various pickup and delivery points. The assignment of vehicles to unit loads is a complex problem that is often solved in real-time with simple dispatching rules. This paper proposes an automated guided vehicles dispatching approach based on computational intelligence. We adopt a fuzzy multicriteria decision strategy to simultaneously take into account multiple aspects in every dispatching decision. Since the typical short-term view of dispatching rules is one of the main limitations of such real-time assignment heuristics, we also incorporate in the multicriteria algorithm a specific heuristic rule that takes into account the empty-vehicle travel on a longer time-horizon. Moreover, we also adopt a genetic algorithm to tune the weights associated to each decision criteria in the global decision algorithm. The proposed approach is validated by means of a comparison with other dispatching rules, and with other recently proposed multicriteria dispatching strategies also based on computational Intelligence. The analysis of the results obtained by the proposed dispatching approach in both nominal and perturbed operating conditions (congestions, faults) confirms its effectiveness.

Decision-making deficit of a patient with axonal damage after traumatic brain injury.

PubMed

Yasuno, Fumihiko; Matsuoka, Kiwamu; Kitamura, Soichiro; Kiuchi, Kuniaki; Kosaka, Jun; Okada, Koji; Tanaka, Syohei; Shinkai, Takayuki; Taoka, Toshiaki; Kishimoto, Toshifumi

2014-02-01

Patients with traumatic brain injury (TBI) were reported to have difficulty making advantageous decisions, but the underlying deficits of the network of brain areas involved in this process were not directly examined. We report a patient with TBI who demonstrated problematic behavior in situations of risk and complexity after cerebral injury from a traffic accident. The Iowa gambling task (IGT) was used to reveal his deficits in the decision-making process. To examine underlying deficits of the network of brain areas, we examined T1-weighted structural MRI, diffusion tensor imaging (DTI) and Tc-ECD SPECT in this patient. The patient showed abnormality in IGT. DTI-MRI results showed a significant decrease in fractional anisotropy (FA) in the fasciculus between the brain stem and cortical regions via the thalamus. He showed significant decrease in gray matter volumes in the bilateral insular cortex, hypothalamus, and posterior cingulate cortex, possibly reflecting Wallerian degeneration secondary to the fasciculus abnormalities. SPECT showed significant blood flow decrease in the broad cortical areas including the ventromedial prefrontal cortex (VM). Our study showed that the patient had dysfunctional decision-making process. Microstructural abnormality in the fasciculus, likely from the traffic accident, caused reduced afferent feedback to the brain, resulting in less efficient decision-making. Our findings support the somatic-marker hypothesis (SMH), where somatic feedback to the brain influences the decision-making process. Copyright © 2013 Elsevier Inc. All rights reserved.

Decisions about weight management: a synthesis of qualitative studies of obesity.

PubMed

Brown, I; Gould, J

2011-04-01

There is a high non-attendance and dropout attrition from weight management interventions for adults with obesity. Patient dissatisfaction with consultations involving decisions about interventions may be a factor. A systematic review was undertaken of qualitative studies reporting perceptions, experiences, contexts and influences for adults facing, or reflecting on, weight management. The aim was to synthesize a generic model of influences on decision-making about weight management for adult patients. Electronic database and hand searches identified 29 qualitative studies involving 1387 participants (mean age 45.3 years; mean BMI 37.1 kg m(-2) ; 79.9% women). Seven overarching themes were inductively derived from extracted data spanning: cultural identity; social structures such as gender; responses to obesity stigma; previous weight loss experiences; personal motivators and barriers; social support; and practical resources. A model is presented in the paper. Improving decisions about weight management requires attention to how diffuse cultural and psycho-social factors, such as obesity stigma, influence patient choices. Reflection on experiences of previous attempts at weight loss is also essential, as are practical resource factors - particularly for less affluent groups. Considering these factors along with more established theories of individual psychological motivations and barriers may help to improve initial participation and retention within interventions. © 2011 The Authors. Clinical Obesity © 2011 International Association for the Study of Obesity.

Group assessment of key indicators of sustainable waste management in developing countries.

PubMed

Tot, Bojana; Vujić, Goran; Srđević, Zorica; Ubavin, Dejan; Russo, Mário Augusto Tavares

2017-09-01

Decision makers in developing countries are struggling to solve the present problems of solid waste management. Prioritisation and ranking of the most important indicators that influence the waste management system is very useful for any decision maker for the future planning and implementation of a sustainable waste management system. The aim of this study is to evaluate key indicators and their related sub-indicators in a group decision-making environment. In order to gain insight into the subject it was necessary to obtain the qualified opinions of decision makers from different countries who understand the situation in the sector of waste management in developing countries. An assessment is performed by 43 decision makers from both developed and developing countries, and the applied methodology is based on a combined use of the analytic hierarchy process, from the multi-criteria decision-making set of tools, and the preferential voting method known as Borda Count, which belongs to social choice theory. Pairwise comparison of indicators is performed with the analytic hierarchy process, and the ranking of indicators once obtained is assessed with Borda Count. Detailed analysis of the final results showed that the Institutional-Administrative indicator was the most important one, with the maximum weight as derived by both groups of decision makers. The results also showed that the combined use of the analytic hierarchy process and Borda Count contributes to the credibility and objectivity of the decision-making process, allowing its use in more complex waste management group decision-making problems to be recommended.

Differential Weighting for Subcomponent Measures of Integrated Clinical Encounter Scores Based on the USMLE Step 2 CS Examination: Effects on Composite Score Reliability and Pass-Fail Decisions.

PubMed

Park, Yoon Soo; Lineberry, Matthew; Hyderi, Abbas; Bordage, Georges; Xing, Kuan; Yudkowsky, Rachel

2016-11-01

Medical schools administer locally developed graduation competency examinations (GCEs) following the structure of the United States Medical Licensing Examination Step 2 Clinical Skills that combine standardized patient (SP)-based physical examination and the patient note (PN) to create integrated clinical encounter (ICE) scores. This study examines how different subcomponent scoring weights in a locally developed GCE affect composite score reliability and pass-fail decisions for ICE scores, contributing to internal structure and consequential validity evidence. Data from two M4 cohorts (2014: n = 177; 2015: n = 182) were used. The reliability of SP encounter (history taking and physical examination), PN, and communication and interpersonal skills scores were estimated with generalizability studies. Composite score reliability was estimated for varying weight combinations. Faculty were surveyed for preferred weights on the SP encounter and PN scores. Composite scores based on Kane's method were compared with weighted mean scores. Faculty suggested weighting PNs higher (60%-70%) than the SP encounter scores (30%-40%). Statistically, composite score reliability was maximized when PN scores were weighted at 40% to 50%. Composite score reliability of ICE scores increased by up to 0.20 points when SP-history taking (SP-Hx) scores were included; excluding SP-Hx only increased composite score reliability by 0.09 points. Classification accuracy for pass-fail decisions between composite and weighted mean scores was 0.77; misclassification was < 5%. Medical schools and certification agencies should consider implications of assigning weights with respect to composite score reliability and consequences on pass-fail decisions.

Using the weighted area under the net benefit curve for decision curve analysis.

PubMed

Talluri, Rajesh; Shete, Sanjay

2016-07-18

Risk prediction models have been proposed for various diseases and are being improved as new predictors are identified. A major challenge is to determine whether the newly discovered predictors improve risk prediction. Decision curve analysis has been proposed as an alternative to the area under the curve and net reclassification index to evaluate the performance of prediction models in clinical scenarios. The decision curve computed using the net benefit can evaluate the predictive performance of risk models at a given or range of threshold probabilities. However, when the decision curves for 2 competing models cross in the range of interest, it is difficult to identify the best model as there is no readily available summary measure for evaluating the predictive performance. The key deterrent for using simple measures such as the area under the net benefit curve is the assumption that the threshold probabilities are uniformly distributed among patients. We propose a novel measure for performing decision curve analysis. The approach estimates the distribution of threshold probabilities without the need of additional data. Using the estimated distribution of threshold probabilities, the weighted area under the net benefit curve serves as the summary measure to compare risk prediction models in a range of interest. We compared 3 different approaches, the standard method, the area under the net benefit curve, and the weighted area under the net benefit curve. Type 1 error and power comparisons demonstrate that the weighted area under the net benefit curve has higher power compared to the other methods. Several simulation studies are presented to demonstrate the improvement in model comparison using the weighted area under the net benefit curve compared to the standard method. The proposed measure improves decision curve analysis by using the weighted area under the curve and thereby improves the power of the decision curve analysis to compare risk prediction models in a clinical scenario.

Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

PubMed

Dai, Huanping; Micheyl, Christophe

2012-11-01

Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

Incorporating the sampling design in weighting adjustments for panel attrition

PubMed Central

Chen, Qixuan; Gelman, Andrew; Tracy, Melissa; Norris, Fran H.; Galea, Sandro

2015-01-01

We review weighting adjustment methods for panel attrition and suggest approaches for incorporating design variables, such as strata, clusters and baseline sample weights. Design information can typically be included in attrition analysis using multilevel models or decision tree methods such as the CHAID algorithm. We use simulation to show that these weighting approaches can effectively reduce bias in the survey estimates that would occur from omitting the effect of design factors on attrition while keeping the resulted weights stable. We provide a step-by-step illustration on creating weighting adjustments for panel attrition in the Galveston Bay Recovery Study, a survey of residents in a community following a disaster, and provide suggestions to analysts in decision making about weighting approaches. PMID:26239405

Management of complex knowledge in planning for sustainable development: The use of multi-criteria decision aids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kain, Jaan-Henrik; Soederberg, Henriette

2008-01-15

The vision of sustainable development entails new and complex planning situations, confronting local policy makers with changing political conditions, different content in decision making and planning and new working methods. Moreover, the call for sustainable development has been a major driving force towards an increasingly multi-stakeholder planning system. This situation requires competence in working in, and managing, groups of actors, including not only experts and project owners but also other categories of stakeholders. Among other qualities, such competence requires a working strategy aimed at integrating various, and sometimes incommensurable, forms of knowledge to construct a relevant and valid knowledge basemore » prior to decision making. Consequently, there lies great potential in methods that facilitate the evaluation of strategies for infrastructural development across multiple knowledge areas, so-called multi-criteria decision aids (MCDAs). In the present article, observations from six case studies are discussed, where the common denominators are infrastructural planning, multi-stakeholder participation and the use of MCDAs as interactive decision support. Three MCDAs are discussed - NAIADE, SCA and STRAD - with an emphasis on how they function in their procedural context. Accordingly, this is not an analysis of MCDA algorithms, of software programming aspects or of MCDAs as context-independent 'decision machines'-the focus is on MCDAs as actor systems, not as expert systems. The analysis is carried out across four main themes: (a) symmetrical management of different forms of knowledge; (b) management of heterogeneity, pluralism and conflict; (c) functionality and ease of use; and (d) transparency and trust. It shows that STRAD, by far, seems to be the most useful MCDA in interactive settings. NAIADE and SCA are roughly equivalent but have their strengths and weaknesses in different areas. Moreover, it was found that some MCDA issues require further attention, i.e., regarding transparency and understandability; qualitative/quantitative knowledge input; switching between different modes of weighting; software flexibility; as well as graphic and user interfaces.« less

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.

Incorporating patient-preference evidence into regulatory decision making.

PubMed

Ho, Martin P; Gonzalez, Juan Marcos; Lerner, Herbert P; Neuland, Carolyn Y; Whang, Joyce M; McMurry-Heath, Michelle; Hauber, A Brett; Irony, Telba

2015-10-01

Patients have a unique role in deciding what treatments should be available for them and regulatory agencies should take their preferences into account when making treatment approval decisions. This is the first study designed to obtain quantitative patient-preference evidence to inform regulatory approval decisions by the Food and Drug Administration Center for Devices and Radiological Health. Five-hundred and forty United States adults with body mass index (BMI) ≥ 30 kg/m(2) evaluated tradeoffs among effectiveness, safety, and other attributes of weight-loss devices in a scientific survey. Discrete-choice experiments were used to quantify the importance of safety, effectiveness, and other attributes of weight-loss devices to obese respondents. A tool based on these measures is being used to inform benefit-risk assessments for premarket approval of medical devices. Respondent choices yielded preference scores indicating their relative value for attributes of weight-loss devices in this study. We developed a tool to estimate the minimum weight loss acceptable by a patient to receive a device with a given risk profile and the maximum mortality risk tolerable in exchange for a given weight loss. For example, to accept a device with 0.01 % mortality risk, a risk tolerant patient will require about 10 % total body weight loss lasting 5 years. Patient preference evidence was used make regulatory decision making more patient-centered. In addition, we captured the heterogeneity of patient preferences allowing market approval of effective devices for risk tolerant patients. CDRH is using the study tool to define minimum clinical effectiveness to evaluate new weight-loss devices. The methods presented can be applied to a wide variety of medical products. This study supports the ongoing development of a guidance document on incorporating patient preferences into medical-device premarket approval decisions.

Low-frequency sine wave hard-limiting technique

NASA Technical Reports Server (NTRS)

Anderson, T. O.

1977-01-01

Circuit includes serial-in/parallel-out shift register and weighting network that are used to eliminate effects of noise and other nonrepetitive circuit transients. Register and weighting network average decisions from section of signal where decisions are more dependable or where differences between two consecutive samples are larger.

A fuzzy MCDM model with objective and subjective weights for evaluating service quality in hotel industries

NASA Astrophysics Data System (ADS)

Zoraghi, Nima; Amiri, Maghsoud; Talebi, Golnaz; Zowghi, Mahdi

2013-12-01

This paper presents a fuzzy multi-criteria decision-making (FMCDM) model by integrating both subjective and objective weights for ranking and evaluating the service quality in hotels. The objective method selects weights of criteria through mathematical calculation, while the subjective method uses judgments of decision makers. In this paper, we use a combination of weights obtained by both approaches in evaluating service quality in hotel industries. A real case study that considered ranking five hotels is illustrated. Examples are shown to indicate capabilities of the proposed method.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rowe, M.D.; Pierce, B.L.

This report presents results of tests of different final site selection methods used for siting large-scale facilities such as nuclear power plants. Test data are adapted from a nuclear power plant siting study conducted on Long Island, New York. The purpose of the tests is to determine whether or not different final site selection methods produce different results, and to obtain some understanding of the nature of any differences found. Decision rules and weighting methods are included. Decision rules tested are Weighting Summation, Power Law, Decision Analysis, Goal Programming, and Goal Attainment; weighting methods tested are Categorization, Ranking, Rating Ratiomore » Estimation, Metfessel Allocation, Indifferent Tradeoff, Decision Analysis lottery, and Global Evaluation. Results show that different methods can, indeed, produce different results, but that the probability that they will do so is controlled by the structure of differences among the sites being evaluated. Differences in weights and suitability scores attributable to methods have reduced significance if the alternatives include one or two sites that are superior to all others in many attributes. The more tradeoffs there are among good and bad levels of different attributes at different sites, the more important are the specifics of methods to the final decision. 5 refs., 14 figs., 19 tabs.« less

Systems engineering and integration: Cost estimation and benefits analysis

NASA Technical Reports Server (NTRS)

Dean, ED; Fridge, Ernie; Hamaker, Joe

1990-01-01

Space Transportation Avionics hardware and software cost has traditionally been estimated in Phase A and B using cost techniques which predict cost as a function of various cost predictive variables such as weight, lines of code, functions to be performed, quantities of test hardware, quantities of flight hardware, design and development heritage, complexity, etc. The output of such analyses has been life cycle costs, economic benefits and related data. The major objectives of Cost Estimation and Benefits analysis are twofold: (1) to play a role in the evaluation of potential new space transportation avionics technologies, and (2) to benefit from emerging technological innovations. Both aspects of cost estimation and technology are discussed here. The role of cost analysis in the evaluation of potential technologies should be one of offering additional quantitative and qualitative information to aid decision-making. The cost analyses process needs to be fully integrated into the design process in such a way that cost trades, optimizations and sensitivities are understood. Current hardware cost models tend to primarily use weights, functional specifications, quantities, design heritage and complexity as metrics to predict cost. Software models mostly use functionality, volume of code, heritage and complexity as cost descriptive variables. Basic research needs to be initiated to develop metrics more responsive to the trades which are required for future launch vehicle avionics systems. These would include cost estimating capabilities that are sensitive to technological innovations such as improved materials and fabrication processes, computer aided design and manufacturing, self checkout and many others. In addition to basic cost estimating improvements, the process must be sensitive to the fact that no cost estimate can be quoted without also quoting a confidence associated with the estimate. In order to achieve this, better cost risk evaluation techniques are needed as well as improved usage of risk data by decision-makers. More and better ways to display and communicate cost and cost risk to management are required.

Supervised spike-timing-dependent plasticity: a spatiotemporal neuronal learning rule for function approximation and decisions.

PubMed

Franosch, Jan-Moritz P; Urban, Sebastian; van Hemmen, J Leo

2013-12-01

How can an animal learn from experience? How can it train sensors, such as the auditory or tactile system, based on other sensory input such as the visual system? Supervised spike-timing-dependent plasticity (supervised STDP) is a possible answer. Supervised STDP trains one modality using input from another one as "supervisor." Quite complex time-dependent relationships between the senses can be learned. Here we prove that under very general conditions, supervised STDP converges to a stable configuration of synaptic weights leading to a reconstruction of primary sensory input.

Parallel constraint satisfaction in memory-based decisions.

PubMed

Glöckner, Andreas; Hodges, Sara D

2011-01-01

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Bayesian Decision Support for Adaptive Lung Treatments

NASA Astrophysics Data System (ADS)

McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall

2014-03-01

Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827

"Proceedings of the 22nd Aschauer Soiree on Growth and Health Screening", held at Altenhof, Germany, November 15th, 2014.

PubMed

Hermanussen, Michael; Anisimova, Anna; Abmann, Christian; Van Buuren, Stef; Camara, Antonio D; Elhusseini, Mona Abbas; Hassan, Mortada; El-Shabrawi, Mortada Hassan; Godina, Elena Zinovyevna; Gomula, Aleksandra; Groth, Detlef; Koziel, Slawomir; Lieberman, Leslie Sue; Meigen, Christof; Mumm, Rebekka; Nariyama, Koichi; Nowak-Szczepanska, Natalia; Novokmet, Natalija; Satake, Takashi; Scheffler, Christiane; Soderhall, Jani; Suchomlinov, Andrej; Tutkuviene, Janina; Wit, Jan M; Witwer-Backofen, Ursula; Yestrebsky, Cherie Lynn

2015-03-01

Twenty-five scientists met at Aschauhof, Altenhof, Germany, to discuss various aspects of the complex network of modern health screening, focusing on current scientific topics including medical sciences, human biology, and mathematics; on problems in implementing these results at the practical level of physicians, nurses, technicians, and engineers; and the level of administrative and political decisions. Whereas major scientific advancements have been published in the understanding and the bio-statistical evaluation of anthropometric screening parameters such as serial measurements of height and weight for preventive medical check-ups, BMI screening and surveillance in schools, etc., the implementation of these advancements into current health screening concepts, strategies and decision-making is poor. Fear of discrimination, misperception of body image, behavioural responses and political concerns, meanwhile dominate and negatively interfere with the implementation of recent scientific results into public health screening concepts and practices.

Making objective decisions in mechanical engineering problems

NASA Astrophysics Data System (ADS)

Raicu, A.; Oanta, E.; Sabau, A.

2017-08-01

Decision making process has a great influence in the development of a given project, the goal being to select an optimal choice in a given context. Because of its great importance, the decision making was studied using various science methods, finally being conceived the game theory that is considered the background for the science of logical decision making in various fields. The paper presents some basic ideas regarding the game theory in order to offer the necessary information to understand the multiple-criteria decision making (MCDM) problems in engineering. The solution is to transform the multiple-criteria problem in a one-criterion decision problem, using the notion of utility, together with the weighting sum model or the weighting product model. The weighted importance of the criteria is computed using the so-called Step method applied to a relation of preferences between the criteria. Two relevant examples from engineering are also presented. The future directions of research consist of the use of other types of criteria, the development of computer based instruments for decision making general problems and to conceive a software module based on expert system principles to be included in the Wiki software applications for polymeric materials that are already operational.

Differences in fairness and trust between lean and corpulent men.

PubMed

Kubera, B; Klement, J; Wagner, C; Rädel, C; Eggeling, J; Füllbrunn, S; Kaczmarek, M C; Levinsky, R; Peters, A

2016-11-01

Employment disparities are known to exist between lean and corpulent people, for example, corpulent people are less likely to be hired and get lower wages. The reasons for these disparities between weight groups are not completely understood. We hypothesize (i) that economic decision making differs between lean and corpulent subjects, (ii) that these differences are influenced by peoples' blood glucose concentrations and (iii) by the body weight of their opponents. A total of 20 lean and 20 corpulent men were examined, who performed a large set of economic games (ultimatum game, trust game and risk game) under euglycemic and hypoglycemic conditions induced by the glucose clamp technique. In the ultimatum game, lean men made less fair decisions and offered 16% less money than corpulent men during euglycemia (P=0.042). During hypoglycemia, study participants of both weight groups accepted smaller amounts of money than during euglycemia (P=0.031), indicating that a lack of energy makes subjects to behave more like a Homo Economicus. In the trust game, lean men allocated twice as much money to lean than to corpulent trustees during hypoglycemia (P<0.001). Risk-seeking behavior did not differ between lean and corpulent men. Our data show that economic decision making is affected by both, the body weight of the participants and the body weight of their opponents, and that blood glucose concentrations should be taken into consideration when analyzing economic decision making. When relating these results to the working environment, the weight bias in economic decision making may be also relevant for employment disparities.

Application of an integrated multi-criteria decision making AHP-TOPSIS methodology for ETL software selection.

PubMed

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

2016-01-01

Actually, a set of ETL software (Extract, Transform and Load) is available to constitute a major investment market. Each ETL uses its own techniques for extracting, transforming and loading data into data warehouse, which makes the task of evaluating ETL software very difficult. However, choosing the right software of ETL is critical to the success or failure of any Business Intelligence project. As there are many impacting factors in the selection of ETL software, the same process is considered as a complex multi-criteria decision making (MCDM) problem. In this study, an application of decision-making methodology that employs the two well-known MCDM techniques, namely Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods is designed. In this respect, the aim of using AHP is to analyze the structure of the ETL software selection problem and obtain weights of the selected criteria. Then, TOPSIS technique is used to calculate the alternatives' ratings. An example is given to illustrate the proposed methodology. Finally, a software prototype for demonstrating both methods is implemented.

Nurse manager cognitive decision-making amidst stress and work complexity.

PubMed

Shirey, Maria R; Ebright, Patricia R; McDaniel, Anna M

2013-01-01

  The present study provides insight into nurse manager cognitive decision-making amidst stress and work complexity.   Little is known about nurse manager decision-making amidst stress and work complexity. Because nurse manager decisions have the potential to impact patient care quality and safety, understanding their decision-making processes is useful for designing supportive interventions.   This qualitative descriptive study interviewed 21 nurse managers from three hospitals to answer the research question: What decision-making processes do nurse managers utilize to address stressful situations in their nurse manager role? Face-to-face interviews incorporating components of the Critical Decision Method illuminated expert-novice practice differences. Content analysis identified one major theme and three sub-themes.   The present study produced a cognitive model that guides nurse manager decision-making related to stressful situations. Experience in the role, organizational context and situation factors influenced nurse manager cognitive decision-making processes.   Study findings suggest that chronic exposure to stress and work complexity negatively affects nurse manager health and their decision-making processes potentially threatening individual, patient and organizational outcomes.   Cognitive decision-making varies based on nurse manager experience and these differences have coaching and mentoring implications. This present study contributes a current understanding of nurse manager decision-making amidst stress and work complexity. © 2012 Blackwell Publishing Ltd.

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average.

PubMed

Gorsevski, Pece V; Donevska, Katerina R; Mitrovski, Cvetko D; Frizado, Joseph P

2012-02-01

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Autonomy, religion and clinical decisions: findings from a national physician survey.

PubMed

Lawrence, R E; Curlin, F A

2009-04-01

Patient autonomy has been promoted as the most important principle to guide difficult clinical decisions. To examine whether practising physicians indeed value patient autonomy above other considerations, physicians were asked to weight patient autonomy against three other criteria that often influence doctors' decisions. Associations between physicians' religious characteristics and their weighting of the criteria were also examined. Mailed survey in 2007 of a stratified random sample of 1000 US primary care physicians, selected from the American Medical Association masterfile. Physicians were asked how much weight should be given to the following: (1) the patient's expressed wishes and values, (2) the physician's own judgment about what is in the patient's best interest, (3) standards and recommendations from professional medical bodies and (4) moral guidelines from religious traditions. Response rate 51% (446/879). Half of physicians (55%) gave the patient's expressed wishes and values "the highest possible weight". In comparative analysis, 40% gave patient wishes more weight than the other three factors, and 13% ranked patient wishes behind some other factor. Religious doctors tended to give less weight to the patient's expressed wishes. For example, 47% of doctors with high intrinsic religious motivation gave patient wishes the "highest possible weight", versus 67% of those with low (OR 0.5; 95% CI 0.3 to 0.8). Doctors believe patient wishes and values are important, but other considerations are often equally or more important. This suggests that patient autonomy does not guide physicians' decisions as much as is often recommended in the ethics literature.

Complexity Science: A Mechanism for Strategic Foresight and Resiliency in National Security Decision-Making.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ackermann, Mark R.; Hayden, Nancy Kay; Backus, George A.

Most national policy decisions are complex with a variety of stakeholders, disparate interests and the potential for unintended consequences. While a number of analytical tools exist to help decision makers sort through the mountains of data and myriad of options, decision support teams are increasingly turning to complexity science for improved analysis and better insight into the potential impact of policy decisions. While complexity science has great potential, it has only proven useful in limited case s and when properly applied. In advance of more widespread use, a national - level effort to refine complexity science and more rigorously establishmore » its technical underpinnings is recommended.« less

Effects of trial complexity on decision making.

PubMed

Horowitz, I A; ForsterLee, L; Brolly, I

1996-12-01

The ability of a civil jury to render fair and rational decisions in complex trials has been questioned. However, the nature, dimensions, and effects of trial complexity on decision making have rarely been addressed. In this research, jury-eligible adults saw a videotape of a complex civil trial that varied in information load and complexity of the language of the witnesses. Information load and complexity differentially affected liability and compensatory decisions. An increase in the number of plaintiffs decreased blameworthiness assigned to the defendant despite contrary evidence and amount of probative evidence processed. Complex language did not affect memory but did affect jurors' ability to appropriately compensate differentially worthy plaintiffs. Jurors assigned compensatory awards commensurate with the plaintiffs' injuries only under low-load and less complex language conditions.

Exploring multicriteria decision strategies in GIS with linguistic quantifiers: A case study of residential quality evaluation

NASA Astrophysics Data System (ADS)

Malczewski, Jacek; Rinner, Claus

2005-06-01

Commonly used GIS combination operators such as Boolean conjunction/disjunction and weighted linear combination can be generalized to the ordered weighted averaging (OWA) family of operators. This multicriteria evaluation method allows decision-makers to define a decision strategy on a continuum between pessimistic and optimistic strategies. Recently, OWA has been introduced to GIS-based decision support systems. We propose to extend a previous implementation of OWA with linguistic quantifiers to simplify the definition of decision strategies and to facilitate an exploratory analysis of multiple criteria. The linguistic quantifier-guided OWA procedure is illustrated using a dataset for evaluating residential quality of neighborhoods in London, Ontario.

Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

PubMed Central

Alguliyev, Rasim M.; Aliguliyev, Ramiz M.; Mahmudova, Rasmiyya S.

2015-01-01

Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method. PMID:26516634

Pythagorean fuzzy analytic hierarchy process to multi-criteria decision making

NASA Astrophysics Data System (ADS)

Mohd, Wan Rosanisah Wan; Abdullah, Lazim

2017-11-01

A numerous approaches have been proposed in the literature to determine the criteria of weight. The weight of criteria is very significant in the process of decision making. One of the outstanding approaches that used to determine weight of criteria is analytic hierarchy process (AHP). This method involves decision makers (DMs) to evaluate the decision to form the pair-wise comparison between criteria and alternatives. In classical AHP, the linguistic variable of pairwise comparison is presented in terms of crisp value. However, this method is not appropriate to present the real situation of the problems because it involved the uncertainty in linguistic judgment. For this reason, AHP has been extended by incorporating the Pythagorean fuzzy sets. In addition, no one has found in the literature proposed how to determine the weight of criteria using AHP under Pythagorean fuzzy sets. In order to solve the MCDM problem, the Pythagorean fuzzy analytic hierarchy process is proposed to determine the criteria weight of the evaluation criteria. Using the linguistic variables, pairwise comparison for evaluation criteria are made to the weights of criteria using Pythagorean fuzzy numbers (PFNs). The proposed method is implemented in the evaluation problem in order to demonstrate its applicability. This study shows that the proposed method provides us with a useful way and a new direction in solving MCDM problems with Pythagorean fuzzy context.

Social Influences in Sequential Decision Making

PubMed Central

Schöbel, Markus; Rieskamp, Jörg; Huber, Rafael

2016-01-01

People often make decisions in a social environment. The present work examines social influence on people’s decisions in a sequential decision-making situation. In the first experimental study, we implemented an information cascade paradigm, illustrating that people infer information from decisions of others and use this information to make their own decisions. We followed a cognitive modeling approach to elicit the weight people give to social as compared to private individual information. The proposed social influence model shows that participants overweight their own private information relative to social information, contrary to the normative Bayesian account. In our second study, we embedded the abstract decision problem of Study 1 in a medical decision-making problem. We examined whether in a medical situation people also take others’ authority into account in addition to the information that their decisions convey. The social influence model illustrates that people weight social information differentially according to the authority of other decision makers. The influence of authority was strongest when an authority's decision contrasted with private information. Both studies illustrate how the social environment provides sources of information that people integrate differently for their decisions. PMID:26784448

Social Influences in Sequential Decision Making.

PubMed

Schöbel, Markus; Rieskamp, Jörg; Huber, Rafael

2016-01-01

People often make decisions in a social environment. The present work examines social influence on people's decisions in a sequential decision-making situation. In the first experimental study, we implemented an information cascade paradigm, illustrating that people infer information from decisions of others and use this information to make their own decisions. We followed a cognitive modeling approach to elicit the weight people give to social as compared to private individual information. The proposed social influence model shows that participants overweight their own private information relative to social information, contrary to the normative Bayesian account. In our second study, we embedded the abstract decision problem of Study 1 in a medical decision-making problem. We examined whether in a medical situation people also take others' authority into account in addition to the information that their decisions convey. The social influence model illustrates that people weight social information differentially according to the authority of other decision makers. The influence of authority was strongest when an authority's decision contrasted with private information. Both studies illustrate how the social environment provides sources of information that people integrate differently for their decisions.

Automated Surgical Approach Planning for Complex Skull Base Targets: Development and Validation of a Cost Function and Semantic At-las.

PubMed

Aghdasi, Nava; Whipple, Mark; Humphreys, Ian M; Moe, Kris S; Hannaford, Blake; Bly, Randall A

2018-06-01

Successful multidisciplinary treatment of skull base pathology requires precise preoperative planning. Current surgical approach (pathway) selection for these complex procedures depends on an individual surgeon's experiences and background training. Because of anatomical variation in both normal tissue and pathology (eg, tumor), a successful surgical pathway used on one patient is not necessarily the best approach on another patient. The question is how to define and obtain optimized patient-specific surgical approach pathways? In this article, we demonstrate that the surgeon's knowledge and decision making in preoperative planning can be modeled by a multiobjective cost function in a retrospective analysis of actual complex skull base cases. Two different approaches- weighted-sum approach and Pareto optimality-were used with a defined cost function to derive optimized surgical pathways based on preoperative computed tomography (CT) scans and manually designated pathology. With the first method, surgeon's preferences were input as a set of weights for each objective before the search. In the second approach, the surgeon's preferences were used to select a surgical pathway from the computed Pareto optimal set. Using preoperative CT and magnetic resonance imaging, the patient-specific surgical pathways derived by these methods were similar (85% agreement) to the actual approaches performed on patients. In one case where the actual surgical approach was different, revision surgery was required and was performed utilizing the computationally derived approach pathway.

Prospective Analysis of Decision Making During Joint Cardiology Cardiothoracic Conference in Treatment of 107 Consecutive Children with Congenital Heart Disease.

PubMed

Duignan, Sophie; Ryan, Aedin; O'Keeffe, Dara; Kenny, Damien; McMahon, Colin J

2018-05-12

The complexity and potential biases involved in decision making have long been recognised and examined in both the aviation and business industries. More recently, the medical community have started to explore this concept and its particular importance in our field. Paediatric cardiology is a rapidly expanding field and for many of the conditions we treat, there is limited evidence available to support our decision-making. Variability exists within decision-making in paediatric cardiology and this may influence outcomes. There are no validated tools available to support and examine consistent decision-making for various treatment strategies in children with congenital heart disease in a multidisciplinary cardiology and cardiothoracic institution. Our primary objective was to analyse the complexity of decision-making for children with cardiac conditions in the context of our joint cardiology and cardiothoracic conference (JCC). Two paediatric cardiologists acted as investigators by observing the weekly joint cardiology-cardiothoracic surgery conference and prospectively evaluating the degree of complexity of decision-making in the management of 107 sequential children with congenital heart disease discussed. Additionally, the group consensus on the same patients was prospectively assessed to compare this to the independent observers. Of 107 consecutive children discussed at our JCC conference 32 (27%) went on to receive surgical intervention, 20 (17%) underwent catheterisation and 65 (56%) received medical treatment. There were 53 (50%) cases rated as simple by one senior observer, while 54 (50%) were rated as complex to some degree. There was high inter-observer agreement with a Krippendorff's alpha of ≥ 0.8 between 2 observers and between 2 observers and the group consensus as a whole for grading of the complexity of decision-making. Different decisions were occasionally made on patients with the same data set. Discussions revisiting the same patient, in complex cases, resulted in different management decisions being reached in this series. Anchoring of decision-making was witnessed in certain cases. Potential application of decision making algorithms is discussed in making decisions in paediatric cardiology patients. Decision-making in our institution's joint cardiology-cardiothoracic conference proved to be complex in approximately half of our patients. Inconsistency in decision-making for patients with the same diagnosis, and different decisions made for the same complex patient at different time points confounds the reliability of the decision-making process. These novel data highlight the absence of evidence-based medicine for many decisions, occasional lack of consistency and the impact of anchoring, heuristics and other biases in complex cases. Validated decision-making algorithms may assist in providing consistency to decision-making in this setting.

75 FR 17605 - Federal Motor Vehicle Safety Standards; Roof Crush Resistance

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-07

...-weight ratio requirement to heavier light vehicles, i.e., ones with a gross vehicle weight rating greater... of that decision as well as the agency's decision not to adopt a dynamic rollover test requirement as.... Petitioner's Claim That Quasi-Static Test and Criteria Do Not Reasonably Differentiate Between the Injury...

A Decision Support System for Solving Multiple Criteria Optimization Problems

ERIC Educational Resources Information Center

Filatovas, Ernestas; Kurasova, Olga

2011-01-01

In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria…

A Core Journal Decision Model Based on Weighted Page Rank

ERIC Educational Resources Information Center

Wang, Hei-Chia; Chou, Ya-lin; Guo, Jiunn-Liang

2011-01-01

Purpose: The paper's aim is to propose a core journal decision method, called the local impact factor (LIF), which can evaluate the requirements of the local user community by combining both the access rate and the weighted impact factor, and by tracking citation information on the local users' articles. Design/methodology/approach: Many…

Utility of Policy Capturing as an Approach to Graduate Admissions Decision Making.

ERIC Educational Resources Information Center

Schmidt, Frank L.; And Others

1978-01-01

The present study examined and evaluated the application of linear policy-capturing models to the real-world decision task of graduate admissions. Utility of the policy-capturing models was great enough to be of practical significance, and least-squares weights showed no predictive advantage over equal weights. (Author/CTM)

A decision analysis approach for risk management of near-earth objects

NASA Astrophysics Data System (ADS)

Lee, Robert C.; Jones, Thomas D.; Chapman, Clark R.

2014-10-01

Risk management of near-Earth objects (NEOs; e.g., asteroids and comets) that can potentially impact Earth is an important issue that took on added urgency with the Chelyabinsk event of February 2013. Thousands of NEOs large enough to cause substantial damage are known to exist, although only a small fraction of these have the potential to impact Earth in the next few centuries. The probability and location of a NEO impact are subject to complex physics and great uncertainty, and consequences can range from minimal to devastating, depending upon the size of the NEO and location of impact. Deflecting a potential NEO impactor would be complex and expensive, and inter-agency and international cooperation would be necessary. Such deflection campaigns may be risky in themselves, and mission failure may result in unintended consequences. The benefits, risks, and costs of different potential NEO risk management strategies have not been compared in a systematic fashion. We present a decision analysis framework addressing this hazard. Decision analysis is the science of informing difficult decisions. It is inherently multi-disciplinary, especially with regard to managing catastrophic risks. Note that risk analysis clarifies the nature and magnitude of risks, whereas decision analysis guides rational risk management. Decision analysis can be used to inform strategic, policy, or resource allocation decisions. First, a problem is defined, including the decision situation and context. Second, objectives are defined, based upon what the different decision-makers and stakeholders (i.e., participants in the decision) value as important. Third, quantitative measures or scales for the objectives are determined. Fourth, alternative choices or strategies are defined. Fifth, the problem is then quantitatively modeled, including probabilistic risk analysis, and the alternatives are ranked in terms of how well they satisfy the objectives. Sixth, sensitivity analyses are performed in order to examine the impact of uncertainties. Finally, the need for further analysis, data collection, or refinement is determined. The first steps of defining the problem and the objectives are critical to constructing an informative decision analysis. Such steps must be undertaken with participation from experts, decision-makers, and stakeholders (defined here as "decision participants"). The basic problem here can be framed as: “What is the best strategy to manage risk associated with NEOs?” Some high-level objectives might be to minimize: mortality and injuries, damage to critical infrastructure (e.g., power, communications and food distribution), ecosystem damage, property damage, ungrounded media and public speculation, resources expended, and overall cost. Another valuable objective would be to maximize inter-agency/government coordination. Some of these objectives (e.g., “minimize mortality”) are readily quantified (e.g., deaths and injuries averted). Others are less so (e.g., “maximize inter-agency/government coordination”), but these can be scaled. Objectives may be inversely related: e.g., a strategy that minimizes mortality may cost more. They are also unlikely to be weighted equally. Defining objectives and assessing their relative weight and interactions requires early engagement with decision participants. High-level decisions include whether to deflect a NEO, when to deflect, what is the best alternative for deflection/destruction, and disaster management strategies if an impact occurs. Important influences include, for example: NEO characteristics (orbital characteristics, diameter, mass, spin and composition), impact probability and location, interval between discovery and projected impact date, interval between discovery and deflection target date, costs of information collection, costs and technological feasibility of deflection alternatives, risks of deflection campaigns, requirements for inter-agency and international cooperation, and timing of informing the public. The analytical aspects of decision analysis center on estimation of the expected value (i.e. utility) of different alternatives. The expected value of an alternative is a function of the probability-weighted consequences, estimated using Bayesian calculations in a decision tree or influence diagram model. The result is a set of expected-value estimates for all alternatives evaluated that enables a ranking; the higher the expected value, the more preferred the alternative. A common way to include resource limitations is by framing the decision analysis in the context of economics (e.g., cost-effectiveness analysis). An important aspect of decision analysis in the NEO risk management case is the ability, known as sensitivity analysis, to examine the effect of parameter uncertainty upon decisions. The simplest way to evaluate uncertainty associated with the information used in a decision analysis is to adjust the input values one at a time (or simultaneously) to examine how the results change. Monte Carlo simulations can be used to adjust the inputs over ranges or distributions of values; statistical means then are used to determine the most influential variables. These techniques yield a measure known as the expected value of imperfect information. This value is highly informative, because it allows the decision-maker with imperfect information to evaluate the impact of using experiments, tests, or data collection (e.g. Earth-based observations, space-based remote sensing, etc.) to refine judgments; and indeed to estimate how much should be spent to reduce uncertainty.

Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

PubMed

Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H

2015-11-30

Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients.

Middle-aged women's decisions about body weight management: needs assessment and testing of a knowledge translation tool.

PubMed

Stacey, Dawn; Jull, Janet; Beach, Sarah; Dumas, Alex; Strychar, Irene; Adamo, Kristi; Brochu, Martin; Prud'homme, Denis

2015-04-01

This study aims to assess middle-aged women's needs when making body weight management decisions and to evaluate a knowledge translation tool for addressing their needs. A mixed-methods study used an interview-guided theory-based survey of professional women aged 40 to 65 years. The tool summarized evidence to address their needs and enabled women to monitor actions taken. Acceptability and usability were reported descriptively. Sixty female participants had a mean body mass index of 28.0 kg/m(2) (range, 17.0-44.9 kg/m(2)), and half were premenopausal. Common options for losing (82%) or maintaining (18%) weight included increasing physical activity (60%), eating healthier (57%), and getting support (40%). Decision-making involved getting information on options (52%), soliciting others' decisions/advice (20%), and being self-motivated (20%). Preferred information sources included written information (97%), counseling (90%), and social networking websites (43%). Five professionals (dietitian, personal trainer, occupational therapist, and two physicians) had similar responses. Of 53 women sent the tool, 27 provided acceptability feedback. They rated it as good to excellent for information on menopause (96%), body weight changes (85%), and managing body weight (85%). Most would tell others about it (81%). After 4 weeks of use, 25 women reported that the wording made sense (96%) and that the tool had clear instructions (92%) and was easy to use across time (88%). The amount of information was rated as just right (64%), but the tool had limited space for responding (72%). When making decisions about body weight management, women's needs were "getting information" and "getting support." The knowledge translation tool was acceptable and usable, but further evaluation is required.

Middle-aged women’s decisions about body weight management: needs assessment and testing of a knowledge translation tool

PubMed Central

Stacey, Dawn; Jull, Janet; Beach, Sarah; Dumas, Alex; Strychar, Irene; Adamo, Kristi; Brochu, Martin; Prud’homme, Denis

2015-01-01

Abstract Objective This study aims to assess middle-aged women’s needs when making body weight management decisions and to evaluate a knowledge translation tool for addressing their needs. Methods A mixed-methods study used an interview-guided theory-based survey of professional women aged 40 to 65 years. The tool summarized evidence to address their needs and enabled women to monitor actions taken. Acceptability and usability were reported descriptively. Results Sixty female participants had a mean body mass index of 28.0 kg/m2 (range, 17.0-44.9 kg/m2), and half were premenopausal. Common options for losing (82%) or maintaining (18%) weight included increasing physical activity (60%), eating healthier (57%), and getting support (40%). Decision-making involved getting information on options (52%), soliciting others’ decisions/advice (20%), and being self-motivated (20%). Preferred information sources included written information (97%), counseling (90%), and social networking websites (43%). Five professionals (dietitian, personal trainer, occupational therapist, and two physicians) had similar responses. Of 53 women sent the tool, 27 provided acceptability feedback. They rated it as good to excellent for information on menopause (96%), body weight changes (85%), and managing body weight (85%). Most would tell others about it (81%). After 4 weeks of use, 25 women reported that the wording made sense (96%) and that the tool had clear instructions (92%) and was easy to use across time (88%). The amount of information was rated as just right (64%), but the tool had limited space for responding (72%). Conclusions When making decisions about body weight management, women’s needs were “getting information” and “getting support.” The knowledge translation tool was acceptable and usable, but further evaluation is required. PMID:25816120

Breast or bottle? Eating disordered childbearing women and infant-feeding decisions.

PubMed

Stapleton, Helen; Fielder, Anna; Kirkham, Mavis

2008-04-01

Debates about infant-feeding methods have intensified in recent years with increasing pressures on women living in industrialized nations to breastfeed their infants. This paper, based on a qualitative study of 16 childbearing women with a pre-existing eating disorder living in the north of England, examines participants' motivations for, and understandings of, infant-feeding decisions and practices. In this study, a small number of participants reported being 'desperate' to formula feed in order to resume practices underpinning their eating disorder and thereby to shed the weight accumulated during pregnancy. These participants anticipated an early return to restrictive eating, heavy exercise regimes and/or bingeing/purging behaviours. Most participants, however, reported being 'desperate' to breastfeed because this implied 'good' mothering and prolonged the time during which they could consume 'naughty' treats. Women who opted to breastfeed generally believed this would accelerate weight loss. This study contributes to research on the subjective experiences of a particular group of women living with chronic illnesses and problematic relationships with their bodies. Negotiating individual transitions to motherhood required participants to confront their own, often longstanding, disrupted eating patterns and to make important decisions about infant-feeding methods. Findings from this study raise questions about some of the assumptions underpinning infant-feeding activities and articulate some of the complexities surrounding these issues. By highlighting ways in which women may compromise their own well-being by prioritizing their baby's needs, for example by persisting with breastfeeding when they were 'desperate' to re-engage with their disordered eating practices, an individualized cost-benefit framing is outlined.

Optimizing Decision Preparedness by Adapting Scenario Complexity and Automating Scenario Generation

NASA Technical Reports Server (NTRS)

Dunne, Rob; Schatz, Sae; Flore, Stephen M.; Nicholson, Denise

2011-01-01

Klein's recognition-primed decision (RPD) framework proposes that experts make decisions by recognizing similarities between current decision situations and previous decision experiences. Unfortunately, military personnel arQ often presented with situations that they have not experienced before. Scenario-based training (S8T) can help mitigate this gap. However, SBT remains a challenging and inefficient training approach. To address these limitations, the authors present an innovative formulation of scenario complexity that contributes to the larger research goal of developing an automated scenario generation system. This system will enable trainees to effectively advance through a variety of increasingly complex decision situations and experiences. By adapting scenario complexities and automating generation, trainees will be provided with a greater variety of appropriately calibrated training events, thus broadening their repositories of experience. Preliminary results from empirical testing (N=24) of the proof-of-concept formula are presented, and future avenues of scenario complexity research are also discussed.

Body Weight Can Change How Your Emotions Are Perceived

PubMed Central

2016-01-01

Accurately interpreting other’s emotions through facial expressions has important adaptive values for social interactions. However, due to the stereotypical social perception of overweight individuals as carefree, humorous, and light-hearted, the body weight of those with whom we interact may have a systematic influence on our emotion judgment even though it has no relevance to the expressed emotion itself. In this experimental study, we examined the role of body weight in faces on the affective perception of facial expressions. We hypothesized that the weight perceived in a face would bias the assessment of an emotional expression, with overweight faces generally more likely to be perceived as having more positive and less negative expressions than healthy weight faces. Using two-alternative forced-choice perceptual decision tasks, participants were asked to sort the emotional expressions of overweight and healthy weight facial stimuli that had been gradually morphed across six emotional intensity levels into one of two categories—“neutral vs. happy” (Experiment 1) and “neutral vs. sad” (Experiment 2). As predicted, our results demonstrated that overweight faces were more likely to be categorized as happy (i.e., lower happy decision threshold) and less likely to be categorized as sad (i.e., higher sad decision threshold) compared to healthy weight faces that had the same levels of emotional intensity. The neutral-sad decision threshold shift was negatively correlated with participant’s own fear of becoming fat, that is, those without a fear of becoming fat more strongly perceived overweight faces as sad relative to those with a higher fear. These findings demonstrate that the weight of the face systematically influences how its emotional expression is interpreted, suggesting that being overweight may make emotional expressions appear more happy and less sad than they really are. PMID:27870892

Body Weight Can Change How Your Emotions Are Perceived.

PubMed

Oh, Yujung; Hass, Norah C; Lim, Seung-Lark

2016-01-01

Accurately interpreting other's emotions through facial expressions has important adaptive values for social interactions. However, due to the stereotypical social perception of overweight individuals as carefree, humorous, and light-hearted, the body weight of those with whom we interact may have a systematic influence on our emotion judgment even though it has no relevance to the expressed emotion itself. In this experimental study, we examined the role of body weight in faces on the affective perception of facial expressions. We hypothesized that the weight perceived in a face would bias the assessment of an emotional expression, with overweight faces generally more likely to be perceived as having more positive and less negative expressions than healthy weight faces. Using two-alternative forced-choice perceptual decision tasks, participants were asked to sort the emotional expressions of overweight and healthy weight facial stimuli that had been gradually morphed across six emotional intensity levels into one of two categories-"neutral vs. happy" (Experiment 1) and "neutral vs. sad" (Experiment 2). As predicted, our results demonstrated that overweight faces were more likely to be categorized as happy (i.e., lower happy decision threshold) and less likely to be categorized as sad (i.e., higher sad decision threshold) compared to healthy weight faces that had the same levels of emotional intensity. The neutral-sad decision threshold shift was negatively correlated with participant's own fear of becoming fat, that is, those without a fear of becoming fat more strongly perceived overweight faces as sad relative to those with a higher fear. These findings demonstrate that the weight of the face systematically influences how its emotional expression is interpreted, suggesting that being overweight may make emotional expressions appear more happy and less sad than they really are.

Multivariate analysis of flow cytometric data using decision trees.

PubMed

Simon, Svenja; Guthke, Reinhard; Kamradt, Thomas; Frey, Oliver

2012-01-01

Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens. For research on the host site, flow cytometry has become one of the major tools in immunology. Advances in technology and reagents allow now the simultaneous assessment of multiple markers on a single cell level generating multidimensional data sets that require multivariate statistical analysis. We explored the explanatory power of the supervised machine learning method called "induction of decision trees" in flow cytometric data. In order to examine whether the production of a certain cytokine is depended on other cytokines, datasets from intracellular staining for six cytokines with complex patterns of co-expression were analyzed by induction of decision trees. After weighting the data according to their class probabilities, we created a total of 13,392 different decision trees for each given cytokine with different parameter settings. For a more realistic estimation of the decision trees' quality, we used stratified fivefold cross validation and chose the "best" tree according to a combination of different quality criteria. While some of the decision trees reflected previously known co-expression patterns, we found that the expression of some cytokines was not only dependent on the co-expression of others per se, but was also dependent on the intensity of expression. Thus, for the first time we successfully used induction of decision trees for the analysis of high dimensional flow cytometric data and demonstrated the feasibility of this method to reveal structural patterns in such data sets.

Bayesian outcome-based strategy classification.

PubMed

Lee, Michael D

2016-03-01

Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014) recently developed a method for making inferences about the decision processes people use in multi-attribute forced choice tasks. Their paper makes a number of worthwhile theoretical and methodological contributions. Theoretically, they provide an insightful psychological motivation for a probabilistic extension of the widely-used "weighted additive" (WADD) model, and show how this model, as well as other important models like "take-the-best" (TTB), can and should be expressed in terms of meaningful priors. Methodologically, they develop an inference approach based on the Minimum Description Length (MDL) principles that balances both the goodness-of-fit and complexity of the decision models they consider. This paper aims to preserve these useful contributions, but provide a complementary Bayesian approach with some theoretical and methodological advantages. We develop a simple graphical model, implemented in JAGS, that allows for fully Bayesian inferences about which models people use to make decisions. To demonstrate the Bayesian approach, we apply it to the models and data considered by Hilbig and Moshagen (Psychonomic Bulletin & Review, 21, 1431-1443, 2014), showing how a prior predictive analysis of the models, and posterior inferences about which models people use and the parameter settings at which they use them, can contribute to our understanding of human decision making.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

PubMed

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection.

PubMed

Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang

2018-01-15

In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes' (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10 -5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.

GIS-based integrated assessment and decision support system for land use planning in consideration of carbon sequestration benefits

NASA Astrophysics Data System (ADS)

Wang, Jun; Chen, J. M.; Li, Manchun; Ju, Weimin

2007-06-01

As the major eligible land use activities in the Clean Development Mechanism (CDM), afforestation and reforestation offer opportunities and potential economic benefits for developing countries to participate in carbon-trade in the potential international carbon (C) sink markets. However, the design and selection of appropriate afforestation and reforestation locations in CDM are complex processes which need integrated assessment (IA) of C sequestration (CS) potential, environmental effects, and socio-economic impacts. This paper promotes the consideration of CS benefits in local land use planning and presents a GIS-based integrated assessment and spatial decision support system (IA-SDSS) to support decision-making on 'where' and 'how' to afforest. It integrates an Integrated Terrestrial Ecosystem Carbon Model (InTEC) and a GIS platform for modeling regional long-term CS potential and assessment of geo-referenced land use criteria including CS consequence, and produces ranking of plantation schemes with different tree species using the Analytic hierarchy process (AHP) method. Three land use scenarios are investigated: (i) traditional land use planning criteria without C benefits, (ii) land use for CS with low C price, and (iii) land use for CS with high price. Different scenarios and consequences will influence the weights of tree-species selection in the AHP decision process.

Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping

NASA Astrophysics Data System (ADS)

Yousefi, Mahyar; Carranza, Emmanuel John M.

2015-01-01

Complexities of geological processes portrayed as certain feature in a map (e.g., faults) are natural sources of uncertainties in decision-making for exploration of mineral deposits. Besides natural sources of uncertainties, knowledge-driven (e.g., fuzzy logic) mineral prospectivity mapping (MPM) is also plagued and incurs further uncertainty in subjective judgment of analyst when there is no reliable proven value of evidential scores corresponding to relative importance of geological features that can directly be measured. In this regard, analysts apply expert opinion to assess relative importance of spatial evidences as meaningful decision support. This paper aims for fuzzification of continuous spatial data used as proxy evidence to facilitate and to support fuzzy MPM to generate exploration target areas for further examination of undiscovered deposits. In addition, this paper proposes to adapt the concept of expected value to further improve fuzzy logic MPM because the analysis of uncertain variables can be presented in terms of their expected value. The proposed modified expected value approach to MPM is not only a multi-criteria approach but it also treats uncertainty of geological processes a depicted by maps or spatial data in term of biased weighting more realistically in comparison with classified evidential maps because fuzzy membership scores are defined continuously whereby, for example, there is no need to categorize distances from evidential features to proximity classes using arbitrary intervals. The proposed continuous weighting approach and then integrating the weighted evidence layers by using modified expected value function, described in this paper can be used efficiently in either greenfields or brownfields.

Estimating Classification Accuracy for Complex Decision Rules Based on Multiple Scores

ERIC Educational Resources Information Center

Douglas, Karen M.; Mislevy, Robert J.

2010-01-01

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

Identification of the Criteria for Decision Making of Cut-Away Peatland Reuse

NASA Astrophysics Data System (ADS)

Padur, Kadi; Ilomets, Mati; Põder, Tõnis

2017-03-01

The total area of abandoned milled peatlands which need to be rehabilitated for sustainable land-use is nearly 10,000 ha in Estonia. According to the agreement between Estonia and the European Union, Estonia has to create suitable conditions for restoration of 2000 ha of abandoned cut-away peatlands by 2023. The decisions on rehabilitation of abandoned milled peatlands have so far relied on a limited knowledgebase with unestablished methodologies, thus the decision making process needs a significant improvement. This study aims to improve the methodology by identifying the criteria for optimal decision making to ensure sustainable land use planning after peat extraction. Therefore relevant environmental, social and economic restrictive and weighted comparison criteria, which assess reuse alternatives suitability for achieving the goal, is developed in cooperation with stakeholders. Restrictive criteria are arranged into a decision tree to help to determine the implementable reuse alternatives in various situations. Weighted comparison criteria are developed in cooperation with stakeholders to rank the reuse alternatives. The comparison criteria are organised hierarchically into a value tree. In the situation, where the selection of a suitable rehabilitation alternative for a specific milled peatland is going to be made, the weighted comparison criteria values need to be identified and the presented approach supports the optimal and transparent decision making. In addition to Estonian context the general results of the study could also be applied to a cut-away peatlands in other regions with need-based site-dependent modifications of criteria values and weights.

Identification of the Criteria for Decision Making of Cut-Away Peatland Reuse.

PubMed

Padur, Kadi; Ilomets, Mati; Põder, Tõnis

2017-03-01

The total area of abandoned milled peatlands which need to be rehabilitated for sustainable land-use is nearly 10,000 ha in Estonia. According to the agreement between Estonia and the European Union, Estonia has to create suitable conditions for restoration of 2000 ha of abandoned cut-away peatlands by 2023. The decisions on rehabilitation of abandoned milled peatlands have so far relied on a limited knowledgebase with unestablished methodologies, thus the decision making process needs a significant improvement. This study aims to improve the methodology by identifying the criteria for optimal decision making to ensure sustainable land use planning after peat extraction. Therefore relevant environmental, social and economic restrictive and weighted comparison criteria, which assess reuse alternatives suitability for achieving the goal, is developed in cooperation with stakeholders. Restrictive criteria are arranged into a decision tree to help to determine the implementable reuse alternatives in various situations. Weighted comparison criteria are developed in cooperation with stakeholders to rank the reuse alternatives. The comparison criteria are organised hierarchically into a value tree. In the situation, where the selection of a suitable rehabilitation alternative for a specific milled peatland is going to be made, the weighted comparison criteria values need to be identified and the presented approach supports the optimal and transparent decision making. In addition to Estonian context the general results of the study could also be applied to a cut-away peatlands in other regions with need-based site-dependent modifications of criteria values and weights.

Should I go with my gut? Investigating the benefits of emotion-focused decision making.

PubMed

Mikels, Joseph A; Maglio, Sam J; Reed, Andrew E; Kaplowitz, Lee J

2011-08-01

Deliberative decision strategies have historically been considered the surest path to sound decisions; however, recent evidence and theory suggest that affective strategies may be equally as effective. In four experiments we examined conditions under which affective versus deliberative decision strategies might result in higher decision quality. While consciously focusing on feelings versus details, participants made choices that varied in complexity, in extent of subsequent conscious deliberation allowed, and in domain. Results indicate that focusing on feelings versus details led to superior objective and subjective decision quality for complex decisions. However, when using a feeling-focused approach, subsequent deliberation after encoding resulted in reduced choice quality. These results suggest that affective decision strategies may be more effective relative to deliberative strategies for certain complex decisions. 2011 APA, all rights reserved

Rank Weighting in Multiattribute Utility Decision Making: Avoiding the Pitfalls of Equal Weights.

DTIC Science & Technology

1979-09-01

set change are discussed in relation to the conditions of Wainer’s (Wainer, 1976) ’ equal weights theorem’ and the resulting sensitivity to weighting of...as equal weights. Rank weighting of importance dimensions demonstrate marked improvement of approximation as reflected in both Pearson and rank order

Possibility-induced simplified neutrosophic aggregation operators and their application to multi-criteria group decision-making

NASA Astrophysics Data System (ADS)

Şahin, Rıdvan; Liu, Peide

2017-07-01

Simplified neutrosophic set (SNS) is an appropriate tool used to express the incompleteness, indeterminacy and uncertainty of the evaluation objects in decision-making process. In this study, we define the concept of possibility SNS including two types of information such as the neutrosophic performance provided from the evaluation objects and its possibility degree using a value ranging from zero to one. Then by extending the existing neutrosophic information, aggregation models for SNSs that cannot be used effectively to fusion the two different information described above, we propose two novel neutrosophic aggregation operators considering possibility, which are named as a possibility-induced simplified neutrosophic weighted arithmetic averaging operator and possibility-induced simplified neutrosophic weighted geometric averaging operator, and discuss their properties. Moreover, we develop a useful method based on the proposed aggregation operators for solving a multi-criteria group decision-making problem with the possibility simplified neutrosophic information, in which the weights of decision-makers and decision criteria are calculated based on entropy measure. Finally, a practical example is utilised to show the practicality and effectiveness of the proposed method.

A cognitive prosthesis for complex decision-making.

PubMed

Tremblay, Sébastien; Gagnon, Jean-François; Lafond, Daniel; Hodgetts, Helen M; Doiron, Maxime; Jeuniaux, Patrick P J M H

2017-01-01

While simple heuristics can be ecologically rational and effective in naturalistic decision making contexts, complex situations require analytical decision making strategies, hypothesis-testing and learning. Sub-optimal decision strategies - using simplified as opposed to analytic decision rules - have been reported in domains such as healthcare, military operational planning, and government policy making. We investigate the potential of a computational toolkit called "IMAGE" to improve decision-making by developing structural knowledge and increasing understanding of complex situations. IMAGE is tested within the context of a complex military convoy management task through (a) interactive simulations, and (b) visualization and knowledge representation capabilities. We assess the usefulness of two versions of IMAGE (desktop and immersive) compared to a baseline. Results suggest that the prosthesis helped analysts in making better decisions, but failed to increase their structural knowledge about the situation once the cognitive prosthesis is removed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Palliative Medicine and Decision Science: The Critical Need for a Shared Agenda To Foster Informed Patient Choice in Serious Illness

PubMed Central

Kryworuchko, Jennifer; Matlock, Dan D.; Volandes, Angelo E.

2011-01-01

Abstract Assisting patients and their families in complex decision making is a foundational skill in palliative care; however, palliative care clinicians and scientists have just begun to establish an evidence base for best practice in assisting patients and families in complex decision making. Decision scientists aim to understand and clarify the concepts and techniques of shared decision making (SDM), decision support, and informed patient choice in order to ensure that patient and family perspectives shape their health care experience. Patients with serious illness and their families are faced with myriad complex decisions over the course of illness and as death approaches. If patients lose capacity, then surrogate decision makers are cast into the decision-making role. The fields of palliative care and decision science have grown in parallel. There is much to be gained in advancing the practices of complex decision making in serious illness through increased collaboration. The purpose of this article is to use a case study to highlight the broad range of difficult decisions, issues, and opportunities imposed by a life-limiting illness in order to illustrate how collaboration and a joint research agenda between palliative care and decision science researchers, theorists, and clinicians might guide best practices for patients and their families. PMID:21895453

A Simulation for Managing Complexity in Sales and Operations Planning Decisions

ERIC Educational Resources Information Center

DuHadway, Scott; Dreyfus, David

2017-01-01

Within the classroom it is often difficult to convey the complexities and intricacies that go into making sales and operations planning decisions. This article describes an in-class simulation that allows students to gain hands-on experience with the complexities in making forecasting, inventory, and supplier selection decisions as part of the…

Behavioural and physiological effects of finely balanced decision-making in chickens.

PubMed

Davies, Anna C; Nicol, Christine J; Persson, Mia E; Radford, Andrew N

2014-01-01

In humans, more difficult decisions result in behavioural and physiological changes suggestive of increased arousal, but little is known about the effect of decision difficulty in other species. A difficult decision can have a number of characteristics; we aimed to monitor how finely balanced decisions, compared to unbalanced ones, affected the behaviour and physiology of chickens. An unbalanced decision was one in which the two options were of unequal net value (1 (Q1) vs. 6 (Q6) pieces of sweetcorn with no cost associated with either option); a finely balanced decision was one in which the options were of equal net value (i.e. hens were "indifferent" to both options). To identify hens' indifference, a titration procedure was used in which a cost (electromagnetic weight on an access door) was applied to the Q6 option, to find the individual point at which hens chose this option approximately equally to Q1 via a non-weighted door. We then compared behavioural and physiological indicators of arousal (head movements, latency to choose, heart-rate variability and surface body temperature) when chickens made decisions that were unbalanced or finely balanced. Significant physiological (heart-rate variability) and behavioural (latency to pen) differences were found between the finely balanced and balanced conditions, but these were likely to be artefacts of the greater time and effort required to push through the weighted doors. No other behavioural and physiological measures were significantly different between the decision categories. We suggest that more information is needed on when best to monitor likely changes in arousal during decision-making and that future studies should consider decisions defined as difficult in other ways.

Probability Weighting Functions Derived from Hyperbolic Time Discounting: Psychophysical Models and Their Individual Level Testing.

PubMed

Takemura, Kazuhisa; Murakami, Hajime

2016-01-01

A probability weighting function (w(p)) is considered to be a nonlinear function of probability (p) in behavioral decision theory. This study proposes a psychophysical model of probability weighting functions derived from a hyperbolic time discounting model and a geometric distribution. The aim of the study is to show probability weighting functions from the point of view of waiting time for a decision maker. Since the expected value of a geometrically distributed random variable X is 1/p, we formulized the probability weighting function of the expected value model for hyperbolic time discounting as w(p) = (1 - k log p)(-1). Moreover, the probability weighting function is derived from Loewenstein and Prelec's (1992) generalized hyperbolic time discounting model. The latter model is proved to be equivalent to the hyperbolic-logarithmic weighting function considered by Prelec (1998) and Luce (2001). In this study, we derive a model from the generalized hyperbolic time discounting model assuming Fechner's (1860) psychophysical law of time and a geometric distribution of trials. In addition, we develop median models of hyperbolic time discounting and generalized hyperbolic time discounting. To illustrate the fitness of each model, a psychological experiment was conducted to assess the probability weighting and value functions at the level of the individual participant. The participants were 50 university students. The results of individual analysis indicated that the expected value model of generalized hyperbolic discounting fitted better than previous probability weighting decision-making models. The theoretical implications of this finding are discussed.

Correlations of decision weights and cognitive function for the masked discrimination of vowels by young and old adults

PubMed Central

Lutfi, Robert A.

2014-01-01

Older adults are often reported in the literature to have greater difficulty than younger adults understanding speech in noise [Helfer and Wilber (1988). J. Acoust. Soc. Am, 859–893]. The poorer performance of older adults has been attributed to a general deterioration of cognitive processing, deterioration of cochlear anatomy, and/or greater difficulty segregating speech from noise. The current work used perturbation analysis [Berg (1990). J. Acoust. Soc. Am., 149–158] to provide a more specific assessment of the effect of cognitive factors on speech perception in noise. Sixteen older (age 56–79 years) and seventeen younger (age 19–30 years) adults discriminated a target vowel masked by randomly selected masker vowels immediately preceding and following the target. Relative decision weights on target and maskers resulting from the analysis revealed large individual differences across participants despite similar performance scores in many cases. On the most difficult vowel discriminations, the older adult decision weights were significantly correlated with inhibitory control (Color Word Interference test) and pure-tone threshold averages (PTA). Young adult decision weights were not correlated with any measures of peripheral (PTA) or central function (inhibition or working memory). PMID:25256580

Computational Complexity and Human Decision-Making.

PubMed

Bossaerts, Peter; Murawski, Carsten

2017-12-01

The rationality principle postulates that decision-makers always choose the best action available to them. It underlies most modern theories of decision-making. The principle does not take into account the difficulty of finding the best option. Here, we propose that computational complexity theory (CCT) provides a framework for defining and quantifying the difficulty of decisions. We review evidence showing that human decision-making is affected by computational complexity. Building on this evidence, we argue that most models of decision-making, and metacognition, are intractable from a computational perspective. To be plausible, future theories of decision-making will need to take into account both the resources required for implementing the computations implied by the theory, and the resource constraints imposed on the decision-maker by biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

When weight management lasts. Lower perceived rule complexity increases adherence.

PubMed

Mata, Jutta; Todd, Peter M; Lippke, Sonia

2010-02-01

Maintaining behavior change is one of the major challenges in weight management and long-term weight loss. We investigated the impact of the cognitive complexity of eating rules on adherence to weight management programs. We studied whether popular weight management programs can fail if participants find the rules too complicated from a cognitive perspective, meaning that individuals are not able to recall or process all required information for deciding what to eat. The impact on program adherence of participants' perceptions of eating rule complexity and other behavioral factors known to influence adherence (including previous weight management, self-efficacy, and planning) was assessed via a longitudinal online questionnaire given to 390 participants on two different popular weight management regimens. As we show, the regimens, Weight Watchers and a popular German recipe diet (Brigitte), strongly differ in objective rule complexity and thus their cognitive demands on the dieter. Perceived rule complexity was the strongest factor associated with increased risk of quitting the cognitively demanding weight management program (Weight Watchers); it was not related to adherence length for the low cognitive demand program (Brigitte). Higher self-efficacy generally helped in maintaining a program. The results emphasize the importance of considering rule complexity to promote long-term weight management. 2009 Elsevier Ltd. All rights reserved.

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale

PubMed Central

Diao, Yuzhu; Hu, Aqin

2018-01-01

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation. PMID:29498699

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

PubMed

Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

2018-03-02

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

Hierarchical Bayesian analysis of outcome- and process-based social preferences and beliefs in Dictator Games and sequential Prisoner's Dilemmas.

PubMed

Aksoy, Ozan; Weesie, Jeroen

2014-05-01

In this paper, using a within-subjects design, we estimate the utility weights that subjects attach to the outcome of their interaction partners in four decision situations: (1) binary Dictator Games (DG), second player's role in the sequential Prisoner's Dilemma (PD) after the first player (2) cooperated and (3) defected, and (4) first player's role in the sequential Prisoner's Dilemma game. We find that the average weights in these four decision situations have the following order: (1)>(2)>(4)>(3). Moreover, the average weight is positive in (1) but negative in (2), (3), and (4). Our findings indicate the existence of strong negative and small positive reciprocity for the average subject, but there is also high interpersonal variation in the weights in these four nodes. We conclude that the PD frame makes subjects more competitive than the DG frame. Using hierarchical Bayesian modeling, we simultaneously analyze beliefs of subjects about others' utility weights in the same four decision situations. We compare several alternative theoretical models on beliefs, e.g., rational beliefs (Bayesian-Nash equilibrium) and a consensus model. Our results on beliefs strongly support the consensus effect and refute rational beliefs: there is a strong relationship between own preferences and beliefs and this relationship is relatively stable across the four decision situations. Copyright © 2014 Elsevier Inc. All rights reserved.

Collaborative Response and Recovery from a Foot-and-Mouth Disease Animal Health Emergency: Supporting Decision Making in a Complex Environment with Multiple Stakeholders

DTIC Science & Technology

2013-12-01

RESPONSE AND RECOVERY FROM A FOOT-AND- MOUTH DISEASE ANIMAL HEALTH EMERGENCY: SUPPORTING DECISION MAKING IN A COMPLEX ENVIRONMENT WITH MULTIPLE...Thesis 4. TITLE AND SUBTITLE COLLABORATIVE RESPONSE AND RECOVERY FROM A FOOT-AND- MOUTH DISEASE ANIMAL HEALTH EMERGENCY: SUPPORTING DECISION MAKING...200 words ) This thesis recommends ways to support decision makers who must operate within the multi-stakeholder complex situation of response and

Gender and Values: What Is the Impact on Decision Making?

ERIC Educational Resources Information Center

Crow, Stephen M.; And Others

1991-01-01

Linkages among gender, decision making, and values related to moral development and equity/equality are studied for 54 graduate and 186 undergraduate business school students (48 percent females) attending a Southern urban university. Results illustrate gender-related differences in value systems, weights of decision issues, and decisions. Future…

A Fuzzy Robust Optimization Model for Waste Allocation Planning Under Uncertainty

PubMed Central

Xu, Ye; Huang, Guohe; Xu, Ling

2014-01-01

Abstract In this study, a fuzzy robust optimization (FRO) model was developed for supporting municipal solid waste management under uncertainty. The Development Zone of the City of Dalian, China, was used as a study case for demonstration. Comparing with traditional fuzzy models, the FRO model made improvement by considering the minimization of the weighted summation among the expected objective values, the differences between two extreme possible objective values, and the penalty of the constraints violation as the objective function, instead of relying purely on the minimization of expected value. Such an improvement leads to enhanced system reliability and the model becomes especially useful when multiple types of uncertainties and complexities are involved in the management system. Through a case study, the applicability of the FRO model was successfully demonstrated. Solutions under three future planning scenarios were provided by the FRO model, including (1) priority on economic development, (2) priority on environmental protection, and (3) balanced consideration for both. The balanced scenario solution was recommended for decision makers, since it respected both system economy and reliability. The model proved valuable in providing a comprehensive profile about the studied system and helping decision makers gain an in-depth insight into system complexity and select cost-effective management strategies. PMID:25317037

A Fuzzy Robust Optimization Model for Waste Allocation Planning Under Uncertainty.

PubMed

Xu, Ye; Huang, Guohe; Xu, Ling

2014-10-01

In this study, a fuzzy robust optimization (FRO) model was developed for supporting municipal solid waste management under uncertainty. The Development Zone of the City of Dalian, China, was used as a study case for demonstration. Comparing with traditional fuzzy models, the FRO model made improvement by considering the minimization of the weighted summation among the expected objective values, the differences between two extreme possible objective values, and the penalty of the constraints violation as the objective function, instead of relying purely on the minimization of expected value. Such an improvement leads to enhanced system reliability and the model becomes especially useful when multiple types of uncertainties and complexities are involved in the management system. Through a case study, the applicability of the FRO model was successfully demonstrated. Solutions under three future planning scenarios were provided by the FRO model, including (1) priority on economic development, (2) priority on environmental protection, and (3) balanced consideration for both. The balanced scenario solution was recommended for decision makers, since it respected both system economy and reliability. The model proved valuable in providing a comprehensive profile about the studied system and helping decision makers gain an in-depth insight into system complexity and select cost-effective management strategies.

Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

NASA Astrophysics Data System (ADS)

Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

2017-11-01

This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

The hidden traps in decision making.

PubMed

Hammond, J S; Keeney, R L; Raiffa, H

1998-01-01

Bad decisions can often be traced back to the way the decisions were made--the alternatives were not clearly defined, the right information was not collected, the costs and benefits were not accurately weighted. But sometimes the fault lies not in the decision-making process but rather in the mind of the decision maker. The way the human brain works can sabotage the choices we make. John Hammond, Ralph Keeney, and Howard Raiffa examine eight psychological traps that are particularly likely to affect the way we make business decisions: The anchoring trap leads us to give disproportionate weight to the first information we receive. The statusquo trap biases us toward maintaining the current situation--even when better alternatives exist. The sunk-cost trap inclines us to perpetuate the mistakes of the past. The confirming-evidence trap leads us to seek out information supporting an existing predilection and to discount opposing information. The framing trap occurs when we misstate a problem, undermining the entire decision-making process. The overconfidence trap makes us overestimate the accuracy of our forecasts. The prudence trap leads us to be overcautious when we make estimates about uncertain events. And the recallability trap leads us to give undue weight to recent, dramatic events. The best way to avoid all the traps is awareness--forewarned is forearmed. But executives can also take other simple steps to protect themselves and their organizations from the various kinds of mental lapses. The authors show how to take action to ensure that important business decisions are sound and reliable.

Decision-making in irrigation networks: Selecting appropriate canal structures using multi-attribute decision analysis.

PubMed

Hosseinzade, Zeinab; Pagsuyoin, Sheree A; Ponnambalam, Kumaraswamy; Monem, Mohammad J

2017-12-01

The stiff competition for water between agriculture and non-agricultural production sectors makes it necessary to have effective management of irrigation networks in farms. However, the process of selecting flow control structures in irrigation networks is highly complex and involves different levels of decision makers. In this paper, we apply multi-attribute decision making (MADM) methodology to develop a decision analysis (DA) framework for evaluating, ranking and selecting check and intake structures for irrigation canals. The DA framework consists of identifying relevant attributes for canal structures, developing a robust scoring system for alternatives, identifying a procedure for data quality control, and identifying a MADM model for the decision analysis. An application is illustrated through an analysis for automation purposes of the Qazvin irrigation network, one of the oldest and most complex irrigation networks in Iran. A survey questionnaire designed based on the decision framework was distributed to experts, managers, and operators of the Qazvin network and to experts from the Ministry of Power in Iran. Five check structures and four intake structures were evaluated. A decision matrix was generated from the average scores collected from the survey, and was subsequently solved using TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. To identify the most critical structure attributes for the selection process, optimal attribute weights were calculated using Entropy method. For check structures, results show that the duckbill weir is the preferred structure while the pivot weir is the least preferred. Use of the duckbill weir can potentially address the problem with existing Amil gates where manual intervention is required to regulate water levels during periods of flow extremes. For intake structures, the Neyrpic® gate and constant head orifice are the most and least preferred alternatives, respectively. Some advantages of the Neyrpic® gate are ease of operation and capacity to measure discharge flows. Overall, the application to the Qazvin irrigation network demonstrates the utility of the proposed DA framework in selecting appropriate structures for regulating water flows in irrigation canals. This framework systematically aids the decision process by capturing decisions made at various levels (individual farmers to high-level management). It can be applied to other cases where a new irrigation network is being designed, or where changes in irrigation structures need to be identified to improve flow control in existing networks. Copyright © 2017 Elsevier B.V. All rights reserved.

An information dimension of weighted complex networks

NASA Astrophysics Data System (ADS)

Wen, Tao; Jiang, Wen

2018-07-01

The fractal and self-similarity are important properties in complex networks. Information dimension is a useful dimension for complex networks to reveal these properties. In this paper, an information dimension is proposed for weighted complex networks. Based on the box-covering algorithm for weighted complex networks (BCANw), the proposed method can deal with the weighted complex networks which appear frequently in the real-world, and it can get the influence of the number of nodes in each box on the information dimension. To show the wide scope of information dimension, some applications are illustrated, indicating that the proposed method is effective and feasible.

Multi-criteria, personalized route planning using quantifier-guided ordered weighted averaging operators

NASA Astrophysics Data System (ADS)

Nadi, S.; Delavar, M. R.

2011-06-01

This paper presents a generic model for using different decision strategies in multi-criteria, personalized route planning. Some researchers have considered user preferences in navigation systems. However, these prior studies typically employed a high tradeoff decision strategy, which used a weighted linear aggregation rule, and neglected other decision strategies. The proposed model integrates a pairwise comparison method and quantifier-guided ordered weighted averaging (OWA) aggregation operators to form a personalized route planning method that incorporates different decision strategies. The model can be used to calculate the impedance of each link regarding user preferences in terms of the route criteria, criteria importance and the selected decision strategy. Regarding the decision strategy, the calculated impedance lies between aggregations that use a logical "and" (which requires all the criteria to be satisfied) and a logical "or" (which requires at least one criterion to be satisfied). The calculated impedance also includes taking the average of the criteria scores. The model results in multiple alternative routes, which apply different decision strategies and provide users with the flexibility to select one of them en-route based on the real world situation. The model also defines the robust personalized route under different decision strategies. The influence of different decision strategies on the results are investigated in an illustrative example. This model is implemented in a web-based geographical information system (GIS) for Isfahan in Iran and verified in a tourist routing scenario. The results demonstrated, in real world situations, the validity of the route planning carried out in the model.

Multifaceted Modelling of Complex Business Enterprises

PubMed Central

2015-01-01

We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control. PMID:26247591

Multifaceted Modelling of Complex Business Enterprises.

PubMed

Chakraborty, Subrata; Mengersen, Kerrie; Fidge, Colin; Ma, Lin; Lassen, David

2015-01-01

We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control.

Some induced intuitionistic fuzzy aggregation operators applied to multi-attribute group decision making

NASA Astrophysics Data System (ADS)

Su, Zhi-xin; Xia, Guo-ping; Chen, Ming-yuan

2011-11-01

In this paper, we define various induced intuitionistic fuzzy aggregation operators, including induced intuitionistic fuzzy ordered weighted averaging (OWA) operator, induced intuitionistic fuzzy hybrid averaging (I-IFHA) operator, induced interval-valued intuitionistic fuzzy OWA operator, and induced interval-valued intuitionistic fuzzy hybrid averaging (I-IIFHA) operator. We also establish various properties of these operators. And then, an approach based on I-IFHA operator and intuitionistic fuzzy weighted averaging (WA) operator is developed to solve multi-attribute group decision-making (MAGDM) problems. In such problems, attribute weights and the decision makers' (DMs') weights are real numbers and attribute values provided by the DMs are intuitionistic fuzzy numbers (IFNs), and an approach based on I-IIFHA operator and interval-valued intuitionistic fuzzy WA operator is developed to solve MAGDM problems where the attribute values provided by the DMs are interval-valued IFNs. Furthermore, induced intuitionistic fuzzy hybrid geometric operator and induced interval-valued intuitionistic fuzzy hybrid geometric operator are proposed. Finally, a numerical example is presented to illustrate the developed approaches.

Hospital-based expert model for health technology procurement planning in hospitals.

PubMed

Miniati, R; Cecconi, G; Frosini, F; Dori, F; Regolini, J; Iadanza, E; Biffi Gentili, G

2014-01-01

Although in the last years technology innovation in healthcare brought big improvements in care level and patient quality of life, hospital complexity and management cost became higher. For this reason, necessity of planning for medical equipment procurement within hospitals is getting more and more important in order to sustainable provide appropriate technology for both routine activity and innovative procedures. In order to support hospital decision makers for technology procurement planning, an expert model was designed as reported in the following paper. It combines the most widely used approaches for technology evaluation by taking into consideration Health Technology Assessment (HTA) and Medical Equipment Replacement Model (MERM). The designing phases include a first definition of prioritization algorithms, then the weighting process through experts' interviews and a final step for the model validation that included both statistical testing and comparison with real decisions. In conclusion, the designed model was able to provide a semi-automated tool that through the use of multidisciplinary information is able to prioritize different requests of technology acquisition in hospitals. Validation outcomes improved the model accuracy and created different "user profiles" according to the specific needs of decision makers.

Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert

PubMed Central

Schmidt, Henk G.; Rikers, Remy M. J. P.; Custers, Eugene J. F. M.; Splinter, Ted A. W.; van Saase, Jan L. C. M.

2010-01-01

Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices’ decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases. PMID:20354726

Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert.

PubMed

Mamede, Sílvia; Schmidt, Henk G; Rikers, Remy M J P; Custers, Eugene J F M; Splinter, Ted A W; van Saase, Jan L C M

2010-11-01

Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices' decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases.

Using data mining to predict success in a weight loss trial.

PubMed

Batterham, M; Tapsell, L; Charlton, K; O'Shea, J; Thorne, R

2017-08-01

Traditional methods for predicting weight loss success use regression approaches, which make the assumption that the relationships between the independent and dependent (or logit of the dependent) variable are linear. The aim of the present study was to investigate the relationship between common demographic and early weight loss variables to predict weight loss success at 12 months without making this assumption. Data mining methods (decision trees, generalised additive models and multivariate adaptive regression splines), in addition to logistic regression, were employed to predict: (i) weight loss success (defined as ≥5%) at the end of a 12-month dietary intervention using demographic variables [body mass index (BMI), sex and age]; percentage weight loss at 1 month; and (iii) the difference between actual and predicted weight loss using an energy balance model. The methods were compared by assessing model parsimony and the area under the curve (AUC). The decision tree provided the most clinically useful model and had a good accuracy (AUC 0.720 95% confidence interval = 0.600-0.840). Percentage weight loss at 1 month (≥0.75%) was the strongest predictor for successful weight loss. Within those individuals losing ≥0.75%, individuals with a BMI (≥27 kg m -2 ) were more likely to be successful than those with a BMI between 25 and 27 kg m -2 . Data mining methods can provide a more accurate way of assessing relationships when conventional assumptions are not met. In the present study, a decision tree provided the most parsimonious model. Given that early weight loss cannot be predicted before randomisation, incorporating this information into a post randomisation trial design may give better weight loss results. © 2017 The British Dietetic Association Ltd.

Supportive decision making at the point of care: refinement of a case-based reasoning application for use in nursing practice.

PubMed

DI Pietro, Tammie L; Doran, Diane M; McArthur, Gregory

2010-01-01

Variations in nursing care have been observed, affecting patient outcomes and quality of care. Case-based reasoners that benchmark for patient indicators can reduce variation through decision support. This study evaluated and validated a case-based reasoning application to establish benchmarks for nursing-sensitive patient outcomes of pain, fatigue, and toilet use, using patient characteristic variables for generating similar cases. Three graduate nursing students participated. Each ranked 25 patient cases using demographics of age, sex, diagnosis, and comorbidities against 10 patients from a database. Participant judgments of case similarity were compared with the case-based reasoning system. Feature weights for each indicator were adjusted to make the case-based reasoning system's similarity ranking correspond more closely to participant judgment. Small differences were noted between initial weights and weights generated from participants. For example, initial weight for comorbidities was 0.35, whereas weights generated by participants for pain, fatigue, and toilet use were 0.49, 0.42, and 0.48, respectively. For the same outcomes, the initial weight for sex was 0.15, but weights generated by the participants were 0.025, 0.002, and 0.000, respectively. Refinement of the case-based reasoning tool established valid benchmarks for patient outcomes in relation to participants and assisted in point-of-care decision making.

"Choice Set" for health behavior in choice-constrained settings to frame research and inform policy: examples of food consumption, obesity and food security.

PubMed

Dover, Robert V H; Lambert, Estelle V

2016-03-16

Using the nexus between food consumption, food security and obesity, this paper addresses the complexity of health behavior decision-making moments that reflect relational social dynamics in context-specific dialogues, often in choice-constrained conditions. A pragmatic review of literature regarding social determinants of health in relation to food consumption, food security and obesity was used to advance this theoretical model. We suggest that health choice, such as food consumption, is based on more than the capacity and volition of individuals to make "healthy" choices, but is dialogic and adaptive. In terms of food consumption, there will always be choice-constrained conditions, along a continuum representing factors over which the individual has little or no control, to those for which they have greater agency. These range from food store geographies and inventories and food availability, logistical considerations such as transportation, food distribution, the structure of equity in food systems, state and non-government food and nutrition programs, to factors where the individual exercises a greater degree of autonomy, such as sociocultural foodways, family and neighborhood shopping strategies, and personal and family food preferences. At any given food decision-making moment, many factors of the continuum are present consciously or unconsciously when the individual makes a decision. These health behavior decision-making moments are mutable, whether from an individual perspective, or within a broader social or policy context. We review the construct of "choice set", the confluence of factors that are temporally weighted by the differentiated and relationally-contextualized importance of certain factors over others in that moment. The choice transition represents an essential shift of the choice set based on the conscious and unconscious weighting of accumulated evidence, such that people can project certain outcomes. Policies and interventions should avoid dichotomies of "good and bad" food choices or health behaviors, but focus on those issues that contribute to the weightedness of factors influencing food choice behavior at a given decision-making moment and within a given choice set.

Diverter Decision Aiding for In-Flight Diversions

NASA Technical Reports Server (NTRS)

Rudolph, Frederick M.; Homoki, David A.; Sexton, George A.

1990-01-01

It was determined that artificial intelligence technology can provide pilots with the help they need in making the complex decisions concerning en route changes in a flight plan. A diverter system should have the capability to take all of the available information and produce a recommendation to the pilot. Phase three illustrated that using Joshua to develop rules for an expert system and a Statice database provided additional flexibility by permitting the development of dynamic weighting of diversion relevant parameters. This increases the fidelity of the AI functions cited as useful in aiding the pilot to perform situational assessment, navigation rerouting, flight planning/replanning, and maneuver execution. Additionally, a prototype pilot-vehicle interface (PVI) was designed providing for the integration of both text and graphical based information. Advanced technologies were applied to PVI design, resulting in a hierarchical menu based architecture to increase the efficiency of information transfer while reducing expected workload. Additional efficiency was gained by integrating spatial and text displays into an integrated user interface.

Rejection or selection: influence of framing in investment decisions.

PubMed

Cheng, Pi-Yueh; Chiou, Wen-Bin

2010-02-01

According to prospect theory, reflection effects result in preferences for risk-averse choices in gain situations and risk-seeking choices in loss situations. However, relevant literature in regard to decision making has suggested that positive information receives more weight in a selection task, whereas negative information receives more weight in a rejection task. The present study examined whether the nature of a decision task (selection vs rejection) would moderate the reflection effects. Undergraduates (47 men, 49 women; M age = 20.5 yr., SD = 1.1), selected according to specific screening criteria, participated in an experimental study. Typical reflection effects were observed in both selection and rejection task conditions. More importantly, negative information (i.e., the information about probable loss in risky choice of gain situations and the information about certain loss in cautious choice of loss situations) provided in the context of a rejection task received more weight and resulted in more frequent endorsements of the cautious choice in gain situations and of the risky choice in loss situations. Hence, the findings suggest that a decision context characterized by rejection may expand the reflection effects and thereby provide important information about situations in which investment decisions occur in a context characterized by rejection.

A decision support tool for landfill methane generation and gas collection.

PubMed

Emkes, Harriet; Coulon, Frédéric; Wagland, Stuart

2015-09-01

This study presents a decision support tool (DST) to enhance methane generation at individual landfill sites. To date there is no such tool available to provide landfill decision makers with clear and simplified information to evaluate biochemical processes within a landfill site, to assess performance of gas production and to identify potential remedies to any issues. The current lack in understanding stems from the complexity of the landfill waste degradation process. Two scoring sets for landfill gas production performance are calculated with the tool: (1) methane output score which measures the deviation of the actual methane output rate at each site which the prediction generated by the first order decay model LandGEM; and (2) landfill gas indicators' score, which measures the deviation of the landfill gas indicators from their ideal ranges for optimal methane generation conditions. Landfill gas indicators include moisture content, temperature, alkalinity, pH, BOD, COD, BOD/COD ratio, ammonia, chloride, iron and zinc. A total landfill gas indicator score is provided using multi-criteria analysis to calculate the sum of weighted scores for each indicator. The weights for each indicator are calculated using an analytical hierarchical process. The tool is tested against five real scenarios for landfill sites in UK with a range of good, average and poor landfill methane generation over a one year period (2012). An interpretation of the results is given for each scenario and recommendations are highlighted for methane output rate enhancement. Results demonstrate how the tool can help landfill managers and operators to enhance their understanding of methane generation at a site-specific level, track landfill methane generation over time, compare and rank sites, and identify problems areas within a landfill site. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-criteria decision analysis tools for prioritising emerging or re-emerging infectious diseases associated with climate change in Canada.

PubMed

Cox, Ruth; Sanchez, Javier; Revie, Crawford W

2013-01-01

Global climate change is known to result in the emergence or re-emergence of some infectious diseases. Reliable methods to identify the infectious diseases of humans and animals and that are most likely to be influenced by climate are therefore required. Since different priorities will affect the decision to address a particular pathogen threat, decision makers need a standardised method of prioritisation. Ranking methods and Multi-Criteria Decision approaches provide such a standardised method and were employed here to design two different pathogen prioritisation tools. The opinion of 64 experts was elicited to assess the importance of 40 criteria that could be used to prioritise emerging infectious diseases of humans and animals in Canada. A weight was calculated for each criterion according to the expert opinion. Attributes were defined for each criterion as a transparent and repeatable method of measurement. Two different Multi-Criteria Decision Analysis tools were tested, both of which used an additive aggregation approach. These were an Excel spreadsheet tool and a tool developed in software 'M-MACBETH'. The tools were trialed on nine 'test' pathogens. Two different methods of criteria weighting were compared, one using fixed weighting values, the other using probability distributions to account for uncertainty and variation in expert opinion. The ranking of the nine pathogens varied according to the weighting method that was used. In both tools, using both weighting methods, the diseases that tended to rank the highest were West Nile virus, Giardiasis and Chagas, while Coccidioidomycosis tended to rank the lowest. Both tools are a simple and user friendly approach to prioritising pathogens according to climate change by including explicit scoring of 40 criteria and incorporating weighting methods based on expert opinion. They provide a dynamic interactive method that can help to identify pathogens for which a full risk assessment should be pursued.

Multi-Criteria Decision Analysis Tools for Prioritising Emerging or Re-Emerging Infectious Diseases Associated with Climate Change in Canada

PubMed Central

Cox, Ruth; Sanchez, Javier; Revie, Crawford W.

2013-01-01

Global climate change is known to result in the emergence or re-emergence of some infectious diseases. Reliable methods to identify the infectious diseases of humans and animals and that are most likely to be influenced by climate are therefore required. Since different priorities will affect the decision to address a particular pathogen threat, decision makers need a standardised method of prioritisation. Ranking methods and Multi-Criteria Decision approaches provide such a standardised method and were employed here to design two different pathogen prioritisation tools. The opinion of 64 experts was elicited to assess the importance of 40 criteria that could be used to prioritise emerging infectious diseases of humans and animals in Canada. A weight was calculated for each criterion according to the expert opinion. Attributes were defined for each criterion as a transparent and repeatable method of measurement. Two different Multi-Criteria Decision Analysis tools were tested, both of which used an additive aggregation approach. These were an Excel spreadsheet tool and a tool developed in software ‘M-MACBETH’. The tools were trialed on nine ‘test’ pathogens. Two different methods of criteria weighting were compared, one using fixed weighting values, the other using probability distributions to account for uncertainty and variation in expert opinion. The ranking of the nine pathogens varied according to the weighting method that was used. In both tools, using both weighting methods, the diseases that tended to rank the highest were West Nile virus, Giardiasis and Chagas, while Coccidioidomycosis tended to rank the lowest. Both tools are a simple and user friendly approach to prioritising pathogens according to climate change by including explicit scoring of 40 criteria and incorporating weighting methods based on expert opinion. They provide a dynamic interactive method that can help to identify pathogens for which a full risk assessment should be pursued. PMID:23950868

Informed decision-making in elective major vascular surgery: analysis of 145 surgeon-patient consultations.

PubMed

Etchells, Edward; Ferrari, Michel; Kiss, Alex; Martyn, Nikki; Zinman, Deborah; Levinson, Wendy

2011-06-01

Prior studies show significant gaps in the informed decision-making process, a central goal of surgical care. These studies have been limited by their focus on low-risk decisions, single visits rather than entire consultations, or both. Our objectives were, first, to rate informed decision-making for major elective vascular surgery based on audiotapes of actual physician-patient conversations and, second, to compare ratings of informed decision-making for first visits to ratings for multiple visits by the same patient over time. We prospectively enrolled patients for whom vascular surgical treatment was a potential option at a tertiary care outpatient vascular surgery clinic. We audio-taped all surgeon-patient conversations, including multiple visits when necessary, until a decision was made. Using an existing method, we evaluated the transcripts for elements of decision-making, including basic elements (e.g., an explanation of the clinical condition), intermediate elements (e.g., risks and benefits) and complex elements (e.g., uncertainty around the decision). We analyzed 145 surgeon-patient consultations. Overall, 45% of consultations contained complex elements, whereas 23% did not contain the basic elements of decision-making. For the 67 consultations that involved multiple visits, ratings were significantly higher when evaluating all visits (50% complex elements) compared with evaluating only the first visit (33% complex elements, p < 0.001.) We found that 45% of consultations contained complex elements, which is higher than prior studies with similar methods. Analyzing decision-making over multiple visits yielded different results than analyzing decision-making for single visits.

What Do Teaching Weights Tell Us?

ERIC Educational Resources Information Center

Harter, Cynthia L.; Schaur, Georg; Watts, Michael

2015-01-01

Academic departments assign different relative weights to the importance of teaching and research. Those weights are used in making decisions about promotion, tenure, and annual raises. Presumably, raising the teaching weight should encourage faculty to increase time on teaching. Using survey data from U.S. faculty in 1995, 2000, 2005, and 2010,…

Human Decision Processes: Implications for SSA Support Tools

NASA Astrophysics Data System (ADS)

Picciano, P.

2013-09-01

Despite significant advances in computing power and artificial intelligence (AI), few critical decisions are made without a human decision maker in the loop. Space Situational Awareness (SSA) missions are both critical and complex, typically adhering to the human-in-the-loop (HITL) model. The collection of human operators injects a needed diversity of expert knowledge, experience, and authority required to successfully fulfill SSA tasking. A wealth of literature on human decision making exists citing myriad empirical studies and offering a varied set of prescriptive and descriptive models of judgment and decision making (Hastie & Dawes, 2001; Baron, 2000). Many findings have been proven sufficiently robust to allow information architects or system/interface designers to take action to improve decision processes. For the purpose of discussion, these concepts are bifurcated in two groups: 1) vulnerabilities to mitigate, and 2) capabilities to augment. These vulnerabilities and capabilities refer specifically to the decision process and should not be confused with a shortcoming or skill of a specific human operator. Thus the framing of questions and orders, the automated tools with which to collaborate, priming and contextual data, and the delivery of information all play a critical role in human judgment and choice. Evaluating the merits of any decision can be elusive; in order to constrain this discussion, ‘rational choice' will tend toward the economic model characteristics such as maximizing utility and selection consistency (e.g., if A preferred to B, and B preferred to C, than A should be preferred to C). Simple decision models often encourage one to list the pros and cons of a decision, perhaps use a weighting schema, but one way or another weigh the future benefit (or harm) of making a selection. The result (sought by the rationalist models) should drive toward higher utility. Despite notable differences in researchers' theses (to be discussed in the full paper), one opinion shared is that the rational, economic, deliberate listing/evaluation of all options is NOT representative of how many decision are made. A framework gaining interest lately describes two systems predominantly at work: intuition and reasoning (Kahneman, 2003). Intuition is fast, automatic, and parallel contrasted with the more effortful, deliberative, and sequential reasoning. One of the issues of contention is that considerable research is stacked supporting both sides claiming that intuition is: • A hallmark of expertise responsible for rapid, optimal decisions in the face of adversity • A vulnerability where biases serve as decision traps leading to wrong choices Using seminal studies from a range of domains and tasking, potential solutions for SSA decision support will be offered. Important issues such as managing uncertainty, framing inquiries, and information architecture, and contextual cues will be discussed. The purpose is to provide awareness of the human limitations and capabilities in complex decision making so engineers and designers can consider such factors in their development of SSA tools.

Complex Decision-Making in Heart Failure: A Systematic Review and Thematic Analysis.

PubMed

Hamel, Aimee V; Gaugler, Joseph E; Porta, Carolyn M; Hadidi, Niloufar Niakosari

Heart failure follows a highly variable and difficult course. Patients face complex decisions, including treatment with implantable cardiac defibrillators, mechanical circulatory support, and heart transplantation. The course of decision-making across multiple treatments is unclear yet integral to providing informed and shared decision-making. Recognizing commonalities across treatment decisions could help nurses and physicians to identify opportunities to introduce discussions and support shared decision-making. The specific aims of this review are to examine complex treatment decision-making, specifically implantable cardiac defibrillators, ventricular assist device, and cardiac transplantation, and to recognize commonalities and key points in the decisional process. MEDLINE, CINAHL, PsycINFO, and Web of Science were searched for English-language studies that included qualitative findings reflecting the complexity of heart failure decision-making. Using a 3-step process, findings were synthesized into themes and subthemes. Twelve articles met criteria for inclusion. Participants included patients, caregivers, and clinicians and included decisions to undergo and decline treatment. Emergent themes were "processing the decision," "timing and prognostication," and "considering the future." Subthemes described how participants received and understood information about the therapy, making and changing a treatment decision, timing their decision and gauging health status outcomes in the context of their decision, the influence of a life or death decision, and the future as a factor in their decisional process. Commonalities were present across therapies, which involved the timing of discussions, the delivery of information, and considerations of the future. Exploring this further could help support patient-centered care and optimize shared decision-making interventions.

Multicriteria decision analysis: Overview and implications for environmental decision making

USGS Publications Warehouse

Hermans, Caroline M.; Erickson, Jon D.; Erickson, Jon D.; Messner, Frank; Ring, Irene

2007-01-01

Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

Decision-model estimation of the age-specific disability weight for schistosomiasis japonica: a systematic review of the literature.

PubMed

Finkelstein, Julia L; Schleinitz, Mark D; Carabin, Hélène; McGarvey, Stephen T

2008-03-05

Schistosomiasis is among the most prevalent parasitic infections worldwide. However, current Global Burden of Disease (GBD) disability-adjusted life year estimates indicate that its population-level impact is negligible. Recent studies suggest that GBD methodologies may significantly underestimate the burden of parasitic diseases, including schistosomiasis. Furthermore, strain-specific disability weights have not been established for schistosomiasis, and the magnitude of human disease burden due to Schistosoma japonicum remains controversial. We used a decision model to quantify an alternative disability weight estimate of the burden of human disease due to S. japonicum. We reviewed S. japonicum morbidity data, and constructed decision trees for all infected persons and two age-specific strata, <15 years (y) and > or =15 y. We conducted stochastic and probabilistic sensitivity analyses for each model. Infection with S. japonicum was associated with an average disability weight of 0.132, with age-specific disability weights of 0.098 (<15 y) and 0.186 (> or =15 y). Re-estimated disability weights were seven to 46 times greater than current GBD measures; no simulations produced disability weight estimates lower than 0.009. Nutritional morbidities had the greatest contribution to the S. japonicum disability weight in the <15 y model, whereas major organ pathologies were the most critical variables in the older age group. GBD disability weights for schistosomiasis urgently need to be revised, and species-specific disability weights should be established. Even a marginal increase in current estimates would result in a substantial rise in the estimated global burden of schistosomiasis, and have considerable implications for public health prioritization and resource allocation for schistosomiasis research, monitoring, and control.

Decision-Model Estimation of the Age-Specific Disability Weight for Schistosomiasis Japonica: A Systematic Review of the Literature

PubMed Central

Finkelstein, Julia L.; Schleinitz, Mark D.; Carabin, Hélène; McGarvey, Stephen T.

2008-01-01

Schistosomiasis is among the most prevalent parasitic infections worldwide. However, current Global Burden of Disease (GBD) disability-adjusted life year estimates indicate that its population-level impact is negligible. Recent studies suggest that GBD methodologies may significantly underestimate the burden of parasitic diseases, including schistosomiasis. Furthermore, strain-specific disability weights have not been established for schistosomiasis, and the magnitude of human disease burden due to Schistosoma japonicum remains controversial. We used a decision model to quantify an alternative disability weight estimate of the burden of human disease due to S. japonicum. We reviewed S. japonicum morbidity data, and constructed decision trees for all infected persons and two age-specific strata, <15 years (y) and ≥15 y. We conducted stochastic and probabilistic sensitivity analyses for each model. Infection with S. japonicum was associated with an average disability weight of 0.132, with age-specific disability weights of 0.098 (<15 y) and 0.186 (≥15 y). Re-estimated disability weights were seven to 46 times greater than current GBD measures; no simulations produced disability weight estimates lower than 0.009. Nutritional morbidities had the greatest contribution to the S. japonicum disability weight in the <15 y model, whereas major organ pathologies were the most critical variables in the older age group. GBD disability weights for schistosomiasis urgently need to be revised, and species-specific disability weights should be established. Even a marginal increase in current estimates would result in a substantial rise in the estimated global burden of schistosomiasis, and have considerable implications for public health prioritization and resource allocation for schistosomiasis research, monitoring, and control. PMID:18320018

Applying ISO 11929:2010 Standard to detection limit calculation in least-squares based multi-nuclide gamma-ray spectrum evaluation

NASA Astrophysics Data System (ADS)

Kanisch, G.

2017-05-01

The concepts of ISO 11929 (2010) are applied to evaluation of radionuclide activities from more complex multi-nuclide gamma-ray spectra. From net peak areas estimated by peak fitting, activities and their standard uncertainties are calculated by weighted linear least-squares method with an additional step, where uncertainties of the design matrix elements are taken into account. A numerical treatment of the standard's uncertainty function, based on ISO 11929 Annex C.5, leads to a procedure for deriving decision threshold and detection limit values. The methods shown allow resolving interferences between radionuclide activities also in case of calculating detection limits where they can improve the latter by including more than one gamma line per radionuclide. The co"mmon single nuclide weighted mean is extended to an interference-corrected (generalized) weighted mean, which, combined with the least-squares method, allows faster detection limit calculations. In addition, a new grouped uncertainty budget was inferred, which for each radionuclide gives uncertainty budgets from seven main variables, such as net count rates, peak efficiencies, gamma emission intensities and others; grouping refers to summation over lists of peaks per radionuclide.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

PubMed Central

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541

Heuristic decision making.

PubMed

Gigerenzer, Gerd; Gaissmaier, Wolfgang

2011-01-01

As reflected in the amount of controversy, few areas in psychology have undergone such dramatic conceptual changes in the past decade as the emerging science of heuristics. Heuristics are efficient cognitive processes, conscious or unconscious, that ignore part of the information. Because using heuristics saves effort, the classical view has been that heuristic decisions imply greater errors than do "rational" decisions as defined by logic or statistical models. However, for many decisions, the assumptions of rational models are not met, and it is an empirical rather than an a priori issue how well cognitive heuristics function in an uncertain world. To answer both the descriptive question ("Which heuristics do people use in which situations?") and the prescriptive question ("When should people rely on a given heuristic rather than a complex strategy to make better judgments?"), formal models are indispensable. We review research that tests formal models of heuristic inference, including in business organizations, health care, and legal institutions. This research indicates that (a) individuals and organizations often rely on simple heuristics in an adaptive way, and (b) ignoring part of the information can lead to more accurate judgments than weighting and adding all information, for instance for low predictability and small samples. The big future challenge is to develop a systematic theory of the building blocks of heuristics as well as the core capacities and environmental structures these exploit.

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection

PubMed Central

Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang

2018-01-01

In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10−5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced. PMID:29342963

A multicriteria-based methodology for site prioritisation in sediment management.

PubMed

Alvarez-Guerra, Manuel; Viguri, Javier R; Voulvoulis, Nikolaos

2009-08-01

Decision-making for sediment management is a complex task that incorporates the selections of areas for remediation and the assessment of options for any mitigation required. The application of Multicriteria Analysis (MCA) to rank different areas, according to their need for sediment management, provides a great opportunity for prioritisation, a first step in an integrated methodology that finally aims to assess and select suitable alternatives for managing the identified priority sites. This paper develops a methodology that starts with the delimitation of management units within areas of study, followed by the application of MCA methods that allows ranking of these management units, according to their need for remediation. This proposed process considers not only scientific evidence on sediment quality, but also other relevant aspects such as social and economic criteria associated with such decisions. This methodology is illustrated with its application to the case study area of the Bay of Santander, in northern Spain, highlighting some of the implications of utilising different MCA methods in the process. It also uses site-specific data to assess the subjectivity in the decision-making process, mainly reflected through the assignment of the criteria weights and uncertainties in the criteria scores. Analysis of the sensitivity of the results to these factors is used as a way to assess the stability and robustness of the ranking as a first step of the sediment management decision-making process.

Ultrafiltration for the Determination of Cu Complexed with Dissolved Organic Matters of Different Molecular Weight from a Eutrophic River, China.

PubMed

Li, Anding; Zhang, Yan; Zhou, Beihai; Xin, Kailing; Gu, Yingnan; Xu, Weijie; Tian, Jie

2018-05-21

The molecular weight of dissolved organic matter (DOM) is one of the essential factors controlling the properties of metal complexes. A continuous ultrafiltration experiment was designed to study the properties of Cu complexes with different molecular weights in a river before and after eutrophication. The results showed that the concentration of DOM increased from 26.47 to 38.20 mg/L during the eutrophication process, however, DOM was still dominated by the small molecular weight fraction before and after eutrophication. The amount of Cu-DOM complexes increased with the increasing of molecular weight, however, the amounts of DOM-Cu complexes before eutrophication were higher than those after eutrophication. This is because DOM contained more -COOH and -OH before eutrophication and these functional groups are the active sites complexed with Cu.

Supplier Selection Using Weighted Utility Additive Method

NASA Astrophysics Data System (ADS)

Karande, Prasad; Chakraborty, Shankar

2015-10-01

Supplier selection is a multi-criteria decision-making (MCDM) problem which mainly involves evaluating a number of available suppliers according to a set of common criteria for choosing the best one to meet the organizational needs. For any manufacturing or service organization, selecting the right upstream suppliers is a key success factor that will significantly reduce purchasing cost, increase downstream customer satisfaction and improve competitive ability. The past researchers have attempted to solve the supplier selection problem employing different MCDM techniques which involve active participation of the decision makers in the decision-making process. This paper deals with the application of weighted utility additive (WUTA) method for solving supplier selection problems. The WUTA method, an extension of utility additive approach, is based on ordinal regression and consists of building a piece-wise linear additive decision model from a preference structure using linear programming (LP). It adopts preference disaggregation principle and addresses the decision-making activities through operational models which need implicit preferences in the form of a preorder of reference alternatives or a subset of these alternatives present in the process. The preferential preorder provided by the decision maker is used as a restriction of a LP problem, which has its own objective function, minimization of the sum of the errors associated with the ranking of each alternative. Based on a given reference ranking of alternatives, one or more additive utility functions are derived. Using these utility functions, the weighted utilities for individual criterion values are combined into an overall weighted utility for a given alternative. It is observed that WUTA method, having a sound mathematical background, can provide accurate ranking to the candidate suppliers and choose the best one to fulfill the organizational requirements. Two real time examples are illustrated to prove its applicability and appropriateness in solving supplier selection problems.

Social Ecological Perspectives of Tube-Feeding Older Adults with Advanced Dementia: A Systematic Literature Review.

PubMed

Douglas, Joy W; Lawrence, Jeannine C; Turner, Lori W

2017-01-01

Dementia is a progressive, debilitating disease that often results in weight loss, malnutrition, and dehydration. Feeding tubes are often prescribed; however, this practice can lead to complications. The purpose of this systematic review was to examine the use of feeding tubes in elderly demented patients from a social ecological perspective. Results indicated that family members often receive inadequate decision-making education. Many health care professionals lack knowledge of evidence-based guidelines pertaining to feeding tube use. Organizational and financial reimbursement structures influence feeding tube use. Feeding practices for patients with advanced dementia is a complex issue, warranting approaches that target each level of the Social Ecological Model.

Walking the Fine Line: Political Decision Making with or without Data.

ERIC Educational Resources Information Center

Merkel-Keller, Claudia

The stages of the policy process are examined and explained in terms of the decision making framework. The policy process is comprised of four stages; policy analysis, policy formation, policy decision, and political analysis. Political analysis is the performance of the market analysis needed for a decision. The political weight, rather than the…

Systems thinking, complexity and managerial decision-making: an analytical review.

PubMed

Cramp, D G; Carson, E R

2009-05-01

One feature that characterizes the organization and delivery of health care is its inherent complexity. All too often, with so much information and so many activities involved, it is difficult for decision-makers to determine in an objective fashion an appropriate course of action. It would appear that a holistic rather than a reductionist approach would be advantageous. The aim of this paper is to review how formal systems thinking can aid decision-making in complex situations. Consideration is given as to how the use of a number of systems modelling methodologies can help in gaining an understanding of a complex decision situation. This in turn can enhance the possibility of a decision being made in a more rational, explicit and transparent fashion. The arguments and approaches are illustrated using examples taken from the public health arena.

A Group Decision Framework with Intuitionistic Preference Relations and Its Application to Low Carbon Supplier Selection.

PubMed

Tong, Xiayu; Wang, Zhou-Jing

2016-09-19

This article develops a group decision framework with intuitionistic preference relations. An approach is first devised to rectify an inconsistent intuitionistic preference relation to derive an additive consistent one. A new aggregation operator, the so-called induced intuitionistic ordered weighted averaging (IIOWA) operator, is proposed to aggregate individual intuitionistic fuzzy judgments. By using the mean absolute deviation between the original and rectified intuitionistic preference relations as an order inducing variable, the rectified consistent intuitionistic preference relations are aggregated into a collective preference relation. This treatment is presumably able to assign different weights to different decision-makers' judgments based on the quality of their inputs (in terms of consistency of their original judgments). A solution procedure is then developed for tackling group decision problems with intuitionistic preference relations. A low carbon supplier selection case study is developed to illustrate how to apply the proposed decision model in practice.

A Group Decision Framework with Intuitionistic Preference Relations and Its Application to Low Carbon Supplier Selection

PubMed Central

Tong, Xiayu; Wang, Zhou-Jing

2016-01-01

This article develops a group decision framework with intuitionistic preference relations. An approach is first devised to rectify an inconsistent intuitionistic preference relation to derive an additive consistent one. A new aggregation operator, the so-called induced intuitionistic ordered weighted averaging (IIOWA) operator, is proposed to aggregate individual intuitionistic fuzzy judgments. By using the mean absolute deviation between the original and rectified intuitionistic preference relations as an order inducing variable, the rectified consistent intuitionistic preference relations are aggregated into a collective preference relation. This treatment is presumably able to assign different weights to different decision-makers’ judgments based on the quality of their inputs (in terms of consistency of their original judgments). A solution procedure is then developed for tackling group decision problems with intuitionistic preference relations. A low carbon supplier selection case study is developed to illustrate how to apply the proposed decision model in practice. PMID:27657097

Comparison of Multi-Criteria Decision Support Methods (AHP, TOPSIS, SAW & PROMENTHEE) for Employee Placement

NASA Astrophysics Data System (ADS)

Widianta, M. M. D.; Rizaldi, T.; Setyohadi, D. P. S.; Riskiawan, H. Y.

2018-01-01

The right decision in placing employees in an appropriate position in a company will support the quality of management and will have an impact on improving the quality of human resources of the company. Such decision-making can be assisted by an approach through the Decision Support System (DSS) to improve accuracy in the employee placement process. The purpose of this paper is to compare the four methods of Multi Criteria Decision Making (MCDM), ie Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Of Evaluations (PROMETHEE) for the application of employee placement in accordance with predetermined criteria. The ranking results and the accuracy level obtained from each method are different depending on the different scaling and weighting processes in each method.

Overrepresentation of extreme events in decision making reflects rational use of cognitive resources.

PubMed

Lieder, Falk; Griffiths, Thomas L; Hsu, Ming

2018-01-01

People's decisions and judgments are disproportionately swayed by improbable but extreme eventualities, such as terrorism, that come to mind easily. This article explores whether such availability biases can be reconciled with rational information processing by taking into account the fact that decision makers value their time and have limited cognitive resources. Our analysis suggests that to make optimal use of their finite time decision makers should overrepresent the most important potential consequences relative to less important, put potentially more probable, outcomes. To evaluate this account, we derive and test a model we call utility-weighted sampling. Utility-weighted sampling estimates the expected utility of potential actions by simulating their outcomes. Critically, outcomes with more extreme utilities have a higher probability of being simulated. We demonstrate that this model can explain not only people's availability bias in judging the frequency of extreme events but also a wide range of cognitive biases in decisions from experience, decisions from description, and memory recall. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

PubMed

Wichary, Szymon; Smolen, Tomasz

2016-01-01

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

Cynefin as Reference Framework to Facilitate Insight and Decision-Making in Complex Contexts of Biomedical Research.

PubMed

Kempermann, Gerd

2017-01-01

The Cynefin scheme is a concept of knowledge management, originally devised to support decision making in management, but more generally applicable to situations, in which complexity challenges the quality of insight, prediction, and decision. Despite the fact that life itself, and especially the brain and its diseases, are complex to the extent that complexity could be considered their cardinal feature, complex problems in biomedicine are often treated as if they were actually not more than the complicated sum of solvable sub-problems. Because of the emergent properties of complex contexts this is not correct. With a set of clear criteria Cynefin helps to set apart complex problems from "simple/obvious," "complicated," "chaotic," and "disordered" contexts in order to avoid misinterpreting the relevant causality structures. The distinction comes with the insight, which specific kind of knowledge is possible in each of these categories and what are the consequences for resulting decisions and actions. From student's theses over the publication and grant writing process to research politics, misinterpretation of complexity can have problematic or even dangerous consequences, especially in clinical contexts. Conceptualization of problems within a straightforward reference language like Cynefin improves clarity and stringency within projects and facilitates communication and decision-making about them.

The effects of critical thinking instruction on training complex decision making.

PubMed

Helsdingen, Anne S; van den Bosch, Karel; van Gog, Tamara; van Merriënboer, Jeroen J G

2010-08-01

Two field studies assessed the effects of critical thinking instruction on training and transfer of a complex decision-making skill. Critical thinking instruction is based on studies of how experienced decision makers approach complex problems. Participants conducted scenario-based exercises in both simplified (Study I) and high-fidelity (Study 2) training environments. In both studies, half of the participants received instruction in critical thinking. The other half conducted the same exercises but without critical thinking instruction. After the training, test scenarios were administered to both groups. The first study showed that critical thinking instruction enhanced decision outcomes during both training and the test. In the second study, critical thinking instruction benefited both decision outcomes and processes, specifically on the transfer to untrained problems. The results suggest that critical thinking instruction improves decision strategy and enhances understanding of the general principles of the domain. The results of this study warrant the implementation of critical thinking instruction in training programs for professional decision makers that have to operate in complex and highly interactive, dynamic environments.

Offside Decisions by Expert Assistant Referees in Association Football: Perception and Recall of Spatial Positions in Complex Dynamic Events

ERIC Educational Resources Information Center

Gilis, Bart; Helsen, Werner; Catteeuw, Peter; Wagemans, Johan

2008-01-01

This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Federation Internationale de Football Association (FIFA; n = 29)…

Improving "At-Action" Decision-Making in Team Sports through a Holistic Coaching Approach

ERIC Educational Resources Information Center

Light, Richard L.; Harvey, Stephen; Mouchet, Alain

2014-01-01

This article draws on Game Sense pedagogy and complex learning theory (CLT) to make suggestions for improving decision-making ability in team sports by adopting a holistic approach to coaching with a focus on decision-making "at-action". It emphasizes the complexity of decision-making and the need to focus on the game as a whole entity,…

The Design and Use of Decision Support Systems by Academic Departments. AIR 1987 Annual Forum Paper.

ERIC Educational Resources Information Center

Johnson, F. Craig

The design and use of a departmental decision support system at Florida State University are described from the perspective of a department head. The decisions selected for study are ones of adequacy, equitability, quality, efficiency, and consistency. The complexity of the decision is related to the complexity of the support system. The major…

Information Search and Decision Making: The Effects of Age and Complexity on Strategy Use

PubMed Central

Queen, Tara L.; Hess, Thomas M.; Ennis, Gilda E.; Dowd, Keith; Grühn, Daniel

2012-01-01

The impact of task complexity on information search strategy and decision quality was examined in a sample of 135 young, middle-aged, and older adults. We were particularly interested in the competing roles of fluid cognitive ability and domain knowledge and experience, with the former being a negative influence and the latter being a positive influence on older adults’ performance. Participants utilized two decision matrices, which varied in complexity, regarding a consumer purchase. Using process tracing software and an algorithm developed to assess decision strategy, we recorded search behavior, strategy selection, and final decision. Contrary to expectations, older adults were not more likely than the younger age groups to engage in information-minimizing search behaviors in response to increases in task complexity. Similarly, adults of all ages used comparable decision strategies and adapted their strategies to the demands of the task. We also examined decision outcomes in relation to participants’ preferences. Overall, it seems that older adults utilize simpler sets of information primarily reflecting the most valued attributes in making their choice. The results of this study suggest that older adults are adaptive in their approach to decision making and this ability may benefit from accrued knowledge and experience. PMID:22663157

In vivo anti-radiation activities of the Ulva pertusa polysaccharides and polysaccharide-iron(III) complex.

PubMed

Shi, Jinming; Cheng, Cuilin; Zhao, Haitian; Jing, Jing; Gong, Ning; Lu, Weihong

2013-09-01

Polysaccharides with different molecular weights were extracted from Ulva pertusa and fractionated by ultrafiltration. Iron(III) complex of the low molecular-weight U. pertusa polysaccharides were synthesized. Atomic absorption spectrum showed that the iron content of iron(III)-polysaccharide complex was 27.4%. The comparison between U. pertusa polysaccharides and their iron(III) complex showed that iron chelating altered the structural characteristics of the polysaccharides. The bioactivity analysis showed that polysaccharide with low molecular weight was more effective than polysaccharide with high molecular weight in protecting mice from radiation induced damages on bone marrow cells and immune system. Results also proved that the anti-radiation and anti-oxidative activity of iron(III) complex of low molecular-weight polysaccharides were not less than that of low molecular-weight polysaccharides. Copyright © 2013 Elsevier B.V. All rights reserved.

Key concepts relevant to quality of complex and shared decision-making in health care: a literature review.

PubMed

Dy, Sydney M; Purnell, Tanjala S

2012-02-01

High-quality provider-patient decision-making is key to quality care for complex conditions. We performed an analysis of key elements relevant to quality and complex, shared medical decision-making. Based on a search of electronic databases, including Medline and the Cochrane Library, as well as relevant articles' reference lists, reviews of tools, and annotated bibliographies, we developed a list of key concepts and applied them to a decision-making example. Key concepts identified included provider competence, trustworthiness, and cultural competence; communication with patients and families; information quality; patient/surrogate competence; and roles and involvement. We applied this concept list to a case example, shared decision-making for live donor kidney transplantation, and identified the likely most important concepts as provider and cultural competence, information quality, and communication with patients and families. This concept list may be useful for conceptualizing the quality of complex shared decision-making and in guiding research in this area. Copyright © 2011 Elsevier Ltd. All rights reserved.

Re-Construction of Reference Population and Generating Weights by Decision Tree

DTIC Science & Technology

2017-07-21

2017 Claflin University Orangeburg, SC 29115 DEFENSE EQUAL OPPORTUNITY MANAGEMENT INSTITUTE RESEARCH, DEVELOPMENT, AND STRATEGIC...Original Dataset 32 List of Figures in Appendix B Figure 1: Flow and Components of Project 20 Figure 2: Decision Tree 31 Figure 3: Effects of Weight...can compare the sample data. The dataset of this project has the reference population on unit level for group and gender, which is in red-dotted box

The System of Objectified Judgement Analysis (SOJA). A tool in rational drug selection for formulary inclusion.

PubMed

Janknegt, R; Steenhoek, A

1997-04-01

Rational drug selection for formulary purposes is important. Besides rational selection criteria, other factors play a role in drug decision making, such as emotional, personal financial and even unconscious criteria. It is agreed that these factors should be excluded as much as possible in the decision making process. A model for drug decision making for formulary purposes is described, the System of Objectified Judgement Analysis (SOJA). In the SOJA method, selection criteria for a given group of drugs are prospectively defined and the extent to which each drug fulfils the requirements for each criterion is determined. Each criterion is given a relative weight, i.e. the more important a given selection criterion is considered, the higher the relative weight. Both the relative scores for each drug per selection criterion and the relative weight of each criterion are determined by a panel of experts in this field. The following selection criteria are applied in all SOJA scores: clinical efficacy, incidence and severity of adverse effects, dosage frequency, drug interactions, acquisition cost, documentation, pharmacokinetics and pharmaceutical aspects. Besides these criteria, group specific criteria are also used, such as development of resistance when a SOJA score was made for antimicrobial agents. The relative weight that is assigned to each criterion will always be a subject of discussion. Therefore, interactive software programs for use on a personal computer have been developed, in which the user of the system may enter their own personal relative weight to each selection criterion and make their own personal SOJA score. The main advantage of the SOJA method is that all nonrational selection criteria are excluded and that drug decision making is based solely on rational criteria. The use of the interactive SOJA discs makes the decision process fully transparent as it becomes clear on which criteria and weighting decisions are based. We have seen that the use of this method for drug decision making greatly aids the discussion in the formulary committee, as discussion becomes much more concrete. The SOJA method is time dependent. Documentation on most products is still increasing and the score for this criterion will therefore change continuously. New products are introduced and prices are also subject to change. To overcome the time-dependence of the SOJA method, regular updates of interactive software programs are being made, in which changes in acquisition cost, documentation or a different weighting of criteria are included, as well as newly introduced products. The possibility of changing the official acquisition cost into the actual purchasing costs for the hospital in question provides a tailor-made interactive program.

Biased and unbiased perceptual decision-making on vocal emotions.

PubMed

Dricu, Mihai; Ceravolo, Leonardo; Grandjean, Didier; Frühholz, Sascha

2017-11-24

Perceptual decision-making on emotions involves gathering sensory information about the affective state of another person and forming a decision on the likelihood of a particular state. These perceptual decisions can be of varying complexity as determined by different contexts. We used functional magnetic resonance imaging and a region of interest approach to investigate the brain activation and functional connectivity behind two forms of perceptual decision-making. More complex unbiased decisions on affective voices recruited an extended bilateral network consisting of the posterior inferior frontal cortex, the orbitofrontal cortex, the amygdala, and voice-sensitive areas in the auditory cortex. Less complex biased decisions on affective voices distinctly recruited the right mid inferior frontal cortex, pointing to a functional distinction in this region following decisional requirements. Furthermore, task-induced neural connectivity revealed stronger connections between these frontal, auditory, and limbic regions during unbiased relative to biased decision-making on affective voices. Together, the data shows that different types of perceptual decision-making on auditory emotions have distinct patterns of activations and functional coupling that follow the decisional strategies and cognitive mechanisms involved during these perceptual decisions.

Flood control project selection using an interval type-2 entropy weight with interval type-2 fuzzy TOPSIS

NASA Astrophysics Data System (ADS)

Zamri, Nurnadiah; Abdullah, Lazim

2014-06-01

Flood control project is a complex issue which takes economic, social, environment and technical attributes into account. Selection of the best flood control project requires the consideration of conflicting quantitative and qualitative evaluation criteria. When decision-makers' judgment are under uncertainty, it is relatively difficult for them to provide exact numerical values. The interval type-2 fuzzy set (IT2FS) is a strong tool which can deal with the uncertainty case of subjective, incomplete, and vague information. Besides, it helps to solve for some situations where the information about criteria weights for alternatives is completely unknown. Therefore, this paper is adopted the information interval type-2 entropy concept into the weighting process of interval type-2 fuzzy TOPSIS. This entropy weight is believed can effectively balance the influence of uncertainty factors in evaluating attribute. Then, a modified ranking value is proposed in line with the interval type-2 entropy weight. Quantitative and qualitative factors that normally linked with flood control project are considered for ranking. Data in form of interval type-2 linguistic variables were collected from three authorised personnel of three Malaysian Government agencies. Study is considered for the whole of Malaysia. From the analysis, it shows that diversion scheme yielded the highest closeness coefficient at 0.4807. A ranking can be drawn using the magnitude of closeness coefficient. It was indicated that the diversion scheme recorded the first rank among five causes.

Aggregation operators of neutrosophic linguistic numbers for multiple attribute group decision making.

PubMed

Ye, Jun

2016-01-01

Based on the concept of neutrosophic linguistic numbers (NLNs) in symbolic neutrosophic theory presented by Smarandache in 2015, the paper firstly proposes basic operational laws of NLNs and the expected value of a NLN to rank NLNs. Then, we propose the NLN weighted arithmetic average (NLNWAA) and NLN weighted geometric average (NLNWGA) operators and discuss their properties. Further, we establish a multiple attribute group decision-making (MAGDM) method by using the NLNWAA and NLNWGA operators under NLN environment. Finally, an illustrative example on a decision-making problem of manufacturing alternatives in the flexible manufacturing system is given to show the application of the proposed MAGDM method.

Releases of whooping cranes to the Florida nonmigratory flock: a structured decision-making approach: report to the International Whooping Crane Recovery Team, September 22, 2008

USGS Publications Warehouse

Moore, Clinton T.; Converse, Sarah J.; Folk, Martin J.; Boughton, Robin; Brooks, Bill; French, John B.; O'Meara, Timothy; Putnam, Michael; Rodgers, James; Spalding, Marilyn

2008-01-01

We used a structured decision-making approach to inform the decision of whether the Florida Fish and Wildlife Conservation Commission should request of the International Whooping Crane Recovery Team that additional whooping crane chicks be released into the Florida Non-Migratory Population (FNMP). Structured decision-making is an application of decision science that strives to produce transparent, replicable, and defensible decisions that recognize the appropriate roles of management policy and science in decision-making. We present a multi-objective decision framework, where management objectives include successful establishment of a whooping crane population in Florida, minimization of costs, positive public relations, information gain, and providing a supply of captive-reared birds to alternative crane release projects, such as the Eastern Migratory Population. We developed models to predict the outcome relative to each of these objectives under 29 different scenarios of the release methodology used from 1993 to 2004, including options of no further releases and variable numbers of releases per year over the next 5-30 years. In particular, we developed a detailed set of population projection models, which make substantially different predictions about the probability of successful establishment of the FNMP. We used expert elicitation to develop prior model weights (measures of confidence in population model predictions); the results of the population model weighting and modelaveraging exercise indicated that the probability of successful establishment of the FNMP ranged from 9% if no additional releases are made, to as high as 41% with additional releases. We also used expert elicitation to develop weights (relative values) on the set of identified objectives, and we then used a formal optimization technique for identifying the optimal decision, which considers the tradeoffs between objectives. The optimal decision was identified as release of 3 cohorts (24 birds) per year over the next 10 years. However, any decision that involved release of 1-3 cohorts (8-24 birds) per year over the next 5 to 20 years, as well as decisions that involve skipping releases in every other year, performed better in our analysis than the alternative of no further releases. These results were driven by the relatively high objective weights that experts placed on the population objective (i.e., successful establishment of the FNMP) and the information gain objective (where releases are expected to accelerate learning on what was identified as a primary uncertainty: the demographic performance of wild-hatched birds). Additional considerations that were not formally integrated into the analysis are also discussed.

Understanding Complex Adaptive Systems by Playing Games

ERIC Educational Resources Information Center

van Bilsen, Arthur; Bekebrede, Geertje; Mayer, Igor

2010-01-01

While educators teach their students about decision making in complex environments, managers have to deal with the complexity of large projects on a daily basis. To make better decisions it is assumed, that the latter would benefit from better understanding of complex phenomena, as do students as the professionals of the future. The goal of this…

Food availability/convenience and obesity.

PubMed

Gordon-Larsen, Penny

2014-11-01

Neighborhood environments have received considerable attention in recent local, state, and national obesity prevention initiatives, with a particular focus on food deserts, or areas with poor access to healthy foods. Yet, there are inconsistencies in the evidence base, suggesting a nuanced association between neighborhood environment, food availability, diet behaviors, and obesity. There is heterogeneity in associations between environmental exposures and health outcomes across race/ethnicity, gender, region, and urbanicity, which results in complexity in the interpretation of findings. There are several limitations in the literature, including a predominance of cross-sectional studies, reliance on commercial business listings, lack of attention to the process by which diet resources are established and expanded within neighborhoods and the potential for individuals to selectively migrate to locate near such facilities, a predominant focus on residential neighborhoods, and lack of information about the decision-making process underlying purchasing patterns. More research is needed to address the complexity of individual-level residential decision making as well as the purposeful placement of food environment resources across social and geographic space using longitudinal data and complex statistical approaches. In addition, improvements in data quality and depth related to food access and availability are needed, including behavioral data on purchase patterns and interactions with the food environment, and greater attention to heterogeneity across subpopulations. As policy changes to the food environment move forward, it is critical that there is rigorous and scientific evaluation of environmental changes and their impact on individual-level diet choices and behaviors, and their further influence on body weight. © 2014 American Society for Nutrition.

Clinical decision-making by midwives: managing case complexity.

PubMed

Cioffi, J; Markham, R

1997-02-01

In making clinical judgements, it is argued that midwives use 'shortcuts' or heuristics based on estimated probabilities to simplify the decision-making task. Midwives (n = 30) were given simulated patient assessment situations of high and low complexity and were required to think aloud. Analysis of verbal protocols showed that subjective probability judgements (heuristics) were used more frequently in the high than low complexity case and predominated in the last quarter of the assessment period for the high complexity case. 'Representativeness' was identified more frequently in the high than in the low case, but was the dominant heuristic in both. Reports completed after each simulation suggest that heuristics based on memory for particular conditions affect decisions. It is concluded that midwives use heuristics, derived mainly from their clinical experiences, in an attempt to save cognitive effort and to facilitate reasonably accurate decisions in the decision-making process.

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

Differentiation of parenteral anticoagulants in the prevention and treatment of venous thromboembolism.

PubMed

Fareed, Jawed; Adiguzel, Cafer; Thethi, Indermohan

2011-03-28

The prevention of venous thromboembolism has been identified as a leading priority in hospital safety. Recommended parenteral anticoagulant agents with different indications for the prevention and treatment of venous thromboembolism include unfractionated heparin, low-molecular-weight heparins and fondaparinux. Prescribing decisions in venous thromboembolism management may seem complex due to the large range of clinical indications and patient types, and the range of anticoagulants available. MEDLINE and EMBASE databases were searched to identify relevant original articles. Low-molecular-weight heparins have nearly replaced unfractionated heparin as the gold standard antithrombotic agent. Low-molecular-weight heparins currently available in the US are enoxaparin, dalteparin, and tinzaparin. Each low-molecular-weight heparin is a distinct pharmacological entity with different licensed indications and available clinical evidence. Enoxaparin is the only low-molecular-weight heparin that is licensed for both venous thromboembolism prophylaxis and treatment. Enoxaparin also has the largest body of clinical evidence supporting its use across the spectrum of venous thromboembolism management and has been used as the reference standard comparator anticoagulant in trials of new anticoagulants. As well as novel oral anticoagulant agents, biosimilar and/or generic low-molecular-weight heparins are now commercially available. Despite similar anticoagulant properties, studies report differences between the branded and biosimilar and/or generic agents and further clinical studies are required to support the use of biosimilar low-molecular-weight heparins. The newer parenteral anticoagulant, fondaparinux, is now also licensed for venous thromboembolism prophylaxis in surgical patients and the treatment of acute deep-vein thrombosis; clinical experience with this anticoagulant is expanding. Parenteral anticoagulants should be prescribed in accordance with recommended dose regimens for each clinical indication, based on the available clinical evidence for each agent to assure optimal safety and efficacy.

A new decision sciences for complex systems.

PubMed

Lempert, Robert J

2002-05-14

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

Young adults, technology, and weight loss: a focus group study.

PubMed

Stephens, Janna; Moscou-Jackson, Gyasi; Allen, Jerilyn K

2015-01-01

Overweight and obesity are a major concern in young adults. Technology has been integrated into many weight loss interventions; however little is known about the use of this technology in young adults. The purpose of this study was to explore through focus group sessions the opinions of young adults on the use of technology for weight loss. A total of 17 young adults, between 18 and 25 years of age, participated in three focus group sessions. Major results indicated that young adults have very little knowledge on the use of Smartphone technology for weight loss but would like to use this type of technology to help them lose weight. Results also indicated that young adults struggle to make healthy food choices and have priorities that outweigh exercise and they need support and guidance to make better decisions. In conclusion, young adults would be open to using Smartphone technology for weight loss but also need feedback and guidance to help make healthy decisions.

Young Adults, Technology, and Weight Loss: A Focus Group Study

PubMed Central

Moscou-Jackson, Gyasi; Allen, Jerilyn K.

2015-01-01

Overweight and obesity are a major concern in young adults. Technology has been integrated into many weight loss interventions; however little is known about the use of this technology in young adults. The purpose of this study was to explore through focus group sessions the opinions of young adults on the use of technology for weight loss. A total of 17 young adults, between 18 and 25 years of age, participated in three focus group sessions. Major results indicated that young adults have very little knowledge on the use of Smartphone technology for weight loss but would like to use this type of technology to help them lose weight. Results also indicated that young adults struggle to make healthy food choices and have priorities that outweigh exercise and they need support and guidance to make better decisions. In conclusion, young adults would be open to using Smartphone technology for weight loss but also need feedback and guidance to help make healthy decisions. PMID:25789170

Identification of key factors in consumers' adoption behavior of intelligent medical terminals based on a hybrid modified MADM model for product improvement.

PubMed

Liu, Yupeng; Chen, Yifei; Tzeng, Gwo-Hshiung

2017-09-01

As a new application technology of the Internet of Things (IoT), intelligent medical treatment has attracted the attention of both nations and industries through its promotion of medical informatisation, modernisation, and intelligentisation. Faced with a wide variety of intelligent medical terminals, consumers may be affected by various factors when making purchase decisions. To examine and evaluate the key influential factors (and their interrelationships) of consumer adoption behavior for improving and promoting intelligent medical terminals toward achieving set aspiration level in each dimension and criterion. A hybrid modified Multiple Attribute Decision-Making (MADM) model was used for this study, based on three components: (1) the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique, to build an influential network relationship map (INRM) at both 'dimensions' and 'criteria' levels; (2) the DEMATEL-based analytic network process (DANP) method, to determine the interrelationships and influential weights among the criteria and identify the source-influential factors; and (3) the modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, to evaluate and improve for reducing the performance gaps to meet the consumers' needs for continuous improvement and sustainable products-development. First, a consensus on the influential factors affecting consumers' adoption of intelligent medical terminals was collected from experts' opinion in practical experience. Next, the interrelationships and influential weights of DANP among dimensions/criteria based on the DEMATEL technique were determined. Finally, two intelligent medicine bottles (AdhereTech, A 1 alternative; and Audio/Visual Alerting Pillbox, A 2 alternative) were reviewed as the terminal devices to verify the accuracy of the MADM model and evaluate its performance on each criterion for improving the total certification gaps by systematics according to the modified VIKOR method based on an INRM. In this paper, the criteria and dimensions used to improve the evaluation framework are validated. The systematic evaluation in index system is constructed on the basis of five dimensions and corresponding ten criteria. Influential weights of all criteria ranges from 0.037 to 0.152, which shows the rank of criteria importance. The evaluative framework were validated synthetically and scientifically. INRM (influential network relation map) was obtained from experts' opinion through DEMATEL technique shows complex interrelationship among factors. At the dimension level, the environmental dimension influences other dimensions the most, whereas the security dimension is most influenced by others. So the improvement order of environmental dimension is prior to security dimension. The newly constructed approach was still further validated by the results of the empirical case, where performance gap improvement strategies were analyzed for decision-makers. The modified VIKOR method was especially validated for solving real-world problems in intelligent medical terminal improvement processes. For this paper, A 1 performs better than A 2 , however, promotion mix, brand factor, and market environment are shortcomings faced by both A 1 and A 2 . In addition, A 2 should be improved in the wireless network technology, and the objective contact with a high degree of gaps. Based on the evaluation index system and the integrated model proposed here, decision-makers in enterprises can identify gaps when promoting intelligent medical terminals, from which they can get valuable advice to improve consumer adoption. Additionally, an INRM and the influential weights of DANP can be combined using the modified VIKOR method as integrated weightings to determine how to reduce gaps and provide the best improvement strategies for reaching set aspiration levels. Copyright © 2017 Elsevier B.V. All rights reserved.

The Multi-Attribute Group Decision-Making Method Based on Interval Grey Trapezoid Fuzzy Linguistic Variables.

PubMed

Yin, Kedong; Wang, Pengyu; Li, Xuemei

2017-12-13

With respect to multi-attribute group decision-making (MAGDM) problems, where attribute values take the form of interval grey trapezoid fuzzy linguistic variables (IGTFLVs) and the weights (including expert and attribute weight) are unknown, improved grey relational MAGDM methods are proposed. First, the concept of IGTFLV, the operational rules, the distance between IGTFLVs, and the projection formula between the two IGTFLV vectors are defined. Second, the expert weights are determined by using the maximum proximity method based on the projection values between the IGTFLV vectors. The attribute weights are determined by the maximum deviation method and the priorities of alternatives are determined by improved grey relational analysis. Finally, an example is given to prove the effectiveness of the proposed method and the flexibility of IGTFLV.

DRUG EVALUATION AND DECISION MAKING IN CATALONIA: DEVELOPMENT AND VALIDATION OF A METHODOLOGICAL FRAMEWORK BASED ON MULTI-CRITERIA DECISION ANALYSIS (MCDA) FOR ORPHAN DRUGS.

PubMed

Gilabert-Perramon, Antoni; Torrent-Farnell, Josep; Catalan, Arancha; Prat, Alba; Fontanet, Manel; Puig-Peiró, Ruth; Merino-Montero, Sandra; Khoury, Hanane; Goetghebeur, Mireille M; Badia, Xavier

2017-01-01

The aim of this study was to adapt and assess the value of a Multi-Criteria Decision Analysis (MCDA) framework (EVIDEM) for the evaluation of Orphan drugs in Catalonia (Catalan Health Service). The standard evaluation and decision-making procedures of CatSalut were compared with the EVIDEM methodology and contents. The EVIDEM framework was adapted to the Catalan context, focusing on the evaluation of Orphan drugs (PASFTAC program), during a Workshop with sixteen PASFTAC members. The criteria weighting was done using two different techniques (nonhierarchical and hierarchical). Reliability was assessed by re-test. The EVIDEM framework and methodology was found useful and feasible for Orphan drugs evaluation and decision making in Catalonia. All the criteria considered for the development of the CatSalut Technical Reports and decision making were considered in the framework. Nevertheless, the framework could improve the reporting of some of these criteria (i.e., "unmet needs" or "nonmedical costs"). Some Contextual criteria were removed (i.e., "Mandate and scope of healthcare system", "Environmental impact") or adapted ("population priorities and access") for CatSalut purposes. Independently of the weighting technique considered, the most important evaluation criteria identified for orphan drugs were: "disease severity", "unmet needs" and "comparative effectiveness", while the "size of the population" had the lowest relevance for decision making. Test-retest analysis showed weight consistency among techniques, supporting reliability overtime. MCDA (EVIDEM framework) could be a useful tool to complement the current evaluation methods of CatSalut, contributing to standardization and pragmatism, providing a method to tackle ethical dilemmas and facilitating discussions related to decision making.

Weighting Primary Care Patient Panel Size: A Novel Electronic Health Record-Derived Measure Using Machine Learning.

PubMed

Rajkomar, Alvin; Yim, Joanne Wing Lan; Grumbach, Kevin; Parekh, Ami

2016-10-14

Characterizing patient complexity using granular electronic health record (EHR) data regularly available to health systems is necessary to optimize primary care processes at scale. To characterize the utilization patterns of primary care patients and create weighted panel sizes for providers based on work required to care for patients with different patterns. We used EHR data over a 2-year period from patients empaneled to primary care clinicians in a single academic health system, including their in-person encounter history and virtual encounters such as telephonic visits, electronic messaging, and care coordination with specialists. Using a combination of decision rules and k-means clustering, we identified clusters of patients with similar health care system activity. Phenotypes with basic demographic information were used to predict future health care utilization using log-linear models. Phenotypes were also used to calculate weighted panel sizes. We identified 7 primary care utilization phenotypes, which were characterized by various combinations of primary care and specialty usage and were deemed clinically distinct by primary care physicians. These phenotypes, combined with age-sex and primary payer variables, predicted future primary care utilization with R 2 of .394 and were used to create weighted panel sizes. Individual patients' health care utilization may be useful for classifying patients by primary care work effort and for predicting future primary care usage.

Integrating evidence and individual preferences using a web-based multi-criteria decision analytic tool: an application to prostate cancer screening.

PubMed

Cunich, Michelle; Salkeld, Glenn; Dowie, Jack; Henderson, Joan; Bayram, Clare; Britt, Helena; Howard, Kirsten

2011-01-01

Annalisa© (AL) is a web-based decision-support template grounded in multi-criteria decision analysis (MCDA). It uses a simple expected value algorithm to calculate a score for each option by taking into account the individual's preferences for different criteria (as importance weights) and the evidence of the performance of each option on each criterion. Given the uncertainty surrounding the trade offs between benefits and harms for prostate cancer screening, this topic was chosen as the vehicle to introduce this new decision-support template. The aim of the study was to introduce a new decision-support template, AL, and to develop and pilot a decision-support tool for prostate cancer screening using it. A decision-support tool for prostate cancer screening (ALProst) was implemented in the AL template. ALProst incorporated evidence on both the benefits and the potential harms of prostate cancer screening (the 'attributes') from published randomized controlled trials (RCTs). Individual weights for each attribute were elicited during interviews. By combining the individual's preferences and the evidence, the best option for the user was identified on the basis of quantified scores. A convenience sample of computer-proficient primary-care physicians (general practitioners [GPs] in Australia) from the Sydney Metropolitan area (Australia) were invited to complete a face-to-face interview involving the decision-support tool. Preference for undergoing prostate-specific antigen testing for prostate cancer, both personally and for their patients, was sought prior to seeing the tool. After gaining hands-on experience with using the tool, GPs were asked to comment on the merits of the template and the tool. Preference for presenting the benefits of prostate cancer screening as the relative or absolute risk reduction in prostate cancer-specific mortality was also sought. Of 60 GPs approached, ten (six men and four women) completed an interview (16.7% response rate). Most GPs agreed/strongly agreed with positive statements about the ease with which they could use AL (seven GPs), and understand the information in, and format of, AL (nine and eight, respectively). Eight agreed/strongly agreed that ALProst would be a useful tool for discussing prostate cancer screening with their patients. GPs were also asked to nominate difficult clinical decisions that they, and their patients, have had to make; responses included cancer screening (including prostate cancer); treating patients with multiple illnesses/diseases; managing multiple cardiovascular disease risk factors; and managing patients who are receiving multiple medications. The common element was the need to consider multiple factors in making these complex decisions. AL is distinguishable from most other decision-support templates available today by its underlying conceptual framework, MCDA, and its power to combine individual preferences with evidence to derive the best option for the user quantitatively. It therefore becomes potentially useful for all decisions at all levels in the healthcare system. Moreover, it will provide a universal graphic 'language' that can overcome the burden to patients of encountering a plethora of widely varying decision aids for different conditions during their lifetime.

A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge.

PubMed

Rahman, M Azizur; Rusteberg, Bernd; Gogu, R C; Lobo Ferreira, J P; Sauter, Martin

2012-05-30

This study reports the development of a new spatial multi-criteria decision analysis (SMCDA) software tool for selecting suitable sites for Managed Aquifer Recharge (MAR) systems. The new SMCDA software tool functions based on the combination of existing multi-criteria evaluation methods with modern decision analysis techniques. More specifically, non-compensatory screening, criteria standardization and weighting, and Analytical Hierarchy Process (AHP) have been combined with Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). This SMCDA tool may be implemented with a wide range of decision maker's preferences. The tool's user-friendly interface helps guide the decision maker through the sequential steps for site selection, those steps namely being constraint mapping, criteria hierarchy, criteria standardization and weighting, and criteria overlay. The tool offers some predetermined default criteria and standard methods to increase the trade-off between ease-of-use and efficiency. Integrated into ArcGIS, the tool has the advantage of using GIS tools for spatial analysis, and herein data may be processed and displayed. The tool is non-site specific, adaptive, and comprehensive, and may be applied to any type of site-selection problem. For demonstrating the robustness of the new tool, a case study was planned and executed at Algarve Region, Portugal. The efficiency of the SMCDA tool in the decision making process for selecting suitable sites for MAR was also demonstrated. Specific aspects of the tool such as built-in default criteria, explicit decision steps, and flexibility in choosing different options were key features, which benefited the study. The new SMCDA tool can be augmented by groundwater flow and transport modeling so as to achieve a more comprehensive approach to the selection process for the best locations of the MAR infiltration basins, as well as the locations of recovery wells and areas of groundwater protection. The new spatial multicriteria analysis tool has already been implemented within the GIS based Gabardine decision support system as an innovative MAR planning tool. Copyright © 2012 Elsevier Ltd. All rights reserved.

Autonomy, religion and clinical decisions: findings from a national physician survey

PubMed Central

Lawrence, R E; Curlin, F A

2010-01-01

Background Patient autonomy has been promoted as the most important principle to guide difficult clinical decisions. To examine whether practising physicians indeed value patient autonomy above other considerations, physicians were asked to weight patient autonomy against three other criteria that often influence doctors’ decisions. Associations between physicians’ religious characteristics and their weighting of the criteria were also examined. Methods Mailed survey in 2007 of a stratified random sample of 1000 US primary care physicians, selected from the American Medical Association masterfile. Physicians were asked how much weight should be given to the following: (1) the patient’s expressed wishes and values, (2) the physician’s own judgment about what is in the patient’s best interest, (3) standards and recommendations from professional medical bodies and (4) moral guidelines from religious traditions. Results Response rate 51% (446/879). Half of physicians (55%) gave the patient’s expressed wishes and values “the highest possible weight”. In comparative analysis, 40% gave patient wishes more weight than the other three factors, and 13% ranked patient wishes behind some other factor. Religious doctors tended to give less weight to the patient’s expressed wishes. For example, 47% of doctors with high intrinsic religious motivation gave patient wishes the “highest possible weight”, versus 67% of those with low (OR 0.5; 95% CI 0.3 to 0.8). Conclusions Doctors believe patient wishes and values are important, but other considerations are often equally or more important. This suggests that patient autonomy does not guide physicians’ decisions as much as is often recommended in the ethics literature. PMID:19332575

Formal Process Modeling to Improve Human Decision-Making in Test and Evaluation Acoustic Range Control

DTIC Science & Technology

2017-09-01

AVAILABILITY STATEMENT Approved for public release. Distribution is unlimited. 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Test and...ambiguities and identify high -value decision points? This thesis explores how formalization of these experience-based decisions as a process model...representing a T&E event may reveal high -value decision nodes where certain decisions carry more weight or potential for impacts to a successful test. The

Molecular structure of the pyruvate dehydrogenase complex from Escherichia coli K-12.

PubMed

Vogel, O; Hoehn, B; Henning, U

1972-06-01

The pyruvate dehydrogenase core complex from E. coli K-12, defined as the multienzyme complex that can be obtained with a unique polypeptide chain composition, has a molecular weight of 3.75 x 10(6). All results obtained agree with the following numerology. The core complex consists of 48 polypeptide chains. There are 16 chains (molecular weight = 100,000) of the pyruvate dehydrogenase component, 16 chains (molecular weight = 80,000) of the dihydrolipoamide dehydrogenase component, and 16 chains (molecular weight = 56,000) of the dihydrolipoamide dehydrogenase component. Usually, but not always, pyruvate dehydrogenase complex is produced in vivo containing at least 2-3 mol more of dimers of the pyruvate dehydrogenase component than the stoichiometric ratio with respect to the core complex. This "excess" component is bound differently than are the eight dimers in the core complex.

Assessment of Unconscious Decision Aids Applied to Complex Patient-Centered Medical Decisions

PubMed Central

Manigault, Andrew Wilhelm; Whillock, Summer Rain

2015-01-01

Background To improve patient health, recent research urges for medical decision aids that are designed to enhance the effectiveness of specific medically related decisions. Many such decisions involve complex information, and decision aids that independently use deliberative (analytical and slower) or intuitive (more affective and automatic) cognitive processes for such decisions result in suboptimal decisions. Unconscious thought can arguably use both intuitive and deliberative (slow and analytic) processes, and this combination may further benefit complex patient (or practitioner) decisions as medical decision aids. Indeed, mounting research demonstrates that individuals render better decisions generally if they are distracted from thinking consciously about complex information after it is presented (but can think unconsciously), relative to thinking about that information consciously or not at all. Objective The current research tested whether the benefits of unconscious thought processes can be replicated using an Internet platform for a patient medical decision involving complex information. This research also explored the possibility that judgments reported after a period of unconscious thought are actually the result of a short period of conscious deliberation occurring during the decision report phase. Methods A total of 173 participants in a Web-based experiment received information about four medical treatments, the best (worst) associated with mostly positive (negative) side-effects/attributes and the others with equal positive-negative ratios. Next, participants were either distracted for 3 minutes (unconscious thought), instructed to think about the information for 3 minutes (conscious thought), or moved directly to the decision task (immediate decision). Finally, participants reported their choice of, and attitudes toward, the treatments while experiencing high, low, or no cognitive load, which varied their ability to think consciously while reporting judgments. Cognitive load was manipulated by having participants memorize semi-random (high), line structured (low), or no dot patterns and recall these intermittently with their decision reports. Overall then, participants were randomly assigned to the conditions of a 3 (thought condition) by 3 (cognitive-load level) between-subjects design. Results A logistic regression analysis indicated that the odds of participants choosing the best treatment were 2.25 times higher in the unconscious-thought condition compared to the immediate-decision condition (b=.81, Wald=4.32, P=.04, 95% CI 1.048-4.836), and 2.39 times greater compared to the conscious-thought condition (b=.87, Wald=4.87, P=.027, 95% CI 1.103-5.186). No difference was observed between the conscious-thought condition compared to the immediate-decision condition, and cognitive load manipulations did not affect choices or alter the above finding. Conclusions This research demonstrates a plausible benefit of unconscious thinking as a decision aid for complex medical decisions, and represents the first use of unconscious thought processes as a patient-centered medical decision aid. Further, the quality of decisions reached unconsciously does not appear to be affected by the amount of cognitive load participants experienced. PMID:25677337

Information search and decision making: effects of age and complexity on strategy use.

PubMed

Queen, Tara L; Hess, Thomas M; Ennis, Gilda E; Dowd, Keith; Grühn, Daniel

2012-12-01

The impact of task complexity on information search strategy and decision quality was examined in a sample of 135 young, middle-aged, and older adults. We were particularly interested in the competing roles of fluid cognitive ability and domain knowledge and experience, with the former being a negative influence and the latter being a positive influence on older adults' performance. Participants utilized 2 decision matrices, which varied in complexity, regarding a consumer purchase. Using process tracing software and an algorithm developed to assess decision strategy, we recorded search behavior, strategy selection, and final decision. Contrary to expectations, older adults were not more likely than the younger age groups to engage in information-minimizing search behaviors in response to increases in task complexity. Similarly, adults of all ages used comparable decision strategies and adapted their strategies to the demands of the task. We also examined decision outcomes in relation to participants' preferences. Overall, it seems that older adults utilize simpler sets of information primarily reflecting the most valued attributes in making their choice. The results of this study suggest that older adults are adaptive in their approach to decision making and that this ability may benefit from accrued knowledge and experience. 2013 APA, all rights reserved

Robust Sensitivity Analysis for Multi-Attribute Deterministic Hierarchical Value Models

DTIC Science & Technology

2002-03-01

such as weighted sum method, weighted 5 product method, and the Analytic Hierarchy Process ( AHP ). This research focuses on only weighted sum...different groups. They can be termed as deterministic, stochastic, or fuzzy multi-objective decision methods if they are classified according to the...weighted product model (WPM), and analytic hierarchy process ( AHP ). His method attempts to identify the most important criteria weight and the most

Multi-Criteria Decision-Making Methods and Their Applications for Human Resources

NASA Astrophysics Data System (ADS)

D'Urso, M. G.; Masi, D.

2015-05-01

Both within the formation field and the labor market Multi-Criteria Decision Methods (MCDM) provide a significant support to the management of human resources in which the best choice among several alternatives can be very complex. This contribution addresses fuzzy logic in multi-criteria decision techniques since they have several applications in the management of human resources with the advantage of ruling out mistakes due to the subjectivity of the person in charge of making a choice. Evaluating educational achievements as well as the professional profile of a technician more suitable for a job in a firm, industry or a professional office are valuable examples of fuzzy logic. For all of the previous issues subjectivity is a fundamental aspect so that fuzzy logic, due to the very meaning of the word fuzzy, should be the preferred choice. However, this is not sufficient to justify its use; fuzzy technique has to make the system of evaluation and choice more effective and objective. The methodological structure of the multi-criteria fuzzy criterion is hierarchic and allows one to select the best alternatives in all those cases in which several alternatives are possible; thus, the optimal choice can be achieved by analyzing the different scopes of each criterion and sub-criterion as well as the relevant weights.

Decision making generalized by a cumulative probability weighting function

NASA Astrophysics Data System (ADS)

dos Santos, Lindomar Soares; Destefano, Natália; Martinez, Alexandre Souto

2018-01-01

Typical examples of intertemporal decision making involve situations in which individuals must choose between a smaller reward, but more immediate, and a larger one, delivered later. Analogously, probabilistic decision making involves choices between options whose consequences differ in relation to their probability of receiving. In Economics, the expected utility theory (EUT) and the discounted utility theory (DUT) are traditionally accepted normative models for describing, respectively, probabilistic and intertemporal decision making. A large number of experiments confirmed that the linearity assumed by the EUT does not explain some observed behaviors, as nonlinear preference, risk-seeking and loss aversion. That observation led to the development of new theoretical models, called non-expected utility theories (NEUT), which include a nonlinear transformation of the probability scale. An essential feature of the so-called preference function of these theories is that the probabilities are transformed by decision weights by means of a (cumulative) probability weighting function, w(p) . We obtain in this article a generalized function for the probabilistic discount process. This function has as particular cases mathematical forms already consecrated in the literature, including discount models that consider effects of psychophysical perception. We also propose a new generalized function for the functional form of w. The limiting cases of this function encompass some parametric forms already proposed in the literature. Far beyond a mere generalization, our function allows the interpretation of probabilistic decision making theories based on the assumption that individuals behave similarly in the face of probabilities and delays and is supported by phenomenological models.

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

PubMed Central

Wichary, Szymon; Smolen, Tomasz

2016-01-01

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

Teachers' Decisions about Mathematics Tasks When Planning

ERIC Educational Resources Information Center

Sullivan, Peter; Clarke, David; Clarke, Doug; Roche, Anne

2013-01-01

At some stage when planning, teachers make decisions about the mathematics tasks they will pose and how they will structure lessons. It seems, though, that these decisions are complex, and that this complexity has been underestimated by curriculum developers and teacher educators. The following is a report of data collection that simulated some of…

Direct migration motion estimation and mode decision to decoder for a low-complexity decoder Wyner-Ziv video coding

NASA Astrophysics Data System (ADS)

Lei, Ted Chih-Wei; Tseng, Fan-Shuo

2017-07-01

This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.

The Effects of Differential Goal Weights on the Performance of a Complex Financial Task.

ERIC Educational Resources Information Center

Edmister, Robert O.; Locke, Edwin A.

1987-01-01

Determined whether people could obtain outcomes on a complex task that would be in line with differential goal weights corresponding to different aspects of the task. Bank lending officers were run through lender-simulation exercises. Five performance goals were weighted. Demonstrated effectiveness of goal setting with complex tasks, using group…

Prediction model of critical weight loss in cancer patients during particle therapy.

PubMed

Zhang, Zhihong; Zhu, Yu; Zhang, Lijuan; Wang, Ziying; Wan, Hongwei

2018-01-01

The objective of this study is to investigate the predictors of critical weight loss in cancer patients receiving particle therapy, and build a prediction model based on its predictive factors. Patients receiving particle therapy were enroled between June 2015 and June 2016. Body weight was measured at the start and end of particle therapy. Association between critical weight loss (defined as >5%) during particle therapy and patients' demographic, clinical characteristic, pre-therapeutic nutrition risk screening (NRS 2002) and BMI were evaluated by logistic regression and decision tree analysis. Finally, 375 cancer patients receiving particle therapy were included. Mean weight loss was 0.55 kg, and 11.5% of patients experienced critical weight loss during particle therapy. The main predictors of critical weight loss during particle therapy were head and neck tumour location, total radiation dose ≥70 Gy on the primary tumour, and without post-surgery, as indicated by both logistic regression and decision tree analysis. Prediction model that includes tumour locations, total radiation dose and post-surgery had a good predictive ability, with the area under receiver operating characteristic curve 0.79 (95% CI: 0.71-0.88) and 0.78 (95% CI: 0.69-0.86) for decision tree and logistic regression model, respectively. Cancer patients with head and neck tumour location, total radiation dose ≥70 Gy and without post-surgery were at higher risk of critical weight loss during particle therapy, and early intensive nutrition counselling or intervention should be target at this population. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Selecting an Architecture for a Safety-Critical Distributed Computer System with Power, Weight and Cost Considerations

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2014-01-01

This report presents an example of the application of multi-criteria decision analysis to the selection of an architecture for a safety-critical distributed computer system. The design problem includes constraints on minimum system availability and integrity, and the decision is based on the optimal balance of power, weight and cost. The analysis process includes the generation of alternative architectures, evaluation of individual decision criteria, and the selection of an alternative based on overall value. In this example presented here, iterative application of the quantitative evaluation process made it possible to deliberately generate an alternative architecture that is superior to all others regardless of the relative importance of cost.

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

PubMed

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

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Molecular Structure of the Pyruvate Dehydrogenase Complex from Escherichia coli K-12

PubMed Central

Vogel, Otto; Hoehn, Barbara; Henning, Ulf

1972-01-01

The pyruvate dehydrogenase core complex from E. coli K-12, defined as the multienzyme complex that can be obtained with a unique polypeptide chain composition, has a molecular weight of 3.75 × 106. All results obtained agree with the following numerology. The core complex consists of 48 polypeptide chains. There are 16 chains (molecular weight = 100,000) of the pyruvate dehydrogenase component, 16 chains (molecular weight = 80,000) of the dihydrolipoamide dehydrogenase component, and 16 chains (molecular weight = 56,000) of the dihydrolipoamide dehydrogenase component. Usually, but not always, pyruvate dehydrogenase complex is produced in vivo containing at least 2-3 mol more of dimers of the pyruvate dehydrogenase component than the stoichiometric ratio with respect to the core complex. This “excess” component is bound differently than are the eight dimers in the core complex. Images PMID:4556465

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis

PubMed Central

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis.

PubMed

Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.

Joint Intelligence Analysis Complex: DOD Partially Used Best Practices for Analyzing Alternatives and Should Do So Fully for Future Military Construction Decisions

DTIC Science & Technology

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

Parental decision-making for medically complex infants and children: an integrated literature review.

PubMed

Allen, Kimberly A

2014-09-01

Many children with life-threatening conditions who would have died at birth are now surviving months to years longer than previously expected. Understanding how parents make decisions is necessary to prevent parental regret about decision-making, which can lead to psychological distress, decreased physical health, and decreased quality of life for the parents. The aim of this integrated literature review was to describe possible factors that affect parental decision-making for medically complex children. The critical decisions included continuation or termination of a high-risk pregnancy, initiation of life-sustaining treatments such as resuscitation, complex cardiothoracic surgery, use of experimental treatments, end-of-life care, and limitation of care or withdrawal of support. PubMed, Cumulative Index of Nursing and Allied Health Literature, and PsycINFO were searched using the combined key terms 'parents and decision-making' to obtain English language publications from 2000 to June 2013. The findings from each of the 31 articles retained were recorded. The strengths of the empirical research reviewed are that decisions about initiating life support and withdrawing life support have received significant attention. Researchers have explored how many different factors impact decision-making and have used multiple different research designs and data collection methods to explore the decision-making process. These initial studies lay the foundation for future research and have provided insight into parental decision-making during times of crisis. Studies must begin to include both parents and providers so that researchers can evaluate how decisions are made for individual children with complex chronic conditions to understand the dynamics between parents and parent-provider relationships. The majority of studies focused on one homogenous diagnostic group of premature infants and children with complex congenital heart disease. Thus comparisons across other child illness categories cannot be made. Most studies also used cross-sectional and/or retrospective research designs, which led to researchers and clinicians having limited understanding of how factors change over time for parents. Copyright © 2014 Elsevier Ltd. All rights reserved.

Research of Simple Multi-Attribute Rating Technique for Decision Support

NASA Astrophysics Data System (ADS)

Siregar, Dodi; Arisandi, Diki; Usman, Ari; Irwan, Dedy; Rahim, Robbi

2017-12-01

One of the roles of decision support system is that it can assist the decision maker in obtaining the appropriate alternative with the desired criteria, one of the methods that could apply for the decision maker is SMART method with multicriteria decision making. This multi-criteria decision-making theory has meaning where every alternative has criteria and has value and weight, and the author uses this approach to facilitate decision making with a compelling case. The problems discussed in this paper are classified into problems of a variety Multiobjective (multiple goals to be accomplished) and multicriteria (many of the decisive criteria in reaching such decisions).

Reward-related decision making in eating and weight disorders: A systematic review and meta-analysis of the evidence from neuropsychological studies.

PubMed

Wu, Mudan; Brockmeyer, Timo; Hartmann, Mechthild; Skunde, Mandy; Herzog, Wolfgang; Friederich, Hans-Christoph

2016-02-01

Eating disorders (EDs) and overweight/obesity (OW/OB) are serious public health concerns that share common neuropsychological features and patterns of disturbed eating. Reward-related decision making as a basic neurocognitive function may trans-diagnostically underlie both pathological overeating and restricted eating. The present meta-analysis synthesizes the evidence from N=82 neuropsychological studies for altered reward-related decision making in all ED subtypes, OW and OB. The overall effect sizes for the differences between currently-ill ED patients and OW/OB people and controls were Hedge's g=-0.49 [CI: -0.63; -0.35], and Hedge's g=-0.39 [CI: -0.53; -0.25], respectively. Decision making was found to be altered to similar degrees in all ED subtypes and OB. Effect sizes, however, diverged for the different measures of decision making. Adolescents appear to be less affected than adults. When foods were used as rewarding stimuli, decision making was found to be intact in OB. The findings support that altered general reward-related decision making is a salient neuropsychological factor across eating and weight disorders in adulthood. Copyright © 2015 Elsevier Ltd. All rights reserved.

An automatic iterative decision-making method for intuitionistic fuzzy linguistic preference relations

NASA Astrophysics Data System (ADS)

Pei, Lidan; Jin, Feifei; Ni, Zhiwei; Chen, Huayou; Tao, Zhifu

2017-10-01

As a new preference structure, the intuitionistic fuzzy linguistic preference relation (IFLPR) was recently introduced to efficiently deal with situations in which the membership and non-membership are represented as linguistic terms. In this paper, we study the issues of additive consistency and the derivation of the intuitionistic fuzzy weight vector of an IFLPR. First, the new concepts of order consistency, additive consistency and weak transitivity for IFLPRs are introduced, and followed by a discussion of the characterisation about additive consistent IFLPRs. Then, a parameterised transformation approach is investigated to convert the normalised intuitionistic fuzzy weight vector into additive consistent IFLPRs. After that, a linear optimisation model is established to derive the normalised intuitionistic fuzzy weights for IFLPRs, and a consistency index is defined to measure the deviation degree between an IFLPR and its additive consistent IFLPR. Furthermore, we develop an automatic iterative decision-making method to improve the IFLPRs with unacceptable additive consistency until the adjusted IFLPRs are acceptable additive consistent, and it helps the decision-maker to obtain the reasonable and reliable decision-making results. Finally, an illustrative example is provided to demonstrate the validity and applicability of the proposed method.

Exponential stability of stochastic complex networks with multi-weights based on graph theory

NASA Astrophysics Data System (ADS)

Zhang, Chunmei; Chen, Tianrui

2018-04-01

In this paper, a novel approach to exponential stability of stochastic complex networks with multi-weights is investigated by means of the graph-theoretical method. New sufficient conditions are provided to ascertain the moment exponential stability and almost surely exponential stability of stochastic complex networks with multiple weights. It is noted that our stability results are closely related with multi-weights and the intensity of stochastic disturbance. Numerical simulations are also presented to substantiate the theoretical results.

Visual saliency-based fast intracoding algorithm for high efficiency video coding

NASA Astrophysics Data System (ADS)

Zhou, Xin; Shi, Guangming; Zhou, Wei; Duan, Zhemin

2017-01-01

Intraprediction has been significantly improved in high efficiency video coding over H.264/AVC with quad-tree-based coding unit (CU) structure from size 64×64 to 8×8 and more prediction modes. However, these techniques cause a dramatic increase in computational complexity. An intracoding algorithm is proposed that consists of perceptual fast CU size decision algorithm and fast intraprediction mode decision algorithm. First, based on the visual saliency detection, an adaptive and fast CU size decision method is proposed to alleviate intraencoding complexity. Furthermore, a fast intraprediction mode decision algorithm with step halving rough mode decision method and early modes pruning algorithm is presented to selectively check the potential modes and effectively reduce the complexity of computation. Experimental results show that our proposed fast method reduces the computational complexity of the current HM to about 57% in encoding time with only 0.37% increases in BD rate. Meanwhile, the proposed fast algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality.

Psychophysical spectro-temporal receptive fields in an auditory task.

PubMed

Shub, Daniel E; Richards, Virginia M

2009-05-01

Psychophysical relative weighting functions, which provide information about the importance of different regions of a stimulus in forming decisions, are traditionally estimated using trial-based procedures, where a single stimulus is presented and a single response is recorded. Everyday listening is much more "free-running" in that we often must detect randomly occurring signals in the presence of a continuous background. Psychophysical relative weighting functions have not been measured with free-running paradigms. Here, we combine a free-running paradigm with the reverse correlation technique used to estimate physiological spectro-temporal receptive fields (STRFs) to generate psychophysical relative weighting functions that are analogous to physiological STRFs. The psychophysical task required the detection of a fixed target signal (a sequence of spectro-temporally coherent tone pips with a known frequency) in the presence of a continuously presented informational masker (spectro-temporally random tone pips). A comparison of psychophysical relative weighting functions estimated with the current free-running paradigm and trial-based paradigms, suggests that in informational-masking tasks subjects' decision strategies are similar in both free-running and trial-based paradigms. For more cognitively challenging tasks there may be differences in the decision strategies with free-running and trial-based paradigms.

Oral Lactobacillus Counts Predict Weight Gain Susceptibility: A 6-Year Follow-Up Study

PubMed Central

Rosing, Johanne Aviaja; Walker, Karen Christina; Jensen, Benjamin A.H.; Heitmann, Berit L.

2017-01-01

Background Recent studies have shown an association between weight change and the makeup of the intestinal microbiota in humans. Specifically, Lactobacillus, a part of the entire gastrointestinal tract's microbiota, has been shown to contribute to weight regulation. Aim We examined the association between the level of oral Lactobacillus and the subsequent 6-year weight change in a healthy population of 322 Danish adults aged 35–65 years at baseline. Design Prospective observational study. Results In unadjusted analysis the level of oral Lactobacillus was inversely associated with subsequent 6-year change in BMI. A statistically significant interaction between the baseline level of oral Lactobacillus and the consumption of complex carbohydrates was found, e.g. high oral Lactobacillus count predicted weight loss for those with a low intake of complex carbohydrates, while a medium intake of complex carbohydrates predicted diminished weight gain. A closer examination of these relations showed that BMI change and Lactobacillus level was unrelated for those with high complex carbohydrate consumption. Conclusion A high level of oral Lactobacillus seems related to weight loss among those with medium and low intakes of complex carbohydrates. Absence, or a low level of oral Lactobacillus, may potentially be a novel marker to identify those at increased risk of weight gain. PMID:29020671

Oral Lactobacillus Counts Predict Weight Gain Susceptibility: A 6-Year Follow-Up Study.

PubMed

Rosing, Johanne Aviaja; Walker, Karen Christina; Jensen, Benjamin A H; Heitmann, Berit L

2017-01-01

Recent studies have shown an association between weight change and the makeup of the intestinal microbiota in humans. Specifically, Lactobacillus, a part of the entire gastrointestinal tract's microbiota, has been shown to contribute to weight regulation. We examined the association between the level of oral Lactobacillus and the subsequent 6-year weight change in a healthy population of 322 Danish adults aged 35-65 years at baseline. Prospective observational study. In unadjusted analysis the level of oral Lactobacillus was inversely associated with subsequent 6-year change in BMI. A statistically significant interaction between the baseline level of oral Lactobacillus and the consumption of complex carbohydrates was found, e.g. high oral Lactobacillus count predicted weight loss for those with a low intake of complex carbohydrates, while a medium intake of complex carbohydrates predicted diminished weight gain. A closer examination of these relations showed that BMI change and Lactobacillus level was unrelated for those with high complex carbohydrate consumption. A high level of oral Lactobacillus seems related to weight loss among those with medium and low intakes of complex carbohydrates. Absence, or a low level of oral Lactobacillus, may potentially be a novel marker to identify those at increased risk of weight gain. © 2017 The Author(s) Published by S. Karger GmbH, Freiburg.

Maternal executive function, infant feeding responsiveness and infant growth during the first 3 months.

PubMed

Fuglestad, A J; Demerath, E W; Finsaas, M C; Moore, C J; Georgieff, M K; Carlson, S M

2017-08-01

There is limited research in young infants, particularly <3 months of age, on maternal feeding practices in spite of increasing evidence that early weight gain velocity is a determinant of later obesity risk. To examine associations between maternal executive function (cognitive control over one's own behaviour), maternal feeding decisions and infant weight and adiposity gains. We used a checklist to assess cues mothers use to decide when to initiate and terminate infant feedings at 2 weeks and 3 months of age (N = 69). Maternal executive function was assessed using the NIH Toolbox Cognition Battery subtests for executive function and infant body composition using air displacement plethysmography. Mothers with higher executive function reported relying on fewer non-satiety cues at 2 weeks of age (β = -0.29, p = 0.037) and on more infant hunger cues at 3 months of age (β = 0.31, p = 0.018) in their decisions on initiating and terminating feedings. Responsive feeding decisions, specifically the use of infant-based hunger cues at 3 months, in turn were associated with lower gains in weight-for-length (β = -0.30, p = 0.028) and percent body fat (β = -0.2, p = 0.091; non-covariate adjusted β = -0.27, p = 0.029). These findings show both an association between maternal executive function and responsive feeding decisions and an association between responsive feeding decisions and infant weight and adiposity gains. The causal nature and direction of these associations require further investigation. © 2017 World Obesity Federation.

The Biggest Loser Thinks Long-Term: Recency as a Predictor of Success in Weight Management.

PubMed

Koritzky, Gilly; Rice, Chantelle; Dieterle, Camille; Bechara, Antoine

2015-01-01

Only a minority of participants in behavioral weight management lose weight significantly. The ability to predict who is likely to benefit from weight management can improve the efficiency of obesity treatment. Identifying predictors of weight loss can also reveal potential ways to improve existing treatments. We propose a neuro-psychological model that is focused on recency: the reliance on recent information at the expense of time-distant information. Forty-four weight-management patients completed a decision-making task and their recency level was estimated by a mathematical model. Impulsivity and risk-taking were also measured for comparison. Weight loss was measured in the end of the 16-week intervention. Consistent with our hypothesis, successful dieters (n = 12) had lower recency scores than unsuccessful ones (n = 32; p = 0.006). Successful and unsuccessful dieters were similar in their demographics, intelligence, risk taking, impulsivity, and delay of gratification. We conclude that dieters who process time-distant information in their decision making are more likely to lose weight than those who are high in recency. We argue that having low recency facilitates future-oriented thinking, and thereby contributes to behavior change treatment adherence. Our findings underline the importance of choosing the right treatment for every individual, and outline a way to improve weight-management processes for more patients.

Decision-making in obesity without eating disorders: a systematic review and meta-analysis of Iowa gambling task performances.

PubMed

Rotge, J-Y; Poitou, C; Fossati, P; Aron-Wisnewsky, J; Oppert, J-M

2017-08-01

There is evidence that obesity is associated with impairments in executive functions, such as deficits in decision-making, planning or problem solving, which might interfere with weight loss in obese individuals. We performed a systematic review and meta-analysis of decision-making abilities, as measured with the Iowa gambling task (IGT), in obesity without eating disorders. A systematic search was conducted to identify studies comparing IGT performances between groups of obese patients without eating disorders and groups of healthy control groups. The standardized mean differences were calculated for the total IGT scores and for the course of IGT scores. Meta-regression analyses were performed to explore the influence of clinical variables on standardized mean differences. Total IGT scores were significantly lower in obese patients compared with normal-weight healthy controls. IGT performances did not differ between groups for the first trials of the task. Significant effect sizes for the last trials of the task were subjected to a high degree of heterogeneity. Risky decision-making is impaired in obesity. The clinical importance of non-food-related decision-making impairments remains to be assessed especially in terms of consequences in daily life or the achievement of weight loss. This meta-analysis has been registered in the Prospero database (CRD42016037533). © 2017 World Obesity Federation.

An improved hybrid multi-criteria/multidimensional model for strategic industrial location selection: Casablanca industrial zones as a case study.

PubMed

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

2015-01-01

In this paper, we examine the issue of strategic industrial location selection in uncertain decision making environments for implanting new industrial corporation. In fact, the industrial location issue is typically considered as a crucial factor in business research field which is related to many calculations about natural resources, distributors, suppliers, customers, and most other things. Based on the integration of environmental, economic and social decisive elements of sustainable development, this paper presents a hybrid decision making model combining fuzzy multi-criteria analysis with analytical capabilities that OLAP systems can provide for successful and optimal industrial location selection. The proposed model mainly consists in three stages. In the first stage, a decision-making committee has been established to identify the evaluation criteria impacting the location selection process. In the second stage, we develop fuzzy AHP software based on the extent analysis method to assign the importance weights to the selected criteria, which allows us to model the linguistic vagueness, ambiguity, and incomplete knowledge. In the last stage, OLAP analysis integrated with multi-criteria analysis employs these weighted criteria as inputs to evaluate, rank and select the strategic industrial location for implanting new business corporation in the region of Casablanca, Morocco. Finally, a sensitivity analysis is performed to evaluate the impact of criteria weights and the preferences given by decision makers on the final rankings of strategic industrial locations.

[About the heterogeneity in adolescents with gender identity disorder: differential importance of psychiatric comorbidity and considerations of individual psychodynamics].

PubMed

Korte, Alexander; Beier, Klaus M; Vukorepa, Julia; Mersmann, Maik; Albiez, Verena

2014-01-01

Gender identity disorder (GID), gender dysphoria (GD) respectively, is considered a multifactorial disease whose etiology is subject to complex bio-psycho-social conditions, each with different weighting. As a result, therapists, who treat children and adolescents with GID/GD, have to deal with a very heterogeneous group with individually varying causes, differing psychopathology and varying disease progression. In addition to general psychiatric aspects of development, particularly psychiatric comorbidity, but also the different individual psychodynamics--i. e. the specific constellation of conflicts and possible ego deficits and structural deficits in the learning history of the person are of differential importance. In regard to the indication for gender reassignment measures this sometimes is relevant for the decision. The difficulties arising for decision making and the usefulness of a systematic evaluation of case reports as a basis for further optimization of the treatment recommendations are illustrated by two case reports. In the course of this, also the disadvantages and potential dangers of too early diagnostic definition and introduction of gender somato-medical and legal measures are shown exemplarily.

Incorporating information from the U.S. Department of Energy low-dose program into regulatory decision-making: three policy integration challenges.

PubMed

Locke, Paul A

2009-11-01

The U.S. Department of Energy (U.S. DOE) sponsors a research program aimed at gaining a better understanding of how low-dose radiation affects cellular functioning and progression toward disease. There have been calls to incorporate into regulatory decision-making the scientific information that this program has produced. After a discussion of the evolution of radiation protection law and the weight-of-evidence approach that agencies employ, this paper offers some preliminary thoughts about how to approach this complex and important policy question. Three implementation challenges are identified and discussed. The first implementation challenge involves explaining low-dose effects in a systems biology model. The second challenge arises when issues of population susceptibility are juxtaposed against molecular and mechanistic studies, such as those that make up much of the U.S. DOE low-dose program. The third challenge concerns integrating the results of radiation epidemiology, especially epidemiologic studies among cohorts that are exposed to low dose and low-dose rate radiation, with the results of U.S. DOE low-dose studies.

Development of a support tool for complex decision-making in the provision of rural maternity care.

PubMed

Hearns, Glen; Klein, Michael C; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-02-01

Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology.

Development of a Support Tool for Complex Decision-Making in the Provision of Rural Maternity Care

PubMed Central

Hearns, Glen; Klein, Michael C.; Trousdale, William; Ulrich, Catherine; Butcher, David; Miewald, Christiana; Lindstrom, Ronald; Eftekhary, Sahba; Rosinski, Jessica; Gómez-Ramírez, Oralia; Procyk, Andrea

2010-01-01

Context: Decisions in the organization of safe and effective rural maternity care are complex, difficult, value laden and fraught with uncertainty, and must often be based on imperfect information. Decision analysis offers tools for addressing these complexities in order to help decision-makers determine the best use of resources and to appreciate the downstream effects of their decisions. Objective: To develop a maternity care decision-making tool for the British Columbia Northern Health Authority (NH) for use in low birth volume settings. Design: Based on interviews with community members, providers, recipients and decision-makers, and employing a formal decision analysis approach, we sought to clarify the influences affecting rural maternity care and develop a process to generate a set of value-focused objectives for use in designing and evaluating rural maternity care alternatives. Setting: Four low-volume communities with variable resources (with and without on-site births, with or without caesarean section capability) were chosen. Participants: Physicians (20), nurses (18), midwives and maternity support service providers (4), local business leaders, economic development officials and elected officials (12), First Nations (women [pregnant and non-pregnant], chiefs and band members) (40), social workers (3), pregnant women (2) and NH decision-makers/administrators (17). Results: We developed a Decision Support Manual to assist with assessing community needs and values, context for decision-making, capacity of the health authority or healthcare providers, identification of key objectives for decision-making, developing alternatives for care, and a process for making trade-offs and balancing multiple objectives. The manual was deemed an effective tool for the purpose by the client, NH. Conclusions: Beyond assisting the decision-making process itself, the methodology provides a transparent communication tool to assist in making difficult decisions. While the manual was specifically intended to deal with rural maternity issues, the NH decision-makers feel the method can be easily adapted to assist decision-making in other contexts in medicine where there are conflicting objectives, values and opinions. Decisions on the location of new facilities or infrastructure, or enhancing or altering services such as surgical or palliative care, would be examples of complex decisions that might benefit from this methodology. PMID:21286270

A lexicographic weighted Tchebycheff approach for multi-constrained multi-objective optimization of the surface grinding process

NASA Astrophysics Data System (ADS)

Khalilpourazari, Soheyl; Khalilpourazary, Saman

2017-05-01

In this article a multi-objective mathematical model is developed to minimize total time and cost while maximizing the production rate and surface finish quality in the grinding process. The model aims to determine optimal values of the decision variables considering process constraints. A lexicographic weighted Tchebycheff approach is developed to obtain efficient Pareto-optimal solutions of the problem in both rough and finished conditions. Utilizing a polyhedral branch-and-cut algorithm, the lexicographic weighted Tchebycheff model of the proposed multi-objective model is solved using GAMS software. The Pareto-optimal solutions provide a proper trade-off between conflicting objective functions which helps the decision maker to select the best values for the decision variables. Sensitivity analyses are performed to determine the effect of change in the grain size, grinding ratio, feed rate, labour cost per hour, length of workpiece, wheel diameter and downfeed of grinding parameters on each value of the objective function.

Effects of Direct and Indirect Instruction on Fostering Decision-Making Competence in Socioscientific Issues

NASA Astrophysics Data System (ADS)

Böttcher, Florian; Meisert, Anke

2013-04-01

In this study the effects of different learning environments on the promotion of decision-making competence for the socioscientific issue of genetically modified crops is investigated. The comparison focuses on direct vs. indirect instructions. Therefore on the one hand a sophisticated decision-making strategy was presented to the directly instructed experimental group (1) and had to be applied correctly. On the other hand indirectly instructed students had to invent an appropriate strategy by themselves (2) based on the given information and the structure of the problem context. Group discussions are analysed qualitatively in order (1) to outline how the given strategy was understood and its results were reflected on by the students and (2) to explore the characteristics of invented strategies and their degree of complexity. Results indicate that the direct instruction of complex decision-making strategies may lead to a lack of understanding of the decision process when the given strategy is applied and therefore may cause rejection of the final decision. Indirectly instructed students were able to invent sophisticated decision-making strategies containing compensatory trade-offs. It is concluded that when directly instructing complex decision-making strategies, essential parts of reflection have to be integrated in order to gain greater transparency. Accordingly, empirical evidence has been found to consider indirect instruction as a possible way to foster decision-making strategies for complex socioscientific issues even if compensatory procedures are considered to be necessary.

Strategic control in decision-making under uncertainty.

PubMed

Venkatraman, Vinod; Huettel, Scott A

2012-04-01

Complex economic decisions - whether investing money for retirement or purchasing some new electronic gadget - often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, evaluate outcomes against a variety of contexts, and flexibly match behavior to changes in the environment. In recent years, substantial research has implicated the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision-making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision-making. This region contains a functional topography such that the posterior dmPFC supports response-related control, whereas the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue for both generalized contributions of the dmPFC to cognitive control, and specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are likely to be critical for decision-making in other domains, including interpersonal interactions in social settings. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Strategic Control in Decision Making under Uncertainty

PubMed Central

Venkatraman, Vinod; Huettel, Scott

2012-01-01

Complex economic decisions – whether investing money for retirement or purchasing some new electronic gadget – often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, to evaluate outcomes against a variety of contexts, and to flexibly match behavior to changes in the environment. In recent years, substantial research implicates the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision making. This region contains a functional topography such that the posterior dmPFC supports response-related control while the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue both for generalized contributions of the dmPFC to cognitive control, and for specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are also likely to be critical for decision making in other domains, including interpersonal interactions in social settings. PMID:22487037

Neural substrates of decision-making.

PubMed

Broche-Pérez, Y; Herrera Jiménez, L F; Omar-Martínez, E

2016-06-01

Decision-making is the process of selecting a course of action from among 2 or more alternatives by considering the potential outcomes of selecting each option and estimating its consequences in the short, medium and long term. The prefrontal cortex (PFC) has traditionally been considered the key neural structure in decision-making process. However, new studies support the hypothesis that describes a complex neural network including both cortical and subcortical structures. The aim of this review is to summarise evidence on the anatomical structures underlying the decision-making process, considering new findings that support the existence of a complex neural network that gives rise to this complex neuropsychological process. Current evidence shows that the cortical structures involved in decision-making include the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC). This process is assisted by subcortical structures including the amygdala, thalamus, and cerebellum. Findings to date show that both cortical and subcortical brain regions contribute to the decision-making process. The neural basis of decision-making is a complex neural network of cortico-cortical and cortico-subcortical connections which includes subareas of the PFC, limbic structures, and the cerebellum. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

Research on comprehensive decision-making of PV power station connecting system

NASA Astrophysics Data System (ADS)

Zhou, Erxiong; Xin, Chaoshan; Ma, Botao; Cheng, Kai

2018-04-01

In allusion to the incomplete indexes system and not making decision on the subjectivity and objectivity of PV power station connecting system, based on the combination of improved Analytic Hierarchy Process (AHP), Criteria Importance Through Intercriteria Correlation (CRITIC) as well as grey correlation degree analysis (GCDA) is comprehensively proposed to select the appropriate system connecting scheme of PV power station. Firstly, indexes of PV power station connecting system are divided the recursion order hierarchy and calculated subjective weight by the improved AHP. Then, CRITIC is adopted to determine the objective weight of each index through the comparison intensity and conflict between indexes. The last the improved GCDA is applied to screen the optimal scheme, so as to, from the subjective and objective angle, select the connecting system. Comprehensive decision of Xinjiang PV power station is conducted and reasonable analysis results are attained. The research results might provide scientific basis for investment decision.

Bounded Rationality and Voting Decisions over 160 Years: Voter Behavior and Increasing Complexity in Decision-Making

PubMed Central

Stadelmann, David; Torgler, Benno

2013-01-01

Using a quasi-natural voting experiment encompassing a 160-year period (1848–2009) in Switzerland, we investigate whether a higher level of complexity leads to increased reliance on trusted parliamentary representatives. We find that when more referenda are held on the same day, constituents are more likely to refer to parliamentary recommendations when making their decisions. This finding holds true even when we narrow our focus to referenda with a relatively lower voter turnout on days on which more than one referendum is held. We also demonstrate that when constituents face a higher level of complexity, they follow the parliamentary recommendations rather than those of interest groups. “Viewed as a geometric figure, the ant’s path is irregular, complex, hard to describe. But its complexity is really a complexity in the surface of the beach, not a complexity in the ant.” ( [1] p. 51) PMID:24391888

Bounded rationality and voting decisions over 160 years: voter behavior and increasing complexity in decision-making.

PubMed

Stadelmann, David; Torgler, Benno

2013-01-01

Using a quasi-natural voting experiment encompassing a 160-year period (1848-2009) in Switzerland, we investigate whether a higher level of complexity leads to increased reliance on trusted parliamentary representatives. We find that when more referenda are held on the same day, constituents are more likely to refer to parliamentary recommendations when making their decisions. This finding holds true even when we narrow our focus to referenda with a relatively lower voter turnout on days on which more than one referendum is held. We also demonstrate that when constituents face a higher level of complexity, they follow the parliamentary recommendations rather than those of interest groups. "Viewed as a geometric figure, the ant's path is irregular, complex, hard to describe. But its complexity is really a complexity in the surface of the beach, not a complexity in the ant." ( [1] p. 51).

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

NASA Astrophysics Data System (ADS)

Zhang, Wancheng; Xu, Yejun; Wang, Huimin

2016-01-01

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

The role (or not) of economic evaluation at the micro level: can Bourdieu's theory provide a way forward for clinical decision-making?

PubMed

Lessard, Chantale; Contandriopoulos, André-Pierre; Beaulieu, Marie-Dominique

2010-06-01

Despite increasing interest in health economic evaluation, investigations have shown limited use by micro (clinical) level decision-makers. A considerable amount of health decisions take place daily at the point of the clinical encounter; especially in primary care. Since every decision has an opportunity cost, ignoring economic information in family physicians' (FPs) decision-making may have a broad impact on health care efficiency. Knowledge translation of economic evaluation is often based on taken-for-granted assumptions about actors' interests and interactions, neglecting much of the complexity of social reality. Health economics literature frequently assumes a rational and linear decision-making process. Clinical decision-making is in fact a complex social, dynamic, multifaceted process, involving relationships and contextual embeddedness. FPs are embedded in complex social networks that have a significant impact on skills, attitudes, knowledge, practices, and on the information being used. Because of their socially constructed nature, understanding preferences, professional culture, practices, and knowledge translation requires serious attention to social reality. There has been little exploration by health economists of whether the problem may be more fundamental and reside in a misunderstanding of the process of decision-making. There is a need to enhance our understanding of the role of economic evaluation in decision-making from a disciplinary perspective different than health economics. This paper argues for a different conceptualization of the role of economic evaluation in FPs' decision-making, and proposes Bourdieu's sociological theory as a research framework. Bourdieu's theory of practice illustrates how the context-sensitive nature of practice must be understood as a socially constituted practical knowledge. The proposed approach could substantially contribute to a more complex understanding of the role of economic evaluation in FPs' decision-making. Copyright 2010 Elsevier Ltd. All rights reserved.

Application of sensitivity analysis for assessment of de-desertification alternatives in the central Iran by using Triantaphyllou method.

PubMed

Sadeghi Ravesh, Mohammad Hassan; Ahmadi, Hassan; Zehtabian, Gholamreza

2011-08-01

Desertification, land degradation in arid, semi-arid, and dry sub-humid regions, is a global environmental problem. With respect to increasing importance of desertification and its complexity, the necessity of attention to the optimal de-desertification alternatives is essential. Therefore, this work presents an analytic hierarchy process (AHP) method to objectively select the optimal de-desertification alternatives based on the results of interviews with experts in Khezr Abad region, central Iran as the case study. This model was used in Yazd Khezr Abad region to evaluate the efficiency in presentation of better alternatives related to personal and environmental situations. Obtained results indicate that the criterion "proportion and adaptation to the environment" with the weighted average of 33.6% is the most important criterion from experts viewpoints. While prevention alternatives of land usage unsuitable of reveres and conversion with 22.88% mean weight and vegetation cover development and reclamation with 21.9% mean weight are recognized ordinarily as the most important de-desertification alternatives in region. Finally, sensitivity analysis is performed in detail by varying the objective factor decision weight, the priority weight of subjective factors, and the gain factors. After the fulfillment of sensitivity analysis and determination of the most sensitive criteria and alternatives, the former classification and ranking of alternatives does not change so much, and it was observed that unsuitable land use alternative with the preference degree of 22.7% was still in the first order of priority. The final priority of livestock grazing control alternative was replaced with the alternative of modification of ground water harvesting.

Analyses of the response of a complex weighted network to nodes removal strategies considering links weight: The case of the Beijing urban road system

NASA Astrophysics Data System (ADS)

Bellingeri, Michele; Lu, Zhe-Ming; Cassi, Davide; Scotognella, Francesco

2018-02-01

Complex network response to node loss is a central question in different fields of science ranging from physics, sociology, biology to ecology. Previous studies considered binary networks where the weight of the links is not accounted for. However, in real-world networks the weights of connections can be widely different. Here, we analyzed the response of real-world road traffic complex network of Beijing, the most prosperous city in China. We produced nodes removal attack simulations using classic binary node features and we introduced weighted ranks for node importance. We measured the network functioning during nodes removal with three different parameters: the size of the largest connected cluster (LCC), the binary network efficiency (Bin EFF) and the weighted network efficiency (Weg EFF). We find that removing nodes according to weighted rank, i.e. considering the weight of the links as a number of taxi flows along the roads, produced in general the highest damage in the system. Our results show that: (i) in order to model Beijing road complex networks response to nodes (intersections) failure, it is necessary to consider the weight of the links; (ii) to discover the best attack strategy, it is important to use nodes rank accounting links weight.

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Decision-making under risk and ambiguity in low-birth-weight pigs.

PubMed

Murphy, Eimear; Kraak, Lynn; van den Broek, Jan; Nordquist, Rebecca E; van der Staay, Franz Josef

2015-03-01

Low birth weight (LBW) in humans is a risk factor for later cognitive, behavioural and emotional problems. In pigs, LBW is associated with higher mortality, but little is known about consequences for surviving piglets. Alteration in hypothalamic-pituitary-adrenal axis function in LBW pigs suggests altered emotionality, but no behavioural indicators have been studied. Decision-making under uncertain conditions, e.g., risk or ambiguity, is susceptible to emotional influences and may provide a means of assessing long-term effects of LBW in piglets. We tested LBW (N = 8) and normal-birth-weight (NBW; N = 8) male pigs in two decision-making tasks. For decision-making under risk, we developed a simple two-choice probabilistic task, the Pig Gambling Task (PGT), where an 'advantageous' option offered small but frequent rewards and a 'disadvantageous' option offered large but infrequent rewards. The advantageous option offered greater overall gain. For decision-making under ambiguity, we used a Judgement Bias Task (JBT) where pigs were trained to make an active response to 'positive' and 'negative' tone cues (signalling large and small rewards, respectively). Responses to ambiguous tone cues were rated as more or less optimistic. LBW pigs chose the advantageous option more often in later blocks of the PGT, and were scored as less optimistic in the JBT, than NBW pigs. Our findings demonstrate that LBW pigs have developed different behavioural strategies with respect to decision-making. We propose that this is guided by changes in emotionality in LBW piglets, and we provide behavioural evidence of increased negative affect in LBW piglets.

Assessing decision quality in patient-centred care requires a preference-sensitive measure

PubMed Central

Kaltoft, Mette; Cunich, Michelle; Salkeld, Glenn; Dowie, Jack

2014-01-01

A theory-based instrument for measuring the quality of decisions made using any form of decision technology, including both decision-aided and unaided clinical consultations is required to enable person- and patient-centred care and to respond positively to individual heterogeneity in the value aspects of decision making. Current instruments using the term ‘decision quality’ have adopted a decision- and thus condition-specific approach. We argue that patient-centred care requires decision quality to be regarded as both preference-sensitive across multiple relevant criteria and generic across all conditions and decisions. MyDecisionQuality is grounded in prescriptive multi criteria decision analysis and employs a simple expected value algorithm to calculate a score for the quality of a decision that combines, in the clinical case, the patient’s individual preferences for eight quality criteria (expressed as importance weights) and their ratings of the decision just taken on each of these criteria (expressed as performance rates). It thus provides an index of decision quality that encompasses both these aspects. It also provides patients with help in prioritizing quality criteria for future decision making by calculating, for each criterion, the Incremental Value of Perfect Rating, that is, the increase in their decision quality score that would result if their performance rating on the criterion had been 100%, weightings unchanged. MyDecisionQuality, which is a web-based generic and preference-sensitive instrument, can constitute a key patient-reported measure of the quality of the decision-making process. It can provide the basis for future decision improvement, especially when the clinician (or other stakeholders) completes the equivalent instrument and the extent and nature of concordance and discordance can be established. Apart from its role in decision preparation and evaluation, it can also provide real time and relevant documentation for the patient’s record. PMID:24335587

A Decision-Oriented Investigation of Air Force Civil Engineering’s Operations Branch and the Implications for a Decision Support System.

DTIC Science & Technology

1984-09-01

information when making a decision [ Szilagyi and Wallace , 1983:3201." Driver and Mock used cognitive complexity ideas to develop this two dimensional...flexible AMOUNT OF INFORMATION USED High hierarchic integrative Figure 6. Cognitive Complexity Model ( Szilagyi and Wallace , 1983:321) Decisive Style. The...large amount of inform- ation. However, he processes this information with a multiple focus approach ( Szilagyi and Wallace , 1983:320-321). 26 McKenney

Mediation: a response to aid-in-dying and the Supreme Court decision.

PubMed

Saulo, M; Wagener, R J; Rothschild, I S

1998-01-01

The recent U.S. Supreme Court decision concerning aid-in-dying has drawn attention to the complexity of end-of-life care. The authors summarize the recent Supreme Court's decision and the problems surrounding this complex issue. A case study is provided to demonstrate how mediation facilitates collaborative problem solving. Finally, the authors demonstrate how nurse leaders can apply this three-stage process and its attendant principles to facilitate ethical decision making in end-of-life care.

A Neurocomputational Model of the Effect of Cognitive Load on Freezing of Gait in Parkinson's Disease.

PubMed

Muralidharan, Vignesh; Balasubramani, Pragathi P; Chakravarthy, V Srinivasa; Gilat, Moran; Lewis, Simon J G; Moustafa, Ahmed A

2016-01-01

Experimental data show that perceptual cues can either exacerbate or ameliorate freezing of gait (FOG) in Parkinson's Disease (PD). For example, simple visual stimuli like stripes on the floor can alleviate freezing whereas complex stimuli like narrow doorways can trigger it. We present a computational model of the cognitive and motor cortico-basal ganglia loops that explains the effects of sensory and cognitive processes on FOG. The model simulates strong causative factors of FOG including decision conflict (a disagreement of various sensory stimuli in their association with a response) and cognitive load (complexity of coupling a stimulus with downstream mechanisms that control gait execution). Specifically, the model simulates gait of PD patients (freezers and non-freezers) as they navigate a series of doorways while simultaneously responding to several Stroop word cues in a virtual reality setup. The model is based on an actor-critic architecture of Reinforcement Learning involving Utility-based decision making, where Utility is a weighted sum of Value and Risk functions. The model accounts for the following experimental data: (a) the increased foot-step latency seen in relation to high conflict cues, (b) the high number of motor arrests seen in PD freezers when faced with a complex cue compared to the simple cue, and (c) the effect of dopamine medication on these motor arrests. The freezing behavior arises as a result of addition of task parameters (doorways and cues) and not due to inherent differences in the subject group. The model predicts a differential role of risk sensitivity in PD freezers and non-freezers in the cognitive and motor loops. Additionally this first-of-its-kind model provides a plausible framework for understanding the influence of cognition on automatic motor actions in controls and Parkinson's Disease.

Ixcatec ethnoecology: plant management and biocultural heritage in Oaxaca, Mexico.

PubMed

Rangel-Landa, Selene; Casas, Alejandro; Rivera-Lozoya, Erandi; Torres-García, Ignacio; Vallejo-Ramos, Mariana

2016-07-20

Studying motives of plant management allows understanding processes that originated agriculture and current forms of traditional technology innovation. Our work analyses the role of native plants in the Ixcatec subsistence, management practices, native plants biocultural importance, and motivations influencing management decisions. Cultural and ecological importance and management complexity may differ among species according with their use value and availability. We hypothesized that decreasing risk in availability of resources underlies the main motives of management, but curiosity, aesthetic, and ethical values may also be determinant. Role of plants in subsistence strategies, forms of use and management was documented through 130 semi-structured interviews and participant observation. Free listing interviews to 38 people were used to estimate the cognitive importance of species used as food, medicine, fuel, fodder, ornament and ceremonial. Species ecological importance was evaluated through sampling vegetation in 22 points. Principal Components Analysis were performed to explore the relation between management, cultural and ecological importance and estimating the biocultural importance of native species. We recorded 627 useful plant species, 589 of them native. Livelihood strategies of households rely on agriculture, livestock and multiple use of forest resources. At least 400 species are managed, some of them involving artificial selection. Management complexity is the main factor reflecting the biocultural importance of plant species, and the weight of ecological importance and cultural value varied among use types. Management strategies aim to ensure resources availability, to have them closer, to embellish human spaces or satisfying ethical principles. Decisions about plants management are influenced by perception of risk to satisfy material needs, but immaterial principles are also important. Studying such relation is crucial for understanding past and present technological innovation processes and understand the complex process of developing biocultural legacy.

A Neurocomputational Model of the Effect of Cognitive Load on Freezing of Gait in Parkinson's Disease

PubMed Central

Muralidharan, Vignesh; Balasubramani, Pragathi P.; Chakravarthy, V. Srinivasa; Gilat, Moran; Lewis, Simon J. G.; Moustafa, Ahmed A.

2017-01-01

Experimental data show that perceptual cues can either exacerbate or ameliorate freezing of gait (FOG) in Parkinson's Disease (PD). For example, simple visual stimuli like stripes on the floor can alleviate freezing whereas complex stimuli like narrow doorways can trigger it. We present a computational model of the cognitive and motor cortico-basal ganglia loops that explains the effects of sensory and cognitive processes on FOG. The model simulates strong causative factors of FOG including decision conflict (a disagreement of various sensory stimuli in their association with a response) and cognitive load (complexity of coupling a stimulus with downstream mechanisms that control gait execution). Specifically, the model simulates gait of PD patients (freezers and non-freezers) as they navigate a series of doorways while simultaneously responding to several Stroop word cues in a virtual reality setup. The model is based on an actor-critic architecture of Reinforcement Learning involving Utility-based decision making, where Utility is a weighted sum of Value and Risk functions. The model accounts for the following experimental data: (a) the increased foot-step latency seen in relation to high conflict cues, (b) the high number of motor arrests seen in PD freezers when faced with a complex cue compared to the simple cue, and (c) the effect of dopamine medication on these motor arrests. The freezing behavior arises as a result of addition of task parameters (doorways and cues) and not due to inherent differences in the subject group. The model predicts a differential role of risk sensitivity in PD freezers and non-freezers in the cognitive and motor loops. Additionally this first-of-its-kind model provides a plausible framework for understanding the influence of cognition on automatic motor actions in controls and Parkinson's Disease. PMID:28119584

Structuring and Judgment in Decision Technology.

DTIC Science & Technology

1981-01-01

partly because it avoids weighting questions in which only remotely related attributes need to be compared. But there are several potential problems...weighting questions in which only remotely related attributes need to be compared. But there are also problems; * C- for example, respondents may add to an...favoring the nuclear option assigned weights which were similar to those preferring coal. All groups gave the highest weight to the health/safety

Decision-Oriented Health Technology Assessment: One Step Forward in Supporting the Decision-Making Process in Hospitals.

PubMed

Ritrovato, Matteo; Faggiano, Francesco C; Tedesco, Giorgia; Derrico, Pietro

2015-06-01

This article outlines the Decision-Oriented Health Technology Assessment: a new implementation of the European network for Health Technology Assessment Core Model, integrating the multicriteria decision-making analysis by using the analytic hierarchy process to introduce a standardized methodological approach as a valued and shared tool to support health care decision making within a hospital. Following the Core Model as guidance (European network for Health Technology Assessment. HTA core model for medical and surgical interventions. Available from: http://www.eunethta.eu/outputs/hta-core-model-medical-and-surgical-interventions-10r. [Accessed May 27, 2014]), it is possible to apply the analytic hierarchy process to break down a problem into its constituent parts and identify priorities (i.e., assigning a weight to each part) in a hierarchical structure. Thus, it quantitatively compares the importance of multiple criteria in assessing health technologies and how the alternative technologies perform in satisfying these criteria. The verbal ratings are translated into a quantitative form by using the Saaty scale (Saaty TL. Decision making with the analytic hierarchy process. Int J Serv Sci 2008;1:83-98). An eigenvectors analysis is used for deriving the weights' systems (i.e., local and global weights' system) that reflect the importance assigned to the criteria and the priorities related to the performance of the alternative technologies. Compared with the Core Model, this methodological approach supplies a more timely as well as contextualized evidence for a specific technology, making it possible to obtain data that are more relevant and easier to interpret, and therefore more useful for decision makers to make investment choices with greater awareness. We reached the conclusion that although there may be scope for improvement, this implementation is a step forward toward the goal of building a "solid bridge" between the scientific evidence and the final decision maker's choice. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

An Intuitionistic Multiplicative ORESTE Method for Patients’ Prioritization of Hospitalization

PubMed Central

Zhang, Cheng; Wu, Xingli; Wu, Di; Luo, Li; Herrera-Viedma, Enrique

2018-01-01

The tension brought about by sickbeds is a common and intractable issue in public hospitals in China due to the large population. Assigning the order of hospitalization of patients is difficult because of complex patient information such as disease type, emergency degree, and severity. It is critical to rank the patients taking full account of various factors. However, most of the evaluation criteria for hospitalization are qualitative, and the classical ranking method cannot derive the detailed relations between patients based on these criteria. Motivated by this, a comprehensive multiple criteria decision making method named the intuitionistic multiplicative ORESTE (organísation, rangement et Synthèse dedonnées relarionnelles, in French) was proposed to handle the problem. The subjective and objective weights of criteria were considered in the proposed method. To do so, first, considering the vagueness of human perceptions towards the alternatives, an intuitionistic multiplicative preference relation model is applied to represent the experts’ preferences over the pairwise alternatives with respect to the predetermined criteria. Then, a correlation coefficient-based weight determining method is developed to derive the objective weights of criteria. This method can overcome the biased results caused by highly-related criteria. Afterwards, we improved the general ranking method, ORESTE, by introducing a new score function which considers both the subjective and objective weights of criteria. An intuitionistic multiplicative ORESTE method was then developed and further highlighted by a case study concerning the patients’ prioritization. PMID:29673212

Intuitionistic fuzzy analytical hierarchical processes for selecting the paradigms of mangroves in municipal wastewater treatment.

PubMed

Ouyang, Xiaoguang; Guo, Fen

2018-04-01

Municipal wastewater discharge is widespread and one of the sources of coastal eutrophication, and is especially uncontrolled in developing and undeveloped coastal regions. Mangrove forests are natural filters of pollutants in wastewater. There are three paradigms of mangroves for municipal wastewater treatment and the selection of the optimal one is a multi-criteria decision-making problem. Combining intuitionistic fuzzy theory, the Fuzzy Delphi Method and the fuzzy analytical hierarchical process (AHP), this study develops an intuitionistic fuzzy AHP (IFAHP) method. For the Fuzzy Delphi Method, the judgments of experts and representatives on criterion weights are made by linguistic variables and quantified by intuitionistic fuzzy theory, which is also used to weight the importance of experts and representatives. This process generates the entropy weights of criteria, which are combined with indices values and weights to rank the alternatives by the fuzzy AHP method. The IFAHP method was used to select the optimal paradigm of mangroves for treating municipal wastewater. The entropy weights were entrained by the valid evaluation of 64 experts and representatives via online survey. Natural mangroves were found to be the optimal paradigm for municipal wastewater treatment. By assigning different weights to the criteria, sensitivity analysis shows that natural mangroves remain to be the optimal paradigm under most scenarios. This study stresses the importance of mangroves for wastewater treatment. Decision-makers need to contemplate mangrove reforestation projects, especially where mangroves are highly deforested but wastewater discharge is uncontrolled. The IFAHP method is expected to be applied in other multi-criteria decision-making cases. Copyright © 2017 Elsevier Ltd. All rights reserved.

Can a Two-Question Test Be Reliable and Valid for Predicting Academic Outcomes?

ERIC Educational Resources Information Center

Bridgeman, Brent

2016-01-01

Scores on essay-based assessments that are part of standardized admissions tests are typically given relatively little weight in admissions decisions compared to the weight given to scores from multiple-choice assessments. Evidence is presented to suggest that more weight should be given to these assessments. The reliability of the writing scores…

Children's Weighting Strategies for Word-Final Stop Voicing Are Not Explained by Auditory Sensitivities

ERIC Educational Resources Information Center

Nittrouer, Susan; Lowenstein, Joanna H.

2007-01-01

Purpose: It has been reported that children and adults weight differently the various acoustic properties of the speech signal that support phonetic decisions. This finding is generally attributed to the fact that the amount of weight assigned to various acoustic properties by adults varies across languages, and that children have not yet…

Strategic Decision Making Paradigms: A Primer for Senior Leaders

DTIC Science & Technology

2009-07-01

decision making . STRATEGIC DECISION MAKING Strategic Change: There are several strategic...influenced by stakeholders outside of the organization. The Ontology of Strategic Decision Making . Strategic decisions are non-routine and involve...Coates USAWC, July 2009 5 The Complexity of Strategic Decision Making Strategic decisions entail “ill-structured,”6 “messy” or

Implementation and consistency of Heart Team decision-making in complex coronary revascularisation.

PubMed

Pavlidis, Antonis N; Perera, Divaka; Karamasis, Grigoris V; Bapat, Vinayak; Young, Chris; Clapp, Brian R; Blauth, Chris; Roxburgh, James; Thomas, Martyn R; Redwood, Simon R

2016-03-01

A multidisciplinary team (MDT) approach for decision-making in patients with complex coronary artery disease (CAD) is now a class IC recommendation in the European and American guidelines for myocardial revascularisation. The aim of this study was to evaluate the implementation and consistency of Heart Team HT decision-making in complex coronary revascularisation. We prospectively evaluated the data of 399 patients derived from 51 consecutive MDT meetings held in a tertiary cardiac centre. A subset of cases was randomly selected and re-presented with the same clinical data to a panel blinded to the initial outcome, at least 6 months after the initial discussion, in order to evaluate the reproducibility of decision-making. The most common decisions included continued medical management (30%), coronary artery bypass grafting (CABG) (26%) and percutaneous coronary intervention (PCI) (17%). Other decisions, such as further assessment of symptoms or evaluation with further invasive or non-invasive tests were made in 25% of the cases. Decisions were implemented in 93% of the cases. On re-discussion of the same data (n=40) within a median period of 9 months 80% of the initial HT recommendations were successfully reproduced. The Heart Team is a robust process in the management of patient with complex CAD and decisions are largely reproducible. Although outcomes are successfully implemented in the majority of the cases, it is important that all clinical information is available during discussion and patient preference is taken into account. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Visualizing Decision-making Behaviours in Agent-based Autonomous Spacecraft

NASA Technical Reports Server (NTRS)

North, Steve; Hennessy, Joseph F. (Technical Monitor)

2003-01-01

The authors will report initial progress on the PIAudit project as a Research Resident Associate Program. The objective of this research is to prototype a tool for visualizing decision-making behaviours in autonomous spacecraft. This visualization will serve as an information source for human analysts. The current visualization prototype for PIAudit combines traditional Decision Trees with Weights of Evidence.

Decision analysis applied to the purchase of frozen premixed intravenous admixtures.

PubMed

Witte, K W; Eck, T A; Vogel, D P

1985-04-01

A structured decision-analysis model was used to evaluate frozen premixed cefazolin admixtures. Decision analysis is a process of stating the desired outcome, establishing and weighting evaluation criteria, identifying options for reaching the outcome, evaluating and numerically ranking each option for each criterion, multiplying the ranking by the weight for each criterion, and calculating total points for each option. It was used to compare objectively frozen premixed cefazolin admixtures with batch reconstitution from vials and reconstitution of lyophilized, ready-to-mix containers. In this institution the model numerically demonstrated a distinct preference for the premixed frozen admixture over these other alternatives. A comparison of these results with the total cost impact of each option resulted in a decision to purchase the frozen premixed solution. The advantages of the frozen premixed solution that contributed most to this decision were decreased waste and personnel time. The latter was especially important since it allowed for the reallocation of personnel resources to other potentially cost-reducing clinical functions. Decision analysis proved to be an effective tool for formalizing the process of selecting among various alternatives to reach a desired outcome in this hospital pharmacy.

Truel Conflict and Complex Decision Making. The Effects of the Three-Party-Duel on Military and Economic Behavior of Decision Making Groups in a Complex Environment.

DTIC Science & Technology

of their decisions in a simulated internation conflict. The duel conflict (conflict between two nations) was maintained for the control groups during...four one-half hour playing periods. Experimental groups were exposed to one duel playing period, and were then exposed to increasing threat of truel

Decision Making and Ratio Processing in Patients with Mild Cognitive Impairment.

PubMed

Pertl, Marie-Theres; Benke, Thomas; Zamarian, Laura; Delazer, Margarete

2015-01-01

Making advantageous decisions is important in everyday life. This study aimed at assessing how patients with mild cognitive impairment (MCI) make decisions under risk. Additionally, it investigated the relationship between decision making, ratio processing, basic numerical abilities, and executive functions. Patients with MCI (n = 22) were compared with healthy controls (n = 29) on a complex task of decision making under risk (Game of Dice Task-Double, GDT-D), on two tasks evaluating basic decision making under risk, on a task of ratio processing, and on several neuropsychological background tests. Patients performed significantly lower than controls on the GDT-D and on ratio processing, whereas groups performed comparably on basic decision tasks. Specifically, in the GDT-D, patients obtained lower net scores and lower mean expected values, which indicate a less advantageous performance relative to that of controls. Performance on the GDT-D correlated significantly with performance in basic decision tasks, ratio processing, and executive-function measures when the analysis was performed on the whole sample. Patients with MCI make sub-optimal decisions in complex risk situations, whereas they perform at the same level as healthy adults in simple decision situations. Ratio processing and executive functions have an impact on the decision-making performance of both patients and healthy older adults. In order to facilitate advantageous decisions in complex everyday situations, information should be presented in an easily comprehensible form and cognitive training programs for patients with MCI should focus--among other abilities--on executive functions and ratio processing.

Close Combat Missile Methodology Study

DTIC Science & Technology

2010-10-14

Modeling: Industrial Applications of DEX.” Informatica 23 (1999): 487-491. Bohanec, Marko, Blaz Zupan, and Vladislav Rajkovic. “Applications of...Lisec. “Multi-attribute Decision Analysis in GIS: Weighted Linear Combination and Ordered Weighted Averaging.” Informatica 33, (1999): 459- 474

Treatment decision-making in ductal carcinoma in situ: A mixed methods systematic review of women's experiences and information needs.

PubMed

Rutherford, Claudia; Mercieca-Bebber, Rebecca; Butow, Phyllis; Wu, Jenny Liang; King, Madeleine T

2017-09-01

Decision-making in ductal carcinoma in situ (DCIS) is complex due to the heterogeneity of the disease. This study aimed to understand women's experience of making treatment decisions for DCIS, their information and support needs, and factors that influenced decisions. We searched six electronic databases, conference proceedings, and key authors. Two reviewers independently applied inclusion and quality criteria, and extracted findings. Thematic analysis was used to combine and summarise findings. We identified six themes and 28 subthemes from 18 studies. Women with DCIS have knowledge deficits about DCIS, experience anxiety related to information given at diagnosis and the complexity of decision-making, and have misconceptions regarding risks and outcomes of treatment. Women's decisions are influenced by their understanding of risk, the clinical features of their DCIS, and the benefits and harms of treatment options. Women are dissatisfied with the decisional support available. Informed and shared decision-making in this complex decision setting requires clear communication of information specific to DCIS and individual's, as well as decision support for patients and clinicians. This approach would educate patients and clinicians, and assist clinicians in supporting patients to an evidence-based treatment plan that aligns with individual values and pReferences. Copyright © 2017 Elsevier B.V. All rights reserved.

The Biggest Loser Thinks Long-Term: Recency as a Predictor of Success in Weight Management

PubMed Central

Koritzky, Gilly; Rice, Chantelle; Dieterle, Camille; Bechara, Antoine

2015-01-01

Only a minority of participants in behavioral weight management lose weight significantly. The ability to predict who is likely to benefit from weight management can improve the efficiency of obesity treatment. Identifying predictors of weight loss can also reveal potential ways to improve existing treatments. We propose a neuro-psychological model that is focused on recency: the reliance on recent information at the expense of time-distant information. Forty-four weight-management patients completed a decision-making task and their recency level was estimated by a mathematical model. Impulsivity and risk-taking were also measured for comparison. Weight loss was measured in the end of the 16-week intervention. Consistent with our hypothesis, successful dieters (n = 12) had lower recency scores than unsuccessful ones (n = 32; p = 0.006). Successful and unsuccessful dieters were similar in their demographics, intelligence, risk taking, impulsivity, and delay of gratification. We conclude that dieters who process time-distant information in their decision making are more likely to lose weight than those who are high in recency. We argue that having low recency facilitates future-oriented thinking, and thereby contributes to behavior change treatment adherence. Our findings underline the importance of choosing the right treatment for every individual, and outline a way to improve weight-management processes for more patients. PMID:26696930

Elapsed decision time affects the weighting of prior probability in a perceptual decision task

PubMed Central

Hanks, Timothy D.; Mazurek, Mark E.; Kiani, Roozbeh; Hopp, Elizabeth; Shadlen, Michael N.

2012-01-01

Decisions are often based on a combination of new evidence with prior knowledge of the probable best choice. Optimal combination requires knowledge about the reliability of evidence, but in many realistic situations, this is unknown. Here we propose and test a novel theory: the brain exploits elapsed time during decision formation to combine sensory evidence with prior probability. Elapsed time is useful because (i) decisions that linger tend to arise from less reliable evidence, and (ii) the expected accuracy at a given decision time depends on the reliability of the evidence gathered up to that point. These regularities allow the brain to combine prior information with sensory evidence by weighting the latter in accordance with reliability. To test this theory, we manipulated the prior probability of the rewarded choice while subjects performed a reaction-time discrimination of motion direction using a range of stimulus reliabilities that varied from trial to trial. The theory explains the effect of prior probability on choice and reaction time over a wide range of stimulus strengths. We found that prior probability was incorporated into the decision process as a dynamic bias signal that increases as a function of decision time. This bias signal depends on the speed-accuracy setting of human subjects, and it is reflected in the firing rates of neurons in the lateral intraparietal cortex (LIP) of rhesus monkeys performing this task. PMID:21525274

Elapsed decision time affects the weighting of prior probability in a perceptual decision task.

PubMed

Hanks, Timothy D; Mazurek, Mark E; Kiani, Roozbeh; Hopp, Elisabeth; Shadlen, Michael N

2011-04-27

Decisions are often based on a combination of new evidence with prior knowledge of the probable best choice. Optimal combination requires knowledge about the reliability of evidence, but in many realistic situations, this is unknown. Here we propose and test a novel theory: the brain exploits elapsed time during decision formation to combine sensory evidence with prior probability. Elapsed time is useful because (1) decisions that linger tend to arise from less reliable evidence, and (2) the expected accuracy at a given decision time depends on the reliability of the evidence gathered up to that point. These regularities allow the brain to combine prior information with sensory evidence by weighting the latter in accordance with reliability. To test this theory, we manipulated the prior probability of the rewarded choice while subjects performed a reaction-time discrimination of motion direction using a range of stimulus reliabilities that varied from trial to trial. The theory explains the effect of prior probability on choice and reaction time over a wide range of stimulus strengths. We found that prior probability was incorporated into the decision process as a dynamic bias signal that increases as a function of decision time. This bias signal depends on the speed-accuracy setting of human subjects, and it is reflected in the firing rates of neurons in the lateral intraparietal area (LIP) of rhesus monkeys performing this task.

Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Hu-Chen; Department of Industrial Engineering and Management, Tokyo Institute of Technology, Tokyo 152-8552; Wu, Jing

Highlights: • Propose a VIKOR-based fuzzy MCDM technique for evaluating HCW disposal methods. • Linguistic variables are used to assess the ratings and weights for the criteria. • The OWA operator is utilized to aggregate individual opinions of decision makers. • A case study is given to illustrate the procedure of the proposed framework. - Abstract: Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires considerationmore » of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include “incineration”, “steam sterilization”, “microwave” and “landfill”. The results obtained using the proposed approach are analyzed in a comparative way.« less

Dynamic Density: An Air Traffic Management Metric

NASA Technical Reports Server (NTRS)

Laudeman, I. V.; Shelden, S. G.; Branstrom, R.; Brasil, C. L.

1998-01-01

The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.

Ethical issues related to caring for low birth weight infants.

PubMed

Webb, Mary S; Passmore, Denise; Cline, Genieveve; Maguire, Denise

2014-09-01

Currently preterm births are the leading causes of newborn deaths and newborn mortality in developed countries. Infants born prematurely remain vulnerable to many acute complications and long-term disabilities. There is a growing concern surrounding the moral and ethical implications of the complex and technological care being provided to extremely low birth weight infants in neonatal intensive care units in the developed nations. The purpose of this study was to describe the ethical and moral issues that neonatal intensive care nurses experience when caring for low birth weight preterm infants and their families. A phenomenological method design was used to describe the lived experiences of nurses with ethical and moral issues encountered in the neonatal intensive care unit. One-on-one, semi-structured interviews using open-ended questions were used to gather data from the participants. The setting for this study was a 97-bed neonatal intensive care. A total of 16 female nurses were interviewed. Approval to conduct the research study was obtained from the institutional review board of the hospital where the study was conducted. Formal signed consent was obtained from each participant. To ensure confidentiality, each participant was asked to choose a confederate name to be used in the interview and the transcriptions. The thematic analysis identified five recurring themes: (a) at the edge of viability, (b) infant pain and discomfort, (c) crucial decisions, (d) communicating with parents, and (e) letting go. Neonatal intensive care unit nurses indicated that they often had challenges to their own sense of morality as they struggled to protect the infant from pain and unnecessary discomfort, provide care to an infant and their family whom they thought was faced with a lifetime of challenges and poor health, accepting decisions made by parents, and feeling as if parents were not adequately informed about outcomes. © The Author(s) 2014.

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

Prospect Theory and Interval-Valued Hesitant Set for Safety Evacuation Model

NASA Astrophysics Data System (ADS)

Kou, Meng; Lu, Na

2018-01-01

The study applies the research results of prospect theory and multi attribute decision making theory, combined with the complexity, uncertainty and multifactor influence of the underground mine fire system and takes the decision makers’ psychological behavior of emotion and intuition into full account to establish the intuitionistic fuzzy multiple attribute decision making method that is based on the prospect theory. The model established by this method can explain the decision maker’s safety evacuation decision behavior in the complex system of underground mine fire due to the uncertainty of the environment, imperfection of the information and human psychological behavior and other factors.

Selection of suitable alternatives to reduce the environmental impact of road traffic noise using a fuzzy multi-criteria decision model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruiz-Padillo, Alejandro, E-mail: aruizp@correo.ugr.es; Civil Engineering Department, University of Granada, Av. Fuentenueva s/n, 18071 Granada; Ruiz, Diego P., E-mail: druiz@ugr.es

Road traffic noise is one of the most significant environmental impacts generated by transport systems. To this regard, the recent implementation of the European Environmental Noise Directive by Public Administrations of the European Union member countries has led to various noise action plans (NAPs) for reducing the noise exposure of EU inhabitants. Every country or administration is responsible for applying criteria based on their own experience or expert knowledge, but there is no regulated process for the prioritization of technical measures within these plans. This paper proposes a multi-criteria decision methodology for the selection of suitable alternatives against traffic noisemore » in each of the road stretches included in the NAPs. The methodology first defines the main criteria and alternatives to be considered. Secondly, it determines the relative weights for the criteria and sub-criteria using the fuzzy extended analytical hierarchy process as applied to the results from an expert panel, thereby allowing expert knowledge to be captured in an automated way. A final step comprises the use of discrete multi-criteria analysis methods such as weighted sum, ELECTRE and TOPSIS, to rank the alternatives by suitability. To illustrate an application of the proposed methodology, this paper describes its implementation in a complex real case study: the selection of optimal technical solutions against traffic noise in the top priority road stretch included in the revision of the NAP of the regional road network in the province of Almeria (Spain).« less

Lost in the crowd? Using eye-tracking to investigate the effect of complexity on attribute non-attendance in discrete choice experiments.

PubMed

Spinks, Jean; Mortimer, Duncan

2016-02-03

The provision of additional information is often assumed to improve consumption decisions, allowing consumers to more accurately weigh the costs and benefits of alternatives. However, increasing the complexity of decision problems may prompt changes in information processing. This is particularly relevant for experimental methods such as discrete choice experiments (DCEs) where the researcher can manipulate the complexity of the decision problem. The primary aims of this study are (i) to test whether consumers actually process additional information in an already complex decision problem, and (ii) consider the implications of any such 'complexity-driven' changes in information processing for design and analysis of DCEs. A discrete choice experiment (DCE) is used to simulate a complex decision problem; here, the choice between complementary and conventional medicine for different health conditions. Eye-tracking technology is used to capture the number of times and the duration that a participant looks at any part of a computer screen during completion of DCE choice sets. From this we can analyse what has become known in the DCE literature as 'attribute non-attendance' (ANA). Using data from 32 participants, we model the likelihood of ANA as a function of choice set complexity and respondent characteristics using fixed and random effects models to account for repeated choice set completion. We also model whether participants are consistent with regard to which characteristics (attributes) they consider across choice sets. We find that complexity is the strongest predictor of ANA when other possible influences, such as time pressure, ordering effects, survey specific effects and socio-demographic variables (including proxies for prior experience with the decision problem) are considered. We also find that most participants do not apply a consistent information processing strategy across choice sets. Eye-tracking technology shows promise as a way of obtaining additional information from consumer research, improving DCE design, and informing the design of policy measures. With regards to DCE design, results from the present study suggest that eye-tracking data can identify the point at which adding complexity (and realism) to DCE choice scenarios becomes self-defeating due to unacceptable increases in ANA. Eye-tracking data therefore has clear application in the construction of guidelines for DCE design and during piloting of DCE choice scenarios. With regards to design of policy measures such as labelling requirements for CAM and conventional medicines, the provision of additional information has the potential to make difficult decisions even harder and may not have the desired effect on decision-making.

A Review of the Impacts of Different Approaches for Diabetes Prevention and a Framework for Making Investment Decisions

PubMed Central

2018-01-01

This paper selectively reviews the economic research on individual (i.e., diabetes prevention programs and financial rewards for weight loss) and population-wide based diabetes prevention interventions (such as food taxes, nutritional labeling, and worksite wellness programs) that demonstrate a direct reduction in diabetes incidence or improvements in diabetes risk factors such as weight, glucose or glycated hemoglobin. The paper suggests a framework to guide decision makers on how to use the available evidence to determine the optimal allocation of resources across population-wide and individual-based interventions. This framework should also assist in the discussion of what parameters are needed from research to inform decision-making on what might be the optimal mix of strategies to reduce diabetes prevalence. PMID:29543711

A Review of the Impacts of Different Approaches for Diabetes Prevention and a Framework for Making Investment Decisions.

PubMed

Alva, Maria L

2018-03-15

This paper selectively reviews the economic research on individual (i.e., diabetes prevention programs and financial rewards for weight loss) and population-wide based diabetes prevention interventions (such as food taxes, nutritional labeling, and worksite wellness programs) that demonstrate a direct reduction in diabetes incidence or improvements in diabetes risk factors such as weight, glucose or glycated hemoglobin. The paper suggests a framework to guide decision makers on how to use the available evidence to determine the optimal allocation of resources across population-wide and individual-based interventions. This framework should also assist in the discussion of what parameters are needed from research to inform decision-making on what might be the optimal mix of strategies to reduce diabetes prevalence.

Implementing an extension of the analytical hierarchy process using ordered weighted averaging operators with fuzzy quantifiers in ArcGIS

NASA Astrophysics Data System (ADS)

Boroushaki, Soheil; Malczewski, Jacek

2008-04-01

This paper focuses on the integration of GIS and an extension of the analytical hierarchy process (AHP) using quantifier-guided ordered weighted averaging (OWA) procedure. AHP_OWA is a multicriteria combination operator. The nature of the AHP_OWA depends on some parameters, which are expressed by means of fuzzy linguistic quantifiers. By changing the linguistic terms, AHP_OWA can generate a wide range of decision strategies. We propose a GIS-multicriteria evaluation (MCE) system through implementation of AHP_OWA within ArcGIS, capable of integrating linguistic labels within conventional AHP for spatial decision making. We suggest that the proposed GIS-MCE would simplify the definition of decision strategies and facilitate an exploratory analysis of multiple criteria by incorporating qualitative information within the analysis.

Influences on the prescribing of new drugs.

PubMed

Tobin, Luke; de Almedia Neto, Abelio C; Wutzke, Sonia; Patterson, Craig; Mackson, Judith; Weekes, Lynn; Williamson, Margaret

2008-01-01

The aim of this study was to identify the factors that influence prescribing of new drugs among general practitioners, endocrinologists and psychiatrists. Four focus groups were conducted with GPs, endocrinologists and psychiatrists on sources of awareness and influences on prescribing of new drugs. Pharmaceutical companies were the most important source for becoming aware of new drugs. There were many influences on the decision to prescribe a new drug, the most important being efficacy, safety, cost and advantage over existing therapies. Endocrinologists placed greater emphasis on evidence from clinical trials and scientific conferences, and psychiatrists and GPs placed more weight on pharmaceutical representatives, colleagues and specialists. New drug prescribing occurs in a complex environment with many influences. Effective interventions to promote rational, safe and effective prescribing of new drugs will need to be cognisant of these factors.

The fuzzy world of precision medicine: deliberations of a precision medicine tumor board

PubMed Central

McGraw, Sarah A; Garber, Judy; Jänne, Pasi A; Lindeman, Neal; Oliver, Nelly; Sholl, Lynette M; Van Allen, Eliezer M; Wagle, Nikhil; Garraway, Levi A; Joffe, Steven; Gray, Stacy W

2017-01-01

Aim: To understand how a cancer precision medicine tumor board (CPM-TB) made choices about return of results. Materials & methods: Observed CPM-TB deliberations and completed in-depth interviews with committee members. Results: Responding to complex evidence of ambiguous significance, deliberations of the CPM-TB were predicated on analytic validity and clinical utility. Members had concerns both about potential harms due to returning results based on weak evidence and about withholding potentially meaningful results. Group dynamics and the clinical experiences of individual committee members shaped their work. Conclusion: Both scientific evidence and the social context surrounding deliberations of a CPM-TB influenced decisions about return of results. Subjective elements, while present in any scientific endeavor, may carry more weight in the face of ambiguous findings. PMID:28757884

Framework for Architecture Trade Study Using MBSE and Performance Simulation

NASA Technical Reports Server (NTRS)

Ryan, Jessica; Sarkani, Shahram; Mazzuchim, Thomas

2012-01-01

Increasing complexity in modern systems as well as cost and schedule constraints require a new paradigm of system engineering to fulfill stakeholder needs. Challenges facing efficient trade studies include poor tool interoperability, lack of simulation coordination (design parameters) and requirements flowdown. A recent trend toward Model Based System Engineering (MBSE) includes flexible architecture definition, program documentation, requirements traceability and system engineering reuse. As a new domain MBSE still lacks governing standards and commonly accepted frameworks. This paper proposes a framework for efficient architecture definition using MBSE in conjunction with Domain Specific simulation to evaluate trade studies. A general framework is provided followed with a specific example including a method for designing a trade study, defining candidate architectures, planning simulations to fulfill requirements and finally a weighted decision analysis to optimize system objectives.

The role of social networks in the development of overweight and obesity among adults: a scoping review.

PubMed

Powell, Katie; Wilcox, John; Clonan, Angie; Bissell, Paul; Preston, Louise; Peacock, Marian; Holdsworth, Michelle

2015-09-30

Although it is increasingly acknowledged that social networks are important to our understanding ofoverweight and obesity, there is limited understanding about the processes by which such networks shapetheir progression. This paper reports the findings of a scoping review of the literature that sought to identify the key processes through which social networks are understood to influence the development of overweight and obesity. A scoping review was conducted. Forty five papers were included in the final review, the findings of which were synthesised to provide an overview of the main processes through which networks have been understood to influence the development of overweight and obesity. Included papers addressed a wide range of research questions framed around six types of networks: a paired network (one's spouse or intimate partner); friends and family (including work colleagues and people within social clubs); ephemeral networks in shared public spaces (such as fellow shoppers in a supermarket or diners in a restaurant); people living within the same geographical region; peers (including co-workers, fellow students, fellow participants in a weight loss programme); and cultural groups (often related toethnicity). As individuals are embedded in many of these different types of social networks at any one time, the pathways of influence from social networks to the development of patterns of overweight and obesity are likely to be complex and interrelated. Included papers addressed a diverse set of issues: body weight trends over time; body size norms or preferences; weight loss and management; physical activity patterns; and dietary patterns. Three inter-related processes were identified: social contagion (whereby the network in which people are embedded influences their weight or weight influencing behaviours), social capital (whereby sense of belonging and social support influence weight or weight influencing behaviours), and social selection (whereby a person's network might develop according to his or her weight). The findings have important implications for understanding about methods to target the spread of obesity, indicating that much greater attention needs to be paid to the social context in which people make decisions about their weight and weight influencing behaviours.

Integrating climate change criteria in reforestation projects using a hybrid decision-support system

NASA Astrophysics Data System (ADS)

Curiel-Esparza, Jorge; Gonzalez-Utrillas, Nuria; Canto-Perello, Julian; Martin-Utrillas, Manuel

2015-09-01

The selection of appropriate species in a reforestation project has always been a complex decision-making problem in which, due mostly to government policies and other stakeholders, not only economic criteria but also other environmental issues interact. Climate change has not usually been taken into account in traditional reforestation decision-making strategies and management procedures. Moreover, there is a lack of agreement on the percentage of each one of the species in reforestation planning, which is usually calculated in a discretionary way. In this context, an effective multicriteria technique has been developed in order to improve the process of selecting species for reforestation in the Mediterranean region of Spain. A hybrid Delphi-AHP methodology is proposed, which includes a consistency analysis in order to reduce random choices. As a result, this technique provides an optimal percentage distribution of the appropriate species to be used in reforestation planning. The highest values of the weight given for each subcriteria corresponded to FR (fire forest response) and PR (pests and diseases risk), because of the increasing importance of the impact of climate change in the forest. However, CB (conservation of biodiversitiy) was in the third position in line with the aim of reforestation. Therefore, the most suitable species were Quercus faginea (19.75%) and Quercus ilex (19.35%), which offer a good balance between all the factors affecting the success and viability of reforestation.

A wavelet-based adaptive fusion algorithm of infrared polarization imaging

NASA Astrophysics Data System (ADS)

Yang, Wei; Gu, Guohua; Chen, Qian; Zeng, Haifang

2011-08-01

The purpose of infrared polarization image is to highlight man-made target from a complex natural background. For the infrared polarization images can significantly distinguish target from background with different features, this paper presents a wavelet-based infrared polarization image fusion algorithm. The method is mainly for image processing of high-frequency signal portion, as for the low frequency signal, the original weighted average method has been applied. High-frequency part is processed as follows: first, the source image of the high frequency information has been extracted by way of wavelet transform, then signal strength of 3*3 window area has been calculated, making the regional signal intensity ration of source image as a matching measurement. Extraction method and decision mode of the details are determined by the decision making module. Image fusion effect is closely related to the setting threshold of decision making module. Compared to the commonly used experiment way, quadratic interpolation optimization algorithm is proposed in this paper to obtain threshold. Set the endpoints and midpoint of the threshold searching interval as initial interpolation nodes, and compute the minimum quadratic interpolation function. The best threshold can be obtained by comparing the minimum quadratic interpolation function. A series of image quality evaluation results show this method has got improvement in fusion effect; moreover, it is not only effective for some individual image, but also for a large number of images.

Optimisation of maintenance concept choice using risk-decision factor - a case study

NASA Astrophysics Data System (ADS)

Popovic, Vladimir M.; Vasic, Branko M.; Rakicevic, Branislav B.; Vorotovic, Goran S.

2012-10-01

The design of maintenance system and the corresponding logistic support is a very complex process, during which the aim is to find the compromise solutions regarding the relations among different maintenance procedures and the ways of their implementation. As a result of this, various solutions can be adopted, since this is conditioned by a series of important factors and criteria, which can be contradictory sometimes. There are different perspectives on ways of solving practical maintenance problems, that is dilemmas when it comes to the choice of maintenance concept. The principal dilemma is how and when to decide on carrying out maintenance procedures. Should the decision be based on theoretical grounds or experience, how does one reconcile those two extremes, who is to decide upon this? In this article we have offered one, basically new solution as a possibility for maintenance concept choice, based on a significant modification of the widely used failure modes and effects analysis (FMEA) method. This solution is risk-decision factor (RDF). This is a result of seven parameters (of different importance and weight) that have the key impact on the process of production and logistic support. The application of this factor is illustrated by the example of planning, organisation and functioning of the maintenance system applied in The Institute for Manufacturing Banknotes and Coins (ZIN) in Belgrade.

Heuristics: foundations for a novel approach to medical decision making.

PubMed

Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V

2015-03-01

Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less

The Neural Basis of Risky Choice with Affective Outcomes

PubMed Central

Suter, Renata S.; Pachur, Thorsten; Hertwig, Ralph; Endestad, Tor; Biele, Guido

2015-01-01

Both normative and many descriptive theories of decision making under risk are based on the notion that outcomes are weighted by their probability, with subsequent maximization of the (subjective) expected outcome. Numerous investigations from psychology, economics, and neuroscience have produced evidence consistent with this notion. However, this research has typically investigated choices involving relatively affect-poor, monetary outcomes. We compared choice in relatively affect-poor, monetary lottery problems with choice in relatively affect-rich medical decision problems. Computational modeling of behavioral data and model-based neuroimaging analyses provide converging evidence for substantial differences in the respective decision mechanisms. Relative to affect-poor choices, affect-rich choices yielded a more strongly curved probability weighting function of cumulative prospect theory, thus signaling that the psychological impact of probabilities is strongly diminished for affect-rich outcomes. Examining task-dependent brain activation, we identified a region-by-condition interaction indicating qualitative differences of activation between affect-rich and affect-poor choices. Moreover, brain activation in regions that were more active during affect-poor choices (e.g., the supramarginal gyrus) correlated with individual trial-by-trial decision weights, indicating that these regions reflect processing of probabilities. Formal reverse inference Neurosynth meta-analyses suggested that whereas affect-poor choices seem to be based on brain mechanisms for calculative processes, affect-rich choices are driven by the representation of outcomes’ emotional value and autobiographical memories associated with them. These results provide evidence that the traditional notion of expectation maximization may not apply in the context of outcomes laden with affective responses, and that understanding the brain mechanisms of decision making requires the domain of the decision to be taken into account. PMID:25830918

The neural basis of risky choice with affective outcomes.

PubMed

Suter, Renata S; Pachur, Thorsten; Hertwig, Ralph; Endestad, Tor; Biele, Guido

2015-01-01

Both normative and many descriptive theories of decision making under risk are based on the notion that outcomes are weighted by their probability, with subsequent maximization of the (subjective) expected outcome. Numerous investigations from psychology, economics, and neuroscience have produced evidence consistent with this notion. However, this research has typically investigated choices involving relatively affect-poor, monetary outcomes. We compared choice in relatively affect-poor, monetary lottery problems with choice in relatively affect-rich medical decision problems. Computational modeling of behavioral data and model-based neuroimaging analyses provide converging evidence for substantial differences in the respective decision mechanisms. Relative to affect-poor choices, affect-rich choices yielded a more strongly curved probability weighting function of cumulative prospect theory, thus signaling that the psychological impact of probabilities is strongly diminished for affect-rich outcomes. Examining task-dependent brain activation, we identified a region-by-condition interaction indicating qualitative differences of activation between affect-rich and affect-poor choices. Moreover, brain activation in regions that were more active during affect-poor choices (e.g., the supramarginal gyrus) correlated with individual trial-by-trial decision weights, indicating that these regions reflect processing of probabilities. Formal reverse inference Neurosynth meta-analyses suggested that whereas affect-poor choices seem to be based on brain mechanisms for calculative processes, affect-rich choices are driven by the representation of outcomes' emotional value and autobiographical memories associated with them. These results provide evidence that the traditional notion of expectation maximization may not apply in the context of outcomes laden with affective responses, and that understanding the brain mechanisms of decision making requires the domain of the decision to be taken into account.

A spatial decision support system (SDSS) for sustainable tourism planning in Cameron Highlands, Malaysia

NASA Astrophysics Data System (ADS)

Aminu, M.; Matori, A. N.; Yusof, K. W.

2014-02-01

The study describes a methodological approach based on an integrated use of Geographic Information System (GIS) and Analytic Network Process (ANP) of Multi Criteria Evaluation (MCE) to determine nature conservation and tourism development priorities among the highland areas. A set of criteria and indicators were defined to evaluate the highlands biodiversity conservation and tourism development. Pair wise comparison technique was used in order to support solution of a decision problem by evaluating possible alternatives from different perspectives. After the weights have been derived from the pairwise comparison technique, the next step was to compute the unweighted supermatrix, weighted supermatrix and the limit matrix. The limit matrix was normalized to obtain the priorities and the results transferred into GIS environment. Elements evaluated and ranked were represented by criterion maps. Map layers reflecting the opinion of different experts involved were summed using the weighted overlay approach of GIS. Subsequently sustainable tourism development scenarios were generated. The generation of scenarios highlighted the critical issues of the decision problem because it allows one to gradually narrow down a problem.

Social Stress Increases Cortisol and Hampers Attention in Adolescents with Excess Weight

PubMed Central

Verdejo-Garcia, Antonio; Moreno-Padilla, Maria; Garcia-Rios, M. Carmen; Lopez-Torrecillas, Francisca; Delgado-Rico, Elena; Schmidt-Rio-Valle, Jacqueline; Fernandez-Serrano, Maria J.

2015-01-01

Objective To experimentally examine if adolescents with excess weight are more sensitive to social stress and hence more sensitive to harmful effects of stress in cognition. Design and Methods We conducted an experimental study in 84 adolescents aged 12 to 18 years old classified in two groups based on age adjusted Body Mass Index percentile: Normal weight (n=42) and Excess weight (n=42). Both groups were exposed to social stress as induced by the virtual reality version of the Trier Social Stress Task --participants were requested to give a public speech about positive and negative aspects of their personalities in front of a virtual audience. The outcome measures were salivary cortisol levels and performance in cognitive tests before and after the social stressor. Cognitive tests included the CANTAB Rapid Visual Processing Test (measuring attention response latency and discriminability) and the Iowa Gambling Task (measuring decision-making). Results Adolescents with excess weight compared to healthy weight controls displayed increased cortisol response and less improvement of attentional performance after the social stressor. Decision-making performance decreased after the social stressor in both groups. Conclusion Adolescents who are overweight or obese have increased sensitivity to social stress, which detrimentally impacts attentional skills. PMID:25898204

Interface Evaluation for Open System Architectures

DTIC Science & Technology

2014-03-01

maker (SDM) is responsible for balancing all of the influences of the IPT when making decisions. Coalescing the IPT perspectives for a single IIM...factors are considered in IIM decisions and that decisions are consistent with the preferences of the SDM, ultimately leading to a balance of schedule... board to perform ranking and weighting determinations. Rank sum, rank exponent, rank reciprocal and ROC leverage a subjective assessment of the

Is the Evaluation of the Students' Values Possible? An Integrated Approach to Determining the Weights of Students' Personal Goals Using Multiple-Criteria Methods

ERIC Educational Resources Information Center

Dadelo, Stanislav; Turskis, Zenonas; Zavadskas, Edmundas Kazimieras; Kacerauskas, Tomas; Dadeliene, Ruta

2016-01-01

To maximize the effectiveness of a decision, it is necessary to support decision-making with integrated methods. It can be assumed that subjective evaluation (considering only absolute values) is only remotely connected with the evaluation of real processes. Therefore, relying solely on these values in process management decision-making would be a…

Improving IT Portfolio Management Decision Confidence Using Multi-Criteria Decision Making and Hypervariate Display Techniques

ERIC Educational Resources Information Center

Landmesser, John Andrew

2014-01-01

Information technology (IT) investment decision makers are required to process large volumes of complex data. An existing body of knowledge relevant to IT portfolio management (PfM), decision analysis, visual comprehension of large volumes of information, and IT investment decision making suggest Multi-Criteria Decision Making (MCDM) and…

Formulary evaluation of third-generation cephalosporins using decision analysis.

PubMed

Cano, S B; Fujita, N K

1988-03-01

A structured, objective approach to formulary review of third-generation cephalosporins using the decision-analysis model is described. The pharmacy and therapeutics (P&T) committee approved the evaluation criteria for this drug class and assigned priority weights (as percentages of 100) to those drug characteristics deemed most important. Clinical data (spectrum of activity, pharmacokinetics, adverse effects, and stability) and financial data (cost of acquisition and cost of therapy per day) were used to determine ranking scores for each drug. Total scores were determined by multiplying ranking scores by the assigned priority weights for the criteria. The two highest-scoring drugs were selected for inclusion in the formulary. By this decision-analysis process, the P&T committee recommended that all current third-generation cephalosporins (cefotaxime, cefoperazone, and moxalactam) be removed from the institutions's formulary and be replaced with ceftazidime and ceftriaxone. P&T committees at other institutions may structure their criteria differently, and different recommendations may result. Using decision analysis for formulary review may promote rational drug therapy and achieve cost savings.

Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

NASA Astrophysics Data System (ADS)

da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

2018-02-01

In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

SEA ARCHER Distributed Aviation Platform

DTIC Science & Technology

2001-12-01

manual processes, but should also improve decision support functions through advanced modeling and simulation. SEA ARCHER’s information architecture...this payload model was the SH-60 for which accurate weights were attained. Weights for the Marine STOVL version of the JSF were also attained, and

Use of Participatory Systems Dynamics Modelling to Generate User-Friendly Decision Support Systems for the Design of Management Policies for Complex Human-Environmental Systems: A Case Study from the Varied Socio-environmental Landscape of Guatemala

NASA Astrophysics Data System (ADS)

Malard, J. J.; Baig, A. I.; Carrera, J.; Mellini, L.; Pineda, P.; Monterroso, O.; Melgar-Quiñonez, H.; Adamowski, J. F.; Halbe, J.; Monardes, H.; Gálvez, J.

2014-12-01

The design of effective management policies for socioenvironmental systems requires the development of comprehensive, yet sufficiently simple, decision support systems (DSS) for policy makers. Guatemala is a particularly complex case, combining an enormous diversity of climates, geographies, and agroecosystems within a very small geographical scale. Although food insecurity levels are very high, indicating a generally inadequate management of the varied agroecosystems of the country, different regions have shown vastly different trends in food insecurity over the past decade, including between regions with similar geophysical and climatic characteristics and/or governmental programmes (e.g., agricultural support). These observations suggest two important points: firstly, that not merely environmental conditions but rather socio-environmental interactions play a crucial role in the successful management of human-environmental systems, and, secondly, that differences in the geophysical and climatic environments between the diverse regions significantly impact the success or failure of policies. This research uses participatory systems dynamic modelling (SDM) to build a DSS that allows local decision-makers to (1) determine the impact of current and potential policies on agroecosystem management and food security, and (2) design sustainable and resilient policies for the future. The use of participatory SDM offers several benefits, including the active involvement of the end recipients in the development of the model, greatly increasing its acceptability; the integration of physical (e.g., precipitation, crop yield) and social components in one model; adequacy for modelling long-term trends in response to particular policy decisions; and the inclusion of local stakeholder knowledge on system structure and trends through the participatory process. Preliminary results suggest that there is a set of common variables explaining the generally high levels of food insecurity in Guatemala (e.g., agricultural productivity), while others (e.g., land dynamics and access to water resources) are restricted to certain regions and have a relatively important weight in determining the success or failure of policies in these regions.

Sustainability Based Decision Making

EPA Science Inventory

With sustainability as the “true north” for EPA research, a premium is placed on the ability to make decisions under highly complex and uncertain conditions. The primary challenge is reconciling disparate criteria toward credible and defensible decisions. Making decisions on on...

Grey situation group decision-making method based on prospect theory.

PubMed

Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

2014-01-01

This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example.

Grey Situation Group Decision-Making Method Based on Prospect Theory

PubMed Central

Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

2014-01-01

This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example. PMID:25197706

Identifying the Complexities within Clients' Thinking and Decision Making.

ERIC Educational Resources Information Center

Heppner, P. Paul

1989-01-01

Responds to Gelatt's conception of decision making in counseling. Concurs with need for a broader view of human reasoning that includes complex processes, both rational and intuitive. Advocates examination of how clients think, feel, and behave as they process information during counseling. (Author/TE)

Bayesian inference and decision theory - A framework for decision making in natural resource management

USGS Publications Warehouse

Dorazio, R.M.; Johnson, F.A.

2003-01-01

Bayesian inference and decision theory may be used in the solution of relatively complex problems of natural resource management, owing to recent advances in statistical theory and computing. In particular, Markov chain Monte Carlo algorithms provide a computational framework for fitting models of adequate complexity and for evaluating the expected consequences of alternative management actions. We illustrate these features using an example based on management of waterfowl habitat.

A qualitative study of factors in nurses' and physicians' decision-making related to family presence during resuscitation.

PubMed

Twibell, Renee; Siela, Debra; Riwitis, Cheryl; Neal, Alexis; Waters, Nicole

2018-01-01

To explore the similarities and differences in factors that influence nurses' and physicians' decision-making related to family presence during resuscitation. Despite the growing acceptance of family presence during resuscitation worldwide, healthcare professionals continue to debate the risks and benefits of family presence. As many hospitals lack a policy to guide family presence during resuscitation, decisions are negotiated by resuscitation teams, families and patients in crisis situations. Research has not clarified the factors that influence the decision-making processes of nurses and physicians related to inviting family presence. This is the first study to elicit written data from healthcare professionals to explicate factors in decision-making about family presence. Qualitative exploratory-descriptive. Convenience samples of registered nurses (n = 325) and acute care physicians (n = 193) from a Midwestern hospital in the United States of America handwrote responses to open-ended questions about family presence. Through thematic analysis, decision-making factors for physicians and nurses were identified and compared. Physicians and nurses evaluated three similar factors and four differing factors when deciding to invite family presence during resuscitation. Furthermore, nurses and physicians weighted the factors differently. Physicians weighted most heavily the family's potential to disrupt life-saving efforts and compromise patient care and then the family's knowledge about resuscitations. Nurses heavily weighted the potential for the family to be traumatised, the potential for the family to disrupt the resuscitation, and possible family benefit. Nurses and physicians considered both similar and different factors when deciding to invite family presence. Physicians focused on the patient primarily, while nurses focused on the patient, family and resuscitation team. Knowledge of factors that influence the decision-making of interprofessional colleagues can improve collaboration and communication in crisis events of family presence during resuscitation. © 2017 John Wiley & Sons Ltd.

Decision Making in the Airplane

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Shafto, Michael G. (Technical Monitor)

1995-01-01

The Importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful In improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking In response to a problem, This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

The complex use of religion in decisions on organ transplantation.

PubMed

Röcklinsberg, Helena

2009-03-01

Because of its existential character, organ transplantation is strongly connected to a person's view of life. This article describes how participants in a focus group use religious elements in decision-making on transplantation medicine in four European countries. Further these findings are related to two influential theologians: James Gustafson and Paul Ramsey, and their thinking on the role of religion in medical ethics. Both participants' and theologians' use of religious elements is complex, and show significant variety in regard to both content and form. Decisions in transplantation medicine would benefit from considering the complexity of religious views when striving for informed consent as participative involvement.

Positive feelings facilitate working memory and complex decision making among older adults.

PubMed

Carpenter, Stephanie M; Peters, Ellen; Västfjäll, Daniel; Isen, Alice M

2013-01-01

The impact of induced mild positive feelings on working memory and complex decision making among older adults (aged 63-85) was examined. Participants completed a computer administered card task in which participants could win money if they chose from "gain" decks and lose money if they chose from "loss" decks. Individuals in the positive-feeling condition chose better than neutral-feeling participants and earned more money overall. Participants in the positive-feeling condition also demonstrated improved working-memory capacity. These effects of positive-feeling induction have implications for affect theory, as well as, potentially, practical implications for people of all ages dealing with complex decisions.

47 CFR 1.251 - Summary decision.

Code of Federal Regulations, 2010 CFR

2010-10-01

... an attachment to pleadings filed by him pursuant to paragraph (b) of this section. (b) Within 14 days... or memoranda of law. The presiding officer, giving appropriate weight to the nature of the proceeding... decision to the extent that the pleadings, affidavits, materials obtained by discovery or otherwise...

Effects of Information Visualization on Older Adults' Decision-Making Performance in a Medicare Plan Selection Task: A Comparative Usability Study.

PubMed

Price, Margaux M; Crumley-Branyon, Jessica J; Leidheiser, William R; Pak, Richard

2016-06-01

Technology gains have improved tools for evaluating complex tasks by providing environmental supports (ES) that increase ease of use and improve performance outcomes through the use of information visualizations (info-vis). Complex info-vis emphasize the need to understand individual differences in abilities of target users, the key cognitive abilities needed to execute a decision task, and the graphical elements that can serve as the most effective ES. Older adults may be one such target user group that would benefit from increased ES to mitigate specific declines in cognitive abilities. For example, choosing a prescription drug plan is a necessary and complex task that can impact quality of life if the wrong choice is made. The decision to enroll in one plan over another can involve comparing over 15 plans across many categories. Within this context, the large amount of complex information and reduced working memory capacity puts older adults' decision making at a disadvantage. An intentionally designed ES, such as an info-vis that reduces working memory demand, may assist older adults in making the most effective decision among many options. The objective of this study is to examine whether the use of an info-vis can lower working memory demands and positively affect complex decision-making performance of older adults in the context of choosing a Medicare prescription drug plan. Participants performed a computerized decision-making task in the context of finding the best health care plan. Data included quantitative decision-making performance indicators and surveys examining previous history with purchasing insurance. Participants used a colored info-vis ES or a table (no ES) to perform the decision task. Task difficulty was manipulated by increasing the number of selection criteria used to make an accurate decision. A repeated measures analysis was performed to examine differences between the two table designs. Twenty-three older adults between the ages of 66 and 80 completed the study. There was a main effect for accuracy such that older adults made more accurate decisions in the color info-vis condition than the table condition. In the low difficulty condition, participants were more successful at choosing the correct answer when the question was about the gap coverage attribute in the info-vis condition. Participants also made significantly faster decisions in the info-vis condition than in the table condition. Reducing the working memory demand of the task through the use of an ES can improve decision accuracy, especially when selection criteria is only focused on a single attribute of the insurance plan.

Outcome based state budget allocation for diabetes prevention programs using multi-criteria optimization with robust weights.

PubMed

Mehrotra, Sanjay; Kim, Kibaek

2011-12-01

We consider the problem of outcomes based budget allocations to chronic disease prevention programs across the United States (US) to achieve greater geographical healthcare equity. We use Diabetes Prevention and Control Programs (DPCP) by the Center for Disease Control and Prevention (CDC) as an example. We present a multi-criteria robust weighted sum model for such multi-criteria decision making in a group decision setting. The principal component analysis and an inverse linear programming techniques are presented and used to study the actual 2009 budget allocation by CDC. Our results show that the CDC budget allocation process for the DPCPs is not likely model based. In our empirical study, the relative weights for different prevalence and comorbidity factors and the corresponding budgets obtained under different weight regions are discussed. Parametric analysis suggests that money should be allocated to states to promote diabetes education and to increase patient-healthcare provider interactions to reduce disparity across the US.

Making decisions based on an imperfect ensemble of climate simulators: strategies and future directions

NASA Astrophysics Data System (ADS)

Sanderson, B. M.

2017-12-01

The CMIP ensembles represent the most comprehensive source of information available to decision-makers for climate adaptation, yet it is clear that there are fundamental limitations in our ability to treat the ensemble as an unbiased sample of possible future climate trajectories. There is considerable evidence that models are not independent, and increasing complexity and resolution combined with computational constraints prevent a thorough exploration of parametric uncertainty or internal variability. Although more data than ever is available for calibration, the optimization of each model is influenced by institutional priorities, historical precedent and available resources. The resulting ensemble thus represents a miscellany of climate simulators which defy traditional statistical interpretation. Models are in some cases interdependent, but are sufficiently complex that the degree of interdependency is conditional on the application. Configurations have been updated using available observations to some degree, but not in a consistent or easily identifiable fashion. This means that the ensemble cannot be viewed as a true posterior distribution updated by available data, but nor can observational data alone be used to assess individual model likelihood. We assess recent literature for combining projections from an imperfect ensemble of climate simulators. Beginning with our published methodology for addressing model interdependency and skill in the weighting scheme for the 4th US National Climate Assessment, we consider strategies for incorporating process-based constraints on future response, perturbed parameter experiments and multi-model output into an integrated framework. We focus on a number of guiding questions: Is the traditional framework of confidence in projections inferred from model agreement leading to biased or misleading conclusions? Can the benefits of upweighting skillful models be reconciled with the increased risk of truth lying outside the weighted ensemble distribution? If CMIP is an ensemble of partially informed best-guesses, can we infer anything about the parent distribution of all possible models of the climate system (and if not, are we implicitly under-representing the risk of a climate catastrophe outside of the envelope of CMIP simulations)?

Universal Physical Fitness Testing for United States Guardians Afloat

DTIC Science & Technology

2016-06-10

not engage in regular physical activities and are likely metabolically obese normal-weight, better known as skinny fat. The U.S. Government, through...of Guardians do not engage in regular physical activities and are likely metabolically obese normal-weight, better known as skinny fat. The U.S...Military Decision Making Process MONW Metabolically Obese Normal Weight NOAA National Oceanic and Atmospheric Administration PFT Physical Fitness

Pharmaceutical counselling about different types of tablet-splitting methods based on the results of weighing tests and mechanical development of splitting devices.

PubMed

Somogyi, O; Meskó, A; Csorba, L; Szabó, P; Zelkó, R

2017-08-30

The division of tablets and adequate methods of splitting them are a complex problem in all sectors of health care. Although tablet-splitting is often required, this procedure can be difficult for patients. Four tablets were investigated with different external features (shape, score-line, film-coat and size). The influencing effect of these features and the splitting methods was investigated according to the precision and "weight loss" of splitting techniques. All four types of tablets were halved by four methods: by hand, with a kitchen knife, with an original manufactured splitting device and with a modified tablet splitter based on a self-developed mechanical model. The mechanical parameters (harness and friability) of the products were measured during the study. The "weight loss" and precision of splitting methods were determined and compared by statistical analysis. On the basis of the results, the external features (geometry), the mechanical parameters of tablets and the mechanical structure of splitting devices can influence the "weight loss" and precision of tablet-splitting. Accordingly, a new decision-making scheme was developed for the selection of splitting methods. In addition, the skills of patients and the specialties of therapy should be considered so that pharmaceutical counselling can be more effective regarding tablet-splitting. Copyright © 2017 Elsevier B.V. All rights reserved.

Cloud E-Learning Service Strategies for Improving E-Learning Innovation Performance in a Fuzzy Environment by Using a New Hybrid Fuzzy Multiple Attribute Decision-Making Model

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…

Multiattribute evaluation in formulary decision making as applied to calcium-channel blockers.

PubMed

Schumacher, G E

1991-02-01

The use of multiattribute utility theory (MAUT) to make a formulary decision involving calcium-channel blockers (CCBs) is described. The MAUT method is a procedure for identifying, characterizing, and comparing the many variables that may affect a decision. Although applications in pharmacy have been infrequent, MAUT should be particularly appealing to formulary committees. The steps of the MAUT method are (1) determine the viewpoint of the decision makers, (2) identify the decision alternatives, (3) identify the attributes to be evaluated, (4) identify the factors to be used in evaluating the attributes, (5) establish a utility scale for scoring each factor, (6) transform the values for each factor to its utility scale, (7) determine weights for each attribute and factor, (8) calculate the total utility score for each decision alternative, (9) determine which decision alternative has the greatest total score, and (10) perform a sensitivity analysis. The viewpoint of a formulary committee in a health maintenance organization was simulated to develop a model for using the MAUT method to compare CCBs for single-agent therapy of chronic stable angina in ambulatory patients for one year. The attributes chosen were effectiveness, safety, patient acceptance, and cost and weighted 36%, 29%, 21%, and 14%, respectively, as contributions to the evaluation. The rank order of the decision alternatives was (1) generic verapamil, (2) brand-name verapamil, (3) diltiazem, (4) nicardipine, and (5) nifedipine. The MAUT method provides a standardized yet flexible format for comparing and selecting among formulary alternatives.

The best bits in an iris code.

PubMed

Hollingsworth, Karen P; Bowyer, Kevin W; Flynn, Patrick J

2009-06-01

Iris biometric systems apply filters to iris images to extract information about iris texture. Daugman's approach maps the filter output to a binary iris code. The fractional Hamming distance between two iris codes is computed and decisions about the identity of a person are based on the computed distance. The fractional Hamming distance weights all bits in an iris code equally. However, not all the bits in an iris code are equally useful. Our research is the first to present experiments documenting that some bits are more consistent than others. Different regions of the iris are compared to evaluate their relative consistency, and contrary to some previous research, we find that the middle bands of the iris are more consistent than the inner bands. The inconsistent-bit phenomenon is evident across genders and different filter types. Possible causes of inconsistencies, such as segmentation, alignment issues, and different filters are investigated. The inconsistencies are largely due to the coarse quantization of the phase response. Masking iris code bits corresponding to complex filter responses near the axes of the complex plane improves the separation between the match and nonmatch Hamming distance distributions.

The effects of spatially separated call components on phonotaxis in túngara frogs: evidence for auditory grouping.

PubMed

Farris, Hamilton E; Rand, A Stanley; Ryan, Michael J

2002-01-01

Numerous animals across disparate taxa must identify and locate complex acoustic signals imbedded in multiple overlapping signals and ambient noise. A requirement of this task is the ability to group sounds into auditory streams in which sounds are perceived as emanating from the same source. Although numerous studies over the past 50 years have examined aspects of auditory grouping in humans, surprisingly few assays have demonstrated auditory stream formation or the assignment of multicomponent signals to a single source in non-human animals. In our study, we present evidence for auditory grouping in female túngara frogs. In contrast to humans, in which auditory grouping may be facilitated by the cues produced when sounds arrive from the same location, we show that spatial cues play a limited role in grouping, as females group discrete components of the species' complex call over wide angular separations. Furthermore, we show that once grouped the separate call components are weighted differently in recognizing and locating the call, so called 'what' and 'where' decisions, respectively. Copyright 2002 S. Karger AG, Basel

Effect of CMC Molecular Weight on Acid-Induced Gelation of Heated WPI-CMC Soluble Complex.

PubMed

Huan, Yan; Zhang, Sha; Vardhanabhuti, Bongkosh

2016-02-01

Acid-induced gelation properties of heated whey protein isolate (WPI) and carboxymethylcellulose (CMC) soluble complex were investigated as a function of CMC molecular weight (270, 680, and 750 kDa) and concentrations (0% to 0.125%). Heated WPI-CMC soluble complex with 6% protein was made by heating biopolymers together at pH 7.0 and 85 °C for 30 min and diluted to 5% protein before acid-induced gelation. Acid-induced gel formed from heated WPI-CMC complexes exhibited increased hardness and decreased water holding capacity with increasing CMC concentrations but gel strength decreased at higher CMC content. The highest gel strength was observed with CMC 750 k at 0.05%. Gels with low CMC concentration showed homogenous microstructure which was independent of CMC molecular weight, while increasing CMC concentration led to microphase separation with higher CMC molecular weight showing more extensive phase separation. When heated WPI-CMC complexes were prepared at 9% protein the acid gels showed improved gel hardness and water holding capacity, which was supported by the more interconnected protein network with less porosity when compared to complexes heated at 6% protein. It is concluded that protein concentration and biopolymer ratio during complex formation are the major factors affecting gel properties while the effect of CMC molecular weight was less significant. © 2016 Institute of Food Technologists®

Fault Detection of Aircraft System with Random Forest Algorithm and Similarity Measure

PubMed Central

Park, Wookje; Jung, Sikhang

2014-01-01

Research on fault detection algorithm was developed with the similarity measure and random forest algorithm. The organized algorithm was applied to unmanned aircraft vehicle (UAV) that was readied by us. Similarity measure was designed by the help of distance information, and its usefulness was also verified by proof. Fault decision was carried out by calculation of weighted similarity measure. Twelve available coefficients among healthy and faulty status data group were used to determine the decision. Similarity measure weighting was done and obtained through random forest algorithm (RFA); RF provides data priority. In order to get a fast response of decision, a limited number of coefficients was also considered. Relation of detection rate and amount of feature data were analyzed and illustrated. By repeated trial of similarity calculation, useful data amount was obtained. PMID:25057508

Does unconscious thought improve complex decision making?

PubMed

Rey, Arnaud; Goldstein, Ryan M; Perruchet, Pierre

2009-05-01

In a recent study, Dijksterhuis et al. (Science 311:1005, 2006) reported that participants were better at solving complex decisions after a period of unconscious thought relative to a period of conscious thought. They interpreted their results as an existence proof of powerful unconscious deliberation mechanisms. In the present report, we used a similar experimental design with an additional control, immediate condition, and we observed that participants produced as good (and even descriptively better) decisions in this condition than in the "unconscious" one, hence challenging the initial interpretation of the authors. However, we still obtained lower performances in the "conscious" relative to the "immediate" condition, suggesting that the initial result of Dijksterhuis et al. was not due to the action of powerful unconscious thought processes, but to the apparent disadvantage of further conscious processing. We provide an explanation for this observation on the basis of current models of decision making. It is finally concluded that the benefit of unconscious thought in complex decision making is still a controversial issue that should be considered cautiously.

Assessing reservoir operations risk under climate change

USGS Publications Warehouse

Brekke, L.D.; Maurer, E.P.; Anderson, J.D.; Dettinger, M.D.; Townsley, E.S.; Harrison, A.; Pruitt, T.

2009-01-01

Risk-based planning offers a robust way to identify strategies that permit adaptive water resources management under climate change. This paper presents a flexible methodology for conducting climate change risk assessments involving reservoir operations. Decision makers can apply this methodology to their systems by selecting future periods and risk metrics relevant to their planning questions and by collectively evaluating system impacts relative to an ensemble of climate projection scenarios (weighted or not). This paper shows multiple applications of this methodology in a case study involving California's Central Valley Project and State Water Project systems. Multiple applications were conducted to show how choices made in conducting the risk assessment, choices known as analytical design decisions, can affect assessed risk. Specifically, risk was reanalyzed for every choice combination of two design decisions: (1) whether to assume climate change will influence flood-control constraints on water supply operations (and how), and (2) whether to weight climate change scenarios (and how). Results show that assessed risk would motivate different planning pathways depending on decision-maker attitudes toward risk (e.g., risk neutral versus risk averse). Results also show that assessed risk at a given risk attitude is sensitive to the analytical design choices listed above, with the choice of whether to adjust flood-control rules under climate change having considerably more influence than the choice on whether to weight climate scenarios. Copyright 2009 by the American Geophysical Union.

Decision Making in Action: Applying Research to Practice

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Hart, Sandra G. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers, aviation, and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment: Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multi-dimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for training will be discussed.

Comparative analysis of decision maker preferences for equity/efficiency attributes in reimbursement decisions in three European countries.

PubMed

Baji, Petra; García-Goñi, Manuel; Gulácsi, László; Mentzakis, Emmanouil; Paolucci, Francesco

2016-09-01

In addition to cost-effectiveness, national guidelines often include other factors in reimbursement decisions. However, weights attached to these are rarely quantified, thus decisions can depend strongly on decision-maker preferences. To explore the preferences of policymakers and healthcare professionals involved in the decision-making process for different efficiency and equity attributes of interventions and to analyse cross-country differences. Discrete choice experiments (DCEs) were carried out in Austria, Hungary, and Norway with policymakers and other professionals working in the health industry (N = 153 respondents). Interventions were described in terms of different efficiency and equity attributes (severity of disease, target age of the population and willingness to subsidise others, potential number of beneficiaries, individual health benefit, and cost-effectiveness). Parameter estimates from the DCE were used to calculate the probability of choosing a healthcare intervention with different characteristics, and to rank different equity and efficiency attributes according to their importance. In all three countries, cost-effectiveness, individual health benefit and severity of the disease were significant and equally important determinants of decisions. All countries show preferences for interventions targeting young and middle aged populations compared to those targeting populations over 60. However, decision-makers in Austria and Hungary show preferences more oriented to efficiency than equity, while those in Norway show equal preferences for equity and efficiency attributes. We find that factors other than cost-effectiveness seem to play an equally important role in decision-making. We also find evidence of cross-country differences in the weight of efficiency and equity attributes.

Designing for psychological change: individuals' reward and cost valuations in weight management.

PubMed

Hsu, Anne; Blandford, Ann

2014-06-26

Knowledge of the psychological constructs that underlie behavior offers valuable design opportunities for persuasive systems. We use the decision theory, which describes how behavior is underpinned by reward-cost valuations, as a framework for investigating such psychological constructs to deliver design objectives for weight management technologies. We applied a decision theory-based analysis in the domain of weight management to understand the rewards and costs that surround individuals' weight management behaviors, with the aim of uncovering design opportunities for weight management technologies. We conducted qualitative interviews with 15 participants who were or had been trying to lose weight. Thematic analysis was used to extract themes that covered the rewards and costs surrounding weight management behaviors. We supplemented our qualitative study with a quantitative survey of 100 respondents investigating the extent to which they agreed with statements reflecting themes from the qualitative study. The primary obstacles to weight management were the rewards associated with unhealthy choices, such as the pleasures of unhealthy foods and unrestricted consumption in social situations, and the significant efforts required to change habits, plan, and exercise. Psychological constructs that supported positive weight management included feeling good after making healthy choices, being good to oneself, experiencing healthy yet still delicious foods, and receiving social support and encouraging messages (although opinions about encouraging messages was mixed). A rewards-costs driven enquiry revealed a wide range of psychological constructs that contribute to discouraging and supporting weight management. The constructs extracted from our qualitative study were verified by our quantitative survey, in which the majority of respondents also reported similar thoughts and feelings. This understanding of the rewards and costs surrounding weight management offers a range of new opportunities for the design of weight management technologies that enhance the encouraging factors and alleviate the discouraging ones.

When 'solutions of yesterday become problems of today': crisis-ridden decision making in a complex adaptive system (CAS)--the Additional Duty Hours Allowance in Ghana.

PubMed

Agyepong, Irene Akua; Kodua, Augustina; Adjei, Sam; Adam, Taghreed

2012-10-01

Implementation of policies (decisions) in the health sector is sometimes defeated by the system's response to the policy itself. This can lead to counter-intuitive, unanticipated, or more modest effects than expected by those who designed the policy. The health sector fits the characteristics of complex adaptive systems (CAS) and complexity is at the heart of this phenomenon. Anticipating both positive and negative effects of policy decisions, understanding the interests, power and interaction between multiple actors; and planning for the delayed and distal impact of policy decisions are essential for effective decision making in CAS. Failure to appreciate these elements often leads to a series of reductionist approach interventions or 'fixes'. This in turn can initiate a series of negative feedback loops that further complicates the situation over time. In this paper we use a case study of the Additional Duty Hours Allowance (ADHA) policy in Ghana to illustrate these points. Using causal loop diagrams, we unpack the intended and unintended effects of the policy and how these effects evolved over time. The overall goal is to advance our understanding of decision making in complex adaptive systems; and through this process identify some essential elements in formulating, updating and implementing health policy that can help to improve attainment of desired outcomes and minimize negative unintended effects.

General Quantum Meet-in-the-Middle Search Algorithm Based on Target Solution of Fixed Weight

NASA Astrophysics Data System (ADS)

Fu, Xiang-Qun; Bao, Wan-Su; Wang, Xiang; Shi, Jian-Hong

2016-10-01

Similar to the classical meet-in-the-middle algorithm, the storage and computation complexity are the key factors that decide the efficiency of the quantum meet-in-the-middle algorithm. Aiming at the target vector of fixed weight, based on the quantum meet-in-the-middle algorithm, the algorithm for searching all n-product vectors with the same weight is presented, whose complexity is better than the exhaustive search algorithm. And the algorithm can reduce the storage complexity of the quantum meet-in-the-middle search algorithm. Then based on the algorithm and the knapsack vector of the Chor-Rivest public-key crypto of fixed weight d, we present a general quantum meet-in-the-middle search algorithm based on the target solution of fixed weight, whose computational complexity is \\sumj = 0d {(O(\\sqrt {Cn - k + 1d - j }) + O(C_kj log C_k^j))} with Σd i =0 Ck i memory cost. And the optimal value of k is given. Compared to the quantum meet-in-the-middle search algorithm for knapsack problem and the quantum algorithm for searching a target solution of fixed weight, the computational complexity of the algorithm is lower. And its storage complexity is smaller than the quantum meet-in-the-middle-algorithm. Supported by the National Basic Research Program of China under Grant No. 2013CB338002 and the National Natural Science Foundation of China under Grant No. 61502526

Healthcare tariffs for specialist inpatient neurorehabilitation services: rationale and development of a UK casemix and costing methodology.

PubMed

Turner-Stokes, Lynne; Sutch, Stephen; Dredge, Robert

2012-03-01

To describe the rationale and development of a casemix model and costing methodology for tariff development for specialist neurorehabilitation services in the UK. Patients with complex needs incur higher treatment costs. Fair payment should be weighted in proportion to costs of providing treatment, and should allow for variation over time CASEMIX MODEL AND BAND-WEIGHTING: Case complexity is measured by the Rehabilitation Complexity Scale (RCS). Cases are divided into five bands of complexity, based on the total RCS score. The principal determinant of costs in rehabilitation is staff time. Total staff hours/week (estimated from the Northwick Park Nursing and Therapy Dependency Scales) are analysed within each complexity band, through cross-sectional analysis of parallel ratings. A 'band-weighting' factor is derived from the relative proportions of staff time within each of the five bands. Total unit treatment costs are obtained from retrospective analysis of provider hospitals' budget and accounting statements. Mean bed-day costs (total unit cost/occupied bed days) are divided broadly into 'variable' and 'non-variable' components. In the weighted costing model, the band-weighting factor is applied to the variable portion of the bed-day cost to derive a banded cost, and thence a set of cost-multipliers. Preliminary data from one unit are presented to illustrate how this weighted costing model will be applied to derive a multilevel banded payment model, based on serial complexity ratings, to allow for change over time.

Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment.

PubMed

Onüt, Semih; Soner, Selin

2008-01-01

Site selection is an important issue in waste management. Selection of the appropriate solid waste site requires consideration of multiple alternative solutions and evaluation criteria because of system complexity. Evaluation procedures involve several objectives, and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision-making (MCDM) has been found to be a useful approach to solve this kind of problem. Different MCDM models have been applied to solve this problem. But most of them are basically mathematical and ignore qualitative and often subjective considerations. It is easier for a decision-maker to describe a value for an alternative by using linguistic terms. In the fuzzy-based method, the rating of each alternative is described using linguistic terms, which can also be expressed as triangular fuzzy numbers. Furthermore, there have not been any studies focused on the site selection in waste management using both fuzzy TOPSIS (technique for order preference by similarity to ideal solution) and AHP (analytical hierarchy process) techniques. In this paper, a fuzzy TOPSIS based methodology is applied to solve the solid waste transshipment site selection problem in Istanbul, Turkey. The criteria weights are calculated by using the AHP.

A Multi-Area Stochastic Model for a Covert Visual Search Task.

PubMed

Schwemmer, Michael A; Feng, Samuel F; Holmes, Philip J; Gottlieb, Jacqueline; Cohen, Jonathan D

2015-01-01

Decisions typically comprise several elements. For example, attention must be directed towards specific objects, their identities recognized, and a choice made among alternatives. Pairs of competing accumulators and drift-diffusion processes provide good models of evidence integration in two-alternative perceptual choices, but more complex tasks requiring the coordination of attention and decision making involve multistage processing and multiple brain areas. Here we consider a task in which a target is located among distractors and its identity reported by lever release. The data comprise reaction times, accuracies, and single unit recordings from two monkeys' lateral interparietal area (LIP) neurons. LIP firing rates distinguish between targets and distractors, exhibit stimulus set size effects, and show response-hemifield congruence effects. These data motivate our model, which uses coupled sets of leaky competing accumulators to represent processes hypothesized to occur in feature-selective areas and limb motor and pre-motor areas, together with the visual selection process occurring in LIP. Model simulations capture the electrophysiological and behavioral data, and fitted parameters suggest that different connection weights between LIP and the other cortical areas may account for the observed behavioral differences between the animals.

Beyond greener pastures: exploring contexts surrounding Filipino nurse migration in Canada through oral history.

PubMed

Ronquillo, Charlene; Boschma, Geertje; Wong, Sabrina T; Quiney, Linda

2011-09-01

The history of immigrant Filipino nurses in Canada has received little attention, yet Canada is a major receiving country of a growing number of Filipino migrants and incorporates Filipino immigrant nurses into its healthcare workforce at a steady rate. This study aims to look beyond the traditional economic and policy analysis perspectives of global migration and beyond the push and pull factors commonly discussed in the migration literature. Through oral history, this study explores biographical histories of nine Filipino immigrant nurses currently working in British Columbia and Alberta, Canada. Narratives reveal the instrumental role of the deeply embedded culture of migration in the Philippines in influencing Filipino nurses to migrate. Additionally, the stories illustrate the weight of cultural pressures and societal constructs these nurses faced that first colored their decision to pursue a career in nursing and ultimately to pursue emigration. Oral history is a powerful tool for examining migration history and sheds light on nuances of experience that might otherwise be neglected. This study explores the complex connections between various factors motivating Filipino nurse migration, the decision-making process, and other pre-migration experiences. © 2011 Blackwell Publishing Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Onuet, Semih; Soner, Selin

Site selection is an important issue in waste management. Selection of the appropriate solid waste site requires consideration of multiple alternative solutions and evaluation criteria because of system complexity. Evaluation procedures involve several objectives, and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision-making (MCDM) has been found to be a useful approach to solve this kind of problem. Different MCDM models have been applied to solve this problem. But most of them are basically mathematical and ignore qualitative and often subjective considerations. It is easier for a decision-maker tomore » describe a value for an alternative by using linguistic terms. In the fuzzy-based method, the rating of each alternative is described using linguistic terms, which can also be expressed as triangular fuzzy numbers. Furthermore, there have not been any studies focused on the site selection in waste management using both fuzzy TOPSIS (technique for order preference by similarity to ideal solution) and AHP (analytical hierarchy process) techniques. In this paper, a fuzzy TOPSIS based methodology is applied to solve the solid waste transshipment site selection problem in Istanbul, Turkey. The criteria weights are calculated by using the AHP.« less

Identifying the mechanisms through which behavioral weight-loss treatment improves food decision-making in obesity.

PubMed

Demos, Kathryn E; McCaffery, Jeanne M; Thomas, J Graham; Mailloux, Kimberly A; Hare, Todd A; Wing, Rena R

2017-07-01

Behavioral weight loss (BWL) programs are the recommended treatment for obesity, yet it is unknown whether these programs change one's ability to use self-control in food choices and what specific mechanisms support such change. Using experimental economics methods, we investigated whether changes in dietary behavior in individuals with obesity following BWL are driven by one or more of the following potential mechanisms: changes in the perception of the 1) health or 2) taste of food items, and/or 3) shifting decision weights for health versus taste attributes. Therefore, we compared these mechanisms between obese participants and lifetime normal weight controls (NW) both before and after BWL. Females with obesity (N = 37, mean BMI = 33.2) completed a food choice task involving health ratings, taste ratings, and decision-making pre- and post-standard BWL intervention. NW controls (N = 30, BMI = 22.4) completed the same task. Individuals with obesity exhibited increased self-control (selecting healthier, less tasty food choices) post-treatment. However, their rates of self-control remained significantly lower than NW. We found no differences in initial health perceptions across groups, and no changes with treatment. In contrast, taste ratings and the relative value of taste versus health decreased following treatment. Although, post-treatment participants continued to perceive unhealthy foods as tastier and used less self-control than NW controls, they showed significant improvements in these domains following a BWL intervention. To help individuals improve dietary decisions, additional research is needed to determine how to make greater changes in taste preferences and/or the assignment of value to taste versus health attributes in food choices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-criteria GIS-based siting of an incineration plant for municipal solid waste.

PubMed

Tavares, Gilberto; Zsigraiová, Zdena; Semiao, Viriato

2011-01-01

Siting a municipal solid waste (MSW) incineration plant requires a comprehensive evaluation to identify the best available location(s) that can simultaneously meet the requirements of regulations and minimise economic, environmental, health, and social costs. A spatial multi-criteria evaluation methodology is presented to assess land suitability for a plant siting and applied to Santiago Island of Cape Verde. It combines the analytical hierarchy process (AHP) to estimate the selected evaluation criteria weights with Geographic Information Systems (GIS) for spatial data analysis that avoids the subjectivity of the judgements of decision makers in establishing the influences between some criteria or clusters of criteria. An innovative feature of the method lies in incorporating the environmental impact assessment of the plant operation as a criterion in the decision-making process itself rather than as an a posteriori assessment. Moreover, a two-scale approach is considered. At a global scale an initial screening identifies inter-municipal zones satisfying the decisive requirements (socio-economic, technical and environmental issues, with weights respectively, of 48%, 41% and 11%). A detailed suitability ranking inside the previously identified zones is then performed at a local scale in two phases and includes environmental assessment of the plant operation. Those zones are ranked by combining the non-environmental feasibility of Phase 1 (with a weight of 75%) with the environmental assessment of the plant operation impact of Phase 2 (with a weight of 25%). The reliability and robustness of the presented methodology as a decision supporting tool is assessed through a sensitivity analysis. The results proved the system effectiveness in the ranking process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Learn ++.NC: combining ensemble of classifiers with dynamically weighted consult-and-vote for efficient incremental learning of new classes.

PubMed

Muhlbaier, Michael D; Topalis, Apostolos; Polikar, Robi

2009-01-01

We have previously introduced an incremental learning algorithm Learn(++), which learns novel information from consecutive data sets by generating an ensemble of classifiers with each data set, and combining them by weighted majority voting. However, Learn(++) suffers from an inherent "outvoting" problem when asked to learn a new class omega(new) introduced by a subsequent data set, as earlier classifiers not trained on this class are guaranteed to misclassify omega(new) instances. The collective votes of earlier classifiers, for an inevitably incorrect decision, then outweigh the votes of the new classifiers' correct decision on omega(new) instances--until there are enough new classifiers to counteract the unfair outvoting. This forces Learn(++) to generate an unnecessarily large number of classifiers. This paper describes Learn(++).NC, specifically designed for efficient incremental learning of multiple new classes using significantly fewer classifiers. To do so, Learn (++).NC introduces dynamically weighted consult and vote (DW-CAV), a novel voting mechanism for combining classifiers: individual classifiers consult with each other to determine which ones are most qualified to classify a given instance, and decide how much weight, if any, each classifier's decision should carry. Experiments on real-world problems indicate that the new algorithm performs remarkably well with substantially fewer classifiers, not only as compared to its predecessor Learn(++), but also as compared to several other algorithms recently proposed for similar problems.

Changing Times, Complex Decisions: Presidential Values and Decision Making

ERIC Educational Resources Information Center

Hornak, Anne M.; Garza Mitchell, Regina L.

2016-01-01

Objective: The objective of this article is to delve more deeply into the thought processes of the key decision makers at community colleges and understand how they make decisions. Specifically, this article focuses on the role of the community college president's personal values in decision making. Method: We conducted interviews with 13…

The Role of Epistemic Motivation in Individuals' Response to Decision Complexity

ERIC Educational Resources Information Center

Amit, Adi; Sagiv, Lilach

2013-01-01

Integrating findings on the effects of more alternatives with findings on the effects of more attributes, we offer a motivational decision-making model, suggesting that epistemic motivation moderates individuals' responses to complex information. Study 1 empirically investigated the shared essence of four conceptualizations of epistemic…

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

NASA Astrophysics Data System (ADS)

Flaming, Susan C.

2007-12-01

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

A Dynamic, Stochastic, Computational Model of Preference Reversal Phenomena

ERIC Educational Resources Information Center

Johnson, Joseph G.; Busemeyer, Jerome R.

2005-01-01

Preference orderings among a set of options may depend on the elicitation method (e.g., choice or pricing); these preference reversals challenge traditional decision theories. Previous attempts to explain these reversals have relied on allowing utility of the options to change across elicitation methods by changing the decision weights, the…

Weight of evidence evaluation of adverse outcome pathways converging at impaired vitellogenin synthesis leading to reproductive impairment

EPA Science Inventory

Adverse outcome pathways (AOPs) provide a framework that supports greater use of mechanistic data measured at lower levels of biological organization as a basis for regulatory decision-making. However, it is recognized that different types of regulatory applications and decisions...

Insights into university freshman weight issues and how they make decisions about eating

USDA-ARS?s Scientific Manuscript database

The transition from high school to college represents a turning point during which health behavior trajectories may be influenced. This study addresses the internal and external factors that guide students’ eating decisions as they are understood and relayed by students through ethnographic, qualit...

Decision-making Capacity for Treatment of Psychotic Patients on Long Acting Injectable Antipsychotic Treatment.

PubMed

Nystazaki, Maria; Pikouli, Katerina; Tsapakis, Eva-Maria; Karanikola, Maria; Ploumpidis, Dimitrios; Alevizopoulos, Giorgos

2018-04-01

Providing informed, consent requires patients' Decision-Making Capacity for treatment. We evaluated the Decision Making Capacity of outpatients diagnosed with schizophrenia and schizoaffective disorder on treatment with Long Acting Injectable Antipsychotic medication. This is a retrospective, cross-sectional, correlational study conducted at two Depot Clinics in Athens, Greece. Participants included 65 outpatients diagnosed with schizophrenia and schizoaffective disorder on treatment with Long Acting Injectable Antipsychotics. Over half of the participants showed poor understanding of the information given regarding their disease and treatment (Understanding subscale), however >70% seemed to comprehend the relevance of this information to their medical condition (Appreciation subscale). Moreover, half of the participants reported adequate reasoning ability (Reasoning subscale), whilst patients who gained >7% of their body weight scored statistically significantly higher in the subscales of Understanding and Appreciation. Our results suggest that there is a proportion of patients with significantly diminished Decision Making Capacity, hence a full assessment is recommended in order to track them down. Further research is needed to better interpret the association between antipsychotic induced weight gain and Decision Making Capacity in patients suffering from schizophrenia or schizoaffective disorder. Copyright © 2017 Elsevier Inc. All rights reserved.

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions.

PubMed

Stewart, G B; Mengersen, K; Meader, N

2014-03-01

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to 'empty' reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence. Copyright © 2013 John Wiley & Sons, Ltd.

Decision making in a human population living sustainably.

PubMed

Hicks, John S; Burgman, Mark A; Marewski, Julian N; Fidler, Fiona; Gigerenzer, Gerd

2012-10-01

The Tiwi people of northern Australia have managed natural resources continuously for 6000-8000 years. Tiwi management objectives and outcomes may reflect how they gather information about the environment. We qualitatively analyzed Tiwi documents and management techniques to examine the relation between the social and physical environment of decision makers and their decision-making strategies. We hypothesized that principles of bounded rationality, namely, the use of efficient rules to navigate complex decision problems, explain how Tiwi managers use simple decision strategies (i.e., heuristics) to make robust decisions. Tiwi natural resource managers reduced complexity in decision making through a process that gathers incomplete and uncertain information to quickly guide decisions toward effective outcomes. They used management feedback to validate decisions through an information loop that resulted in long-term sustainability of environmental use. We examined the Tiwi decision-making processes relative to management of barramundi (Lates calcarifer) fisheries and contrasted their management with the state government's management of barramundi. Decisions that enhanced the status of individual people and their attainment of aspiration levels resulted in reliable resource availability for Tiwi consumers. Different decision processes adopted by the state for management of barramundi may not secure similarly sustainable outcomes. ©2012 Society for Conservation Biology.

Real-time evaluation of polyphenol oxidase (PPO) activity in lychee pericarp based on weighted combination of spectral data and image features as determined by fuzzy neural network.

PubMed

Yang, Yi-Chao; Sun, Da-Wen; Wang, Nan-Nan; Xie, Anguo

2015-07-01

A novel method of using hyperspectral imaging technique with the weighted combination of spectral data and image features by fuzzy neural network (FNN) was proposed for real-time prediction of polyphenol oxidase (PPO) activity in lychee pericarp. Lychee images were obtained by a hyperspectral reflectance imaging system operating in the range of 400-1000nm. A support vector machine-recursive feature elimination (SVM-RFE) algorithm was applied to eliminating variables with no or little information for the prediction from all bands, resulting in a reduced set of optimal wavelengths. Spectral information at the optimal wavelengths and image color features were then used respectively to develop calibration models for the prediction of PPO in pericarp during storage, and the results of two models were compared. In order to improve the prediction accuracy, a decision strategy was developed based on weighted combination of spectral data and image features, in which the weights were determined by FNN for a better estimation of PPO activity. The results showed that the combined decision model was the best among all of the calibration models, with high R(2) values of 0.9117 and 0.9072 and low RMSEs of 0.45% and 0.459% for calibration and prediction, respectively. These results demonstrate that the proposed weighted combined decision method has great potential for improving model performance. The proposed technique could be used for a better prediction of other internal and external quality attributes of fruits. Copyright © 2015 Elsevier B.V. All rights reserved.

Assigning Resources to Health Care Use for Health Services Research: Options and Consequences

PubMed Central

Fishman, Paul A.; Hornbrook, Mark C.

2013-01-01

Aims Our goals are threefold: 1) to review the leading options for assigning resource coefficients to health services utilization; 2) to discuss the relative advantages of each option; and, 3) provide examples where the research question had marked implications for the choice of which resource measure to employ. Methods Three approaches have been used to establish relative resource weights in health services research: a) direct estimation of production costs through micro-costing or step down allocation methods; b) macro-costing/regression analysis; and, c) standardized resource assignment. We describe each of these methods and provide examples of how the study question drove the choice of resource use measure. Findings All empirical resource-intensity weighting systems contain distortions that limit their universal application. Hence, users must select the weighting system that matches the needs of their specific analysis. All systems require significant data resources and data processing. However, inattention to the distortions contained in a complex resource weighting system may undermine the validity and generalizability of an economic evaluation. Conclusions Direct estimation of production costs are useful for empirical analyses, but they contain distortions that undermine optimal resource allocation decisions. Researchers must ensure that the data being used meets both the study design and the question being addressed. They also should ensure that the choice of resource measure is the best fit for the analysis. Implications for Research and Policy Researchers should consider which of the available measures is the most appropriate for the question being addressed rather than take ‘cost’ or utilization as a variable over which they have no control PMID:19536002

Independent but coordinated trials: insights from the practice-based Opportunities for Weight Reduction Trials Collaborative Research Group.

PubMed

Yeh, Hsin-Chieh; Clark, Jeanne M; Emmons, Karen E; Moore, Reneé H; Bennett, Gary G; Warner, Erica T; Sarwer, David B; Jerome, Gerald J; Miller, Edgar R; Volger, Sheri; Louis, Thomas A; Wells, Barbara; Wadden, Thomas A; Colditz, Graham A; Appel, Lawrence J

2010-08-01

The National Heart, Lung, and Blood Institute (NHLBI) funded three institutions to conduct effectiveness trials of weight loss interventions in primary care settings. Unlike traditional multi-center clinical trials, each study was established as an independent trial with a distinct protocol. Still, efforts were made to coordinate and standardize several aspects of the trials. The three trials formed a collaborative group, the 'Practice-based Opportunities for Weight Reduction (POWER) Trials Collaborative Research Group.' We describe the common and distinct features of the three trials, the key characteristics of the collaborative group, and the lessons learned from this novel organizational approach. The Collaborative Research Group consists of three individual studies: 'Be Fit, Be Well' (Washington University in St. Louis/Harvard University), 'POWER Hopkins' (Johns Hopkins), and 'POWER-UP' (University of Pennsylvania). There are a total of 15 participating clinics with ~1100 participants. The common primary outcome is change in weight at 24 months of follow-up, but each protocol has trial-specific elements including different interventions and different secondary outcomes. A Resource Coordinating Unit at Johns Hopkins provides administrative support. The Collaborative Research Group established common components to facilitate potential cross-site comparisons. The main advantage of this approach is to develop and evaluate several interventions, when there is insufficient evidence to test one or two approaches, as would be done in a traditional multi-center trial. The challenges of the organizational design include the complex decision-making process, the extent of potential data pooling, time intensive efforts to standardize reports, and the additional responsibilities of the DSMB to monitor three distinct protocols.

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

Reasoning on Weighted Delegatable Authorizations

NASA Astrophysics Data System (ADS)

Ruan, Chun; Varadharajan, Vijay

This paper studies logic based methods for representing and evaluating complex access control policies needed by modern database applications. In our framework, authorization and delegation rules are specified in a Weighted Delegatable Authorization Program (WDAP) which is an extended logic program. We show how extended logic programs can be used to specify complex security policies which support weighted administrative privilege delegation, weighted positive and negative authorizations, and weighted authorization propagations. We also propose a conflict resolution method that enables flexible delegation control by considering priorities of authorization grantors and weights of authorizations. A number of rules are provided to achieve delegation depth control, conflict resolution, and authorization and delegation propagations.

Post-weaning and whole-of-life performance of pigs is determined by live weight at weaning and the complexity of the diet fed after weaning.

PubMed

Collins, Cherie L; Pluske, John R; Morrison, Rebecca S; McDonald, Trevor N; Smits, Robert J; Henman, David J; Stensland, Ingunn; Dunshea, Frank R

2017-12-01

The production performance and financial outcomes associated with weaner diet complexity for pigs of different weight classes at weaning were examined in this experiment. A total of 720 weaner pigs (360 entire males and 360 females) were selected at weaning (27 ± 3 d) and allocated to pens of 10 based on individual weaning weight (light weaning weight: pigs below 6.5 kg; medium weaning weight: 6.5 to 8 kg; heavy weaning weight: above 8.5 kg). Pens were then allocated in a 3 × 2 × 2 factorial arrangement of treatments with the respective factors being weaning weight (heavy, medium and light; H, M and L, respectively), weaner diet complexity (high complexity/cost, HC; low complexity/cost, LC), and gender (male and female). Common diets were fed to both treatment groups during the final 4 weeks of the weaner period (a period of 39 days). In the first 6 d after weaning, pigs offered the HC diets gained weight faster and used feed more efficiently than those offered the LC diets ( P  = 0.031). Pigs fed a HC diet after weaning tended to be heavier at the sale live weight of 123 d of age compared with pigs fed the LC diet ( P  = 0.056). There were no other main effects of the feeding program on growth performance through to slaughter. Weaning weight had a profound influence on lifetime growth performance and weight at 123 d of age, with H pigs at weaning increasing their weight advantage over the M and L pigs (101.3, 97.1, 89.6 kg respectively, P  < 0.001). Cost-benefit analyses suggested there was a minimal benefit in terms of cost per unit live weight gain over lifetime when pigs were offered a HC feeding program to L, with a lower feed cost/kg gain. The results from this investigation confirm the impact of weaning weight on lifetime growth performance, and suggest that a HC feeding program should be focused on L weaner pigs (i.e., weaning weight less than 6.5 kg at 27 d of age) in order to maximise financial returns.

Methods Used to Support a Life Cycle of Complex Engineering Products

NASA Astrophysics Data System (ADS)

Zakharova, Alexandra A.; Kolegova, Olga A.; Nekrasova, Maria E.; Eremenko, Andrey O.

2016-08-01

Management of companies involved in the design, development and operation of complex engineering products recognize the relevance of creating systems for product lifecycle management. A system of methods is proposed to support life cycles of complex engineering products, based on fuzzy set theory and hierarchical analysis. The system of methods serves to demonstrate the grounds for making strategic decisions in an environment of uncertainty, allows the use of expert knowledge, and provides interconnection of decisions at all phases of strategic management and all stages of a complex engineering product lifecycle.

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

NASA Astrophysics Data System (ADS)

Doherty, John; Simmons, Craig T.

2013-11-01

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

Feedback produces divergence from prospect theory in descriptive choice.

PubMed

Jessup, Ryan K; Bishara, Anthony J; Busemeyer, Jerome R

2008-10-01

A recent study demonstrated that individuals making experience-based choices underweight small probabilities, in contrast to the overweighting observed in a typical descriptive paradigm. We tested whether trial-by-trial feedback in a repeated descriptive paradigm would engender choices more correspondent with experiential or descriptive paradigms. The results of a repeated gambling task indicated that individuals receiving feedback underweighted small probabilities, relative to their no-feedback counterparts. These results implicate feedback as a critical component during the decision-making process, even in the presence of fully specified descriptive information. A model comparison at the individual-subject level suggested that feedback drove individuals' decision weights toward objective probability weighting.

Exponential operations and aggregation operators of interval neutrosophic sets and their decision making methods.

PubMed

Ye, Jun

2016-01-01

An interval neutrosophic set (INS) is a subclass of a neutrosophic set and a generalization of an interval-valued intuitionistic fuzzy set, and then the characteristics of INS are independently described by the interval numbers of its truth-membership, indeterminacy-membership, and falsity-membership degrees. However, the exponential parameters (weights) of all the existing exponential operational laws of INSs and the corresponding exponential aggregation operators are crisp values in interval neutrosophic decision making problems. As a supplement, this paper firstly introduces new exponential operational laws of INSs, where the bases are crisp values or interval numbers and the exponents are interval neutrosophic numbers (INNs), which are basic elements in INSs. Then, we propose an interval neutrosophic weighted exponential aggregation (INWEA) operator and a dual interval neutrosophic weighted exponential aggregation (DINWEA) operator based on these exponential operational laws and introduce comparative methods based on cosine measure functions for INNs and dual INNs. Further, we develop decision-making methods based on the INWEA and DINWEA operators. Finally, a practical example on the selecting problem of global suppliers is provided to illustrate the applicability and rationality of the proposed methods.

Eating Right: Linking Food-Related Decision-Making Concepts from Neuroscience, Psychology, and Education

ERIC Educational Resources Information Center

Doucerain, Matthias; Fellows, Lesley K.

2012-01-01

This literature review uses four dimensions to classify and compare how food-related decision-making is conceptualized and experimentally assessed in neuroscience and other disciplines: (1) food-related decision-making other than the decision of "what" to eat that is part of each eating episode, (2) decision complexes other than the…

The geometric nature of weights in real complex networks

NASA Astrophysics Data System (ADS)

Allard, Antoine; Serrano, M. Ángeles; García-Pérez, Guillermo; Boguñá, Marián

2017-01-01

The topology of many real complex networks has been conjectured to be embedded in hidden metric spaces, where distances between nodes encode their likelihood of being connected. Besides of providing a natural geometrical interpretation of their complex topologies, this hypothesis yields the recipe for sustainable Internet's routing protocols, sheds light on the hierarchical organization of biochemical pathways in cells, and allows for a rich characterization of the evolution of international trade. Here we present empirical evidence that this geometric interpretation also applies to the weighted organization of real complex networks. We introduce a very general and versatile model and use it to quantify the level of coupling between their topology, their weights and an underlying metric space. Our model accurately reproduces both their topology and their weights, and our results suggest that the formation of connections and the assignment of their magnitude are ruled by different processes.

3D printed renal cancer models derived from MRI data: application in pre-surgical planning.

PubMed

Wake, Nicole; Rude, Temitope; Kang, Stella K; Stifelman, Michael D; Borin, James F; Sodickson, Daniel K; Huang, William C; Chandarana, Hersh

2017-05-01

To determine whether patient-specific 3D printed renal tumor models change pre-operative planning decisions made by urological surgeons in preparation for complex renal mass surgical procedures. From our ongoing IRB approved study on renal neoplasms, ten renal mass cases were retrospectively selected based on Nephrometry Score greater than 5 (range 6-10). A 3D post-contrast fat-suppressed gradient-echo T1-weighted sequence was used to generate 3D printed models. The cases were evaluated by three experienced urologic oncology surgeons in a randomized fashion using (1) imaging data on PACS alone and (2) 3D printed model in addition to the imaging data. A questionnaire regarding surgical approach and planning was administered. The presumed pre-operative approaches with and without the model were compared. Any change between the presumed approaches and the actual surgical intervention was recorded. There was a change in planned approach with the 3D printed model for all ten cases with the largest impact seen regarding decisions on transperitoneal or retroperitoneal approach and clamping, with changes seen in 30%-50% of cases. Mean parenchymal volume loss for the operated kidney was 21.4%. Volume losses >20% were associated with increased ischemia times and surgeons tended to report a different approach with the use of the 3D model compared to that with imaging alone in these cases. The 3D printed models helped increase confidence regarding the chosen operative procedure in all cases. Pre-operative physical 3D models created from MRI data may influence surgical planning for complex kidney cancer.

On Convergence of Development Costs and Cost Models for Complex Spaceflight Instrument Electronics

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Patel, Umeshkumar D.; Kasa, Robert L.; Hestnes, Phyllis; Brown, Tammy; Vootukuru, Madhavi

2008-01-01

Development costs of a few recent spaceflight instrument electrical and electronics subsystems have diverged from respective heritage cost model predictions. The cost models used are Grass Roots, Price-H and Parametric Model. These cost models originated in the military and industry around 1970 and were successfully adopted and patched by NASA on a mission-by-mission basis for years. However, the complexity of new instruments recently changed rapidly by orders of magnitude. This is most obvious in the complexity of representative spaceflight instrument electronics' data system. It is now required to perform intermediate processing of digitized data apart from conventional processing of science phenomenon signals from multiple detectors. This involves on-board instrument formatting of computational operands from row data for example, images), multi-million operations per second on large volumes of data in reconfigurable hardware (in addition to processing on a general purpose imbedded or standalone instrument flight computer), as well as making decisions for on-board system adaptation and resource reconfiguration. The instrument data system is now tasked to perform more functions, such as forming packets and instrument-level data compression of more than one data stream, which are traditionally performed by the spacecraft command and data handling system. It is furthermore required that the electronics box for new complex instruments is developed for one-digit watt power consumption, small size and that it is light-weight, and delivers super-computing capabilities. The conflict between the actual development cost of newer complex instruments and its electronics components' heritage cost model predictions seems to be irreconcilable. This conflict and an approach to its resolution are addressed in this paper by determining the complexity parameters, complexity index, and their use in enhanced cost model.

Beyond Wiki to Judgewiki for Transparent Climate Change Decisions

NASA Astrophysics Data System (ADS)

Capron, M. E.

2008-12-01

Climate Change is like the prisoner's dilemma, a zero-sum game, or cheating in sports. Everyone and every country is tempted to selfishly maintain or advance their standard of living. The tremendous difference between standards of living amplifies the desire to opt out of Climate Change solutions adverse to economic competitiveness. Climate Change is also exceedingly complex. No one person, one organization, one country, or partial collection of countries has the capacity and the global support needed to make decisions on Climate Change solutions. There are thousands of potential actions, tens of thousands of known and unknown environmental and economic impacts. Some actions are belatedly found to be unsustainable beyond token volumes, corn ethanol or soy-biodiesel for example. Mankind can address human nature and complexity with a globally transparent information and decision process available to all 7 billion of us. We need a process that builds trust and simplifies complexity. Fortunately, we have the Internet for trust building communication and computers to simplify complexity. Mankind can produce new software tailored to the challenge. We would combine group information collection software (a wiki) with a decision-matrix (a judge), market forecasting, and video games to produce the tool mankind needs for trust building transparent decisions on Climate Change actions. The resulting software would be a judgewiki.

Ethical Issues in the Assessment and Treatment of a Rational Suicidal Client.

ERIC Educational Resources Information Center

Snipe, Rosetta M.

1988-01-01

Notes that rational client's decision to commit suicide may present complex ethical issues for therapist. Presents and discusses three-month account of therapy with client, from perspective of ethical values and principles upon which assessment and treatment decisions were made, and complex ethical dilemmas encountered as therapist juxtaposed…

Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

PubMed Central

2014-01-01

This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions). PMID:25152926

Salience driven value integration explains decision biases and preference reversal

PubMed Central

Tsetsos, Konstantinos; Chater, Nick; Usher, Marius

2012-01-01

Human choice behavior exhibits many paradoxical and challenging patterns. Traditional explanations focus on how values are represented, but little is known about how values are integrated. Here we outline a psychophysical task for value integration that can be used as a window on high-level, multiattribute decisions. Participants choose between alternative rapidly presented streams of numerical values. By controlling the temporal distribution of the values, we demonstrate that this process underlies many puzzling choice paradoxes, such as temporal, risk, and framing biases, as well as preference reversals. These phenomena can be explained by a simple mechanism based on the integration of values, weighted by their salience. The salience of a sampled value depends on its temporal order and momentary rank in the decision context, whereas the direction of the weighting is determined by the task framing. We show that many known choice anomalies may arise from the microstructure of the value integration process. PMID:22635271

False recall is reduced by damage to the ventromedial prefrontal cortex: implications for understanding the neural correlates of schematic memory.

PubMed

Warren, David E; Jones, Samuel H; Duff, Melissa C; Tranel, Daniel

2014-05-28

Schematic memory, or contextual knowledge derived from experience (Bartlett, 1932), benefits memory function by enhancing retention and speeding learning of related information (Bransford and Johnson, 1972; Tse et al., 2007). However, schematic memory can also promote memory errors, producing false memories. One demonstration is the "false memory effect" of the Deese-Roediger-McDermott (DRM) paradigm (Roediger and McDermott, 1995): studying words that fit a common schema (e.g., cold, blizzard, winter) often produces memory for a nonstudied word (e.g., snow). We propose that frontal lobe regions that contribute to complex decision-making processes by weighting various alternatives, such as ventromedial prefrontal cortex (vmPFC), may also contribute to memory processes by weighting the influence of schematic knowledge. We investigated the role of human vmPFC in false memory by combining a neuropsychological approach with the DRM task. Patients with vmPFC lesions (n = 7) and healthy comparison participants (n = 14) studied word lists that excluded a common associate (the critical item). Recall and recognition tests revealed expected high levels of false recall and recognition of critical items by healthy participants. In contrast, vmPFC patients showed consistently reduced false recall, with significantly fewer intrusions of critical items. False recognition was also marginally reduced among vmPFC patients. Our findings suggest that vmPFC increases the influence of schematically congruent memories, a contribution that may be related to the role of the vmPFC in decision making. These novel neuropsychological results highlight a role for the vmPFC as part of a memory network including the medial temporal lobes and hippocampus (Andrews-Hanna et al., 2010). Copyright © 2014 the authors 0270-6474/14/347677-06$15.00/0.

False Recall Is Reduced by Damage to the Ventromedial Prefrontal Cortex: Implications for Understanding the Neural Correlates of Schematic Memory

PubMed Central

Jones, Samuel H.; Duff, Melissa C.; Tranel, Daniel

2014-01-01

Schematic memory, or contextual knowledge derived from experience (Bartlett, 1932), benefits memory function by enhancing retention and speeding learning of related information (Bransford and Johnson, 1972; Tse et al., 2007). However, schematic memory can also promote memory errors, producing false memories. One demonstration is the “false memory effect” of the Deese–Roediger–McDermott (DRM) paradigm (Roediger and McDermott, 1995): studying words that fit a common schema (e.g., cold, blizzard, winter) often produces memory for a nonstudied word (e.g., snow). We propose that frontal lobe regions that contribute to complex decision-making processes by weighting various alternatives, such as ventromedial prefrontal cortex (vmPFC), may also contribute to memory processes by weighting the influence of schematic knowledge. We investigated the role of human vmPFC in false memory by combining a neuropsychological approach with the DRM task. Patients with vmPFC lesions (n = 7) and healthy comparison participants (n = 14) studied word lists that excluded a common associate (the critical item). Recall and recognition tests revealed expected high levels of false recall and recognition of critical items by healthy participants. In contrast, vmPFC patients showed consistently reduced false recall, with significantly fewer intrusions of critical items. False recognition was also marginally reduced among vmPFC patients. Our findings suggest that vmPFC increases the influence of schematically congruent memories, a contribution that may be related to the role of the vmPFC in decision making. These novel neuropsychological results highlight a role for the vmPFC as part of a memory network including the medial temporal lobes and hippocampus (Andrews-Hanna et al., 2010). PMID:24872571

Effects of task complexity on activation of language areas in a semantic decision fMRI protocol.

PubMed

Lopes, Tátila Martins; Yasuda, Clarissa Lin; de Campos, Brunno Machado; Balthazar, Marcio L F; Binder, Jeffrey R; Cendes, Fernando

2016-01-29

Language tasks used for clinical fMRI studies may be too complex for some patients with cognitive impairments, and "easier" versions are sometimes substituted, though the effects on brain activity of such changes in task complexity are largely unknown. To investigate these differences, we compared two versions of an fMRI language comprehension protocol, with different levels of difficulty, in 24 healthy right-handed adults. The protocol contrasted an auditory word comprehension task (semantic decision) with a nonspeech control task using tone sequences (tone decision). In the "complex" version (CV), the semantic decision task required two complex semantic decisions for each word, and the tone decision task required the participant to count the number of target tones in each sequence. In the "easy" version (EV), the semantic task required only a single easier decision, and the tone task required only detection of the presence or absence of a target tone in each sequence. The protocols were adapted for a Brazilian population. Typical left hemisphere language lateralization was observed in 92% of participants for both CV and EV using the whole-brain lateralization index, and typical language lateralization was also observed for others regions of interest. Task performance was superior on the EV compared to the CV (p=0.014). There were many common areas of activation across the two version; however, the CV produced greater activation in the left superior and middle frontal giri, angular gyrus, and left posterior cingulate gyrus compared to the EV, the majority of which are areas previously identified with language and semantic processing. The EV produced stronger activation only in a small area in the posterior middle temporal gyrus. These results reveal differences between two versions of the protocol and provide evidence that both are useful for language lateralization and worked well for Brazilian population. The complex version produces stronger activation in several nodes of the semantic network and therefore is elected for participants who can perform well these tasks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Combining multi-criteria decision analysis and mini-health technology assessment: A funding decision-support tool for medical devices in a university hospital setting.

PubMed

Martelli, Nicolas; Hansen, Paul; van den Brink, Hélène; Boudard, Aurélie; Cordonnier, Anne-Laure; Devaux, Capucine; Pineau, Judith; Prognon, Patrice; Borget, Isabelle

2016-02-01

At the hospital level, decisions about purchasing new and oftentimes expensive medical devices must take into account multiple criteria simultaneously. Multi-criteria decision analysis (MCDA) is increasingly used for health technology assessment (HTA). One of the most successful hospital-based HTA approaches is mini-HTA, of which a notable example is the Matrix4value model. To develop a funding decision-support tool combining MCDA and mini-HTA, based on Matrix4value, suitable for medical devices for individual patient use in French university hospitals - known as the IDA tool, short for 'innovative device assessment'. Criteria for assessing medical devices were identified from a literature review and a survey of 18 French university hospitals. Weights for the criteria, representing their relative importance, were derived from a survey of 25 members of a medical devices committee using an elicitation technique involving pairwise comparisons. As a test of its usefulness, the IDA tool was applied to two new drug-eluting beads (DEBs) for transcatheter arterial chemoembolization. The IDA tool comprises five criteria and weights for each of two over-arching categories: risk and value. The tool revealed that the two new DEBs conferred no additional value relative to DEBs currently available. Feedback from participating decision-makers about the IDA tool was very positive. The tool could help to promote a more structured and transparent approach to HTA decision-making in French university hospitals. Copyright © 2015 Elsevier Inc. All rights reserved.

Exaggerated Risk: Prospect Theory and Probability Weighting in Risky Choice

ERIC Educational Resources Information Center

Kusev, Petko; van Schaik, Paul; Ayton, Peter; Dent, John; Chater, Nick

2009-01-01

In 5 experiments, we studied precautionary decisions in which participants decided whether or not to buy insurance with specified cost against an undesirable event with specified probability and cost. We compared the risks taken for precautionary decisions with those taken for equivalent monetary gambles. Fitting these data to Tversky and…

Child Decision-Making: On the Burden of Predecisional Information Search

ERIC Educational Resources Information Center

Lindow, Stefanie; Betsch, Tilmann

2018-01-01

In many decision situations, individuals must actively search information before they can make a satisfying choice. In such instances, individuals must be aware of the fact that not all information may be equally relevant for the choice at hand--thus, individuals should weight information by its respective relevance. We compared children's and…

Insights into freshman weight issues: An ethnographic study of how first-year college students make decisions about eating

USDA-ARS?s Scientific Manuscript database

The transition from high school to college represents a life turning point during which health behavior trajectories may be influenced. This study addresses the internal and external factors that guide students’ eating decisions as they are understood and relayed by students through ethnographic, qu...

Age-Related Changes in Decision Making: Comparing Informed and Noninformed Situations

ERIC Educational Resources Information Center

Van Duijvenvoorde, Anna C. K.; Jansen, Brenda R. J.; Bredman, Joren C.; Huizenga, Hilde M.

2012-01-01

Advantageous decision making progressively develops into early adulthood, most specifically in complex and motivationally salient decision situations in which direct feedback on gains and losses is provided (Figner & Weber, 2011). However, the factors that underlie this developmental improvement in decision making are still not well understood.…

Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method.

PubMed

Liu, Hu-Chen; Wu, Jing; Li, Ping

2013-12-01

Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include "incineration", "steam sterilization", "microwave" and "landfill". The results obtained using the proposed approach are analyzed in a comparative way. Copyright © 2013. Published by Elsevier Ltd.

Maclaurin symmetric mean operators of linguistic intuitionistic fuzzy numbers and their application to multiple-attribute decision-making

NASA Astrophysics Data System (ADS)

Liu, Peide; Qin, Xiyou

2017-11-01

Linguistic intuitionistic fuzzy number (LIFN) is a special intuitionistic fuzzy number which can more easily describe the vagueness existing in the real decision-making. Maclaurin symmetric mean (MSM) operator has the characteristic of considering the interrelationships among any number of input parameters. In this paper, we extended the MSM operator to the LIFNs and some extended MSM operators for LIFNs were proposed, some new decision-making methods were developed. Firstly, we introduced the definition, score function, properties and operational rules of the LIFNs. Then, we proposed some linguistic intuitionistic fuzzy MSM operators, such as linguistic intuitionistic fuzzy Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy Maclaurin symmetric mean (WLIFMSM) operator, linguistic intuitionistic fuzzy dual Maclaurin symmetric mean operator, weighted linguistic intuitionistic fuzzy dual Maclaurin symmetric mean (WLIFDMSM) operator. In the meantime, we studied some important properties of these operators, and developed some methods based on WLIFMSM operator and WLIFDMSM operator for multi-attribute decision-making. Finally, we use an example to demonstrate the effectiveness of the proposed methods.

I know why you voted for Trump: (Over)inferring motives based on choice.

PubMed

Barasz, Kate; Kim, Tami; Evangelidis, Ioannis

2018-05-10

People often speculate about why others make the choices they do. This paper investigates how such inferences are formed as a function of what is chosen. Specifically, when observers encounter someone else's choice (e.g., of political candidate), they use the chosen option's attribute values (e.g., a candidate's specific stance on a policy issue) to infer the importance of that attribute (e.g., the policy issue) to the decision-maker. Consequently, when a chosen option has an attribute whose value is extreme (e.g., an extreme policy stance), observers infer-sometimes incorrectly-that this attribute disproportionately motivated the decision-maker's choice. Seven studies demonstrate how observers use an attribute's value to infer its weight-the value-weight heuristic-and identify the role of perceived diagnosticity: more extreme attribute values give observers the subjective sense that they know more about a decision-maker's preferences, and in turn, increase the attribute's perceived importance. The paper explores how this heuristic can produce erroneous inferences and influence broader beliefs about decision-makers. Copyright © 2018 Elsevier B.V. All rights reserved.

The Role of Mental Models in Dynamic Decision-Making

DTIC Science & Technology

2009-03-01

Humansystems® Incorporated 111 Farquhar St., Guelph, ON N1H 3N4 Project Manager : Lisa A. Rehak PWGSC Contract No.: W7711-078110/001/TOR Call...simulate the processes that people use to manage complex systems. These analogies, moreover, represent one way to help people to form more accurate...make complex decisions. Control theory’s primary emphasis is on the role of feedback while managing a complex system. What is common to all of these

Effects of Information Visualization on Older Adults’ Decision-Making Performance in a Medicare Plan Selection Task: A Comparative Usability Study

PubMed Central

Price, Margaux M; Crumley-Branyon, Jessica J; Leidheiser, William R

2016-01-01

Background Technology gains have improved tools for evaluating complex tasks by providing environmental supports (ES) that increase ease of use and improve performance outcomes through the use of information visualizations (info-vis). Complex info-vis emphasize the need to understand individual differences in abilities of target users, the key cognitive abilities needed to execute a decision task, and the graphical elements that can serve as the most effective ES. Older adults may be one such target user group that would benefit from increased ES to mitigate specific declines in cognitive abilities. For example, choosing a prescription drug plan is a necessary and complex task that can impact quality of life if the wrong choice is made. The decision to enroll in one plan over another can involve comparing over 15 plans across many categories. Within this context, the large amount of complex information and reduced working memory capacity puts older adults’ decision making at a disadvantage. An intentionally designed ES, such as an info-vis that reduces working memory demand, may assist older adults in making the most effective decision among many options. Objective The objective of this study is to examine whether the use of an info-vis can lower working memory demands and positively affect complex decision-making performance of older adults in the context of choosing a Medicare prescription drug plan. Methods Participants performed a computerized decision-making task in the context of finding the best health care plan. Data included quantitative decision-making performance indicators and surveys examining previous history with purchasing insurance. Participants used a colored info-vis ES or a table (no ES) to perform the decision task. Task difficulty was manipulated by increasing the number of selection criteria used to make an accurate decision. A repeated measures analysis was performed to examine differences between the two table designs. Results Twenty-three older adults between the ages of 66 and 80 completed the study. There was a main effect for accuracy such that older adults made more accurate decisions in the color info-vis condition than the table condition. In the low difficulty condition, participants were more successful at choosing the correct answer when the question was about the gap coverage attribute in the info-vis condition. Participants also made significantly faster decisions in the info-vis condition than in the table condition. Conclusions Reducing the working memory demand of the task through the use of an ES can improve decision accuracy, especially when selection criteria is only focused on a single attribute of the insurance plan. PMID:27251110

Low Molecular Weight Chitosan–Insulin Polyelectrolyte Complex: Characterization and Stability Studies

PubMed Central

Al-Kurdi, Zakieh I.; Chowdhry, Babur Z.; Leharne, Stephen A.; Al Omari, Mahmoud M. H.; Badwan, Adnan A.

2015-01-01

The aim of the work reported herein was to investigate the effect of various low molecular weight chitosans (LMWCs) on the stability of insulin using USP HPLC methods. Insulin was found to be stable in a polyelectrolyte complex (PEC) consisting of insulin and LMWC in the presence of a Tris-buffer at pH 6.5. In the presence of LMWC, the stability of insulin increased with decreasing molecular weight of LMWC; 13 kDa LMWC was the most efficient molecular weight for enhancing the physical and chemical stability of insulin. Solubilization of insulin-LMWC polyelectrolyte complex (I-LMWC PEC) in a reverse micelle (RM) system, administered to diabetic rats, results in an oral delivery system for insulin with acceptable bioactivity. PMID:25830681

Decision Making in Action

NASA Technical Reports Server (NTRS)

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

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.

Decision Making in Action: Applying Research to Practice

NASA Technical Reports Server (NTRS)

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

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relations between leadership, communication, decision making and overall crew performance. Implications of these findings for spaceflight and training for offshore installations will be discussed.

A method of evaluating crown fuels in forest stands.

Treesearch

Rodney W. Sando; Charles H. Wick

1972-01-01

A method of describing the crown fuels in a forest fuel complex based on crown weight and crown volume was developed. A computer program is an integral part of the method. Crown weight data are presented in graphical form and are separated into hardwood and coniferous fuels. The fuel complex is described using total crown weight per acre, mean height to the base of...

Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

NASA Astrophysics Data System (ADS)

Zaiwani, B. E.; Zarlis, M.; Efendi, S.

2018-03-01

In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

Using Decision Support System to Find Suitable Sites for Groundwater Artificial Recharge

NASA Astrophysics Data System (ADS)

Ghasemian, D.; Winter, C. L.; Kheirkhah Zarkesh, M. M.; Moradi, H. R.

2014-12-01

Some parts of Iran are considered as one of the driest regions of the world, where water is a limiting factor for lasting life therefore using seasonal floodwaters is very important in these arid regions. On the other hand, special attention has been paid to artificial groundwater recharge in these regions. Floodwater spreading on the permeable terrain is one of the flood control and utilization methods. Determination of appropriate site for water spreading is one of the most important stages of this project. Parameters considered in the selection of groundwater artificial recharge locations are diverse and complex. These factors consist of earth sciences (geology, geomorphology and soils), hydrology (runoff, sediment yield, infiltration and groundwater conditions) and socio-economic aspects (irrigated agriculture, flood damage mitigation, environment, job creation and so on). Hence, decision making depends on criteria of diverse nature. The goal of this study is defining a Decision Support System for floodwater site selection in Shahriary area. Four main criteria were selected in this research which are floodwater characters, infiltration, water applications and flood damage. In order to determine the weight of factors, Analytical Hierarchy Process was used. The results showed that soil texture and floodwater volume of infiltration are the most important factors. After providing output maps which had been defined in five scenarios, Kappa Index was used to evaluate the model. Based on the obtained results, the maps showed an acceptable agreement with control zones.

Tsunami vertical-evacuation planning in the U.S. Pacific Northwest as a geospatial, multi-criteria decision problem

USGS Publications Warehouse

Wood, Nathan; Jones, Jeanne; Schelling, John; Schmidtlein, Mathew

2014-01-01

Tsunami vertical-evacuation (TVE) refuges can be effective risk-reduction options for coastal communities with local tsunami threats but no accessible high ground for evacuations. Deciding where to locate TVE refuges is a complex risk-management question, given the potential for conflicting stakeholder priorities and multiple, suitable sites. We use the coastal community of Ocean Shores (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, multi-criteria decision analysis for framing the locational problem of TVE siting. We demonstrate a mixed-methods approach that uses potential TVE sites identified at community workshops, geospatial analysis to model changes in pedestrian evacuation times for TVE options, and statistical analysis to develop metrics for comparing population tradeoffs and to examine influences in decision making. Results demonstrate that no one TVE site can save all at-risk individuals in the community and each site provides varying benefits to residents, employees, customers at local stores, tourists at public venues, children at schools, and other vulnerable populations. The benefit of some proposed sites varies depending on whether or not nearby bridges will be functioning after the preceding earthquake. Relative rankings of the TVE sites are fairly stable under various criteria-weighting scenarios but do vary considerably when comparing strategies to exclusively protect tourists or residents. The proposed geospatial framework can serve as an analytical foundation for future TVE siting discussions.

Return of the JITAI: Applying a Just-in-Time Adaptive Intervention Framework to the Development of m-Health Solutions for Addictive Behaviors

PubMed Central

Evans, Brittney C.; Flack, Daniel; Juarascio, Adrienne; Manasse, Stephanie; Zhang, Fengqing; Forman, Evan M.

2018-01-01

Purpose Lapses are strong indicators of later relapse among individuals with addictive disorders, and thus are an important intervention target. However, lapse behavior has proven resistant to change due to the complex interplay of lapse triggers that are present in everyday life. It could be possible to prevent lapses before they occur by using m-Health solutions to deliver interventions in real-time. Method Just-in-time adaptive intervention (JITAI) is an intervention design framework that could be delivered via mobile app to facilitate in-the-moment monitoring of triggers for lapsing, and deliver personalized coping strategies to the user to prevent lapses from occurring. An organized framework is key for successful development of a JITAI. Results Nahum-Shani and colleagues (2014) set forth six core elements of a JITAI and guidelines for designing each: distal outcomes, proximal outcomes, tailoring variables, decision points, decision rules, and intervention options. The primary aim of this paper is to illustrate the use of this framework as it pertains to developing a JITAI that targets lapse behavior among individuals following a weight control diet. Conclusion We will detail our approach to various decision points during the development phases, report on preliminary findings where applicable, identify problems that arose during development, and provide recommendations for researchers who are currently undertaking their own JITAI development efforts. Issues such as missing data, the rarity of lapses, advantages/disadvantages of machine learning, and user engagement are discussed. PMID:28083725

Return of the JITAI: Applying a Just-in-Time Adaptive Intervention Framework to the Development of m-Health Solutions for Addictive Behaviors.

PubMed

Goldstein, Stephanie P; Evans, Brittney C; Flack, Daniel; Juarascio, Adrienne; Manasse, Stephanie; Zhang, Fengqing; Forman, Evan M

2017-10-01

Lapses are strong indicators of later relapse among individuals with addictive disorders, and thus are an important intervention target. However, lapse behavior has proven resistant to change due to the complex interplay of lapse triggers that are present in everyday life. It could be possible to prevent lapses before they occur by using m-Health solutions to deliver interventions in real-time. Just-in-time adaptive intervention (JITAI) is an intervention design framework that could be delivered via mobile app to facilitate in-the-moment monitoring of triggers for lapsing, and deliver personalized coping strategies to the user to prevent lapses from occurring. An organized framework is key for successful development of a JITAI. Nahum-Shani and colleagues (2014) set forth six core elements of a JITAI and guidelines for designing each: distal outcomes, proximal outcomes, tailoring variables, decision points, decision rules, and intervention options. The primary aim of this paper is to illustrate the use of this framework as it pertains to developing a JITAI that targets lapse behavior among individuals following a weight control diet. We will detail our approach to various decision points during the development phases, report on preliminary findings where applicable, identify problems that arose during development, and provide recommendations for researchers who are currently undertaking their own JITAI development efforts. Issues such as missing data, the rarity of lapses, advantages/disadvantages of machine learning, and user engagement are discussed.

Complexity, Public Reporting, and Choice of Doctors: A Look Inside the Blackest Box of Consumer Behavior

PubMed Central

Schlesinger, Mark; Kanouse, David E.; Martino, Steven C.; Shaller, Dale; Rybowski, Lise

2017-01-01

Health care consumers often make choices that are imperfectly informed and inconsistent with their expressed preferences. Past research suggests that these shortcomings become more pronounced as choices become more complex, through either additional options or more performance metrics. But it is unclear why this is true: Consumer choice remains a “black box” that research has scarcely illuminated. In this article, we identify four pathways through which complexity may impair consumer choice. We examine these pathways using data from an experiment in which consumers (hypothetically) selected a primary care physician. Some of the loss of decision quality accompanying more complex choice sets can be explained by consumers’ skills and decision-making style, but even after accounting for these factors, complexity undermines the quality of decision making in ways that cannot be fully explained. We conclude by discussing implications for report designers, sponsors, and policy makers aspiring to promote consumer empowerment and health care quality. PMID:23999489

Complexity, public reporting, and choice of doctors: a look inside the blackest box of consumer behavior.

PubMed

Schlesinger, Mark; Kanouse, David E; Martino, Steven C; Shaller, Dale; Rybowski, Lise

2014-10-01

Health care consumers often make choices that are imperfectly informed and inconsistent with their expressed preferences. Past research suggests that these shortcomings become more pronounced as choices become more complex, through either additional options or more performance metrics. But it is unclear why this is true: Consumer choice remains a "black box" that research has scarcely illuminated. In this article, we identify four pathways through which complexity may impair consumer choice. We examine these pathways using data from an experiment in which consumers (hypothetically) selected a primary care physician. Some of the loss of decision quality accompanying more complex choice sets can be explained by consumers' skills and decision-making style, but even after accounting for these factors, complexity undermines the quality of decision making in ways that cannot be fully explained. We conclude by discussing implications for report designers, sponsors, and policy makers aspiring to promote consumer empowerment and health care quality. © The Author(s) 2013.

Neuronal variability in orbitofrontal cortex during economic decisions.

PubMed

Conen, Katherine E; Padoa-Schioppa, Camillo

2015-09-01

Neuroeconomic models assume that economic decisions are based on the activity of offer value cells in the orbitofrontal cortex (OFC), but testing this assertion has proven difficult. In principle, the decision made on a given trial should correlate with the stochastic fluctuations of these cells. However, this correlation, measured as a choice probability (CP), is small. Importantly, a neuron's CP reflects not only its individual contribution to the decision (termed readout weight), but also the intensity and the structure of correlated variability across the neuronal population (termed noise correlation). A precise mathematical relation between CPs, noise correlations, and readout weights was recently derived by Haefner and colleagues (Haefner RM, Gerwinn S, Macke JH, Bethge M. Nat Neurosci 16: 235-242, 2013) for a linear decision model. In this framework, concurrent measurements of noise correlations and CPs can provide quantitative information on how a population of cells contributes to a decision. Here we examined neuronal variability in the OFC of rhesus monkeys during economic decisions. Noise correlations had similar structure but considerably lower strength compared with those typically measured in sensory areas during perceptual decisions. In contrast, variability in the activity of individual cells was high and comparable to that recorded in other cortical regions. Simulation analyses based on Haefner's equation showed that noise correlations measured in the OFC combined with a plausible readout of offer value cells reproduced the experimental measures of CPs. In other words, the results obtained for noise correlations and those obtained for CPs taken together support the hypothesis that economic decisions are primarily based on the activity of offer value cells. Copyright © 2015 the American Physiological Society.

Expert Financial Advice Neurobiologically “Offloads” Financial Decision-Making under Risk

PubMed Central

Engelmann, Jan B.; Capra, C. Monica; Noussair, Charles; Berns, Gregory S.

2009-01-01

Background Financial advice from experts is commonly sought during times of uncertainty. While the field of neuroeconomics has made considerable progress in understanding the neurobiological basis of risky decision-making, the neural mechanisms through which external information, such as advice, is integrated during decision-making are poorly understood. In the current experiment, we investigated the neurobiological basis of the influence of expert advice on financial decisions under risk. Methodology/Principal Findings While undergoing fMRI scanning, participants made a series of financial choices between a certain payment and a lottery. Choices were made in two conditions: 1) advice from a financial expert about which choice to make was displayed (MES condition); and 2) no advice was displayed (NOM condition). Behavioral results showed a significant effect of expert advice. Specifically, probability weighting functions changed in the direction of the expert's advice. This was paralleled by neural activation patterns. Brain activations showing significant correlations with valuation (parametric modulation by value of lottery/sure win) were obtained in the absence of the expert's advice (NOM) in intraparietal sulcus, posterior cingulate cortex, cuneus, precuneus, inferior frontal gyrus and middle temporal gyrus. Notably, no significant correlations with value were obtained in the presence of advice (MES). These findings were corroborated by region of interest analyses. Neural equivalents of probability weighting functions showed significant flattening in the MES compared to the NOM condition in regions associated with probability weighting, including anterior cingulate cortex, dorsolateral PFC, thalamus, medial occipital gyrus and anterior insula. Finally, during the MES condition, significant activations in temporoparietal junction and medial PFC were obtained. Conclusions/Significance These results support the hypothesis that one effect of expert advice is to “offload” the calculation of value of decision options from the individual's brain. PMID:19308261

Measuring the Benefits of Healthcare: DALYs and QALYs – Does the Choice of Measure Matter? A Case Study of Two Preventive Interventions

PubMed Central

Augustovski, Federico; Colantonio, Lisandro D.; Galante, Julieta; Bardach, Ariel; Caporale, Joaquín E.; Zárate, Víctor; Chuang, Ling Hsiang; Riviere, Andres Pichon; Kind, Paul

2018-01-01

Background: The measurement of health benefits is a key issue in health economic evaluations. There is very scarce empirical literature exploring the differences of using quality-adjusted life years (QALYs) or disability-adjusted life years (DALYs) as benefit metrics and their potential impact in decision-making. Methods: Two previously published models delivering outputs in QALYs, were adapted to estimate DALYs: a Markov model for human papilloma virus (HPV) vaccination, and a pneumococcal vaccination deterministic model (PNEUMO). Argentina, Chile, and the United Kingdom studies were used, where local EQ-5D social value weights were available to provide local QALY weights. A primary study with descriptive vignettes was done (n = 73) to obtain EQ-5D data for all health states included in both models. Several scenario analyses were carried-out to evaluate the relative importance of using different metrics (DALYS or QALYs) to estimate health benefits on these economic evaluations. Results: QALY gains were larger than DALYs avoided in all countries for HPV, leading to more favorable decisions using the former. With discounting and age-weighting – scenario with greatest differences in all countries – incremental DALYs avoided represented the 75%, 68%, and 43% of the QALYs gained in Argentina, Chile, and United Kingdom respectively. Differences using QALYs or DALYs were less consistent and sometimes in the opposite direction for PNEUMO. These differences, similar to other widely used assumptions, could directly influence decision-making using usual gross domestic products (GDPs) per capita per DALY or QALY thresholds. Conclusion: We did not find evidence that contradicts current practice of many researchers and decision-makers of using QALYs or DALYs interchangeably. Differences attributed to the choice of metric could influence final decisions, but similarly to other frequently used assumptions. PMID:29524936

Neuroscience, moral reasoning, and the law.

PubMed

Knabb, Joshua J; Welsh, Robert K; Ziebell, Joseph G; Reimer, Kevin S

2009-01-01

Modern advancements in functional magnetic resonance imaging (fMRI) technology have given neuroscientists the opportunity to more fully appreciate the brain's contribution to human behavior and decision making. Morality and moral reasoning are relative newcomers to the growing literature on decision neuroscience. With recent attention given to the salience of moral factors (e.g. moral emotions, moral reasoning) in the process of decision making, neuroscientists have begun to offer helpful frameworks for understanding the interplay between the brain, morality, and human decision making. These frameworks are relatively unfamiliar to the community of forensic psychologists, despite the fact that they offer an improved understanding of judicial decision making from a biological perspective. This article presents a framework reviewing how event-feature-emotion complexes (EFEC) are relevant to jurors and understanding complex criminal behavior. Future directions regarding converging fields of neuroscience and legal decision making are considered. Copyright 2009 John Wiley & Sons, Ltd.

Decision analysis with cumulative prospect theory.

PubMed

Bayoumi, A M; Redelmeier, D A

2000-01-01

Individuals sometimes express preferences that do not follow expected utility theory. Cumulative prospect theory adjusts for some phenomena by using decision weights rather than probabilities when analyzing a decision tree. The authors examined how probability transformations from cumulative prospect theory might alter a decision analysis of a prophylactic therapy in AIDS, eliciting utilities from patients with HIV infection (n = 75) and calculating expected outcomes using an established Markov model. They next focused on transformations of three sets of probabilities: 1) the probabilities used in calculating standard-gamble utility scores; 2) the probabilities of being in discrete Markov states; 3) the probabilities of transitioning between Markov states. The same prophylaxis strategy yielded the highest quality-adjusted survival under all transformations. For the average patient, prophylaxis appeared relatively less advantageous when standard-gamble utilities were transformed. Prophylaxis appeared relatively more advantageous when state probabilities were transformed and relatively less advantageous when transition probabilities were transformed. Transforming standard-gamble and transition probabilities simultaneously decreased the gain from prophylaxis by almost half. Sensitivity analysis indicated that even near-linear probability weighting transformations could substantially alter quality-adjusted survival estimates. The magnitude of benefit estimated in a decision-analytic model can change significantly after using cumulative prospect theory. Incorporating cumulative prospect theory into decision analysis can provide a form of sensitivity analysis and may help describe when people deviate from expected utility theory.

Overlapping community detection in weighted networks via a Bayesian approach

NASA Astrophysics Data System (ADS)

Chen, Yi; Wang, Xiaolong; Xiang, Xin; Tang, Buzhou; Chen, Qingcai; Fan, Shixi; Bu, Junzhao

2017-02-01

Complex networks as a powerful way to represent complex systems have been widely studied during the past several years. One of the most important tasks of complex network analysis is to detect communities embedded in networks. In the real world, weighted networks are very common and may contain overlapping communities where a node is allowed to belong to multiple communities. In this paper, we propose a novel Bayesian approach, called the Bayesian mixture network (BMN) model, to detect overlapping communities in weighted networks. The advantages of our method are (i) providing soft-partition solutions in weighted networks; (ii) providing soft memberships, which quantify 'how strongly' a node belongs to a community. Experiments on a large number of real and synthetic networks show that our model has the ability in detecting overlapping communities in weighted networks and is competitive with other state-of-the-art models at shedding light on community partition.

Determination of criteria weights in solving multi-criteria problems

NASA Astrophysics Data System (ADS)

Kasim, Maznah Mat

2014-12-01

A multi-criteria (MC) problem comprises of units to be analyzed under a set of evaluation criteria. Solving a MC problem is basically the process of finding the overall performance or overall quality of the units of analysis by using certain aggregation method. Based on these overall measures of each unit, a decision can be made whether to sort them, to select the best or to group them according to certain ranges. Prior to solving the MC problems, the weights of the related criteria have to be determined with the assumption that the weights represent the degree of importance or the degree of contribution towards the overall performance of the units. This paper presents two main approaches which are called as subjective and objective approaches, where the first one involves evaluator(s) while the latter approach depends on the intrinsic information contained in each criterion. The subjective and objective weights are defined if the criteria are assumed to be independent with each other, but if they are dependent, there is another type of weight, which is called as monotone measure weight or compound weights which represent degree of interaction among the criteria. The measure of individual weights or compound weights must be addressed in solving multi-criteria problems so that the solutions are more reliable since in the real world, evaluation criteria always come with different degree of importance or are dependent with each other. As the real MC problems have their own uniqueness, it is up to the decision maker(s) to decide which type of weights and which method are the most applicable ones for the problem under study.

A Novel Algorithm for Detecting Protein Complexes with the Breadth First Search

PubMed Central

Tang, Xiwei; Wang, Jianxin; Li, Min; He, Yiming; Pan, Yi

2014-01-01

Most biological processes are carried out by protein complexes. A substantial number of false positives of the protein-protein interaction (PPI) data can compromise the utility of the datasets for complexes reconstruction. In order to reduce the impact of such discrepancies, a number of data integration and affinity scoring schemes have been devised. The methods encode the reliabilities (confidence) of physical interactions between pairs of proteins. The challenge now is to identify novel and meaningful protein complexes from the weighted PPI network. To address this problem, a novel protein complex mining algorithm ClusterBFS (Cluster with Breadth-First Search) is proposed. Based on the weighted density, ClusterBFS detects protein complexes of the weighted network by the breadth first search algorithm, which originates from a given seed protein used as starting-point. The experimental results show that ClusterBFS performs significantly better than the other computational approaches in terms of the identification of protein complexes. PMID:24818139

The Myth of the Rational Decision Maker: A Framework for Applying and Enhancing Heuristic and Intuitive Decision Making by School Leaders

ERIC Educational Resources Information Center

Davis, Stephen H.

2004-01-01

This article takes a critical look at administrative decision making in schools and the extent to which complex decisions conform to normative models and common expectations of rationality. An alternative framework for administrative decision making is presented that is informed, but not driven, by theories of rationality. The framework assumes…

Avoiding bias in medical ethical decision-making. Lessons to be learnt from psychology research.

PubMed

Albisser Schleger, Heidi; Oehninger, Nicole R; Reiter-Theil, Stella

2011-05-01

When ethical decisions have to be taken in critical, complex medical situations, they often involve decisions that set the course for or against life-sustaining treatments. Therefore the decisions have far-reaching consequences for the patients, their relatives, and often for the clinical staff. Although the rich psychology literature provides evidence that reasoning may be affected by undesired influences that may undermine the quality of the decision outcome, not much attention has been given to this phenomenon in health care or ethics consultation. In this paper, we aim to contribute to the sensitization of the problem of systematic reasoning biases by showing how exemplary individual and group biases can affect the quality of decision-making on an individual and group level. We are addressing clinical ethicists as well as clinicians who guide complex decision-making processes of ethical significance. Knowledge regarding exemplary group psychological biases (e.g. conformity bias), and individual biases (e.g. stereotypes), will be taken from the disciplines of social psychology and cognitive decision science and considered in the field of ethical decision-making. Finally we discuss the influence of intuitive versus analytical (systematical) reasoning on the validity of ethical decision-making.

Comparison of two multi-criteria decision techniques for eliciting treatment preferences in people with neurological disorders.

PubMed

Ijzerman, Maarten J; van Til, Janine A; Snoek, Govert J

2008-12-01

To present and compare two multi-criteria decision techniques (analytic hierarchy process [AHP] and conjoint analysis [CA]) for eliciting preferences in patients with cervical spinal cord injury (SCI) who are eligible for surgical augmentation of hand function, either with or without implantation of a neuroprosthesis. The methods were compared in respect to attribute weights, overall preference, and practical experiences. Two previously designed and administered multi-criteria decision surveys in patients with SCI were compared and further analysed. Attributes and their weights in the AHP experiment were determined by an expert panel, followed by determination of the weights in the patient group. Attributes for the CA were selected and validated using an expert panel, piloted in six patients with SCI and subsequently administered to the same group of patients as participated in the AHP experiment. Both experiments showed the importance of non-outcome-related factors such as inpatient stay and number of surgical procedures. In particular, patients were less concerned with clinical outcomes in actual decision making. Overall preference in both the AHP and CA was in favor of tendon reconstruction (0.6 vs 0.4 for neuroprosthetic implantation). Both methods were easy to apply, but AHP was less easily explained and understood. Both the AHP and CA methods produced similar outcomes, which may have been caused by the obvious preferences of patients. CA may be preferred because of the holistic approach of considering all treatment attributes simultaneously and, hence, its power in simulating real market decisions. On the other hand, the AHP method is preferred as a hands-on, easy-to-implement task with immediate feedback to the respondent. This flexibility allows AHP to be used in shared decision making. However, the way the technique is composed results in many inconsistencies. Patients preferred CA but complained about the number of choice tasks.

Three-dimensional-printed cardiac prototypes aid surgical decision-making and preoperative planning in selected cases of complex congenital heart diseases: Early experience and proof of concept in a resource-limited environment.

PubMed

Kappanayil, Mahesh; Koneti, Nageshwara Rao; Kannan, Rajesh R; Kottayil, Brijesh P; Kumar, Krishna

2017-01-01

Three-dimensional. (3D) printing is an innovative manufacturing process that allows computer-assisted conversion of 3D imaging data into physical "printouts" Healthcare applications are currently in evolution. The objective of this study was to explore the feasibility and impact of using patient-specific 3D-printed cardiac prototypes derived from high-resolution medical imaging data (cardiac magnetic resonance imaging/computed tomography [MRI/CT]) on surgical decision-making and preoperative planning in selected cases of complex congenital heart diseases (CHDs). Five patients with complex CHD with previously unresolved management decisions were chosen. These included two patients with complex double-outlet right ventricle, two patients with criss-cross atrioventricular connections, and one patient with congenitally corrected transposition of great arteries with pulmonary atresia. Cardiac MRI was done for all patients, cardiac CT for one; specific surgical challenges were identified. Volumetric data were used to generate patient-specific 3D models. All cases were reviewed along with their 3D models, and the impact on surgical decision-making and preoperative planning was assessed. Accurate life-sized 3D cardiac prototypes were successfully created for all patients. The models enabled radically improved 3D understanding of anatomy, identification of specific technical challenges, and precise surgical planning. Augmentation of existing clinical and imaging data by 3D prototypes allowed successful execution of complex surgeries for all five patients, in accordance with the preoperative planning. 3D-printed cardiac prototypes can radically assist decision-making, planning, and safe execution of complex congenital heart surgery by improving understanding of 3D anatomy and allowing anticipation of technical challenges.

Weaving and neural complexity in symmetric quantum states

NASA Astrophysics Data System (ADS)

Susa, Cristian E.; Girolami, Davide

2018-04-01

We study the behaviour of two different measures of the complexity of multipartite correlation patterns, weaving and neural complexity, for symmetric quantum states. Weaving is the weighted sum of genuine multipartite correlations of any order, where the weights are proportional to the correlation order. The neural complexity, originally introduced to characterize correlation patterns in classical neural networks, is here extended to the quantum scenario. We derive closed formulas of the two quantities for GHZ states mixed with white noise.

Opinion: The use of natural hazard modeling for decision making under uncertainty

Treesearch

David E. Calkin; Mike Mentis

2015-01-01

Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, there is a growing body of work focused on developing best practices for natural hazard modeling and to create structured evaluation criteria for complex...

The Role of Gist and Verbatim Memory in Complex Decision Making: Explaining the Unconscious-Thought Effect

ERIC Educational Resources Information Center

Abadie, Marlène; Waroquier, Laurent; Terrier, Patrice

2017-01-01

Previous research showed that the "unconscious-thought effect", which refers to an improvement in complex decision making following a distraction period, was moderated by the presentation format of pieces of information about different options. The aim of the current study was to replicate this finding and further examine the memory…

Verifying Holstein heifer heart girth to body weight prediction equations

USDA-ARS?s Scientific Manuscript database

The estimation of Holstein heifer body weight (BW) from heart girth (HG) measurements is needed as many farms do not have animal scales to make the management decisions that require BW. The correlation between HG and BW is known to vary with differing animal conformation. The previous equation to co...

Allocating scarce medical resources to the overweight.

PubMed

Furnham, Adrian; Loganathan, Niroosha; McClelland, Alastair

2010-01-01

A programmatic research effort investigated how lay people weigh information on hypothetical patients when making decisions regarding the allocation of scarce medical resources. This study is partly replicative and partly innovative, and looks particularly at whether overweight patients would be discriminated against in allocating resources. This study aims to determine the importance given to specific patient characteristics when lay participants are asked to allocate scarce medical resources. In all, 156 British adults (82 males, 73 females), aged 19 to 84 years, took part. There were few students. Participants completed a questionnaire requiring them to rank 16 hypothetical patients for access to a kidney dialysis machine.The demographic information presented regarding each hypothetical patient differed on four dimensions: gender, weight, mental health, and religiousness. There were significant main effects for gender, weight, and mental health; females, patients of normal weight, and the mentally well were ranked the highest priority for access to a kidney dialysis machine. Participants discriminated most regarding the weight of hypothetical patients. Different patient characteristics, unrelated to medical prognoses, particularly being overweight, may have an impact on decisions regarding the use of scarce medical resources.

Topological analysis of long-chain branching patterns in polyolefins.

PubMed

Bonchev, D; Markel, E; Dekmezian, A

2001-01-01

Patterns in molecular topology and complexity for long-chain branching are quantitatively described. The Wiener number, the topological complexity index, and a new index of 3-starness are used to quantify polymer structure. General formulas for these indices were derived for the cases of 3-arm star, H-shaped, and B-arm comb polymers. The factors affecting complexity in monodisperse polymer systems are ranked as follows: number of arms > arm length > arm central position approximately equal to arm clustering > total molecular weight approximately equal to backbone molecular weight. Topological indices change rapidly and then plateau as the molecular weight of branches on a polyolefin backbone increases from 0 to 5 kD. Complexity calculations relate 2-arm or 3-arm comb structures to the corresponding 3-arm stars of equivalent complexity but much higher molecular weight. In a subsequent paper, we report the application of topological analysis for developing structure/property relationships for monodisperse polymers. While the focus of the present work is on the description of monodisperse, well-defined architectures, the methods may be extended to the description of polydisperse systems.

Decision-making process of Kala Azar care: results from a qualitative study carried out in disease endemic areas of Nepal

PubMed Central

2013-01-01

Background Analysis of consumer decision making in the health sector is a complex process of comparing feasible alternatives and evaluating the levels of satisfaction associated with the relevant options. This paper makes an attempt to understand how and why consumers make specific decisions, what motivates them to adopt a specific health intervention, and what features they find attractive in each of the options. Method The study used a descriptive-explanatory design to analyze the factors determining the choices of healthcare providers. Information was collected through focus group discussions and in-depth interviews. Results The results suggest that the decision making related to seeking healthcare for Kala Azar (KA) treatment is a complex, interactive process. Patients and family members follow a well-defined road map for decision making. The process of decision making starts from the recognition of healthcare needs and is then modified by a number of other factors, such as indigenous knowledge, healthcare alternatives, and available resources. Household and individual characteristics also play important roles in facilitating the process of decision making. The results from the group discussions and in-depth interviews are consistent with the idea that KA patients and family members follow the rational approach of weighing the costs against the benefits of using specific types of medical care. Conclusion The process of decision making related to seeking healthcare follows a complex set of steps and many of the potential factors affect the decision making in a non-linear fashion. Our analysis suggests that it is possible to derive a generalized road map of the decision-making process starting from the recognition of healthcare needs, and then modifying it to show the influences of indigenous knowledge, healthcare alternatives, and available resources. PMID:23849617

Decision-making process of Kala Azar care: results from a qualitative study carried out in disease endemic areas of Nepal.

PubMed

Adhikari, Shiva Raj; Supakankunti, Siripen; Khan, M Mahmud

2013-07-12

Analysis of consumer decision making in the health sector is a complex process of comparing feasible alternatives and evaluating the levels of satisfaction associated with the relevant options. This paper makes an attempt to understand how and why consumers make specific decisions, what motivates them to adopt a specific health intervention, and what features they find attractive in each of the options. The study used a descriptive-explanatory design to analyze the factors determining the choices of healthcare providers. Information was collected through focus group discussions and in-depth interviews. The results suggest that the decision making related to seeking healthcare for Kala Azar (KA) treatment is a complex, interactive process. Patients and family members follow a well-defined road map for decision making. The process of decision making starts from the recognition of healthcare needs and is then modified by a number of other factors, such as indigenous knowledge, healthcare alternatives, and available resources. Household and individual characteristics also play important roles in facilitating the process of decision making. The results from the group discussions and in-depth interviews are consistent with the idea that KA patients and family members follow the rational approach of weighing the costs against the benefits of using specific types of medical care. The process of decision making related to seeking healthcare follows a complex set of steps and many of the potential factors affect the decision making in a non-linear fashion. Our analysis suggests that it is possible to derive a generalized road map of the decision-making process starting from the recognition of healthcare needs, and then modifying it to show the influences of indigenous knowledge, healthcare alternatives, and available resources.

Developmental weighting shifts for noise components of fricative-vowel syllables.

PubMed

Nittrouer, S; Miller, M E

1997-07-01

Previous studies have convincingly shown that the weight assigned to vocalic formant transitions in decisions of fricative identity for fricative-vowel syllables decreases with development. Although these same studies suggested a developmental increase in the weight assigned to the noise spectrum, the role of the aperiodic-noise portions of the signals in these fricative decisions have not been as well-studied. The purpose of these experiments was to examine more closely developmental shifts in the weight assigned to the aperiodic-noise components of the signals in decisions of syllable-initial fricative identity. Two experiments used noises varying along continua from a clear /s/ percept to a clear /[symbol: see text]/ percept. In experiment 1, these noises were created by combining /s/ and /[symbol: see text]/ noises produced by a human vocal tract at different amplitude ratios, a process that resulted in stimuli differing primarily in the amplitude of a relatively low-frequency (roughly 2.2-kHz) peak. In experiment 2, noises that varied only in the amplitude of a similar low-frequency peak were created with a software synthesizer. Both experiments used synthetic /a/ and /u/ portions, and efforts were made to minimize possible contributions of vocalic formant transitions to fricative labeling. Children and adults labeled the resulting stimuli as /s/ vowel or /[symbol: see text]/ vowel. Combined results of the two experiments showed that children's responses were less influenced than those of adults by the amplitude of the low-frequency peak of fricative noises.

Chitosan-Copper (II) complex as antibacterial agent: synthesis, characterization and coordinating bond- activity correlation study

NASA Astrophysics Data System (ADS)

Mekahlia, S.; Bouzid, B.

2009-11-01

The antimicrobial activity of chitosan is unstable and sensitive to many factors such as molecular weight. Recent investigations showed that low molecular weight chitosan exhibited strong bactericidal activities compared to chitosan with high molecular weight. Since chitosan degradation can be caused by the coordinating bond, we attempt to synthesize and characterize the chitosan-Cu (II) complex, and thereafter study the coordinating bond effect on its antibacterial activity against Salmonella enteritidis. Seven chitosan-copper complexes with different copper contents were prepared and characterized by FT-IR, UV-vis, XRD and atomic absorption spectrophotometry (AAS). Results indicated that for chitosan-Cu (II) complexes with molar ratio close to 1:1, the inhibition rate reached 100%.

A Tentative Organizational Schema for Decision-Making Problems.

ERIC Educational Resources Information Center

Osborn, William C.; Goodman, Barbara Ettinger

This report presents the results of research that examined widely diverse decision problems and attempted to specify their common behavior elements. To take into account the psychological complexity of most real-life decision problems, and to develop a tentative organization of decision behavior that will embrace the many, highly diverse types of…

Fire behavior modeling-a decision tool

Treesearch

Jack Cohen; Bill Bradshaw

1986-01-01

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

Decisions Matter: Using a Decision-Making Framework with Contemporary Student Affairs Case Studies

ERIC Educational Resources Information Center

Vaccaro, Annemarie; McCoy, Brian; Champagne, Delight; Siegel, Michael

2013-01-01

"Decisions Matter" is an innovative guide designed to help novice student affairs professionals develop effective decision-making skills. Written by seasoned student affairs educators and practitioners, this book contains a systematic method for solving a wide range of complex problems. In this exceptional instructional tool, the authors…

Making ResourceFULL™ Decisions: A Process Model for Civic Engagement

ERIC Educational Resources Information Center

Radke, Barbara; Chazdon, Scott

2015-01-01

Many public issues are becoming more complex, interconnected, and cannot be resolved by one individual or entity. Research shows an informed decision is not enough. Addressing these issues requires authentic civic engagement (deliberative dialogue) with the public to reach resourceFULL™ decisions--a decision based on diverse sources of information…

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…

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

Treesearch

Erin J. Belval; Yu Wei; Michael Bevers

2015-01-01

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

The value of decision models: Using ecologically based invasive plant management as an example

USDA-ARS?s Scientific Manuscript database

Humans have both fast and slow thought processes which influence our judgment and decision-making. The fast system is intuitive and valuable for decisions which do not require multiple steps or the application of logic or statistics. However, many decisions in natural resources are complex and req...

Chimpanzees and Bonobos Exhibit Emotional Responses to Decision Outcomes

PubMed Central

Rosati, Alexandra G.; Hare, Brian

2013-01-01

The interface between cognition, emotion, and motivation is thought to be of central importance in understanding complex cognitive functions such as decision-making and executive control in humans. Although nonhuman apes have complex repertoires of emotional expression, little is known about the role of affective processes in ape decision-making. To illuminate the evolutionary origins of human-like patterns of choice, we investigated decision-making in humans' closest phylogenetic relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). In two studies, we examined these species' temporal and risk preferences, and assessed whether apes show emotional and motivational responses in decision-making contexts. We find that (1) chimpanzees are more patient and more risk-prone than are bonobos, (2) both species exhibit affective and motivational responses following the outcomes of their decisions, and (3) some emotional and motivational responses map onto species-level and individual-differences in decision-making. These results indicate that apes do exhibit emotional responses to decision-making, like humans. We explore the hypothesis that affective and motivational biases may underlie the psychological mechanisms supporting value-based preferences in these species. PMID:23734175

Rigorous study of low-complexity adaptive space-time block-coded MIMO receivers in high-speed mode multiplexed fiber-optic transmission links using few-mode fibers

NASA Astrophysics Data System (ADS)

Weng, Yi; He, Xuan; Wang, Junyi; Pan, Zhongqi

2017-01-01

Spatial-division multiplexing (SDM) techniques have been purposed to increase the capacity of optical fiber transmission links by utilizing multicore fibers or few-mode fibers (FMF). The most challenging impairments of SDMbased long-haul optical links mainly include modal dispersion and mode-dependent loss (MDL), whereas MDL arises from inline component imperfections, and breaks modal orthogonality thus degrading the capacity of multiple-inputmultiple- output (MIMO) receivers. To reduce MDL, optical approaches include mode scramblers and specialty fiber designs, yet these methods were burdened with high cost, yet cannot completely remove the accumulated MDL in the link. Besides, space-time trellis codes (STTC) were purposed to lessen MDL, but suffered from high complexity. In this work, we investigated the performance of space-time block-coding (STBC) scheme to mitigate MDL in SDM-based optical communication by exploiting space and delay diversity, whereas weight matrices of frequency-domain equalization (FDE) were updated heuristically using decision-directed recursive-least-squares (RLS) algorithm for convergence and channel estimation. The STBC was evaluated in a six-mode multiplexed system over 30-km FMF via 6×6 MIMO FDE, with modal gain offset 3 dB, core refractive index 1.49, numerical aperture 0.5. Results show that optical-signal-to-noise ratio (OSNR) tolerance can be improved via STBC by approximately 3.1, 4.9, 7.8 dB for QPSK, 16- and 64-QAM with respective bit-error-rates (BER) and minimum-mean-square-error (MMSE). Besides, we also evaluate the complexity optimization of STBC decoding scheme with zero-forcing decision feedback (ZFDF) equalizer by shortening the coding slot length, which is robust to frequency-selective fading channels, and can be scaled up for SDM systems with more dynamic channels.

Multi-criteria decision-making for flood risk management: a survey of the current state of the art

NASA Astrophysics Data System (ADS)

Madruga de Brito, Mariana; Evers, Mariele

2016-04-01

This paper provides a review of multi-criteria decision-making (MCDM) applications to flood risk management, seeking to highlight trends and identify research gaps. A total of 128 peer-reviewed papers published from 1995 to June 2015 were systematically analysed. Results showed that the number of flood MCDM publications has exponentially grown during this period, with over 82 % of all papers published since 2009. A wide range of applications were identified, with most papers focusing on ranking alternatives for flood mitigation, followed by risk, hazard, and vulnerability assessment. The analytical hierarchy process (AHP) was the most popular method, followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Simple Additive Weighting (SAW). Although there is greater interest in MCDM, uncertainty analysis remains an issue and was seldom applied in flood-related studies. In addition, participation of multiple stakeholders has been generally fragmented, focusing on particular stages of the decision-making process, especially on the definition of criteria weights. Therefore, addressing the uncertainties around stakeholders' judgments and endorsing an active participation in all steps of the decision-making process should be explored in future applications. This could help to increase the quality of decisions and the implementation of chosen measures.

Modelling a suitable location for Urban Solid Waste Management using AHP method and GIS -A geospatial approach and MCDM Model

NASA Astrophysics Data System (ADS)

Iqbal, M.; Islam, A.; Hossain, A.; Mustaque, S.

2016-12-01

Multi-Criteria Decision Making(MCDM) is advanced analytical method to evaluate appropriate result or decision from multiple criterion environment. Present time in advanced research, MCDM technique is progressive analytical process to evaluate a logical decision from various conflict. In addition, Present day Geospatial approach (e.g. Remote sensing and GIS) also another advanced technical approach in a research to collect, process and analyze various spatial data at a time. GIS and Remote sensing together with the MCDM technique could be the best platform to solve a complex decision making process. These two latest process combined very effectively used in site selection for solid waste management in urban policy. The most popular MCDM technique is Weighted Linear Method (WLC) where Analytical Hierarchy Process (AHP) is another popular and consistent techniques used in worldwide as dependable decision making. Consequently, the main objective of this study is improving a AHP model as MCDM technique with Geographic Information System (GIS) to select a suitable landfill site for urban solid waste management. Here AHP technique used as a MCDM tool to select the best suitable landfill location for urban solid waste management. To protect the urban environment in a sustainable way municipal waste needs an appropriate landfill site considering environmental, geological, social and technical aspect of the region. A MCDM model generate from five class related which related to environmental, geological, social and technical using AHP method and input the result set in GIS for final model location for urban solid waste management. The final suitable location comes out that 12.2% of the area corresponds to 22.89 km2 considering the total study area. In this study, Keraniganj sub-district of Dhaka district in Bangladesh is consider as study area which is densely populated city currently undergoes an unmanaged waste management system especially the suitable landfill sites for waste dumping site.

Enhancing the ecological risk assessment process.

PubMed

Dale, Virginia H; Biddinger, Gregory R; Newman, Michael C; Oris, James T; Suter, Glenn W; Thompson, Timothy; Armitage, Thomas M; Meyer, Judith L; Allen-King, Richelle M; Burton, G Allen; Chapman, Peter M; Conquest, Loveday L; Fernandez, Ivan J; Landis, Wayne G; Master, Lawrence L; Mitsch, William J; Mueller, Thomas C; Rabeni, Charles F; Rodewald, Amanda D; Sanders, James G; van Heerden, Ivor L

2008-07-01

The Ecological Processes and Effects Committee of the US Environmental Protection Agency Science Advisory Board conducted a self-initiated study and convened a public workshop to characterize the state of the ecological risk assessment (ERA), with a view toward advancing the science and application of the process. That survey and analysis of ERA in decision making shows that such assessments have been most effective when clear management goals were included in the problem formulation; translated into information needs; and developed in collaboration with decision makers, assessors, scientists, and stakeholders. This process is best facilitated when risk managers, risk assessors, and stakeholders are engaged in an ongoing dialogue about problem formulation. Identification and acknowledgment of uncertainties that have the potential to profoundly affect the results and outcome of risk assessments also improves assessment effectiveness. Thus we suggest 1) through peer review of ERAs be conducted at the problem formulation stage and 2) the predictive power of risk-based decision making be expanded to reduce uncertainties through analytical and methodological approaches like life cycle analysis. Risk assessment and monitoring programs need better integration to reduce uncertainty and to evaluate risk management decision outcomes. Postdecision audit programs should be initiated to evaluate the environmental outcomes of risk-based decisions. In addition, a process should be developed to demonstrate how monitoring data can be used to reduce uncertainties. Ecological risk assessments should include the effects of chemical and nonchemical stressors at multiple levels of biological organization and spatial scale, and the extent and resolution of the pertinent scales and levels of organization should be explicitly considered during problem formulation. An approach to interpreting lines of evidence and weight of evidence is critically needed for complex assessments, and it would be useful to develop case studies and/or standards of practice for interpreting lines of evidence. In addition, tools for cumulative risk assessment should be developed because contaminants are often released into stressed environments.

Keeping Communication Continuous

NASA Technical Reports Server (NTRS)

2003-01-01

General Dynamics Decision Systems employees have played a role in supplying telemetry, tracking, and control (TT&C) and other communications systems to NASA and the U.S. Department of Defense for over 40 years. Providing integrated communication systems and subsystems for nearly all manned and unmanned U.S. space flights, the heritage of this Scottsdale, Arizona-based company includes S-band transceivers that enabled millions of Americans to see Neil Armstrong and hear his prophetic words from the Moon in 1969. More recently, Decision Systems has collaborated with NASA s Goddard Space Flight Center to develop transponders, wireless communications devices that pick up and automatically respond to an incoming signal, for NASA s Tracking and Data Relay Satellite System (TDRSS). Four generations of Decision Systems TDRSS transponders have been developed under Goddard s sponsorship. The company s Fourth Generation TDRSS User Transponder (TDRSS IV) allows low-Earth-orbiting spacecraft to communicate continuously with a single ground station at White Sands, New Mexico, through a constellation of geostationary relay satellites positioned at key locations around the Earth. In addition to the communications of forward link control commands and return link telemetry data, the TDRSS IV also supports spacecraft orbit tracking through coherent turn-around of a pseudo-noise ranging code and two-way Doppler tracking.When the NSBF adopted the use of global positioning system receivers for balloon position tracking, Decision Systems concluded that a simpler, noncoherent transceiver could provide the NSBF with the necessary TDRSS communications without the additional cost and complexity of a coherent transponder. The solution was to take the core design of the TDRSS IV Transponder, but remove the extra functionality that supported coherent turn-around. This would simplify the production effort, reduce the testing required, and result in a lower cost product with smaller size, weight, and power consumption. Once NSBF and Decision Systems agreed on a concept for this new product, known as the Multi-Mode Transceiver (MMT), the NSBF approached Goddard for approval and funding.

Participatory monitoring and evaluation approaches that influence decision-making: lessons from a maternal and newborn study in Eastern Uganda.

PubMed

Kananura, Rornald Muhumuza; Ekirapa-Kiracho, Elizabeth; Paina, Ligia; Bumba, Ahmed; Mulekwa, Godfrey; Nakiganda-Busiku, Dinah; Oo, Htet Nay Lin; Kiwanuka, Suzanne Namusoke; George, Asha; Peters, David H

2017-12-28

The use of participatory monitoring and evaluation (M&E) approaches is important for guiding local decision-making, promoting the implementation of effective interventions and addressing emerging issues in the course of implementation. In this article, we explore how participatory M&E approaches helped to identify key design and implementation issues and how they influenced stakeholders' decision-making in eastern Uganda. The data for this paper is drawn from a retrospective reflection of various M&E approaches used in a maternal and newborn health project that was implemented in three districts in eastern Uganda. The methods included qualitative and quantitative M&E techniques such as  key informant interviews, formal surveys and supportive supervision, as well as participatory approaches, notably participatory impact pathway analysis. At the design stage, the M&E approaches were useful for identifying key local problems and feasible local solutions and informing the activities that were subsequently implemented. During the implementation phase, the M&E approaches provided evidence that informed decision-making and helped identify emerging issues, such as weak implementation by some village health teams, health facility constraints such as poor use of standard guidelines, lack of placenta disposal pits, inadequate fuel for the ambulance at some facilities, and poor care for low birth weight infants. Sharing this information with key stakeholders prompted them to take appropriate actions. For example, the sub-county leadership constructed placenta disposal pits, the district health officer provided fuel for ambulances, and health workers received refresher training and mentorship on how to care for newborns. Diverse sources of information and perspectives can help researchers and decision-makers understand and adapt evidence to contexts for more effective interventions. Supporting districts to have crosscutting, routine information generating and sharing platforms that bring together stakeholders from different sectors is therefore crucial for the successful implementation of complex development interventions.

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

PubMed Central

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details. PMID:26158662

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

PubMed

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

Complexity science and participation in decision making among Taiwanese nurses.

PubMed

Liu, Yi

2008-04-01

The perspective of interconnection in complexity science is used to examine the concept of participation in decision making among Taiwanese nurses in the context of Chinese communication culture. Participation in decision making among nurses has been widely discussed and tested in the Western healthcare systems. Many studies have shown that participation in decision making relates to nurses' autonomy, job satisfaction and quality of care. However, participation in decision making has not been fully discussed in Taiwan's nursing community. In a different cultural environment, participation in decision making may have different effects. The concept of participation in decision making is analysed in three facets of Chinese communication culture: (1) hierarchical social relationship; (2) harmony maintenance; and (3) insider effects. Key issues Taiwanese nurses might establish different levels of participation and need to use different strategies to enhance participation in decision making for desired outcomes. While applying participation in decision making in a different context, it is very important to consider the social and cultural differences. Two implications are made. First, nursing leaders/managers who are working with a multicultural team should be aware of the cultural difference in the pattern of interaction in the process of participation in decision making. Second, leaders/managers should be creative and try to apply different strategies to encourage staff's participation in decision making.

A Response-Time Approach to Comparing Generalized Rational and Take-the-Best Models of Decision Making

ERIC Educational Resources Information Center

Bergert, F. Bryan; Nosofsky, Robert M.

2007-01-01

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT)…

Rationality in Human Movement.

PubMed

O'Brien, Megan K; Ahmed, Alaa A

2016-01-01

It long has been appreciated that humans behave irrationally in economic decisions under risk: they fail to objectively consider uncertainty, costs, and rewards and instead exhibit risk-seeking or risk-averse behavior. We hypothesize that poor estimates of motor variability (influenced by motor task) and distorted probability weighting (influenced by relevant emotional processes) contribute to characteristic irrationality in human movement decisions.

Lost in Search: (Mal-)Adaptation to Probabilistic Decision Environments in Children and Adults

ERIC Educational Resources Information Center

Betsch, Tilmann; Lehmann, Anne; Lindow, Stefanie; Lang, Anna; Schoemann, Martin

2016-01-01

Adaptive decision making in probabilistic environments requires individuals to use probabilities as weights in predecisional information searches and/or when making subsequent choices. Within a child-friendly computerized environment (Mousekids), we tracked 205 children's (105 children 5-6 years of age and 100 children 9-10 years of age) and 103…

Coding Theory Information Theory and Radar

DTIC Science & Technology

2005-01-01

the design and synthesis of artificial multiagent systems and for the understanding of human decision-making processes. This... altruism that may exist in a complex society. SGT derives its ability to account simultaneously for both group and individual interests from the structure of ...satisficing decision theory as a model of human decision mak- ing. 2 Multi-Attribute Decision Making Many decision problems involve the consideration of

Randomized controlled trial of changes in dietary carbohydrate/fat ratio and simple vs complex carbohydrates on body weight and blood lipids: the CARMEN study. The Carbohydrate Ratio Management in European National diets.

PubMed

Saris, W H; Astrup, A; Prentice, A M; Zunft, H J; Formiguera, X; Verboeket-van de Venne, W P; Raben, A; Poppitt, S D; Seppelt, B; Johnston, S; Vasilaras, T H; Keogh, G F

2000-10-01

To investigate the long-term effects of changes in dietary carbohydrate/fat ratio and simple vs complex carbohydrates. Randomized controlled multicentre trial (CARMEN), in which subjects were allocated for 6 months either to a seasonal control group (no intervention) or to one of three experimental groups: a control diet group (dietary intervention typical of the average national intake); a low-fat high simple carbohydrate group; or a low-fat high complex carbohydrate group. Three hundred and ninety eight moderately obese adults. The change in body weight was the primary outcome; changes in body composition and blood lipids were secondary outcomes. Body weight loss in the low-fat high simple carbohydrate and low-fat high complex carbohydrate groups was 0.9 kg (P < 0.05) and 1.8 kg (P < 0.001), while the control diet and seasonal control groups gained weight (0.8 and 0.1 kg, NS). Fat mass changed by -1.3kg (P< 0.01), -1.8kg (P< 0.001) and +0.6kg (NS) in the low-fat high simple carbohydrate, low-fat high complex carbohydrate and control diet groups, respectively. Changes in blood lipids did not differ significantly between the dietary treatment groups. Our findings suggest that reduction of fat intake results in a modest but significant reduction in body weight and body fatness. The concomitant increase in either simple or complex carbohydrates did not indicate significant differences in weight change. No adverse effects on blood lipids were observed. These findings underline the importance of this dietary change and its potential impact on the public health implications of obesity.

A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

PubMed

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.

The relationship between reward and punishment processing and the 5-HT1A receptor as shown by PET.

PubMed

Faulkner, Paul; Selvaraj, Sudhakar; Pine, Alex; Howes, Oliver D; Roiser, Jonathan P

2014-07-01

The serotonin (5-HT) system has been reported to be involved in decision-making. A key component of this neurotransmitter system is the 5-HT1A receptor, and research is beginning to show how this receptor can influence decision-making. However, this relationship has rarely been studied in humans. This study assessed whether individual variability in 5-HT1A availability correlates with decision-making in healthy volunteers. We measured regional availability of the 5-HT1A receptor in the hippocampal complex and striatum using positron emission tomography and correlated this with performance on two decision-making tasks measuring sensitivity to probability, rewards and punishments and temporal discounting, respectively. No relationship between decision-making behaviour and 5-HT1A availability in the striatum was found. However, a positive correlation was detected between participants' 5-HT1A availability in the hippocampal complex and their sensitivity to the probability of winning. Furthermore, there was a negative correlation between the degree to which participants discounted future rewards and 5-HT1A availability in the hippocampal complex. These data support a role for the 5-HT1A receptor in the aberrant decision-making that can occur in neuropsychiatric disorders such as depression.

Technology selection for ballast water treatment by multi-stakeholders: A multi-attribute decision analysis approach based on the combined weights and extension theory.

PubMed

Ren, Jingzheng

2018-01-01

This objective of this study is to develop a generic multi-attribute decision analysis framework for ranking the technologies for ballast water treatment and determine their grades. An evaluation criteria system consisting of eight criteria in four categories was used to evaluate the technologies for ballast water treatment. The Best-Worst method, which is a subjective weighting method and Criteria importance through inter-criteria correlation method, which is an objective weighting method, were combined to determine the weights of the evaluation criteria. The extension theory was employed to prioritize the technologies for ballast water treatment and determine their grades. An illustrative case including four technologies for ballast water treatment, i.e. Alfa Laval (T 1 ), Hyde (T 2 ), Unitor (T 3 ), and NaOH (T 4 ), were studied by the proposed method, and the Hyde (T 2 ) was recognized as the best technology. Sensitivity analysis was also carried to investigate the effects of the combined coefficients and the weights of the evaluation criteria on the final priority order of the four technologies for ballast water treatment. The sum weighted method and the TOPSIS was also employed to rank the four technologies, and the results determined by these two methods are consistent to that determined by the proposed method in this study. Copyright © 2017 Elsevier Ltd. All rights reserved.