Testosterone, Cortisol and Financial Risk-Taking

PubMed Central

Herbert, Joe

2018-01-01

Both testosterone and cortisol have major actions on financial decision-making closely related to their primary biological functions, reproductive success and response to stress, respectively. Financial risk-taking represents a particular example of strategic decisions made in the context of choice under conditions of uncertainty. Such decisions have multiple components, and this article considers how much we know of how either hormone affects risk-appetite, reward value, information processing and estimation of the costs and benefits of potential success or failure, both personal and social. It also considers how far we can map these actions on neural mechanisms underlying risk appetite and decision-making, with particular reference to areas of the brain concerned in either cognitive or emotional functions. PMID:29867399

Who Shall Teach Young Children in Multiple Settings?

ERIC Educational Resources Information Center

Roderick, Jessie A.

1987-01-01

Discusses the qualities that educators need to function effectively in a range of child care settings (multiple settings) such as traditional schools, shopping malls, industrial establishments and museums. Decision-making skills, sensitive communicative skills, interest in continuing to learn, and questioning of practice are among the qualities…

Putting Bandits into Context: How Function Learning Supports Decision Making

ERIC Educational Resources Information Center

Schulz, Eric; Konstantinidis, Emmanouil; Speekenbrink, Maarten

2018-01-01

The authors introduce the contextual multi-armed bandit task as a framework to investigate learning and decision making in uncertain environments. In this novel paradigm, participants repeatedly choose between multiple options in order to maximize their rewards. The options are described by a number of contextual features which are predictive of…

Managing the University Campus: Exploring Models for the Future and Supporting Today's Decisions

ERIC Educational Resources Information Center

den Heijer, Alexandra

2012-01-01

Managing contemporary campuses and taking decisions that will impact on those of tomorrow is a complex task for universities worldwide. It involves strategic, financial, functional and physical aspects as well as multiple stakeholders. This article summarises the conclusions of a comprehensive PhD research project which was enriched with lessons…

A boost of confidence: The role of the ventromedial prefrontal cortex in memory, decision-making, and schemas.

PubMed

Hebscher, Melissa; Gilboa, Asaf

2016-09-01

The ventromedial prefrontal cortex (vmPFC) has been implicated in a wide array of functions across multiple domains. In this review, we focus on the vmPFC's involvement in mediating strategic aspects of memory retrieval, memory-related schema functions, and decision-making. We suggest that vmPFC generates a confidence signal that informs decisions and memory-guided behaviour. Confidence is central to these seemingly diverse functions: (1) Strategic retrieval: lesions to the vmPFC impair an early, automatic, and intuitive monitoring process ("feeling of rightness"; FOR) often associated with confabulation (spontaneous reporting of erroneous memories). Critically, confabulators typically demonstrate high levels of confidence in their false memories, suggesting that faulty monitoring following vmPFC damage may lead to indiscriminate confidence signals. (2) Memory schemas: the vmPFC is critically involved in instantiating and maintaining contextually relevant schemas, broadly defined as higher level knowledge structures that encapsulate lower level representational elements. The correspondence between memory retrieval cues and these activated schemas leads to FOR monitoring. Stronger, more elaborate schemas produce stronger FOR and influence confidence in the veracity of memory candidates. (3) Finally, we review evidence on the vmPFC's role in decision-making, extending this role to decision-making during memory retrieval. During non-mnemonic and mnemonic decision-making the vmPFC automatically encodes confidence. Confidence signal in the vmPFC is revealed as a non-linear relationship between a first-order monitoring assessment and second-order action or choice. Attempting to integrate the multiple functions of the vmPFC, we propose a posterior-anterior organizational principle for this region. More posterior vmPFC regions are involved in earlier, automatic, subjective, and contextually sensitive functions, while more anterior regions are involved in controlled actions based on these earlier functions. Confidence signals reflect the non-linear relationship between first-order, posterior-mediated and second-order, anterior-mediated processes and are represented along the entire axis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Embedding Human Expert Cognition Into Autonomous UAS Trajectory Planning.

PubMed

Narayan, Pritesh; Meyer, Patrick; Campbell, Duncan

2013-04-01

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

A vertical-energy-thresholding procedure for data reduction with multiple complex curves.

PubMed

Jung, Uk; Jeong, Myong K; Lu, Jye-Chyi

2006-10-01

Due to the development of sensing and computer technology, measurements of many process variables are available in current manufacturing processes. It is very challenging, however, to process a large amount of information in a limited time in order to make decisions about the health of the processes and products. This paper develops a "preprocessing" procedure for multiple sets of complicated functional data in order to reduce the data size for supporting timely decision analyses. The data type studied has been used for fault detection, root-cause analysis, and quality improvement in such engineering applications as automobile and semiconductor manufacturing and nanomachining processes. The proposed vertical-energy-thresholding (VET) procedure balances the reconstruction error against data-reduction efficiency so that it is effective in capturing key patterns in the multiple data signals. The selected wavelet coefficients are treated as the "reduced-size" data in subsequent analyses for decision making. This enhances the ability of the existing statistical and machine-learning procedures to handle high-dimensional functional data. A few real-life examples demonstrate the effectiveness of our proposed procedure compared to several ad hoc techniques extended from single-curve-based data modeling and denoising procedures.

Resolving response, decision, and strategic control: evidence for a functional topography in dorsomedial prefrontal cortex.

PubMed

Venkatraman, Vinod; Rosati, Alexandra G; Taren, Adrienne A; Huettel, Scott A

2009-10-21

The dorsomedial prefrontal cortex (DMPFC) plays a central role in aspects of cognitive control and decision making. Here, we provide evidence for an anterior-to-posterior topography within the DMPFC using tasks that evoke three distinct forms of control demands--response, decision, and strategic--each of which could be mapped onto independent behavioral data. Specifically, we identify three spatially distinct regions within the DMPFC: a posterior region associated with control demands evoked by multiple incompatible responses, a middle region associated with control demands evoked by the relative desirability of decision options, and an anterior region that predicts control demands related to deviations from an individual's preferred decision-making strategy. These results provide new insight into the functional organization of DMPFC and suggest how recent controversies about its role in complex decision making and response mapping can be reconciled.

Resolving Response, Decision, and Strategic Control: Evidence for a Functional Topography in Dorsomedial Prefrontal Cortex

PubMed Central

Venkatraman, Vinod; Rosati, Alexandra G.; Taren, Adrienne A.; Huettel, Scott A.

2009-01-01

The dorsomedial prefrontal cortex (DMPFC) plays a central role in aspects of cognitive control and decision making. Here, we provide evidence for an anterior-to-posterior topography within the DMPFC using tasks that evoke three distinct forms of control demands – response, decision, and strategic – each of which could be mapped on to independent behavioral data. Specifically, we identify three spatially distinct regions within the DMPFC: a posterior region associated with control demands evoked by multiple incompatible responses, a middle region associated with control demands evoked by the relative desirability of decision options, and an anterior region that predicts control demands related to deviations from an individual's preferred decision-making strategy. These results provide new insight into the functional organization of DMPFC, and suggest how recent controversies about its role in complex decision making and response mapping can be reconciled. PMID:19846703

Multiple Case Studies of Public Library Systems in New York State: Service Decision-Making Processes

ERIC Educational Resources Information Center

Ren, Xiaoai

2012-01-01

This research examined the functions and roles of public library systems in New York State and the services they provide for individual libraries and the public. The dissertation further studied the service decision-making processes at three selected New York State cooperative public library systems. Public library systems have played an important…

Online Learning Era: Exploring the Most Decisive Determinants of MOOCs in Taiwanese Higher Education

ERIC Educational Resources Information Center

Hsieh, Ming-Yuan

2016-01-01

Because the development of Taiwanese Massive Open Online Course (MOOCs) websites is at this moment full of vitality, this research employs a series of analytical cross-measurements of Quality Function Deployment method of House of Quality (QFD-HOQ) model and Multiple Criteria Decision Making (MCDM) methodology to cross-evaluate the weighted…

Uncertainty in sample estimates and the implicit loss function for soil information.

NASA Astrophysics Data System (ADS)

Lark, Murray

2015-04-01

One significant challenge in the communication of uncertain information is how to enable the sponsors of sampling exercises to make a rational choice of sample size. One way to do this is to compute the value of additional information given the loss function for errors. The loss function expresses the costs that result from decisions made using erroneous information. In certain circumstances, such as remediation of contaminated land prior to development, loss functions can be computed and used to guide rational decision making on the amount of resource to spend on sampling to collect soil information. In many circumstances the loss function cannot be obtained prior to decision making. This may be the case when multiple decisions may be based on the soil information and the costs of errors are hard to predict. The implicit loss function is proposed as a tool to aid decision making in these circumstances. Conditional on a logistical model which expresses costs of soil sampling as a function of effort, and statistical information from which the error of estimates can be modelled as a function of effort, the implicit loss function is the loss function which makes a particular decision on effort rational. In this presentation the loss function is defined and computed for a number of arbitrary decisions on sampling effort for a hypothetical soil monitoring problem. This is based on a logistical model of sampling cost parameterized from a recent geochemical survey of soil in Donegal, Ireland and on statistical parameters estimated with the aid of a process model for change in soil organic carbon. It is shown how the implicit loss function might provide a basis for reflection on a particular choice of sample size by comparing it with the values attributed to soil properties and functions. Scope for further research to develop and apply the implicit loss function to help decision making by policy makers and regulators is then discussed.

The Cut-Score Operating Function: A New Tool to Aid in Standard Setting

ERIC Educational Resources Information Center

Grabovsky, Irina; Wainer, Howard

2017-01-01

In this essay, we describe the construction and use of the Cut-Score Operating Function in aiding standard setting decisions. The Cut-Score Operating Function shows the relation between the cut-score chosen and the consequent error rate. It allows error rates to be defined by multiple loss functions and will show the behavior of each loss…

Decision-Making in Multiple Sclerosis Patients: A Systematic Review.

PubMed

Neuhaus, Mireille; Calabrese, Pasquale; Annoni, Jean-Marie

2018-01-01

Multiple sclerosis (MS) is frequently associated with cognitive and behavioural deficits. A growing number of studies suggest an impact of MS on decision-making abilities. The aim of this systematic review was to assess if (1) performance of MS patients in decision-making tasks was consistently different from controls and (2) whether this modification was associated with cognitive dysfunction and emotional alterations. The search was conducted on Pubmed/Medline database. 12 studies evaluating the difference between MS patients and healthy controls using validated decision-making tasks were included. Outcomes considered were quantitative (net scores) and qualitative measurements (deliberation time and learning from feedback). Quantitative and qualitative decision-making impairment in MS was present in 64.7% of measurements. Patients were equally impaired in tasks for decision-making under risk and ambiguity. A correlation to other cognitive functions was present in 50% of cases, with the highest associations in the domains of processing speed and attentional capacity. In MS patients, qualitative and quantitative modifications may be present in any kind of decision-making task and can appear independently of other cognitive measures. Since decision-making abilities have a significant impact on everyday life, this cognitive aspect has an influential importance in various MS-related treatment settings.

Decision Making and Cognitive Behavioral Flexibility in a OCD Sample: a Study in a Virtual Environment.

PubMed

la Paglia, Filippo; la Cascia, Caterina; Rizzo, Rosalinda; Riva, Giuseppe; la Barbera, Daniele

2015-01-01

Neuropsychological disorders are common in Obsessive-Compulsive Disorder (OCD) patients. Executive functions, verbal fluency and verbal memory, shifting attention from one aspect of stimuli to others, mental flexibility, engaging in executive planning and decision making, are the most involved cognitive domains. We focus on two aspects of neuropsychological function: decision making and cognitive behavioral flexibility, assessed through a virtual version of the Multiple Errand Test (V-MET), developed using the NeuroVR software. Thirty OCD patients were compared with thirty matched control subjects. The results showed the presence of difficulties in OCD patients with tasks where the goal is not clear, the information is incomplete or the parameters are ill-defined.

Decision-making competence in younger and older adults: which cognitive abilities contribute to the application of decision rules?

PubMed

Rosi, Alessia; Bruine de Bruin, Wändi; Del Missier, Fabio; Cavallini, Elena; Russo, Riccardo

2017-12-28

Older adults perform worse than younger adults when applying decision rules to choose between options that vary along multiple attributes. Although previous studies have shown that general fluid cognitive abilities contribute to the accurate application of decision rules, relatively little is known about which specific cognitive abilities play the most important role. We examined the independent roles of working memory, verbal fluency, semantic knowledge, and components of executive functioning. We found that age-related decline in applying decision rules was statistically mediated by age-related decline in working memory and verbal fluency. Our results have implications for theories of aging and decision-making.

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

Hybrid Discrete-Continuous Markov Decision Processes

NASA Technical Reports Server (NTRS)

Feng, Zhengzhu; Dearden, Richard; Meuleau, Nicholas; Washington, Rich

2003-01-01

This paper proposes a Markov decision process (MDP) model that features both discrete and continuous state variables. We extend previous work by Boyan and Littman on the mono-dimensional time-dependent MDP to multiple dimensions. We present the principle of lazy discretization, and piecewise constant and linear approximations of the model. Having to deal with several continuous dimensions raises several new problems that require new solutions. In the (piecewise) linear case, we use techniques from partially- observable MDPs (POMDPS) to represent value functions as sets of linear functions attached to different partitions of the state space.

Decision tree analysis in subarachnoid hemorrhage: prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis.

PubMed

Hostettler, Isabel Charlotte; Muroi, Carl; Richter, Johannes Konstantin; Schmid, Josef; Neidert, Marian Christoph; Seule, Martin; Boss, Oliver; Pangalu, Athina; Germans, Menno Robbert; Keller, Emanuela

2018-01-19

OBJECTIVE The aim of this study was to create prediction models for outcome parameters by decision tree analysis based on clinical and laboratory data in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS The database consisted of clinical and laboratory parameters of 548 patients with aSAH who were admitted to the Neurocritical Care Unit, University Hospital Zurich. To examine the model performance, the cohort was randomly divided into a derivation cohort (60% [n = 329]; training data set) and a validation cohort (40% [n = 219]; test data set). The classification and regression tree prediction algorithm was applied to predict death, functional outcome, and ventriculoperitoneal (VP) shunt dependency. Chi-square automatic interaction detection was applied to predict delayed cerebral infarction on days 1, 3, and 7. RESULTS The overall mortality was 18.4%. The accuracy of the decision tree models was good for survival on day 1 and favorable functional outcome at all time points, with a difference between the training and test data sets of < 5%. Prediction accuracy for survival on day 1 was 75.2%. The most important differentiating factor was the interleukin-6 (IL-6) level on day 1. Favorable functional outcome, defined as Glasgow Outcome Scale scores of 4 and 5, was observed in 68.6% of patients. Favorable functional outcome at all time points had a prediction accuracy of 71.1% in the training data set, with procalcitonin on day 1 being the most important differentiating factor at all time points. A total of 148 patients (27%) developed VP shunt dependency. The most important differentiating factor was hyperglycemia on admission. CONCLUSIONS The multiple variable analysis capability of decision trees enables exploration of dependent variables in the context of multiple changing influences over the course of an illness. The decision tree currently generated increases awareness of the early systemic stress response, which is seemingly pertinent for prognostication.

Concussions and Risk Within Cultural Contexts of Play.

PubMed

Torres Colón, Gabriel Alejandro; Smith, Sharia; Fucillo, Jenny

2017-06-01

Concussions are a type of traumatic injury caused by a jolting of the brain that disrupts normal brain function, and multiple concussions can lead to serious long-term health consequences. In this article, we examine the relationship between college students' understanding of concussions and their willingness to continue playing despite the possibility of sustaining multiple head injuries. We use a mixed-methods approach that includes participant observation, cultural domain analysis, and structured interviews. Our research finds that students hold a robust cognitive understanding of concussion yet discursively frame concussions as skeletomuscular injuries. More importantly, students affirm the importance of playing sports for themselves and others, so their decisions to risk multiple concussions must be understood within cultural and biocultural contexts of meaningful social play. We suggest that peoples' decision to risk multiple head injuries should be understood as a desire for meaningful social play rather than an uninformed health risk.

Modeling Choice Under Uncertainty in Military Systems Analysis

DTIC Science & Technology

1991-11-01

operators rather than fuzzy operators. This is suggested for further research. 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) In AHP , objectives, functions and...14 4.1 IMPRECISELY SPECIFIED MULTIPLE A’ITRIBUTE UTILITY THEORY... 14 4.2 FUZZY DECISION ANALYSIS...14 4.3 ANALYTIC HIERARCHICAL PROCESS ( AHP ) ................................... 14 4.4 SUBJECTIVE TRANSFER FUNCTION APPROACH

Altered functional MR imaging language activation in elderly individuals with cerebral leukoaraiosis.

PubMed

Welker, Kirk M; De Jesus, Reordan O; Watson, Robert E; Machulda, Mary M; Jack, Clifford R

2012-10-01

To test the hypothesis that leukoaraiosis alters functional activation during a semantic decision language task. With institutional review board approval and written informed consent, 18 right-handed, cognitively healthy elderly participants with an aggregate leukoaraiosis lesion volume of more than 25 cm(3) and 18 age-matched control participants with less than 5 cm(3) of leukoaraiosis underwent functional MR imaging to allow comparison of activation during semantic decisions with that during visual perceptual decisions. Brain statistical maps were derived from the general linear model. Spatially normalized group t maps were created from individual contrast images. A cluster extent threshold of 215 voxels was used to correct for multiple comparisons. Intergroup random effects analysis was performed. Language laterality indexes were calculated for each participant. In control participants, semantic decisions activated the bilateral visual cortex, left posteroinferior temporal lobe, left posterior cingulate gyrus, left frontal lobe expressive language regions, and left basal ganglia. Visual perceptual decisions activated the right parietal and posterior temporal lobes. Participants with leukoaraiosis showed reduced activation in all regions associated with semantic decisions; however, activation associated with visual perceptual decisions increased in extent. Intergroup analysis showed significant activation decreases in the left anterior occipital lobe (P=.016), right posterior temporal lobe (P=.048), and right basal ganglia (P=.009) in particpants with leukoariosis. Individual participant laterality indexes showed a strong trend (P=.059) toward greater left lateralization in the leukoaraiosis group. Moderate leukoaraiosis is associated with atypical functional activation during semantic decision tasks. Consequently, leukoaraiosis is an important confounding variable in functional MR imaging studies of elderly individuals. © RSNA, 2012.

Prefrontal Contribution to Decision-Making under Free-Choice Conditions

PubMed Central

Funahashi, Shintaro

2017-01-01

Executive function is thought to be the coordinated operation of multiple neural processes and allows to accomplish a current goal flexibly. The most important function of the prefrontal cortex is the executive function. Among a variety of executive functions in which the prefrontal cortex participates, decision-making is one of the most important. Although the prefrontal contribution to decision-making has been examined using a variety of behavioral tasks, recent studies using fMRI have shown that the prefrontal cortex participates in decision-making under free-choice conditions. Since decision-making under free-choice conditions represents the very first stage for any kind of decision-making process, it is important that we understand its neural mechanism. Although few studies have examined this issue while a monkey performed a free-choice task, those studies showed that, when the monkey made a decision to subsequently choose one particular option, prefrontal neurons showing selectivity to that option exhibited transient activation just before presentation of the imperative cue. Further studies have suggested that this transient increase is caused by the irregular fluctuation of spontaneous firing just before cue presentation, which enhances the response to the cue and biases the strength of the neuron's selectivity to the option. In addition, this biasing effect was observed only in neurons that exhibited sustained delay-period activity, indicating that this biasing effect not only influences the animal's decision for an upcoming choice, but also is linked to working memory mechanisms in the prefrontal cortex. PMID:28798662

Chemotherapy treatment decision-making experiences of older adults with cancer, their family members, oncologists and family physicians: a mixed methods study.

PubMed

Puts, Martine T E; Sattar, Schroder; McWatters, Kara; Lee, Katherine; Kulik, Michael; MacDonald, Mary-Ellen; Jang, Raymond; Amir, Eitan; Krzyzanowska, Monika K; Leighl, Natasha; Fitch, Margaret; Joshua, Anthony M; Warde, Padraig; Tourangeau, Ann E; Alibhai, Shabbir M H

2017-03-01

Although comorbidities, frailty, and functional impairment are common in older adults (OA) with cancer, little is known about how these factors are considered during the treatment decision-making process by OAs, their families, and health care providers. Our aim was to better understand the treatment decision process from all these perspectives. A mixed methods multi-perspective longitudinal study using semi-structured interviews and surveys with 29 OAs aged ≥70 years with advanced prostate, breast, colorectal, or lung cancer, 24 of their family members,13 oncologists, and 15 family physicians was conducted. The sample was stratified on age (70-79 and 80+). All interviews were analyzed using thematic analysis. There was no difference in the treatment decision-making experience based on age. Most OAs felt that they should have the final say in the treatment decision, but strongly valued their oncologists' opinion. "Trust in my oncologist" and "chemotherapy as the last resort to prolong life" were the most important reasons to accept treatment. Families indicated a need to improve communication between them, the patient and the specialist, particularly around goals of treatment. Comorbidity and potential side-effects did not play a major role in the treatment decision-making for patients, families, or oncologists. Family physicians reported no involvement in decisions but desired to be more involved. This first study using multiple perspectives showed neither frailty nor comorbidity played a role in the treatment decision-making process. Efforts to improve communication were identified as an opportunity that may enhance quality of care. In a mixed methods study multiple perspective study with older adults with cancer, their family members, their oncologist and their family physician we explored the treatment decision making process and found that most older adults were satisfied with their decision. Comorbidity, functional status and frailty did not impact the older adult's or their family members' decision.

PROBING HUMAN AND MONKEY ANTERIOR CINGULATE CORTEX IN VARIABLE ENVIRONMENTS

PubMed Central

Walton, Mark E.; Mars, Rogier B.

2008-01-01

Previous research has identified the anterior cingulate cortex (ACC) as an important node in the neural network underlying decision making in primates. Decision making can, however, be studied under large variety of circumstances, ranging from the standard well-controlled lab situation to more natural, stochastic settings during which multiple agents interact. Here, we illustrate how these different varieties of decision making studied can influence theories of ACC function in monkeys. Converging evidence from unit recordings and lesions studies now suggest that the ACC is important for interpreting outcome information according to the current task context to guide future action selection. We then apply this framework to the study of human ACC function and discuss its potential implications. PMID:18189014

Web-services-based spatial decision support system to facilitate nuclear waste siting

NASA Astrophysics Data System (ADS)

Huang, L. Xinglai; Sheng, Grant

2006-10-01

The availability of spatial web services enables data sharing among managers, decision and policy makers and other stakeholders in much simpler ways than before and subsequently has created completely new opportunities in the process of spatial decision making. Though generally designed for a certain problem domain, web-services-based spatial decision support systems (WSDSS) can provide a flexible problem-solving environment to explore the decision problem, understand and refine problem definition, and generate and evaluate multiple alternatives for decision. This paper presents a new framework for the development of a web-services-based spatial decision support system. The WSDSS is comprised of distributed web services that either have their own functions or provide different geospatial data and may reside in different computers and locations. WSDSS includes six key components, namely: database management system, catalog, analysis functions and models, GIS viewers and editors, report generators, and graphical user interfaces. In this study, the architecture of a web-services-based spatial decision support system to facilitate nuclear waste siting is described as an example. The theoretical, conceptual and methodological challenges and issues associated with developing web services-based spatial decision support system are described.

Decision-Making in Multiple Sclerosis Patients: A Systematic Review

PubMed Central

2018-01-01

Background Multiple sclerosis (MS) is frequently associated with cognitive and behavioural deficits. A growing number of studies suggest an impact of MS on decision-making abilities. The aim of this systematic review was to assess if (1) performance of MS patients in decision-making tasks was consistently different from controls and (2) whether this modification was associated with cognitive dysfunction and emotional alterations. Methods The search was conducted on Pubmed/Medline database. 12 studies evaluating the difference between MS patients and healthy controls using validated decision-making tasks were included. Outcomes considered were quantitative (net scores) and qualitative measurements (deliberation time and learning from feedback). Results Quantitative and qualitative decision-making impairment in MS was present in 64.7% of measurements. Patients were equally impaired in tasks for decision-making under risk and ambiguity. A correlation to other cognitive functions was present in 50% of cases, with the highest associations in the domains of processing speed and attentional capacity. Conclusions In MS patients, qualitative and quantitative modifications may be present in any kind of decision-making task and can appear independently of other cognitive measures. Since decision-making abilities have a significant impact on everyday life, this cognitive aspect has an influential importance in various MS-related treatment settings. PMID:29721338

A trainable decisions-in decision-out (DEI-DEO) fusion system

NASA Astrophysics Data System (ADS)

Dasarathy, Belur V.

1998-03-01

Most of the decision fusion systems proposed hitherto in the literature for multiple data source (sensor) environments operate on the basis of pre-defined fusion logic, be they crisp (deterministic), probabilistic, or fuzzy in nature, with no specific learning phase. The fusion systems that are trainable, i.e., ones that have a learning phase, mostly operate in the features-in-decision-out mode, which essentially reduces the fusion process functionally to a pattern classification task in the joint feature space. In this study, a trainable decisions-in-decision-out fusion system is described which estimates a fuzzy membership distribution spread across the different decision choices based on the performance of the different decision processors (sensors) corresponding to each training sample (object) which is associated with a specific ground truth (true decision). Based on a multi-decision space histogram analysis of the performance of the different processors over the entire training data set, a look-up table associating each cell of the histogram with a specific true decision is generated which forms the basis for the operational phase. In the operational phase, for each set of decision inputs, a pointer to the look-up table learnt previously is generated from which a fused decision is derived. This methodology, although primarily designed for fusing crisp decisions from the multiple decision sources, can be adapted for fusion of fuzzy decisions as well if such are the inputs from these sources. Examples, which illustrate the benefits and limitations of the crisp and fuzzy versions of the trainable fusion systems, are also included.

Clustering and group selection of multiple criteria alternatives with application to space-based networks.

PubMed

Malakooti, Behnam; Yang, Ziyong

2004-02-01

In many real-world problems, the range of consequences of different alternatives are considerably different. In addition, sometimes, selection of a group of alternatives (instead of only one best alternative) is necessary. Traditional decision making approaches treat the set of alternatives with the same method of analysis and selection. In this paper, we propose clustering alternatives into different groups so that different methods of analysis, selection, and implementation for each group can be applied. As an example, consider the selection of a group of functions (or tasks) to be processed by a group of processors. The set of tasks can be grouped according to their similar criteria, and hence, each cluster of tasks to be processed by a processor. The selection of the best alternative for each clustered group can be performed using existing methods; however, the process of selecting groups is different than the process of selecting alternatives within a group. We develop theories and procedures for clustering discrete multiple criteria alternatives. We also demonstrate how the set of alternatives is clustered into mutually exclusive groups based on 1) similar features among alternatives; 2) ideal (or most representative) alternatives given by the decision maker; and 3) other preferential information of the decision maker. The clustering of multiple criteria alternatives also has the following advantages. 1) It decreases the set of alternatives to be considered by the decision maker (for example, different decision makers are assigned to different groups of alternatives). 2) It decreases the number of criteria. 3) It may provide a different approach for analyzing multiple decision makers problems. Each decision maker may cluster alternatives differently, and hence, clustering of alternatives may provide a basis for negotiation. The developed approach is applicable for solving a class of telecommunication networks problems where a set of objects (such as routers, processors, or intelligent autonomous vehicles) are to be clustered into similar groups. Objects are clustered based on several criteria and the decision maker's preferences.

Effort-Based Decision-Making in Schizophrenia.

PubMed

Culbreth, Adam J; Moran, Erin K; Barch, Deanna M

2018-08-01

Motivational impairment has long been associated with schizophrenia but the underlying mechanisms are not clearly understood. Recently, a small but growing literature has suggested that aberrant effort-based decision-making may be a potential contributory mechanism for motivational impairments in psychosis. Specifically, multiple reports have consistently demonstrated that individuals with schizophrenia are less willing than healthy controls to expend effort to obtain rewards. Further, this effort-based decision-making deficit has been shown to correlate with severity of negative symptoms and level of functioning, in many but not all studies. In the current review, we summarize this literature and discuss several factors that may underlie aberrant effort-based decision-making in schizophrenia.

Overlapping Networks Engaged during Spoken Language Production and Its Cognitive Control

PubMed Central

Wise, Richard J.S.; Mehta, Amrish; Leech, Robert

2014-01-01

Spoken language production is a complex brain function that relies on large-scale networks. These include domain-specific networks that mediate language-specific processes, as well as domain-general networks mediating top-down and bottom-up attentional control. Language control is thought to involve a left-lateralized fronto-temporal-parietal (FTP) system. However, these regions do not always activate for language tasks and similar regions have been implicated in nonlinguistic cognitive processes. These inconsistent findings suggest that either the left FTP is involved in multidomain cognitive control or that there are multiple spatially overlapping FTP systems. We present evidence from an fMRI study using multivariate analysis to identify spatiotemporal networks involved in spoken language production in humans. We compared spoken language production (Speech) with multiple baselines, counting (Count), nonverbal decision (Decision), and “rest,” to pull apart the multiple partially overlapping networks that are involved in speech production. A left-lateralized FTP network was activated during Speech and deactivated during Count and nonverbal Decision trials, implicating it in cognitive control specific to sentential spoken language production. A mirror right-lateralized FTP network was activated in the Count and Decision trials, but not Speech. Importantly, a second overlapping left FTP network showed relative deactivation in Speech. These three networks, with distinct time courses, overlapped in the left parietal lobe. Contrary to the standard model of the left FTP as being dominant for speech, we revealed a more complex pattern within the left FTP, including at least two left FTP networks with competing functional roles, only one of which was activated in speech production. PMID:24966373

Overlapping networks engaged during spoken language production and its cognitive control.

PubMed

Geranmayeh, Fatemeh; Wise, Richard J S; Mehta, Amrish; Leech, Robert

2014-06-25

Spoken language production is a complex brain function that relies on large-scale networks. These include domain-specific networks that mediate language-specific processes, as well as domain-general networks mediating top-down and bottom-up attentional control. Language control is thought to involve a left-lateralized fronto-temporal-parietal (FTP) system. However, these regions do not always activate for language tasks and similar regions have been implicated in nonlinguistic cognitive processes. These inconsistent findings suggest that either the left FTP is involved in multidomain cognitive control or that there are multiple spatially overlapping FTP systems. We present evidence from an fMRI study using multivariate analysis to identify spatiotemporal networks involved in spoken language production in humans. We compared spoken language production (Speech) with multiple baselines, counting (Count), nonverbal decision (Decision), and "rest," to pull apart the multiple partially overlapping networks that are involved in speech production. A left-lateralized FTP network was activated during Speech and deactivated during Count and nonverbal Decision trials, implicating it in cognitive control specific to sentential spoken language production. A mirror right-lateralized FTP network was activated in the Count and Decision trials, but not Speech. Importantly, a second overlapping left FTP network showed relative deactivation in Speech. These three networks, with distinct time courses, overlapped in the left parietal lobe. Contrary to the standard model of the left FTP as being dominant for speech, we revealed a more complex pattern within the left FTP, including at least two left FTP networks with competing functional roles, only one of which was activated in speech production. Copyright © 2014 Geranmayeh et al.

Cortical topography of intracortical inhibition influences the speed of decision making.

PubMed

Wilimzig, Claudia; Ragert, Patrick; Dinse, Hubert R

2012-02-21

The neocortex contains orderly topographic maps; however, their functional role remains controversial. Theoretical studies have suggested a role in minimizing computational costs, whereas empirical studies have focused on spatial localization. Using a tactile multiple-choice reaction time (RT) task before and after the induction of perceptual learning through repetitive sensory stimulation, we extend the framework of cortical topographies by demonstrating that the topographic arrangement of intracortical inhibition contributes to the speed of human perceptual decision-making processes. RTs differ among fingers, displaying an inverted U-shaped function. Simulations using neural fields show the inverted U-shaped RT distribution as an emergent consequence of lateral inhibition. Weakening inhibition through learning shortens RTs, which is modeled through topographically reorganized inhibition. Whereas changes in decision making are often regarded as an outcome of higher cortical areas, our data show that the spatial layout of interaction processes within representational maps contributes to selection and decision-making processes.

Cortical topography of intracortical inhibition influences the speed of decision making

PubMed Central

Wilimzig, Claudia; Ragert, Patrick; Dinse, Hubert R.

2012-01-01

The neocortex contains orderly topographic maps; however, their functional role remains controversial. Theoretical studies have suggested a role in minimizing computational costs, whereas empirical studies have focused on spatial localization. Using a tactile multiple-choice reaction time (RT) task before and after the induction of perceptual learning through repetitive sensory stimulation, we extend the framework of cortical topographies by demonstrating that the topographic arrangement of intracortical inhibition contributes to the speed of human perceptual decision-making processes. RTs differ among fingers, displaying an inverted U-shaped function. Simulations using neural fields show the inverted U-shaped RT distribution as an emergent consequence of lateral inhibition. Weakening inhibition through learning shortens RTs, which is modeled through topographically reorganized inhibition. Whereas changes in decision making are often regarded as an outcome of higher cortical areas, our data show that the spatial layout of interaction processes within representational maps contributes to selection and decision-making processes. PMID:22315409

Game theory and neural basis of social decision making

PubMed Central

Lee, Daeyeol

2008-01-01

Decision making in a social group displays two unique features. First, humans and other animals routinely alter their behaviors in response to changes in their physical and social environment. As a result, the outcomes of decisions that depend on the behaviors of multiple decision makers are difficult to predict, and this requires highly adaptive decision-making strategies. Second, decision makers may have other-regarding preferences and therefore choose their actions to improve or reduce the well-beings of others. Recently, many neurobiological studies have exploited game theory to probe the neural basis of decision making, and found that these unique features of social decision making might be reflected in the functions of brain areas involved in reward evaluation and reinforcement learning. Molecular genetic studies have also begun to identify genetic mechanisms for personal traits related to reinforcement learning and complex social decision making, further illuminating the biological basis of social behavior. PMID:18368047

Minimising farm crop protection pressure supported by the multiple functionalities of the DISCUSS indicator set.

PubMed

Wustenberghs, Hilde; Fevery, Davina; Lauwers, Ludwig; Marchand, Fleur; Spanoghe, Pieter

2018-03-15

Sustainable crop protection (SCP) has many facets. Farmers may therefore perceive transition to SCP as very complex. The Dual Indicator Set for Crop Protection Sustainability (DISCUSS) can handle this complexity. To provide targeted support throughout the transition to SCP, complexity capture must be synchronised with the time course of on-farm decision-making. Tool use must be tuned to farmer awareness and appropriate level of data in consecutive stages. This paper thus explores the potential functionalities of DISCUSS in relation to both complexity and time. Results from apple and potato crop protection show three potential functions: DISCUSS can be used as (1) a simulation tool for communication and decision support, (2) an assessment and monitoring tool, and (3) a discussion support tool for farmer groups. Analysis of these functionalities using a framework for guiding on-farm sustainability assessment and strategic decision-making shows how each functionality can support the consecutive steps of transition to SCP, i.e. using the right tool functionality at the right time. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Multiple IMU system hardware interface design, volume 2

NASA Technical Reports Server (NTRS)

Landey, M.; Brown, D.

1975-01-01

The design of each system component is described. Emphasis is placed on functional requirements unique in this system, including data bus communication, data bus transmitters and receivers, and ternary-to-binary torquing decision logic. Mechanization drawings are presented.

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.

Functional and Structural Signatures of the Anterior Insula are associated with Risk-taking Tendency of Analgesic Decision-making.

PubMed

Lin, Chia-Shu; Lin, Hsiao-Han; Wu, Shih-Yun

2016-11-28

In a medical context, decision-making is associated with complicated assessment of gains, losses and uncertainty of outcomes. We here provide novel evidence about the brain mechanisms underlying decision-making of analgesic treatment. Thirty-six healthy participants were recruited and completed the Analgesic Decision-making Task (ADT), which quantified individual tendency of risk-taking (RPI), as the frequency of choosing a riskier option to relieve pain. All the participants received resting-state (rs) functional magnetic resonance imaging (MRI) and structural MRI. On rs-functional connectome, degree centrality (DC) of the bilateral anterior insula (aINS) was positively correlated with the RPI. The functional connectivity between the aINS, the nucleus accumbens and multiple brain regions, predominantly the medial frontal cortex, was positively correlated with the RPI. On structural signatures, the RPI was positively correlated with grey matter volume at the right aINS, and such an association was mediated by DC of the left aINS. Regression analyses revealed that both DC of the left aINS and participants' imagined pain relief, as the utility of pain reduction, could predict the individual RPI. The findings suggest that the functional and structural brain signature of the aINS is associated with the individual differences of risk-taking tendency in the context of analgesic decision-making.

A Decision Analysis Framework for Evaluation of Helmet Mounted Display Alternatives for Fighter Aircraft

DTIC Science & Technology

2014-12-26

additive value function, which assumes mutual preferential independence (Gregory S. Parnell, 2013). In other words, this method can be used if the... additive value function method to calculate the aggregate value of multiple objectives. Step 9 : Sensitivity Analysis Once the global values are...gravity metric, the additive method will be applied using equal weights for each axis value function. Pilot Satisfaction (Usability) As expressed

A Practical Approach to Address Uncertainty in Stakeholder Deliberations.

PubMed

Gregory, Robin; Keeney, Ralph L

2017-03-01

This article addresses the difficulties of incorporating uncertainty about consequence estimates as part of stakeholder deliberations involving multiple alternatives. Although every prediction of future consequences necessarily involves uncertainty, a large gap exists between common practices for addressing uncertainty in stakeholder deliberations and the procedures of prescriptive decision-aiding models advanced by risk and decision analysts. We review the treatment of uncertainty at four main phases of the deliberative process: with experts asked to describe possible consequences of competing alternatives, with stakeholders who function both as individuals and as members of coalitions, with the stakeholder committee composed of all stakeholders, and with decisionmakers. We develop and recommend a model that uses certainty equivalents as a theoretically robust and practical approach for helping diverse stakeholders to incorporate uncertainties when evaluating multiple-objective alternatives as part of public policy decisions. © 2017 Society for Risk Analysis.

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

The influences and neural correlates of past and present during gambling in humans.

PubMed

Sacré, Pierre; Subramanian, Sandya; Kerr, Matthew S D; Kahn, Kevin; Johnson, Matthew A; Bulacio, Juan; González-Martínez, Jorge A; Sarma, Sridevi V; Gale, John T

2017-12-07

During financial decision-making tasks, humans often make "rational" decisions, where they maximize expected reward. However, this rationality may compete with a bias that reflects past outcomes. That is, if one just lost money or won money, this may impact future decisions. It is unclear how past outcomes influence future decisions in humans, and how neural circuits encode present and past information. In this study, six human subjects performed a financial decision-making task while we recorded local field potentials from multiple brain structures. We constructed a model for each subject characterizing bets on each trial as a function of present and past information. The models suggest that some patients are more influenced by previous trial outcomes (i.e., previous return and risk) than others who stick to more fixed decision strategies. In addition, past return and present risk modulated with the activity in the cuneus; while present return and past risk modulated with the activity in the superior temporal gyrus and the angular gyrus, respectively. Our findings suggest that these structures play a role in decision-making beyond their classical functions by incorporating predictions and risks in humans' decision strategy, and provide new insight into how humans link their internal biases to decisions.

The grey matter correlates of impaired decision-making in multiple sclerosis

PubMed Central

Muhlert, Nils; Sethi, Varun; Cipolotti, Lisa; Haroon, Hamied; Parker, Geoff J M; Yousry, Tarek; Wheeler-Kingshott, Claudia; Miller, David; Ron, Maria; Chard, Declan

2015-01-01

Objective People with multiple sclerosis (MS) have difficulties with decision-making but it is unclear if this is due to changes in impulsivity, risk taking, deliberation or risk adjustment, and how this relates to brain pathology. Methods We assessed these aspects of decision-making in 105 people with MS and 43 healthy controls. We used a novel diffusion MRI method, diffusion orientational complexity (DOC), as an index of grey matter pathology in regions associated with decision-making and also measured grey matter tissue volumes and white matter lesion volumes. Results People with MS showed less adjustment to risk and slower decision-making than controls. Moreover, impaired decision-making correlated with reduced executive function, memory and processing speed. Decision-making impairments were most prevalent in people with secondary progressive MS. They were seen in patients with cognitive impairment and those without cognitive impairment. On diffusion MRI, people with MS showed DOC changes in all regions except the occipital cortex, relative to controls. Risk adjustment correlated with DOC in the hippocampi and deliberation time with DOC in the medial prefrontal, middle frontal gyrus, anterior cingulate and caudate parcellations and with white matter lesion volumes. Conclusions These data clarify the features of decision-making deficits in MS, and provide the first evidence that they relate to grey and white matter abnormalities seen using MRI. PMID:25006208

Developing objectives with multiple stakeholders: adaptive management of horseshoe crabs and Red Knots in the Delaware Bay

USGS Publications Warehouse

McGowan, Conor P.; Lyons, James E.; Smith, David

2015-01-01

Structured decision making (SDM) is an increasingly utilized approach and set of tools for addressing complex decisions in environmental management. SDM is a value-focused thinking approach that places paramount importance on first establishing clear management objectives that reflect core values of stakeholders. To be useful for management, objectives must be transparently stated in unambiguous and measurable terms. We used these concepts to develop consensus objectives for the multiple stakeholders of horseshoe crab harvest in Delaware Bay. Participating stakeholders first agreed on a qualitative statement of fundamental objectives, and then worked to convert those objectives to specific and measurable quantities, so that management decisions could be assessed. We used a constraint-based approach where the conservation objectives for Red Knots, a species of migratory shorebird that relies on horseshoe crab eggs as a food resource during migration, constrained the utility of crab harvest. Developing utility functions to effectively reflect the management objectives allowed us to incorporate stakeholder risk aversion even though different stakeholder groups were averse to different or competing risks. While measurable objectives and quantitative utility functions seem scientific, developing these objectives was fundamentally driven by the values of the participating stakeholders.

Developing Objectives with Multiple Stakeholders: Adaptive Management of Horseshoe Crabs and Red Knots in the Delaware Bay

NASA Astrophysics Data System (ADS)

McGowan, Conor P.; Lyons, James E.; Smith, David R.

2015-04-01

Structured decision making (SDM) is an increasingly utilized approach and set of tools for addressing complex decisions in environmental management. SDM is a value-focused thinking approach that places paramount importance on first establishing clear management objectives that reflect core values of stakeholders. To be useful for management, objectives must be transparently stated in unambiguous and measurable terms. We used these concepts to develop consensus objectives for the multiple stakeholders of horseshoe crab harvest in Delaware Bay. Participating stakeholders first agreed on a qualitative statement of fundamental objectives, and then worked to convert those objectives to specific and measurable quantities, so that management decisions could be assessed. We used a constraint-based approach where the conservation objectives for Red Knots, a species of migratory shorebird that relies on horseshoe crab eggs as a food resource during migration, constrained the utility of crab harvest. Developing utility functions to effectively reflect the management objectives allowed us to incorporate stakeholder risk aversion even though different stakeholder groups were averse to different or competing risks. While measurable objectives and quantitative utility functions seem scientific, developing these objectives was fundamentally driven by the values of the participating stakeholders.

Evaluating gambles using dynamics

NASA Astrophysics Data System (ADS)

Peters, O.; Gell-Mann, M.

2016-02-01

Gambles are random variables that model possible changes in wealth. Classic decision theory transforms money into utility through a utility function and defines the value of a gamble as the expectation value of utility changes. Utility functions aim to capture individual psychological characteristics, but their generality limits predictive power. Expectation value maximizers are defined as rational in economics, but expectation values are only meaningful in the presence of ensembles or in systems with ergodic properties, whereas decision-makers have no access to ensembles, and the variables representing wealth in the usual growth models do not have the relevant ergodic properties. Simultaneously addressing the shortcomings of utility and those of expectations, we propose to evaluate gambles by averaging wealth growth over time. No utility function is needed, but a dynamic must be specified to compute time averages. Linear and logarithmic "utility functions" appear as transformations that generate ergodic observables for purely additive and purely multiplicative dynamics, respectively. We highlight inconsistencies throughout the development of decision theory, whose correction clarifies that our perspective is legitimate. These invalidate a commonly cited argument for bounded utility functions.

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…

Scenario and multiple criteria decision analysis for energy and environmental security of military and industrial installations.

PubMed

Karvetski, Christopher W; Lambert, James H; Linkov, Igor

2011-04-01

Military and industrial facilities need secure and reliable power generation. Grid outages can result in cascading infrastructure failures as well as security breaches and should be avoided. Adding redundancy and increasing reliability can require additional environmental, financial, logistical, and other considerations and resources. Uncertain scenarios consisting of emergent environmental conditions, regulatory changes, growth of regional energy demands, and other concerns result in further complications. Decisions on selecting energy alternatives are made on an ad hoc basis. The present work integrates scenario analysis and multiple criteria decision analysis (MCDA) to identify combinations of impactful emergent conditions and to perform a preliminary benefits analysis of energy and environmental security investments for industrial and military installations. Application of a traditional MCDA approach would require significant stakeholder elicitations under multiple uncertain scenarios. The approach proposed in this study develops and iteratively adjusts a scoring function for investment alternatives to find the scenarios with the most significant impacts on installation security. A robust prioritization of investment alternatives can be achieved by integrating stakeholder preferences and focusing modeling and decision-analytical tools on a few key emergent conditions and scenarios. The approach is described and demonstrated for a campus of several dozen interconnected industrial buildings within a major installation. Copyright © 2010 SETAC.

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

DTIC Science & Technology

2008-06-01

The most common outranking methods are the preference ranking organization method for enrichment evaluation ( PROMETHEE ) and the elimination and...Brans and Ph. Vincke, “A Preference Ranking Organization Method: (The PROMETHEE Method for Multiple Criteria Decision-Making),” Management Science 31... PROMETHEE ). This method needs a preference function for each criterion to compute the degree of preference.72 “The credibility of the outranking

Interactive Reference Point Procedure Based on the Conic Scalarizing Function

PubMed Central

2014-01-01

In multiobjective optimization methods, multiple conflicting objectives are typically converted into a single objective optimization problem with the help of scalarizing functions. The conic scalarizing function is a general characterization of Benson proper efficient solutions of non-convex multiobjective problems in terms of saddle points of scalar Lagrangian functions. This approach preserves convexity. The conic scalarizing function, as a part of a posteriori or a priori methods, has successfully been applied to several real-life problems. In this paper, we propose a conic scalarizing function based interactive reference point procedure where the decision maker actively takes part in the solution process and directs the search according to her or his preferences. An algorithmic framework for the interactive solution of multiple objective optimization problems is presented and is utilized for solving some illustrative examples. PMID:24723795

Executive function, approach sensitivity, and emotional decision making as influences on risk behaviors in young adults.

PubMed

Patrick, Megan E; Blair, Clancy; Maggs, Jennifer L

2008-05-01

Relations among executive function, behavioral approach sensitivity, emotional decision making, and risk behaviors (alcohol use, drug use, and delinquent behavior) were examined in single female college students (N = 72). Hierarchical multiple regressions indicated a significant Approach Sensitivity x Working Memory interaction in which higher levels of alcohol use were associated with the combination of greater approach tendency and better working memory. This Approach Sensitivity x Working Memory interaction was also marginally significant for drug use and delinquency. Poor emotional decision making, as measured by a gambling task, was also associated with higher levels of alcohol use, but only for individuals low in inhibitory control. Findings point to the complexity of relations among aspects of self-regulation and personality and provide much needed data on neuropsychological correlates of risk behaviors in a nonclinical population.

Clinical decision making-a functional medicine perspective.

PubMed

Pizzorno, Joseph E

2012-09-01

As 21st century health care moves from a disease-based approach to a more patient-centric system that can address biochemical individuality to improve health and function, clinical decision making becomes more complex. Accentuating the problem is the lack of a clear standard for this more complex functional medicine approach. While there is relatively broad agreement in Western medicine for what constitutes competent assessment of disease and identification of related treatment approaches, the complex functional medicine model posits multiple and individualized diagnostic and therapeutic approaches, most or many of which have reasonable underlying science and principles, but which have not been rigorously tested in a research or clinical setting. This has led to non-rigorous thinking and sometimes to uncritical acceptance of both poorly documented diagnostic procedures and ineffective therapies, resulting in less than optimal clinical care.

Clinical Decision Making—A Functional Medicine Perspective

PubMed Central

2012-01-01

As 21st century health care moves from a disease-based approach to a more patient-centric system that can address biochemical individuality to improve health and function, clinical decision making becomes more complex. Accentuating the problem is the lack of a clear standard for this more complex functional medicine approach. While there is relatively broad agreement in Western medicine for what constitutes competent assessment of disease and identification of related treatment approaches, the complex functional medicine model posits multiple and individualized diagnostic and therapeutic approaches, most or many of which have reasonable underlying science and principles, but which have not been rigorously tested in a research or clinical setting. This has led to non-rigorous thinking and sometimes to uncritical acceptance of both poorly documented diagnostic procedures and ineffective therapies, resulting in less than optimal clinical care. PMID:24278827

ASSESSMENT OF UPPER EXTREMITY IMPAIRMENT, FUNCTION, AND ACTIVITY FOLLOWING STROKE: FOUNDATIONS FOR CLINICAL DECISION MAKING

PubMed Central

Lang, Catherine E.; Bland, Marghuretta D.; Bailey, Ryan R.; Schaefer, Sydney Y.; Birkenmeier, Rebecca L.

2012-01-01

The purpose of this review is to provide a comprehensive approach for assessing the upper extremity (UE) after stroke. First, common upper extremity impairments and how to assess them are briefly discussed. While multiple UE impairments are typically present after stroke, the severity of one impairment, paresis, is the primary determinant of UE functional loss. Second, UE function is operationally defined and a number of clinical measures are discussed. It is important to consider how impairment and loss of function affect UE activity outside of the clinical environment. Thus, this review also identifies accelerometry as an objective method for assessing UE activity in daily life. Finally, the role that each of these levels of assessment should play in clinical decision making is discussed in order to optimize the provision of stroke rehabilitation services. PMID:22975740

Fuzzy bilevel programming with multiple non-cooperative followers: model, algorithm and application

NASA Astrophysics Data System (ADS)

Ke, Hua; Huang, Hu; Ralescu, Dan A.; Wang, Lei

2016-04-01

In centralized decision problems, it is not complicated for decision-makers to make modelling technique selections under uncertainty. When a decentralized decision problem is considered, however, choosing appropriate models is no longer easy due to the difficulty in estimating the other decision-makers' inconclusive decision criteria. These decision criteria may vary with different decision-makers because of their special risk tolerances and management requirements. Considering the general differences among the decision-makers in decentralized systems, we propose a general framework of fuzzy bilevel programming including hybrid models (integrated with different modelling methods in different levels). Specially, we discuss two of these models which may have wide applications in many fields. Furthermore, we apply the proposed two models to formulate a pricing decision problem in a decentralized supply chain with fuzzy coefficients. In order to solve these models, a hybrid intelligent algorithm integrating fuzzy simulation, neural network and particle swarm optimization based on penalty function approach is designed. Some suggestions on the applications of these models are also presented.

Efficient group decision making in workshop settings

Treesearch

Daniel L. Schmoldt; David L. Peterson

2001-01-01

Public land managers must treat multiple values coincidentally in time and space, which requires the participation of multiple resource specialists and consideration of diverse clientele interests in the decision process. This implies decision making that includes multiple participants, both internally and externally. Decades of social science research on decision...

Repetition priming influences distinct brain systems: evidence from task-evoked data and resting-state correlations.

PubMed

Wig, Gagan S; Buckner, Randy L; Schacter, Daniel L

2009-05-01

Behavioral dissociations suggest that a single experience can separately influence multiple processing components. Here we used a repetition priming functional magnetic resonance imaging paradigm that directly contrasted the effects of stimulus and decision changes to identify the underlying brain systems. Direct repetition of stimulus features caused marked reductions in posterior regions of the inferior temporal lobe that were insensitive to whether the decision was held constant or changed between study and test. By contrast, prefrontal cortex showed repetition effects that were sensitive to the exact stimulus-to-decision mapping. Analysis of resting-state functional connectivity revealed that the dissociated repetition effects are embedded within distinct brain systems. Regions that were sensitive to changes in the stimulus correlated with perceptual cortices, whereas the decision changes attenuated activity in regions correlated with middle-temporal regions and a frontoparietal control system. These results thus explain the long-known dissociation between perceptual and conceptual components of priming by revealing how a single experience can separately influence distinct, concurrently active brain systems.

Effects of Age, Sex, and Neuropsychological Performance on Financial Decision-Making

PubMed Central

Shivapour, Sara K.; Nguyen, Christopher M.; Cole, Catherine A.; Denburg, Natalie L.

2012-01-01

The capacity to make sound financial decisions across the lifespan is critical for interpersonal, occupational, and psychological health and success. In the present study, we explored how healthy younger and older adults make a series of increasingly complex financial decisions. One-hundred sixteen healthy older adults, aged 56–90 years, and 102 college undergraduates, completed the Financial Decision-Making Questionnaire, which requires selecting and justifying financial choices across four hypothetical scenarios and answering questions pertaining to financial knowledge. Results indicated that Older participants significantly outperformed Younger participants on a multiple-choice test of acquired financial knowledge. However, after controlling for such pre-existing knowledge, several age effects were observed. For example, Older participants were more likely to make immediate investment decisions, whereas Younger participants exhibited a preference for delaying decision-making pending additional information. Older participants also rated themselves as more concerned with avoiding monetary loss (i.e., a prevention orientation), whereas Younger participants reported greater interest in financial gain (i.e., a promotion orientation). In terms of sex differences, Older Males were more likely to pay credit card bills and utilize savings accounts than were Older Females. Multiple positive correlations were observed between Older participants’ financial decision-making ability and performance on neuropsychological measures of non-verbal intellect and executive functioning. Lastly, the ability to justify one’s financial decisions declined with age, among the Older participants. Several of the aforementioned results parallel findings from the medical decision-making literature, suggesting that older adults make decisions in a manner that conserves diminishing cognitive resources. PMID:22715322

Command and Compensation in a Neuromodulatory Decision Network

PubMed Central

Luan, Haojiang; Diao, Fengqiu; Peabody, Nathan C.; White, Benjamin H.

2012-01-01

The neural circuits that mediate behavioral choices must not only weigh internal demands and environmental circumstances, but also select and implement specific actions, including associated visceral or neuroendocrine functions. Coordinating these multiple processes suggests considerable complexity. As a consequence, even circuits that support simple behavioral decisions remain poorly understood. Here we show that the environmentally-sensitive wing expansion decision of adult fruit flies is coordinated by a single pair of neuromodulatory neurons with command-like function. Targeted suppression of these neurons using the Split Gal4 system abrogates the fly's ability to expand its wings in the face of environmental challenges, while stimulating them forces expansion by coordinately activating both motor and neuroendocrine outputs. The arbitration and implementation of the wing expansion decision by this neuronal pair may illustrate a general strategy by which neuromodulatory neurons orchestrate behavior. Interestingly, the decision network shows a behavioral plasticity that is unmasked under conducive environmental conditions in flies lacking the function of the command-like neuromodulatory neurons. Such flies can often expand their wings using a motor program distinct from that of wildtype animals and controls. This compensatory program may be the vestige of an ancestral, environmentally-insensitive program used for wing expansion that existed prior to the evolution of the environmentally-adaptive program currently used by Drosophila and other cyclorrhaphan flies. PMID:22262886

Analytical group decision making in natural resources: methodology and application

Treesearch

Daniel L. Schmoldt; David L. Peterson

2000-01-01

Group decision making is becoming increasingly important in natural resource management and associated scientific applications, because multiple values are treated coincidentally in time and space, multiple resource specialists are needed, and multiple stakeholders must be included in the decision process. Decades of social science research on decision making in groups...

A multi-valued neutrosophic qualitative flexible approach based on likelihood for multi-criteria decision-making problems

NASA Astrophysics Data System (ADS)

Peng, Juan-juan; Wang, Jian-qiang; Yang, Wu-E.

2017-01-01

In this paper, multi-criteria decision-making (MCDM) problems based on the qualitative flexible multiple criteria method (QUALIFLEX), in which the criteria values are expressed by multi-valued neutrosophic information, are investigated. First, multi-valued neutrosophic sets (MVNSs), which allow the truth-membership function, indeterminacy-membership function and falsity-membership function to have a set of crisp values between zero and one, are introduced. Then the likelihood of multi-valued neutrosophic number (MVNN) preference relations is defined and the corresponding properties are also discussed. Finally, an extended QUALIFLEX approach based on likelihood is explored to solve MCDM problems where the assessments of alternatives are in the form of MVNNs; furthermore an example is provided to illustrate the application of the proposed method, together with a comparison analysis.

Incentives for Optimal Multi-level Allocation of HIV Prevention Resources

PubMed Central

Malvankar, Monali M.; Zaric, Gregory S.

2013-01-01

HIV/AIDS prevention funds are often allocated at multiple levels of decision-making. Optimal allocation of HIV prevention funds maximizes the number of HIV infections averted. However, decision makers often allocate using simple heuristics such as proportional allocation. We evaluate the impact of using incentives to encourage optimal allocation in a two-level decision-making process. We model an incentive based decision-making process consisting of an upper-level decision maker allocating funds to a single lower-level decision maker who then distributes funds to local programs. We assume that the lower-level utility function is linear in the amount of the budget received from the upper-level, the fraction of funds reserved for proportional allocation, and the number of infections averted. We assume that the upper level objective is to maximize the number of infections averted. We illustrate with an example using data from California, U.S. PMID:23766551

Surgical Versus Conservative Intervention for Acute Achilles Tendon Rupture: A PRISMA-Compliant Systematic Review of Overlapping Meta-Analyses.

PubMed

Zhang, Hao; Tang, Hao; He, Qianyun; Wei, Qiang; Tong, Dake; Wang, Chuangfeng; Wu, Dajiang; Wang, Guangchao; Zhang, Xin; Ding, Wenbin; Li, Di; Ding, Chen; Liu, Kang; Ji, Fang

2015-11-01

Although many meta-analyses comparing surgical intervention with conservative treatment have been conducted for acute Achilles tendon rupture, discordant conclusions are shown. This study systematically reviewed the overlapping meta-analyses relating to surgical versus conservative intervention of acute Achilles tendon rupture to assist decision makers select among conflicting meta-analyses, and to offer intervention recommendations based on the currently best evidence.Multiple databases were comprehensively searched for meta-analyses comparing surgical with conservative treatment of acute Achilles tendon rupture. Meta-analyses only comprising randomized controlled trials (RCTs) were included. Two authors independently evaluated the meta-analysis quality and extracted data. The Jadad decision algorithm was applied to ascertain which meta-analysis offered the best evidence.A total of 9 meta-analyses were included. Only RCTs were determined as Level-II evidence. The scores of Assessment of Multiple Systematic Reviews (AMSTAR) ranged from 5 to 10 (median 7). A high-quality meta-analysis with more RCTs was selected according to the Jadad decision algorithm. This study found that when functional rehabilitation was used, conservative intervention was equal to surgical treatment regarding the incidence of rerupture, range of motion, calf circumference, and functional outcomes, while reducing the incidence of other complications. Where functional rehabilitation was not performed, conservative intervention could significantly increase rerupture rate.Conservative intervention may be preferred for acute Achilles tendon rupture at centers offering functional rehabilitation, because it shows a similar rerupture rate with a lower risk of other complications when compared with surgical treatment. However, surgical treatment should be considered at centers without functional rehabilitation as this can reduce the incidence of rerupture.

MatLab Script and Functional Programming

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali

2007-01-01

MatLab Script and Functional Programming: MatLab is one of the most widely used very high level programming languages for scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. The MatLab seminar covers the functional and script programming aspect of MatLab language. Specific expectations are: a) Recognize MatLab commands, script and function. b) Create, and run a MatLab function. c) Read, recognize, and describe MatLab syntax. d) Recognize decisions, loops and matrix operators. e) Evaluate scope among multiple files, and multiple functions within a file. f) Declare, define and use scalar variables, vectors and matrices.

Natural Resource Information System. Volume 1: Overall description

NASA Technical Reports Server (NTRS)

1972-01-01

A prototype computer-based Natural Resource Information System was designed which could store, process, and display data of maximum usefulness to land management decision making. The system includes graphic input and display, the use of remote sensing as a data source, and it is useful at multiple management levels. A survey established current decision making processes and functions, information requirements, and data collection and processing procedures. The applications of remote sensing data and processing requirements were established. Processing software was constructed and a data base established using high-altitude imagery and map coverage of selected areas of SE Arizona. Finally a demonstration of system processing functions was conducted utilizing material from the data base.

A Structured approach to incidental take decision making

USGS Publications Warehouse

McGowan, Conor P.

2013-01-01

Decision making related to incidental take of endangered species under U.S. law lends itself well to a structured decision making approach. Incidental take is the permitted killing, harming, or harassing of a protected species under the law as long as that harm is incidental to an otherwise lawful activity and does not “reduce appreciably the probability of survival and recovery in the wild.” There has been inconsistency in the process used for determining incidental take allowances across species and across time for the same species, and structured decision making has been proposed to improve decision making. I use an example decision analysis to demonstrate the process and its applicability to incidental take decisions, even under significant demographic uncertainty and multiple, competing objectives. I define the example problem, present an objectives statement and a value function, use a simulation model to assess the consequences of a set of management actions, and evaluate the tradeoffs among the different actions. The approach results in transparent and repeatable decisions.

Multiple attribute decision making model and application to food safety risk evaluation.

PubMed

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Practical Strategies for Integrating Final Ecosystem Goods and ...

EPA Pesticide Factsheets

The concept of Final Ecosystem Goods and Services (FEGS) explicitly connects ecosystem services to the people that benefit from them. This report presents a number of practical strategies for incorporating FEGS, and more broadly ecosystem services, into the decision-making process. Whether a decision process is in early or late stages, or whether a process includes informal or formal decision analysis, there are multiple points where ecosystem services concepts can be integrated. This report uses Structured Decision Making (SDM) as an organizing framework to illustrate the role ecosystem services can play in a values-focused decision-process, including: • Clarifying the decision context: Ecosystem services can help clarify the potential impacts of an issue on natural resources together with their spatial and temporal extent based on supply and delivery of those services, and help identify beneficiaries for inclusion as stakeholders in the deliberative process. • Defining objectives and performance measures: Ecosystem services may directly represent stakeholder objectives, or may be means toward achieving other objectives. • Creating alternatives: Ecosystem services can bring to light creative alternatives for achieving other social, economic, health, or general well-being objectives. • Estimating consequences: Ecosystem services assessments can implement ecological production functions (EPFs) and ecological benefits functions (EBFs) to link decision alt

Team Leadership and Cancer End-of-Life Decision Making.

PubMed

Waldfogel, Julie M; Battle, Dena J; Rosen, Michael; Knight, Louise; Saiki, Catherine B; Nesbit, Suzanne A; Cooper, Rhonda S; Browner, Ilene S; Hoofring, Laura H; Billing, Lynn S; Dy, Sydney M

2016-11-01

End-of-life decision making in cancer can be a complicated process. Patients and families encounter multiple providers throughout their cancer care. When the efforts of these providers are not well coordinated in teams, opportunities for high-quality, longitudinal goals of care discussions can be missed. This article reviews the case of a 55-year-old man with lung cancer, illustrating the barriers and missed opportunities for end-of-life decision making in his care through the lens of team leadership, a key principle in the science of teams. The challenges demonstrated in this case reflect the importance of the four functions of team leadership: information search and structuring, information use in problem solving, managing personnel resources, and managing material resources. Engaging in shared leadership of these four functions can help care providers improve their interactions with patients and families concerning end-of-life care decision making. This shared leadership can also produce a cohesive care plan that benefits from the expertise of the range of available providers while reflecting patient needs and preferences. Clinicians and researchers should consider the roles of team leadership functions and shared leadership in improving patient care when developing and studying models of cancer care delivery.

Progressive decline of decision-making performances during multiple sclerosis.

PubMed

Simioni, Samanta; Ruffieux, Christiane; Kleeberg, Joerg; Bruggimann, Laure; du Pasquier, Renaud A; Annoni, Jean-Marie; Schluep, Myriam

2009-03-01

The purpose of this study was to evaluate longitudinally, using the Iowa Gambling Task (IGT), the dynamics of decision-making capacity at a two-year interval (median: 2.1 years) in a group of patients with multiple sclerosis (MS) (n = 70) and minor neurological disability [Expanded Disability Status Scale (EDSS) < or = 2.5 at baseline]. Cognition (memory, executive functions, attention), behavior, handicap, and perceived health status were also investigated. Standardized change scores [(score at retest-score at baseline)/standard deviation of baseline score] were computed. Results showed that IGT performances decreased from baseline to retest (from 0.3, SD = 0.4 to 0.1, SD = 0.3, p = .005). MS patients who worsened in the IGT were more likely to show a decreased perceived health status and emotional well-being (SEP-59; p = .05 for both). Relapsing rate, disability progression, cognitive, and behavioral changes were not associated with decreased IGT performances. In conclusion, decline in decision making can appear as an isolated deficit in MS.

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.

Factors affecting self-regulatory driving practices among older adults.

PubMed

Molnar, Lisa J; Charlton, Judith L; Eby, David W; Langford, Jim; Koppel, Sjaan; Kolenic, Giselle E; Marshall, Shawn

2014-01-01

The primary objective of this study was to better understand how self-regulatory driving practices at multiple levels of driver decision making are influenced by various factors. Specifically, the study investigated patterns of tactical and strategic self-regulation among a sample of 246 Australian older drivers. Of special interest was the relative influence of several variables on the adoption of self-regulation, including self-perceptions of health, functioning, and abilities for safe driving and driving confidence and comfort. The research was carried out at the Monash University Accident Research Centre, as part of its Ozcandrive study, a partnership with the Canadian Driving Research Initiative for Vehicular Safety in the Elderly (Candrive), and in conjunction with the University of Michigan Transportation Research Institute (UMTRI). Candrive/Ozcandrive represents the first study to follow a large group of older drivers over several years and collect comprehensive self-reported and objectively derived data on health, functioning, and driving. This study used a subset of data from the Candrive/Ozcandrive study. Upon enrolling in the study, participants underwent a comprehensive clinical assessment during which data on visual, cognitive, and psychomotor functioning were collected. Approximately 4 months after study enrollment, participants completed the Advanced Driving Decisions and Patterns of Travel (ADDAPT) questionnaire, a computer-based self-regulation instrument developed and pilot-tested at UMTRI. Self-regulation among older adults was found to be a multidimensional concept. Rates of self-regulation were tied closely to specific driving situations, as well as level of decision making. In addition, self-regulatory practices at the strategic and tactical levels of decision making were influenced by different sets of factors. Continuing efforts to better understand the self-regulatory practices of older drivers at multiple levels of driver performance and decision making should provide important insights into how the transition from driving to nondriving can be better managed to balance the interdependent needs of public safety and personal mobility.

A Decision Analysis Perspective on Multiple Response Robust Optimization

DTIC Science & Technology

2012-03-01

the utility function in question is monotonically increasing and is twice differentiable . If γ(y) = 0, the utility function is describing risk neutral...twice differentiable , the risk aversion function with respect to a single attribute, yi, i = 1, . . . , n, is given in Equation 2.9, γUyi = − U ′′yi U...UV (V (y1, y2)) and fol- lowing the chain rule of differentiation , Matheson and Abbas [31] show that the risk aversion with respect to a single

A feedback control model for network flow with multiple pure time delays

NASA Technical Reports Server (NTRS)

Press, J.

1972-01-01

A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.

The amygdala and decision-making.

PubMed

Gupta, Rupa; Koscik, Timothy R; Bechara, Antoine; Tranel, Daniel

2011-03-01

Decision-making is a complex process that requires the orchestration of multiple neural systems. For example, decision-making is believed to involve areas of the brain involved in emotion (e.g., amygdala, ventromedial prefrontal cortex) and memory (e.g., hippocampus, dorsolateral prefrontal cortex). In this article, we will present findings related to the amygdala's role in decision-making, and differentiate the contributions of the amygdala from those of other structurally and functionally connected neural regions. Decades of research have shown that the amygdala is involved in associating a stimulus with its emotional value. This tradition has been extended in newer work, which has shown that the amygdala is especially important for decision-making, by triggering autonomic responses to emotional stimuli, including monetary reward and punishment. Patients with amygdala damage lack these autonomic responses to reward and punishment, and consequently, cannot utilize "somatic marker" type cues to guide future decision-making. Studies using laboratory decision-making tests have found deficient decision-making in patients with bilateral amygdala damage, which resembles their real-world difficulties with decision-making. Additionally, we have found evidence for an interaction between sex and laterality of amygdala functioning, such that unilateral damage to the right amygdala results in greater deficits in decision-making and social behavior in men, while left amygdala damage seems to be more detrimental for women. We have posited that the amygdala is part of an "impulsive," habit type system that triggers emotional responses to immediate outcomes. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Chen, Ting-Yu

2012-06-01

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

Planned versus actual outcomes as a result of animal feeding operation decisions for managing phosphorus.

PubMed

Cabot, Perry E; Nowak, Pete

2005-01-01

The paper explores how decisions made on animal feeding operations (AFOs) influence the management of manure and phosphorus. Variability among these decisions from operation to operation and from field to field can influence the validity of nutrient loss risk assessments. These assessments are based on assumptions that the decision outcomes regarding manure distribution will occur as they are planned. The discrepancy between planned versus actual outcomes in phosphorus management was explored on nine AFOs managing a contiguous set of 210 fields in south-central Wisconsin. A total of 2611 soil samples were collected and multiple interviews conducted to assign phosphorus index (PI) ratings to the fields. Spearman's rank correlation coefficients (r(S)) indicated that PI ratings were less sensitive to soil test phosphorus (STP) levels (r(S) = 0.378), universal soil loss equation (USLE) (r(S) = 0.261), ratings for chemical fertilizer application (r(S) = 0.185), and runoff class (r(S) = -0.089), and more sensitive to ratings for manure application (r(S) = 0.854). One-way ANOVA indicated that mean field STP levels were more homogenous than field PI ratings between AFOs. Kolmogorov-Smirnov (K-S) tests displayed several nonsignificant comparisons for cumulative distribution functions, S(x), of mean STP levels on AFO fields. On the other hand, the K-S tests of S(x) for PI ratings indicated that the majority of these S(x) functions were significantly different between AFOs at or greater than the 0.05 significance level. Interviews suggested multiple reasons for divergence between planned and actual outcomes in managing phosphorus, and that this divergence arises at the strategic, tactical, and operational levels of decision-making.

Impulsive Control for Continuous-Time Markov Decision Processes: A Linear Programming Approach

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

Dufour, F., E-mail: dufour@math.u-bordeaux1.fr; Piunovskiy, A. B., E-mail: piunov@liv.ac.uk

2016-08-15

In this paper, we investigate an optimization problem for continuous-time Markov decision processes with both impulsive and continuous controls. We consider the so-called constrained problem where the objective of the controller is to minimize a total expected discounted optimality criterion associated with a cost rate function while keeping other performance criteria of the same form, but associated with different cost rate functions, below some given bounds. Our model allows multiple impulses at the same time moment. The main objective of this work is to study the associated linear program defined on a space of measures including the occupation measures ofmore » the controlled process and to provide sufficient conditions to ensure the existence of an optimal control.« less

Internal Consistency and Cross-Informant Agreement of the Lithuanian-Translated Behavioral and Emotional Rating Scale

ERIC Educational Resources Information Center

Sointu, Erkko T.; Geležiniene, Renata; Lambert, Matthew C.; Nordness, Philip D.

2015-01-01

Educational professionals need assessments that yield psychometrically sound scores to assess students' behavioral and emotional functioning in order to guide data-driven decision-making processes. Rating scales have been found to be effective and economical, and often multiple informant perspectives can be obtained. The agreement between multiple…

Using Discrete Loss Functions and Weighted Kappa for Classification: An Illustration Based on Bayesian Network Analysis

ERIC Educational Resources Information Center

Zwick, Rebecca; Lenaburg, Lubella

2009-01-01

In certain data analyses (e.g., multiple discriminant analysis and multinomial log-linear modeling), classification decisions are made based on the estimated posterior probabilities that individuals belong to each of several distinct categories. In the Bayesian network literature, this type of classification is often accomplished by assigning…

Feasibility of neuro-morphic computing to emulate error-conflict based decision making.

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

Branch, Darren W.

2009-09-01

A key aspect of decision making is determining when errors or conflicts exist in information and knowing whether to continue or terminate an action. Understanding the error-conflict processing is crucial in order to emulate higher brain functions in hardware and software systems. Specific brain regions, most notably the anterior cingulate cortex (ACC) are known to respond to the presence of conflicts in information by assigning a value to an action. Essentially, this conflict signal triggers strategic adjustments in cognitive control, which serve to prevent further conflict. The most probable mechanism is the ACC reports and discriminates different types of feedback,more » both positive and negative, that relate to different adaptations. Unique cells called spindle neurons that are primarily found in the ACC (layer Vb) are known to be responsible for cognitive dissonance (disambiguation between alternatives). Thus, the ACC through a specific set of cells likely plays a central role in the ability of humans to make difficult decisions and solve challenging problems in the midst of conflicting information. In addition to dealing with cognitive dissonance, decision making in high consequence scenarios also relies on the integration of multiple sets of information (sensory, reward, emotion, etc.). Thus, a second area of interest for this proposal lies in the corticostriatal networks that serve as an integration region for multiple cognitive inputs. In order to engineer neurological decision making processes in silicon devices, we will determine the key cells, inputs, and outputs of conflict/error detection in the ACC region. The second goal is understand in vitro models of corticostriatal networks and the impact of physical deficits on decision making, specifically in stressful scenarios with conflicting streams of data from multiple inputs. We will elucidate the mechanisms of cognitive data integration in order to implement a future corticostriatal-like network in silicon devices for improved decision processing.« less

Successful choice behavior is associated with distinct and coherent network states in anterior cingulate cortex

PubMed Central

Lapish, Christopher C.; Durstewitz, Daniel; Chandler, L. Judson; Seamans, Jeremy K.

2008-01-01

Successful decision making requires an ability to monitor contexts, actions, and outcomes. The anterior cingulate cortex (ACC) is thought to be critical for these functions, monitoring and guiding decisions especially in challenging situations involving conflict and errors. A number of different single-unit correlates have been observed in the ACC that reflect the diverse cognitive components involved. Yet how ACC neurons function as an integrated network is poorly understood. Here we show, using advanced population analysis of multiple single-unit recordings from the rat ACC during performance of an ecologically valid decision-making task, that ensembles of neurons move through different coherent and dissociable states as the cognitive requirements of the task change. This organization into distinct network patterns with respect to both firing-rate changes and correlations among units broke down during trials with numerous behavioral errors, especially at choice points of the task. These results point to an underlying functional organization into cell assemblies in the ACC that may monitor choices, outcomes, and task contexts, thus tracking the animal's progression through “task space.” PMID:18708525

A study of an arbiter function in the structures of a shared bus

NASA Astrophysics Data System (ADS)

Seck, J.-P.

The results of a comparative study of synchronous and asynchronous arbiters for managing user access to a shared bus is presented. The best available method is determined to be modular arbiter structures attached only to the decision module. Linear and circular arbitration strategies are examined for suitability for automatic decision-making. A multiple strategies arbiter scheme is devised, involving the superposition of various strategies of one sequential machine into another. It is then possible to modify the strategy on-line if the current strategy is ineffective. The utilization of a multiple structure of cascading arbiter devices is noted to be effective if response time is not a critical matter. Finally, attention is given to automatic circuit testing and fault detection. An example is furnished in terms of a management system for a shared memory in a multimicroprocessor structure.

Managing Multiplicity: Conceptualizing Physician Cognition in Multipatient Environments.

PubMed

Chan, Teresa M; Mercuri, Mathew; Van Dewark, Kenneth; Sherbino, Jonathan; Schwartz, Alan; Norman, Geoff; Lineberry, Matthew

2018-05-01

Emergency physicians (EPs) regularly manage multiple patients simultaneously, often making time-sensitive decisions around priorities for multiple patients. Few studies have explored physician cognition in multipatient scenarios. The authors sought to develop a conceptual framework to describe how EPs think in busy, multipatient environments. From July 2014 to May 2015, a qualitative study was conducted at McMaster University, using a think-aloud protocol to examine how 10 attending EPs and 10 junior residents made decisions in multipatient environments. Participants engaged in the think-aloud exercise for five different simulated multipatient scenarios. Transcripts from recorded interviews were analyzed inductively, with an iterative process involving two independent coders, and compared between attendings and residents. The attending EPs and junior residents used similar processes to prioritize patients in these multipatient scenarios. The think-aloud processes demonstrated a similar process used by almost all participants. The cognitive task of patient prioritization consisted of three components: a brief overview of the entire cohort of patients to determine a general strategy; an individual chart review, whereby the participant created a functional patient story from information available in a file (i.e., vitals, brief clinical history); and creation of a relative priority list. Compared with residents, the attendings were better able to construct deeper and more complex patient stories. The authors propose a conceptual framework for how EPs prioritize care for multiple patients in complex environments. This study may be useful to teachers who train physicians to function more efficiently in busy clinical environments.

Dempster-Shafer theory applied to regulatory decision process for selecting safer alternatives to toxic chemicals in consumer products.

PubMed

Park, Sung Jin; Ogunseitan, Oladele A; Lejano, Raul P

2014-01-01

Regulatory agencies often face a dilemma when regulating chemicals in consumer products-namely, that of making decisions in the face of multiple, and sometimes conflicting, lines of evidence. We present an integrative approach for dealing with uncertainty and multiple pieces of evidence in toxics regulation. The integrative risk analytic framework is grounded in the Dempster-Shafer (D-S) theory that allows the analyst to combine multiple pieces of evidence and judgments from independent sources of information. We apply the integrative approach to the comparative risk assessment of bisphenol-A (BPA)-based polycarbonate and the functionally equivalent alternative, Eastman Tritan copolyester (ETC). Our results show that according to cumulative empirical evidence, the estimated probability of toxicity of BPA is 0.034, whereas the toxicity probability for ETC is 0.097. However, when we combine extant evidence with strength of confidence in the source (or expert judgment), we are guided by a richer interval measure, (Bel(t), Pl(t)). With the D-S derived measure, we arrive at various intervals for BPA, with the low-range estimate at (0.034, 0.250), and (0.097,0.688) for ETC. These new measures allow a reasonable basis for comparison and a justifiable procedure for decision making that takes advantage of multiple sources of evidence. Through the application of D-S theory to toxicity risk assessment, we show how a multiplicity of scientific evidence can be converted into a unified risk estimate, and how this information can be effectively used for comparative assessments to select potentially less toxic alternative chemicals. © 2013 SETAC.

Big data and high-performance analytics in structural health monitoring for bridge management

NASA Astrophysics Data System (ADS)

Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed

2016-04-01

Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.

Towards ethical decision support and knowledge management in neonatal intensive care.

PubMed

Yang, L; Frize, M; Eng, P; Walker, R; Catley, C

2004-01-01

Recent studies in neonatal medicine, clinical nursing, and cognitive psychology have indicated the need to augment current decision-making practice in neonatal intensive care units with computerized, intelligent decision support systems. Rapid progress in artificial intelligence and knowledge management facilitates the design of collaborative ethical decision-support tools that allow clinicians to provide better support for parents facing inherently difficult choices, such as when to withdraw aggressive treatment. The appropriateness of using computers to support ethical decision-making is critically analyzed through research and literature review. In ethical dilemmas, multiple diverse participants need to communicate and function as a team to select the best treatment plan. In order to do this, physicians require reliable estimations of prognosis, while parents need a highly useable tool to help them assimilate complex medical issues and address their own value system. Our goal is to improve and structuralize the ethical decision-making that has become an inevitable part of modern neonatal care units. The paper contributes to clinical decision support by outlining the needs and basis for ethical decision support and justifying the proposed development efforts.

Incorporating ecosystem function concept in environmental planning and decision making by means of multi-criteria evaluation: the case-study of Kalloni, Lesbos, Greece.

PubMed

Oikonomou, Vera; Dimitrakopoulos, Panayiotis G; Troumbis, Andreas Y

2011-01-01

Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.

Incorporating Ecosystem Function Concept in Environmental Planning and Decision Making by Means of Multi-Criteria Evaluation: The Case-Study of Kalloni, Lesbos, Greece

NASA Astrophysics Data System (ADS)

Oikonomou, Vera; Dimitrakopoulos, Panayiotis G.; Troumbis, Andreas Y.

2011-01-01

Nature provides life-support services which do not merely constitute the basis for ecosystem integrity but also benefit human societies. The importance of such multiple outputs is often ignored or underestimated in environmental planning and decision making. The economic valuation of ecosystem functions or services has been widely used to make these benefits economically visible and thus address this deficiency. Alternatively, the relative importance of the components of ecosystem value can be identified and compared by means of multi-criteria evaluation. Hereupon, this article proposes a conceptual framework that couples ecosystem function analysis, multi criteria evaluation and social research methodologies for introducing an ecosystem function-based planning and management approach. The framework consists of five steps providing the structure of a participative decision making process which is then tested and ratified, by applying the discrete multi-criteria method NAIADE, in the Kalloni Natura 2000 site, on Lesbos, Greece. Three scenarios were developed and evaluated with regard to their impacts on the different types of ecosystem functions and the social actors' value judgements. A conflict analysis permitted the better elaboration of the different views, outlining the coalitions formed in the local community and shaping the way towards reaching a consensus.

Recursive feature elimination for biomarker discovery in resting-state functional connectivity.

PubMed

Ravishankar, Hariharan; Madhavan, Radhika; Mullick, Rakesh; Shetty, Teena; Marinelli, Luca; Joel, Suresh E

2016-08-01

Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensionality of images, inter-subject and intra-subject variability and small numbers of subjects compared to the number of derived features. Traditional univariate analysis suffers from the problem of multiple comparisons. Here, we adopt an alternative data-driven method for identifying population differences in functional connectivity. We propose a machine-learning approach to down-select functional connectivity features associated with symptom severity in mild traumatic brain injury (mTBI). Using this approach, we identified functional regions with altered connectivity in mTBI. including the executive control, visual and precuneus networks. We compared functional connections at multiple resolutions to determine which scale would be more sensitive to changes related to patient recovery. These modular network-level features can be used as diagnostic tools for predicting disease severity and recovery profiles.

Regional resources buffer the impact of functional limitations on perceived autonomy in older adults with multiple illnesses.

PubMed

Schüz, Benjamin; Westland, Josh N; Wurm, Susanne; Tesch-Römer, Clemens; Wolff, Julia K; Warner, Lisa M; Schwarzer, Ralf

2016-03-01

Retaining perceptions of autonomy is a key component of successful aging. Perceived autonomy refers to the capacity to make and enact self-directed decisions. These perceptions are often threatened in older adults with multiple illnesses, when functional limitations resulting from these illnesses impede the enactment of self-directed decisions. Regional resources (in Germany specifically at the level of administrative districts) might counteract these impediments of autonomy. Economically stronger districts can provide more-concrete support resources for older adults, buffering the negative effect of functional limitations on self-perceived autonomy. This study assessed participants aged over 65 with 2 or more chronic conditions. In total, N = 287 provided data (Mage = 73.3, SD = 5.07), and n = 97 were women. Gross domestic product (GDP) per capita was used as a proxy measure of administrative district wealth in Germany. Hierarchical multilevel regression analyses with cross-level interactions were conducted. Results suggest that the detrimental effect of functional limitations on perceived autonomy is less pronounced for participants residing in higher GDP districts. Conversely, for participants in lower GDP districts, the effect is exacerbated. This finding suggests that districts with greater financial resources might be better able to invest in supports that promote and facilitate autonomy and, thus, provide a buffer against threats to individual perceived autonomy. (c) 2016 APA, all rights reserved).

Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Thokala, Praveen; Devlin, Nancy; Marsh, Kevin; Baltussen, Rob; Boysen, Meindert; Kalo, Zoltan; Longrenn, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Ijzerman, Maarten

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients' access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making. Copyright © 2016. Published by Elsevier Inc.

Integrating Decision Tree and Hidden Markov Model (HMM) for Subtype Prediction of Human Influenza A Virus

NASA Astrophysics Data System (ADS)

Attaluri, Pavan K.; Chen, Zhengxin; Weerakoon, Aruna M.; Lu, Guoqing

Multiple criteria decision making (MCDM) has significant impact in bioinformatics. In the research reported here, we explore the integration of decision tree (DT) and Hidden Markov Model (HMM) for subtype prediction of human influenza A virus. Infection with influenza viruses continues to be an important public health problem. Viral strains of subtype H3N2 and H1N1 circulates in humans at least twice annually. The subtype detection depends mainly on the antigenic assay, which is time-consuming and not fully accurate. We have developed a Web system for accurate subtype detection of human influenza virus sequences. The preliminary experiment showed that this system is easy-to-use and powerful in identifying human influenza subtypes. Our next step is to examine the informative positions at the protein level and extend its current functionality to detect more subtypes. The web functions can be accessed at http://glee.ist.unomaha.edu/.

Interpretable Decision Sets: A Joint Framework for Description and Prediction

PubMed Central

Lakkaraju, Himabindu; Bach, Stephen H.; Jure, Leskovec

2016-01-01

One of the most important obstacles to deploying predictive models is the fact that humans do not understand and trust them. Knowing which variables are important in a model’s prediction and how they are combined can be very powerful in helping people understand and trust automatic decision making systems. Here we propose interpretable decision sets, a framework for building predictive models that are highly accurate, yet also highly interpretable. Decision sets are sets of independent if-then rules. Because each rule can be applied independently, decision sets are simple, concise, and easily interpretable. We formalize decision set learning through an objective function that simultaneously optimizes accuracy and interpretability of the rules. In particular, our approach learns short, accurate, and non-overlapping rules that cover the whole feature space and pay attention to small but important classes. Moreover, we prove that our objective is a non-monotone submodular function, which we efficiently optimize to find a near-optimal set of rules. Experiments show that interpretable decision sets are as accurate at classification as state-of-the-art machine learning techniques. They are also three times smaller on average than rule-based models learned by other methods. Finally, results of a user study show that people are able to answer multiple-choice questions about the decision boundaries of interpretable decision sets and write descriptions of classes based on them faster and more accurately than with other rule-based models that were designed for interpretability. Overall, our framework provides a new approach to interpretable machine learning that balances accuracy, interpretability, and computational efficiency. PMID:27853627

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review.

PubMed

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh; Sadiq, Rehan

2015-01-01

Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, and finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Distinct Roles of Dopamine and Subthalamic Nucleus in Learning and Probabilistic Decision Making

ERIC Educational Resources Information Center

Coulthard, Elizabeth J.; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K.; Murphy, Gillian; Keeley, Sophie; Whone, Alan L.

2012-01-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making…

Interfacing to the brain’s motor decisions

PubMed Central

2017-01-01

It has been long known that neural activity, recorded with electrophysiological methods, contains rich information about a subject’s motor intentions, sensory experiences, allocation of attention, action planning, and even abstract thoughts. All these functions have been the subject of neurophysiological investigations, with the goal of understanding how neuronal activity represents behavioral parameters, sensory inputs, and cognitive functions. The field of brain-machine interfaces (BMIs) strives for a somewhat different goal: it endeavors to extract information from neural modulations to create a communication link between the brain and external devices. Although many remarkable successes have been already achieved in the BMI field, questions remain regarding the possibility of decoding high-order neural representations, such as decision making. Could BMIs be employed to decode the neural representations of decisions underlying goal-directed actions? In this review we lay out a framework that describes the computations underlying goal-directed actions as a multistep process performed by multiple cortical and subcortical areas. We then discuss how BMIs could connect to different decision-making steps and decode the neural processing ongoing before movements are initiated. Such decision-making BMIs could operate as a system with prediction that offers many advantages, such as shorter reaction time, better error processing, and improved unsupervised learning. To present the current state of the art, we review several recent BMIs incorporating decision-making components. PMID:28003406

Nurse-led immunotreatment DEcision Coaching In people with Multiple Sclerosis (DECIMS) - Feasibility testing, pilot randomised controlled trial and mixed methods process evaluation.

PubMed

Rahn, A C; Köpke, S; Backhus, I; Kasper, J; Anger, K; Untiedt, B; Alegiani, A; Kleiter, I; Mühlhauser, I; Heesen, C

2018-02-01

Treatment decision-making is complex for people with multiple sclerosis. Profound information on available options is virtually not possible in regular neurologist encounters. The "nurse decision coach model" was developed to redistribute health professionals' tasks in supporting immunotreatment decision-making following the principles of informed shared decision-making. To test the feasibility of a decision coaching programme and recruitment strategies to inform the main trial. Feasibility testing and parallel pilot randomised controlled trial, accompanied by a mixed methods process evaluation. Two German multiple sclerosis university centres. People with suspected or relapsing-remitting multiple sclerosis facing immunotreatment decisions on first line drugs were recruited. Randomisation to the intervention (n = 38) or control group (n = 35) was performed on a daily basis. Quantitative and qualitative process data were collected from people with multiple sclerosis, nurses and physicians. We report on the development and piloting of the decision coaching programme. It comprises a training course for multiple sclerosis nurses and the coaching intervention. The intervention consists of up to three structured nurse-led decision coaching sessions, access to an evidence-based online information platform (DECIMS-Wiki) and a final physician consultation. After feasibility testing, a pilot randomised controlled trial was performed. People with multiple sclerosis were randomised to the intervention or control group. The latter had also access to the DECIMS-Wiki, but received otherwise care as usual. Nurses were not blinded to group assignment, while people with multiple sclerosis and physicians were. The primary outcome was 'informed choice' after six months including the sub-dimensions' risk knowledge (after 14 days), attitude concerning immunotreatment (after physician consultation), and treatment uptake (after six months). Quantitative process evaluation data were collected via questionnaires. Qualitative interviews were performed with all nurses and a convenience sample of nine people with multiple sclerosis. 116 people with multiple sclerosis fulfilled the inclusion criteria and 73 (63%) were included. Groups were comparable at baseline. Data of 51 people with multiple sclerosis (70%) were available for the primary endpoint. In the intervention group 15 of 31 (48%) people with multiple sclerosis achieved an informed choice after six months and 6 of 20 (30%) in the control group. Process evaluation data illustrated a positive response towards the coaching programme as well as good acceptance. The pilot-phase showed promising results concerning acceptability and feasibility of the intervention, which was well perceived by people with multiple sclerosis, most nurses and physicians. Delegating parts of the immunotreatment decision-making process to trained nurses has the potential to increase informed choice and participation as well as effectiveness of patient-physician consultations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Paediatricians' decision making about prescribing stimulant medications for children with attention-deficit/hyperactivity disorder.

PubMed

Chow, S-J; Sciberras, E; Gillam, L H; Green, J; Efron, D

2014-05-01

Attention-deficit/hyperactivity disorder (ADHD) is now the most common reason for a child to present to a paediatrician in Australia. Stimulant medications are commonly prescribed for children with ADHD, to reduce symptoms and improve function. In this study we investigated the factors that influence paediatricians' decisions about prescribing stimulant medications. In-depth, semi-structured interviews were conducted with paediatricians (n = 13) who were purposively recruited so as to sample a broad demographic of paediatricians working in diverse clinical settings. Paediatricians were recruited from public outpatient and private paediatrician clinics in Victoria, Australia. The interviews were audio-recorded and transcribed verbatim for thematic analysis. Paediatricians also completed a questionnaire describing their demographic and practice characteristics. Our findings showed that the decision to prescribe is a dynamic process involving two key domains: (1) weighing up clinical factors; and (2) interacting with parents and the patient along the journey to prescribing. Five themes relating to this process emerged from data analysis: comprehensive assessments that include history, examination and information from others; influencing factors such as functional impairment and social inclusion; previous success; facilitating parental understanding including addressing myths and parental confusion; and decision-making model. Paediatricians' decisions to prescribe stimulant medications are influenced by multiple factors that operate concurrently and interdependently. Paediatricians do not make decisions about prescribing in isolation; rather, they actively involve parents, teachers and patients, to arrive at a collective, well-informed decision. © 2013 John Wiley & Sons Ltd.

[Decision making and executive function in severe traumatic brain injured patients: validation of a decision-making task and correlated features].

PubMed

Wiederkehr, S; Barat, M; Dehail, P; de Sèze, M; Lozes-Boudillon, S; Giroire, J-M

2005-02-01

At the chronic stage, severe traumatic brain injured (TBI) patients experience difficulty in making decisions. Several studies have demonstrated the involvement of the prefrontal cortex, in particular the orbitofrontal region, in decision-making. The aim of the present study was to validate a decision-making task in this population and to ascertain whether the components of their dysexecutive syndrome may affect their decision-making and lead to difficulties for social rehabilitation. Fifteen TBI patients and 15 controlled subjects matched for age, sex and years of education were assessed by a battery of executive tests (GREFEX) and by the gambling task (GT). The TBI subjects performed significantly worse than the controlled group in five out of six GREFEX tests. The TBI choices are significantly more disadvantageous than the choices of the control group when considering the three last blocks of 20 cards of the GT. The GT total score correlated significantly with execution time of the Stroop interference condition and the Trail Making Task B, as well as with the two measures (correct sequence span and number of crossed boxes) of the double condition of Baddeley's task. We postulate that executive functioning (supervisory attentional system) influence performance in the gambling task through mechanisms of inhibitory control, divided attention and working memory. Thus, this task seems to be determined by multiple factors; the process of decision-making may depend on frontal integrity.

Reward modulates the effect of visual cortical microstimulation on perceptual decisions

PubMed Central

Cicmil, Nela; Cumming, Bruce G; Parker, Andrew J; Krug, Kristine

2015-01-01

Effective perceptual decisions rely upon combining sensory information with knowledge of the rewards available for different choices. However, it is not known where reward signals interact with the multiple stages of the perceptual decision-making pathway and by what mechanisms this may occur. We combined electrical microstimulation of functionally specific groups of neurons in visual area V5/MT with performance-contingent reward manipulation, while monkeys performed a visual discrimination task. Microstimulation was less effective in shifting perceptual choices towards the stimulus preferences of the stimulated neurons when available reward was larger. Psychophysical control experiments showed this result was not explained by a selective change in response strategy on microstimulated trials. A bounded accumulation decision model, applied to analyse behavioural performance, revealed that the interaction of expected reward with microstimulation can be explained if expected reward modulates a sensory representation stage of perceptual decision-making, in addition to the better-known effects at the integration stage. DOI: http://dx.doi.org/10.7554/eLife.07832.001 PMID:26402458

Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

A multimedia electronic patient record (ePR) system to improve decision support in pre- and rehabilitation through clinical and movement analysis

NASA Astrophysics Data System (ADS)

Liu, Brent; Documet, Jorge; McNitt-Gray, Sarah; Requejo, Phil; McNitt-Gray, Jill

2011-03-01

Clinical decisions for improving motor function in patients both with disability as well as improving an athlete's performance are made through clinical and movement analysis. Currently, this analysis facilitates identifying abnormalities in a patient's motor function for a large amount of neuro-musculoskeletal pathologies. However definitively identifying the underlying cause or long-term consequences of a specific abnormality in the patient's movement pattern is difficult since this requires information from multiple sources and formats across different times and currently relies on the experience and intuition of the expert clinician. In addition, this data must be persistent for longitudinal outcomes studies. Therefore a multimedia ePR system integrating imaging informatics data could have a significant impact on decision support within this clinical workflow. We present the design and architecture of such an ePR system as well as the data types that need integration in order to develop relevant decision support tools. Specifically, we will present two data model examples: 1) A performance improvement project involving volleyball athletes and 2) Wheelchair propulsion evaluation of patients with disabilities. The end result is a new frontier area of imaging informatics research within rehabilitation engineering and biomechanics.

Effects of automation of information-processing functions on teamwork.

PubMed

Wright, Melanie C; Kaber, David B

2005-01-01

We investigated the effects of automation as applied to different stages of information processing on team performance in a complex decision-making task. Forty teams of 2 individuals performed a simulated Theater Defense Task. Four automation conditions were simulated with computer assistance applied to realistic combinations of information acquisition, information analysis, and decision selection functions across two levels of task difficulty. Multiple measures of team effectiveness and team coordination were used. Results indicated different forms of automation have different effects on teamwork. Compared with a baseline condition, an increase in automation of information acquisition led to an increase in the ratio of information transferred to information requested; an increase in automation of information analysis resulted in higher team coordination ratings; and automation of decision selection led to better team effectiveness under low levels of task difficulty but at the cost of higher workload. The results support the use of early and intermediate forms of automation related to acquisition and analysis of information in the design of team tasks. Decision-making automation may provide benefits in more limited contexts. Applications of this research include the design and evaluation of automation in team environments.

Improved CLARAty Functional-Layer/Decision-Layer Interface

NASA Technical Reports Server (NTRS)

Estlin, Tara; Rabideau, Gregg; Gaines, Daniel; Johnston, Mark; Chouinard, Caroline; Nessnas, Issa; Shu, I-Hsiang

2008-01-01

Improved interface software for communication between the CLARAty Decision and Functional layers has been developed. [The Coupled Layer Architecture for Robotics Autonomy (CLARAty) was described in Coupled-Layer Robotics Architecture for Autonomy (NPO-21218), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48. To recapitulate: the CLARAty architecture was developed to improve the modularity of robotic software while tightening coupling between planning/execution and basic control subsystems. Whereas prior robotic software architectures typically contained three layers, the CLARAty contains two layers: a decision layer (DL) and a functional layer (FL).] Types of communication supported by the present software include sending commands from DL modules to FL modules and sending data updates from FL modules to DL modules. The present software supplants prior interface software that had little error-checking capability, supported data parameters in string form only, supported commanding at only one level of the FL, and supported only limited updates of the state of the robot. The present software offers strong error checking, and supports complex data structures and commanding at multiple levels of the FL, and relative to the prior software, offers a much wider spectrum of state-update capabilities.

Battling Arrow's Paradox to Discover Robust Water Management Alternatives

NASA Astrophysics Data System (ADS)

Kasprzyk, J. R.; Reed, P. M.; Hadka, D.

2013-12-01

This study explores whether or not Arrow's Impossibility Theorem, a theory of social choice, affects the formulation of water resources systems planning problems. The theorem discusses creating an aggregation function for voters choosing from more than three alternatives for society. The Impossibility Theorem is also called Arrow's Paradox, because when trying to add more voters, a single individual's preference will dictate the optimal group decision. In the context of water resources planning, our study is motivated by recent theoretical work that has generalized the insights for Arrow's Paradox to the design of complex engineered systems. In this framing of the paradox, states of society are equivalent to water planning or design alternatives, and the voters are equivalent to multiple planning objectives (e.g. minimizing cost or maximizing performance). Seen from this point of view, multi-objective water planning problems are functionally equivalent to the social choice problem described above. Traditional solutions to such multi-objective problems aggregate multiple performance measures into a single mathematical objective. The Theorem implies that a subset of performance concerns will inadvertently dictate the overall design evaluations in unpredictable ways using such an aggregation. We suggest that instead of aggregation, an explicit many-objective approach to water planning can help overcome the challenges posed by Arrow's Paradox. Many-objective planning explicitly disaggregates measures of performance while supporting the discovery of the planning tradeoffs, employing multiobjective evolutionary algorithms (MOEAs) to find solutions. Using MOEA-based search to address Arrow's Paradox requires that the MOEAs perform robustly with increasing problem complexity, such as adding additional objectives and/or decisions. This study uses comprehensive diagnostic evaluation of MOEA search performance across multiple problem formulations (both aggregated and many-objective) to show whether or not aggregating performance measures biases decision making. In this study, we explore this hypothesis using an urban water portfolio management case study in the Lower Rio Grande Valley. The diagnostic analysis shows that modern self-adaptive MOEA search is efficient, effective, and reliable for the more complex many-objective LRGV planning formulations. Results indicate that although many classical water systems planning frameworks seek to account for multiple objectives, the common practice of reducing the problem into one or more highly aggregated performance measures can severely and negatively bias planning decisions.

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

Dynamic afferent synapses to decision-making networks improve performance in tasks requiring stimulus associations and discriminations

PubMed Central

Bourjaily, Mark A.

2012-01-01

Animals must often make opposing responses to similar complex stimuli. Multiple sensory inputs from such stimuli combine to produce stimulus-specific patterns of neural activity. It is the differences between these activity patterns, even when small, that provide the basis for any differences in behavioral response. In the present study, we investigate three tasks with differing degrees of overlap in the inputs, each with just two response possibilities. We simulate behavioral output via winner-takes-all activity in one of two pools of neurons forming a biologically based decision-making layer. The decision-making layer receives inputs either in a direct stimulus-dependent manner or via an intervening recurrent network of neurons that form the associative layer, whose activity helps distinguish the stimuli of each task. We show that synaptic facilitation of synapses to the decision-making layer improves performance in these tasks, robustly increasing accuracy and speed of responses across multiple configurations of network inputs. Conversely, we find that synaptic depression worsens performance. In a linearly nonseparable task with exclusive-or logic, the benefit of synaptic facilitation lies in its superlinear transmission: effective synaptic strength increases with presynaptic firing rate, which enhances the already present superlinearity of presynaptic firing rate as a function of stimulus-dependent input. In linearly separable single-stimulus discrimination tasks, we find that facilitating synapses are always beneficial because synaptic facilitation always enhances any differences between inputs. Thus we predict that for optimal decision-making accuracy and speed, synapses from sensory or associative areas to decision-making or premotor areas should be facilitating. PMID:22457467

Multiple stakeholders in multi-criteria decision-making in the context of Municipal Solid Waste Management: A review

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

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh

2015-01-15

Highlights: • We review Municipal Solid Waste Management studies with focus on multiple stakeholders. • We focus on studies with multi-criteria decision analysis methods and discover their trends. • Most studies do not offer solutions for situations where stakeholders compete for more benefits or have unequal voting powers. • Governments and experts are the most participated stakeholders and AHP is the most dominant method. - Abstract: Municipal Solid Waste Management (MSWM) is a complicated process that involves multiple environmental and socio-economic criteria. Decision-makers look for decision support frameworks that can guide in defining alternatives, relevant criteria and their weights, andmore » finding a suitable solution. In addition, decision-making in MSWM problems such as finding proper waste treatment locations or strategies often requires multiple stakeholders such as government, municipalities, industries, experts, and/or general public to get involved. Multi-criteria Decision Analysis (MCDA) is the most popular framework employed in previous studies on MSWM; MCDA methods help multiple stakeholders evaluate the often conflicting criteria, communicate their different preferences, and rank or prioritize MSWM strategies to finally agree on some elements of these strategies and make an applicable decision. This paper reviews and brings together research on the application of MCDA for solving MSWM problems with more focus on the studies that have considered multiple stakeholders and offers solutions for such problems. Results of this study show that AHP is the most common approach in consideration of multiple stakeholders and experts and governments/municipalities are the most common participants in these studies.« less

Cognitive Neural Prosthetics

PubMed Central

Andersen, Richard A.; Hwang, Eun Jung; Mulliken, Grant H.

2010-01-01

The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations. The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation. We review a number of high-level cortical signals and their application for CNPs, including intention, motor imagery, decision making, forward estimation, executive function, attention, learning, and multi-effector movement planning. CNPs are defined by the cognitive function they extract, not the cortical region from which the signals are recorded. However, some cortical areas may be better than others for particular applications. Signals can also be extracted in parallel from multiple cortical areas using multiple implants, which in many circumstances can increase the range of applications of CNPs. The CNP approach relies on scientific understanding of the neural processes involved in cognition, and many of the decoding algorithms it uses also have parallels to underlying neural circuit functions. PMID:19575625

Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

NASA Astrophysics Data System (ADS)

Ohdaira, Tetsushi

2014-07-01

Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision.

Working Memory and Decision-Making in a Frontoparietal Circuit Model

PubMed Central

2017-01-01

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models. SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental “building blocks” of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks. PMID:29114071

Working Memory and Decision-Making in a Frontoparietal Circuit Model.

PubMed

Murray, John D; Jaramillo, Jorge; Wang, Xiao-Jing

2017-12-13

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models. SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks. Copyright © 2017 the authors 0270-6474/17/3712167-20$15.00/0.

ATR evaluation through the synthesis of multiple performance measures

NASA Astrophysics Data System (ADS)

Bassham, Christopher B.; Klimack, William K.; Bauer, Kenneth W., Jr.

2002-07-01

This research demonstrates the application of decision analysis (DA) techniques to decisions made within Automatic Target Recognition (ATR) technology development. This work is accomplished to improve the means by which ATR technologies are evaluated. The first step in this research was to create a flexible decision analysis framework that could be applied to several decisions across different ATR programs evaluated by the Comprehensive ATR Scientific Evaluation (COMPASE) Center of the Air Force Research Laboratory (AFRL). For the purposes of this research, a single COMPASE Center representative provided the value, utility, and preference functions for the DA framework. The DA framework employs performance measures collected during ATR classification system (CS) testing to calculate value and utility scores. The authors gathered data from the Moving and Stationary Target Acquisition and Recognition (MSTAR) program to demonstrate how the decision framework could be used to evaluate three different ATR CSs. A decision-maker may use the resultant scores to gain insight into any of the decisions that occur throughout the lifecycle of ATR technologies. Additionally, a means of evaluating ATR CS self-assessment ability is presented. This represents a new criterion that emerged from this study, and no present evaluation metric is known.

Impaired decision making and delayed memory are related with anxiety and depressive symptoms in acromegaly.

PubMed

Crespo, Iris; Santos, Alicia; Valassi, Elena; Pires, Patricia; Webb, Susan M; Resmini, Eugenia

2015-12-01

Evaluation of cognitive function in acromegaly has revealed contradictory findings; some studies report normal cognition in patients with long-term cured acromegaly, while others show attention and memory deficits. Moreover, the presence of affective disorders in these patients is common. Our aim was to evaluate memory and decision making in acromegalic patients and explore their relationship with affective disorders like anxiety and depressive symptoms. Thirty-one patients with acromegaly (mean age 49.5 ± 8.5 years, 14 females and 17 males) and thirty-one healthy controls participated in this study. The Iowa Gambling Task (IGT), Rey Auditory Verbal Learning Test, State-Trait Anxiety Inventory, and Beck Depression Inventory-II (BDI-II) were used to evaluate decision making, verbal memory, anxiety, and depressive symptoms, respectively. Acromegalic patients showed impairments in delayed verbal memory (p < 0.05) and more anxiety and depressive symptoms (p < 0.05) than controls. In the IGT, acromegalic patients presented an altered decision-making strategy compared to controls, choosing a lower number of the safer cards (p < 0.05) and higher number of the riskier cards (p < 0.05). Moreover, multiple correlations between anxiety and depressive symptoms and performance in memory and decision making were found. Impaired delayed memory and decision making observed in acromegalic patients are related to anxiety and depressive symptoms. Providing emotional support to the patients could improve their cognitive function. A key clinical application of this research is the finding that depressive symptoms and anxiety are essentially modifiable factors.

A probabilistic approach to aircraft design emphasizing stability and control uncertainties

NASA Astrophysics Data System (ADS)

Delaurentis, Daniel Andrew

In order to address identified deficiencies in current approaches to aerospace systems design, a new method has been developed. This new method for design is based on the premise that design is a decision making activity, and that deterministic analysis and synthesis can lead to poor, or misguided decision making. This is due to a lack of disciplinary knowledge of sufficient fidelity about the product, to the presence of uncertainty at multiple levels of the aircraft design hierarchy, and to a failure to focus on overall affordability metrics as measures of goodness. Design solutions are desired which are robust to uncertainty and are based on the maximum knowledge possible. The new method represents advances in the two following general areas. 1. Design models and uncertainty. The research performed completes a transition from a deterministic design representation to a probabilistic one through a modeling of design uncertainty at multiple levels of the aircraft design hierarchy, including: (1) Consistent, traceable uncertainty classification and representation; (2) Concise mathematical statement of the Probabilistic Robust Design problem; (3) Variants of the Cumulative Distribution Functions (CDFs) as decision functions for Robust Design; (4) Probabilistic Sensitivities which identify the most influential sources of variability. 2. Multidisciplinary analysis and design. Imbedded in the probabilistic methodology is a new approach for multidisciplinary design analysis and optimization (MDA/O), employing disciplinary analysis approximations formed through statistical experimentation and regression. These approximation models are a function of design variables common to the system level as well as other disciplines. For aircraft, it is proposed that synthesis/sizing is the proper avenue for integrating multiple disciplines. Research hypotheses are translated into a structured method, which is subsequently tested for validity. Specifically, the implementation involves the study of the relaxed static stability technology for a supersonic commercial transport aircraft. The probabilistic robust design method is exercised resulting in a series of robust design solutions based on different interpretations of "robustness". Insightful results are obtained and the ability of the method to expose trends in the design space are noted as a key advantage.

Portability scenarios for intelligent robotic control agent software

NASA Astrophysics Data System (ADS)

Straub, Jeremy

2014-06-01

Portability scenarios are critical in ensuring that a piece of AI control software will run effectively across the collection of craft that it is required to control. This paper presents scenarios for control software that is designed to control multiple craft with heterogeneous movement and functional characteristics. For each prospective target-craft type, its capabilities, mission function, location, communications capabilities and power profile are presented and performance characteristics are reviewed. This work will inform future work related to decision making related to software capabilities, hardware control capabilities and processing requirements.

Flexible high speed codec

NASA Technical Reports Server (NTRS)

Boyd, R. W.; Hartman, W. F.

1992-01-01

The project's objective is to develop an advanced high speed coding technology that provides substantial coding gains with limited bandwidth expansion for several common modulation types. The resulting technique is applicable to several continuous and burst communication environments. Decoding provides a significant gain with hard decisions alone and can utilize soft decision information when available from the demodulator to increase the coding gain. The hard decision codec will be implemented using a single application specific integrated circuit (ASIC) chip. It will be capable of coding and decoding as well as some formatting and synchronization functions at data rates up to 300 megabits per second (Mb/s). Code rate is a function of the block length and can vary from 7/8 to 15/16. Length of coded bursts can be any multiple of 32 that is greater than or equal to 256 bits. Coding may be switched in or out on a burst by burst basis with no change in the throughput delay. Reliability information in the form of 3-bit (8-level) soft decisions, can be exploited using applique circuitry around the hard decision codec. This applique circuitry will be discrete logic in the present contract. However, ease of transition to LSI is one of the design guidelines. Discussed here is the selected coding technique. Its application to some communication systems is described. Performance with 4, 8, and 16-ary Phase Shift Keying (PSK) modulation is also presented.

Intuitionistic fuzzy evidential power aggregation operator and its application in multiple criteria decision-making

NASA Astrophysics Data System (ADS)

Jiang, Wen; Wei, Boya

2018-02-01

The theory of intuitionistic fuzzy sets (IFS) is widely used for dealing with vagueness and the Dempster-Shafer (D-S) evidence theory has a widespread use in multiple criteria decision-making problems under uncertain situation. However, there are many methods to aggregate intuitionistic fuzzy numbers (IFNs), but the aggregation operator to fuse basic probability assignment (BPA) is rare. Power average (P-A) operator, as a powerful operator, is useful and important in information fusion. Motivated by the idea of P-A power, in this paper, a new operator based on the IFS and D-S evidence theory is proposed, which is named as intuitionistic fuzzy evidential power average (IFEPA) aggregation operator. First, an IFN is converted into a BPA, and the uncertainty is measured in D-S evidence theory. Second, the difference between BPAs is measured by Jousselme distance and a satisfying support function is proposed to get the support degree between each other effectively. Then the IFEPA operator is used for aggregating the original IFN and make a more reasonable decision. The proposed method is objective and reasonable because it is completely driven by data once some parameters are required. At the same time, it is novel and interesting. Finally, an application of developed models to the 'One Belt, One road' investment decision-making problems is presented to illustrate the effectiveness and feasibility of the proposed operator.

Neural Systems Underlying Individual Differences in Intertemporal Decision-making.

PubMed

Elton, Amanda; Smith, Christopher T; Parrish, Michael H; Boettiger, Charlotte A

2017-03-01

Excessively choosing immediate over larger future rewards, or delay discounting (DD), associates with multiple clinical conditions. Individual differences in DD likely depend on variations in the activation of and functional interactions between networks, representing possible endophenotypes for associated disorders, including alcohol use disorders (AUDs). Numerous fMRI studies have probed the neural bases of DD, but investigations of large-scale networks remain scant. We addressed this gap by testing whether activation within large-scale networks during Now/Later decision-making predicts individual differences in DD. To do so, we scanned 95 social drinkers (18-40 years old; 50 women) using fMRI during hypothetical choices between small monetary amounts available "today" or larger amounts available later. We identified neural networks engaged during Now/Later choice using independent component analysis and tested the relationship between component activation and degree of DD. The activity of two components during Now/Later choice correlated with individual DD rates: A temporal lobe network positively correlated with DD, whereas a frontoparietal-striatal network negatively correlated with DD. Activation differences between these networks predicted individual differences in DD, and their negative correlation during Now/Later choice suggests functional competition. A generalized psychophysiological interactions analysis confirmed a decrease in their functional connectivity during decision-making. The functional connectivity of these two networks negatively correlates with alcohol-related harm, potentially implicating these networks in AUDs. These findings provide novel insight into the neural underpinnings of individual differences in impulsive decision-making with potential implications for addiction and related disorders in which impulsivity is a defining feature.

Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Marsh, Kevin; IJzerman, Maarten; Thokala, Praveen; Baltussen, Rob; Boysen, Meindert; Kaló, Zoltán; Lönngren, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Devlin, Nancy

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Analysis of strength-of-preference measures in dichotomous choice models

Treesearch

Donald F. Dennis; Peter Newman; Robert Manning

2008-01-01

Choice models are becoming increasingly useful for soliciting and analyzing multiple objective decisions faced by recreation managers and others interested in decisions involving natural resources. Choice models are used to estimate relative values for multiple aspects of natural resource management, not individually but within the context of other relevant decision...

Decision-making in crisis: Applying a healthcare triage methodology to business continuity management.

PubMed

Moore, Bethany; Bone, Eric A

2017-01-01

The concept of triage in healthcare has been around for centuries and continues to be applied today so that scarce resources are allocated according to need. A business impact analysis (BIA) is a form of triage in that it identifies which processes are most critical, which to address first and how to allocate limited resources. On its own, however, the BIA provides only a roadmap of the impacts and interdependencies of an event. When disaster strikes, organisational decision-makers often face difficult decisions with regard to allocating limited resources between multiple 'mission-critical' functions. Applying the concept of triage to business continuity provides those decision-makers navigating a rapidly evolving and unpredictable event with a path that protects the fundamental priorities of the organisation. A business triage methodology aids decision-makers in times of crisis by providing a simplified framework for decision-making based on objective, evidence-based criteria, which is universally accepted and understood. When disaster strikes, the survival of the organisation depends on critical decision-making and quick actions to stabilise the incident. This paper argues that organisations need to supplement BIA processes with a decision-making triage methodology that can be quickly applied during the chaos of an actual event.

IEEE 802.21 Assisted Seamless and Energy Efficient Handovers in Mixed Networks

NASA Astrophysics Data System (ADS)

Liu, Huaiyu; Maciocco, Christian; Kesavan, Vijay; Low, Andy L. Y.

Network selection is the decision process for a mobile terminal to handoff between homogeneous or heterogeneous networks. With multiple available networks, the selection process must evaluate factors like network services/conditions, monetary cost, system conditions, user preferences etc. In this paper, we investigate network selection using a cost function and information provided by IEEE 802.21. The cost function provides flexibility to balance different factors in decision making and our research is focused on improving both seamlessness and energy efficiency of handovers. Our solution is evaluated using real WiFi, WiMax, and 3G signal strength traces. The results show that appropriate networks were selected based on selection policies, handovers were triggered at optimal times to increase overall network connectivity as compared to traditional triggering schemes, while at the same time the energy consumption of multi-radio devices for both on-going operations as well as during handovers is optimized.

A comprehensive model of the spatio-temporal stem cell and tissue organisation in the intestinal crypt.

PubMed

Buske, Peter; Galle, Jörg; Barker, Nick; Aust, Gabriela; Clevers, Hans; Loeffler, Markus

2011-01-06

We introduce a novel dynamic model of stem cell and tissue organisation in murine intestinal crypts. Integrating the molecular, cellular and tissue level of description, this model links a broad spectrum of experimental observations encompassing spatially confined cell proliferation, directed cell migration, multiple cell lineage decisions and clonal competition.Using computational simulations we demonstrate that the model is capable of quantitatively describing and predicting the dynamic behaviour of the intestinal tissue during steady state as well as after cell damage and following selective gain or loss of gene function manipulations affecting Wnt- and Notch-signalling. Our simulation results suggest that reversibility and flexibility of cellular decisions are key elements of robust tissue organisation of the intestine. We predict that the tissue should be able to fully recover after complete elimination of cellular subpopulations including subpopulations deemed to be functional stem cells. This challenges current views of tissue stem cell organisation.

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.

The subthalamic nucleus during decision-making with multiple alternatives.

PubMed

Keuken, Max C; Van Maanen, Leendert; Bogacz, Rafal; Schäfer, Andreas; Neumann, Jane; Turner, Robert; Forstmann, Birte U

2015-10-01

Several prominent neurocomputational models predict that an increase of choice alternatives is modulated by increased activity in the subthalamic nucleus (STN). In turn, increased STN activity allows prolonged accumulation of information. At the same time, areas in the medial frontal cortex such as the anterior cingulate cortex (ACC) and the pre-SMA are hypothesized to influence the information processing in the STN. This study set out to test concrete predictions of STN activity in multiple-alternative decision-making using a multimodal combination of 7 Tesla structural and functional Magnetic Resonance Imaging, and ancestral graph (AG) modeling. The results are in line with the predictions in that increased STN activity was found with an increasing amount of choice alternatives. In addition, our study shows that activity in the ACC is correlated with activity in the STN without directly modulating it. This result sheds new light on the information processing streams between medial frontal cortex and the basal ganglia. © 2015 Wiley Periodicals, Inc.

Balancing habitat delivery for breeding marsh birds and nonbreeding waterfowl: An integrated waterbird management and monitoring approach at Clarence Cannon National Wildlife Refuge, Missouri

USGS Publications Warehouse

Loges, Brian W.; Lyons, James E.; Tavernia, Brian G.

2017-08-23

The Clarence Cannon National Wildlife Refuge (CCNWR) in the Mississippi River flood plain of eastern Missouri provides high quality emergent marsh and moist-soil habitat benefitting both nesting marsh birds and migrating waterfowl. Staff of CCNWR manipulate water levels and vegetation in the 17 units of the CCNWR to provide conditions favorable to these two important guilds. Although both guilds include focal species at multiple planning levels and complement objectives to provide a diversity of wetland community types and water regimes, additional decision support is needed for choosing how much emergent marsh and moist-soil habitat should be provided through annual management actions.To develop decision guidance for balanced delivery of high-energy waterfowl habitat and breeding marsh bird habitat, two measureable management objectives were identified: nonbreeding Anas Linnaeus (dabbling duck) use-days and Rallus elegans (king rail) occupancy of managed units. Three different composite management actions were identified to achieve these objectives. Each composite management action is a unique combination of growing season water regime and soil disturbance. The three composite management actions are intense moist-soil management (moist-soil), intermediate moist-soil (intermediate), and perennial management, which idles soils disturbance (perennial). The two management objectives and three management options were used in a multi-criteria decision analysis to indicate resource allocations and inform annual decision making. Outcomes of the composite management actions were predicted in two ways and multi-criteria decision analysis was used with each set of predictions. First, outcomes were predicted using expert-elicitation techniques and a panel of subject matter experts. Second, empirical data from the Integrated Waterbird Management and Monitoring Initiative collected between 2010 and 2013 were used; where data were lacking, expert judgment was used. Also, a Bayesian decision model was developed that can be updated with monitoring data in an adaptive management framework.Optimal resource allocations were identified in the form of portfolios of composite management actions for the 17 units in the framework. A constrained optimization (linear programming) was used to maximize an objective function that was based on the sum of dabbling duck and king rail utility. The constraints, which included management costs and a minimum energetic carrying capacity (total moist-soil acres), were applied to balance habitat delivery for dabbling ducks and king rails. Also, the framework was constrained in some cases to apply certain management actions of interest to certain management units; these constraints allowed for a variety of hypothetical Habitat Management Plans, including one based on output from a hydrogeomorphic study of the refuge. The decision analysis thus created numerous refuge-wide scenarios, each representing a unique mix of options (one for each of 17 units) and associated benefits (i.e., outcomes with respect to two management objectives).Prepared in collaboration with the U.S. Fish and Wildlife Service, the decision framework presented here is designed as a decision-aiding tool for CCNWR managers who ultimately make difficult decisions each year with multiple objectives, multiple management units, and the complexity of natural systems. The framework also provides a way to document hypotheses about how the managed system functions. Furthermore, the framework identifies specific monitoring needs and illustrates precisely how monitoring data will be used for decision-aiding and adaptive management.

Tailoring Software for Multiple Processor Systems

DTIC Science & Technology

1982-10-01

resource management decisions . Despite the lack of programming support, the use of multiple processor systems has grown sub- -stantially. Software has...making resource management decisions . Specifically, program- 1 mers need not allocate specific hardware resources to individual program components...Instead, such allocation decisions are automatically made based on high-level resource directives stated by ap- plication programmers, where each directive

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…

The multiple resource inventory decision-making process

Treesearch

Victor A. Rudis

1993-01-01

A model of the multiple resource inventory decision-making process is presented that identifies steps in conducting inventories, describes the infrastructure, and points out knowledge gaps that are common to many interdisciplinary studies.Successful efforts to date suggest the need to bridge the gaps by sharing elements, maintain dialogue among stakeholders in multiple...

An Integrated Multi-layer Approach for Seamless Soft Handoff in Mobile Ad Hoc Networks

DTIC Science & Technology

2011-01-01

network to showcase how to leverage the IEEE 802.21 Media Independent Handover ( MIH ) framework [3] in our handoff solution. Moreover, to further...to the seamless handoff problem. The architecture leverages the IEEE 802.21 MIH standard to facilitate handover related decisions on multiple...provided by the MIH function (MIHF), the topology control manager dynamically activates/deactivates the wireless interfaces to ensure the network is

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

Crime prediction modeling

NASA Technical Reports Server (NTRS)

1971-01-01

A study of techniques for the prediction of crime in the City of Los Angeles was conducted. Alternative approaches to crime prediction (causal, quasicausal, associative, extrapolative, and pattern-recognition models) are discussed, as is the environment within which predictions were desired for the immediate application. The decision was made to use time series (extrapolative) models to produce the desired predictions. The characteristics of the data and the procedure used to choose equations for the extrapolations are discussed. The usefulness of different functional forms (constant, quadratic, and exponential forms) and of different parameter estimation techniques (multiple regression and multiple exponential smoothing) are compared, and the quality of the resultant predictions is assessed.

MULTIPLE SCALES FOR SUSTAINABLE RESULTS

EPA Science Inventory

This session will highlight recent research that incorporates the use of multiple scales and innovative environmental accounting to better inform decisions that affect sustainability, resilience, and vulnerability at all scales. Effective decision-making involves assessment at mu...

A Model For Change: An Approach for Forecasting Well-Being ...

EPA Pesticide Factsheets

Every community decision incorporates a "forecasting" strategy (whether formal or implicit) to help visualize expected results and evaluate the potential “feelings” that people living in that community may have about those results. With more communities seeking to make decisions based on sustainable alternatives, forecasting efforts that examine potential impacts of decisions on overall community well-being may prove to be valuable for not only gaging future benefits and trade-offs, but also for recognizing a community’s affective response to the outcomes of those decisions. This paper describes a forecasting approach based on concepts introduced in the development of the U.S. Environmental Protection Agency’s (US EPA) Human Well-Being Index (HWBI) (Smith, et. al. 2014; Summers et al. 2014). The approach examines the relationships among selected economic, environmental and social services that can be directly impacted by community decisions and eight domains of human well-being. Using models developed from constructed- or fixed-effect step-wise and multiple regressions and eleven years of data (2000-2010), these relationship functions may be used to characterize likely direct impacts of decisions on future well-being as well as the possible intended and unintended secondary and tertiary effects relative to any main decision effects. This paper describes an approach to using HWBI in decision making models to characterize likely impacts of decisions on fut

Does Choice of Multicriteria Method Matter? An Experiment in Water Resources Planning

NASA Astrophysics Data System (ADS)

Hobbs, Benjamin F.; Chankong, Vira; Hamadeh, Wael; Stakhiv, Eugene Z.

1992-07-01

Many multiple criteria decision making methods have been proposed and applied to water planning. Their purpose is to provide information on tradeoffs among objectives and to help users articulate value judgments in a systematic, coherent, and documentable manner. The wide variety of available techniques confuses potential users, causing inappropriate matching of methods with problems. Experiments in which water planners apply more than one multicriteria procedure to realistic problems can help dispel this confusion by testing method appropriateness, ease of use, and validity. We summarize one such experiment where U.S. Army Corps of Engineers personnel used several methods to screen urban water supply plans. The methods evaluated include goal programming, ELECTRE I, additive value functions, multiplicative utility functions, and three techniques for choosing weights (direct rating, indifference tradeoff, and the analytical hierarchy process). Among the conclusions we reach are the following. First, experienced planners generally prefer simpler, more transparent methods. Additive value functions are favored. Yet none of the methods are endorsed by a majority of the participants; many preferred to use no formal method at all. Second, there is strong evidence that rating, the most commonly applied weight selection method, is likely to lead to weights that fail to represent the trade-offs that users are willing to make among criteria. Finally, we show that decisions can be as or more sensitive to the method used as to which person applies it. Therefore, if who chooses is important, then so too is how a choice is made.

Multiple perspective vulnerability analysis of the power network

NASA Astrophysics Data System (ADS)

Wang, Shuliang; Zhang, Jianhua; Duan, Na

2018-02-01

To understand the vulnerability of the power network from multiple perspectives, multi-angle and multi-dimensional vulnerability analysis as well as community based vulnerability analysis are proposed in this paper. Taking into account of central China power grid as an example, correlation analysis of different vulnerability models is discussed. Then, vulnerabilities produced by different vulnerability metrics under the given vulnerability models and failure scenarios are analyzed. At last, applying the community detecting approach, critical areas of central China power grid are identified, Vulnerable and robust communities on both topological and functional perspective are acquired and analyzed. The approach introduced in this paper can be used to help decision makers develop optimal protection strategies. It will be also useful to give a multiple vulnerability analysis of the other infrastructure systems.

Multiple Forensic Interviews during Investigations of Child Sexual Abuse: A Cost-Effectiveness Analysis

ERIC Educational Resources Information Center

Block, Stephanie D.; Foster, E. Michael; Pierce, Matthew W.; Berkoff, Molly C.; Runyan, Desmond K.

2013-01-01

In suspected child sexual abuse some professionals recommend multiple child interviews to increase the likelihood of disclosure or more details to improve decision-making and increase convictions. We modeled the yield of a policy of routinely conducting multiple child interviews and increased convictions. Our decision tree reflected the path of a…

Applying voting theory in natural resource management: a case of multiple-criteria group decision support.

PubMed

Laukkanen, Sanna; Kangas, Annika; Kangas, Jyrki

2002-02-01

Voting theory has a lot in common with utility theory, and especially with group decision-making. An expected-utility-maximising strategy exists in voting situations, as well as in decision-making situations. Therefore, it is natural to utilise the achievements of voting theory also in group decision-making. Most voting systems are based on a single criterion or holistic preference information on decision alternatives. However, a voting scheme called multicriteria approval is specially developed for decision-making situations with multiple criteria. This study considers the voting theory from the group decision support point of view and compares it with some other methods applied to similar purposes in natural resource management. A case study is presented, where the approval voting approach is introduced to natural resources planning and tested in a forestry group decision-making process. Applying multicriteria approval method was found to be a potential approach for handling some challenges typical for forestry group decision support. These challenges include (i) utilising ordinal information in the evaluation of decision alternatives, (ii) being readily understandable for and treating equally all the stakeholders in possession of different levels of knowledge on the subject considered, (iii) fast and cheap acquisition of preference information from several stakeholders, and (iv) dealing with multiple criteria.

Multimorbidity and Decision-Making Preferences Among Older Adults.

PubMed

Chi, Winnie C; Wolff, Jennifer; Greer, Raquel; Dy, Sydney

2017-11-01

Understanding individuals' preferences for participating in health care decisions is foundational to delivering person-centered care. We aimed to (1) explore preferences for health care decision making among older adults, and (2) identify multimorbidity profiles associated with preferring less active, ie, passive, participation among older US adults. Ours was a cross-sectional, nationally representative study of 2,017 National Health and Aging Trends Study respondents. Passive decision-making preference was defined as preferring to leave decisions to physicians. Multimorbidity profiles, based on 13 prevalent chronic conditions, were examined as (1) presence of 2 or more conditions, (2) a simple conditions count, and (3) a condition clusters count. Multiple logistic regression was used with adjustment for age, sex, education, English proficiency, and mobility limitation. Most older adults preferred to participate actively in making health care decisions. Older adults with 4 or more conditions, however, and those with multiple condition clusters are relatively less likely to prefer active decision making. Primary care physicians should initiate a shared decision-making process with older adults with 4 or more conditions or multiple condition clusters. Physicians should anticipate variation in decision-making preferences among older adults and adapt a decision-making process that suits individuals' preferences for participation to ensure person-centered care delivery. © 2017 Annals of Family Medicine, Inc.

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

NASA Astrophysics Data System (ADS)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

Creating ensembles of decision trees through sampling

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick

2005-08-30

A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

Medical decision-making capacity and its cognitive predictors in progressive MS: Preliminary evidence.

PubMed

Gerstenecker, Adam; Lowry, Kathleen; Myers, Terina; Bashir, Khurram; Triebel, Kristen L; Martin, Roy C; Marson, Daniel C

2017-09-15

Medical decision-making capacity (MDC) refers to the ability to make informed decisions about treatment and declines in cognition are associated with declines in MDC across multiple disease entities. However, although it is well known that cognitive impairment is prevalent in multiple sclerosis (MS), little is known about MDC in the disease. Data from 22 persons with progressive MS and 18 healthy controls were analyzed. All diagnoses were made by a board-certified neurologist with experience in MS. All study participants were administered a vignette-based measure of MDC and also a neuropsychological battery. Performance on three MDC consent standards (i.e., Appreciation, Reasoning, Understanding) was significantly lower for people with progressive MS as compared to healthy controls. In the progressive MS group, verbal fluency was the primary cognitive predictor for both Reasoning and Understanding consent standards. Verbal learning and memory was the primary cognitive predictor for Appreciation. MS severity was not significantly correlated with any MDC variable. MDC is a complex and cognitively mediated functional ability that is impaired in many people with progressive MS. Verbal measures of fluency and memory are strongly associated with MDC performances in the current sample of people with MS and could potentially be utilized to quickly screen for MDC impairment in MS. Copyright © 2017 Elsevier B.V. All rights reserved.

Local classifier weighting by quadratic programming.

PubMed

Cevikalp, Hakan; Polikar, Robi

2008-10-01

It has been widely accepted that the classification accuracy can be improved by combining outputs of multiple classifiers. However, how to combine multiple classifiers with various (potentially conflicting) decisions is still an open problem. A rich collection of classifier combination procedures -- many of which are heuristic in nature -- have been developed for this goal. In this brief, we describe a dynamic approach to combine classifiers that have expertise in different regions of the input space. To this end, we use local classifier accuracy estimates to weight classifier outputs. Specifically, we estimate local recognition accuracies of classifiers near a query sample by utilizing its nearest neighbors, and then use these estimates to find the best weights of classifiers to label the query. The problem is formulated as a convex quadratic optimization problem, which returns optimal nonnegative classifier weights with respect to the chosen objective function, and the weights ensure that locally most accurate classifiers are weighted more heavily for labeling the query sample. Experimental results on several data sets indicate that the proposed weighting scheme outperforms other popular classifier combination schemes, particularly on problems with complex decision boundaries. Hence, the results indicate that local classification-accuracy-based combination techniques are well suited for decision making when the classifiers are trained by focusing on different regions of the input space.

Assessing Neurocognition via Gamified Experimental Logic: A Novel Approach to Simultaneous Acquisition of Multiple ERPs.

PubMed

Nair, Ajay K; Sasidharan, Arun; John, John P; Mehrotra, Seema; Kutty, Bindu M

2016-01-01

The present study describes the development of a neurocognitive paradigm: "Assessing Neurocognition via Gamified Experimental Logic" (ANGEL), for performing the parametric evaluation of multiple neurocognitive functions simultaneously. ANGEL employs an audiovisual sensory motor design for the acquisition of multiple event related potentials (ERPs)-the C1, P50, MMN, N1, N170, P2, N2pc, LRP, P300, and ERN. The ANGEL paradigm allows assessment of 10 neurocognitive variables over the course of three "game" levels of increasing complexity ranging from simple passive observation to complex discrimination and response in the presence of multiple distractors. The paradigm allows assessment of several levels of rapid decision making: speeded up response vs. response-inhibition; responses to easy vs. difficult tasks; responses based on gestalt perception of clear vs. ambiguous stimuli; and finally, responses with set shifting during challenging tasks. The paradigm has been tested using 18 healthy participants from both sexes and the possibilities of varied data analyses have been presented in this paper. The ANGEL approach provides an ecologically valid assessment (as compared to existing tools) that quickly yields a very rich dataset and helps to assess multiple ERPs that can be studied extensively to assess cognitive functions in health and disease conditions.

Assessing Neurocognition via Gamified Experimental Logic: A Novel Approach to Simultaneous Acquisition of Multiple ERPs

PubMed Central

Nair, Ajay K.; Sasidharan, Arun; John, John P.; Mehrotra, Seema; Kutty, Bindu M.

2016-01-01

The present study describes the development of a neurocognitive paradigm: “Assessing Neurocognition via Gamified Experimental Logic” (ANGEL), for performing the parametric evaluation of multiple neurocognitive functions simultaneously. ANGEL employs an audiovisual sensory motor design for the acquisition of multiple event related potentials (ERPs)—the C1, P50, MMN, N1, N170, P2, N2pc, LRP, P300, and ERN. The ANGEL paradigm allows assessment of 10 neurocognitive variables over the course of three “game” levels of increasing complexity ranging from simple passive observation to complex discrimination and response in the presence of multiple distractors. The paradigm allows assessment of several levels of rapid decision making: speeded up response vs. response-inhibition; responses to easy vs. difficult tasks; responses based on gestalt perception of clear vs. ambiguous stimuli; and finally, responses with set shifting during challenging tasks. The paradigm has been tested using 18 healthy participants from both sexes and the possibilities of varied data analyses have been presented in this paper. The ANGEL approach provides an ecologically valid assessment (as compared to existing tools) that quickly yields a very rich dataset and helps to assess multiple ERPs that can be studied extensively to assess cognitive functions in health and disease conditions. PMID:26858586

Robustness of Multiple Objective Decision Analysis Preference Functions

DTIC Science & Technology

2002-06-01

p p′ : The probability of some event. ,i ip q : The probability of event . i Π : An aggregation of proportional data used in calculating a test ...statistical tests of the significance of the term and also is conducted in a multivariate framework rather than the ROSA univariate approach. A...residual error is ˆ−e = y y (45) The coefficient provides a ready indicator of the contribution for the associated variable and statistical tests

Evaluating the Functionality of Conceptual Models

NASA Astrophysics Data System (ADS)

Mehmood, Kashif; Cherfi, Samira Si-Said

Conceptual models serve as the blueprints of information systems and their quality plays decisive role in the success of the end system. It has been witnessed that majority of the IS change-requests results due to deficient functionalities in the information systems. Therefore, a good analysis and design method should ensure that conceptual models are functionally correct and complete, as they are the communicating mediator between the users and the development team. Conceptual model is said to be functionally complete if it represents all the relevant features of the application domain and covers all the specified requirements. Our approach evaluates the functional aspects on multiple levels of granularity in addition to providing the corrective actions or transformation for improvement. This approach has been empirically validated by practitioners through a survey.

Treatment of progressive multiple sclerosis: what works, what does not, and what is needed.

PubMed

Feinstein, Anthony; Freeman, Jenny; Lo, Albert C

2015-02-01

Disease-modifying drugs have mostly failed as treatments for progressive multiple sclerosis. Management of the disease therefore solely aims to minimise symptoms and, if possible, improve function. The degree to which this approach is based on empirical data derived from studies of progressive disease or whether treatment decisions are based on what is known about relapsing-remitting disease remains unclear. Symptoms rated as important by patients with multiple sclerosis include balance and mobility impairments, weakness, reduced cardiovascular fitness, ataxia, fatigue, bladder dysfunction, spasticity, pain, cognitive deficits, depression, and pseudobulbar affect; a comprehensive literature search shows a notable paucity of studies devoted solely to these symptoms in progressive multiple sclerosis, which translates to few proven therapeutic options in the clinic. A new strategy that can be used in future rehabilitation trials is therefore needed, with the adoption of approaches that look beyond single interventions to concurrent, potentially synergistic, treatments that maximise what remains of neural plasticity in patients with progressive multiple sclerosis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Regulation and function of mTOR signalling in T cell fate decision

PubMed Central

Chi, Hongbo

2012-01-01

The evolutionary conserved kinase mTOR couples cell growth and metabolism to environmental inputs in eukaryotes. T cells depend on mTOR signalling to integrate immune signals and metabolic cues for their proper maintenance and activation. Under steady-state conditions, mTOR is actively controlled by multiple inhibitory mechanisms, and this enforces normal T cell homeostasis. Antigen recognition by naïve CD4+ and CD8+ T cells triggers mTOR activation, which in turn programs their differentiation into functionally distinct lineages. This Review focuses on the signalling mechanisms of mTOR in T cell homeostatic and functional fates and therapeutic implications of targeting mTOR in T cells. PMID:22517423

Can hydro-economic river basin models simulate water shadow prices under asymmetric access?

PubMed

Kuhn, A; Britz, W

2012-01-01

Hydro-economic river basin models (HERBM) based on mathematical programming are conventionally formulated as explicit 'aggregate optimization' problems with a single, aggregate objective function. Often unintended, this format implicitly assumes that decisions on water allocation are made via central planning or functioning markets such as to maximize social welfare. In the absence of perfect water markets, however, individually optimal decisions by water users will differ from the social optimum. Classical aggregate HERBMs cannot simulate that situation and thus might be unable to describe existing institutions governing access to water and might produce biased results for alternative ones. We propose a new solution format for HERBMs, based on the format of the mixed complementarity problem (MCP), where modified shadow price relations express spatial externalities resulting from asymmetric access to water use. This new problem format, as opposed to commonly used linear (LP) or non-linear programming (NLP) approaches, enables the simultaneous simulation of numerous 'independent optimization' decisions by multiple water users while maintaining physical interdependences based on water use and flow in the river basin. We show that the alternative problem format allows the formulation HERBMs that yield more realistic results when comparing different water management institutions.

Questionnaire-Based Maladaptive Decision-Coping Patterns Involved in Binge Eating Among 1013 College Students

PubMed Central

Yan, Wan-Sen; Zhang, Ran-Ran; Lan, Yan; Li, Zhi-Ming; Li, Yong-Hui

2018-01-01

Binge Eating Disorder (BED), considered a public health problem because of its impact on psychiatric, physical, and social functioning, merits much attention given its elevation to an independent diagnosis in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Similar with substance use disorders, some neuropsychological and personality constructs are potentially implicated in the onset and development of BED, in which poor decision-making has been suggested to facilitate overeating and BED. The objective of this study was to investigate the associations between decision-coping patterns, monetary decision-making, and binge-eating behavior in young adults. A sample of 1013 college students, equally divided into binge-eating and non-binge-eating groups according to the scores on the Binge Eating Scale (BES), were administered multiple measures of decision-making including the Melbourne Decision-Making Questionnaire (MDMQ), the Delay-discounting Test (DDT), and the Probability Discounting Test (PDT). Compared with the non-binge-eating group, the binge-eating group displayed elevated scores on maladaptive decision-making patterns including Procrastination, Buck-passing, and Hypervigilance. Logistic regression model revealed that only Procrastination positively predicted binge eating. These findings suggest that different dimensions of decision-making may be distinctly linked to binge eating among young adults, with Procrastination putatively identified as a risk trait in the development of overeating behavior, which might promote a better understanding of this disorder. PMID:29765343

The decision neuroscience perspective on suicidal behavior: evidence and hypotheses

PubMed Central

Dombrovski, Alexandre Y.; Hallquist, Michael N.

2017-01-01

Purpose of review Suicide attempts are usually regretted by people who survive them. Furthermore, addiction and gambling are over-represented among people who attempt or die by suicide, raising the question whether their decision-making is impaired. Advances in decision neuroscience have enabled us to investigate decision processes in suicidal people and to elucidate putative neural substrates of disadvantageous decision-making. Recent findings Early studies have linked attempted suicide to poor performance on gambling tasks. More recently, functional MRI augmented with a reinforcement learning computational model revealed that impaired decision-making in suicide attempters is paralleled by disrupted expected value (expected reward) signals in the ventromedial prefrontal cortex. Behavioral studies have linked increased delay discounting to low-lethality/poorly planned attempts, multiple attempts, and the co-occurrence of attempted suicide and addiction. This behavioral tendency may be related to altered integrity of the basal ganglia. By contrast, well-planned, serious suicide attempts were associated with intact/diminished delay discounting. One study has linked high-lethality suicide attempts and impaired social decision-making. Summary This emerging literature supports the notion that various impairments in decision-making – often broadly related to impulsivity – may mark different pathways to suicide. We propose that aggressive and self-destructive responses to social stressors in people prone to suicide result from a predominance of automatic, Pavlovian processes over goal-directed computations. PMID:27875379

Influence of ventral tegmental area input on cortico-subcortical networks underlying action control and decision making.

PubMed

Richter, Anja; Gruber, Oliver

2018-02-01

It is argued that the mesolimbic system has a more general function in processing all salient events, including and extending beyond rewards. Saliency was defined as an event that is unexpected due to its frequency of occurrence and elicits an attentional-behavioral switch. Using functional magnetic resonance imaging (fMRI), signals were measured in response to the modulation of salience of rewarding and nonrewarding events during a reward-based decision making task, the so called desire-reason dilemma paradigm (DRD). Replicating previous findings, both frequent and infrequent, and therefore salient, reward stimuli elicited reliable activation of the ventral tegmental area (VTA) and ventral striatum (vStr). When immediate reward desiring contradicted the superordinate task-goal, we found an increased activation of the VTA and vStr when the salient reward stimuli were presented compared to the nonsalient reward stimuli, indicating a boosting of activation in these brain regions. Furthermore, we found a significantly increased functional connectivity between the VTA and vStr, confirming the boosting of vStr activation via VTA input. Moreover, saliency per se without a reward association led to an increased activation of brain regions in the mesolimbic reward system as well as the orbitofrontal cortex (OFC), inferior frontal gyrus (IFG), and anterior cingulate cortex (ACC). Finally, findings uncovered multiple increased functional interactions between cortical saliency-processing brain areas and the VTA and vStr underlying detection and processing of salient events and adaptive decision making. © 2017 Wiley Periodicals, Inc.

A model of human decision making in multiple process monitoring situations

NASA Technical Reports Server (NTRS)

Greenstein, J. S.; Rouse, W. B.

1982-01-01

Human decision making in multiple process monitoring situations is considered. It is proposed that human decision making in many multiple process monitoring situations can be modeled in terms of the human's detection of process related events and his allocation of attention among processes once he feels event have occurred. A mathematical model of human event detection and attention allocation performance in multiple process monitoring situations is developed. An assumption made in developing the model is that, in attempting to detect events, the human generates estimates of the probabilities that events have occurred. An elementary pattern recognition technique, discriminant analysis, is used to model the human's generation of these probability estimates. The performance of the model is compared to that of four subjects in a multiple process monitoring situation requiring allocation of attention among processes.

Hesitant triangular fuzzy information aggregation operators based on Bonferroni means and their application to multiple attribute decision making.

PubMed

Wang, Chunyong; Li, Qingguo; Zhou, Xiaoqiang; Yang, Tian

2014-01-01

We investigate the multiple attribute decision-making (MADM) problems with hesitant triangular fuzzy information. Firstly, definition and some operational laws of hesitant triangular fuzzy elements are introduced. Then, we develop some hesitant triangular fuzzy aggregation operators based on Bonferroni means and discuss their basic properties. Some existing operators can be viewed as their special cases. Next, we apply the proposed operators to deal with multiple attribute decision-making problems under hesitant triangular fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness.

Hesitant Triangular Fuzzy Information Aggregation Operators Based on Bonferroni Means and Their Application to Multiple Attribute Decision Making

PubMed Central

Zhou, Xiaoqiang; Yang, Tian

2014-01-01

We investigate the multiple attribute decision-making (MADM) problems with hesitant triangular fuzzy information. Firstly, definition and some operational laws of hesitant triangular fuzzy elements are introduced. Then, we develop some hesitant triangular fuzzy aggregation operators based on Bonferroni means and discuss their basic properties. Some existing operators can be viewed as their special cases. Next, we apply the proposed operators to deal with multiple attribute decision-making problems under hesitant triangular fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness. PMID:25140338

Strategy of Surgical Resection for Glioma Based on Intraoperative Functional Mapping and Monitoring

PubMed Central

TAMURA, Manabu; MURAGAKI, Yoshihiro; SAITO, Taiichi; MARUYAMA, Takashi; NITTA, Masayuki; TSUZUKI, Shunsuke; ISEKI, Hiroshi; OKADA, Yoshikazu

2015-01-01

A growing number of papers have pointed out the relationship between aggressive resection of gliomas and survival prognosis. For maximum resection, the current concept of surgical decision-making is in “information-guided surgery” using multimodal intraoperative information. With this, anatomical information from intraoperative magnetic resonance imaging (MRI) and navigation, functional information from brain mapping and monitoring, and histopathological information must all be taken into account in the new perspective for innovative minimally invasive surgical treatment of glioma. Intraoperative neurofunctional information such as neurophysiological functional monitoring takes the most important part in the process to acquire objective visual data during tumor removal and to integrate these findings as digitized data for intraoperative surgical decision-making. Moreover, the analysis of qualitative data and threshold-setting for quantitative data raise difficult issues in the interpretation and processing of each data type, such as determination of motor evoked potential (MEP) decline, underestimation in tractography, and judgments of patient response for neurofunctional mapping and monitoring during awake craniotomy. Neurofunctional diagnosis of false-positives in these situations may affect the extent of resection, while false-negatives influence intra- and postoperative complication rates. Additionally, even though the various intraoperative visualized data from multiple sources contribute significantly to the reliability of surgical decisions when the information is integrated and provided, it is not uncommon for individual pieces of information to convey opposing suggestions. Such conflicting pieces of information facilitate higher-order decision-making that is dependent on the policies of the facility and the priorities of the patient, as well as the availability of the histopathological characteristics from resected tissue. PMID:26185825

Risky Decision Making in Neurofibromatosis Type 1: An Exploratory Study.

PubMed

Jonas, Rachel K; Roh, EunJi; Montojo, Caroline A; Pacheco, Laura A; Rosser, Tena; Silva, Alcino J; Bearden, Carrie E

2017-03-01

Neurofibromatosis type 1 (NF1) is a monogenic disorder affecting cognitive function. About one third of children with NF1 have attentional disorders, and the cognitive phenotype is characterized by impairment in prefrontally-mediated functions. Mouse models of NF1 show irregularities in GABA release and striatal dopamine metabolism. We hypothesized that youth with NF1 would show abnormal behavior and neural activity on a task of risk-taking reliant on prefrontal-striatal circuits. Youth with NF1 (N=29) and demographically comparable healthy controls (N=22), ages 8-19, were administered a developmentally sensitive gambling task, in which they chose between low-risk gambles with a high probability of obtaining a small reward, and high-risk gambles with a low probability of obtaining a large reward. We used functional magnetic resonance imaging (fMRI) to investigate neural activity associated with risky decision making, as well as age-associated changes in these behavioral and neural processes. Behaviorally, youth with NF1 tended to make fewer risky decisions than controls. Neuroimaging analyses revealed significantly reduced neural activity across multiple brain regions involved in higher-order semantic processing and motivation (i.e., anterior cingulate, paracingulate, supramarginal, and angular gyri) in patients with NF1 relative to controls during the task. We also observed atypical age-associated changes in neural activity in patients with NF1, such that during risk taking, neural activity tended to decrease with age in controls, whereas it tended to increase with age in patients with NF1. Findings suggest that developmental trajectories of neural activity during risky decision-making may be disrupted in youth with NF1.

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…

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

NASA Astrophysics Data System (ADS)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

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.

A framework for multi-stakeholder decision-making and conflict resolution

EPA Science Inventory

We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimiz...

Presenting evidence and summary measures to best inform societal decisions when comparing multiple strategies.

PubMed

Eckermann, Simon; Willan, Andrew R

2011-07-01

Multiple strategy comparisons in health technology assessment (HTA) are becoming increasingly important, with multiple alternative therapeutic actions, combinations of therapies and diagnostic and genetic testing alternatives. Comparison under uncertainty of incremental cost, effects and cost effectiveness across more than two strategies is conceptually and practically very different from that for two strategies, where all evidence can be summarized in a single bivariate distribution on the incremental cost-effectiveness plane. Alternative methods for comparing multiple strategies in HTA have been developed in (i) presenting cost and effects on the cost-disutility plane and (ii) summarizing evidence with multiple strategy cost-effectiveness acceptability (CEA) and expected net loss (ENL) curves and frontiers. However, critical questions remain for the analyst and decision maker of how these techniques can be best employed across multiple strategies to (i) inform clinical and cost inference in presenting evidence, and (ii) summarize evidence of cost effectiveness to inform societal reimbursement decisions where preferences may be risk neutral or somewhat risk averse under the Arrow-Lind theorem. We critically consider how evidence across multiple strategies can be best presented and summarized to inform inference and societal reimbursement decisions, given currently available methods. In the process, we make a number of important original findings. First, in presenting evidence for multiple strategies, the joint distribution of costs and effects on the cost-disutility plane with associated flexible comparators varying across replicates for cost and effect axes ensure full cost and effect inference. Such inference is usually confounded on the cost-effectiveness plane with comparison relative to a fixed origin and axes. Second, in summarizing evidence for risk-neutral societal decision making, ENL curves and frontiers are shown to have advantages over the CEA frontier in directly presenting differences in expected net benefit (ENB). The CEA frontier, while identifying strategies that maximize ENB, only presents their probability of maximizing net benefit (NB) and, hence, fails to explain why strategies maximize ENB at any given threshold value. Third, in summarizing evidence for somewhat risk-averse societal decision making, trade-offs between the strategy maximizing ENB and other potentially optimal strategies with higher probability of maximizing NB should be presented over discrete threshold values where they arise. However, the probabilities informing these trade-offs and associated discrete threshold value regions should be derived from bilateral CEA curves to prevent confounding by other strategies inherent in multiple strategy CEA curves. Based on these findings, a series of recommendations are made for best presenting and summarizing cost-effectiveness evidence for reimbursement decisions when comparing multiple strategies, which are contrasted with advice for comparing two strategies. Implications for joint research and reimbursement decisions are also discussed.

Multiple Objects Fusion Tracker Using a Matching Network for Adaptively Represented Instance Pairs

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

Multiple-object tracking is affected by various sources of distortion, such as occlusion, illumination variations and motion changes. Overcoming these distortions by tracking on RGB frames, such as shifting, has limitations because of material distortions caused by RGB frames. To overcome these distortions, we propose a multiple-object fusion tracker (MOFT), which uses a combination of 3D point clouds and corresponding RGB frames. The MOFT uses a matching function initialized on large-scale external sequences to determine which candidates in the current frame match with the target object in the previous frame. After conducting tracking on a few frames, the initialized matching function is fine-tuned according to the appearance models of target objects. The fine-tuning process of the matching function is constructed as a structured form with diverse matching function branches. In general multiple object tracking situations, scale variations for a scene occur depending on the distance between the target objects and the sensors. If the target objects in various scales are equally represented with the same strategy, information losses will occur for any representation of the target objects. In this paper, the output map of the convolutional layer obtained from a pre-trained convolutional neural network is used to adaptively represent instances without information loss. In addition, MOFT fuses the tracking results obtained from each modality at the decision level to compensate the tracking failures of each modality using basic belief assignment, rather than fusing modalities by selectively using the features of each modality. Experimental results indicate that the proposed tracker provides state-of-the-art performance considering multiple objects tracking (MOT) and KITTIbenchmarks. PMID:28420194

A guide to multi-objective optimization for ecological problems with an application to cackling goose management

USGS Publications Warehouse

Williams, Perry J.; Kendall, William L.

2017-01-01

Choices in ecological research and management are the result of balancing multiple, often competing, objectives. Multi-objective optimization (MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including engineering, economics, and operations research. However, its application for solving ecological problems has been sparse, perhaps due to a lack of widespread understanding. Thus, our objective was to provide an accessible primer on MOO, including a review of methods common in other fields, a review of their application in ecology, and a demonstration to an applied resource management problem.A large class of methods for solving MOO problems can be separated into two strategies: modelling preferences pre-optimization (the a priori strategy), or modelling preferences post-optimization (the a posteriori strategy). The a priori strategy requires describing preferences among objectives without knowledge of how preferences affect the resulting decision. In the a posteriori strategy, the decision maker simultaneously considers a set of solutions (the Pareto optimal set) and makes a choice based on the trade-offs observed in the set. We describe several methods for modelling preferences pre-optimization, including: the bounded objective function method, the lexicographic method, and the weighted-sum method. We discuss modelling preferences post-optimization through examination of the Pareto optimal set. We applied each MOO strategy to the natural resource management problem of selecting a population target for cackling goose (Branta hutchinsii minima) abundance. Cackling geese provide food security to Native Alaskan subsistence hunters in the goose's nesting area, but depredate crops on private agricultural fields in wintering areas. We developed objective functions to represent the competing objectives related to the cackling goose population target and identified an optimal solution first using the a priori strategy, and then by examining trade-offs in the Pareto set using the a posteriori strategy. We used four approaches for selecting a final solution within the a posteriori strategy; the most common optimal solution, the most robust optimal solution, and two solutions based on maximizing a restricted portion of the Pareto set. We discuss MOO with respect to natural resource management, but MOO is sufficiently general to cover any ecological problem that contains multiple competing objectives that can be quantified using objective functions.

A parametric LQ approach to multiobjective control system design

NASA Technical Reports Server (NTRS)

Kyr, Douglas E.; Buchner, Marc

1988-01-01

The synthesis of a constant parameter output feedback control law of constrained structure is set in a multiple objective linear quadratic regulator (MOLQR) framework. The use of intuitive objective functions such as model-following ability and closed-loop trajectory sensitivity, allow multiple objective decision making techniques, such as the surrogate worth tradeoff method, to be applied. For the continuous-time deterministic problem with an infinite time horizon, dynamic compensators as well as static output feedback controllers can be synthesized using a descent Anderson-Moore algorithm modified to impose linear equality constraints on the feedback gains by moving in feasible directions. Results of three different examples are presented, including a unique reformulation of the sensitivity reduction problem.

A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization.

PubMed

Yang, Shaofu; Liu, Qingshan; Wang, Jun

2018-04-01

This paper is concerned with multiple-objective distributed optimization. Based on objective weighting and decision space decomposition, a collaborative neurodynamic approach to multiobjective distributed optimization is presented. In the approach, a system of collaborative neural networks is developed to search for Pareto optimal solutions, where each neural network is associated with one objective function and given constraints. Sufficient conditions are derived for ascertaining the convergence to a Pareto optimal solution of the collaborative neurodynamic system. In addition, it is proved that each connected subsystem can generate a Pareto optimal solution when the communication topology is disconnected. Then, a switching-topology-based method is proposed to compute multiple Pareto optimal solutions for discretized approximation of Pareto front. Finally, simulation results are discussed to substantiate the performance of the collaborative neurodynamic approach. A portfolio selection application is also given.

Pruning a decision tree for selecting computer-related assistive devices for people with disabilities.

PubMed

Chi, Chia-Fen; Tseng, Li-Kai; Jang, Yuh

2012-07-01

Many disabled individuals lack extensive knowledge about assistive technology, which could help them use computers. In 1997, Denis Anson developed a decision tree of 49 evaluative questions designed to evaluate the functional capabilities of the disabled user and choose an appropriate combination of assistive devices, from a selection of 26, that enable the individual to use a computer. In general, occupational therapists guide the disabled users through this process. They often have to go over repetitive questions in order to find an appropriate device. A disabled user may require an alphanumeric entry device, a pointing device, an output device, a performance enhancement device, or some combination of these. Therefore, the current research eliminates redundant questions and divides Anson's decision tree into multiple independent subtrees to meet the actual demand of computer users with disabilities. The modified decision tree was tested by six disabled users to prove it can determine a complete set of assistive devices with a smaller number of evaluative questions. The means to insert new categories of computer-related assistive devices was included to ensure the decision tree can be expanded and updated. The current decision tree can help the disabled users and assistive technology practitioners to find appropriate computer-related assistive devices that meet with clients' individual needs in an efficient manner.

Pitfalls of Counterfactual Thinking in Medical Practice: Preventing Errors by Using More Functional Reference Points

PubMed Central

Petrocelli, John V.

2013-01-01

Background Counterfactual thinking involves mentally simulating alternatives to reality. The current article reviews literature pertaining to the relevance counterfactual thinking has for the quality of medical decision making. Although earlier counterfactual thought research concluded that counterfactuals have important benefits for the individual, there are reasons to believe that counterfactual thinking is also associated with dysfunctional consequences. Of particular focus is whether or not medical experience, and its influence on counterfactual thinking, actually informs or improves medical practice. It is hypothesized that relatively more probable decision alternatives, followed by undesirable outcomes and counterfactual thought responses, can be abandoned for relatively less probable decision alternatives. Design and Methods Building on earlier research demonstrating that counterfactual thinking can impede memory and learning in a decision paradigm with undergraduate students, the current study examines the extent to which earlier findings can be generalized to practicing physicians (N=10). Participants were asked to complete 60 trials of a computerized Monty Hall Problem simulation. Learning by experience was operationalized as the frequency of switch-decisions. Results Although some learning was evidenced by a general increase in switch-decision frequency across block trials, the extent of learning demonstrated was not ideal, nor practical. Conclusions A simple, multiple-trial, decision paradigm demonstrated that doctors fail to learn basic decision-outcome associations through experience. An agenda for future research, which tests the functionality of reference points (other than counterfactual alternatives) for the purposes of medical decision making, is proposed. Significance for public health The quality of healthcare depends heavily on the judgments and decisions made by doctors and other medical professionals. Findings from this research indicate that doctors fail to learn basic decision-outcome associations through experience, as evidenced by the sample’s tendency to select the optimal decision strategy in only 50% of 60 trials (each of which was followed by veridical feedback). These findings suggest that professional experience is unlikely to enhance the quality of medical decision making. Thus, this research has implications for understanding how doctors’ reactions to medical outcomes shape their judgments and affect the degree to which their future treatment intentions are consistent with clinical practice guidelines. The current research is integrated with earlier research on counter-factual thinking, which appears to be a primary element inhibiting the learning of decision-outcome associations. An agenda for future research is proposed. PMID:25170495

[Giving up life in the labyrinth].

PubMed

Portera Sánchez, A

2001-01-01

A brief historic survey of the labyrinth, from prehistoric images carved in stone, to gardens, Renaissance drawings and architectonic constructions will presented. The metaphor of the labyrinths, which began with Theseus killing the Minotaur with the help of Ariadne, can be applied to all: scientific investigation, artistic creation, wickedness, theology ... to life. In these eculiar and chaotic designs, structural simplicity and functional complexity coincide and therefore may produce repeated erroneous decisions. To wander successfully through these labyrinths, caution and repeated decision-makings are required to enable the traveller to reach the desired and elusive center. In each instant, decisions are made in our mind as a consequence of complex cerebral systems, activated by stimuli which originate in the intimate regions of the mind, the most complex labyrinth of all. These types of mental labyrinths are immaterial, without paths or walks, where each successive decision made facing multiple bifurcations, causes the mental traveller to advance until reaching the center. This center deceptively becomes the entrance to another of the innumerable and unknown mental labyrinths that the intimate life proposes.

The Aeronautical Data Link: Decision Framework for Architecture Analysis

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Goode, Plesent W.

2003-01-01

A decision analytic approach that develops optimal data link architecture configuration and behavior to meet multiple conflicting objectives of concurrent and different airspace operations functions has previously been developed. The approach, premised on a formal taxonomic classification that correlates data link performance with operations requirements, information requirements, and implementing technologies, provides a coherent methodology for data link architectural analysis from top-down and bottom-up perspectives. This paper follows the previous research by providing more specific approaches for mapping and transitioning between the lower levels of the decision framework. The goal of the architectural analysis methodology is to assess the impact of specific architecture configurations and behaviors on the efficiency, capacity, and safety of operations. This necessarily involves understanding the various capabilities, system level performance issues and performance and interface concepts related to the conceptual purpose of the architecture and to the underlying data link technologies. Efficient and goal-directed data link architectural network configuration is conditioned on quantifying the risks and uncertainties associated with complex structural interface decisions. Deterministic and stochastic optimal design approaches will be discussed that maximize the effectiveness of architectural designs.

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.

A forward error correction technique using a high-speed, high-rate single chip codec

NASA Astrophysics Data System (ADS)

Boyd, R. W.; Hartman, W. F.; Jones, Robert E.

The authors describe an error-correction coding approach that allows operation in either burst or continuous modes at data rates of multiple hundreds of megabits per second. Bandspreading is low since the code rate is 7/8 or greater, which is consistent with high-rate link operation. The encoder, along with a hard-decision decoder, fits on a single application-specific integrated circuit (ASIC) chip. Soft-decision decoding is possible utilizing applique hardware in conjunction with the hard-decision decoder. Expected coding gain is a function of the application and is approximately 2.5 dB for hard-decision decoding at 10-5 bit-error rate with phase-shift-keying modulation and additive Gaussian white noise interference. The principal use envisioned for this technique is to achieve a modest amount of coding gain on high-data-rate, bandwidth-constrained channels. Data rates of up to 300 Mb/s can be accommodated by the codec chip. The major objective is burst-mode communications, where code words are composed of 32 n data bits followed by 32 overhead bits.

Objective consensus from decision trees.

PubMed

Putora, Paul Martin; Panje, Cedric M; Papachristofilou, Alexandros; Dal Pra, Alan; Hundsberger, Thomas; Plasswilm, Ludwig

2014-12-05

Consensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources. Based on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus. Based on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters. Recommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.

Mesolimbic Dopamine Signals the Value of Work

PubMed Central

Hamid, Arif A.; Pettibone, Jeffrey R.; Mabrouk, Omar S.; Hetrick, Vaughn L.; Schmidt, Robert; Vander Weele, Caitlin M.; Kennedy, Robert T.; Aragona, Brandon J.; Berke, Joshua D.

2015-01-01

Dopamine cell firing can encode errors in reward prediction, providing a learning signal to guide future behavior. Yet dopamine is also a key modulator of motivation, invigorating current behavior. Existing theories propose that fast (“phasic”) dopamine fluctuations support learning, while much slower (“tonic”) dopamine changes are involved in motivation. We examined dopamine release in the nucleus accumbens across multiple time scales, using complementary microdialysis and voltammetric methods during adaptive decision-making. We first show that minute-by-minute dopamine levels covary with reward rate and motivational vigor. We then show that second-by-second dopamine release encodes an estimate of temporally-discounted future reward (a value function). We demonstrate that changing dopamine immediately alters willingness to work, and reinforces preceding action choices by encoding temporal-difference reward prediction errors. Our results indicate that dopamine conveys a single, rapidly-evolving decision variable, the available reward for investment of effort, that is employed for both learning and motivational functions. PMID:26595651

Computer Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2013-03-01

the decisions made by each individual modality. Fusion of features is the simple concatenation of feature vectors from multiple modalities to be...of Features BayesNet MDL 330 LibSVM PCA 80 J48 Wrapper Evaluator 11 3.5.3 Ensemble Based Decision Level Fusion. In ensemble learning multiple ...The high fusion percentages validate our hypothesis that by combining features from multiple modalities, classification accuracy can be improved. As

Monitoring and predicting cognitive state and performance via physiological correlates of neuronal signals.

PubMed

Russo, Michael B; Stetz, Melba C; Thomas, Maria L

2005-07-01

Judgment, decision making, and situational awareness are higher-order mental abilities critically important to operational cognitive performance. Higher-order mental abilities rely on intact functioning of multiple brain regions, including the prefrontal, thalamus, and parietal areas. Real-time monitoring of individuals for cognitive performance capacity via an approach based on sampling multiple neurophysiologic signals and integrating those signals with performance prediction models potentially provides a method of supporting warfighters' and commanders' decision making and other operationally relevant mental processes and is consistent with the goals of augmented cognition. Cognitive neurophysiological assessments that directly measure brain function and subsequent cognition include positron emission tomography, functional magnetic resonance imaging, mass spectroscopy, near-infrared spectroscopy, magnetoencephalography, and electroencephalography (EEG); however, most direct measures are not practical to use in operational environments. More practical, albeit indirect measures that are generated by, but removed from the actual neural sources, are movement activity, oculometrics, heart rate, and voice stress signals. The goal of the papers in this section is to describe advances in selected direct and indirect cognitive neurophysiologic monitoring techniques as applied for the ultimate purpose of preventing operational performance failures. These papers present data acquired in a wide variety of environments, including laboratory, simulator, and clinical arenas. The papers discuss cognitive neurophysiologic measures such as digital signal processing wrist-mounted actigraphy; oculometrics including blinks, saccadic eye movements, pupillary movements, the pupil light reflex; and high-frequency EEG. These neurophysiological indices are related to cognitive performance as measured through standard test batteries and simulators with conditions including sleep loss, time on task, and aviation flight-induced fatigue.

Linking functional diversity and social actor strategies in a framework for interdisciplinary analysis of nature's benefits to society

PubMed Central

Díaz, Sandra; Cáceres, Daniel M.; Trainor, Sarah F.; Pérez-Harguindeguy, Natalia; Bret-Harte, M. Syndonia; Finegan, Bryan; Peña-Claros, Marielos; Poorter, Lourens

2011-01-01

The crucial role of biodiversity in the links between ecosystems and societies has been repeatedly highlighted both as source of wellbeing and as a target of human actions, but not all aspects of biodiversity are equally important to different ecosystem services. Similarly, different social actors have different perceptions of and access to ecosystem services, and therefore, they have different wants and capacities to select directly or indirectly for particular biodiversity and ecosystem characteristics. Their choices feed back onto the ecosystem services provided to all parties involved and in turn, affect future decisions. Despite this recognition, the research communities addressing biodiversity, ecosystem services, and human outcomes have yet to develop frameworks that adequately treat the multiple dimensions and interactions in the relationship. Here, we present an interdisciplinary framework for the analysis of relationships between functional diversity, ecosystem services, and human actions that is applicable to specific social environmental systems at local scales. We connect the mechanistic understanding of the ecological role of diversity with its social relevance: ecosystem services. The framework permits connections between functional diversity components and priorities of social actors using land use decisions and ecosystem services as the main links between these ecological and social components. We propose a matrix-based method that provides a transparent and flexible platform for quantifying and integrating social and ecological information and negotiating potentially conflicting land uses among multiple social actors. We illustrate the applicability of our framework by way of land use examples from temperate to subtropical South America, an area of rapid social and ecological change. PMID:21220325

The Decision Path Not Taken

PubMed Central

Connor, Charles E.; Stuphorn, Veit

2017-01-01

Real-life decisions often involve multiple intermediate choices among competing, interdependent options. Lorteije et al. (2015) introduce a new paradigm for dissecting the neural strategies underlying such decisions. PMID:26402598

Using histograms to introduce randomization in the generation of ensembles of decision trees

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick; Littau, David

2005-02-22

A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.

The alcoholic brain: neural bases of impaired reward-based decision-making in alcohol use disorders.

PubMed

Galandra, Caterina; Basso, Gianpaolo; Cappa, Stefano; Canessa, Nicola

2018-03-01

Neuroeconomics is providing insights into the neural bases of decision-making in normal and pathological conditions. In the neuropsychiatric domain, this discipline investigates how abnormal functioning of neural systems associated with reward processing and cognitive control promotes different disorders, and whether such evidence may inform treatments. This endeavor is crucial when studying different types of addiction, which share a core promoting mechanism in the imbalance between impulsive subcortical neural signals associated with immediate pleasurable outcomes and inhibitory signals mediated by a prefrontal reflective system. The resulting impairment in behavioral control represents a hallmark of alcohol use disorders (AUDs), a chronic relapsing disorder characterized by excessive alcohol consumption despite devastating consequences. This review aims to summarize available magnetic resonance imaging (MRI) evidence on reward-related decision-making alterations in AUDs, and to envision possible future research directions. We review functional MRI (fMRI) studies using tasks involving monetary rewards, as well as MRI studies relating decision-making parameters to neurostructural gray- or white-matter metrics. The available data suggest that excessive alcohol exposure affects neural signaling within brain networks underlying adaptive behavioral learning via the implementation of prediction errors. Namely, weaker ventromedial prefrontal cortex activity and altered connectivity between ventral striatum and dorsolateral prefrontal cortex likely underpin a shift from goal-directed to habitual actions which, in turn, might underpin compulsive alcohol consumption and relapsing episodes despite adverse consequences. Overall, these data highlight abnormal fronto-striatal connectivity as a candidate neurobiological marker of impaired choice in AUDs. Further studies are needed, however, to unveil its implications in the multiple facets of decision-making.

Reduced Abd-B Hox function during kidney development results in lineage infidelity.

PubMed

Magella, Bliss; Mahoney, Robert; Adam, Mike; Potter, S Steven

2018-06-15

Hox genes can function as key drivers of segment identity, with Hox mutations in Drosophila often resulting in dramatic homeotic transformations. In addition, however, they can serve other essential functions. In mammals, the study of Hox gene roles in development is complicated by the presence of four Hox clusters with a total of 39 genes showing extensive functional overlap. In this study, in order to better understand shared core Hox functions, we examined kidney development in mice with frameshift mutations of multiple Abd-B type Hox genes. The resulting phenotypes included dramatically reduced branching morphogenesis of the ureteric bud, premature depletion of nephron progenitors and abnormal development of the stromal compartment. Most unexpected, however, we also observed a cellular level lineage infidelity in nephron segments. Scattered cells within the proximal tubules, for example, expressed genes normally expressed only in collecting ducts. Multiple combinations of inappropriate nephron segment specific marker expression were found. In some cases, cells within a tubule showed incorrect identity, while in other cases cells showed ambiguous character, with simultaneous expression of genes associated with more than one nephron segment. These results give evidence that Hox genes have an overlapping core function at the cellular level in driving and/or maintaining correct differentiation decisions. Copyright © 2018 Elsevier Inc. All rights reserved.

Cognitive decline impairs financial and health literacy among community-based older persons without dementia

PubMed Central

Boyle, Patricia A.; Yu, Lei; Wilson, Robert S.; Segawa, Eisuke; Buchman, Aron S.; Bennett, David A.

2013-01-01

Literacy is an important determinant of health and well-being across the lifespan but is critical in aging, when many influential health and financial decisions are made. Prior studies suggest that older persons exhibit lower literacy than younger persons, particularly in the domains of financial and health literacy, but the reasons why remain unknown. The objectives of this study were to: a) examine pathways linking diverse resources (i.e., education, word knowledge, cognitive function, and decision making style) to health and financial literacy among older persons and determine the extent to which the relation of age with literacy represents a direct effect versus an indirect effect due to decrements in specific cognitive functions (i.e., executive functions and episodic memory), and b) test the hypothesis that declines in executive function and episodic memory are associated with lower literacy among older persons without dementia. 645 community-based older persons without dementia underwent detailed assessments of diverse resources, including education, word knowledge, cognitive function (i.e., executive function, episodic memory) and decision making style (i.e., risk aversion), and completed a measure of literacy that included items similar to those assessed in the Health and Retirement Study, such as numeracy, financial concepts such as compound inflation and knowledge of stocks and bonds, and important health concepts such as understanding of drug risk and Medicare Part D. Path analysis revealed a strong effect of age on literacy, with about half of the effect of age on literacy due to decrements in executive functions and episodic memory. In addition, executive function had an indirect effect on literacy via decision making style (i.e., risk aversion), and education and word knowledge had independent effects on literacy. Finally, among (n=447) persons with repeated cognitive assessments available for up to 14 years, regression analysis supported the association of multiple resources with literacy; moreover, more rapid declines in executive function and episodic memory over an average of 6.4 years prior to the literacy assessment predicted lower literacy scores (p’s<0.02), but rate of decline in word knowledge did not. These findings suggest that diverse individual resources contribute to financial and health literacy and lower literacy in old age is partially due to declines in executive function and episodic memory. PMID:23957225

Cognitive decline impairs financial and health literacy among community-based older persons without dementia.

PubMed

Boyle, Patricia A; Yu, Lei; Wilson, Robert S; Segawa, Eisuke; Buchman, Aron S; Bennett, David A

2013-09-01

Literacy is an important determinant of health and well-being across the life span but is critical in aging, when many influential health and financial decisions are made. Prior studies suggest that older persons exhibit lower literacy than younger persons, particularly in the domains of financial and health literacy, but the reasons why remain unknown. The objectives of this study were to: (a) examine pathways linking diverse resources (i.e., education, word knowledge, cognitive function, and decision making style) to health and financial literacy among older persons and determine the extent to which the relation of age with literacy represents a direct effect versus an indirect effect due to decrements in specific cognitive functions (i.e., executive functions and episodic memory); and (b) test the hypothesis that declines in executive function and episodic memory are associated with lower literacy among older persons without dementia. Six-hundred and forty-five community-based older persons without dementia underwent detailed assessments of diverse resources, including education, word knowledge, cognitive function (i.e., executive function, episodic memory) and decision making style (i.e., risk aversion), and completed a measure of literacy that included items similar to those used in the Health and Retirement Study, such as numeracy, financial concepts such as compound inflation and knowledge of stocks and bonds, and important health concepts such as understanding of drug risk and Medicare Part D. Path analysis revealed a strong effect of age on literacy, with about half of the effect of age on literacy due to decrements in executive functions and episodic memory. In addition, executive function had an indirect effect on literacy via decision making style (i.e., risk aversion), and education and word knowledge had independent effects on literacy. Finally, among (n = 447) persons with repeated cognitive assessments available for up to 14 years, regression analysis supported the association of multiple resources with literacy; moreover, more rapid declines in executive function and episodic memory over an average of 6.4 years prior to the literacy assessment predicted lower literacy scores (ps < 0.02), but rate of decline in word knowledge did not. These findings suggest that diverse individual resources contribute to financial and health literacy and lower literacy in old age is partially due to declines in executive function and episodic memory.

Decision Making in Adults with ADHD

ERIC Educational Resources Information Center

Montyla, Timo; Still, Johanna; Gullberg, Stina; Del Missier, Fabio

2012-01-01

Objectives: This study examined decision-making competence in ADHD by using multiple decision tasks with varying demands on analytic versus affective processes. Methods: Adults with ADHD and healthy controls completed two tasks of analytic decision making, as measured by the Adult Decision-Making Competence (A-DMC) battery, and two affective…

GIS coupled Multiple Criteria based Decision Support for Classification of Urban Coastal Areas in India

NASA Astrophysics Data System (ADS)

Dhiman, R.; Kalbar, P.; Inamdar, A. B.

2017-12-01

Coastal area classification in India is a challenge for federal and state government agencies due to fragile institutional framework, unclear directions in implementation of costal regulations and violations happening at private and government level. This work is an attempt to improvise the objectivity of existing classification methods to synergies the ecological systems and socioeconomic development in coastal cities. We developed a Geographic information system coupled Multi-criteria Decision Making (GIS-MCDM) approach to classify urban coastal areas where utility functions are used to transform the costal features into quantitative membership values after assessing the sensitivity of urban coastal ecosystem. Furthermore, these membership values for costal features are applied in different weighting schemes to derive Coastal Area Index (CAI) which classifies the coastal areas in four distinct categories viz. 1) No Development Zone, 2) Highly Sensitive Zone, 3) Moderately Sensitive Zone and 4) Low Sensitive Zone based on the sensitivity of urban coastal ecosystem. Mumbai, a coastal megacity in India is used as case study for demonstration of proposed method. Finally, uncertainty analysis using Monte Carlo approach to validate the sensitivity of CAI under specific multiple scenarios is carried out. Results of CAI method shows the clear demarcation of coastal areas in GIS environment based on the ecological sensitivity. CAI provides better decision support for federal and state level agencies to classify urban coastal areas according to the regional requirement of coastal resources considering resilience and sustainable development. CAI method will strengthen the existing institutional framework for decision making in classification of urban coastal areas where most effective coastal management options can be proposed.

Shared Decision Making and Autonomy Among US Participants with Multiple Sclerosis in the NARCOMS Registry

PubMed Central

Thomas, Nina; Tyry, Tuula; Fox, Robert J.; Salter, Amber

2017-01-01

Background: Treatment decisions in multiple sclerosis (MS) are affected by many factors and are made by the patient, doctor, or both. With new disease-modifying therapies (DMTs) emerging, the complexity surrounding treatment decisions is increasing, further emphasizing the importance of understanding decision-making preferences. Methods: North American Research Committee on Multiple Sclerosis (NARCOMS) Registry participants completed the Fall 2014 Update survey, which included the Control Preferences Scale (CPS). The CPS consists of five images showing different patient/doctor roles in treatment decision making. The images were collapsed to three categories: patient-centered, shared, and physician-centered decision-making preferences. Associations between decision-making preferences and demographic and clinical factors were evaluated using multivariable logistic regression. Results: Of 7009 participants, 79.3% were women and 93.5% were white (mean [SD] age, 57.6 [10.3] years); 56.7% reported a history of relapses. Patient-centered decision making was most commonly preferred by participants (47.9%), followed by shared decision making (SDM; 42.8%). SDM preference was higher for women and those taking DMTs and increased with age and disease duration (all P < .05). Patient-centered decisions were most common for respondents not taking a DMT at the time of the survey and were preferred by those who had no DMT history compared with those who had previously taken a DMT (P < .0001). There was no difference in SDM preference by current MS disease course after adjusting for other disease-related factors. Conclusions: Responders reported most commonly considering their doctor's opinion before making a treatment decision and making decisions jointly with their doctor. DMT use, gender, and age were associated with decision-making preference. PMID:29270088

Impairment of cognitive abilities and decision making after chronic use of alcohol: the impact of multiple detoxifications.

PubMed

Loeber, Sabine; Duka, Theodora; Welzel, Helga; Nakovics, Helmut; Heinz, Andreas; Flor, Herta; Mann, Karl

2009-01-01

In the present study, the effect of previous detoxifications on prefrontal function and decision making was examined in alcohol-dependent patients. Further, we examined whether the length of abstinence affects cognitive function. Forty-eight alcohol-dependent patients were recruited from an inpatient detoxification treatment facility and cognitive function was compared to a control group of 36 healthy controls. The patient population was then divided into a group of patients with less than two previous detoxifications (LO-detox group, n = 27) and a group of patients with two or more previous detoxifications (HI-detox group, n = 21) and cognitive function was compared. In addition, cognitive function of recently (i.e. less than 16 days; median split) and longer abstinent patients was compared. We assessed prefrontal function, memory function and intelligence. Alcoholics, when compared to healthy controls, performed worse with regard to the performance index Attention/Executive function. Cognitive impairment in these tasks was pronounced in recently abstinent patients. We found no significant differences between HI-detox and LO-detox patients with regard to the Attention/Executive function. However, in the IOWA gambling Task, the HI-detox group seemed to be less able to learn to choose cards from the more advantageous decks over time. Our results provide additional evidence for cognitive impairment of alcohol-dependent patients with regard to tasks sensitive to frontal lobe function and underline the importance of abstinence for these impairments to recover. We found only little evidence for the impairing effects of repeated withdrawal on prefrontal function and we suggest that executive function is affected earlier in dependence.

Connecting synthetic chemistry decisions to cell and genome biology using small-molecule phenotypic profiling

PubMed Central

Wagner, Bridget K.; Clemons, Paul A.

2009-01-01

Discovering small-molecule modulators for thousands of gene products requires multiple stages of biological testing, specificity evaluation, and chemical optimization. Many cellular profiling methods, including cellular sensitivity, gene-expression, and cellular imaging, have emerged as methods to assess the functional consequences of biological perturbations. Cellular profiling methods applied to small-molecule science provide opportunities to use complex phenotypic information to prioritize and optimize small-molecule structures simultaneously against multiple biological endpoints. As throughput increases and cost decreases for such technologies, we see an emerging paradigm of using more information earlier in probe- and drug-discovery efforts. Moreover, increasing access to public datasets makes possible the construction of “virtual” profiles of small-molecule performance, even when multiplexed measurements were not performed or when multidimensional profiling was not the original intent. We review some key conceptual advances in small-molecule phenotypic profiling, emphasizing connections to other information, such as protein-binding measurements, genetic perturbations, and cell states. We argue that to maximally leverage these measurements in probe and drug discovery requires a fundamental connection to synthetic chemistry, allowing the consequences of synthetic decisions to be described in terms of changes in small-molecule profiles. Mining such data in the context of chemical structure and synthesis strategies can inform decisions about chemistry procurement and library development, leading to optimal small-molecule screening collections. PMID:19825513

A method of classification for multisource data in remote sensing based on interval-valued probabilities

NASA Technical Reports Server (NTRS)

Kim, Hakil; Swain, Philip H.

1990-01-01

An axiomatic approach to intervalued (IV) probabilities is presented, where the IV probability is defined by a pair of set-theoretic functions which satisfy some pre-specified axioms. On the basis of this approach representation of statistical evidence and combination of multiple bodies of evidence are emphasized. Although IV probabilities provide an innovative means for the representation and combination of evidential information, they make the decision process rather complicated. It entails more intelligent strategies for making decisions. The development of decision rules over IV probabilities is discussed from the viewpoint of statistical pattern recognition. The proposed method, so called evidential reasoning method, is applied to the ground-cover classification of a multisource data set consisting of Multispectral Scanner (MSS) data, Synthetic Aperture Radar (SAR) data, and digital terrain data such as elevation, slope, and aspect. By treating the data sources separately, the method is able to capture both parametric and nonparametric information and to combine them. Then the method is applied to two separate cases of classifying multiband data obtained by a single sensor. In each case a set of multiple sources is obtained by dividing the dimensionally huge data into smaller and more manageable pieces based on the global statistical correlation information. By a divide-and-combine process, the method is able to utilize more features than the conventional maximum likelihood method.

The Impact of Multiple Concussions on Emotional Distress, Post-Concussive Symptoms, and Neurocognitive Functioning in Active Duty United States Marines Independent of Combat Exposure or Emotional Distress

PubMed Central

Lathan, Corinna E.; Bleiberg, Joseph; Tsao, Jack W.

2014-01-01

Abstract Controversy exists as to whether the lingering effects of concussion on emotional, physical, and cognitive symptoms is because of the effects of brain trauma or purely to emotional factors such as post-traumatic stress disorder or depression. This study examines the independent effects of concussion on persistent symptoms. The Defense Automated Neurobehavioral Assessment, a clinical decision support tool, was used to assess neurobehavioral functioning in 646 United States Marines, all of whom were fit for duty. Marines were assessed for concussion history, post-concussive symptoms, emotional distress, neurocognitive functioning, and deployment history. Results showed that a recent concussion or ever having experienced a concussion was associated with an increase in emotional distress, but not with persistent post-concussive symptoms (PPCS) or neurocognitive functioning. Having had multiple lifetime concussions, however, was associated with greater emotional distress, PPCS, and reduced neurocognitive functioning that needs attention and rapid discrimination, but not for memory-based tasks. These results are independent of deployment history, combat exposure, and symptoms of post-traumatic stress disorder and depression. Results supported earlier findings that a previous concussion is not generally associated with post-concussive symptoms independent of covariates. In contrast with other studies that failed to find a unique contribution for concussion to PPCS, however, evidence of recent and multiple concussion was seen across a range of emotional distress, post-concussive symptoms, and neurocognitive functioning in this study population. Results are discussed in terms of implications for assessing concussion on return from combat. PMID:25003552

Kinetic therapy in multiple trauma patients with severe blunt chest trauma: an analysis at a level-1 trauma center.

PubMed

Zeckey, C; Wendt, K; Mommsen, P; Winkelmann, M; Frömke, C; Weidemann, J; Stübig, T; Krettek, C; Hildebrand, F

2015-01-01

Chest trauma is a relevant risk factor for mortality after multiple trauma. Kinetic therapy (KT) represents a potential treatment option in order to restore pulmonary function. Decision criteria for performing kinetic therapy are not fully elucidated. The purpose of this study was to investigate the decision making process to initiate kinetic therapy in a well defined multiple trauma cohort. A retrospective analysis (2000-2009) of polytrauma patients (age > 16 years, ISS ⩾ 16) with severe chest trauma (AIS(Chest) ⩾ 3) was performed. Patients with AIS(Head) ⩾ 3 were excluded. Patients receiving either kinetic (KT+) or lung protective ventilation strategy (KT-) were compared. Chest trauma was classified according to the AIS(Chest), Pulmonary Contusion Score (PCS), Wagner Jamieson Score and Thoracic Trauma Severity Score (TTS). There were multiple outcome parameters investigated included mortality, posttraumatic complications and clinical data. A multivariate regression analysis was performed. Two hundred and eighty-three patients were included (KT+: n=160; KT-: n=123). AIS(Chest), age and gender were comparable in both groups. There were significant higher values of the ISS, PCS, Wagner Jamieson Score and TTS in group KT+. The incidence of posttraumatic complications and mortality was increased compared to group KT- (p< 0.05). Despite that, kinetic therapy failed to be an independent risk factor for mortality in multivariate logistic regression analysis. Kinetic therapy is an option in severely injured patients with severe chest trauma. Decision making is not only based on anatomical aspects such as the AIS(Chest), but on overall injury severity, pulmonary contusions and physiological deterioration. It could be assumed that the increased mortality in patients receiving KT is primarily caused by these factors and does not reflect an independent adverse effect of KT. Furthermore, KT was not shown to be an independent risk factor for mortality.

Switching of the positive feedback for RAS activation by a concerted function of SOS membrane association domains.

PubMed

Nakamura, Yuki; Hibino, Kayo; Yanagida, Toshio; Sako, Yasushi

2016-01-01

Son of sevenless (SOS) is a guanine nucleotide exchange factor that regulates cell behavior by activating the small GTPase RAS. Recent in vitro studies have suggested that an interaction between SOS and the GTP-bound active form of RAS generates a positive feedback loop that propagates RAS activation. However, it remains unclear how the multiple domains of SOS contribute to the regulation of the feedback loop in living cells. Here, we observed single molecules of SOS in living cells to analyze the kinetics and dynamics of SOS behavior. The results indicate that the histone fold and Grb2-binding domains of SOS concertedly produce an intermediate state of SOS on the cell surface. The fraction of the intermediated state was reduced in positive feedback mutants, suggesting that the feedback loop functions during the intermediate state. Translocation of RAF, recognizing the active form of RAS, to the cell surface was almost abolished in the positive feedback mutants. Thus, the concerted functions of multiple membrane-associating domains of SOS governed the positive feedback loop, which is crucial for cell fate decision regulated by RAS.

A matter of tradeoffs: reintroduction as a multiple objective decision

USGS Publications Warehouse

Converse, Sarah J.; Moore, Clinton T.; Folk, Martin J.; Runge, Michael C.

2013-01-01

Decision making in guidance of reintroduction efforts is made challenging by the substantial scientific uncertainty typically involved. However, a less recognized challenge is that the management objectives are often numerous and complex. Decision makers managing reintroduction efforts are often concerned with more than just how to maximize the probability of reintroduction success from a population perspective. Decision makers are also weighing other concerns such as budget limitations, public support and/or opposition, impacts on the ecosystem, and the need to consider not just a single reintroduction effort, but conservation of the entire species. Multiple objective decision analysis is a powerful tool for formal analysis of such complex decisions. We demonstrate the use of multiple objective decision analysis in the case of the Florida non-migratory whooping crane reintroduction effort. In this case, the State of Florida was considering whether to resume releases of captive-reared crane chicks into the non-migratory whooping crane population in that state. Management objectives under consideration included maximizing the probability of successful population establishment, minimizing costs, maximizing public relations benefits, maximizing the number of birds available for alternative reintroduction efforts, and maximizing learning about the demographic patterns of reintroduced whooping cranes. The State of Florida engaged in a collaborative process with their management partners, first, to evaluate and characterize important uncertainties about system behavior, and next, to formally evaluate the tradeoffs between objectives using the Simple Multi-Attribute Rating Technique (SMART). The recommendation resulting from this process, to continue releases of cranes at a moderate intensity, was adopted by the State of Florida in late 2008. Although continued releases did not receive support from the International Whooping Crane Recovery Team, this approach does provide a template for the formal, transparent consideration of multiple, potentially competing, objectives in reintroduction decision making.

A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging.

PubMed

Nair, Shalini Rajandran; Tan, Li Kuo; Mohd Ramli, Norlisah; Lim, Shen Yang; Rahmat, Kartini; Mohd Nor, Hazman

2013-06-01

To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD). 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3. Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified. Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.

Risky Decision Making in Neurofibromatosis Type 1: An Exploratory Study

PubMed Central

Jonas, Rachel K.; Roh, EunJi; Montojo, Caroline A.; Pacheco, Laura A.; Rosser, Tena; Silva, Alcino J.; Bearden, Carrie E.

2016-01-01

Background Neurofibromatosis type 1 (NF1) is a monogenic disorder affecting cognitive function. About one third of children with NF1 have attentional disorders, and the cognitive phenotype is characterized by impairment in prefrontally-mediated functions. Mouse models of NF1 show irregularities in GABA release and striatal dopamine metabolism. We hypothesized that youth with NF1 would show abnormal behavior and neural activity on a task of risk-taking reliant on prefrontal-striatal circuits. Methods Youth with NF1 (N=29) and demographically comparable healthy controls (N=22), ages 8-19, were administered a developmentally sensitive gambling task, in which they chose between low-risk gambles with a high probability of obtaining a small reward, and high-risk gambles with a low probability of obtaining a large reward. We used functional magnetic resonance imaging (fMRI) to investigate neural activity associated with risky decision making, as well as age-associated changes in these behavioral and neural processes. Results Behaviorally, youth with NF1 tended to make fewer risky decisions than controls. Neuroimaging analyses revealed significantly reduced neural activity across multiple brain regions involved in higher-order semantic processing and motivation (i.e., anterior cingulate, paracingulate, supramarginal, and angular gyri) in patients with NF1 relative to controls during the task. We also observed atypical age-associated changes in neural activity in patients with NF1, such that during risk taking, neural activity tended to decrease with age in controls, whereas it tended to increase with age in patients with NF1. Conclusions Findings suggest that developmental trajectories of neural activity during risky decision-making may be disrupted in youth with NF1. PMID:28736755

Demand driven decision support for efficient water resources allocation in irrigated agriculture

NASA Astrophysics Data System (ADS)

Schuetze, Niels; Grießbach, Ulrike Ulrike; Röhm, Patric; Stange, Peter; Wagner, Michael; Seidel, Sabine; Werisch, Stefan; Barfus, Klemens

2014-05-01

Due to climate change, extreme weather conditions, such as longer dry spells in the summer months, may have an increasing impact on the agriculture in Saxony (Eastern Germany). For this reason, and, additionally, declining amounts of rainfall during the growing season the use of irrigation will be more important in future in Eastern Germany. To cope with this higher demand of water, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from the optimized agronomic response at farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF) which provide the estimated yield subject to the minimum amount of irrigation water. These functions take into account the different soil types, crops and stochastically generated climate scenarios. By applying mathematical interpolation and optimization techniques, the SCWPF's are used to compute the water demand considering different constraints, for instance variable and fix costs or the producer price. This generic approach enables the computation for both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance Irrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies for an effective and efficient utilization of water in order to meet future demands. The prototype is implemented as a web-based decision support system and it is based on a service-oriented geo-database architecture.

Analyzing Test-Taking Behavior: Decision Theory Meets Psychometric Theory.

PubMed

Budescu, David V; Bo, Yuanchao

2015-12-01

We investigate the implications of penalizing incorrect answers to multiple-choice tests, from the perspective of both test-takers and test-makers. To do so, we use a model that combines a well-known item response theory model with prospect theory (Kahneman and Tversky, Prospect theory: An analysis of decision under risk, Econometrica 47:263-91, 1979). Our results reveal that when test-takers are fully informed of the scoring rule, the use of any penalty has detrimental effects for both test-takers (they are always penalized in excess, particularly those who are risk averse and loss averse) and test-makers (the bias of the estimated scores, as well as the variance and skewness of their distribution, increase as a function of the severity of the penalty).

Network meta-analysis of diagnostic test accuracy studies identifies and ranks the optimal diagnostic tests and thresholds for health care policy and decision-making.

PubMed

Owen, Rhiannon K; Cooper, Nicola J; Quinn, Terence J; Lees, Rosalind; Sutton, Alex J

2018-07-01

Network meta-analyses (NMA) have extensively been used to compare the effectiveness of multiple interventions for health care policy and decision-making. However, methods for evaluating the performance of multiple diagnostic tests are less established. In a decision-making context, we are often interested in comparing and ranking the performance of multiple diagnostic tests, at varying levels of test thresholds, in one simultaneous analysis. Motivated by an example of cognitive impairment diagnosis following stroke, we synthesized data from 13 studies assessing the efficiency of two diagnostic tests: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), at two test thresholds: MMSE <25/30 and <27/30, and MoCA <22/30 and <26/30. Using Markov chain Monte Carlo (MCMC) methods, we fitted a bivariate network meta-analysis model incorporating constraints on increasing test threshold, and accounting for the correlations between multiple test accuracy measures from the same study. We developed and successfully fitted a model comparing multiple tests/threshold combinations while imposing threshold constraints. Using this model, we found that MoCA at threshold <26/30 appeared to have the best true positive rate, whereas MMSE at threshold <25/30 appeared to have the best true negative rate. The combined analysis of multiple tests at multiple thresholds allowed for more rigorous comparisons between competing diagnostics tests for decision making. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Incorporating the patient experience into regulatory decision making in the USA, Europe, and Canada.

PubMed

Kluetz, Paul G; O'Connor, Daniel J; Soltys, Katherine

2018-05-01

The clinical development of cancer therapeutics is a global undertaking, and incorporation of the patient experience into the clinical decision-making process is of increasing interest to the international regulatory and health policy community. Disease and treatment-related symptoms and their effect on patient function and health-related quality of life are important outcomes to consider. The identification of methods to scientifically assess, analyse, interpret, and present these clinical outcomes requires sustained international collaboration by multiple stakeholders including patients, clinicians, scientists, and policy makers. Several data sources can be considered to capture the patient experience, including patient-reported outcome (PRO) measures, performance measures, wearable devices, and biosensors, as well as the careful collection and analysis of clinical events and supportive care medications. In this Policy Review, we focus on PRO measures and present the perspectives of three international regulatory scientists to identify areas of common ground regarding opportunities to incorporate rigorous PRO data into the regulatory decision-making process. Copyright © 2018 Elsevier Ltd. All rights reserved.

The role of medial prefrontal cortex in memory and decision making.

PubMed

Euston, David R; Gruber, Aaron J; McNaughton, Bruce L

2012-12-20

Some have claimed that the medial prefrontal cortex (mPFC) mediates decision making. Others suggest mPFC is selectively involved in the retrieval of remote long-term memory. Yet others suggests mPFC supports memory and consolidation on time scales ranging from seconds to days. How can all these roles be reconciled? We propose that the function of the mPFC is to learn associations between context, locations, events, and corresponding adaptive responses, particularly emotional responses. Thus, the ubiquitous involvement of mPFC in both memory and decision making may be due to the fact that almost all such tasks entail the ability to recall the best action or emotional response to specific events in a particular place and time. An interaction between multiple memory systems may explain the changing importance of mPFC to different types of memories over time. In particular, mPFC likely relies on the hippocampus to support rapid learning and memory consolidation. Copyright © 2012 Elsevier Inc. All rights reserved.

Capturing the temporal evolution of choice across prefrontal cortex

PubMed Central

Hunt, Laurence T; Behrens, Timothy EJ; Hosokawa, Takayuki; Wallis, Jonathan D; Kennerley, Steven W

2015-01-01

Activity in prefrontal cortex (PFC) has been richly described using economic models of choice. Yet such descriptions fail to capture the dynamics of decision formation. Describing dynamic neural processes has proven challenging due to the problem of indexing the internal state of PFC and its trial-by-trial variation. Using primate neurophysiology and human magnetoencephalography, we here recover a single-trial index of PFC internal states from multiple simultaneously recorded PFC subregions. This index can explain the origins of neural representations of economic variables in PFC. It describes the relationship between neural dynamics and behaviour in both human and monkey PFC, directly bridging between human neuroimaging data and underlying neuronal activity. Moreover, it reveals a functionally dissociable interaction between orbitofrontal cortex, anterior cingulate cortex and dorsolateral PFC in guiding cost-benefit decisions. We cast our observations in terms of a recurrent neural network model of choice, providing formal links to mechanistic dynamical accounts of decision-making. DOI: http://dx.doi.org/10.7554/eLife.11945.001 PMID:26653139

Success in School for Justice-Involved Girls: Do Specific Aspects of Developmental Immaturity Matter?

PubMed Central

Haney-Caron, Emily; Goldstein, Naomi E. S.; Giallella, Christy L.; Kemp, Kathleen; Romaine, Christina Riggs

2016-01-01

Developmental immaturity (DI) may help explain some of the variability in aspects of academic achievement among girls in the juvenile justice system, a population with high rates of truancy, dropout, and school failure. This study examined the relationships among the decision making and independent functioning components of DI, verbal intelligence, and academic achievement within this population. Using data from 60 girls in residential juvenile justice facilities, multiple regression analyses indicated that verbal IQ moderated the relationship between the DI construct of decision making and academic achievement. Self-reported school attendance and number of previous arrests did not significantly mediate the relationship between DI and academic achievement. These results may indicate that the decision-making factor of DI may be particularly important, and, if results are replicated, future intervention efforts could focus more on improving this skill within this juvenile justice population. Additionally, the overall importance of the full DI construct is an important area of future study. PMID:28082833

The neural representation of unexpected uncertainty during value-based decision making.

PubMed

Payzan-LeNestour, Elise; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P

2013-07-10

Uncertainty is an inherent property of the environment and a central feature of models of decision-making and learning. Theoretical propositions suggest that one form, unexpected uncertainty, may be used to rapidly adapt to changes in the environment, while being influenced by two other forms: risk and estimation uncertainty. While previous studies have reported neural representations of estimation uncertainty and risk, relatively little is known about unexpected uncertainty. Here, participants performed a decision-making task while undergoing functional magnetic resonance imaging (fMRI), which, in combination with a Bayesian model-based analysis, enabled us to separately examine each form of uncertainty examined. We found representations of unexpected uncertainty in multiple cortical areas, as well as the noradrenergic brainstem nucleus locus coeruleus. Other unique cortical regions were found to encode risk, estimation uncertainty, and learning rate. Collectively, these findings support theoretical models in which several formally separable uncertainty computations determine the speed of learning. Copyright © 2013 Elsevier Inc. All rights reserved.

Primary care clinicians' experiences with treatment decision making for older persons with multiple conditions.

PubMed

Fried, Terri R; Tinetti, Mary E; Iannone, Lynne

2011-01-10

Clinicians are caring for an increasing number of older patients with multiple diseases in the face of uncertainty concerning the benefits and harms associated with guideline-directed interventions. Understanding how primary care clinicians approach treatment decision making for these patients is critical to the design of interventions to improve the decision-making process. Focus groups were conducted with 40 primary care clinicians (physicians, nurse practitioners, and physician assistants) in academic, community, and Veterans Affairs-affiliated primary care practices. Participants were given open-ended questions about their approach to treatment decision making for older persons with multiple medical conditions. Responses were organized into themes using qualitative content analysis. The participants were concerned about their patients' ability to adhere to complex regimens derived from guideline-directed care. There was variability in beliefs regarding, and approaches to balancing, the benefits and harms of guideline-directed care. There was also variability regarding how the participants involved patients in the process of decision making, with clinicians describing conflicts between their own and their patients' goals. The participants listed a number of barriers to making good treatment decisions, including the lack of outcome data, the role of specialists, patient and family expectations, and insufficient time and reimbursement. The experiences of practicing clinicians suggest that they struggle with the uncertainties of applying disease-specific guidelines to their older patients with multiple conditions. To improve decision making, they need more data, alternative guidelines, approaches to reconciling their own and their patients' priorities, the support of their subspecialist colleagues, and an altered reimbursement system.

Analytical group decision making in natural resources: Methodology and application

USGS Publications Warehouse

Schmoldt, D.L.; Peterson, D.L.

2000-01-01

Group decision making is becoming increasingly important in natural resource management and associated scientific applications, because multiple values are treated coincidentally in time and space, multiple resource specialists are needed, and multiple stakeholders must be included in the decision process. Decades of social science research on decision making in groups have provided insights into the impediments to effective group processes and on techniques that can be applied in a group context. Nevertheless, little integration and few applications of these results have occurred in resource management decision processes, where formal groups are integral, either directly or indirectly. A group decision-making methodology is introduced as an effective approach for temporary, formal groups (e.g., workshops). It combines the following three components: (1) brainstorming to generate ideas; (2) the analytic hierarchy process to produce judgments, manage conflict, enable consensus, and plan for implementation; and (3) a discussion template (straw document). Resulting numerical assessments of alternative decision priorities can be analyzed statistically to indicate where group member agreement occurs and where priority values are significantly different. An application of this group process to fire research program development in a workshop setting indicates that the process helps focus group deliberations; mitigates groupthink, nondecision, and social loafing pitfalls; encourages individual interaction; identifies irrational judgments; and provides a large amount of useful quantitative information about group preferences. This approach can help facilitate scientific assessments and other decision-making processes in resource management.

Managing data from multiple disciplines, scales, and sites to support synthesis and modeling

USGS Publications Warehouse

Olson, R. J.; Briggs, J. M.; Porter, J.H.; Mah, Grant R.; Stafford, S.G.

1999-01-01

The synthesis and modeling of ecological processes at multiple spatial and temporal scales involves bringing together and sharing data from numerous sources. This article describes a data and information system model that facilitates assembling, managing, and sharing diverse data from multiple disciplines, scales, and sites to support integrated ecological studies. Cross-site scientific-domain working groups coordinate the development of data associated with their particular scientific working group, including decisions about data requirements, data to be compiled, data formats, derived data products, and schedules across the sites. The Web-based data and information system consists of nodes for each working group plus a central node that provides data access, project information, data query, and other functionality. The approach incorporates scientists and computer experts in the working groups and provides incentives for individuals to submit documented data to the data and information system.

Integrated Forecast-Decision Systems For River Basin Planning and Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.

2005-12-01

A central application of climatology, meteorology, and hydrology is the generation of reliable forecasts for water resources management. In principle, effective use of forecasts could improve water resources management by providing extra protection against floods, mitigating the adverse effects of droughts, generating more hydropower, facilitating recreational activities, and minimizing the impacts of extreme events on the environment and the ecosystems. In practice, however, realization of these benefits depends on three requisite elements. First is the skill and reliability of forecasts. Second is the existence of decision support methods/systems with the ability to properly utilize forecast information. And third is the capacity of the institutional infrastructure to incorporate the information provided by the decision support systems into the decision making processes. This presentation discusses several decision support systems (DSS) using ensemble forecasting that have been developed by the Georgia Water Resources Institute for river basin management. These DSS are currently operational in Africa, Europe, and the US and address integrated water resources and energy planning and management in river basins with multiple water uses, multiple relevant temporal and spatial scales, and multiple decision makers. The article discusses the methods used and advocates that the design, development, and implementation of effective forecast-decision support systems must bring together disciplines, people, and institutions necessary to address today's complex water resources challenges.

Multiple Criteria Evaluation of Quality and Optimisation of e-Learning System Components

ERIC Educational Resources Information Center

Kurilovas, Eugenijus; Dagiene, Valentina

2010-01-01

The main research object of the paper is investigation and proposal of the comprehensive Learning Object Repositories (LORs) quality evaluation tool suitable for their multiple criteria decision analysis, evaluation and optimisation. Both LORs "internal quality" and "quality in use" evaluation (decision making) criteria are analysed in the paper.…

Evaluator-blinded trial evaluating nurse-led immunotherapy DEcision Coaching In persons with relapsing-remitting Multiple Sclerosis (DECIMS) and accompanying process evaluation: study protocol for a cluster randomised controlled trial.

PubMed

Rahn, Anne Christin; Köpke, Sascha; Kasper, Jürgen; Vettorazzi, Eik; Mühlhauser, Ingrid; Heesen, Christoph

2015-03-21

Multiple sclerosis is a chronic neurological condition usually starting in early adulthood and regularly leading to severe disability. Immunotherapy options are growing in number and complexity, while costs of treatments are high and adherence rates remain low. Therefore, treatment decision-making has become more complex for patients. Structured decision coaching, based on the principles of evidence-based patient information and shared decision-making, has the potential to facilitate participation of individuals in the decision-making process. This cluster randomised controlled trial follows the assumption that decision coaching by trained nurses, using evidence-based patient information and preference elicitation, will facilitate informed choices and induce higher decision quality, as well as better decisional adherence. The decision coaching programme will be evaluated through an evaluator-blinded superiority cluster randomised controlled trial, including 300 patients with suspected or definite relapsing-remitting multiple sclerosis, facing an immunotherapy decision. The clusters are 12 multiple sclerosis outpatient clinics in Germany. Further, the trial will be accompanied by a mixed-methods process evaluation and a cost-effectiveness study. Nurses in the intervention group will be trained in shared decision-making, coaching, and evidence-based patient information principles. Patients who meet the inclusion criteria will receive decision coaching (intervention group) with up to three face-to-face coaching sessions with a trained nurse (decision coach) or counselling as usual (control group). Patients in both groups will be given access to an evidence-based online information tool. The primary outcome is 'informed choice' after six months, assessed with the multi-dimensional measure of informed choice including the sub-dimensions risk knowledge (questionnaire), attitude concerning immunotherapy (questionnaire), and immunotherapy uptake (telephone survey). Secondary outcomes include decisional conflict, adherence to immunotherapy decisions, autonomy preference, planned behaviour, coping self-efficacy, and perceived involvement in coaching and decisional encounters. Safety outcomes are comprised of anxiety and depression and disease-specific quality of life. This trial will assess the effectiveness of a new model of patient decision support concerning MS-immunotherapy options. The delegation of treatment information provision from physicians to trained nurses bears the potential to change current doctor-focused practice in Germany. Current Controlled Trials (identifier: ISRCTN37929939 ), May 27, 2014.

Computational mate choice: theory and empirical evidence.

PubMed

Castellano, Sergio; Cadeddu, Giorgia; Cermelli, Paolo

2012-06-01

The present review is based on the thesis that mate choice results from information-processing mechanisms governed by computational rules and that, to understand how females choose their mates, we should identify which are the sources of information and how they are used to make decisions. We describe mate choice as a three-step computational process and for each step we present theories and review empirical evidence. The first step is a perceptual process. It describes the acquisition of evidence, that is, how females use multiple cues and signals to assign an attractiveness value to prospective mates (the preference function hypothesis). The second step is a decisional process. It describes the construction of the decision variable (DV), which integrates evidence (private information by direct assessment), priors (public information), and value (perceived utility) of prospective mates into a quantity that is used by a decision rule (DR) to produce a choice. We make the assumption that females are optimal Bayesian decision makers and we derive a formal model of DV that can explain the effects of preference functions, mate copying, social context, and females' state and condition on the patterns of mate choice. The third step of mating decision is a deliberative process that depends on the DRs. We identify two main categories of DRs (absolute and comparative rules), and review the normative models of mate sampling tactics associated to them. We highlight the limits of the normative approach and present a class of computational models (sequential-sampling models) that are based on the assumption that DVs accumulate noisy evidence over time until a decision threshold is reached. These models force us to rethink the dichotomy between comparative and absolute decision rules, between discrimination and recognition, and even between rational and irrational choice. Since they have a robust biological basis, we think they may represent a useful theoretical tool for behavioural ecologist interested in integrating proximate and ultimate causes of mate choice. Copyright © 2012 Elsevier B.V. All rights reserved.

Cognitive performance predicts treatment decisional abilities in mild to moderate dementia.

PubMed

Gurrera, R J; Moye, J; Karel, M J; Azar, A R; Armesto, J C

2006-05-09

To examine the contribution of neuropsychological test performance to treatment decision-making capacity in community volunteers with mild to moderate dementia. The authors recruited volunteers (44 men, 44 women) with mild to moderate dementia from the community. Subjects completed a battery of 11 neuropsychological tests that assessed auditory and visual attention, logical memory, language, and executive function. To measure decision making capacity, the authors administered the Capacity to Consent to Treatment Interview, the Hopemont Capacity Assessment Interview, and the MacCarthur Competence Assessment Tool--Treatment. Each of these instruments individually scores four decisional abilities serving capacity: understanding, appreciation, reasoning, and expression of choice. The authors used principal components analysis to generate component scores for each ability across instruments, and to extract principal components for neuropsychological performance. Multiple linear regression analyses demonstrated that neuropsychological performance significantly predicted all four abilities. Specifically, it predicted 77.8% of the common variance for understanding, 39.4% for reasoning, 24.6% for appreciation, and 10.2% for expression of choice. Except for reasoning and appreciation, neuropsychological predictor (beta) profiles were unique for each ability. Neuropsychological performance substantially and differentially predicted capacity for treatment decisions in individuals with mild to moderate dementia. Relationships between elemental cognitive function and decisional capacity may differ in individuals whose decisional capacity is impaired by other disorders, such as mental illness.

Resting-State Functional Connectivity Underlying Costly Punishment: A Machine-Learning Approach.

PubMed

Feng, Chunliang; Zhu, Zhiyuan; Gu, Ruolei; Wu, Xia; Luo, Yue-Jia; Krueger, Frank

2018-06-08

A large number of studies have demonstrated costly punishment to unfair events across human societies. However, individuals exhibit a large heterogeneity in costly punishment decisions, whereas the neuropsychological substrates underlying the heterogeneity remain poorly understood. Here, we addressed this issue by applying a multivariate machine-learning approach to compare topological properties of resting-state brain networks as a potential neuromarker between individuals exhibiting different punishment propensities. A linear support vector machine classifier obtained an accuracy of 74.19% employing the features derived from resting-state brain networks to distinguish two groups of individuals with different punishment tendencies. Importantly, the most discriminative features that contributed to the classification were those regions frequently implicated in costly punishment decisions, including dorsal anterior cingulate cortex (dACC) and putamen (salience network), dorsomedial prefrontal cortex (dmPFC) and temporoparietal junction (mentalizing network), and lateral prefrontal cortex (central-executive network). These networks are previously implicated in encoding norm violation and intentions of others and integrating this information for punishment decisions. Our findings thus demonstrated that resting-state functional connectivity (RSFC) provides a promising neuromarker of social preferences, and bolster the assertion that human costly punishment behaviors emerge from interactions among multiple neural systems. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Decision making and preferences for acoustic signals in choice situations by female crickets.

PubMed

Gabel, Eileen; Kuntze, Janine; Hennig, R Matthias

2015-08-01

Multiple attributes usually have to be assessed when choosing a mate. Efficient choice of the best mate is complicated if the available cues are not positively correlated, as is often the case during acoustic communication. Because of varying distances of signalers, a female may be confronted with signals of diverse quality at different intensities. Here, we examined how available cues are weighted for a decision by female crickets. Two songs with different temporal patterns and/or sound intensities were presented in a choice paradigm and compared with female responses from a no-choice test. When both patterns were presented at equal intensity, preference functions became wider in choice situations compared with a no-choice paradigm. When the stimuli in two-choice tests were presented at different intensities, this effect was counteracted as preference functions became narrower compared with choice tests using stimuli of equal intensity. The weighting of intensity differences depended on pattern quality and was therefore non-linear. A simple computational model based on pattern and intensity cues reliably predicted female decisions. A comparison of processing schemes suggested that the computations for pattern recognition and directionality are performed in a network with parallel topology. However, the computational flow of information corresponded to serial processing. © 2015. Published by The Company of Biologists Ltd.

A framework for multi-stakeholder decision-making and ...

EPA Pesticide Factsheets

We propose a decision-making framework to compute compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives. In our setting, we shape the stakeholder dis-satisfaction distribution by solving a conditional-value-at-risk (CVaR) minimization problem. The CVaR problem is parameterized by a probability level that shapes the tail of the dissatisfaction distribution. The proposed approach allows us to compute a family of compromise solutions and generalizes multi-stakeholder settings previously proposed in the literature that minimize average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem +and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework that involve complex decision-making processes. We demonstrate the developments using a biowaste facility location case study in which we seek to balance stakeholder priorities on transportation, safety, water quality, and capital costs. This manuscript describes the methodology of a new decision-making framework that computes compromise solutions that balance conflicting priorities of multiple stakeholders on multiple objectives as needed for SHC Decision Science and Support Tools project. A biowaste facility location is employed as the case study

A web-based decision support tool for prognosis simulation in multiple sclerosis.

PubMed

Veloso, Mário

2014-09-01

A multiplicity of natural history studies of multiple sclerosis provides valuable knowledge of the disease progression but individualized prognosis remains elusive. A few decision support tools that assist the clinician in such task have emerged but have not received proper attention from clinicians and patients. The objective of the current work is to implement a web-based tool, conveying decision relevant prognostic scientific evidence, which will help clinicians discuss prognosis with individual patients. Data were extracted from a set of reference studies, especially those dealing with the natural history of multiple sclerosis. The web-based decision support tool for individualized prognosis simulation was implemented with NetLogo, a program environment suited for the development of complex adaptive systems. Its prototype has been launched online; it enables clinicians to predict both the likelihood of CIS to CDMS conversion, and the long-term prognosis of disability level and SPMS conversion, as well as assess and monitor the effects of treatment. More robust decision support tools, which convey scientific evidence and satisfy the needs of clinical practice by helping clinicians discuss prognosis expectations with individual patients, are required. The web-based simulation model herein introduced proposes to be a step forward toward this purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

Perspectives of Patients, Clinicians, and Health System Leaders on Changes Needed to Improve the Health Care and Outcomes of Older Adults With Multiple Chronic Conditions.

PubMed

Ferris, Rosie; Blaum, Caroline; Kiwak, Eliza; Austin, Janet; Esterson, Jessica; Harkless, Gene; Oftedahl, Gary; Parchman, Michael; Van Ness, Peter H; Tinetti, Mary E

2018-06-01

To ascertain perspectives of multiple stakeholders on contributors to inappropriate care for older adults with multiple chronic conditions. Perspectives of 36 purposively sampled patients, clinicians, health systems, and payers were elicited. Data analysis followed a constant comparative method. Structural factors triggering burden and fragmentation include disease-based quality metrics and need to interact with multiple clinicians. The key cultural barrier identified is the assumption that "physicians know best." Inappropriate decision making may result from inattention to trade-offs and adherence to multiple disease guidelines. Stakeholders recommended changes in culture, structure, and decision making. Care options and quality metrics should reflect a focus on patients' priorities. Clinician-patient partnerships should reflect patients knowing their health goals and clinicians knowing how to achieve them. Access to specialty expertise should not require visits. Stakeholders' recommendations suggest health care redesigns that incorporate patients' health priorities into care decisions and realign relationships across patients and clinicians.

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Jamshidi, Mo

1997-01-01

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

Optimal crop selection and water allocation under limited water supply in irrigation

NASA Astrophysics Data System (ADS)

Stange, Peter; Grießbach, Ulrike; Schütze, Niels

2015-04-01

Due to climate change, extreme weather conditions such as droughts may have an increasing impact on irrigated agriculture. To cope with limited water resources in irrigation systems, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand at the same time. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from optimized agronomic response on farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF). These functions take into account different soil types, crops and stochastically generated climate scenarios. The SCWPF's are used to compute the water demand considering different conditions, e.g., variable and fixed costs. This generic approach enables the consideration of both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance IRrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies.

Effects of tailored neck-shoulder pain treatment based on a decision model guided by clinical assessments and standardized functional tests. A study protocol of a randomized controlled trial.

PubMed

Björklund, Martin; Djupsjöbacka, Mats; Svedmark, Asa; Häger, Charlotte

2012-05-20

A major problem with rehabilitation interventions for neck pain is that the condition may have multiple causes, thus a single treatment approach is seldom efficient. The present study protocol outlines a single blinded randomised controlled trial evaluating the effect of tailored treatment for neck-shoulder pain. The treatment is based on a decision model guided by standardized clinical assessment and functional tests with cut-off values. Our main hypothesis is that the tailored treatment has better short, intermediate and long-term effects than either non-tailored treatment or treatment-as-usual (TAU) on pain and function. We sub-sequentially hypothesize that tailored and non-tailored treatment both have better effect than TAU. 120 working women with minimum six weeks of nonspecific neck-shoulder pain aged 20-65, are allocated by minimisation with the factors age, duration of pain, pain intensity and disability in to the groups tailored treatment (T), non-tailored treatment (NT) or treatment-as-usual (TAU). Treatment is given to the groups T and NT for 11 weeks (27 sessions evenly distributed). An extensive presentation of the tests and treatment decision model is provided. The main treatment components are manual therapy, cranio-cervical flexion exercise and strength training, EMG-biofeedback training, treatment for cervicogenic headache, neck motor control training. A decision algorithm based on the baseline assessment determines the treatment components given to each participant of T- and NT-groups. Primary outcome measures are physical functioning (Neck Disability Index) and average pain intensity last week (Numeric Rating Scale). Secondary outcomes are general improvement (Patient Global Impression of Change scale), symptoms (Profile Fitness Mapping neck questionnaire), capacity to work in the last 6 weeks (quality and quantity) and pressure pain threshold of m. trapezius. Primary and secondary outcomes will be reported for each group with effect size and its precision. We have chosen not to include women with psychological ill-health and focus on biomedical aspects of neck pain. Future studies should aim at including psychosocial aspects in a widened treatment decision model. No important adverse events or side-effects are expected.

"Usability of data integration and visualization software for multidisciplinary pediatric intensive care: a human factors approach to assessing technology".

PubMed

Lin, Ying Ling; Guerguerian, Anne-Marie; Tomasi, Jessica; Laussen, Peter; Trbovich, Patricia

2017-08-14

Intensive care clinicians use several sources of data in order to inform decision-making. We set out to evaluate a new interactive data integration platform called T3™ made available for pediatric intensive care. Three primary functions are supported: tracking of physiologic signals, displaying trajectory, and triggering decisions, by highlighting data or estimating risk of patient instability. We designed a human factors study to identify interface usability issues, to measure ease of use, and to describe interface features that may enable or hinder clinical tasks. Twenty-two participants, consisting of bedside intensive care physicians, nurses, and respiratory therapists, tested the T3™ interface in a simulation laboratory setting. Twenty tasks were performed with a true-to-setting, fully functional, prototype, populated with physiological and therapeutic intervention patient data. Primary data visualization was time series and secondary visualizations were: 1) shading out-of-target values, 2) mini-trends with exaggerated maxima and minima (sparklines), and 3) bar graph of a 16-parameter indicator. Task completion was video recorded and assessed using a use error rating scale. Usability issues were classified in the context of task and type of clinician. A severity rating scale was used to rate potential clinical impact of usability issues. Time series supported tracking a single parameter but partially supported determining patient trajectory using multiple parameters. Visual pattern overload was observed with multiple parameter data streams. Automated data processing using shading and sparklines was often ignored but the 16-parameter data reduction algorithm, displayed as a persistent bar graph, was visually intuitive. However, by selecting or automatically processing data, triggering aids distorted the raw data that clinicians use regularly. Consequently, clinicians could not rely on new data representations because they did not know how they were established or derived. Usability issues, observed through contextual use, provided directions for tangible design improvements of data integration software that may lessen use errors and promote safe use. Data-driven decision making can benefit from iterative interface redesign involving clinician-users in simulated environments. This study is a first step in understanding how software can support clinicians' decision making with integrated continuous monitoring data. Importantly, testing of similar platforms by all the different disciplines who may become clinician users is a fundamental step necessary to understand the impact on clinical outcomes of decision aids.

A multi-objective decision-making approach to the journal submission problem.

PubMed

Wong, Tony E; Srikrishnan, Vivek; Hadka, David; Keller, Klaus

2017-01-01

When researchers complete a manuscript, they need to choose a journal to which they will submit the study. This decision requires to navigate trade-offs between multiple objectives. One objective is to share the new knowledge as widely as possible. Citation counts can serve as a proxy to quantify this objective. A second objective is to minimize the time commitment put into sharing the research, which may be estimated by the total time from initial submission to final decision. A third objective is to minimize the number of rejections and resubmissions. Thus, researchers often consider the trade-offs between the objectives of (i) maximizing citations, (ii) minimizing time-to-decision, and (iii) minimizing the number of resubmissions. To complicate matters further, this is a decision with multiple, potentially conflicting, decision-maker rationalities. Co-authors might have different preferences, for example about publishing fast versus maximizing citations. These diverging preferences can lead to conflicting trade-offs between objectives. Here, we apply a multi-objective decision analytical framework to identify the Pareto-front between these objectives and determine the set of journal submission pathways that balance these objectives for three stages of a researcher's career. We find multiple strategies that researchers might pursue, depending on how they value minimizing risk and effort relative to maximizing citations. The sequences that maximize expected citations within each strategy are generally similar, regardless of time horizon. We find that the "conditional impact factor"-impact factor times acceptance rate-is a suitable heuristic method for ranking journals, to strike a balance between minimizing effort objectives and maximizing citation count. Finally, we examine potential co-author tension resulting from differing rationalities by mapping out each researcher's preferred Pareto front and identifying compromise submission strategies. The explicit representation of trade-offs, especially when multiple decision-makers (co-authors) have different preferences, facilitates negotiations and can support the decision process.

A multi-objective decision-making approach to the journal submission problem

PubMed Central

Hadka, David; Keller, Klaus

2017-01-01

When researchers complete a manuscript, they need to choose a journal to which they will submit the study. This decision requires to navigate trade-offs between multiple objectives. One objective is to share the new knowledge as widely as possible. Citation counts can serve as a proxy to quantify this objective. A second objective is to minimize the time commitment put into sharing the research, which may be estimated by the total time from initial submission to final decision. A third objective is to minimize the number of rejections and resubmissions. Thus, researchers often consider the trade-offs between the objectives of (i) maximizing citations, (ii) minimizing time-to-decision, and (iii) minimizing the number of resubmissions. To complicate matters further, this is a decision with multiple, potentially conflicting, decision-maker rationalities. Co-authors might have different preferences, for example about publishing fast versus maximizing citations. These diverging preferences can lead to conflicting trade-offs between objectives. Here, we apply a multi-objective decision analytical framework to identify the Pareto-front between these objectives and determine the set of journal submission pathways that balance these objectives for three stages of a researcher’s career. We find multiple strategies that researchers might pursue, depending on how they value minimizing risk and effort relative to maximizing citations. The sequences that maximize expected citations within each strategy are generally similar, regardless of time horizon. We find that the “conditional impact factor”—impact factor times acceptance rate—is a suitable heuristic method for ranking journals, to strike a balance between minimizing effort objectives and maximizing citation count. Finally, we examine potential co-author tension resulting from differing rationalities by mapping out each researcher’s preferred Pareto front and identifying compromise submission strategies. The explicit representation of trade-offs, especially when multiple decision-makers (co-authors) have different preferences, facilitates negotiations and can support the decision process. PMID:28582430

Local Approximation and Hierarchical Methods for Stochastic Optimization

NASA Astrophysics Data System (ADS)

Cheng, Bolong

In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the PJM Interconnect and show that it outperforms the baseline approach used in the industry.

Functional Freedom: A Psychological Model of Freedom in Decision-Making.

PubMed

Lau, Stephan; Hiemisch, Anette

2017-07-05

The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one's own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model's implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview.

How decisions emerge: action dynamics in intertemporal decision making.

PubMed

Dshemuchadse, Maja; Scherbaum, Stefan; Goschke, Thomas

2013-02-01

In intertemporal decision making, individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to an extent that seems irrational from an economical perspective. This behavior has been attributed to a lack of self-control and reflection, the nonlinearity of human time perception, and several other sources. Although an increasing number of models propose different mathematical descriptions of temporal discounting, the dynamics of the decision process behind temporal discounting are much less clear. In this study, we obtained further insights into the mechanisms of intertemporal decisions by observing choice action dynamics via a novel combination of continuously recorded mouse movements and a multiple regression approach. Participants had to choose between two hypothetical options (sooner/smaller vs. later/larger) by moving the mouse cursor from the bottom of the screen either to the top left or to the top right. We observed less direct mouse movements when participants chose later/larger rewards, indicating that participants had to overcome the attraction of the sooner/smaller reward first. Additionally, our results suggest that framing time information differently changes the weighting of value. We conclude that using a continuous process-oriented approach could further advance the understanding of intertemporal choice beyond the identification of the best fitted mathematical description of the discounting function by uncovering the way intertemporal decisions are performed. 2013 APA, all rights reserved

A collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers.

PubMed

Li, Guo; Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

PubMed Central

Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104

What failure in collective decision-making tells us about metacognition

PubMed Central

Bahrami, Bahador; Olsen, Karsten; Bang, Dan; Roepstorff, Andreas; Rees, Geraint; Frith, Chris

2012-01-01

Condorcet (1785) proposed that a majority vote drawn from individual, independent and fallible (but not totally uninformed) opinions provides near-perfect accuracy if the number of voters is adequately large. Research in social psychology has since then repeatedly demonstrated that collectives can and do fail more often than expected by Condorcet. Since human collective decisions often follow from exchange of opinions, these failures provide an exquisite opportunity to understand human communication of metacognitive confidence. This question can be addressed by recasting collective decision-making as an information-integration problem similar to multisensory (cross-modal) perception. Previous research in systems neuroscience shows that one brain can integrate information from multiple senses nearly optimally. Inverting the question, we ask: under what conditions can two brains integrate information about one sensory modality optimally? We review recent work that has taken this approach and report discoveries about the quantitative limits of collective perceptual decision-making, and the role of the mode of communication and feedback in collective decision-making. We propose that shared metacognitive confidence conveys the strength of an individual's opinion and its reliability inseparably. We further suggest that a functional role of shared metacognition is to provide substitute signals in situations where outcome is necessary for learning but unavailable or impossible to establish. PMID:22492752

An integrated decision making approach for assessing healthcare waste treatment technologies from a multiple stakeholder.

PubMed

Shi, Hua; Liu, Hu-Chen; Li, Ping; Xu, Xue-Guo

2017-01-01

With increased worldwide awareness of environmental issues, healthcare waste (HCW) management has received much attention from both researchers and practitioners over the past decade. The task of selecting the optimum treatment technology for HCWs is a challenging decision making problem involving conflicting evaluation criteria and multiple stakeholders. In this paper, we develop an integrated decision making framework based on cloud model and MABAC method for evaluating and selecting the best HCW treatment technology from a multiple stakeholder perspective. The introduced framework deals with uncertain linguistic assessments of alternatives by using interval 2-tuple linguistic variables, determines decision makers' relative weights based on the uncertainty and divergence degrees of every decision maker, and obtains the ranking of all HCW disposal alternatives with the aid of an extended MABAC method. Finally, an empirical example from Shanghai, China, is provided to illustrate the feasibility and effectiveness of the proposed approach. Results indicate that the methodology being proposed is more suitable and effective to handle the HCW treatment technology selection problem under vague and uncertain information environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial attention improves the quality of population codes in human visual cortex.

PubMed

Saproo, Sameer; Serences, John T

2010-08-01

Selective attention enables sensory input from behaviorally relevant stimuli to be processed in greater detail, so that these stimuli can more accurately influence thoughts, actions, and future goals. Attention has been shown to modulate the spiking activity of single feature-selective neurons that encode basic stimulus properties (color, orientation, etc.). However, the combined output from many such neurons is required to form stable representations of relevant objects and little empirical work has formally investigated the relationship between attentional modulations on population responses and improvements in encoding precision. Here, we used functional MRI and voxel-based feature tuning functions to show that spatial attention induces a multiplicative scaling in orientation-selective population response profiles in early visual cortex. In turn, this multiplicative scaling correlates with an improvement in encoding precision, as evidenced by a concurrent increase in the mutual information between population responses and the orientation of attended stimuli. These data therefore demonstrate how multiplicative scaling of neural responses provides at least one mechanism by which spatial attention may improve the encoding precision of population codes. Increased encoding precision in early visual areas may then enhance the speed and accuracy of perceptual decisions computed by higher-order neural mechanisms.

The curse of planning: dissecting multiple reinforcement-learning systems by taxing the central executive.

PubMed

Otto, A Ross; Gershman, Samuel J; Markman, Arthur B; Daw, Nathaniel D

2013-05-01

A number of accounts of human and animal behavior posit the operation of parallel and competing valuation systems in the control of choice behavior. In these accounts, a flexible but computationally expensive model-based reinforcement-learning system has been contrasted with a less flexible but more efficient model-free reinforcement-learning system. The factors governing which system controls behavior-and under what circumstances-are still unclear. Following the hypothesis that model-based reinforcement learning requires cognitive resources, we demonstrated that having human decision makers perform a demanding secondary task engenders increased reliance on a model-free reinforcement-learning strategy. Further, we showed that, across trials, people negotiate the trade-off between the two systems dynamically as a function of concurrent executive-function demands, and people's choice latencies reflect the computational expenses of the strategy they employ. These results demonstrate that competition between multiple learning systems can be controlled on a trial-by-trial basis by modulating the availability of cognitive resources.

The Curse of Planning: Dissecting multiple reinforcement learning systems by taxing the central executive

PubMed Central

Otto, A. Ross; Gershman, Samuel J.; Markman, Arthur B.; Daw, Nathaniel D.

2013-01-01

A number of accounts of human and animal behavior posit the operation of parallel and competing valuation systems in the control of choice behavior. Along these lines, a flexible but computationally expensive model-based reinforcement learning system has been contrasted with a less flexible but more efficient model-free reinforcement learning system. The factors governing which system controls behavior—and under what circumstances—are still unclear. Based on the hypothesis that model-based reinforcement learning requires cognitive resources, we demonstrate that having human decision-makers perform a demanding secondary task engenders increased reliance on a model-free reinforcement learning strategy. Further, we show that across trials, people negotiate this tradeoff dynamically as a function of concurrent executive function demands and their choice latencies reflect the computational expenses of the strategy employed. These results demonstrate that competition between multiple learning systems can be controlled on a trial-by-trial basis by modulating the availability of cognitive resources. PMID:23558545

Purchasing a Used Car Using Multiple Criteria Decision Making

ERIC Educational Resources Information Center

Edwards, Thomas G.; Chelst, Kenneth R.

2007-01-01

When studying mathematics, students often ask the age-old question, "When will I ever use this in my future?" The activities described in this article demonstrate for students a process that brings the power of mathematical reasoning to bear on a difficult decision involving multiple criteria that is sure to resonate with the interests of many of…

Annual Research Review: Transdiagnostic neuroscience of child and adolescent mental disorders--differentiating decision making in attention-deficit/hyperactivity disorder, conduct disorder, depression, and anxiety.

PubMed

Sonuga-Barke, Edmund J S; Cortese, Samuele; Fairchild, Graeme; Stringaris, Argyris

2016-03-01

Ineffective decision making is a major source of everyday functional impairment and reduced quality of life for young people with mental disorders. However, very little is known about what distinguishes decision making by individuals with different disorders or the neuropsychological processes or brain systems underlying these. This is the focus of the current review. We first propose a neuroeconomic model of the decision-making process with separate stages for the prechoice evaluation of expected utility of future options; choice execution and postchoice management; the appraisal of outcome against expectation; and the updating of value estimates to guide future decisions. According to the proposed model, decision making is mediated by neuropsychological processes operating within three domains: (a) self-referential processes involved in autobiographical reflection on past, and prospection about future, experiences; (b) executive functions, such as working memory, inhibition, and planning, that regulate the implementation of decisions; and (c) processes involved in value estimation and outcome appraisal and learning. These processes are underpinned by the interplay of multiple brain networks, especially medial and lateralized cortical components of the default mode network, dorsal corticostriatal circuits underpinning higher order cognitive and behavioral control, and ventral frontostriatal circuits, connecting to brain regions implicated in emotion processing, that control valuation and learning processes. Based on clinical insights and considering each of the decision-making stages in turn, we outline disorder-specific hypotheses about impaired decision making in four childhood disorders: attention-deficit/hyperactivity disorder (ADHD), conduct disorder (CD), depression, and anxiety. We hypothesize that decision making in ADHD is deficient (i.e. inefficient, insufficiently reflective, and inconsistent) and impulsive (biased toward immediate over delayed alternatives). In CD, it is reckless and insensitive to negative consequences. In depression, it is disengaged, perseverative, and pessimistic, while in anxiety, it is hesitant, risk-averse, and self-deprecating. A survey of current empirical indications related to these disorder-specific hypotheses highlights the limited and fragmentary nature of the evidence base and illustrates the need for a major research initiative in decision making in childhood disorders. The final section highlights a number of important additional general themes that need to be considered in future research. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

Utilization of multiple-criteria decision analysis (MCDA) to support healthcare decision-making FIFARMA, 2016

PubMed Central

Drake, Julia I.; de Hart, Juan Carlos Trujillo; Monleón, Clara; Toro, Walter; Valentim, Joice

2017-01-01

ABSTRACT Background and objectives:   MCDA is a decision-making tool with increasing use in the healthcare sector, including HTA (Health Technology Assessment). By applying multiple criteria, including innovation, in a comprehensive, structured and explicit manner, MCDA fosters a transparent, participative, consistent decision-making process taking into consideration values of all stakeholders. This paper by FIFARMA (Latin American Federation of Pharmaceutical Industry) proposes the deliberative (partial) MCDA as a more pragmatic, agile approach, especially when newly implemented. Methods: Literature review including real-world examples of effective MCDA implementation in healthcare decision making in both the public and private sector worldwide and in LA. Results and conclusion: It is the view of FIFARMA that MCDA should strongly be considered as a tool to support HTA and broader healthcare decision making such as the contracts and tenders process in order to foster transparency, fairness, and collaboration amongst stakeholders. PMID:29081919

Emotion and decision making: multiple modulatory neural circuits.

PubMed

Phelps, Elizabeth A; Lempert, Karolina M; Sokol-Hessner, Peter

2014-01-01

Although the prevalent view of emotion and decision making is derived from the notion that there are dual systems of emotion and reason, a modulatory relationship more accurately reflects the current research in affective neuroscience and neuroeconomics. Studies show two potential mechanisms for affect's modulation of the computation of subjective value and decisions. Incidental affective states may carry over to the assessment of subjective value and the decision, and emotional reactions to the choice may be incorporated into the value calculation. In addition, this modulatory relationship is reciprocal: Changing emotion can change choices. This research suggests that the neural mechanisms mediating the relation between affect and choice vary depending on which affective component is engaged and which decision variables are assessed. We suggest that a detailed and nuanced understanding of emotion and decision making requires characterizing the multiple modulatory neural circuits underlying the different means by which emotion and affect can influence choices.

HIV epidemic control-a model for optimal allocation of prevention and treatment resources.

PubMed

Alistar, Sabina S; Long, Elisa F; Brandeau, Margaret L; Beck, Eduard J

2014-06-01

With 33 million people living with human immunodeficiency virus (HIV) worldwide and 2.7 million new infections occurring annually, additional HIV prevention and treatment efforts are urgently needed. However, available resources for HIV control are limited and must be used efficiently to minimize the future spread of the epidemic. We develop a model to determine the appropriate resource allocation between expanded HIV prevention and treatment services. We create an epidemic model that incorporates multiple key populations with different transmission modes, as well as production functions that relate investment in prevention and treatment programs to changes in transmission and treatment rates. The goal is to allocate resources to minimize R 0, the reproductive rate of infection. We first develop a single-population model and determine the optimal resource allocation between HIV prevention and treatment. We extend the analysis to multiple independent populations, with resource allocation among interventions and populations. We then include the effects of HIV transmission between key populations. We apply our model to examine HIV epidemic control in two different settings, Uganda and Russia. As part of these applications, we develop a novel approach for estimating empirical HIV program production functions. Our study provides insights into the important question of resource allocation for a country's optimal response to its HIV epidemic and provides a practical approach for decision makers. Better decisions about allocating limited HIV resources can improve response to the epidemic and increase access to HIV prevention and treatment services for millions of people worldwide.

Coleadership Among Chief Residents: Exploration of Experiences Across Specialties

PubMed Central

Pettit, Jeffrey E.

2015-01-01

Background Many departments have multiple chief residents. How these coleaders relate to each other could affect their performance, the residency program, and the department. Objective This article reports on how co-chiefs work together during the chief year, and what may allow them to be more effective coleaders. Methods A phenomenological research design was used to investigate experiences of outgoing chief residents from 13 specialties at the University of Iowa Hospitals and Clinics over a 2-year period from 2012 through 2013. Thematic analysis of semistructured interviews was conducted to investigate commonalities and recommendations. Results Face-to-face interviews with 19 chief residents from 13 different specialties identified experiences that helped co-chiefs work effectively with each other in orienting new co-chiefs, setting goals and expectations, making decisions, managing interpersonal conflict, leadership styles, communicating, working with program directors, and providing evaluations and feedback. Although the interviewed chief residents received guidance on how to be an effective chief resident, none had been given advice on how to effectively work with a co-chief, and 26% (5 of 19) of the respondents reported having an ineffective working relationship with their co-chief. Conclusions Chief residents often colead in carrying out their multiple functions. To successfully function in a multichief environment, chief residents may benefit from a formal co-orientation in which they discuss goals and expectations, agree on a decision-making process, understand each other's leadership style, and receive feedback on their efficacy as leaders. PMID:26221435

Physician participation in hospital strategic decision making: the effect of hospital strategy and decision content.

PubMed Central

Ashmos, D P; McDaniel, R R

1991-01-01

An exploratory study examined variation in the participation of physicians in hospital strategic decision making as a function of (1) strategic decision content or (2) hospital strategy, or both. The findings revealed that who participates is a function of decision content while how physicians participate is a function of decision content and the interaction of decision content and hospital strategy. PMID:1869445

Introduction to the special section on "Hormones and cognition: perspectives, controversies, and challenges for future research".

PubMed

Frick, Karyn M

2012-02-01

The research of the past two decades has firmly established that hormones modulate numerous aspects of cognitive function, including memory, attention, decision-making, and sensory processing. That such a wide variety of hormones influence cognition mediated by multiple nonhypothalamic brain regions illustrates the critical importance of hormones to neural and cognitive function. The diversity of hormonal effects on cognition is evident in the collection of reviews and original research articles assembled for this special section. Together, these articles provide an overview of recent research on varied topics in hormones and cognition, address controversial issues in the field, and discuss challenges that must be overcome in future research to gain a better understanding of the mechanisms through which hormones modulate cognitive function.

The role of emotions in clinical reasoning and decision making.

PubMed

Marcum, James A

2013-10-01

What role, if any, should emotions play in clinical reasoning and decision making? Traditionally, emotions have been excluded from clinical reasoning and decision making, but with recent advances in cognitive neuropsychology they are now considered an important component of them. Today, cognition is thought to be a set of complex processes relying on multiple types of intelligences. The role of mathematical logic (hypothetico-deductive thinking) or verbal linguistic intelligence in cognition, for example, is well documented and accepted; however, the role of emotional intelligence has received less attention-especially because its nature and function are not well understood. In this paper, I argue for the inclusion of emotions in clinical reasoning and decision making. To that end, developments in contemporary cognitive neuropsychology are initially examined and analyzed, followed by a review of the medical literature discussing the role of emotions in clinical practice. Next, a published clinical case is reconstructed and used to illustrate the recognition and regulation of emotions played during a series of clinical consultations, which resulted in a positive medical outcome. The paper's main thesis is that emotions, particularly in terms of emotional intelligence as a practical form of intelligence, afford clinical practitioners a robust cognitive resource for providing quality medical care.

Tool for Ranking Research Options

NASA Technical Reports Server (NTRS)

Ortiz, James N.; Scott, Kelly; Smith, Harold

2005-01-01

Tool for Research Enhancement Decision Support (TREDS) is a computer program developed to assist managers in ranking options for research aboard the International Space Station (ISS). It could likely also be adapted to perform similar decision-support functions in industrial and academic settings. TREDS provides a ranking of the options, based on a quantifiable assessment of all the relevant programmatic decision factors of benefit, cost, and risk. The computation of the benefit for each option is based on a figure of merit (FOM) for ISS research capacity that incorporates both quantitative and qualitative inputs. Qualitative inputs are gathered and partly quantified by use of the time-tested analytical hierarchical process and used to set weighting factors in the FOM corresponding to priorities determined by the cognizant decision maker(s). Then by use of algorithms developed specifically for this application, TREDS adjusts the projected benefit for each option on the basis of levels of technical implementation, cost, and schedule risk. Based partly on Excel spreadsheets, TREDS provides screens for entering cost, benefit, and risk information. Drop-down boxes are provided for entry of qualitative information. TREDS produces graphical output in multiple formats that can be tailored by users.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

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

PubMed

Li, Yan

2017-05-25

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

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

From single steps to mass migration: the problem of scale in the movement ecology of the Serengeti wildebeest.

PubMed

Torney, Colin J; Hopcraft, J Grant C; Morrison, Thomas A; Couzin, Iain D; Levin, Simon A

2018-05-19

A central question in ecology is how to link processes that occur over different scales. The daily interactions of individual organisms ultimately determine community dynamics, population fluctuations and the functioning of entire ecosystems. Observations of these multiscale ecological processes are constrained by various technological, biological or logistical issues, and there are often vast discrepancies between the scale at which observation is possible and the scale of the question of interest. Animal movement is characterized by processes that act over multiple spatial and temporal scales. Second-by-second decisions accumulate to produce annual movement patterns. Individuals influence, and are influenced by, collective movement decisions, which then govern the spatial distribution of populations and the connectivity of meta-populations. While the field of movement ecology is experiencing unprecedented growth in the availability of movement data, there remain challenges in integrating observations with questions of ecological interest. In this article, we present the major challenges of addressing these issues within the context of the Serengeti wildebeest migration, a keystone ecological phenomena that crosses multiple scales of space, time and biological complexity.This article is part of the theme issue 'Collective movement ecology'. © 2018 The Author(s).

Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

PubMed

Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao

2018-05-01

Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.

Functional Freedom: A Psychological Model of Freedom in Decision-Making

PubMed Central

Lau, Stephan; Hiemisch, Anette

2017-01-01

The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one’s own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model’s implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview. PMID:28678165

Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA.

PubMed

Mühlbacher, Axel C; Kaczynski, Anika

2016-02-01

Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.

A method for integrating multiple components in a decision support system

Treesearch

Donald Nute; Walter D. Potter; Zhiyuan Cheng; Mayukh Dass; Astrid Glende; Frederick Maierv; Cy Routh; Hajime Uchiyama; Jin Wang; Sarah Witzig; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher

2005-01-01

We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and...

Maximum entropy perception-action space: a Bayesian model of eye movement selection

NASA Astrophysics Data System (ADS)

Colas, Francis; Bessière, Pierre; Girard, Benoît

2011-03-01

In this article, we investigate the issue of the selection of eye movements in a free-eye Multiple Object Tracking task. We propose a Bayesian model of retinotopic maps with a complex logarithmic mapping. This model is structured in two parts: a representation of the visual scene, and a decision model based on the representation. We compare different decision models based on different features of the representation and we show that taking into account uncertainty helps predict the eye movements of subjects recorded in a psychophysics experiment. Finally, based on experimental data, we postulate that the complex logarithmic mapping has a functional relevance, as the density of objects in this space in more uniform than expected. This may indicate that the representation space and control strategies are such that the object density is of maximum entropy.

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.

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

ERIC Educational Resources Information Center

Mehrens, William A.; And Others

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

Lenses for Framing Decisions: Undergraduates' Decision Making about Stem Cell Research

ERIC Educational Resources Information Center

Halverson, Kristy Lynn; Siegel, Marcelle A.; Freyermuth, Sharyn K.

2009-01-01

Decision making is influenced by multiple factors, especially when approaching controversial socio-scientific issues, such as stem cell research. In the present study, we used qualitative data from 132 college student papers in a biotechnology course to investigate how students made decisions about stem cell research issues. Students indicated…

The Wildland Fire Decision Support System: Integrating science, technology, and fire management

Treesearch

Morgan Pence; Tom Zimmerman

2011-01-01

Federal agency policy requires documentation and analysis of all wildland fire response decisions. In the past, planning and decision documentation for fires were completed using multiple unconnected processes, yielding many limitations. In response, interagency fire management executives chartered the development of the Wildland Fire Decision Support System (WFDSS)....

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...

A Multi-criterial Decision Support System for Forest Management

Treesearch

Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch

1999-01-01

We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...

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...

Toolbox or Adjustable Spanner? A Critical Comparison of Two Metaphors for Adaptive Decision Making

ERIC Educational Resources Information Center

Söllner, Anke; Bröder, Arndt

2016-01-01

For multiattribute decision tasks, different metaphors exist that describe the process of decision making and its adaptation to diverse problems and situations. Multiple strategy models (MSMs) assume that decision makers choose adaptively from a set of different strategies (toolbox metaphor), whereas evidence accumulation models (EAMs) hold that a…

Finding the numerical compensation in multiple criteria decision-making problems under fuzzy environment

NASA Astrophysics Data System (ADS)

Gupta, Mahima; Mohanty, B. K.

2017-04-01

In this paper, we have developed a methodology to derive the level of compensation numerically in multiple criteria decision-making (MCDM) problems under fuzzy environment. The degree of compensation is dependent on the tranquility and anxiety level experienced by the decision-maker while taking the decision. Higher tranquility leads to the higher realisation of the compensation whereas the increased level of anxiety reduces the amount of compensation in the decision process. This work determines the level of tranquility (or anxiety) using the concept of fuzzy sets and its various level sets. The concepts of indexing of fuzzy numbers, the risk barriers and the tranquility level of the decision-maker are used to derive his/her risk prone or risk averse attitude of decision-maker in each criterion. The aggregation of the risk levels in each criterion gives us the amount of compensation in the entire MCDM problem. Inclusion of the compensation leads us to model the MCDM problem as binary integer programming problem (BIP). The solution to BIP gives us the compensatory decision to MCDM. The proposed methodology is illustrated through a numerical example.

Neurons in the Frontal Lobe Encode the Value of Multiple Decision Variables

PubMed Central

Kennerley, Steven W.; Dahmubed, Aspandiar F.; Lara, Antonio H.; Wallis, Jonathan D.

2009-01-01

A central question in behavioral science is how we select among choice alternatives to obtain consistently the most beneficial outcomes. Three variables are particularly important when making a decision: the potential payoff, the probability of success, and the cost in terms of time and effort. A key brain region in decision making is the frontal cortex as damage here impairs the ability to make optimal choices across a range of decision types. We simultaneously recorded the activity of multiple single neurons in the frontal cortex while subjects made choices involving the three aforementioned decision variables. This enabled us to contrast the relative contribution of the anterior cingulate cortex (ACC), the orbito-frontal cortex, and the lateral prefrontal cortex to the decision-making process. Neurons in all three areas encoded value relating to choices involving probability, payoff, or cost manipulations. However, the most significant signals were in the ACC, where neurons encoded multiplexed representations of the three different decision variables. This supports the notion that the ACC is an important component of the neural circuitry underlying optimal decision making. PMID:18752411

Activational and effort-related aspects of motivation: neural mechanisms and implications for psychopathology

PubMed Central

Yohn, Samantha E.; López-Cruz, Laura; San Miguel, Noemí; Correa, Mercè

2016-01-01

Abstract Motivation has been defined as the process that allows organisms to regulate their internal and external environment, and control the probability, proximity and availability of stimuli. As such, motivation is a complex process that is critical for survival, which involves multiple behavioural functions mediated by a number of interacting neural circuits. Classical theories of motivation suggest that there are both directional and activational aspects of motivation, and activational aspects (i.e. speed and vigour of both the instigation and persistence of behaviour) are critical for enabling organisms to overcome work-related obstacles or constraints that separate them from significant stimuli. The present review discusses the role of brain dopamine and related circuits in behavioural activation, exertion of effort in instrumental behaviour, and effort-related decision-making, based upon both animal and human studies. Impairments in behavioural activation and effort-related aspects of motivation are associated with psychiatric symptoms such as anergia, fatigue, lassitude and psychomotor retardation, which cross multiple pathologies, including depression, schizophrenia, and Parkinson’s disease. Therefore, this review also attempts to provide an interdisciplinary approach that integrates findings from basic behavioural neuroscience, behavioural economics, clinical neuropsychology, psychiatry, and neurology, to provide a coherent framework for future research and theory in this critical field. Although dopamine systems are a critical part of the brain circuitry regulating behavioural activation, exertion of effort, and effort-related decision-making, mesolimbic dopamine is only one part of a distributed circuitry that includes multiple neurotransmitters and brain areas. Overall, there is a striking similarity between the brain areas involved in behavioural activation and effort-related processes in rodents and in humans. Animal models of effort-related decision-making are highly translatable to humans, and an emerging body of evidence indicates that alterations in effort-based decision-making are evident in several psychiatric and neurological disorders. People with major depression, schizophrenia, and Parkinson’s disease show evidence of decision-making biases towards a lower exertion of effort. Translational studies linking research with animal models, human volunteers, and clinical populations are greatly expanding our knowledge about the neural basis of effort-related motivational dysfunction, and it is hoped that this research will ultimately lead to improved treatment for motivational and psychomotor symptoms in psychiatry and neurology. PMID:27189581

A visualization tool to support decision making in environmental and biological planning

USGS Publications Warehouse

Romañach, Stephanie S.; McKelvy, James M.; Conzelmann, Craig; Suir, Kevin J.

2014-01-01

Large-scale ecosystem management involves consideration of many factors for informed decision making. The EverVIEW Data Viewer is a cross-platform desktop decision support tool to help decision makers compare simulation model outputs from competing plans for restoring Florida's Greater Everglades. The integration of NetCDF metadata conventions into EverVIEW allows end-users from multiple institutions within and beyond the Everglades restoration community to share information and tools. Our development process incorporates continuous interaction with targeted end-users for increased likelihood of adoption. One of EverVIEW's signature features is side-by-side map panels, which can be used to simultaneously compare species or habitat impacts from alternative restoration plans. Other features include examination of potential restoration plan impacts across multiple geographic or tabular displays, and animation through time. As a result of an iterative, standards-driven approach, EverVIEW is relevant to large-scale planning beyond Florida, and is used in multiple biological planning efforts in the United States.

Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration.

PubMed

Oh-Descher, Hanna; Beck, Jeffrey M; Ferrari, Silvia; Sommer, Marc A; Egner, Tobias

2017-11-15

Real-life decision-making often involves combining multiple probabilistic sources of information under finite time and cognitive resources. To mitigate these pressures, people "satisfice", foregoing a full evaluation of all available evidence to focus on a subset of cues that allow for fast and "good-enough" decisions. Although this form of decision-making likely mediates many of our everyday choices, very little is known about the way in which the neural encoding of cue information changes when we satisfice under time pressure. Here, we combined human functional magnetic resonance imaging (fMRI) with a probabilistic classification task to characterize neural substrates of multi-cue decision-making under low (1500 ms) and high (500 ms) time pressure. Using variational Bayesian inference, we analyzed participants' choices to track and quantify cue usage under each experimental condition, which was then applied to model the fMRI data. Under low time pressure, participants performed near-optimally, appropriately integrating all available cues to guide choices. Both cortical (prefrontal and parietal cortex) and subcortical (hippocampal and striatal) regions encoded individual cue weights, and activity linearly tracked trial-by-trial variations in the amount of evidence and decision uncertainty. Under increased time pressure, participants adaptively shifted to using a satisficing strategy by discounting the least informative cue in their decision process. This strategic change in decision-making was associated with an increased involvement of the dopaminergic midbrain, striatum, thalamus, and cerebellum in representing and integrating cue values. We conclude that satisficing the probabilistic inference process under time pressure leads to a cortical-to-subcortical shift in the neural drivers of decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Pilot study of a point-of-use decision support tool for cancer clinical trials eligibility.

PubMed

Breitfeld, P P; Weisburd, M; Overhage, J M; Sledge, G; Tierney, W M

1999-01-01

Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites.

Pilot Study of a Point-of-use Decision Support Tool for Cancer Clinical Trials Eligibility

PubMed Central

Breitfeld, Philip P.; Weisburd, Marina; Overhage, J. Marc; Sledge, George; Tierney, William M.

1999-01-01

Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites. PMID:10579605

Intelligent robotic tracker

NASA Technical Reports Server (NTRS)

Otaguro, W. S.; Kesler, L. O.; Land, K. C.; Rhoades, D. E.

1987-01-01

An intelligent tracker capable of robotic applications requiring guidance and control of platforms, robotic arms, and end effectors has been developed. This packaged system capable of supervised autonomous robotic functions is partitioned into a multiple processor/parallel processing configuration. The system currently interfaces to cameras but has the capability to also use three-dimensional inputs from scanning laser rangers. The inputs are fed into an image processing and tracking section where the camera inputs are conditioned for the multiple tracker algorithms. An executive section monitors the image processing and tracker outputs and performs all the control and decision processes. The present architecture of the system is presented with discussion of its evolutionary growth for space applications. An autonomous rendezvous demonstration of this system was performed last year. More realistic demonstrations in planning are discussed.

Factors influencing health information system adoption in American hospitals.

PubMed

Wang, Bill B; Wan, Thomas T H; Burke, Darrell E; Bazzoli, Gloria J; Lin, Blossom Y J

2005-01-01

To study the number of health information systems (HISs), applicable to administrative, clinical, and executive decision support functionalities, adopted by acute care hospitals and to examine how hospital market, organizational, and financial factors influence HIS adoption. A cross-sectional analysis was performed with 1441 hospitals selected from metropolitan statistical areas in the United States. Multiple data sources were merged. Six hypotheses were empirically tested by multiple regression analysis. HIS adoption was influenced by the hospital market, organizational, and financial factors. Larger, system-affiliated, and for-profit hospitals with more preferred provider organization contracts are more likely to adopt managerial information systems than their counterparts. Operating revenue is positively associated with HIS adoption. The study concludes that hospital organizational and financial factors influence on hospitals' strategic adoption of clinical, administrative, and managerial information systems.

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

Data fusion strategies for hazard detection and safe site selection for planetary and small body landings

NASA Astrophysics Data System (ADS)

Câmara, F.; Oliveira, J.; Hormigo, T.; Araújo, J.; Ribeiro, R.; Falcão, A.; Gomes, M.; Dubois-Matra, O.; Vijendran, S.

2015-06-01

This paper discusses the design and evaluation of data fusion strategies to perform tiered fusion of several heterogeneous sensors and a priori data. The aim is to increase robustness and performance of hazard detection and avoidance systems, while enabling safe planetary and small body landings anytime, anywhere. The focus is on Mars and asteroid landing mission scenarios and three distinct data fusion algorithms are introduced and compared. The first algorithm consists of a hybrid camera-LIDAR hazard detection and avoidance system, the H2DAS, in which data fusion is performed at both sensor-level data (reconstruction of the point cloud obtained with a scanning LIDAR using the navigation motion states and correcting the image for motion compensation using IMU data), feature-level data (concatenation of multiple digital elevation maps, obtained from consecutive LIDAR images, to achieve higher accuracy and resolution maps while enabling relative positioning) as well as decision-level data (fusing hazard maps from multiple sensors onto a single image space, with a single grid orientation and spacing). The second method presented is a hybrid reasoning fusion, the HRF, in which innovative algorithms replace the decision-level functions of the previous method, by combining three different reasoning engines—a fuzzy reasoning engine, a probabilistic reasoning engine and an evidential reasoning engine—to produce safety maps. Finally, the third method presented is called Intelligent Planetary Site Selection, the IPSIS, an innovative multi-criteria, dynamic decision-level data fusion algorithm that takes into account historical information for the selection of landing sites and a piloting function with a non-exhaustive landing site search capability, i.e., capable of finding local optima by searching a reduced set of global maps. All the discussed data fusion strategies and algorithms have been integrated, verified and validated in a closed-loop simulation environment. Monte Carlo simulation campaigns were performed for the algorithms performance assessment and benchmarking. The simulations results comprise the landing phases of Mars and Phobos landing mission scenarios.

The relationship between soil management and the Sustainable Development Goals: the case of global banana production

NASA Astrophysics Data System (ADS)

Stoorvogel, Jetse; Segura, Rafael; Erima, Rockefeller

2017-04-01

The Sustainable Development Goals (SDGs) are a good example of the increasing demand on our soil resources. Our soil resources play a central role in multiple SDGs while talking about poverty (SDG 1), food security (SDG 2), clean energy through biofuels (SDG 7), climate mitigation (SDG 13), and land degradation (SDG 15). This means that basic decisions on soil management are now placed in the context of multiple soil functions. A good example is the global production of bananas and plantains with a total harvested area of almost 10 million ha. While the export bananas played a central role in economic development, an even larger share of the production plays a role in food security. Nevertheless, the production is also criticized due the intensive use of agricultural chemicals (fertilizers and pesticides) and the risk of soil degradation in the monoculture plantations. Decisions on soil management are context specific and depending on the environment. In this study we will analyse and discuss three production environments from the Philippines, Uganda, and Costa Rica. The role of the SDGs in the regions is very different. Where SDG 1 and SDG15 play an important role in the Costa Rican situation, SDG 2 is more important in Uganda and the Philippines. Decisions on soil management strongly depend on the agro-ecology with the available technological packages. The technological packages include low external input farming, organic farming, precision agriculture, and so-called best management practices. While producers take decisions at the field and farm level, we are now increasingly forced for joined action at the regional level with the rapid spread of highly virulent crop diseases. The SDGs have major consequences for soil management but this study shows that, at the same time, they cannot be translated one-to-one to the farm level at which the management decisions are taken. Therefore, off-farm effects and externalities are often not considered in farm management except if they are explicitly being targeted by policies or other interventions. Specific attention is required to analyse the aggregated effect of soil management decisions at the regional level.

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

PubMed

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

2016-09-01

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

Quantitative assessment of upper extremities motor function in multiple sclerosis.

PubMed

Daunoraviciene, Kristina; Ziziene, Jurgita; Griskevicius, Julius; Pauk, Jolanta; Ovcinikova, Agne; Kizlaitiene, Rasa; Kaubrys, Gintaras

2018-05-18

Upper extremity (UE) motor function deficits are commonly noted in multiple sclerosis (MS) patients and assessing it is challenging because of the lack of consensus regarding its definition. Instrumented biomechanical analysis of upper extremity movements can quantify coordination with different spatiotemporal measures and facilitate disability rating in MS patients. To identify objective quantitative parameters for more accurate evaluation of UE disability and relate it to existing clinical scores. Thirty-four MS patients and 24 healthy controls (CG) performed a finger-to-nose test as fast as possible and, in addition, clinical evaluation kinematic parameters of UE were measured by using inertial sensors. Generally, a higher disability score was associated with an increase of several temporal parameters, like slower task performance. The time taken to touch their nose was longer when the task was fulfilled with eyes closed. Time to peak angular velocity significantly changed in MS patients (EDSS > 5.0). The inter-joint coordination significantly decreases in MS patients (EDSS 3.0-5.5). Spatial parameters indicated that maximal ROM changes were in elbow flexion. Our findings have revealed that spatiotemporal parameters are related to the UE motor function and MS disability level. Moreover, they facilitate clinical rating by supporting clinical decisions with quantitative data.

Switching of the positive feedback for RAS activation by a concerted function of SOS membrane association domains

PubMed Central

Nakamura, Yuki; Hibino, Kayo; Yanagida, Toshio; Sako, Yasushi

2016-01-01

Son of sevenless (SOS) is a guanine nucleotide exchange factor that regulates cell behavior by activating the small GTPase RAS. Recent in vitro studies have suggested that an interaction between SOS and the GTP-bound active form of RAS generates a positive feedback loop that propagates RAS activation. However, it remains unclear how the multiple domains of SOS contribute to the regulation of the feedback loop in living cells. Here, we observed single molecules of SOS in living cells to analyze the kinetics and dynamics of SOS behavior. The results indicate that the histone fold and Grb2-binding domains of SOS concertedly produce an intermediate state of SOS on the cell surface. The fraction of the intermediated state was reduced in positive feedback mutants, suggesting that the feedback loop functions during the intermediate state. Translocation of RAF, recognizing the active form of RAS, to the cell surface was almost abolished in the positive feedback mutants. Thus, the concerted functions of multiple membrane-associating domains of SOS governed the positive feedback loop, which is crucial for cell fate decision regulated by RAS. PMID:27924253

MICROPIK: A Multiple-Alternatives, Criterion-Referenced Decisioning Model for Evaluating CAI Software and Microcomputer Hardware Against Selected Curriculum Instructional Objectives. Paper and Report Series No. 73.

ERIC Educational Resources Information Center

Wholeben, Brent Edward

This report describing the use of operations research techniques to determine which courseware packages or what microcomputer systems best address varied instructional objectives focuses on the MICROPIK model, a highly structured evaluation technique for making such complex instructional decisions. MICROPIK is a multiple alternatives model (MAA)…

Managing wildfire events: risk-based decision making among a group of federal fire managers

Treesearch

Robyn S. Wilson; Patricia L. Winter; Lynn A. Maguire; Timothy Ascher

2011-01-01

Managing wildfire events to achieve multiple management objectives involves a high degree of decision complexity and uncertainty, increasing the likelihood that decisions will be informed by experience-based heuristics triggered by available cues at the time of the decision. The research reported here tests the prevalence of three risk-based biases among 206...

Decision making.

PubMed

Chambers, David W

2011-01-01

A decision is a commitment of resources under conditions of risk in expectation of the best future outcome. The smart decision is always the strategy with the best overall expected value-the best combination of facts and values. Some of the special circumstances involved in decision making are discussed, including decisions where there are multiple goals, those where more than one person is involved in making the decision, using trigger points, framing decisions correctly, commitments to lost causes, and expert decision makers. A complex example of deciding about removal of asymptomatic third molars, with and without an EBD search, is discussed.

Cognitive performance predicts treatment decisional abilities in mild to moderate dementia

PubMed Central

Gurrera, R.J.; Moye, J.; Karel, M.J.; Azar, A.R.; Armesto, J.C.

2016-01-01

Objective To examine the contribution of neuropsychological test performance to treatment decision-making capacity in community volunteers with mild to moderate dementia. Methods The authors recruited volunteers (44 men, 44 women) with mild to moderate dementia from the community. Subjects completed a battery of 11 neuropsychological tests that assessed auditory and visual attention, logical memory, language, and executive function. To measure decision making capacity, the authors administered the Capacity to Consent to Treatment Interview, the Hopemont Capacity Assessment Interview, and the MacCarthur Competence Assessment Tool—Treatment. Each of these instruments individually scores four decisional abilities serving capacity: understanding, appreciation, reasoning, and expression of choice. The authors used principal components analysis to generate component scores for each ability across instruments, and to extract principal components for neuropsychological performance. Results Multiple linear regression analyses demonstrated that neuropsychological performance significantly predicted all four abilities. Specifically, it predicted 77.8% of the common variance for understanding, 39.4% for reasoning, 24.6% for appreciation, and 10.2% for expression of choice. Except for reasoning and appreciation, neuropsychological predictor (β) profiles were unique for each ability. Conclusions Neuropsychological performance substantially and differentially predicted capacity for treatment decisions in individuals with mild to moderate dementia. Relationships between elemental cognitive function and decisional capacity may differ in individuals whose decisional capacity is impaired by other disorders, such as mental illness. PMID:16682669

Integrating Susceptibility into Environmental Policy: An Analysis of the National Ambient Air Quality Standard for Lead

PubMed Central

Chari, Ramya; Burke, Thomas A.; White, Ronald H.; Fox, Mary A.

2012-01-01

Susceptibility to chemical toxins has not been adequately addressed in risk assessment methodologies. As a result, environmental policies may fail to meet their fundamental goal of protecting the public from harm. This study examines how characterization of risk may change when susceptibility is explicitly considered in policy development; in particular we examine the process used by the U.S. Environmental Protection Agency (EPA) to set a National Ambient Air Quality Standard (NAAQS) for lead. To determine a NAAQS, EPA estimated air lead-related decreases in child neurocognitive function through a combination of multiple data elements including concentration-response (CR) functions. In this article, we present alternative scenarios for determining a lead NAAQS using CR functions developed in populations more susceptible to lead toxicity due to socioeconomic disadvantage. The use of CR functions developed in susceptible groups resulted in cognitive decrements greater than original EPA estimates. EPA’s analysis suggested that a standard level of 0.15 µg/m3 would fulfill decision criteria, but by incorporating susceptibility we found that options for the standard could reasonably be extended to lower levels. The use of data developed in susceptible populations would result in the selection of a more protective NAAQS under the same decision framework applied by EPA. Results are used to frame discussion regarding why cumulative risk assessment methodologies are needed to help inform policy development. PMID:22690184

Multiple perspectives on shared decision-making and interprofessional collaboration in mental healthcare.

PubMed

Chong, Wei Wen; Aslani, Parisa; Chen, Timothy F

2013-05-01

Shared decision-making is an essential element of patient-centered care in mental health. Since mental health services involve healthcare providers from different professions, a multiple perspective to shared decision-making may be valuable. The objective of this study was to explore the perceptions of different healthcare professionals on shared decision-making and current interprofessional collaboration in mental healthcare. Semi-structured interviews were conducted with 31 healthcare providers from a range of professions, which included medical practitioners (psychiatrists, general practitioners), pharmacists, nurses, occupational therapists, psychologists and social workers. Findings indicated that healthcare providers supported the notion of shared decision-making in mental health, but felt that it should be condition dependent. Medical practitioners advocated a more active participation from consumers in treatment decision-making; whereas other providers (e.g. pharmacists, occupational therapists) focused more toward acknowledging consumers' needs in decisions, perceiving themselves to be in an advisory role in supporting consumers' decision-making. Although healthcare providers acknowledged the importance of interprofessional collaboration, only a minority discussed it within the context of shared decision-making. In conclusion, healthcare providers appeared to have differing perceptions on the level of consumer involvement in shared decision-making. Interprofessional roles to facilitate shared decision-making in mental health need to be acknowledged, understood and strengthened, before an interprofessional approach to shared decision-making in mental health can be effectively implemented.

Do physicians’ recommendations pull patients away from their preferred treatment options?

PubMed Central

Mendel, Rosmarie; Traut‐Mattausch, Eva; Frey, Dieter; Bühner, Markus; Berthele, Achim; Kissling, Werner; Hamann, Johannes

2011-01-01

Abstract Context and objective  Shared decision making is especially advocated for preference‐sensitive decisions. We investigated whether physicians’ recommendations pull patients away from their preferred treatment option when making a preference‐sensitive decision. Design, participants and methods  Inpatients (N = 102 with schizophrenia, N = 101 with multiple sclerosis) were presented with a hypothetical scenario (the choice between two drugs). They were first asked about their preferences concerning the two drugs and then they received a (fictitious) clinician’s recommendation that was contrary to their preferences. Subsequently they made a final choice between the two drugs. Main outcome measures  The main outcome measure was whether the patient followed the physician’s advice in the hypothetical scenario. Thereby patient’s (pre‐recommendation) preferences served as a baseline. Results  In the decision scenario, about 48% of the patients with schizophrenia and 26% of the patients with multiple sclerosis followed the advice of their physician and thus chose the treatment option that went against their initial preferences. Patients who followed their physician’s advice were less satisfied with their decision than patients not following their physician’s advice (schizophrenia: t = 2.61, P = 0.01; multiple sclerosis: t = 2.67, P = 0.009). Discussion and conclusions  When sharing decisions with patients, physicians should be aware that their advice might influence patients’ decisions away from their preferred treatment option. They should encourage their patients to identify their own preferences and help to find the treatment option most consistent with them. PMID:21323824

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

PubMed Central

Ratcliff, Roger; Starns, Jeffrey J.

2014-01-01

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

The neuroeconomics of alcohol demand: an initial investigation of the neural correlates of alcohol cost-benefit decision making in heavy drinking men.

PubMed

MacKillop, James; Amlung, Michael T; Acker, John; Gray, Joshua C; Brown, Courtney L; Murphy, James G; Ray, Lara A; Sweet, Lawrence H

2014-07-01

Neuroeconomics integrates concepts and methods from psychology, economics, and cognitive neuroscience to understand how the brain makes decisions. In economics, demand refers to the relationship between a commodity's consumption and its cost, and, in behavioral studies, high alcohol demand has been consistently associated with greater alcohol misuse. Relatively little is known about how the brain processes demand decision making, and the current study is an initial investigation of the neural correlates of alcohol demand among heavy drinkers. Using an event-related functional magnetic resonance imaging (fMRI) paradigm, participants (N=24) selected how much they would drink under varying levels of price. These choices determined access to alcohol during a subsequent bar laboratory self-administration period. During decisions to drink in general, greater activity was present in multiple distinct subunits of the prefrontal and parietal cortices. In contrast, during decisions to drink that were demonstrably affected by the cost of alcohol, significantly greater activation was evident in frontostriatal regions, suggesting an active interplay between cognitive deliberation and subjective reward value. These choices were also characterized by significant deactivation in default mode network regions, suggesting suppression resulting from greater cognitive load. Across choice types, the anterior insula was notably recruited in diverse roles, further implicating the importance of interoceptive processing in decision-making behavior. These findings reveal the neural signatures subserving alcohol cost-benefit decision making, providing a foundation for future clinical applications of this paradigm and extending this approach to understanding the neural correlates of demand for other addictive commodities.

Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews.

PubMed

Kuesten, Carla; Bi, Jian

2018-06-03

Conventional drivers of liking analysis was extended with a time dimension into temporal drivers of liking (TDOL) based on functional data analysis methodology and non-additive models for multiple-attribute time-intensity (MATI) data. The non-additive models, which consider both direct effects and interaction effects of attributes to consumer overall liking, include Choquet integral and fuzzy measure in the multi-criteria decision-making, and linear regression based on variance decomposition. Dynamics of TDOL, i.e., the derivatives of the relative importance functional curves were also explored. Well-established R packages 'fda', 'kappalab' and 'relaimpo' were used in the paper for developing TDOL. Applied use of these methods shows that the relative importance of MATI curves offers insights for understanding the temporal aspects of consumer liking for fruit chews.

Decision making under uncertainty: a quasimetric approach.

PubMed

N'Guyen, Steve; Moulin-Frier, Clément; Droulez, Jacques

2013-01-01

We propose a new approach for solving a class of discrete decision making problems under uncertainty with positive cost. This issue concerns multiple and diverse fields such as engineering, economics, artificial intelligence, cognitive science and many others. Basically, an agent has to choose a single or series of actions from a set of options, without knowing for sure their consequences. Schematically, two main approaches have been followed: either the agent learns which option is the correct one to choose in a given situation by trial and error, or the agent already has some knowledge on the possible consequences of his decisions; this knowledge being generally expressed as a conditional probability distribution. In the latter case, several optimal or suboptimal methods have been proposed to exploit this uncertain knowledge in various contexts. In this work, we propose following a different approach, based on the geometric intuition of distance. More precisely, we define a goal independent quasimetric structure on the state space, taking into account both cost function and transition probability. We then compare precision and computation time with classical approaches.

Plan Execution Interchange Language (PLEXIL)

NASA Technical Reports Server (NTRS)

Estlin, Tara; Jonsson, Ari; Pasareanu, Corina; Simmons, Reid; Tso, Kam; Verma, Vandi

2006-01-01

Plan execution is a cornerstone of spacecraft operations, irrespective of whether the plans to be executed are generated on board the spacecraft or on the ground. Plan execution frameworks vary greatly, due to both different capabilities of the execution systems, and relations to associated decision-making frameworks. The latter dependency has made the reuse of execution and planning frameworks more difficult, and has all but precluded information sharing between different execution and decision-making systems. As a step in the direction of addressing some of these issues, a general plan execution language, called the Plan Execution Interchange Language (PLEXIL), is being developed. PLEXIL is capable of expressing concepts used by many high-level automated planners and hence provides an interface to multiple planners. PLEXIL includes a domain description that specifies command types, expansions, constraints, etc., as well as feedback to the higher-level decision-making capabilities. This document describes the grammar and semantics of PLEXIL. It includes a graphical depiction of this grammar and illustrative rover scenarios. It also outlines ongoing work on implementing a universal execution system, based on PLEXIL, using state-of-the-art rover functional interfaces and planners as test cases.

Evaluating the decision accuracy and speed of clinical data visualizations.

PubMed

Pieczkiewicz, David S; Finkelstein, Stanley M

2010-01-01

Clinicians face an increasing volume of biomedical data. Assessing the efficacy of systems that enable accurate and timely clinical decision making merits corresponding attention. This paper discusses the multiple-reader multiple-case (MRMC) experimental design and linear mixed models as means of assessing and comparing decision accuracy and latency (time) for decision tasks in which clinician readers must interpret visual displays of data. These tools can assess and compare decision accuracy and latency (time). These experimental and statistical techniques, used extensively in radiology imaging studies, offer a number of practical and analytic advantages over more traditional quantitative methods such as percent-correct measurements and ANOVAs, and are recommended for their statistical efficiency and generalizability. An example analysis using readily available, free, and commercial statistical software is provided as an appendix. While these techniques are not appropriate for all evaluation questions, they can provide a valuable addition to the evaluative toolkit of medical informatics research.

[Adoption of new technologies by health services: the challenge of analyzing relevant factors].

PubMed

Trindade, Evelinda

2008-05-01

The exponential increase in the incorporation of health technologies has been considered a key factor in increased expenditures by the health sector. Such decisions involve multiple levels and stakeholders. Decentralization has multiplied the decision-making levels, with numerous difficult choices and limited resources. The interrelationship between stakeholders is complex, in creative systems with multiple determinants and confounders. The current review discusses the interaction between the factors influencing the decisions to incorporate technologies by health services, and proposes a structure for their analysis. The application and intensity of these factors in decision-making and the incorporation of products and programs by health services shapes the installed capacity of local and regional networks and modifies the health system. Empirical observation of decision-making and technology incorporation in Brazilian health services poses an important challenge. The structured recognition and measurement of these variables can assist proactive planning of health services.

Fuzzy decision-making framework for treatment selection based on the combined QUALIFLEX-TODIM method

NASA Astrophysics Data System (ADS)

Ji, Pu; Zhang, Hong-yu; Wang, Jian-qiang

2017-10-01

Treatment selection is a multi-criteria decision-making problem of significant concern in the medical field. In this study, a fuzzy decision-making framework is established for treatment selection. The framework mitigates information loss by introducing single-valued trapezoidal neutrosophic numbers to denote evaluation information. Treatment selection has multiple criteria that remarkably exceed the alternatives. In consideration of this characteristic, the framework utilises the idea of the qualitative flexible multiple criteria method. Furthermore, it considers the risk-averse behaviour of a decision maker by employing a concordance index based on TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) method. A sensitivity analysis is performed to illustrate the robustness of the framework. Finally, a comparative analysis is conducted to compare the framework with several extant methods. Results indicate the advantages of the framework and its better performance compared with the extant methods.

A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

PubMed

Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

2018-01-01

Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.

A Method of Detections' Fusion for GNSS Anti-Spoofing.

PubMed

Tao, Huiqi; Li, Hong; Lu, Mingquan

2016-12-19

The spoofing attack is one of the security threats of systems depending on the Global Navigation Satellite System (GNSS). There have been many GNSS spoofing detection methods, and each of them focuses on a characteristic of the GNSS signal or a measurement that the receiver has obtained. The method based on a single detector is insufficient against spoofing attacks in some scenarios. How to fuse multiple detections together is a problem that concerns the performance of GNSS anti-spoofing. Scholars have put forward a model to fuse different detection results based on the Dempster-Shafer theory (DST) of evidence combination. However, there are some problems in the application. The main challenge is the valuation of the belief function, which is a key issue in DST. This paper proposes a practical method of detections' fusion based on an approach to assign the belief function for spoofing detections. The frame of discernment is simplified, and the hard decision of hypothesis testing is replaced by the soft decision; then, the belief functions for some detections can be evaluated. The method is discussed in detail, and a performance evaluation is provided, as well. Detections' fusion reduces false alarms of detection and makes the result more reliable. Experimental results based on public test datasets demonstrate the performance of the proposed method.

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

PubMed

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

2015-05-01

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

An export coefficient based inexact fuzzy bi-level multi-objective programming model for the management of agricultural nonpoint source pollution under uncertainty

NASA Astrophysics Data System (ADS)

Cai, Yanpeng; Rong, Qiangqiang; Yang, Zhifeng; Yue, Wencong; Tan, Qian

2018-02-01

In this research, an export coefficient based inexact fuzzy bi-level multi-objective programming (EC-IFBLMOP) model was developed through integrating export coefficient model (ECM), interval parameter programming (IPP) and fuzzy parameter programming (FPP) within a bi-level multi-objective programming framework. The proposed EC-IFBLMOP model can effectively deal with the multiple uncertainties expressed as discrete intervals and fuzzy membership functions. Also, the complexities in agricultural systems, such as the cooperation and gaming relationship between the decision makers at different levels, can be fully considered in the model. The developed model was then applied to identify the optimal land use patterns and BMP implementing levels for agricultural nonpoint source (NPS) pollution management in a subcatchment in the upper stream watershed of the Miyun Reservoir in north China. The results of the model showed that the desired optimal land use patterns and implementing levels of best management of practices (BMPs) would be obtained. It is the gaming result between the upper- and lower-level decision makers, when the allowable discharge amounts of NPS pollutants were limited. Moreover, results corresponding to different decision scenarios could provide a set of decision alternatives for the upper- and lower-level decision makers to identify the most appropriate management strategy. The model has a good applicability and can be effectively utilized for agricultural NPS pollution management.

Wetlands as large-scale nature-based solutions: status and future challenges for research and management

NASA Astrophysics Data System (ADS)

Thorslund, Josefin; Jarsjö, Jerker; Destouni, Georgia

2017-04-01

Wetlands are often considered as nature-based solutions that can provide a multitude of services of great social, economic and environmental value to humankind. The services may include recreation, greenhouse gas sequestration, contaminant retention, coastal protection, groundwater level and soil moisture regulation, flood regulation and biodiversity support. Changes in land-use, water use and climate can all impact wetland functions and occur at scales extending well beyond the local scale of an individual wetland. However, in practical applications, management decisions usually regard and focus on individual wetland sites and local conditions. To understand the potential usefulness and services of wetlands as larger-scale nature-based solutions, e.g. for mitigating negative impacts from large-scale change pressures, one needs to understand the combined function multiple wetlands at the relevant large scales. We here systematically investigate if and to what extent research so far has addressed the large-scale dynamics of landscape systems with multiple wetlands, which are likely to be relevant for understanding impacts of regional to global change. Our investigation regards key changes and impacts of relevance for nature-based solutions, such as large-scale nutrient and pollution retention, flow regulation and coastal protection. Although such large-scale knowledge is still limited, evidence suggests that the aggregated functions and effects of multiple wetlands in the landscape can differ considerably from those observed at individual wetlands. Such scale differences may have important implications for wetland function-effect predictability and management under large-scale change pressures and impacts, such as those of climate change.

Intersubjective decision-making for computer-aided forging technology design

NASA Astrophysics Data System (ADS)

Kanyukov, S. I.; Konovalov, A. V.; Muizemnek, O. Yu.

2017-12-01

We propose a concept of intersubjective decision-making for problems of open-die forging technology design. The intersubjective decisions are chosen from a set of feasible decisions using the fundamentals of the decision-making theory in fuzzy environment according to the Bellman-Zadeh scheme. We consider the formalization of subjective goals and the choice of membership functions for the decisions depending on subjective goals. We study the arrangement of these functions into an intersubjective membership function. The function is constructed for a resulting decision, which is chosen from a set of feasible decisions. The choice of the final intersubjective decision is discussed. All the issues are exemplified by a specific technological problem. The considered concept of solving technological problems under conditions of fuzzy goals allows one to choose the most efficient decisions from a set of feasible ones. These decisions correspond to the stated goals. The concept allows one to reduce human participation in automated design. This concept can be used to develop algorithms and design programs for forging numerous types of forged parts.

Nuclear localization of metabolic enzymes in immunity and metastasis.

PubMed

He, Yuchen; Gao, Menghui; Cao, Yiqu; Tang, Haosheng; Liu, Shuang; Tao, Yongguang

2017-12-01

Metabolism is essential to all living organisms that provide cells with energy, regulators, building blocks, enzyme cofactors and signaling molecules, and is in tune with nutritional conditions and the function of cells to make the appropriate developmental decisions or maintain homeostasis. As a fundamental biological process, metabolism state affects the production of multiple metabolites and the activation of various enzymes that participate in regulating gene expression, cell apoptosis, cancer progression and immunoreactions. Previous studies generally focus on the function played by the metabolic enzymes in the cytoplasm and mitochondrion. In this review, we conclude the role of them in the nucleus and their implications for cancer progression, immunity and metastasis. Copyright © 2017 Elsevier B.V. All rights reserved.

A System of Systems Approach to Integrating Global Sea Level Change Application Programs

NASA Astrophysics Data System (ADS)

Bambachus, M. J.; Foster, R. S.; Powell, C.; Cole, M.

2005-12-01

The global sea level change application community has numerous disparate models used to make predications over various regional and temporal scales. These models have typically been focused on limited sets of data and optimized for specific areas or questions of interest. Increasingly, decision makers at the national, international, and local/regional levels require access to these application data models and want to be able to integrate large disparate data sets, with new ubiquitous sensor data, and use these data across models from multiple sources. These requirements will force the Global Sea Level Change application community to take a new system-of-systems approach to their programs. We present a new technical architecture approach to the global sea level change program that provides external access to the vast stores of global sea level change data, provides a collaboration forum for the discussion and visualization of data, and provides a simulation environment to evaluate decisions. This architectural approach will provide the tools to support multi-disciplinary decision making. A conceptual system of systems approach is needed to address questions around the multiple approaches to tracking and predicting Sea Level Change. A systems of systems approach would include (1) a forum of data providers, modelers, and users, (2) a service oriented architecture including interoperable web services with a backbone of Grid computing capability, and (3) discovery and access functionality to the information developed through this structure. Each of these three areas would be clearly designed to maximize communication, data use for decision making and flexibility and extensibility for evolution of technology and requirements. In contemplating a system-of-systems approach, it is important to highlight common understanding and coordination as foundational to success across the multiple systems. The workflow of science in different applications is often conceptually similar but different in the details. These differences can discourage the potential for collaboration. Resources that are not inherently shared (or do not spring from a common authority) must be explicitly coordinated to avoid disrupting the collaborative research workflow. This includes tools which make the interaction of systems (and users with systems, and administrators of systems) more conceptual and higher-level than is typically done today. Such tools all appear under the heading of Grid, within a larger idea of metacomputing. We present an approach for successful collaboration and shared use of distributed research resources. The real advances in research throughput that are occurring through the use of large computers are occurring less as a function of progress in a given discrete algorithm and much more as a function of model and data coupling. Complexity normally reduces the ability of the human mind to understand and work with this kind of coupling. Intuitive Grid-based computational resources simultaneously reduce the effect of this complexity on the scientist/decision maker, and increase the ability to rationalize complexity. Research progress can even be achieved before full understanding of complexity has been reached, by modeling and experimenting and providing more data to think about. Analytic engines provided via the Grid can help digest this data and make it tractable through visualization and exploration tools. We present a rationale for increasing research throughput by leveraging more complex model and data interaction.

Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review

NASA Astrophysics Data System (ADS)

Uhde, Britta; Andreas Hahn, W.; Griess, Verena C.; Knoke, Thomas

2015-08-01

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.

Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review.

PubMed

Uhde, Britta; Hahn, W Andreas; Griess, Verena C; Knoke, Thomas

2015-08-01

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.

MAGDM linear-programming models with distinct uncertain preference structures.

PubMed

Xu, Zeshui S; Chen, Jian

2008-10-01

Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.

An Interactive Platform to Visualize Data-Driven Clinical Pathways for the Management of Multiple Chronic Conditions.

PubMed

Zhang, Yiye; Padman, Rema

2017-01-01

Patients with multiple chronic conditions (MCC) pose an increasingly complex health management challenge worldwide, particularly due to the significant gap in our understanding of how to provide coordinated care. Drawing on our prior research on learning data-driven clinical pathways from actual practice data, this paper describes a prototype, interactive platform for visualizing the pathways of MCC to support shared decision making. Created using Python web framework, JavaScript library and our clinical pathway learning algorithm, the visualization platform allows clinicians and patients to learn the dominant patterns of co-progression of multiple clinical events from their own data, and interactively explore and interpret the pathways. We demonstrate functionalities of the platform using a cluster of 36 patients, identified from a dataset of 1,084 patients, who are diagnosed with at least chronic kidney disease, hypertension, and diabetes. Future evaluation studies will explore the use of this platform to better understand and manage MCC.

Value Focused Thinking in Developing Aerobatic Aircraft Selection Model for Turkish Air Force

DTIC Science & Technology

2012-03-22

many reasons . Most problems in decision- making involve multiple objectives and uncertainties. The number of alternatives can be significant and make ...and Republic of Turkey all around the world”. This is a clear and concise statement of the most basic reason for decision. After making interview...Hwang, C.-L. (1995). Multiple Attribute Decison Making : An Introduction. California: Sage Publications. 90 Vita First Lieutenant

Actualizing Flexible National Security Space Systems

DTIC Science & Technology

2011-01-01

single launch vehicle is a decision unique to small satellites that adds an extra dimension to the launch risk calculation. While bundling...following a launch failure. The ability to bundle multiple payloads on a single launch vehicle is a decision unique to small satellites that adds an extra ... dimension to the launch risk calculation. While bundling multiple small satellites on a single launch vehicle spreads the initial launch cost across

What can the rangeland decision-making survey do for you?

USDA-ARS?s Scientific Manuscript database

Every day, rangeland managers make complicated decisions to balance multiple outcomes. The complex nature of ranch decision-making is not well understood by scientists, policy makers or the general public. To fill this gap, the Wyoming Stock Growers Association has partnered with the Agricultural Re...

Reaching for the Unknown: Multiple Target Encoding and Real-Time Decision-Making in a Rapid Reach Task

ERIC Educational Resources Information Center

Chapman, Craig S.; Gallivan, Jason P.; Wood, Daniel K.; Milne, Jennifer L.; Culham, Jody C.; Goodale, Melvyn A.

2010-01-01

Decision-making is central to human cognition. Fundamental to every decision is the ability to internally represent the available choices and their relative costs and benefits. The most basic and frequent decisions we make occur as our motor system chooses and executes only those actions that achieve our current goals. Although these interactions…

Decision-Making Styles of Active-Duty Police Officers: A Multiple-Case Occupational Study

ERIC Educational Resources Information Center

Calhoun, Patrick Wayne

2013-01-01

Little is known about the decision-making styles of active-duty police officers or what the consequences of not understanding those decision-making styles may be. The purpose of the study was to describe the demographics and decision-making profiles of active-duty police officers, as well as any relationships that may exist among these variables,…

Evidence of strategic periodicities in collective conflict dynamics.

PubMed

Dedeo, Simon; Krakauer, David; Flack, Jessica

2011-09-07

We analyse the timescales of conflict decision-making in a primate society. We present evidence for multiple, periodic timescales associated with social decision-making and behavioural patterns. We demonstrate the existence of periodicities that are not directly coupled to environmental cycles or known ultraridian mechanisms. Among specific biological and socially defined demographic classes, periodicities span timescales between hours and days. Our results indicate that these periodicities are not driven by exogenous or internal regularities but are instead driven by strategic responses to social interaction patterns. Analyses also reveal that a class of individuals, playing a critical functional role, policing, have a signature timescale of the order of 1 h. We propose a classification of behavioural timescales analogous to those of the nervous system, with high frequency, or α-scale, behaviour occurring on hour-long scales, through to multi-hour, or β-scale, behaviour, and, finally γ periodicities observed on a timescale of days.

Learning the wrong lessons? Science and fisheries management in the Chesapeake Bay blue crab fishery.

PubMed

Beem, Betsi

2012-05-01

This paper argues that information produced and then taken up for policy decision making is a function of a complex interplay within the scientific community and between scientists and the broader policy network who are all grappling with issues in a complex environment with a high degree of scientific uncertainty. The dynamics of forming and re-forming the scientific community are shaped by political processes, as are the directions and questions scientists attend to in their roles as policy advisors. Three factors: 1) social construction of scientific communities, 2) the indeterminacy of science, and 3) demands by policy makers to have concrete information for decision making; are intertwined in the production and dissemination of information that may serve as the basis for policy learning. Through this process, however, what gets learned may not be what is needed to mitigate the problem, be complete in terms of addressing multiple causations, or be correct.

Neural priming in human frontal cortex: multiple forms of learning reduce demands on the prefrontal executive system.

PubMed

Race, Elizabeth A; Shanker, Shanti; Wagner, Anthony D

2009-09-01

Past experience is hypothesized to reduce computational demands in PFC by providing bottom-up predictive information that informs subsequent stimulus-action mapping. The present fMRI study measured cortical activity reductions ("neural priming"/"repetition suppression") during repeated stimulus classification to investigate the mechanisms through which learning from the past decreases demands on the prefrontal executive system. Manipulation of learning at three levels of representation-stimulus, decision, and response-revealed dissociable neural priming effects in distinct frontotemporal regions, supporting a multiprocess model of neural priming. Critically, three distinct patterns of neural priming were identified in lateral frontal cortex, indicating that frontal computational demands are reduced by three forms of learning: (a) cortical tuning of stimulus-specific representations, (b) retrieval of learned stimulus-decision mappings, and (c) retrieval of learned stimulus-response mappings. The topographic distribution of these neural priming effects suggests a rostrocaudal organization of executive function in lateral frontal cortex.

An interactive modular design for computerized photometry in spectrochemical analysis

NASA Technical Reports Server (NTRS)

Bair, V. L.

1980-01-01

A general functional description of totally automatic photometry of emission spectra is not available for an operating environment in which the sample compositions and analysis procedures are low-volume and non-routine. The advantages of using an interactive approach to computer control in such an operating environment are demonstrated. This approach includes modular subroutines selected at multiple-option, menu-style decision points. This style of programming is used to trace elemental determinations, including the automated reading of spectrographic plates produced by a 3.4 m Ebert mount spectrograph using a dc-arc in an argon atmosphere. The simplified control logic and modular subroutine approach facilitates innovative research and program development, yet is easily adapted to routine tasks. Operator confidence and control are increased by the built-in options including degree of automation, amount of intermediate data printed out, amount of user prompting, and multidirectional decision points.

Effects of tailored neck-shoulder pain treatment based on a decision model guided by clinical assessments and standardized functional tests. A study protocol of a randomized controlled trial

PubMed Central

2012-01-01

Background A major problem with rehabilitation interventions for neck pain is that the condition may have multiple causes, thus a single treatment approach is seldom efficient. The present study protocol outlines a single blinded randomised controlled trial evaluating the effect of tailored treatment for neck-shoulder pain. The treatment is based on a decision model guided by standardized clinical assessment and functional tests with cut-off values. Our main hypothesis is that the tailored treatment has better short, intermediate and long-term effects than either non-tailored treatment or treatment-as-usual (TAU) on pain and function. We sub-sequentially hypothesize that tailored and non-tailored treatment both have better effect than TAU. Methods/Design 120 working women with minimum six weeks of nonspecific neck-shoulder pain aged 20–65, are allocated by minimisation with the factors age, duration of pain, pain intensity and disability in to the groups tailored treatment (T), non-tailored treatment (NT) or treatment-as-usual (TAU). Treatment is given to the groups T and NT for 11 weeks (27 sessions evenly distributed). An extensive presentation of the tests and treatment decision model is provided. The main treatment components are manual therapy, cranio-cervical flexion exercise and strength training, EMG-biofeedback training, treatment for cervicogenic headache, neck motor control training. A decision algorithm based on the baseline assessment determines the treatment components given to each participant of T- and NT-groups. Primary outcome measures are physical functioning (Neck Disability Index) and average pain intensity last week (Numeric Rating Scale). Secondary outcomes are general improvement (Patient Global Impression of Change scale), symptoms (Profile Fitness Mapping neck questionnaire), capacity to work in the last 6 weeks (quality and quantity) and pressure pain threshold of m. trapezius. Primary and secondary outcomes will be reported for each group with effect size and its precision. Discussion We have chosen not to include women with psychological ill-health and focus on biomedical aspects of neck pain. Future studies should aim at including psychosocial aspects in a widened treatment decision model. No important adverse events or side-effects are expected. Trial registration Current Controlled Trials registration ISRCTN49348025. PMID:22607546

The Mechanosensory Lateral Line System Mediates Activation of Socially-Relevant Brain Regions during Territorial Interactions.

PubMed

Butler, Julie M; Maruska, Karen P

2016-01-01

Animals use multiple senses during social interactions and must integrate this information in the brain to make context-dependent behavioral decisions. For fishes, the largest group of vertebrates, the mechanosensory lateral line system provides crucial hydrodynamic information for survival behaviors, but little is known about its function in social communication. Our previous work using the African cichlid fish, Astatotilapia burtoni, provided the first empirical evidence that fish use their lateral line system to detect water movements from conspecifics for mutual assessment and behavioral choices. It is unknown, however, where this socially-relevant mechanosensory information is processed in the brain to elicit adaptive behavioral responses. To examine for the first time in any fish species which brain regions receive contextual mechanosensory information, we quantified expression of the immediate early gene cfos as a proxy for neural activation in sensory and socially-relevant brain nuclei from lateral line-intact and -ablated fish following territorial interactions. Our in situ hybridization results indicate that in addition to known lateral line processing regions, socially-relevant mechanosensory information is processed in the ATn (ventromedial hypothalamus homolog), Dl (putative hippocampus homolog), and Vs (putative medial extended amygdala homolog). In addition, we identified a functional network within the conserved social decision-making network (SDMN) whose co-activity corresponds with mutual assessment and behavioral choice. Lateral line-intact and -ablated fight winners had different patterns of co-activity of these function networks and group identity could be determined solely by activation patterns, indicating the importance of mechanoreception to co-activity of the SDMN. These data show for the first time that the mechanosensory lateral line system provides relevant information to conserved decision-making centers of the brain during territorial interactions to mediate crucial behavioral choices such as whether or not to engage in a territorial fight. To our knowledge, this is also the first evidence of a subpallial nucleus receiving mechanosensory input, providing important information for elucidating homologies of decision-making circuits across vertebrates. These novel results highlight the importance of considering multimodal sensory input in mediating context-appropriate behaviors that will provide broad insights on the evolution of decision-making networks across all taxa.

Engineering tradeoff problems viewed as multiple objective optimizations and the VODCA methodology

NASA Astrophysics Data System (ADS)

Morgan, T. W.; Thurgood, R. L.

1984-05-01

This paper summarizes a rational model for making engineering tradeoff decisions. The model is a hybrid from the fields of social welfare economics, communications, and operations research. A solution methodology (Vector Optimization Decision Convergence Algorithm - VODCA) firmly grounded in the economic model is developed both conceptually and mathematically. The primary objective for developing the VODCA methodology was to improve the process for extracting relative value information about the objectives from the appropriate decision makers. This objective was accomplished by employing data filtering techniques to increase the consistency of the relative value information and decrease the amount of information required. VODCA is applied to a simplified hypothetical tradeoff decision problem. Possible use of multiple objective analysis concepts and the VODCA methodology in product-line development and market research are discussed.

Development of an autonomous treatment planning strategy for radiation therapy with effective use of population-based prior data.

PubMed

Wang, Huan; Dong, Peng; Liu, Hongcheng; Xing, Lei

2017-02-01

Current treatment planning remains a costly and labor intensive procedure and requires multiple trial-and-error adjustments of system parameters such as the weighting factors and prescriptions. The purpose of this work is to develop an autonomous treatment planning strategy with effective use of prior knowledge and in a clinically realistic treatment planning platform to facilitate radiation therapy workflow. Our technique consists of three major components: (i) a clinical treatment planning system (TPS); (ii) a formulation of decision-function constructed using an assemble of prior treatment plans; (iii) a plan evaluator or decision-function and an outer-loop optimization independent of the clinical TPS to assess the TPS-generated plan and to drive the search toward a solution optimizing the decision-function. Microsoft (MS) Visual Studio Coded UI is applied to record some common planner-TPS interactions as subroutines for querying and interacting with the TPS. These subroutines are called back in the outer-loop optimization program to navigate the plan selection process through the solution space iteratively. The utility of the approach is demonstrated by using clinical prostate and head-and-neck cases. An autonomous treatment planning technique with effective use of an assemble of prior treatment plans is developed to automatically maneuver the clinical treatment planning process in the platform of a commercial TPS. The process mimics the decision-making process of a human planner and provides a clinically sensible treatment plan automatically, thus reducing/eliminating the tedious manual trial-and-errors of treatment planning. It is found that the prostate and head-and-neck treatment plans generated using the approach compare favorably with that used for the patients' actual treatments. Clinical inverse treatment planning process can be automated effectively with the guidance of an assemble of prior treatment plans. The approach has the potential to significantly improve the radiation therapy workflow. © 2016 American Association of Physicists in Medicine.

Collaborative Strategic Decision Making in School Districts

ERIC Educational Resources Information Center

Brazer, S. David; Rich, William; Ross, Susan A.

2010-01-01

Purpose: The dual purpose of this paper is to determine how superintendents in US school districts work with stakeholders in the decision-making process and to learn how different choices superintendents make affect decision outcomes. Design/methodology/approach: This multiple case study of three school districts employs qualitative methodology to…

Decision Aids for Multiple-Decision Disease Management as Affected by Weather Input Errors

USDA-ARS?s Scientific Manuscript database

Many disease management decision support systems (DSS) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation or estimation from off-site sources, may affect model calculations and manage...

Exploring the Functioning of Decision Space: A Review of the Available Health Systems Literature

PubMed Central

Roman, Tamlyn Eslie; Cleary, Susan; McIntyre, Diane

2017-01-01

Background: The concept of decision space holds appeal as an approach to disaggregating the elements that may influence decision-making in decentralized systems. This narrative review aims to explore the functioning of decision space and the factors that influence decision space. Methods: A narrative review of the literature was conducted with searches of online databases and academic journals including PubMed Central, Emerald, Wiley, Science Direct, JSTOR, and Sage. The articles were included in the review based on the criteria that they provided insight into the functioning of decision space either through the explicit application of or reference to decision space, or implicitly through discussion of decision-making related to organizational capacity or accountability mechanisms. Results: The articles included in the review encompass literature related to decentralisation, management and decision space. The majority of the studies utilise qualitative methodologies to assess accountability mechanisms, organisational capacities such as finance, human resources and management, and the extent of decision space. Of the 138 articles retrieved, 76 articles were included in the final review. Conclusion: The literature supports Bossert’s conceptualization of decision space as being related to organizational capacities and accountability mechanisms. These functions influence the decision space available within decentralized systems. The exact relationship between decision space and financial and human resource capacities needs to be explored in greater detail to determine the potential influence on system functioning. PMID:28812832

Decision net, directed graph, and neural net processing of imaging spectrometer data

NASA Technical Reports Server (NTRS)

Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki; Barnard, Etienne

1989-01-01

A decision-net solution involving a novel hierarchical classifier and a set of multiple directed graphs, as well as a neural-net solution, are respectively presented for large-class problem and mixture problem treatments of imaging spectrometer data. The clustering method for hierarchical classifier design, when used with multiple directed graphs, yields an efficient decision net. New directed-graph rules for reducing local maxima as well as the number of perturbations required, and the new starting-node rules for extending the reachability and reducing the search time of the graphs, are noted to yield superior results, as indicated by an illustrative 500-class imaging spectrometer problem.

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.

The role of the host in a cooperating mainframe and workstation environment, volumes 1 and 2

NASA Technical Reports Server (NTRS)

Kusmanoff, Antone; Martin, Nancy L.

1989-01-01

In recent years, advancements made in computer systems have prompted a move from centralized computing based on timesharing a large mainframe computer to distributed computing based on a connected set of engineering workstations. A major factor in this advancement is the increased performance and lower cost of engineering workstations. The shift to distributed computing from centralized computing has led to challenges associated with the residency of application programs within the system. In a combined system of multiple engineering workstations attached to a mainframe host, the question arises as to how does a system designer assign applications between the larger mainframe host and the smaller, yet powerful, workstation. The concepts related to real time data processing are analyzed and systems are displayed which use a host mainframe and a number of engineering workstations interconnected by a local area network. In most cases, distributed systems can be classified as having a single function or multiple functions and as executing programs in real time or nonreal time. In a system of multiple computers, the degree of autonomy of the computers is important; a system with one master control computer generally differs in reliability, performance, and complexity from a system in which all computers share the control. This research is concerned with generating general criteria principles for software residency decisions (host or workstation) for a diverse yet coupled group of users (the clustered workstations) which may need the use of a shared resource (the mainframe) to perform their functions.

Toward the modelling of safety violations in healthcare systems.

PubMed

Catchpole, Ken

2013-09-01

When frontline staff do not adhere to policies, protocols, or checklists, managers often regard these violations as indicating poor practice or even negligence. More often than not, however, these policy and protocol violations reflect the efforts of well intentioned professionals to carry out their work efficiently in the face of systems poorly designed to meet the diverse demands of patient care. Thus, non-compliance with institutional policies and protocols often signals a systems problem, rather than a people problem, and can be influenced among other things by training, competing goals, context, process, location, case complexity, individual beliefs, the direct or indirect influence of others, job pressure, flexibility, rule definition, and clinician-centred design. Three candidates are considered for developing a model of safety behaviour and decision making. The dynamic safety model helps to understand the relationship between systems designs and human performance. The theory of planned behaviour suggests that intention is a function of attitudes, social norms and perceived behavioural control. The naturalistic decision making paradigm posits that decisions are based on a wider view of multiple patients, expertise, systems complexity, behavioural intention, individual beliefs and current understanding of the system. Understanding and predicting behavioural safety decisions could help us to encourage compliance to current processes and to design better interventions.

Managing and learning with multiple models: Objectives and optimization algorithms

USGS Publications Warehouse

Probert, William J. M.; Hauser, C.E.; McDonald-Madden, E.; Runge, M.C.; Baxter, P.W.J.; Possingham, H.P.

2011-01-01

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. ?? 2010 Elsevier Ltd.

An architecture for a continuous, user-driven, and data-driven application of clinical guidelines and its evaluation.

PubMed

Shalom, Erez; Shahar, Yuval; Lunenfeld, Eitan

2016-02-01

Design, implement, and evaluate a new architecture for realistic continuous guideline (GL)-based decision support, based on a series of requirements that we have identified, such as support for continuous care, for multiple task types, and for data-driven and user-driven modes. We designed and implemented a new continuous GL-based support architecture, PICARD, which accesses a temporal reasoning engine, and provides several different types of application interfaces. We present the new architecture in detail in the current paper. To evaluate the architecture, we first performed a technical evaluation of the PICARD architecture, using 19 simulated scenarios in the preeclampsia/toxemia domain. We then performed a functional evaluation with the help of two domain experts, by generating patient records that simulate 60 decision points from six clinical guideline-based scenarios, lasting from two days to four weeks. Finally, 36 clinicians made manual decisions in half of the scenarios, and had access to the automated GL-based support in the other half. The measures used in all three experiments were correctness and completeness of the decisions relative to the GL. Mean correctness and completeness in the technical evaluation were 1±0.0 and 0.96±0.03 respectively. The functional evaluation produced only several minor comments from the two experts, mostly regarding the output's style; otherwise the system's recommendations were validated. In the clinically oriented evaluation, the 36 clinicians applied manually approximately 41% of the GL's recommended actions. Completeness increased to approximately 93% when using PICARD. Manual correctness was approximately 94.5%, and remained similar when using PICARD; but while 68% of the manual decisions included correct but redundant actions, only 3% of the actions included in decisions made when using PICARD were redundant. The PICARD architecture is technically feasible and is functionally valid, and addresses the realistic continuous GL-based application requirements that we have defined; in particular, the requirement for care over significant time frames. The use of the PICARD architecture in the domain we examined resulted in enhanced completeness and in reduction of redundancies, and is potentially beneficial for general GL-based management of chronic patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks

PubMed Central

Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng

2017-01-01

High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity. PMID:28212328

Redefining neuromarketing as an integrated science of influence

PubMed Central

Breiter, Hans C.; Block, Martin; Blood, Anne J.; Calder, Bobby; Chamberlain, Laura; Lee, Nick; Livengood, Sherri; Mulhern, Frank J.; Raman, Kalyan; Schultz, Don; Stern, Daniel B.; Viswanathan, Vijay; Zhang, Fengqing (Zoe)

2015-01-01

Multiple transformative forces target marketing, many of which derive from new technologies that allow us to sample thinking in real time (i.e., brain imaging), or to look at large aggregations of decisions (i.e., big data). There has been an inclination to refer to the intersection of these technologies with the general topic of marketing as “neuromarketing”. There has not been a serious effort to frame neuromarketing, which is the goal of this paper. Neuromarketing can be compared to neuroeconomics, wherein neuroeconomics is generally focused on how individuals make “choices”, and represent distributions of choices. Neuromarketing, in contrast, focuses on how a distribution of choices can be shifted or “influenced”, which can occur at multiple “scales” of behavior (e.g., individual, group, or market/society). Given influence can affect choice through many cognitive modalities, and not just that of valuation of choice options, a science of influence also implies a need to develop a model of cognitive function integrating attention, memory, and reward/aversion function. The paper concludes with a brief description of three domains of neuromarketing application for studying influence, and their caveats. PMID:25709573

Redefining neuromarketing as an integrated science of influence.

PubMed

Breiter, Hans C; Block, Martin; Blood, Anne J; Calder, Bobby; Chamberlain, Laura; Lee, Nick; Livengood, Sherri; Mulhern, Frank J; Raman, Kalyan; Schultz, Don; Stern, Daniel B; Viswanathan, Vijay; Zhang, Fengqing Zoe

2014-01-01

Multiple transformative forces target marketing, many of which derive from new technologies that allow us to sample thinking in real time (i.e., brain imaging), or to look at large aggregations of decisions (i.e., big data). There has been an inclination to refer to the intersection of these technologies with the general topic of marketing as "neuromarketing". There has not been a serious effort to frame neuromarketing, which is the goal of this paper. Neuromarketing can be compared to neuroeconomics, wherein neuroeconomics is generally focused on how individuals make "choices", and represent distributions of choices. Neuromarketing, in contrast, focuses on how a distribution of choices can be shifted or "influenced", which can occur at multiple "scales" of behavior (e.g., individual, group, or market/society). Given influence can affect choice through many cognitive modalities, and not just that of valuation of choice options, a science of influence also implies a need to develop a model of cognitive function integrating attention, memory, and reward/aversion function. The paper concludes with a brief description of three domains of neuromarketing application for studying influence, and their caveats.

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).

Developmental changes in decision making under risk: The role of executive functions and reasoning abilities in 8- to 19-year-old decision makers.

PubMed

Schiebener, Johannes; García-Arias, María; García-Villamisar, Domingo; Cabanyes-Truffino, Javier; Brand, Matthias

2015-01-01

Previous studies have shown that children and adolescents often tend toward risky decisions despite explicit knowledge about the potential negative consequences. This phenomenon has been suggested to be associated with the immaturity of brain areas involved in cognitive control functions. Particularly, "frontal lobe functions," such as executive functions and reasoning, mature until young adulthood and are thought to be involved in age-related changes in decision making under explicit risk conditions. We investigated 112 participants, aged 8-19 years, with a frequently used task assessing decisions under risk, the Game of Dice Task (GDT). Additionally, we administered the Modified Card Sorting Test assessing executive functioning (categorization, cognitive flexibility, and strategy maintenance) as well as the Ravens Progressive Matrices assessing reasoning. The results showed that risk taking in the GDT decreased with increasing age and this effect was not moderated by reasoning but by executive functions: Particularly, young persons with weak executive functioning showed very risky decision making. Thus, the individual maturation of executive functions, associated with areas in the prefrontal cortex, seems to be an important factor in young peoples' behavior in risky decision-making situations.

The influence of multiple ownership interests and decision-making networks on the management of family forest lands: evidence from the United States

Treesearch

Stephanie A. Snyder; Michael A. Kilgore

2018-01-01

A national assessment of how the number of parcel owners influence family forest land management and use decisions in the US was conducted using a subset of the US Forest Service's National Woodland Owner Survey Dataset. Seventy-two percent of single parcel family forest land ownership respondents of at least 4.05 ha had multiple owners. The extent to which past...

Departures From Optimality When Pursuing Multiple Approach or Avoidance Goals

PubMed Central

2016-01-01

This article examines how people depart from optimality during multiple-goal pursuit. The authors operationalized optimality using dynamic programming, which is a mathematical model used to calculate expected value in multistage decisions. Drawing on prospect theory, they predicted that people are risk-averse when pursuing approach goals and are therefore more likely to prioritize the goal in the best position than the dynamic programming model suggests is optimal. The authors predicted that people are risk-seeking when pursuing avoidance goals and are therefore more likely to prioritize the goal in the worst position than is optimal. These predictions were supported by results from an experimental paradigm in which participants made a series of prioritization decisions while pursuing either 2 approach or 2 avoidance goals. This research demonstrates the usefulness of using decision-making theories and normative models to understand multiple-goal pursuit. PMID:26963081

Multiple Hypotheses Image Segmentation and Classification With Application to Dietary Assessment

PubMed Central

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

2016-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier’s confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback. PMID:25561457

Markov logic network based complex event detection under uncertainty

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Jia, Bin; Chen, Genshe; Chen, Hua-mei; Sullivan, Nichole; Pham, Khanh; Blasch, Erik

2018-05-01

In a cognitive reasoning system, the four-stage Observe-Orient-Decision-Act (OODA) reasoning loop is of interest. The OODA loop is essential for the situational awareness especially in heterogeneous data fusion. Cognitive reasoning for making decisions can take advantage of different formats of information such as symbolic observations, various real-world sensor readings, or the relationship between intelligent modalities. Markov Logic Network (MLN) provides mathematically sound technique in presenting and fusing data at multiple levels of abstraction, and across multiple intelligent sensors to conduct complex decision-making tasks. In this paper, a scenario about vehicle interaction is investigated, in which uncertainty is taken into consideration as no systematic approaches can perfectly characterize the complex event scenario. MLNs are applied to the terrestrial domain where the dynamic features and relationships among vehicles are captured through multiple sensors and information sources regarding the data uncertainty.

Multiple hypotheses image segmentation and classification with application to dietary assessment.

PubMed

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J; Delp, Edward J

2015-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier's confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback.

Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery.

PubMed

Speicher, Nora K; Pfeifer, Nico

2015-06-15

Despite ongoing cancer research, available therapies are still limited in quantity and effectiveness, and making treatment decisions for individual patients remains a hard problem. Established subtypes, which help guide these decisions, are mainly based on individual data types. However, the analysis of multidimensional patient data involving the measurements of various molecular features could reveal intrinsic characteristics of the tumor. Large-scale projects accumulate this kind of data for various cancer types, but we still lack the computational methods to reliably integrate this information in a meaningful manner. Therefore, we apply and extend current multiple kernel learning for dimensionality reduction approaches. On the one hand, we add a regularization term to avoid overfitting during the optimization procedure, and on the other hand, we show that one can even use several kernels per data type and thereby alleviate the user from having to choose the best kernel functions and kernel parameters for each data type beforehand. We have identified biologically meaningful subgroups for five different cancer types. Survival analysis has revealed significant differences between the survival times of the identified subtypes, with P values comparable or even better than state-of-the-art methods. Moreover, our resulting subtypes reflect combined patterns from the different data sources, and we demonstrate that input kernel matrices with only little information have less impact on the integrated kernel matrix. Our subtypes show different responses to specific therapies, which could eventually assist in treatment decision making. An executable is available upon request. © The Author 2015. Published by Oxford University Press.

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

NASA Astrophysics Data System (ADS)

Webb, E.

2006-12-01

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

Identification of water quality management policy of watershed system with multiple uncertain interactions using a multi-level-factorial risk-inference-based possibilistic-probabilistic programming approach.

PubMed

Liu, Jing; Li, Yongping; Huang, Guohe; Fu, Haiyan; Zhang, Junlong; Cheng, Guanhui

2017-06-01

In this study, a multi-level-factorial risk-inference-based possibilistic-probabilistic programming (MRPP) method is proposed for supporting water quality management under multiple uncertainties. The MRPP method can handle uncertainties expressed as fuzzy-random-boundary intervals, probability distributions, and interval numbers, and analyze the effects of uncertainties as well as their interactions on modeling outputs. It is applied to plan water quality management in the Xiangxihe watershed. Results reveal that a lower probability of satisfying the objective function (θ) as well as a higher probability of violating environmental constraints (q i ) would correspond to a higher system benefit with an increased risk of violating system feasibility. Chemical plants are the major contributors to biological oxygen demand (BOD) and total phosphorus (TP) discharges; total nitrogen (TN) would be mainly discharged by crop farming. It is also discovered that optimistic decision makers should pay more attention to the interactions between chemical plant and water supply, while decision makers who possess a risk-averse attitude would focus on the interactive effect of q i and benefit of water supply. The findings can help enhance the model's applicability and identify a suitable water quality management policy for environmental sustainability according to the practical situations.

Multi-objective Decision Based Available Transfer Capability in Deregulated Power System Using Heuristic Approaches

NASA Astrophysics Data System (ADS)

Pasam, Gopi Krishna; Manohar, T. Gowri

2016-09-01

Determination of available transfer capability (ATC) requires the use of experience, intuition and exact judgment in order to meet several significant aspects in the deregulated environment. Based on these points, this paper proposes two heuristic approaches to compute ATC. The first proposed heuristic algorithm integrates the five methods known as continuation repeated power flow, repeated optimal power flow, radial basis function neural network, back propagation neural network and adaptive neuro fuzzy inference system to obtain ATC. The second proposed heuristic model is used to obtain multiple ATC values. Out of these, a specific ATC value will be selected based on a number of social, economic, deregulated environmental constraints and related to specific applications like optimization, on-line monitoring, and ATC forecasting known as multi-objective decision based optimal ATC. The validity of results obtained through these proposed methods are scrupulously verified on various buses of the IEEE 24-bus reliable test system. The results presented and derived conclusions in this paper are very useful for planning, operation, maintaining of reliable power in any power system and its monitoring in an on-line environment of deregulated power system. In this way, the proposed heuristic methods would contribute the best possible approach to assess multiple objective ATC using integrated methods.

Identifying psychophysiological indices of expert vs. novice performance in deadly force judgment and decision making

PubMed Central

Johnson, Robin R.; Stone, Bradly T.; Miranda, Carrie M.; Vila, Bryan; James, Lois; James, Stephen M.; Rubio, Roberto F.; Berka, Chris

2014-01-01

Objective: To demonstrate that psychophysiology may have applications for objective assessment of expertise development in deadly force judgment and decision making (DFJDM). Background: Modern training techniques focus on improving decision-making skills with participative assessment between trainees and subject matter experts primarily through subjective observation. Objective metrics need to be developed. The current proof of concept study explored the potential for psychophysiological metrics in deadly force judgment contexts. Method: Twenty-four participants (novice, expert) were recruited. All wore a wireless Electroencephalography (EEG) device to collect psychophysiological data during high-fidelity simulated deadly force judgment and decision-making simulations using a modified Glock firearm. Participants were exposed to 27 video scenarios, one-third of which would have justified use of deadly force. Pass/fail was determined by whether the participant used deadly force appropriately. Results: Experts had a significantly higher pass rate compared to novices (p < 0.05). Multiple metrics were shown to distinguish novices from experts. Hierarchical regression analyses indicate that psychophysiological variables are able to explain 72% of the variability in expert performance, but only 37% in novices. Discriminant function analysis (DFA) using psychophysiological metrics was able to discern between experts and novices with 72.6% accuracy. Conclusion: While limited due to small sample size, the results suggest that psychophysiology may be developed for use as an objective measure of expertise in DFDJM. Specifically, discriminant function measures may have the potential to objectively identify expert skill acquisition. Application: Psychophysiological metrics may create a performance model with the potential to optimize simulator-based DFJDM training. These performance models could be used for trainee feedback, and/or by the instructor to assess performance objectively. PMID:25100966

Recent advances in applying decision science to managing national forests

Treesearch

Bruce G. Marcot; Matthew P. Thompson; Michael C. Runge; Frank R. Thompson; Steven McNulty; David Cleaves; Monica Tomosy; Larry A. Fisher; Andrew Bliss

2012-01-01

Management of federal public forests to meet sustainability goals and multiple use regulations is an immense challenge. To succeed, we suggest use of formal decision science procedures and tools in the context of structured decision making (SDM). SDM entails four stages: problem structuring (framing the problem and defining objectives and evaluation criteria), problem...

How Students' Values Are Intertwined with Decisions in a Socio-Scientific Issue

ERIC Educational Resources Information Center

Paraskeva-Hadjichambi, Demetra; Hadjichambis, Andreas Ch.; Korfiatis, Konstantinos

2015-01-01

The present study incorporated a scaffolding decision making procedure on an authentic environmental socio-scientific issue and investigated how students' decisions are intertwined with their values. Computer-based activities provided necessary information and allowed for the consideration of multiple aspects of the issue, the study of the effects…

Space and Power in the Ivory Tower: Decision Making in Public Higher Education

ERIC Educational Resources Information Center

Blanchette, Sandra McCoskrie

2011-01-01

The challenges of managing physical space in higher education are often left unspoken and under researched. In this multiple case study of three urban universities, decision-making processes are examined with particular attention to who has institutional decision-making authority. Effective and efficient space management is important because the…

Space and Power in the Ivory Tower: Decision Making in Public Higher Education

ERIC Educational Resources Information Center

Blanchette, Sandra McCoskrie

2010-01-01

The challenges of managing physical space in public higher education are often left unspoken and under researched. In this multiple case study of three urban universities, decision-making processes are examined with particular attention to who has institutional decision-making authority. Effective and efficient space management is important…

Teaching Empathy and Ethical Decision Making in Business Schools

ERIC Educational Resources Information Center

Baker, Diane F.

2017-01-01

Researchers in behavioral ethics seek to understand how individuals respond to the ethical dilemmas in their lives. In any given situation, multiple social and psychological variables interact to influence ethical decision making. The purpose of this article is to explore how one such variable, empathy, affects the ethical decision-making process…

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

ERIC Educational Resources Information Center

Anders, Mary C.; Christopher, F. Scott

2011-01-01

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

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

ERIC Educational Resources Information Center

Francis, Perry C.

2015-01-01

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

Data Informed Decision Making--Perspectives of Oklahoma Superintendents

ERIC Educational Resources Information Center

Kettles, Thomas D.

2017-01-01

This descriptive, multiple case study was designed to convey a clear portrayal of the DIDM practice of six superintendents and to provide a description of what these superintendents employ during their decision making process. The ability of local education leaders to strategically influence the use of data for decision making has a large effect…

A digital protection system incorporating knowledge based learning

NASA Astrophysics Data System (ADS)

Watson, Karan; Russell, B. Don; McCall, Kurt

A digital system architecture used to diagnoses the operating state and health of electric distribution lines and to generate actions for line protection is presented. The architecture is described functionally and to a limited extent at the hardware level. This architecture incorporates multiple analysis and fault-detection techniques utilizing a variety of parameters. In addition, a knowledge-based decision maker, a long-term memory retention and recall scheme, and a learning environment are described. Preliminary laboratory implementations of the system elements have been completed. Enhanced protection for electric distribution feeders is provided by this system. Advantages of the system are enumerated.

Operations concepts for Mars missions with multiple mobile spacecraft

NASA Technical Reports Server (NTRS)

Dias, William C.

1993-01-01

Missions are being proposed which involve landing a varying number (anywhere from one to 24) of small mobile spacecraft on Mars. Mission proposals include sample returns, in situ geochemistry and geology, and instrument deployment functions. This paper discusses changes needed in traditional space operations methods for support of rover operations. Relevant differences include more frequent commanding, higher risk acceptance, streamlined procedures, and reliance on additional spacecraft autonomy, advanced fault protection, and prenegotiated decisions. New methods are especially important for missions with several Mars rovers operating concurrently against time limits. This paper also discusses likely mission design limits imposed by operations constraints .

Are gains in decision-making autonomy during early adolescence beneficial for emotional functioning? The case of the United States and china.

PubMed

Qin, Lili; Pomerantz, Eva M; Wang, Qian

2009-01-01

This research examined the role of children's decision-making autonomy in their emotional functioning during early adolescence in the United States and China. Four times over the 7th and 8th grades, 825 American and Chinese children (M = 12.73 years) reported on the extent to which they versus their parents make decisions about issues children often deem as under their authority. Children also reported on their emotional functioning. American children made greater gains over time in decision-making autonomy than did Chinese children. Initial decision-making autonomy predicted enhanced emotional functioning similarly among American and Chinese children. However, gains over time in decision-making autonomy predicted enhanced emotional functioning more in the United States (vs. China) where such gains were normative.

Methodology for fleet deployment decisions. Final report

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

Stremel, J.; Matousek, M.

1995-01-01

In today`s more competitive energy market, selecting investment and operating plans for a generating system, specific plants, and major plant components is becoming increasingly critical and complex. As utilities consider off-system sales, the key factor for fleet deployment decisions is no longer simply minimizing revenue requirements. Rather, system-level value dominates. This is a measure that can be difficult to determine in the context of traditional decision making methods. Selecting the best fleet deployment option requires the ability to account for multiple sources of value under uncertain conditions for multiple utility stakeholders. The object of this paper was to develope andmore » test an approach for assessing the system-wide value of alternative fleet deployment decisions. This was done, and the approach was tested at Consolidated Edison and at Central Illinois Public Service Company.« less

Optimal allocation model of construction land based on two-level system optimization theory

NASA Astrophysics Data System (ADS)

Liu, Min; Liu, Yanfang; Xia, Yuping; Lei, Qihong

2007-06-01

The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.

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.

Nature of collective decision-making by simple yes/no decision units.

PubMed

Hasegawa, Eisuke; Mizumoto, Nobuaki; Kobayashi, Kazuya; Dobata, Shigeto; Yoshimura, Jin; Watanabe, Saori; Murakami, Yuuka; Matsuura, Kenji

2017-10-31

The study of collective decision-making spans various fields such as brain and behavioural sciences, economics, management sciences, and artificial intelligence. Despite these interdisciplinary applications, little is known regarding how a group of simple 'yes/no' units, such as neurons in the brain, can select the best option among multiple options. One prerequisite for achieving such correct choices by the brain is correct evaluation of relative option quality, which enables a collective decision maker to efficiently choose the best option. Here, we applied a sensory discrimination mechanism using yes/no units with differential thresholds to a model for making a collective choice among multiple options. The performance corresponding to the correct choice was shown to be affected by various parameters. High performance can be achieved by tuning the threshold distribution with the options' quality distribution. The number of yes/no units allocated to each option and its variability profoundly affects performance. When this variability is large, a quorum decision becomes superior to a majority decision under some conditions. The general features of this collective decision-making by a group of simple yes/no units revealed in this study suggest that this mechanism may be useful in applications across various fields.

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

PubMed

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

2014-02-01

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

Making assessments while taking repeated risks: a pattern of multiple response pathways.

PubMed

Pleskac, Timothy J; Wershbale, Avishai

2014-02-01

Beyond simply a decision process, repeated risky decisions also require a number of cognitive processes including learning, search and exploration, and attention. In this article, we examine how multiple response pathways develop over repeated risky decisions. Using the Balloon Analogue Risk Task (BART) as a case study, we show that 2 different response pathways emerge over the course of the task. The assessment pathway is a slower, more controlled pathway where participants deliberate over taking a risk. The 2nd pathway is a faster, more automatic process where no deliberation occurs. Results imply the slower assessment pathway is taken as choice conflict increases and that the faster automatic response is a learned response. Based on these results, we modify an existing formal cognitive model of decision making during the BART to account for these dual response pathways. The slower more deliberative response process is modeled with a sequential sampling process where evidence is accumulated to a threshold, while the other response is given automatically. We show that adolescents with conduct disorder and substance use disorder symptoms not only evaluate risks differently during the BART but also differ in the rate at which they develop the more automatic response. More broadly, our results suggest cognitive models of judgment decision making need to transition from treating observed decisions as the result of a single response pathway to the result of multiple response pathways that change and develop over time.

Evaluation and selection of decision-making methods to assess landfill mining projects.

PubMed

Hermann, Robert; Baumgartner, Rupert J; Vorbach, Stefan; Ragossnig, Arne; Pomberger, Roland

2015-09-01

For the first time in Austria, fundamental technological and economic studies on recovering secondary raw materials from large landfills have been carried out, based on the 'LAMIS - Landfill Mining Austria' pilot project. A main focus of the research - and the subject of this article - was to develop an assessment or decision-making procedure that allows landfill owners to thoroughly examine the feasibility of a landfill mining project in advance. Currently there are no standard procedures that would sufficiently cover all the multiple-criteria requirements. The basic structure of the multiple attribute decision making process was used to narrow down on selection, conceptual design and assessment of suitable procedures. Along with a breakdown into preliminary and main assessment, the entire foundation required was created, such as definitions of requirements to an assessment method, selection and accurate description of the various assessment criteria and classification of the target system for the present 'landfill mining' vs. 'retaining the landfill in after-care' decision-making problem. Based on these studies, cost-utility analysis and the analytical-hierarchy process were selected from the range of multiple attribute decision-making procedures and examined in detail. Overall, both methods have their pros and cons with regard to their use for assessing landfill mining projects. Merging these methods or connecting them with single-criteria decision-making methods (like the net present value method) may turn out to be reasonable and constitute an appropriate assessment method. © The Author(s) 2015.

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

Providing the Missing Link: the Exposure Science Ontology ...

EPA Pesticide Factsheets

Although knowledge-discovery tools are new to the exposure science community, these tools are critical for leveraging exposure information to design health studies and interpret results for improved public health decisions. Standardized ontologies define relationships, allow for automated reasoning, and facilitate meta-analyses. ExO will facilitate development of biologically relevant exposure metrics, design of in vitro toxicity tests, and incorporation of information on susceptibility and background exposures for risk assessment. In this approach, there are multiple levels of organization, from the global environment down through ecosystems, communities, indoor spaces, populations, organisms, tissues, and cells. We anticipate that the exposure science and environmental health community will adopt and contribute to this work, as wide acceptance is key to integration and federated searching of exposure data to support environmental and public health research. In particular, we anticipate acceptance of the concept that exposure science provides the spatial/temporal narrative about the intensity (concentration) of a stressor at the boundary between two systems: one functioning as an “environment” (stressor) and one functioning as a target (receptor). An agreed-upon exposure ontology with clear definitions and relationships should help to facilitate decision-making, study design and prioritization of research initiatives by enhancing the capacity for data colle

Peer effects on self-regulation in adolescence depend on the nature and quality of the peer interaction.

PubMed

King, Kevin M; McLaughlin, Katie A; Silk, Jennifer; Monahan, Kathryn C

2017-11-21

Adolescence is a critical period for the development of self-regulation, and peer interactions are thought to strongly influence regulation ability. Simple exposure to peers has been found to alter decisions about risky behaviors and increase sensitivity to rewards. The link between peer exposure and self-regulation is likely to vary as a function of the type and quality of peer interaction (e.g., rejection or acceptance). Little is known about how the nature of interactions with peers influences different dimensions of self-regulation. We examined how randomization to acceptance or rejection by online "virtual" peers influenced multiple dimensions of self-regulation in a multisite community sample of 273 adolescents aged 16-17 years. Compared to a neutral condition, exposure to peers produced increases in cold cognitive control, but decreased hot cognitive control. Relative to peer acceptance, peer rejection reduced distress tolerance and increased sensitivity to losses. These findings suggest that different dimensions of adolescent self-regulation are influenced by the nature of the peer context: basic cognitive functions are altered by mere exposure to peers, whereas more complex decision making and emotion regulation processes are influenced primarily by the quality of that exposure.

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.

Four Common Simplifications of Multi-Criteria Decision Analysis do not hold for River Rehabilitation

PubMed Central

2016-01-01

River rehabilitation aims at alleviating negative effects of human impacts such as loss of biodiversity and reduction of ecosystem services. Such interventions entail difficult trade-offs between different ecological and often socio-economic objectives. Multi-Criteria Decision Analysis (MCDA) is a very suitable approach that helps assessing the current ecological state and prioritizing river rehabilitation measures in a standardized way, based on stakeholder or expert preferences. Applications of MCDA in river rehabilitation projects are often simplified, i.e. using a limited number of objectives and indicators, assuming linear value functions, aggregating individual indicator assessments additively, and/or assuming risk neutrality of experts. Here, we demonstrate an implementation of MCDA expert preference assessments to river rehabilitation and provide ample material for other applications. To test whether the above simplifications reflect common expert opinion, we carried out very detailed interviews with five river ecologists and a hydraulic engineer. We defined essential objectives and measurable quality indicators (attributes), elicited the experts´ preferences for objectives on a standardized scale (value functions) and their risk attitude, and identified suitable aggregation methods. The experts recommended an extensive objectives hierarchy including between 54 and 93 essential objectives and between 37 to 61 essential attributes. For 81% of these, they defined non-linear value functions and in 76% recommended multiplicative aggregation. The experts were risk averse or risk prone (but never risk neutral), depending on the current ecological state of the river, and the experts´ personal importance of objectives. We conclude that the four commonly applied simplifications clearly do not reflect the opinion of river rehabilitation experts. The optimal level of model complexity, however, remains highly case-study specific depending on data and resource availability, the context, and the complexity of the decision problem. PMID:26954353

Linking decision-making research and cancer prevention and control: important themes.

PubMed

McCaul, Kevin D; Peters, Ellen; Nelson, Wendy; Stefanek, Michael

2005-07-01

This article describes 6 themes underlying the multiple presentations from the Basic and Applied Decision Making in Cancer Control meeting, held February 19-20, 2004. The following themes have important implications for research and practice linking basic decision-making research to cancer prevention and control: (a) Traditional decision-making theories fail to capture real-world decision making, (b) decision makers are often unable to predict future preferences, (c) preferences are often constructed on the spot and thus are influenced by situational cues, (d) decision makers often rely on feelings rather than beliefs when making a decision, (e) the perspective of the decision maker is critical in determining preferences, and (f) informed decision making may--or may not--yield the best decisions.

Incorporation of a health economic modelling tool into public health commissioning: Evidence use in a politicised context.

PubMed

Sanders, Tom; Grove, Amy; Salway, Sarah; Hampshaw, Susan; Goyder, Elizabeth

2017-08-01

This paper explores how commissioners working in an English local government authority (LA) viewed a health economic decision tool for planning services in relation to diabetes. We conducted 15 interviews and 2 focus groups between July 2015 and February 2016, with commissioners (including public health managers, data analysts and council members). Two overlapping themes were identified explaining the obstacles and enablers of using such a tool in commissioning: a) evidence cultures, and b) system interdependency. The former highlighted the diverse evidence cultures present in the LA with politicians influenced by the 'soft' social care agendas affecting their local population and treating local opinion as evidence, whilst public health managers prioritised the scientific view of evidence informed by research. System interdependency further complicated the decision making process by recognizing interlinking with departments and other disease groups. To achieve legitimacy within the commissioning arena health economic modelling needs to function effectively in a highly politicised environment where decisions are made not only on the basis of research evidence, but on grounds of 'soft' data, personal opinion and intelligence. In this context decisions become politicised, with multiple opinions seeking a voice. The way that such decisions are negotiated and which ones establish authority is of importance. We analyse the data using Larson's (1990) discursive field concept to show how the tool becomes an object of research push and pull likely to be used instrumentally by stakeholders to advance specific agendas, not a means of informing complex decisions. In conclusion, LA decision making is underpinned by a transactional business ethic which is a further potential 'pull' mechanism for the incorporation of health economic modelling in local commissioning. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Risky decisions and their consequences: neural processing by boys with Antisocial Substance Disorder.

PubMed

Crowley, Thomas J; Dalwani, Manish S; Mikulich-Gilbertson, Susan K; Du, Yiping P; Lejuez, Carl W; Raymond, Kristen M; Banich, Marie T

2010-09-22

Adolescents with conduct and substance problems ("Antisocial Substance Disorder" (ASD)) repeatedly engage in risky antisocial and drug-using behaviors. We hypothesized that, during processing of risky decisions and resulting rewards and punishments, brain activation would differ between abstinent ASD boys and comparison boys. We compared 20 abstinent adolescent male patients in treatment for ASD with 20 community controls, examining rapid event-related blood-oxygen-level-dependent (BOLD) responses during functional magnetic resonance imaging. In 90 decision trials participants chose to make either a cautious response that earned one cent, or a risky response that would either gain 5 cents or lose 10 cents; odds of losing increased as the game progressed. We also examined those times when subjects experienced wins, or separately losses, from their risky choices. We contrasted decision trials against very similar comparison trials requiring no decisions, using whole-brain BOLD-response analyses of group differences, corrected for multiple comparisons. During decision-making ASD boys showed hypoactivation in numerous brain regions robustly activated by controls, including orbitofrontal and dorsolateral prefrontal cortices, anterior cingulate, basal ganglia, insula, amygdala, hippocampus, and cerebellum. While experiencing wins, ASD boys had significantly less activity than controls in anterior cingulate, temporal regions, and cerebellum, with more activity nowhere. During losses ASD boys had significantly more activity than controls in orbitofrontal cortex, dorsolateral prefrontal cortex, brain stem, and cerebellum, with less activity nowhere. Adolescent boys with ASD had extensive neural hypoactivity during risky decision-making, coupled with decreased activity during reward and increased activity during loss. These neural patterns may underlie the dangerous, excessive, sustained risk-taking of such boys. The findings suggest that the dysphoria, reward insensitivity, and suppressed neural activity observed among older addicted persons also characterize youths early in the development of substance use disorders.

UML Profiles for Design Decisions and Non-Functional Requirements

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

Zhu, Liming; Gorton, Ian

2007-06-30

A software architecture is composed of a collection of design decisions. Each design decision helps or hinders certain Non-Functional Requirements (NFR). Current software architecture views focus on expressing components and connectors in the system. Design decisions and their relationships with non-functional requirements are often captured in separate design documentation, not explicitly expressed in any views. This disassociation makes architecture comprehension and architecture evolution harder. In this paper, we propose a UML profile for modeling design decisions and an associated UML profile for modeling non-functional requirements in a generic way. The two UML profiles treat design decisions and nonfunctional requirements asmore » first-class elements. Modeled design decisions always refer to existing architectural elements and thus maintain traceability between the two. We provide a mechanism for checking consistency over this traceability. An exemplar is given as« less

Decision feedback loop for tracking a polyphase modulated carrier

NASA Technical Reports Server (NTRS)

Simon, M. K. (Inventor)

1974-01-01

A multiple phase modulated carrier tracking loop for use in a frequency shift keying system is described in which carrier tracking efficiency is improved by making use of the decision signals made on the data phase transmitted in each T-second interval. The decision signal is used to produce a pair of decision-feedback quadrature signals for enhancing the loop's performance in developing a loop phase error signal.

Undetected cognitive impairment and decision-making capacity in patients receiving hospice care.

PubMed

Burton, Cynthia Z; Twamley, Elizabeth W; Lee, Lana C; Palmer, Barton W; Jeste, Dilip V; Dunn, Laura B; Irwin, Scott A

2012-04-01

: Cognitive dysfunction is common in patients with advanced, life-threatening illness and can be attributed to a variety of factors (e.g., advanced age, opiate medication). Such dysfunction likely affects decisional capacity, which is a crucial consideration as the end-of-life approaches and patients face multiple choices regarding treatment, family, and estate planning. This study examined the prevalence of cognitive impairment and its impact on decision-making abilities among hospice patients with neither a chart diagnosis of a cognitive disorder nor clinically apparent cognitive impairment (e.g., delirium, unresponsiveness). : A total of 110 participants receiving hospice services completed a 1-hour neuropsychological battery, a measure of decisional capacity, and accompanying interviews. : In general, participants were mildly impaired on measures of verbal learning, verbal memory, and verbal fluency; 54% of the sample was classified as having significant, previously undetected cognitive impairment. These individuals performed significantly worse than the other participants on all neuropsychological and decisional capacity measures, with effect sizes ranging from medium to very large (0.43-2.70). A number of verbal abilities as well as global cognitive functioning significantly predicted decision-making capacity. : Despite an absence of documented or clinically obvious impairment, more than half of the sample had significant cognitive impairments. Assessment of cognition in hospice patients is warranted, including assessment of verbal abilities that may interfere with understanding or reasoning related to treatment decisions. Identification of patients at risk for impaired cognition and decision making may lead to effective interventions to improve decision making and honor the wishes of patients and families.

Calcium dynamics regulating the timing of decision-making in C. elegans.

PubMed

Tanimoto, Yuki; Yamazoe-Umemoto, Akiko; Fujita, Kosuke; Kawazoe, Yuya; Miyanishi, Yosuke; Yamazaki, Shuhei J; Fei, Xianfeng; Busch, Karl Emanuel; Gengyo-Ando, Keiko; Nakai, Junichi; Iino, Yuichi; Iwasaki, Yuishi; Hashimoto, Koichi; Kimura, Koutarou D

2017-05-23

Brains regulate behavioral responses with distinct timings. Here we investigate the cellular and molecular mechanisms underlying the timing of decision-making during olfactory navigation in Caenorhabditis elegans . We find that, based on subtle changes in odor concentrations, the animals appear to choose the appropriate migratory direction from multiple trials as a form of behavioral decision-making. Through optophysiological, mathematical and genetic analyses of neural activity under virtual odor gradients, we further find that odor concentration information is temporally integrated for a decision by a gradual increase in intracellular calcium concentration ([Ca 2+ ] i ), which occurs via L-type voltage-gated calcium channels in a pair of olfactory neurons. In contrast, for a reflex-like behavioral response, [Ca 2+ ] i rapidly increases via multiple types of calcium channels in a pair of nociceptive neurons. Thus, the timing of neuronal responses is determined by cell type-dependent involvement of calcium channels, which may serve as a cellular basis for decision-making.

Multiple Attribute Group Decision-Making Methods Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Partitioned Bonferroni Mean Aggregation Operators.

PubMed

Yin, Kedong; Yang, Benshuo; Li, Xuemei

2018-01-24

In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making.

Calcium dynamics regulating the timing of decision-making in C. elegans

PubMed Central

Tanimoto, Yuki; Yamazoe-Umemoto, Akiko; Fujita, Kosuke; Kawazoe, Yuya; Miyanishi, Yosuke; Yamazaki, Shuhei J; Fei, Xianfeng; Busch, Karl Emanuel; Gengyo-Ando, Keiko; Nakai, Junichi; Iino, Yuichi; Iwasaki, Yuishi; Hashimoto, Koichi; Kimura, Koutarou D

2017-01-01

Brains regulate behavioral responses with distinct timings. Here we investigate the cellular and molecular mechanisms underlying the timing of decision-making during olfactory navigation in Caenorhabditis elegans. We find that, based on subtle changes in odor concentrations, the animals appear to choose the appropriate migratory direction from multiple trials as a form of behavioral decision-making. Through optophysiological, mathematical and genetic analyses of neural activity under virtual odor gradients, we further find that odor concentration information is temporally integrated for a decision by a gradual increase in intracellular calcium concentration ([Ca2+]i), which occurs via L-type voltage-gated calcium channels in a pair of olfactory neurons. In contrast, for a reflex-like behavioral response, [Ca2+]i rapidly increases via multiple types of calcium channels in a pair of nociceptive neurons. Thus, the timing of neuronal responses is determined by cell type-dependent involvement of calcium channels, which may serve as a cellular basis for decision-making. DOI: http://dx.doi.org/10.7554/eLife.21629.001 PMID:28532547

Multiple Attribute Group Decision-Making Methods Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Partitioned Bonferroni Mean Aggregation Operators

PubMed Central

Yin, Kedong; Yang, Benshuo

2018-01-01

In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making. PMID:29364849

Interprofessional education about patient decision support in specialty care.

PubMed

Politi, Mary C; Pieterse, Arwen H; Truant, Tracy; Borkhoff, Cornelia; Jha, Vikram; Kuhl, Laura; Nicolai, Jennifer; Goss, Claudia

2011-11-01

Specialty care involves services provided by health professionals who focus on treating diseases affecting one body system. In contrast to primary care - aimed at providing continuous, comprehensive care - specialty care often involves intermittent episodes of care focused around specific medical conditions. In addition, it typically includes multiple providers who have unique areas of expertise that are important in supporting patients' care. Interprofessional care involves multiple professionals from different disciplines collaborating to provide an integrated approach to patient care. For patients to experience continuity of care across interprofessional providers, providers need to communicate and maintain a shared sense of responsibility to their patients. In this article, we describe challenges inherent in providing interprofessional patient decision support in specialty care. We propose ways for providers to engage in interprofessional decision support and discuss promising approaches to teaching an interprofessional decision support to specialty care providers. Additional evaluation and empirical research are required before further recommendations can be made about education for interprofessional decision support in specialty care.

Activational and effort-related aspects of motivation: neural mechanisms and implications for psychopathology.

PubMed

Salamone, John D; Yohn, Samantha E; López-Cruz, Laura; San Miguel, Noemí; Correa, Mercè

2016-05-01

Motivation has been defined as the process that allows organisms to regulate their internal and external environment, and control the probability, proximity and availability of stimuli. As such, motivation is a complex process that is critical for survival, which involves multiple behavioural functions mediated by a number of interacting neural circuits. Classical theories of motivation suggest that there are both directional and activational aspects of motivation, and activational aspects (i.e. speed and vigour of both the instigation and persistence of behaviour) are critical for enabling organisms to overcome work-related obstacles or constraints that separate them from significant stimuli. The present review discusses the role of brain dopamine and related circuits in behavioural activation, exertion of effort in instrumental behaviour, and effort-related decision-making, based upon both animal and human studies. Impairments in behavioural activation and effort-related aspects of motivation are associated with psychiatric symptoms such as anergia, fatigue, lassitude and psychomotor retardation, which cross multiple pathologies, including depression, schizophrenia, and Parkinson's disease. Therefore, this review also attempts to provide an interdisciplinary approach that integrates findings from basic behavioural neuroscience, behavioural economics, clinical neuropsychology, psychiatry, and neurology, to provide a coherent framework for future research and theory in this critical field. Although dopamine systems are a critical part of the brain circuitry regulating behavioural activation, exertion of effort, and effort-related decision-making, mesolimbic dopamine is only one part of a distributed circuitry that includes multiple neurotransmitters and brain areas. Overall, there is a striking similarity between the brain areas involved in behavioural activation and effort-related processes in rodents and in humans. Animal models of effort-related decision-making are highly translatable to humans, and an emerging body of evidence indicates that alterations in effort-based decision-making are evident in several psychiatric and neurological disorders. People with major depression, schizophrenia, and Parkinson's disease show evidence of decision-making biases towards a lower exertion of effort. Translational studies linking research with animal models, human volunteers, and clinical populations are greatly expanding our knowledge about the neural basis of effort-related motivational dysfunction, and it is hoped that this research will ultimately lead to improved treatment for motivational and psychomotor symptoms in psychiatry and neurology. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.

PubMed

Abidi, Samina

2017-10-26

Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.

Impact of Seasonal Forecasts on Agriculture

NASA Astrophysics Data System (ADS)

Aldor-Noiman, S. C.

2014-12-01

More extreme and volatile weather conditions are a threat to U.S. agricultural productivity today, as multiple environmental conditions during the growing season impact crop yields. That's why farmers' agronomic management decisions are dominated by consideration for near, medium and seasonal forecasts of climate. The Climate Corporation aims to help farmers around the world protect and improve their farming operations by providing agronomic decision support tools that leverage forecasts on multiple timescales to provide valuable insights directly to farmers. In this talk, we will discuss the impact of accurate seasonal forecasts on major decisions growers face each season. We will also discuss assessment and evaluation of seasonal forecasts in the context of agricultural applications.

Altered Intrinsic Hippocmapus Declarative Memory Network and Its Association with Impulsivity in Abstinent Heroin Dependent Subjects

PubMed Central

Zhai, Tian-Ye; Shao, Yong-Cong; Xie, Chun-Ming; Ye, En-Mao; Zou, Feng; Fu, Li-Ping; Li, Wen-Jun; Chen, Gang; Chen, Guang-Yu; Zhang, Zheng-Guo; Li, Shi-Jiang; Yang, Zheng

2014-01-01

Converging evidence suggests that addiction can be considered a disease of aberrant learning and memory with impulsive decision-making. In the past decades, numerous studies have demonstrated that drug addiction is involved in multiple memory systems such as classical conditioned drug memory, instrumental learning memory and the habitual learning memory. However, most of these studies have focused on the contributions of non-declarative memory, and declarative memory has largely been neglected in the research of addiction. Based on a recent finding that hippocampus, as a core functioning region of declarative memory, was proved biased the decision-making process based on past experiences by spreading associated reward values throughout memory. Our present study focused on the hippocampus. By utilizing seed-based network analysis on the resting-state functional MRI datasets with the seed hippocampus we tested how the intrinsic hippocampal memory network altered towards drug addiction, and examined how the functional connectivity strength within the altered hippocampal network correlated with behavioral index ‘impulsivity’. Our results demonstrated that HD group showed enhanced coherence between hippocampus which represents declarative memory system and non-declarative rewardguided learning memory system, and also showed attenuated intrinsic functional link between hippocampus and top-down control system, compared to the CN group. This alteration was furthered found to have behavioral significance over the behavioral index ‘impulsivity’ measured with Barratt Impulsiveness Scale (BIS). These results provide insights into the mechanism of declarative memory underlying the impulsive behavior in drug addiction. PMID:25008351

Numeric Function Generators Using Decision Diagrams for Discrete Functions

DTIC Science & Technology

2009-05-01

Taylor series and Chebyshev series. Since polynomial functions can be realized with multipliers and adders, any numeric functions can be realized in...NFGs from the decision diagrams. Since nu- meric functions can be expanded into polynomial functions, such as a Taylor series, in this section, we use...pp. 107–114, July 1995. [13] T. Kam, T. Villa, R. K. Brayton , and A. L. Sangiovanni- Vincentelli, “Multi-valued decision diagrams: Theory and appli

Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks.

PubMed

Fogelmark, Karl; Peterson, Carsten; Troein, Carl

2016-01-01

Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks.

Decomposition-Based Decision Making for Aerospace Vehicle Design

NASA Technical Reports Server (NTRS)

Borer, Nicholas K.; Mavris, DImitri N.

2005-01-01

Most practical engineering systems design problems have multiple and conflicting objectives. Furthermore, the satisfactory attainment level for each objective ( requirement ) is likely uncertain early in the design process. Systems with long design cycle times will exhibit more of this uncertainty throughout the design process. This is further complicated if the system is expected to perform for a relatively long period of time, as now it will need to grow as new requirements are identified and new technologies are introduced. These points identify a need for a systems design technique that enables decision making amongst multiple objectives in the presence of uncertainty. Traditional design techniques deal with a single objective or a small number of objectives that are often aggregates of the overarching goals sought through the generation of a new system. Other requirements, although uncertain, are viewed as static constraints to this single or multiple objective optimization problem. With either of these formulations, enabling tradeoffs between the requirements, objectives, or combinations thereof is a slow, serial process that becomes increasingly complex as more criteria are added. This research proposal outlines a technique that attempts to address these and other idiosyncrasies associated with modern aerospace systems design. The proposed formulation first recasts systems design into a multiple criteria decision making problem. The now multiple objectives are decomposed to discover the critical characteristics of the objective space. Tradeoffs between the objectives are considered amongst these critical characteristics by comparison to a probabilistic ideal tradeoff solution. The proposed formulation represents a radical departure from traditional methods. A pitfall of this technique is in the validation of the solution: in a multi-objective sense, how can a decision maker justify a choice between non-dominated alternatives? A series of examples help the reader to observe how this technique can be applied to aerospace systems design and compare the results of this so-called Decomposition-Based Decision Making to more traditional design approaches.

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

PubMed Central

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

2015-01-01

Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases. PMID:26295344

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

PubMed

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

2015-01-01

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

Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

PubMed

Yaeli, Steve; Meir, Ron

2010-01-01

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

An intelligent, knowledge-based multiple criteria decision making advisor for systems design

NASA Astrophysics Data System (ADS)

Li, Yongchang

In systems engineering, design and operation of systems are two main problems which always attract researcher's attentions. The accomplishment of activities in these problems often requires proper decisions to be made so that the desired goal can be achieved, thus, decision making needs to be carefully fulfilled in the design and operation of systems. Design is a decision making process which permeates through out the design process, and is at the core of all design activities. In modern aircraft design, more and more attention is paid to the conceptual and preliminary design phases so as to increase the odds of choosing a design that will ultimately be successful at the completion of the design process, therefore, decisions made during these early design stages play a critical role in determining the success of a design. Since aerospace systems are complex systems with interacting disciplines and technologies, the Decision Makers (DMs) dealing with such design problems are involved in balancing the multiple, potentially conflicting attributes/criteria, transforming a large amount of customer supplied guidelines into a solidly defined set of requirement definitions. Thus, one could state with confidence that modern aerospace system design is a Multiple Criteria Decision Making (MCDM) process. A variety of existing decision making methods are available to deal with this type of decision problems. The selection of the most appropriate decision making method is of particular importance since inappropriate decision methods are likely causes of misleading engineering design decisions. With no sufficient knowledge about each of the methods, it is usually difficult for the DMs to find an appropriate analytical model capable of solving their problems. In addition, with the complexity of the decision problem and the demand for more capable methods increasing, new decision making methods are emerging with time. These various methods exacerbate the difficulty of the selection of an appropriate decision making method. Furthermore, some DMs may be exclusively using one or two specific methods which they are familiar with or trust and not realizing that they may be inappropriate to handle certain classes of the problems, thus yielding erroneous results. These issues reveal that in order to ensure a good decision a suitable decision method should be chosen before the decision making process proceeds. The first part of this dissertation proposes an MCDM process supported by an intelligent, knowledge-based advisor system referred to as Multi-Criteria Interactive Decision-Making Advisor and Synthesis process (MIDAS), which is able to facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. The second part of this dissertation presents an autonomous decision making advisor which is capable of dealing with ever-evolving real time information and making autonomous decisions under uncertain conditions. The advisor encompasses a Markov Decision Process (MDP) formulation which takes uncertainty into account when determines the best action for each system state. (Abstract shortened by UMI.)

Individual differences in intrinsic brain connectivity predict decision strategy.

PubMed

Barnes, Kelly Anne; Anderson, Kevin M; Plitt, Mark; Martin, Alex

2014-10-15

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

Education Leaders' Decision-Making Processes about Educational Facilities in a University Multiple Stakeholder Environment

ERIC Educational Resources Information Center

Kelting, Scott

2011-01-01

This research is a retrospective case study designed to document and analyze the process of decision-making by educational leaders and stakeholders at a four-year university. For this study, educational leaders and key stakeholders agreed to extensive interviews about the decisions made during the design, construction, and post-occupancy phases of…

An Improved Decision Tree for Predicting a Major Product in Competing Reactions

ERIC Educational Resources Information Center

Graham, Kate J.

2014-01-01

When organic chemistry students encounter competing reactions, they are often overwhelmed by the task of evaluating multiple factors that affect the outcome of a reaction. The use of a decision tree is a useful tool to teach students to evaluate a complex situation and propose a likely outcome. Specifically, a decision tree can help students…

Decision Making for Educational Leaders: Underexamined Dimensions and Issues. SUNY Series, Educational Leadership

ERIC Educational Resources Information Center

Johnson, Bob L., Jr.; Kruse, Sharon D.

2010-01-01

Why another book on decision making? In this increasingly complex world, there are many tensions inherent in the daily practice of educational leaders. This book illuminates these tensions, and acknowledges the reality that there are already multiple approaches to decision making in any educational context. The authors offer a guide to integrate…

Altered moral decision-making in patients with idiopathic Parkinson's disease.

PubMed

Rosen, Jan B; Rott, Elisa; Ebersbach, Georg; Kalbe, Elke

2015-10-01

Moral decision-making essentially contributes to social conduct. Although patients with Parkinson's disease (PD) show deficits in (non-moral) decision making and related neuropsychological functions, i.e. executive functions, theory of mind (ToM), and empathy, moral decision-making has rarely been examined in PD patients. We examined possible alterations of moral decision-making and associated functions in PD. Twenty non-demented PD patients and 23 age- and education-matched healthy control participants were examined with tests that assess reasoning, executive functions (set-shifting and planning), ToM and empathy, decision-making under risk, and moral intuitions. Moral decision-making was assessed with a close-to-everyday moral dilemma paradigm that opposes socially oriented "altruistic" choices to self-beneficial "egoistic" choices in 20 moral dilemma short stories (10 high and 10 low emotional). Concurrently, electrodermal activity was recorded. PD patients made more egoistic moral decisions than healthy controls. Remarkably, while reasoning, planning and empathy correlated with moral decision-making in the control group, in the PD group neuropsychological functions and dopaminergic medication did not correlate with moral decisions. No evidence for reduced skin conductance responses in PD patients and no relationships between skin conductance responses and moral decisions were observed. This study provides evidence for moral decision-making dysfunctions in PD patients who made more egoistic moral decisions. As a possible underlying mechanism, reduced exercise of attentional control due to a dysfunctional interplay between the prefrontal cortex and the basal ganglia is discussed. Future research will have to determine the impact of PD patients' moral decision-making dysfunctions on everyday life and further determine correlates of the deficits. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integration of Multiple Data Sources to Simulate the Dynamics of Land Systems

PubMed Central

Deng, Xiangzheng; Su, Hongbo; Zhan, Jinyan

2008-01-01

In this paper we present and develop a new model, which we have called Dynamics of Land Systems (DLS). The DLS model is capable of integrating multiple data sources to simulate the dynamics of a land system. Three main modules are incorporated in DLS: a spatial regression module, to explore the relationship between land uses and influencing factors, a scenario analysis module of the land uses of a region during the simulation period and a spatial disaggregation module, to allocate land use changes from a regional level to disaggregated grid cells. A case study on Taips County in North China is incorporated in this paper to test the functionality of DLS. The simulation results under the baseline, economic priority and environmental scenarios help to understand the land system dynamics and project near future land-use trajectories of a region, in order to focus management decisions on land uses and land use planning. PMID:27879726

Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

NASA Astrophysics Data System (ADS)

Bevilacqua, R.; Lehmann, T.; Romano, M.

2011-04-01

This work introduces a novel control algorithm for close proximity multiple spacecraft autonomous maneuvers, based on hybrid linear quadratic regulator/artificial potential function (LQR/APF), for applications including autonomous docking, on-orbit assembly and spacecraft servicing. Both theoretical developments and experimental validation of the proposed approach are presented. Fuel consumption is sub-optimized in real-time through re-computation of the LQR at each sample time, while performing collision avoidance through the APF and a high level decisional logic. The underlying LQR/APF controller is integrated with a customized wall-following technique and a decisional logic, overcoming problems such as local minima. The algorithm is experimentally tested on a four spacecraft simulators test bed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School. The metrics to evaluate the control algorithm are: autonomy of the system in making decisions, successful completion of the maneuver, required time, and propellant consumption.

Enhancement Of Reading Accuracy By Multiple Data Integration

NASA Astrophysics Data System (ADS)

Lee, Kangsuk

1989-07-01

In this paper, a multiple sensor integration technique with neural network learning algorithms is presented which can enhance the reading accuracy of the hand-written numerals. Many document reading applications involve hand-written numerals in a predetermined location on a form, and in many cases, critical data is redundantly described. The amount of a personal check is one such case which is written redundantly in numerals and in alphabetical form. Information from two optical character recognition modules, one specialized for digits and one for words, is combined to yield an enhanced recognition of the amount. The combination can be accomplished by a decision tree with "if-then" rules, but by simply fusing two or more sets of sensor data in a single expanded neural net, the same functionality can be expected with a much reduced system cost. Experimental results of fusing two neural nets to enhance overall recognition performance using a controlled data set are presented.

A management and optimisation model for water supply planning in water deficit areas

NASA Astrophysics Data System (ADS)

Molinos-Senante, María; Hernández-Sancho, Francesc; Mocholí-Arce, Manuel; Sala-Garrido, Ramón

2014-07-01

The integrated water resources management approach has proven to be a suitable option for efficient, equitable and sustainable water management. In water-poor regions experiencing acute and/or chronic shortages, optimisation techniques are a useful tool for supporting the decision process of water allocation. In order to maximise the value of water use, an optimisation model was developed which involves multiple supply sources (conventional and non-conventional) and multiple users. Penalties, representing monetary losses in the event of an unfulfilled water demand, have been incorporated into the objective function. This model represents a novel approach which considers water distribution efficiency and the physical connections between water supply and demand points. Subsequent empirical testing using data from a Spanish Mediterranean river basin demonstrated the usefulness of the global optimisation model to solve existing water imbalances at the river basin level.

Integration of Ancillary Data for Improved Clinical Use: A Prototype within the VA's DHCP

PubMed Central

Andrews, Robert D.

1989-01-01

The Department of Veterans Affairs' (VA) Decentralized Hospital Computer Program (DHCP) is composed of several clinical modules that provide for the clinical information needs of their respective ancillary services. Using information from multiple ancillary packages is sometimes cumbersome. A prototype is being developed aimed at integrating ancillary data by storing clinical data oriented to the patient so that there is easy interaction of data from multiple services. A set of program utilities provide for user-defined functions of reporting, queries, entry, and decision support. Information can be used to monitor quality of care by providing feedback in the form of reports, reminders, and bulletins. Initial testing has indicated the prototype's design and implementation are feasible (in terms of space requirements, speed, and ease of use) in both outpatient and inpatient environments. The design and development of this prototype are described.

CAN BIVALVES BE USEFUL INDICATORS OF ECOSYSTEM CONDITION?

EPA Science Inventory

Numerous management decisions are made to sustain multiple, and often competing, products and services from coastal ecosystems. Scientific support for these decisions emanate from environmental indicators or selected measurements used in a monitoring program. Indicators are surro...

Clinical cognition and diagnostic error: applications of a dual process model of reasoning.

PubMed

Croskerry, Pat

2009-09-01

Both systemic and individual factors contribute to missed or delayed diagnoses. Among the multiple factors that impact clinical performance of the individual, the caliber of cognition is perhaps the most relevant and deserves our attention and understanding. In the last few decades, cognitive psychologists have gained substantial insights into the processes that underlie cognition, and a new, universal model of reasoning and decision making has emerged, Dual Process Theory. The theory has immediate application to medical decision making and provides an overall schema for understanding the variety of theoretical approaches that have been taken in the past. The model has important practical applications for decision making across the multiple domains of healthcare, and may be used as a template for teaching decision theory, as well as a platform for future research. Importantly, specific operating characteristics of the model explain how diagnostic failure occurs.

Coaching Ourselves to Perform Multiplicity and Advocacy: A Response to Stephens and Mills

ERIC Educational Resources Information Center

Cahnmann-Taylor, Melisa

2014-01-01

Cahnmann-Taylor draws on Boalian Theatre of the Oppressed to offer a practice for literacy teachers and coaches that can open up multiple perspectives and multiple levels of intentions and motivations for a teacher's decision making. She challenges coaches and teachers to engage in artistic examinations of multiplicity to move toward performing…

Exploring Canadian Women's Multiple Abortion Experiences: Implications for Reducing Stigma and Improving Patient-Centered Care.

PubMed

LaRoche, Kathryn J; Foster, Angel M

2018-05-24

Roughly one-third of all abortions in Canada are subsequent abortions. However, few published reports showcase women's voices or explore women's experiences on this topic. Our study aimed to understand better the ways that women who have had multiple abortions talk about and view those experiences. Between 2012 and 2016, we conducted in-depth interviews with 41 Canadian women who had a total of 87 abortions in the 5 years preceding the interviews. We audio-recorded and transcribed all English- and French-language interviews and analyzed our data for content and themes using a multiphased iterative approach and inductive and deductive techniques. Women described their abortion experiences as unique life events, even in cases when the overarching circumstances surrounding the pregnancies were similar. Participants recalled multiple factors that influenced their decisions to terminate, including their relationship status; level of support from family and friends; financial situation; health status; previous reproductive health, pregnancy, and abortion experiences; and desire to parent. In general, a previous abortion demystified the abortion process but did not play a significant role in decision making. Women described intensified feelings of shame and both internalized and externalized stigma surrounding their decision to have more than one abortion. However, the overwhelming majority were confident in their decisions. The often-used phase "repeat abortion" fails to capture women's experiences and the complex decision making surrounding each pregnancy. Efforts to reframe the narrative of multiple abortions, including among health care providers, could help reduce the amplified stigma associated with having more than one lifetime abortion. Copyright © 2018 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

The effects of normal aging on multiple aspects of financial decision-making.

PubMed

Bangma, Dorien F; Fuermaier, Anselm B M; Tucha, Lara; Tucha, Oliver; Koerts, Janneke

2017-01-01

Financial decision-making (FDM) is crucial for independent living. Due to cognitive decline that accompanies normal aging, older adults might have difficulties in some aspects of FDM. However, an improved knowledge, personal experience and affective decision-making, which are also related to normal aging, may lead to a stable or even improved age-related performance in some other aspects of FDM. Therefore, the present explorative study examines the effects of normal aging on multiple aspects of FDM. One-hundred and eighty participants (range 18-87 years) were assessed with eight FDM tests and several standard neuropsychological tests. Age effects were evaluated using hierarchical multiple regression analyses. The validity of the prediction models was examined by internal validation (i.e. bootstrap resampling procedure) as well as external validation on another, independent, sample of participants (n = 124). Multiple regression and correlation analyses were applied to investigate the mediation effect of standard measures of cognition on the observed effects of age on FDM. On a relatively basic level of FDM (e.g., paying bills or using FDM styles) no significant effects of aging were found. However more complex FDM, such as making decisions in accordance with specific rules, becomes more difficult with advancing age. Furthermore, an older age was found to be related to a decreased sensitivity for impulsive buying. These results were confirmed by the internal and external validation analyses. Mediation effects of numeracy and planning were found to explain parts of the association between one aspect of FDM (i.e. Competence in decision rules) and age; however, these cognitive domains were not able to completely explain the relation between age and FDM. Normal aging has a negative influence on a complex aspect of FDM, however, other aspects appear to be unaffected by normal aging or improve.

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

DOEpatents

Hodgin, C Reed [Westminster, CO

2012-03-20

A system and method for inputting, analyzing, and disseminating information necessary for identified decision-makers to respond to emergency situations. This system and method provides consistency and integration among multiple groups, and may be used for both initial consequence-based decisions and follow-on consequence-based decisions. The system and method in a preferred embodiment also provides tools for accessing and manipulating information that are appropriate for each decision-maker, in order to achieve more reasoned and timely consequence-based decisions. The invention includes processes for designing and implementing a system or method for responding to emergency situations.

Cognitive Phenotypes and the Evolution of Animal Decisions.

PubMed

Mendelson, Tamra C; Fitzpatrick, Courtney L; Hauber, Mark E; Pence, Charles H; Rodríguez, Rafael L; Safran, Rebecca J; Stern, Caitlin A; Stevens, Jeffrey R

2016-11-01

Despite the clear fitness consequences of animal decisions, the science of animal decision making in evolutionary biology is underdeveloped compared with decision science in human psychology. Specifically, the field lacks a conceptual framework that defines and describes the relevant components of a decision, leading to imprecise language and concepts. The 'judgment and decision-making' (JDM) framework in human psychology is a powerful tool for framing and understanding human decisions, and we apply it here to components of animal decisions, which we refer to as 'cognitive phenotypes'. We distinguish multiple cognitive phenotypes in the context of a JDM framework and highlight empirical approaches to characterize them as evolvable traits. Copyright © 2016 Elsevier Ltd. All rights reserved.

A latent class multiple constraint multiple discrete-continuous extreme value model of time use and goods consumption.

DOT National Transportation Integrated Search

2016-06-01

This paper develops a microeconomic theory-based multiple discrete continuous choice model that considers: (a) that both goods consumption and time allocations (to work and non-work activities) enter separately as decision variables in the utility fu...

Parent perspectives on the decision to initiate medication treatment of attention-deficit/hyperactivity disorder.

PubMed

Coletti, Daniel J; Pappadopulos, Elizabeth; Katsiotas, Nikki J; Berest, Alison; Jensen, Peter S; Kafantaris, Vivian

2012-06-01

Despite substantial evidence supporting the efficacy of stimulant medication for children with attention-deficit/hyperactivity disorder (ADHD), adherence to stimulant treatment is often suboptimal. Applying social/cognitive theories to understanding and assessing parent attitudes toward initiating medication may provide insight into factors influencing parent decisions to follow ADHD treatment recommendations. This report describes results from formative research that used focus groups to obtain parent input to guide development of a provider-delivered intervention to improve adherence to stimulants. Participants were caregivers of children with ADHD who were given a stimulant treatment recommendation. Focus groups were recorded and transcribed verbatim. Data were analyzed by inductive, grounded theory methods as well as a deductive analytic strategy using an adapted version of the Unified Theory of Behavior Change to organize and understand parent accounts. Five groups were conducted with 27 parents (mean child age=9.35 years; standard deviation [SD]=2.00), mean time since diagnosis=3.33 years (SD=2.47). Most parents (81.5%) had pursued stimulant treatment. Inductive analysis revealed 17 attitudes facilitating adherence and 25 barriers. Facilitators included parent beliefs that medication treatment resulted in multiple functional gains and that treatment was imperative for their children's safety. Barriers included fears of personality changes and medication side effects. Complex patterns of parent adherence to medication regimens were also identified, as well as preferences for psychiatrists who were diagnostically expert, gave psychoeducation using multiple modalities, and used a chronic illness metaphor to explain ADHD. Theory-based analyses revealed conflicting expectancies about treatment risks and benefits, significant family pressures to avoid medication, guilt and concern that their children required medication, and distorted ideas about treatment risks. Parents, however, took pride in successfully pursuing efforts to manage their child behaviorally and to avoid medication when possible. Focus group data identified social, cognitive, and affective influences on treatment decision making. Results support prior research comparing family/social functioning, physician characteristics, and adherence. Findings suggest that parent attitudes to psychiatric care need to be assessed comprehensively at initial evaluation to aid the development of psychoeducational messages, and a more careful consideration about how parents interpret and respond to adherence-related questioning.

Two studies on participation in decision-making and equity among FAA personnel.

DOT National Transportation Integrated Search

1991-07-01

Study 1 Moderated multiple regression analyses on data collected from 2,177 FAA air traffic controller specialists indicated that equity perceptions moderated the relationship between participation in decision-making and level of job satisfaction. Sp...

Eating and drinking interventions for people at risk of lacking decision-making capacity: who decides and how?

PubMed

Clarke, Gemma; Galbraith, Sarah; Woodward, Jeremy; Holland, Anthony; Barclay, Stephen

2015-06-11

Some people with progressive neurological diseases find they need additional support with eating and drinking at mealtimes, and may require artificial nutrition and hydration. Decisions concerning artificial nutrition and hydration at the end of life are ethically complex, particularly if the individual lacks decision-making capacity. Decisions may concern issues of life and death: weighing the potential for increasing morbidity and prolonging suffering, with potentially shortening life. When individuals lack decision-making capacity, the standard processes of obtaining informed consent for medical interventions are disrupted. Increasingly multi-professional groups are being utilised to make difficult ethical decisions within healthcare. This paper reports upon a service evaluation which examined decision-making within a UK hospital Feeding Issues Multi-Professional Team. A three month observation of a hospital-based multi-professional team concerning feeding issues, and a one year examination of their records. The key research questions are: a) How are decisions made concerning artificial nutrition for individuals at risk of lacking decision-making capacity? b) What are the key decision-making factors that are balanced? c) Who is involved in the decision-making process? Decision-making was not a singular decision, but rather involved many different steps. Discussions involving relatives and other clinicians, often took place outside of meetings. Topics of discussion varied but the outcome relied upon balancing the information along four interdependent axes: (1) Risks, burdens and benefits; (2) Treatment goals; (3) Normative ethical values; (4) Interested parties. Decision-making was a dynamic ongoing process with many people involved. The multiple points of decision-making, and the number of people involved with the decision-making process, mean the question of 'who decides' cannot be fully answered. There is a potential for anonymity of multiple decision-makers to arise. Decisions in real world clinical practice may not fit precisely into a model of decision-making. The findings from this service evaluation illustrate that within multi-professional team decision-making; decisions may contain elements of both substituted and supported decision-making, and may be better represented as existing upon a continuum.

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

PubMed

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

2017-03-01

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

Exploring the Functioning of Decision Space: A Review of the Available Health Systems Literature.

PubMed

Roman, Tamlyn Eslie; Cleary, Susan; McIntyre, Diane

2017-02-27

The concept of decision space holds appeal as an approach to disaggregating the elements that may influence decision-making in decentralized systems. This narrative review aims to explore the functioning of decision space and the factors that influence decision space. A narrative review of the literature was conducted with searches of online databases and academic journals including PubMed Central, Emerald, Wiley, Science Direct, JSTOR, and Sage. The articles were included in the review based on the criteria that they provided insight into the functioning of decision space either through the explicit application of or reference to decision space, or implicitly through discussion of decision-making related to organizational capacity or accountability mechanisms. The articles included in the review encompass literature related to decentralisation, management and decision space. The majority of the studies utilise qualitative methodologies to assess accountability mechanisms, organisational capacities such as finance, human resources and management, and the extent of decision space. Of the 138 articles retrieved, 76 articles were included in the final review. The literature supports Bossert's conceptualization of decision space as being related to organizational capacities and accountability mechanisms. These functions influence the decision space available within decentralized systems. The exact relationship between decision space and financial and human resource capacities needs to be explored in greater detail to determine the potential influence on system functioning. © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The performance analysis of three-dimensional track-before-detect algorithm based on Fisher-Tippett-Gnedenko theorem

NASA Astrophysics Data System (ADS)

Cho, Hoonkyung; Chun, Joohwan; Song, Sungchan

2016-09-01

The dim moving target tracking from the infrared image sequence in the presence of high clutter and noise has been recently under intensive investigation. The track-before-detect (TBD) algorithm processing the image sequence over a number of frames before decisions on the target track and existence is known to be especially attractive in very low SNR environments (⩽ 3 dB). In this paper, we shortly present a three-dimensional (3-D) TBD with dynamic programming (TBD-DP) algorithm using multiple IR image sensors. Since traditional two-dimensional TBD algorithm cannot track and detect the along the viewing direction, we use 3-D TBD with multiple sensors and also strictly analyze the detection performance (false alarm and detection probabilities) based on Fisher-Tippett-Gnedenko theorem. The 3-D TBD-DP algorithm which does not require a separate image registration step uses the pixel intensity values jointly read off from multiple image frames to compute the merit function required in the DP process. Therefore, we also establish the relationship between the pixel coordinates of image frame and the reference coordinates.

Information processing in decision-making systems.

PubMed

van der Meer, Matthijs; Kurth-Nelson, Zeb; Redish, A David

2012-08-01

Decisions result from an interaction between multiple functional systems acting in parallel to process information in very different ways, each with strengths and weaknesses. In this review, the authors address three action-selection components of decision-making: The Pavlovian system releases an action from a limited repertoire of potential actions, such as approaching learned stimuli. Like the Pavlovian system, the habit system is computationally fast but, unlike the Pavlovian system permits arbitrary stimulus-action pairings. These associations are a "forward'' mechanism; when a situation is recognized, the action is released. In contrast, the deliberative system is flexible but takes time to process. The deliberative system uses knowledge of the causal structure of the world to search into the future, planning actions to maximize expected rewards. Deliberation depends on the ability to imagine future possibilities, including novel situations, and it allows decisions to be taken without having previously experienced the options. Various anatomical structures have been identified that carry out the information processing of each of these systems: hippocampus constitutes a map of the world that can be used for searching/imagining the future; dorsal striatal neurons represent situation-action associations; and ventral striatum maintains value representations for all three systems. Each system presents vulnerabilities to pathologies that can manifest as psychiatric disorders. Understanding these systems and their relation to neuroanatomy opens up a deeper way to treat the structural problems underlying various disorders.

Information Processing in Decision-Making Systems

PubMed Central

van der Meer, Matthijs; Kurth-Nelson, Zeb; Redish, A. David

2015-01-01

Decisions result from an interaction between multiple functional systems acting in parallel to process information in very different ways, each with strengths and weaknesses. In this review, the authors address three action-selection components of decision-making: The Pavlovian system releases an action from a limited repertoire of potential actions, such as approaching learned stimuli. Like the Pavlovian system, the habit system is computationally fast but, unlike the Pavlovian system permits arbitrary stimulus-action pairings. These associations are a “forward” mechanism; when a situation is recognized, the action is released. In contrast, the deliberative system is flexible but takes time to process. The deliberative system uses knowledge of the causal structure of the world to search into the future, planning actions to maximize expected rewards. Deliberation depends on the ability to imagine future possibilities, including novel situations, and it allows decisions to be taken without having previously experienced the options. Various anatomical structures have been identified that carry out the information processing of each of these systems: hippocampus constitutes a map of the world that can be used for searching/imagining the future; dorsal striatal neurons represent situation-action associations; and ventral striatum maintains value representations for all three systems. Each system presents vulnerabilities to pathologies that can manifest as psychiatric disorders. Understanding these systems and their relation to neuroanatomy opens up a deeper way to treat the structural problems underlying various disorders. PMID:22492194

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

NASA Technical Reports Server (NTRS)

Breininger, David; Duncan, Brean; Eaton, Mitchell; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process where science informs how management alternatives can influence resources and then decision makers can use this to make decisions. A more efficient process is to directly integrate science and decision making, where science allows us to learn to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuels monitoring with decision making focused on dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy, but habitat trajectories suggest tradeoffs. Knowledge about system responses to actions can be informed by applying competing management actions to different land units in the same system state and by ideas about fire behavior. Monitoring and management integration is important to optimize state-specific management decisions and increase knowledge about system responses. We believe this approach has broad utility for and cover modeling programs intended to inform decision making.

Capturing a Commander's decision making style

NASA Astrophysics Data System (ADS)

Santos, Eugene; Nguyen, Hien; Russell, Jacob; Kim, Keumjoo; Veenhuis, Luke; Boparai, Ramnjit; Stautland, Thomas Kristoffer

2017-05-01

A Commander's decision making style represents how he weighs his choices and evaluates possible solutions with regards to his goals. Specifically, in the naval warfare domain, it relates the way he processes a large amount of information in dynamic, uncertain environments, allocates resources, and chooses appropriate actions to pursue. In this paper, we describe an approach to capture a Commander's decision style by creating a cognitive model that captures his decisionmaking process and evaluate this model using a set of scenarios using an online naval warfare simulation game. In this model, we use the Commander's past behaviors and generalize Commander's actions across multiple problems and multiple decision making sequences in order to recommend actions to a Commander in a manner that he may have taken. Our approach builds upon the Double Transition Model to represent the Commander's focus and beliefs to estimate his cognitive state. Each cognitive state reflects a stage in a Commander's decision making process, each action reflects the tasks that he has taken to move himself closer to a final decision, and the reward reflects how close he is to achieving his goal. We then use inverse reinforcement learning to compute a reward for each of the Commander's actions. These rewards and cognitive states are used to compare between different styles of decision making. We construct a set of scenarios in the game where rational, intuitive and spontaneous decision making styles will be evaluated.

An Examination of Virginia Elementary School Principals' Scheduling Decisions Regarding Opportunities for Students to Participate in Physical Activity during the School Day

ERIC Educational Resources Information Center

Greve, Andrew W.

2017-01-01

The principal is ultimately responsible for decisions regarding the master schedule at the elementary level of education (Canady & Rettig, 2013; Young, 2008), and these scheduling decisions are influenced by multiple factors (Benamati, 2010; Harris, 2013; Howard & Rakoz, 2009). Although principals have become increasingly aware of the need…

Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

ERIC Educational Resources Information Center

Manouselis, Nikos; Sampson, Demetrios

This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…

A Multi-criteria Decision Analysis System for Prioritizing Sites and Types of Low Impact Development Practices

NASA Astrophysics Data System (ADS)

Song, Jae Yeol; Chung, Eun-Sung

2017-04-01

This study developed a multi-criteria decision analysis framework to prioritize sites and types of low impact development (LID) practices. This framework was systemized as a web-based system coupled with the Storm Water Management Model (SWMM) from the Environmental Protection Agency (EPA). Using the technique for order of preference by similarity to ideal solution (TOPSIS), which is a type of multi-criteria decision-making (MCDM) method, multiple types and sites of designated LID practices are prioritized. This system is named the Water Management Prioritization Module (WMPM) and is an improved version of the Water Management Analysis Module (WMAM) that automatically generates and simulates multiple scenarios of LID design and planning parameters for a single LID type. WMPM can simultaneously determine the priority of multiple LID types and sites. In this study, an infiltration trench and permeable pavement were considered for multiple sub-catchments in South Korea to demonstrate the WMPM procedures. The TOPSIS method was manually incorporated to select the vulnerable target sub-catchments and to prioritize the LID planning scenarios for multiple types and sites considering socio-economic, hydrologic and physical-geometric factors. In this application, the Delphi method and entropy theory were used to determine the subjective and objective weights, respectively. Comparing the ranks derived by this system, two sub-catchments, S16 and S4, out of 18 were considered to be the most suitable places for installing an infiltration trench and porous pavement to reduce the peak and total flow, respectively, considering both socio-economic factors and hydrological effectiveness. WMPM can help policy-makers to objectively develop urban water plans for sustainable development. Keywords: Low Impact Development, Multi-Criteria Decision Analysis, SWMM, TOPSIS, Water Management Prioritization Module (WMPM)

An integrative formal model of motivation and decision making: The MGPM*.

PubMed

Ballard, Timothy; Yeo, Gillian; Loft, Shayne; Vancouver, Jeffrey B; Neal, Andrew

2016-09-01

We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Structured decision making for managing pneumonia epizootics in bighorn sheep

USGS Publications Warehouse

Sells, Sarah N.; Mitchell, Michael S.; Edwards, Victoria L.; Gude, Justin A.; Anderson, Neil J.

2016-01-01

Good decision-making is essential to conserving wildlife populations. Although there may be multiple ways to address a problem, perfect solutions rarely exist. Managers are therefore tasked with identifying decisions that will best achieve desired outcomes. Structured decision making (SDM) is a method of decision analysis used to identify the most effective, efficient, and realistic decisions while accounting for values and priorities of the decision maker. The stepwise process includes identifying the management problem, defining objectives for solving the problem, developing alternative approaches to achieve the objectives, and formally evaluating which alternative is most likely to accomplish the objectives. The SDM process can be more effective than informal decision-making because it provides a transparent way to quantitatively evaluate decisions for addressing multiple management objectives while incorporating science, uncertainty, and risk tolerance. To illustrate the application of this process to a management need, we present an SDM-based decision tool developed to identify optimal decisions for proactively managing risk of pneumonia epizootics in bighorn sheep (Ovis canadensis) in Montana. Pneumonia epizootics are a major challenge for managers due to long-term impacts to herds, epistemic uncertainty in timing and location of future epizootics, and consequent difficulty knowing how or when to manage risk. The decision tool facilitates analysis of alternative decisions for how to manage herds based on predictions from a risk model, herd-specific objectives, and predicted costs and benefits of each alternative. Decision analyses for 2 example herds revealed that meeting management objectives necessitates specific approaches unique to each herd. The analyses showed how and under what circumstances the alternatives are optimal compared to other approaches and current management. Managers can be confident that these decisions are effective, efficient, and realistic because they explicitly account for important considerations managers implicitly weigh when making decisions, including competing management objectives, uncertainty in potential outcomes, and risk tolerance.

Testing the Multiple in the Multiple Read-Out Model of Visual Word Recognition

ERIC Educational Resources Information Center

De Moor, Wendy; Verguts, Tom; Brysbaert, Marc

2005-01-01

This study provided a test of the multiple criteria concept used for lexical decision, as implemented in J. Grainger and A. M. Jacobs's (1996) multiple read-out model. This account predicts more inhibition (or less facilitation) from a masked neighbor when accuracy is stressed more but more facilitation (or less inhibition) when the speed of…

15q11.2 CNV affects cognitive, structural and functional correlates of dyslexia and dyscalculia.

PubMed

Ulfarsson, M O; Walters, G B; Gustafsson, O; Steinberg, S; Silva, A; Doyle, O M; Brammer, M; Gudbjartsson, D F; Arnarsdottir, S; Jonsdottir, G A; Gisladottir, R S; Bjornsdottir, G; Helgason, H; Ellingsen, L M; Halldorsson, J G; Saemundsen, E; Stefansdottir, B; Jonsson, L; Eiriksdottir, V K; Eiriksdottir, G R; Johannesdottir, G H; Unnsteinsdottir, U; Jonsdottir, B; Magnusdottir, B B; Sulem, P; Thorsteinsdottir, U; Sigurdsson, E; Brandeis, D; Meyer-Lindenberg, A; Stefansson, H; Stefansson, K

2017-04-25

Several copy number variants have been associated with neuropsychiatric disorders and these variants have been shown to also influence cognitive abilities in carriers unaffected by psychiatric disorders. Previously, we associated the 15q11.2(BP1-BP2) deletion with specific learning disabilities and a larger corpus callosum. Here we investigate, in a much larger sample, the effect of the 15q11.2(BP1-BP2) deletion on cognitive, structural and functional correlates of dyslexia and dyscalculia. We report that the deletion confers greatest risk of the combined phenotype of dyslexia and dyscalculia. We also show that the deletion associates with a smaller left fusiform gyrus. Moreover, tailored functional magnetic resonance imaging experiments using phonological lexical decision and multiplication verification tasks demonstrate altered activation in the left fusiform and the left angular gyri in carriers. Thus, by using convergent evidence from neuropsychological testing, and structural and functional neuroimaging, we show that the 15q11.2(BP1-BP2) deletion affects cognitive, structural and functional correlates of both dyslexia and dyscalculia.

15q11.2 CNV affects cognitive, structural and functional correlates of dyslexia and dyscalculia

PubMed Central

Ulfarsson, M O; Walters, G B; Gustafsson, O; Steinberg, S; Silva, A; Doyle, O M; Brammer, M; Gudbjartsson, D F; Arnarsdottir, S; Jonsdottir, G A; Gisladottir, R S; Bjornsdottir, G; Helgason, H; Ellingsen, L M; Halldorsson, J G; Saemundsen, E; Stefansdottir, B; Jonsson, L; Eiriksdottir, V K; Eiriksdottir, G R; Johannesdottir, G H; Unnsteinsdottir, U; Jonsdottir, B; Magnusdottir, B B; Sulem, P; Thorsteinsdottir, U; Sigurdsson, E; Brandeis, D; Meyer-Lindenberg, A; Stefansson, H; Stefansson, K

2017-01-01

Several copy number variants have been associated with neuropsychiatric disorders and these variants have been shown to also influence cognitive abilities in carriers unaffected by psychiatric disorders. Previously, we associated the 15q11.2(BP1–BP2) deletion with specific learning disabilities and a larger corpus callosum. Here we investigate, in a much larger sample, the effect of the 15q11.2(BP1–BP2) deletion on cognitive, structural and functional correlates of dyslexia and dyscalculia. We report that the deletion confers greatest risk of the combined phenotype of dyslexia and dyscalculia. We also show that the deletion associates with a smaller left fusiform gyrus. Moreover, tailored functional magnetic resonance imaging experiments using phonological lexical decision and multiplication verification tasks demonstrate altered activation in the left fusiform and the left angular gyri in carriers. Thus, by using convergent evidence from neuropsychological testing, and structural and functional neuroimaging, we show that the 15q11.2(BP1–BP2) deletion affects cognitive, structural and functional correlates of both dyslexia and dyscalculia. PMID:28440815

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems.

PubMed

Whitacre, James M; Bender, Axel

2010-06-15

A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems.

The extraction of simple relationships in growth factor-specific multiple-input and multiple-output systems in cell-fate decisions by backward elimination PLS regression.

PubMed

Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya

2013-01-01

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

Age-related variance in decisions under ambiguity is explained by changes in reasoning, executive functions, and decision-making under risk.

PubMed

Schiebener, Johannes; Brand, Matthias

2017-06-01

Previous literature has explained older individuals' disadvantageous decision-making under ambiguity in the Iowa Gambling Task (IGT) by reduced emotional warning signals preceding decisions. We argue that age-related reductions in IGT performance may also be explained by reductions in certain cognitive abilities (reasoning, executive functions). In 210 participants (18-86 years), we found that the age-related variance on IGT performance occurred only in the last 60 trials. The effect was mediated by cognitive abilities and their relation with decision-making performance under risk with explicit rules (Game of Dice Task). Thus, reductions in cognitive functions in older age may be associated with both a reduced ability to gain explicit insight into the rules of the ambiguous decision situation and with failure to choose the less risky options consequently after the rules have been understood explicitly. Previous literature may have underestimated the relevance of cognitive functions for age-related decline in decision-making performance under ambiguity.

Altruistic decisions following penetrating traumatic brain injury.

PubMed

Moll, Jorge; de Oliveira-Souza, Ricardo; Basilio, Rodrigo; Bramati, Ivanei Edson; Gordon, Barry; Rodríguez-Nieto, Geraldine; Zahn, Roland; Krueger, Frank; Grafman, Jordan

2018-05-01

The cerebral correlates of altruistic decisions have increasingly attracted the interest of neuroscientists. To date, investigations on the neural underpinnings of altruistic decisions have primarily been conducted in healthy adults undergoing functional neuroimaging as they engaged in decisions to punish third parties. The chief purpose of the present study was to investigate altruistic decisions following focal brain damage with a novel altruistic decision task. In contrast to studies that have focused either on altruistic punishment or donation, the Altruistic Decision Task allows players to anonymously punish or donate to 30 charitable organizations involved with salient societal issues such as abortion, nuclear energy and civil rights. Ninety-four Vietnam War veterans with variable patterns of penetrating traumatic brain injury and 28 healthy veterans who also served in combat participated in the study as normal controls. Participants were asked to invest $1 to punish or reward real societal organizations, or keep the money for themselves. Associations between lesion distribution and performance on the task were analysed with multivariate support vector regression, which enables the assessment of the joint contribution of multiple regions in the determination of a given behaviour of interest. Our main findings were: (i) bilateral dorsomedial prefrontal lesions increased altruistic punishment, whereas lesions of the right perisylvian region and left temporo-insular cortex decreased punishment; (ii) altruistic donations were increased by bilateral lesions of the dorsomedial parietal cortex, whereas lesions of the right posterior superior temporal sulcus and middle temporal gyri decreased donations; (iii) altruistic punishment and donation were only weakly correlated, emphasizing their dissociable neuroanatomical associations; and (iv) altruistic decisions were not related to post-traumatic personality changes. These findings indicate that altruistic punishment and donation are determined by largely non-overlapping cerebral regions, which have previously been implicated in social cognition and moral experience such as evaluations of intentionality and intuitions of justice and morality.10.1093/brain/awy064_video1awy064media15758316955001.

Performing a secondary executive task with affective stimuli interferes with decision making under risk conditions.

PubMed

Gathmann, Bettina; Pawlikowski, Mirko; Schöler, Tobias; Brand, Matthias

2014-05-01

Previous studies demonstrated that executive functions are crucial for advantageous decision making under risk and that therefore decision making is disrupted when working memory capacity is demanded while working on a decision task. While some studies also showed that emotions can affect decision making under risk, it is unclear how affective processing and executive functions predict decision-making performance in interaction. The current experimental study used a between-subjects design to examine whether affective pictures (positive and negative pictures compared to neutral pictures), included in a parallel executive task (working memory 2-back task), have an impact on decision making under risk as assessed by the Game of Dice Task (GDT). Moreover, the performance GDT plus 2-back task was compared to the performance in the GDT without any additional task (GDT solely). The results show that the performance in the GDT differed between groups (positive, negative, neutral, and GDT solely). The groups with affective pictures, especially those with positive pictures in the 2-back task, showed more disadvantageous decisions in the GDT than the groups with neutral pictures and the group performing the GDT without any additional task. However, executive functions moderated the effect of the affective pictures. Regardless of affective influence, subjects with good executive functions performed advantageously in the GDT. These findings support the assumption that executive functions and emotional processing interact in predicting decision making under risk.

Identifying the performance characteristics of a winning outcome in elite mixed martial arts competition.

PubMed

James, Lachlan P; Robertson, Sam; Haff, G Gregory; Beckman, Emma M; Kelly, Vincent G

2017-03-01

To determine those performance indicators that have the greatest influence on classifying outcome at the elite level of mixed martial arts (MMA). A secondary objective was to establish the efficacy of decision tree analysis in explaining the characteristics of victory when compared to alternate statistical methods. Cross-sectional observational. Eleven raw performance indicators from male Ultimate Fighting Championship bouts (n=234) from July 2014 to December 2014 were screened for analysis. Each raw performance indicator was also converted to a rate-dependent measure to be scaled to fight duration. Further, three additional performance indicators were calculated from the dataset and included in the analysis. Cohen's d effect sizes were employed to determine the magnitude of the differences between Wins and Losses, while decision tree (chi-square automatic interaction detector (CHAID)) and discriminant function analyses (DFA) were used to classify outcome (Win and Loss). Effect size comparisons revealed differences between Wins and Losses across a number of performance indicators. Decision tree (raw: 71.8%; rate-scaled: 76.3%) and DFA (raw: 71.4%; rate-scaled 71.2%) achieved similar classification accuracies. Grappling and accuracy performance indicators were the most influential in explaining outcome. The decision tree models also revealed multiple combinations of performance indicators leading to victory. The decision tree analyses suggest that grappling activity and technique accuracy are of particular importance in achieving victory in elite-level MMA competition. The DFA results supported the importance of these performance indicators. Decision tree induction represents an intuitive and slightly more accurate approach to explaining bout outcome in this sport when compared to DFA. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

The development of a disease oriented eFolder for multiple sclerosis decision support

NASA Astrophysics Data System (ADS)

Ma, Kevin; Jacobs, Colin; Fernandez, James; Amezcua, Lilyana; Liu, Brent

2010-03-01

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. The chronic nature of MS necessitates multiple MRI studies to track disease progression. Currently, MRI assessment of multiple sclerosis requires manual lesion measurement and yields an estimate of lesion volume and change that is highly variable and user-dependent. In the setting of a longitudinal study, disease trends and changes become difficult to extrapolate from the lesions. In addition, it is difficult to establish a correlation between these imaged lesions and clinical factors such as treatment course. To address these clinical needs, an MS specific e-Folder for decision support in the evaluation and assessment of MS has been developed. An e-Folder is a disease-centric electronic medical record in contrast to a patient-centric electronic health record. Along with an MS lesion computer aided detection (CAD) package for lesion load, location, and volume, clinical parameters such as patient demographics, disease history, clinical course, and treatment history are incorporated to make the e-Folder comprehensive. With the integration of MRI studies together with related clinical data and informatics tools designed for monitoring multiple sclerosis, it provides a platform to improve the detection of treatment response in patients with MS. The design and deployment of MS e-Folder aims to standardize MS lesion data and disease progression to aid in decision making and MS-related research.

Geospatial optimization of siting large-scale solar projects

USGS Publications Warehouse

Macknick, Jordan; Quinby, Ted; Caulfield, Emmet; Gerritsen, Margot; Diffendorfer, James E.; Haines, Seth S.

2014-01-01

guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.

Reversible RNA adenosine methylation in biological regulation

PubMed Central

Jia, Guifang; Fu, Ye; He, Chuan

2012-01-01

N6-methyladenosine (m6A) is a ubiquitous modification in messenger RNA (mRNA) and other RNAs across most eukaryotes. For many years, however, the exact functions of m6A were not clearly understood. The discovery that the fat mass and obesity associated protein (FTO) is an m6A demethylase indicates that this modification is reversible and dynamically regulated, suggesting it has regulatory roles. In addition, it has been shown that m6A affects cell fate decisions in yeast and plant development. Recent affinity-based m6A profiling in mouse and human cells further showed that this modification is a widespread mark in coding and non-coding RNA transcripts and is likely dynamically regulated throughout developmental processes. Therefore, reversible RNA methylation, analogous to reversible DNA and histone modifications, may affect gene expression and cell fate decisions by modulating multiple RNA-related cellular pathways, which potentially provides rapid responses to various cellular and environmental signals, including energy and nutrient availability in mammals. PMID:23218460

Perceptual Decision-Making as Probabilistic Inference by Neural Sampling.

PubMed

Haefner, Ralf M; Berkes, Pietro; Fiser, József

2016-05-04

We address two main challenges facing systems neuroscience today: understanding the nature and function of cortical feedback between sensory areas and of correlated variability. Starting from the old idea of perception as probabilistic inference, we show how to use knowledge of the psychophysical task to make testable predictions for the influence of feedback signals on early sensory representations. Applying our framework to a two-alternative forced choice task paradigm, we can explain multiple empirical findings that have been hard to account for by the traditional feedforward model of sensory processing, including the task dependence of neural response correlations and the diverging time courses of choice probabilities and psychophysical kernels. Our model makes new predictions and characterizes a component of correlated variability that represents task-related information rather than performance-degrading noise. It demonstrates a normative way to integrate sensory and cognitive components into physiologically testable models of perceptual decision-making. Copyright © 2016 Elsevier Inc. All rights reserved.

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

PubMed Central

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for “temporal receptive windows” that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision-making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or EEG/MEG) by taking into account inter-areal heterogeneity. PMID:26439530

Uncovering multiple pathways to substance use: a comparison of methods for identifying population subgroups.

PubMed

Dierker, Lisa; Rose, Jennifer; Tan, Xianming; Li, Runze

2010-12-01

This paper describes and compares a selection of available modeling techniques for identifying homogeneous population subgroups in the interest of informing targeted substance use intervention. We present a nontechnical review of the common and unique features of three methods: (a) trajectory analysis, (b) functional hierarchical linear modeling (FHLM), and (c) decision tree methods. Differences among the techniques are described, including required data features, strengths and limitations in terms of the flexibility with which outcomes and predictors can be modeled, and the potential of each technique for helping to inform the selection of targets and timing of substance intervention programs.

Ethical, financial, and policy considerations in hand transplantation.

PubMed

Chang, Jeff; Mathes, David W

2011-11-01

Currently, more than 65 hand transplants have been performed with studies demonstrating favorable cosmetic and functional outcomes and cortical reintegration of the transplanted hand. Due to such favorable outcomes, many view hand transplant as a potential gold standard for treatment of a double amputee. However, ethical debate continues regarding risks and benefits of this nonlifesaving procedure. Clinicians, patients, and society must agree on whether hand transplantation is ethical and affordable. If a decision is made to transplant a hand, this must be performed in a dedicated center that facilitates integration of multiple specialists, ethicists, pharmacists, and rehabilitationists. Copyright © 2011 Elsevier Inc. All rights reserved.

An approximate dynamic programming approach to resource management in multi-cloud scenarios

NASA Astrophysics Data System (ADS)

Pietrabissa, Antonio; Priscoli, Francesco Delli; Di Giorgio, Alessandro; Giuseppi, Alessandro; Panfili, Martina; Suraci, Vincenzo

2017-03-01

The programmability and the virtualisation of network resources are crucial to deploy scalable Information and Communications Technology (ICT) services. The increasing demand of cloud services, mainly devoted to the storage and computing, requires a new functional element, the Cloud Management Broker (CMB), aimed at managing multiple cloud resources to meet the customers' requirements and, simultaneously, to optimise their usage. This paper proposes a multi-cloud resource allocation algorithm that manages the resource requests with the aim of maximising the CMB revenue over time. The algorithm is based on Markov decision process modelling and relies on reinforcement learning techniques to find online an approximate solution.

Refining Inquiry with Multi-Form Assessment: Formative and summative assessment functions for flexible inquiry

NASA Astrophysics Data System (ADS)

Zuiker, Steven; Reid Whitaker, J.

2014-04-01

This paper describes the 5E+I/A inquiry model and reports a case study of one curricular enactment by a US fifth-grade classroom. A literature review establishes the model's conceptual adequacy with respect to longstanding research related to both the 5E inquiry model and multiple, incremental innovations of it. As a collective line of research, the review highlights a common emphasis on formative assessment, at times coupled either with differentiated instruction strategies or with activities that target the generalization of learning. The 5E+I/A model contributes a multi-level assessment strategy that balances formative and summative functions of multiple forms of assessment in order to support classroom participation while still attending to individual achievement. The case report documents the enactment of a weeklong 5E+I/A curricular design as a preliminary account of the model's empirical adequacy. A descriptive and analytical narrative illustrates variable ways that multi-level assessment makes student thinking visible and pedagogical decision-making more powerful. In light of both, it also documents productive adaptations to a flexible curricular design and considers future research to advance this collective line of inquiry.

Cutting Edge: Differential Regulation of PTEN by TCR, Akt, and FoxO1 Controls CD4+ T Cell Fate Decisions.

PubMed

Hawse, William F; Sheehan, Robert P; Miskov-Zivanov, Natasa; Menk, Ashley V; Kane, Lawrence P; Faeder, James R; Morel, Penelope A

2015-05-15

Signaling via the Akt/mammalian target of rapamycin pathway influences CD4(+) T cell differentiation; low levels favor regulatory T cell induction and high levels favor Th induction. Although the lipid phosphatase phosphatase and tensin homolog (PTEN) suppresses Akt activity, the control of PTEN activity is poorly studied in T cells. In this study, we identify multiple mechanisms that regulate PTEN expression. During Th induction, PTEN function is suppressed via lower mRNA levels, lower protein levels, and an increase in C-terminal phosphorylation. Conversely, during regulatory T cell induction, PTEN function is maintained through the stabilization of PTEN mRNA transcription and sustained protein levels. We demonstrate that differential Akt/mammalian target of rapamycin signaling regulates PTEN transcription via the FoxO1 transcription factor. A mathematical model that includes multiple modes of PTEN regulation recapitulates our experimental findings and demonstrates how several feedback loops determine differentiation outcomes. Collectively, this work provides novel mechanistic insights into how differential regulation of PTEN controls alternate CD4(+) T cell fate outcomes. Copyright © 2015 by The American Association of Immunologists, Inc.

Therapeutic Decisions In Multiple Sclerosis: Moving Beyond Efficacy

PubMed Central

Brück, Wolfgang; Ralf, Gold; Lund, Brett T.; Celia, Oreja-Guevara; Prat, Alexandre; Spencer, Collin M.; Steinman, Lawrence; Mar, Tintoré; Vollmer, Timothy; Weber, Martin S.; Weiner, Leslie P.; Ziemssen, Tjalf; Zamvil, Scott S.

2014-01-01

Importance Several innovative disease-modifying treatments (DMTs) for relapsing remitting multiple sclerosis (RRMS) have been licensed recently, or are in late-stage development. The molecular targets of several of these DMTs are well defined. All affect at least one of four properties: (1) immune cell trafficking, (2) cell depletion, (3) immune cell function, or (4) cell replication. In contrast to β-interferons and glatiramer acetate, the first generation DMTs, several newer therapies are imbued with safety issues. In addition to efficacy, understanding the relationship between the mechanism of action (MOA) of the DMTs and their safety profile is essential for decision-making in patient care. Objective In this article, we relate safety issues of newer DMTs to their pharmacological characteristics, including molecular targets, MOA, chemical structure, and metabolism. Some newer DMTs also represent repurposing or modifications of previous treatments used in other diseases. Here, we describe how identification and understanding of adverse events (AEs) observed with these established drugs within the same class, provide clues regarding safety and toxicities of newer MS therapeutics. Conclusions and relevance While understanding mechanisms underlying DMT toxicities is incomplete, it is important to further develop this knowledge to minimize risk to patients, and to ensure future therapies have the most advantageous risk-benefit profiles. Recognizing the individual classes of DMTs described here may be beneficial when considering use of such agents sequentially and possibly in combination. PMID:23921521

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

Reasoning in explanation-based decision making.

PubMed

Pennington, N; Hastie, R

1993-01-01

A general theory of explanation-based decision making is outlined and the multiple roles of inference processes in the theory are indicated. A typology of formal and informal inference forms, originally proposed by Collins (1978a, 1978b), is introduced as an appropriate framework to represent inferences that occur in the overarching explanation-based process. Results from the analysis of verbal reports of decision processes are presented to demonstrate the centrality and systematic character of reasoning in a representative legal decision-making task.

Decision-making deficits in pathological gambling: the role of executive functions, explicit knowledge and impulsivity in relation to decisions made under ambiguity and risk.

PubMed

Ochoa, Cristian; Alvarez-Moya, Eva M; Penelo, Eva; Aymami, M Neus; Gómez-Peña, Mónica; Fernández-Aranda, Fernando; Granero, Roser; Vallejo-Ruiloba, Julio; Menchón, José Manuel; Lawrence, Natalia S; Jiménez-Murcia, Susana

2013-01-01

A variety of cognitive and emotional processes influence the decision-making deficits observed in pathological gambling (PG). This study investigated the role of immediate/delayed sensitivity to reward and punishment, executive functions, impulsivity and explicit knowledge in relation to decision-making performance on the original Iowa Gambling Task (IGT-ABCD) and a variant (IGT-EFGH). We assessed 131 consecutive patients with a diagnosis of PG by using executive functioning and decision-making tasks, self-report measures of impulsivity and explicit knowledge. The majority of pathological gamblers (PGs) showed deficits in decision-making, characterized mainly by myopia for the future. Decisions made under risk showed different predictors. Performance on the IGT-ABCD for decisions made under risk was predicted by medium and high levels of explicit knowledge of the task, as well as by scores on the Disorderliness subscale and the degree of Stroop interference. By contrast, IGT-EFGH results were only associated with self-report impulsivity measures. Decision making in PG involves distinct patterns of deficits, and the predictors differ depending on the reinforcement schedule. Decisions made under risk on the IGT-ABCD are associated with explicit knowledge, executive functions and impulsivity traits related to conscious awareness and control processes. On the IGT-EFGH, however, only impulsivity traits predict decision making. Copyright © American Academy of Addiction Psychiatry.

Multimorbidity, service organization and clinical decision making in primary care: a qualitative study.

PubMed

Bower, Peter; Macdonald, Wendy; Harkness, Elaine; Gask, Linda; Kendrick, Tony; Valderas, Jose M; Dickens, Chris; Blakeman, Tom; Sibbald, Bonnie

2011-10-01

Primary care professionals often manage patients with multiple long-term health conditions, but managing multimorbidity is challenging given time and resource constraints and interactions between conditions. To explore GP and nurse perceptions of multimorbidity and the influence on service organization and clinical decision making. A qualitative interview study with primary care professionals in practices in Greater Manchester, U.K. Interviews were conducted with 15 GPs and 10 practice nurses. Primary care professionals identified tensions between delivering care to meet quality targets and fulfilling the patient's agenda, tensions which are exacerbated in multimorbidity. They were aware of the inconvenience suffered by patients through attendance at multiple clinic appointments when care was structured around individual conditions. They reported difficulties managing patients with multimorbidity in limited consultation time, which led to adoption of an 'additive-sequential' decision-making model which dealt with problems in priority order until consultation resources were exhausted, when further management was deferred. Other challenges included the need for patients to co-ordinate their care, the difficulties of self-management support in multimorbidity and problems of making sense of the relationships between physical and mental health. Doctor and nurse accounts included limited consideration of multimorbidity in terms of the interactions between conditions or synergies between management of different conditions. Primary care professionals identify a number of challenges in care for multimorbidity and adopt a particular model of decision making to deliver care for multiple individual conditions. However, they did not describe specific decision making around managing multimorbidity per se.

Measurement of Function Post Hip Fracture: Testing a Comprehensive Measurement Model of Physical Function

PubMed Central

Gruber-Baldini, Ann L.; Hicks, Gregory; Ostir, Glen; Klinedinst, N. Jennifer; Orwig, Denise; Magaziner, Jay

2015-01-01

Background Measurement of physical function post hip fracture has been conceptualized using multiple different measures. Purpose This study tested a comprehensive measurement model of physical function. Design This was a descriptive secondary data analysis including 168 men and 171 women post hip fracture. Methods Using structural equation modeling, a measurement model of physical function which included grip strength, activities of daily living, instrumental activities of daily living and performance was tested for fit at 2 and 12 months post hip fracture and among male and female participants and validity of the measurement model of physical function was evaluated based on how well the model explained physical activity, exercise and social activities post hip fracture. Findings The measurement model of physical function fit the data. The amount of variance the model or individual factors of the model explained varied depending on the activity. Conclusion Decisions about the ideal way in which to measure physical function should be based on outcomes considered and participant Clinical Implications The measurement model of physical function is a reliable and valid method to comprehensively measure physical function across the hip fracture recovery trajectory. Practical but useful assessment of function should be considered and monitored over the recovery trajectory post hip fracture. PMID:26492866

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…

Using structured decision making with landowners to address private forest management and parcelization: balancing multiple objectives and incorporating uncertainty

Treesearch

Paige F. B. Ferguson; Michael J. Conroy; John F. Chamblee; Jeffrey Hepinstall-Cymerman

2015-01-01

Parcelization and forest fragmentation are of concern for ecological, economic, and social reasons. Efforts to keep large, private forests intact may be supported by a decision-making process that incorporates landowners’ objectives and uncertainty. We used structured decision making (SDM) with owners of large, private forests in Macon County, North Carolina....

Developing inventory and monitoring programs based on multiple objectives

NASA Astrophysics Data System (ADS)

Schmoldt, Daniel L.; Peterson, David L.; Silsbee, David G.

1994-09-01

Resource inventory and monitoring (I&M) programs in national parks combine multiple objectives in order to create a plan of action over a finite time horizon. Because all program activities are constrained by time and money, it is critical to plan I&M activities that make the best use of available agency resources. However, multiple objectives complicate a relatively straightforward allocation process. The analytic hierarchy process (AHP) offers a structure for multiobjective decision making so that decision-makers’ preferences can be formally incorporated in seeking potential solutions. Within the AHP, inventory and monitoring program objectives and decision criteria are organized into a hierarchy. Pairwise comparisons among decision elements at any level of the hierarchy provide a ratio scale ranking of those elements. The resulting priority values for all projects are used as each project’s contribution to the value of an overall I&M program. These priorities, along with budget and personnel constraints, are formulated as a zero/one integer programming problem that can be solved to select those projects that produce the best program. An extensive example illustrates how this approach is being applied to I&M projects in national parks in the Pacific Northwest region of the United States. The proposed planning process provides an analytical framework for multicriteria decisionmaking that is rational, consistent, explicit, and defensible.

Decision Making Configurations: An Alternative to the Centralization/Decentralization Conceptualization.

ERIC Educational Resources Information Center

Cullen, John B.; Perrewe, Pamela L.

1981-01-01

Used factors identified in the literature as predictors of centralization/decentralization as potential discriminating variables among several decision making configurations in university affiliated professional schools. The model developed from multiple discriminant analysis had reasonable success in classifying correctly only the decentralized…

A green chemistry-based classification model for the synthesis of silver nanoparticles

EPA Science Inventory

The assessment of implementation of green chemistry principles in the synthesis of nanomaterials is a complex decision-making problem that necessitates integration of several evaluation criteria. Multiple Criteria Decision Aiding (MCDA) provides support for such a challenge. One ...

Living with Multiple Health Problems: What Older Adults Should Know

MedlinePlus

... treatments may take longer than others to show benefits. You should also decide if you want to make all of your care decisions on your own or include others in the decision-making process. These can include spouses, family members, or ...

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.

Semantic Ambiguity: Do Multiple Meanings Inhibit or Facilitate Word Recognition?

ERIC Educational Resources Information Center

Haro, Juan; Ferré, Pilar

2018-01-01

It is not clear whether multiple unrelated meanings inhibit or facilitate word recognition. Some studies have found a disadvantage for words having multiple meanings with respect to unambiguous words in lexical decision tasks (LDT), whereas several others have shown a facilitation for such words. In the present study, we argue that these…

Healthcare decision-making in end stage renal disease-patient preferences and clinical correlates.

PubMed

Jayanti, Anuradha; Neuvonen, Markus; Wearden, Alison; Morris, Julie; Foden, Philip; Brenchley, Paul; Mitra, Sandip

2015-11-14

Medical decision-making is critical to patient survival and well-being. Patients with end stage renal disease (ESRD) are faced with incrementally complex decision-making throughout their treatment journey. The extent to which patients seek involvement in the decision-making process and factors which influence these in ESRD need to be understood. 535 ESRD patients were enrolled into the cross-sectional study arm and 30 patients who started dialysis were prospectively evaluated. Patients were enrolled into 3 groups- 'predialysis' (group A), 'in-centre' haemodialysis (HD) (group B) and self-care HD (93 % at home-group C) from across five tertiary UK renal centres. The Autonomy Preference Index (API) has been employed to study patient preferences for information-seeking (IS) and decision-making (DM). Demographic, psychosocial and neuropsychometric assessments are considered for analyses. 458 complete responses were available. API items have high internal consistency in the study population (Cronbach's alpha > 0.70). Overall and across individual study groups, the scores for information-seeking and decision-making are significantly different indicating that although patients had a strong preference to be well informed, they were more neutral in their preference to participate in DM (p < 0.05). In the age, education and study group adjusted multiple linear regression analysis, lower age, female gender, marital status; higher API IS scores and white ethnicity background were significant predictors of preference for decision-making. DM scores were subdivided into tertiles to identify variables associated with high (DM > 70: and low DM (≤30) scores. This shows association of higher DM scores with lower age, lower comorbidity index score, higher executive brain function, belonging in the self-caring cohort and being unemployed. In the prospectively studied cohort of predialysis patients, there was no change in decision-making preference scores after commencement of dialysis. ESRD patients prefer to receive information, but this does not always imply active involvement in decision-making. By understanding modifiable and non-modifiable factors which affect patient preferences for involvement in healthcare decision-making, health professionals may acknowledge the need to accommodate individual patient preferences to the extent determined by the individual patient factors.

A Qualitative Study of Breast Reconstruction Decision-Making among Asian Immigrant Women Living in the United States.

PubMed

Fu, Rose; Chang, Michelle Milee; Chen, Margaret; Rohde, Christine Hsu

2017-02-01

Despite research supporting improved psychosocial well-being, quality of life, and survival for patients undergoing postmastectomy breast reconstruction, Asian patients remain one-fifth as likely as Caucasians to choose reconstruction. This study investigates cultural factors, values, and perceptions held by Asian women that might impact breast reconstruction rates. The authors conducted semistructured interviews of immigrant East Asian women treated for breast cancer in the New York metropolitan area, investigating social structure, culture, attitudes toward surgery, and body image. Three investigators independently coded transcribed interviews, and then collectively evaluated them through axial coding of recurring themes. Thirty-five immigrant East Asian women who underwent surgical treatment for breast cancer were interviewed. Emerging themes include functionality, age, perceptions of plastic surgery, inconvenience, community/family, fear of implants, language, and information. Patients spoke about breasts as a function of their roles as a wife or mother, eliminating the need for breasts when these roles were fulfilled. Many addressed the fear of multiple operations. Quality and quantity of information, and communication with practitioners, impacted perceptions about treatment. Reconstructive surgery was often viewed as cosmetic. Community and family played a significant role in decision-making. Asian women are statistically less likely than Caucasians to pursue breast reconstruction. This is the first study to investigate culture-specific perceptions of breast reconstruction. Results from this study can be used to improve cultural competency in addressing patient concerns. Improving access to information regarding treatment options and surgical outcomes may improve informed decision-making among immigrant Asian women.

The functional neuroanatomy of decision-making.

PubMed

Rosenbloom, Michael H; Schmahmann, Jeremy D; Price, Bruce H

2012-01-01

Decision-making is a complex executive function that draws on past experience, present goals, and anticipation of outcome, and which is influenced by prevailing and predicted emotional tone and cultural context. Functional imaging investigations and focal lesion studies identify the orbitofrontal, anterior cingulate, and dorsolateral prefrontal cortices as critical to decision-making. The authors review the connections of these prefrontal regions with the neocortex, limbic system, basal ganglia, and cerebellum, highlight current ideas regarding the cognitive processes of decision-making that these networks subserve, and present a novel integrated neuroanatomical model for decision-making. Finally, clinical relevance of this circuitry is illustrated through a discussion of frontotemporal dementia, traumatic brain injury, and sociopathy.

Reward circuit connectivity relates to delay discounting in children with attention-deficit/hyperactivity disorder

PubMed Central

Costa Dias, Taciana G.; Wilson, Vanessa B.; Bathula, Deepti R.; Iyer, Swathi P.; Mills, Kathryn L.; Thurlow, Bria L.; Stevens, Corinne A.; Musser, Erica D.; Carpenter, Samuel D.; Grayson, David S.; Mitchell, Suzanne H.; Nigg, Joel T.; Fair, Damien A.

2012-01-01

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent psychiatric disorder that has poor long-term outcomes and remains a major public health concern. Recent theories have proposed that ADHD arises from alterations in multiple neural pathways. Alterations in reward circuits are hypothesized as one core dysfunction, leading to altered processing of anticipated rewards. The nucleus accumbens (NAcc) is particularly important for reward processes; task-based fMRI studies have found atypical activation of this region while the participants performed a reward task. Understanding how reward circuits are involved with ADHD may be further enhanced by considering how the NAcc interacts with other brain regions. Here we used the technique of resting-state functional connectivity MRI (rs-fcMRI) to examine the alterations in the NAcc interactions and how they relate to impulsive decision making in ADHD. Using rs-fcMRI, this study: examined differences in functional connectivity of the NAcc between children with ADHD and control children; correlated the functional connectivity of NAcc with impulsivity, as measured by a delay discounting task; and combined these two initial segments to identify the atypical NAcc connections that were associated with impulsive decision making in ADHD. We found that functional connectivity of NAcc was atypical in children with ADHD and the ADHD-related increased connectivity between NAcc and the prefrontal cortex was associated with greater impulsivity (steeper delayed-reward discounting). These findings are consistent with the hypothesis that atypical signaling of the NAcc to the prefrontal cortex in ADHD may lead to excessive approach and failure in estimating future consequences; thus, leading to impulsive behavior. PMID:23206930

Altered intrinsic hippocmapus declarative memory network and its association with impulsivity in abstinent heroin dependent subjects.

PubMed

Zhai, Tian-Ye; Shao, Yong-Cong; Xie, Chun-Ming; Ye, En-Mao; Zou, Feng; Fu, Li-Ping; Li, Wen-Jun; Chen, Gang; Chen, Guang-Yu; Zhang, Zheng-Guo; Li, Shi-Jiang; Yang, Zheng

2014-10-01

Converging evidence suggests that addiction can be considered a disease of aberrant learning and memory with impulsive decision-making. In the past decades, numerous studies have demonstrated that drug addiction is involved in multiple memory systems such as classical conditioned drug memory, instrumental learning memory and the habitual learning memory. However, most of these studies have focused on the contributions of non-declarative memory, and declarative memory has largely been neglected in the research of addiction. Based on a recent finding that hippocampus, as a core functioning region of declarative memory, was proved biased the decision-making process based on past experiences by spreading associated reward values throughout memory. Our present study focused on the hippocampus. By utilizing seed-based network analysis on the resting-state functional MRI datasets with the seed hippocampus we tested how the intrinsic hippocampal memory network altered toward drug addiction, and examined how the functional connectivity strength within the altered hippocampal network correlated with behavioral index 'impulsivity'. Our results demonstrated that HD group showed enhanced coherence between hippocampus which represents declarative memory system and non-declarative reward-guided learning memory system, and also showed attenuated intrinsic functional link between hippocampus and top-down control system, compared to the CN group. This alteration was furthered found to have behavioral significance over the behavioral index 'impulsivity' measured with Barratt Impulsiveness Scale (BIS). These results provide insights into the mechanism of declarative memory underlying the impulsive behavior in drug addiction. Copyright © 2014 Elsevier B.V. All rights reserved.

Identifying Opportunities for Decision Support Systems in Support of Regional Resource Use Planning: An Approach Through Soft Systems Methodology.

PubMed

Zhu; Dale

2000-10-01

/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.

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.

Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks

PubMed Central

Fogelmark, Karl; Peterson, Carsten; Troein, Carl

2016-01-01

Background Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. Methodology To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. Principal Findings We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks. PMID:26927540

Surveying multidisciplinary aspects in real-time distributed coding for Wireless Sensor Networks.

PubMed

Braccini, Carlo; Davoli, Franco; Marchese, Mario; Mongelli, Maurizio

2015-01-27

Wireless Sensor Networks (WSNs), where a multiplicity of sensors observe a physical phenomenon and transmit their measurements to one or more sinks, pertain to the class of multi-terminal source and channel coding problems of Information Theory. In this category, "real-time" coding is often encountered for WSNs, referring to the problem of finding the minimum distortion (according to a given measure), under transmission power constraints, attainable by encoding and decoding functions, with stringent limits on delay and complexity. On the other hand, the Decision Theory approach seeks to determine the optimal coding/decoding strategies or some of their structural properties. Since encoder(s) and decoder(s) possess different information, though sharing a common goal, the setting here is that of Team Decision Theory. A more pragmatic vision rooted in Signal Processing consists of fixing the form of the coding strategies (e.g., to linear functions) and, consequently, finding the corresponding optimal decoding strategies and the achievable distortion, generally by applying parametric optimization techniques. All approaches have a long history of past investigations and recent results. The goal of the present paper is to provide the taxonomy of the various formulations, a survey of the vast related literature, examples from the authors' own research, and some highlights on the inter-play of the different theories.

What is a good medical decision? A research agenda guided by perspectives from multiple stakeholders.

PubMed

Hamilton, Jada G; Lillie, Sarah E; Alden, Dana L; Scherer, Laura; Oser, Megan; Rini, Christine; Tanaka, Miho; Baleix, John; Brewster, Mikki; Craddock Lee, Simon; Goldstein, Mary K; Jacobson, Robert M; Myers, Ronald E; Zikmund-Fisher, Brian J; Waters, Erika A

2017-02-01

Informed and shared decision making are critical aspects of patient-centered care, which has contributed to an emphasis on decision support interventions to promote good medical decision making. However, researchers and healthcare providers have not reached a consensus on what defines a good decision, nor how to evaluate it. This position paper, informed by conference sessions featuring diverse stakeholders held at the 2015 Society of Behavioral Medicine and Society for Medical Decision Making annual meetings, describes key concepts that influence the decision making process itself and that may change what it means to make a good decision: interpersonal factors, structural constraints, affective influences, and values clarification methods. This paper also proposes specific research questions within each of these priority areas, with the goal of moving medical decision making research to a more comprehensive definition of a good medical decision, and enhancing the ability to measure and improve the decision making process.

Energy cane as a multiple-products alternative

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

Alexander, A.G.

1984-01-01

CANE SUGAR planting as it was formerly known is in serious and essentially irreversible trouble. Diversification of sugarcane to alternative farm crops is indicated in some instances. Yet, for the most part, the more logical alternative is an internal diversification to a multiple-products biomass commodity. Sometimes termed the energy cane approach, its keystones are the management of sugarcane as a quantitative rather than qualitative entity, and the inclusion of certain tropical-grass relatives to assist cane in its year-round supply of biomass to industrial consumers. Managed in this way, absolute tonnages of whole cane are increased materially beyond what is possiblemore » from sugar-crop management. Juice quality declines but sugar yields are significant as a function of high biomass tonnages per acre. Usage of the lignocellulose can range from low-quality humid boiler fuel in furnaces designed for refuse incineration, to higher-quality fuels in more efficient boilers, to proprietary fuels and chemical products, and to lignocellulose supply as the feedstock for primary chemicals production. The latter might include, for example, synthesis gas and petrochemicals in tropical regions lacking natural gas, naphtha, or coal as starting materials. Diversification of sugarcane to completely new farm commodities is opposed in favor of internal diversification to a high-growth, multiple-products commodity. Decisive issues here are as much educational as they are technical. The energy cane concept maintains that sugarcane is a future resource of enormous national and international value. It should develop accordingly where decision-taking is by persons who respect the cane plant and who have done their homework on its alternative-use potentials. 35 references, 5 figures, 6 tables.« less

Signal processing and neural network toolbox and its application to failure diagnosis and prognosis

NASA Astrophysics Data System (ADS)

Tu, Fang; Wen, Fang; Willett, Peter K.; Pattipati, Krishna R.; Jordan, Eric H.

2001-07-01

Many systems are comprised of components equipped with self-testing capability; however, if the system is complex involving feedback and the self-testing itself may occasionally be faulty, tracing faults to a single or multiple causes is difficult. Moreover, many sensors are incapable of reliable decision-making on their own. In such cases, a signal processing front-end that can match inference needs will be very helpful. The work is concerned with providing an object-oriented simulation environment for signal processing and neural network-based fault diagnosis and prognosis. In the toolbox, we implemented a wide range of spectral and statistical manipulation methods such as filters, harmonic analyzers, transient detectors, and multi-resolution decomposition to extract features for failure events from data collected by data sensors. Then we evaluated multiple learning paradigms for general classification, diagnosis and prognosis. The network models evaluated include Restricted Coulomb Energy (RCE) Neural Network, Learning Vector Quantization (LVQ), Decision Trees (C4.5), Fuzzy Adaptive Resonance Theory (FuzzyArtmap), Linear Discriminant Rule (LDR), Quadratic Discriminant Rule (QDR), Radial Basis Functions (RBF), Multiple Layer Perceptrons (MLP) and Single Layer Perceptrons (SLP). Validation techniques, such as N-fold cross-validation and bootstrap techniques, are employed for evaluating the robustness of network models. The trained networks are evaluated for their performance using test data on the basis of percent error rates obtained via cross-validation, time efficiency, generalization ability to unseen faults. Finally, the usage of neural networks for the prediction of residual life of turbine blades with thermal barrier coatings is described and the results are shown. The neural network toolbox has also been applied to fault diagnosis in mixed-signal circuits.

Integrating land cover modeling and adaptive management to conserve endangered species and reduce catastrophic fire risk

USGS Publications Warehouse

Breininger, David; Duncan, Brean; Eaton, Mitchell J.; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process, where science informs how management alternatives can influence resources, and then, decision makers can use this information to make decisions. A more efficient process is to directly integrate science and decision-making, where science allows us to learn in order to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by the specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuel monitoring with decision-making focused on the dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy; other conditions require tradeoffs between objectives. Knowledge about system responses to actions can be informed by developing hypotheses based on ideas about fire behavior and then applying competing management actions to different land units in the same system state. Monitoring and management integration is important to optimize state-specific management decisions and to increase knowledge about system responses. We believe this approach has broad utility and identifies a clear role for land cover modeling programs intended to inform decision-making.

ToxPi GUI: an interactive visualization tool for transparent integration of data from diverse sources of evidence.

PubMed

Reif, David M; Sypa, Myroslav; Lock, Eric F; Wright, Fred A; Wilson, Ander; Cathey, Tommy; Judson, Richard R; Rusyn, Ivan

2013-02-01

Scientists and regulators are often faced with complex decisions, where use of scarce resources must be prioritized using collections of diverse information. The Toxicological Prioritization Index (ToxPi™) was developed to enable integration of multiple sources of evidence on exposure and/or safety, transformed into transparent visual rankings to facilitate decision making. The rankings and associated graphical profiles can be used to prioritize resources in various decision contexts, such as testing chemical toxicity or assessing similarity of predicted compound bioactivity profiles. The amount and types of information available to decision makers are increasing exponentially, while the complex decisions must rely on specialized domain knowledge across multiple criteria of varying importance. Thus, the ToxPi bridges a gap, combining rigorous aggregation of evidence with ease of communication to stakeholders. An interactive ToxPi graphical user interface (GUI) application has been implemented to allow straightforward decision support across a variety of decision-making contexts in environmental health. The GUI allows users to easily import and recombine data, then analyze, visualize, highlight, export and communicate ToxPi results. It also provides a statistical metric of stability for both individual ToxPi scores and relative prioritized ranks. The ToxPi GUI application, complete user manual and example data files are freely available from http://comptox.unc.edu/toxpi.php.

Message survival and decision dynamics in a class of reactive complex systems subject to external fields

NASA Astrophysics Data System (ADS)

Rodriguez Lucatero, C.; Schaum, A.; Alarcon Ramos, L.; Bernal-Jaquez, R.

2014-07-01

In this study, the dynamics of decisions in complex networks subject to external fields are studied within a Markov process framework using nonlinear dynamical systems theory. A mathematical discrete-time model is derived using a set of basic assumptions regarding the convincement mechanisms associated with two competing opinions. The model is analyzed with respect to the multiplicity of critical points and the stability of extinction states. Sufficient conditions for extinction are derived in terms of the convincement probabilities and the maximum eigenvalues of the associated connectivity matrices. The influences of exogenous (e.g., mass media-based) effects on decision behavior are analyzed qualitatively. The current analysis predicts: (i) the presence of fixed-point multiplicity (with a maximum number of four different fixed points), multi-stability, and sensitivity with respect to the process parameters; and (ii) the bounded but significant impact of exogenous perturbations on the decision behavior. These predictions were verified using a set of numerical simulations based on a scale-free network topology.

Shared decision making in preventive care in Switzerland: From theory to action.

PubMed

Selby, Kevin; Auer, Reto; Cornuz, Jacques

2017-06-01

Switzerland with its decentralized, liberal health system and its tradition of direct democracy may be an ideal place for shared decision making (SDM) to take root organically, rather than using top-down regulations seen in other countries. There are now multiple directives and programmes in place to encourage SDM, with the creation of several decision aids and specific training programs in the five Swiss medical schools. There has been an emphasis on preventive care, with the integration of patient preference into an organized colorectal cancer screening program, clear recommendations for prostate cancer screening, and inroads into the primary prevention of cardiovascular disease. Focusing on the experience of the University of Lausanne, we describe multiple approaches being taken to teaching SDM and the local development of decision aids, drawing on international experience but tailored to local needs. Efforts are being made to further involve patients in not only SDM, but also associated research and quality improvement projects. Copyright © 2017. Published by Elsevier GmbH.

The neural circuit and synaptic dynamics underlying perceptual decision-making

NASA Astrophysics Data System (ADS)

Liu, Feng

2015-03-01

Decision-making with several choice options is central to cognition. To elucidate the neural mechanisms of multiple-choice motion discrimination, we built a continuous recurrent network model to represent a local circuit in the lateral intraparietal area (LIP). The network is composed of pyramidal cells and interneurons, which are directionally tuned. All neurons are reciprocally connected, and the synaptic connectivity strength is heterogeneous. Specifically, we assume two types of inhibitory connectivity to pyramidal cells: opposite-feature and similar-feature inhibition. The model accounted for both physiological and behavioral data from monkey experiments. The network is endowed with slow excitatory reverberation, which subserves the buildup and maintenance of persistent neural activity, and predominant feedback inhibition, which underlies the winner-take-all competition and attractor dynamics. The opposite-feature and opposite-feature inhibition have different effects on decision-making, and only their combination allows for a categorical choice among 12 alternatives. Together, our work highlights the importance of structured synaptic inhibition in multiple-choice decision-making processes.

Simultaneous modeling of visual saliency and value computation improves predictions of economic choice.

PubMed

Towal, R Blythe; Mormann, Milica; Koch, Christof

2013-10-01

Many decisions we make require visually identifying and evaluating numerous alternatives quickly. These usually vary in reward, or value, and in low-level visual properties, such as saliency. Both saliency and value influence the final decision. In particular, saliency affects fixation locations and durations, which are predictive of choices. However, it is unknown how saliency propagates to the final decision. Moreover, the relative influence of saliency and value is unclear. Here we address these questions with an integrated model that combines a perceptual decision process about where and when to look with an economic decision process about what to choose. The perceptual decision process is modeled as a drift-diffusion model (DDM) process for each alternative. Using psychophysical data from a multiple-alternative, forced-choice task, in which subjects have to pick one food item from a crowded display via eye movements, we test four models where each DDM process is driven by (i) saliency or (ii) value alone or (iii) an additive or (iv) a multiplicative combination of both. We find that models including both saliency and value weighted in a one-third to two-thirds ratio (saliency-to-value) significantly outperform models based on either quantity alone. These eye fixation patterns modulate an economic decision process, also described as a DDM process driven by value. Our combined model quantitatively explains fixation patterns and choices with similar or better accuracy than previous models, suggesting that visual saliency has a smaller, but significant, influence than value and that saliency affects choices indirectly through perceptual decisions that modulate economic decisions.

Simultaneous modeling of visual saliency and value computation improves predictions of economic choice

PubMed Central

Towal, R. Blythe; Mormann, Milica; Koch, Christof

2013-01-01

Many decisions we make require visually identifying and evaluating numerous alternatives quickly. These usually vary in reward, or value, and in low-level visual properties, such as saliency. Both saliency and value influence the final decision. In particular, saliency affects fixation locations and durations, which are predictive of choices. However, it is unknown how saliency propagates to the final decision. Moreover, the relative influence of saliency and value is unclear. Here we address these questions with an integrated model that combines a perceptual decision process about where and when to look with an economic decision process about what to choose. The perceptual decision process is modeled as a drift–diffusion model (DDM) process for each alternative. Using psychophysical data from a multiple-alternative, forced-choice task, in which subjects have to pick one food item from a crowded display via eye movements, we test four models where each DDM process is driven by (i) saliency or (ii) value alone or (iii) an additive or (iv) a multiplicative combination of both. We find that models including both saliency and value weighted in a one-third to two-thirds ratio (saliency-to-value) significantly outperform models based on either quantity alone. These eye fixation patterns modulate an economic decision process, also described as a DDM process driven by value. Our combined model quantitatively explains fixation patterns and choices with similar or better accuracy than previous models, suggesting that visual saliency has a smaller, but significant, influence than value and that saliency affects choices indirectly through perceptual decisions that modulate economic decisions. PMID:24019496

The Computational Complexity of Valuation and Motivational Forces in Decision-Making Processes.

PubMed

Redish, A David; Schultheiss, Nathan W; Carter, Evan C

2016-01-01

The concept of value is fundamental to most theories of motivation and decision making. However, value has to be measured experimentally. Different methods of measuring value produce incompatible valuation hierarchies. Taking the agent's perspective (rather than the experimenter's), we interpret the different valuation measurement methods as accessing different decision-making systems and show how these different systems depend on different information processing algorithms. This identifies the translation from these multiple decision-making systems into a single action taken by a given agent as one of the most important open questions in decision making today. We conclude by looking at how these different valuation measures accessing different decision-making systems can be used to understand and treat decision dysfunction such as in addiction.

Are multiple-trial experiments appropriate for eyewitness identification studies? Accuracy, choosing, and confidence across trials.

PubMed

Mansour, J K; Beaudry, J L; Lindsay, R C L

2017-12-01

Eyewitness identification experiments typically involve a single trial: A participant views an event and subsequently makes a lineup decision. As compared to this single-trial paradigm, multiple-trial designs are more efficient, but significantly reduce ecological validity and may affect the strategies that participants use to make lineup decisions. We examined the effects of a number of forensically relevant variables (i.e., memory strength, type of disguise, degree of disguise, and lineup type) on eyewitness accuracy, choosing, and confidence across 12 target-present and 12 target-absent lineup trials (N = 349; 8,376 lineup decisions). The rates of correct rejections and choosing (across both target-present and target-absent lineups) did not vary across the 24 trials, as reflected by main effects or interactions with trial number. Trial number had a significant but trivial quadratic effect on correct identifications (OR = 0.99) and interacted significantly, but again trivially, with disguise type (OR = 1.00). Trial number did not significantly influence participants' confidence in correct identifications, confidence in correct rejections, or confidence in target-absent selections. Thus, multiple-trial designs appear to have minimal effects on eyewitness accuracy, choosing, and confidence. Researchers should thus consider using multiple-trial designs for conducting eyewitness identification experiments.

Application of risk-based multiple criteria decision analysis for selection of the best agricultural scenario for effective watershed management.

PubMed

Javidi Sabbaghian, Reza; Zarghami, Mahdi; Nejadhashemi, A Pouyan; Sharifi, Mohammad Bagher; Herman, Matthew R; Daneshvar, Fariborz

2016-03-01

Effective watershed management requires the evaluation of agricultural best management practice (BMP) scenarios which carefully consider the relevant environmental, economic, and social criteria involved. In the Multiple Criteria Decision-Making (MCDM) process, scenarios are first evaluated and then ranked to determine the most desirable outcome for the particular watershed. The main challenge of this process is the accurate identification of the best solution for the watershed in question, despite the various risk attitudes presented by the associated decision-makers (DMs). This paper introduces a novel approach for implementation of the MCDM process based on a comparative neutral risk/risk-based decision analysis, which results in the selection of the most desirable scenario for use in the entire watershed. At the sub-basin level, each scenario includes multiple BMPs with scores that have been calculated using the criteria derived from two cases of neutral risk and risk-based decision-making. The simple additive weighting (SAW) operator is applied for use in neutral risk decision-making, while the ordered weighted averaging (OWA) and induced OWA (IOWA) operators are effective for risk-based decision-making. At the watershed level, the BMP scores of the sub-basins are aggregated to calculate each scenarios' combined goodness measurements; the most desirable scenario for the entire watershed is then selected based on the combined goodness measurements. Our final results illustrate the type of operator and risk attitudes needed to satisfy the relevant criteria within the number of sub-basins, and how they ultimately affect the final ranking of the given scenarios. The methodology proposed here has been successfully applied to the Honeyoey Creek-Pine Creek watershed in Michigan, USA to evaluate various BMP scenarios and determine the best solution for both the stakeholders and the overall stream health. Copyright © 2015 Elsevier Ltd. All rights reserved.

SYSTEMATIC PROCEDURE FOR DESIGNING PROCESSES WITH MULTIPLE ENVIRONMENTAL OBJECTIVES

EPA Science Inventory

Evaluation of multiple objectives is very important in designing environmentally benign processes. It requires a systematic procedure for solving multiobjective decision-making problems, due to the complex nature of the problems, the need for complex assessments, and complicated ...