A new decision sciences for complex systems.

PubMed

Lempert, Robert J

2002-05-14

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

Mental models: an alternative evaluation of a sensemaking approach to ethics instruction.

PubMed

Brock, Meagan E; Vert, Andrew; Kligyte, Vykinta; Waples, Ethan P; Sevier, Sydney T; Mumford, Michael D

2008-09-01

In spite of the wide variety of approaches to ethics training it is still debatable which approach has the highest potential to enhance professionals' integrity. The current effort assesses a novel curriculum that focuses on metacognitive reasoning strategies researchers use when making sense of day-to-day professional practices that have ethical implications. The evaluated trainings effectiveness was assessed by examining five key sensemaking processes, such as framing, emotion regulation, forecasting, self-reflection, and information integration that experts and novices apply in ethical decision-making. Mental models of trained and untrained graduate students, as well as faculty, working in the field of physical sciences were compared using a think-aloud protocol 6 months following the ethics training. Evaluation and comparison of the mental models of participants provided further validation evidence for sensemaking training. Specifically, it was found that trained students applied metacognitive reasoning strategies learned during training in their ethical decision-making that resulted in complex mental models focused on the objective assessment of the situation. Mental models of faculty and untrained students were externally-driven with a heavy focus on autobiographical processes. The study shows that sensemaking training has a potential to induce shifts in researchers' mental models by making them more cognitively complex via the use of metacognitive reasoning strategies. Furthermore, field experts may benefit from sensemaking training to improve their ethical decision-making framework in highly complex, novel, and ambiguous situations.

Application of TOPSIS and VIKOR improved versions in a multi criteria decision analysis to develop an optimized municipal solid waste management model.

PubMed

Aghajani Mir, M; Taherei Ghazvinei, P; Sulaiman, N M N; Basri, N E A; Saheri, S; Mahmood, N Z; Jahan, A; Begum, R A; Aghamohammadi, N

2016-01-15

Selecting a suitable Multi Criteria Decision Making (MCDM) method is a crucial stage to establish a Solid Waste Management (SWM) system. Main objective of the current study is to demonstrate and evaluate a proposed method using Multiple Criteria Decision Making methods (MCDM). An improved version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied to obtain the best municipal solid waste management method by comparing and ranking the scenarios. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Besides, Viekriterijumsko Kompromisno Rangiranje (VIKOR) compromise solution method applied for sensitivity analyses. The proposed method can assist urban decision makers in prioritizing and selecting an optimized Municipal Solid Waste (MSW) treatment system. Besides, a logical and systematic scientific method was proposed to guide an appropriate decision-making. A modified TOPSIS methodology as a superior to existing methods for first time was applied for MSW problems. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Next, 11 scenarios of MSW treatment methods are defined and compared environmentally and economically based on the waste management conditions. Results show that integrating a sanitary landfill (18.1%), RDF (3.1%), composting (2%), anaerobic digestion (40.4%), and recycling (36.4%) was an optimized model of integrated waste management. An applied decision-making structure provides the opportunity for optimum decision-making. Therefore, the mix of recycling and anaerobic digestion and a sanitary landfill with Electricity Production (EP) are the preferred options for MSW management. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

Career Decision Making and Its Evaluation.

ERIC Educational Resources Information Center

Miller-Tiedeman, Anna

1979-01-01

The author discusses a career decision-making program which she designed and implemented using a pyramidal model of exploration, crystallization, choice, and classification. Her article outlines the value of rigorous evaluation techniques applied by the local practitioner. (MF)

Forecasting in Military Affairs. A Soviet View,

DTIC Science & Technology

1975-01-01

particular, forecasting models must take adequate account of time. This applies especially to models of processes of armed conflict, as the most complex and...too varied for permanently fixed rules to be applied to them."’ Combat situations are always more complex and varied than thosereferred to in various...writing this book was to make up for the lack of Soviet literature on the subject of forecasting as it applies specifically to military activities

Do Teachers Make Decisions Like Firefighters? Applying Naturalistic Decision-Making Methods to Teachers' In-Class Decision Making in Mathematics

ERIC Educational Resources Information Center

Jazby, Dan

2014-01-01

Research into human decision making (DM) processes from outside of education paint a different picture of DM than current DM models in education. This pilot study assesses the use of critical decision method (CDM)--developed from observations of firefighters' DM -- in the context of primary mathematics teachers' in-class DM. Preliminary results…

Three Cases of Adolescent Childbearing Decision-Making: The Importance of Ambivalence

ERIC Educational Resources Information Center

Bender, Soley S.

2008-01-01

Limited information is available about the childbearing decision-making experience by the pregnant adolescent. The purpose of this case study was to explore this experience with three pregnant teenagers. The study is based on nine qualitative interviews. Within-case descriptions applying the theoretical model of decision-making regarding unwanted…

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…

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

PubMed Central

2018-01-01

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

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

PubMed

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

2018-01-01

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

The Influence of Socioeconomic Status on Changes in Young People's Expectations of Applying to University

ERIC Educational Resources Information Center

Anders, Jake

2017-01-01

A much larger proportion of English 14-year-olds expect to apply to university than ultimately make an application by age 21, but the proportion expecting to apply falls from age 14 onwards. In order to assess the role of socioeconomic status in explaining changes in expectations, this paper applies duration modelling techniques to the…

Embracing uncertainty in applied ecology.

PubMed

Milner-Gulland, E J; Shea, K

2017-12-01

Applied ecologists often face uncertainty that hinders effective decision-making.Common traps that may catch the unwary are: ignoring uncertainty, acknowledging uncertainty but ploughing on, focussing on trivial uncertainties, believing your models, and unclear objectives.We integrate research insights and examples from a wide range of applied ecological fields to illustrate advances that are generally underused, but could facilitate ecologists' ability to plan and execute research to support management.Recommended approaches to avoid uncertainty traps are: embracing models, using decision theory, using models more effectively, thinking experimentally, and being realistic about uncertainty. Synthesis and applications . Applied ecologists can become more effective at informing management by using approaches that explicitly take account of uncertainty.

Competency in health care management: a training model in epidemiologic methods for assessing and improving the quality of clinical practice through evidence-based decision making.

PubMed

Hudak, R P; Jacoby, I; Meyer, G S; Potter, A L; Hooper, T I; Krakauer, H

1997-01-01

This article describes a training model that focuses on health care management by applying epidemiologic methods to assess and improve the quality of clinical practice. The model's uniqueness is its focus on integrating clinical evidence-based decision making with fundamental principles of resource management to achieve attainable, cost-effective, high-quality health outcomes. The target students are current and prospective clinical and administrative executives who must optimize decision making at the clinical and managerial levels of health care organizations.

An Examination of Factors Influencing Students Selection of Business Majors Using TRA Framework

ERIC Educational Resources Information Center

Kumar, Anil; Kumar, Poonam

2013-01-01

Making decisions regarding the selection of a business major is both very important and challenging for students. An understanding of this decision-making process can be valuable for students, parents, and university programs. The current study applies the Theory of Reasoned Action (TRA) consumer decision-making model to examine factors that…

Learning from Decoding across Disciplines and within Communities of Practice

ERIC Educational Resources Information Center

Miller-Young, Janice; Boman, Jennifer

2017-01-01

This final chapter synthesizes the findings and implications derived from applying the Decoding the Disciplines model across disciplines and within communities of practice. We make practical suggestions for teachers and researchers who wish to apply and extend this work.

Practical Findings from Applying the PSD Model for Evaluating Software Design Specifications

NASA Astrophysics Data System (ADS)

Räisänen, Teppo; Lehto, Tuomas; Oinas-Kukkonen, Harri

This paper presents practical findings from applying the PSD model to evaluating the support for persuasive features in software design specifications for a mobile Internet device. On the one hand, our experiences suggest that the PSD model fits relatively well for evaluating design specifications. On the other hand, the model would benefit from more specific heuristics for evaluating each technique to avoid unnecessary subjectivity. Better distinction between the design principles in the social support category would also make the model easier to use. Practitioners who have no theoretical background can apply the PSD model to increase the persuasiveness of the systems they design. The greatest benefit of the PSD model for researchers designing new systems may be achieved when it is applied together with a sound theory, such as the Elaboration Likelihood Model. Using the ELM together with the PSD model, one may increase the chances for attitude change.

Genetic algorithm dynamics on a rugged landscape

NASA Astrophysics Data System (ADS)

Bornholdt, Stefan

1998-04-01

The genetic algorithm is an optimization procedure motivated by biological evolution and is successfully applied to optimization problems in different areas. A statistical mechanics model for its dynamics is proposed based on the parent-child fitness correlation of the genetic operators, making it applicable to general fitness landscapes. It is compared to a recent model based on a maximum entropy ansatz. Finally it is applied to modeling the dynamics of a genetic algorithm on the rugged fitness landscape of the NK model.

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

Treesearch

Mo Zhou; Joseph Buongiorno

2011-01-01

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

An examination of the impact of five grade crossing safety factors on driver decision making

DOT National Transportation Integrated Search

2014-04-01

The authors applied signal detection theory to model the impact : of five grade-crossing safety factors to understand their impact : on driver decision making. The safety factors were improving : commercial motor vehicle (CMV) driver safety through f...

A hybrid fuzzy logic/constraint satisfaction problem approach to automatic decision making in simulation game models.

PubMed

Braathen, Sverre; Sendstad, Ole Jakob

2004-08-01

Possible techniques for representing automatic decision-making behavior approximating human experts in complex simulation model experiments are of interest. Here, fuzzy logic (FL) and constraint satisfaction problem (CSP) methods are applied in a hybrid design of automatic decision making in simulation game models. The decision processes of a military headquarters are used as a model for the FL/CSP decision agents choice of variables and rulebases. The hybrid decision agent design is applied in two different types of simulation games to test the general applicability of the design. The first application is a two-sided zero-sum sequential resource allocation game with imperfect information interpreted as an air campaign game. The second example is a network flow stochastic board game designed to capture important aspects of land manoeuvre operations. The proposed design is shown to perform well also in this complex game with a very large (billionsize) action set. Training of the automatic FL/CSP decision agents against selected performance measures is also shown and results are presented together with directions for future research.

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

PubMed

McCullough, Laurence B

2013-02-01

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

The Myth of the Rational Decision Maker: A Framework for Applying and Enhancing Heuristic and Intuitive Decision Making by School Leaders

ERIC Educational Resources Information Center

Davis, Stephen H.

2004-01-01

This article takes a critical look at administrative decision making in schools and the extent to which complex decisions conform to normative models and common expectations of rationality. An alternative framework for administrative decision making is presented that is informed, but not driven, by theories of rationality. The framework assumes…

"Supporting" Beginning Secondary Science Teachers through Induction: A Multi-Case Study of Their Meaning Making and Identities

ERIC Educational Resources Information Center

Webb, Angela W.

2012-01-01

The purpose of this study was to explore the induction experiences of beginning secondary science teachers, including their afforded and enacted identities-in-practice and their meaning making. I applied a model of identities and meaning making that considered the iterative nature of the (a) normative science teacher identities afforded by…

Generic Software Architecture for Prognostics (GSAP) User Guide

NASA Technical Reports Server (NTRS)

Teubert, Christopher Allen; Daigle, Matthew John; Watkins, Jason; Sankararaman, Shankar; Goebel, Kai

2016-01-01

The Generic Software Architecture for Prognostics (GSAP) is a framework for applying prognostics. It makes applying prognostics easier by implementing many of the common elements across prognostic applications. The standard interface enables reuse of prognostic algorithms and models across systems using the GSAP framework.

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.

NASA Applied Sciences Program Rapid Prototyping Results and Conclusions

NASA Astrophysics Data System (ADS)

Cox, E. L.

2007-12-01

NASA's Applied Sciences Program seeks to expand the use of Earth science research results to benefit current and future operational systems tasked with making policy and management decisions. The Earth Science Division within the Science Mission Directorate sponsors over 1000 research projects annually to answer the fundamental research question: How is the Earth changing and what are the consequences for life on Earth? As research results become available, largely from satellite observations and Earth system model outputs, the Applied Sciences Program works diligently with scientists and researchers (internal and external to NASA) , and other government agency officials (USDA, EPA, CDC, DOE, US Forest Service, US Fish and Wildlife Service, DHS, USAID) to determine useful applications for these results in decision-making, ultimately benefiting society. The complexity of Earth science research results and the breadth of the Applied Sciences Program national priority areas dictate a broad scope and multiple approaches available to implement their use in decision-making. Over the past five years, the Applied Sciences Program has examined scientific and engineering practices and solicited the community for methods and steps that can lead to the enhancement of operational systems (Decision Support Systems - DSS) required for decision-making. In November 2006, the Applied Sciences Program launched an initiative aimed at demonstrating the applicability of NASA data (satellite observations, models, geophysical parameters from data archive centers) being incorporated into decision support systems and their related environments at a low cost and quick turnaround of results., i.e. designed rapid prototyping. Conceptually, an understanding of Earth science research (and results) coupled with decision-making requirements and needs leads to a demonstration (experiment) depicting enhancements or improvements to an operational decisions process through the use of NASA data. Five NASA centers (GSFC, LaRC, SSC, MSFC, ARC) participated and are currently conducting fifteen prototyping experiments covering eight of the twelve national priority applications - Energy, Coastal, Carbon, and Disaster Management; Agricultural Efficiency, Aviation, Air Quality, and Ecological Forecasting. Results from six experiments will be discussed highlighting purpose, expected results, enhancement to the decision-making process achieved, and the potential plans for future collaboration and sustainable projects.

Lessons from NASA Applied Sciences Program: Success Factors in Applying Earth Science in Decision Making

NASA Astrophysics Data System (ADS)

Friedl, L. A.; Cox, L.

2008-12-01

The NASA Applied Sciences Program collaborates with organizations to discover and demonstrate applications of NASA Earth science research and technology to decision making. The desired outcome is for public and private organizations to use NASA Earth science products in innovative applications for sustained, operational uses to enhance their decisions. In addition, the program facilitates the end-user feedback to Earth science to improve products and demands for research. The Program thus serves as a bridge between Earth science research and technology and the applied organizations and end-users with management, policy, and business responsibilities. Since 2002, the Applied Sciences Program has sponsored over 115 applications-oriented projects to apply Earth observations and model products to decision making activities. Projects have spanned numerous topics - agriculture, air quality, water resources, disasters, public health, aviation, etc. The projects have involved government agencies, private companies, universities, non-governmental organizations, and foreign entities in multiple types of teaming arrangements. The paper will examine this set of applications projects and present specific examples of successful use of Earth science in decision making. The paper will discuss scientific, organizational, and management factors that contribute to or impede the integration of the Earth science research in policy and management. The paper will also present new methods the Applied Sciences Program plans to implement to improve linkages between science and end users.

A preference aggregation model and application in AHP-group decision making

NASA Astrophysics Data System (ADS)

Yang, Taiyi; Yang, De; Chao, Xiangrui

2018-04-01

Group decision making process integrate individual preferences to obtain the group preference by applying aggregation rules and preference relations. The two most useful approaches, the aggregation of individual judgements and the aggregation of individual priorities, traditionally are employed in the Analytic Hierarchy Process to deal with group decision making problems. In both cases, it is assumed that the group preference is approximate weighted mathematical expectation of individual judgements and individual priorities. We propose new preference aggregation methods using optimization models in order to obtain group preference which is close to all individual priorities. Some illustrative examples are finally examined to demonstrate proposed models for application.

Integrated Bayesian models of learning and decision making for saccadic eye movements.

PubMed

Brodersen, Kay H; Penny, Will D; Harrison, Lee M; Daunizeau, Jean; Ruff, Christian C; Duzel, Emrah; Friston, Karl J; Stephan, Klaas E

2008-11-01

The neurophysiology of eye movements has been studied extensively, and several computational models have been proposed for decision-making processes that underlie the generation of eye movements towards a visual stimulus in a situation of uncertainty. One class of models, known as linear rise-to-threshold models, provides an economical, yet broadly applicable, explanation for the observed variability in the latency between the onset of a peripheral visual target and the saccade towards it. So far, however, these models do not account for the dynamics of learning across a sequence of stimuli, and they do not apply to situations in which subjects are exposed to events with conditional probabilities. In this methodological paper, we extend the class of linear rise-to-threshold models to address these limitations. Specifically, we reformulate previous models in terms of a generative, hierarchical model, by combining two separate sub-models that account for the interplay between learning of target locations across trials and the decision-making process within trials. We derive a maximum-likelihood scheme for parameter estimation as well as model comparison on the basis of log likelihood ratios. The utility of the integrated model is demonstrated by applying it to empirical saccade data acquired from three healthy subjects. Model comparison is used (i) to show that eye movements do not only reflect marginal but also conditional probabilities of target locations, and (ii) to reveal subject-specific learning profiles over trials. These individual learning profiles are sufficiently distinct that test samples can be successfully mapped onto the correct subject by a naïve Bayes classifier. Altogether, our approach extends the class of linear rise-to-threshold models of saccadic decision making, overcomes some of their previous limitations, and enables statistical inference both about learning of target locations across trials and the decision-making process within trials.

Critical thinking in clinical nurse education: application of Paul's model of critical thinking.

PubMed

Andrea Sullivan, E

2012-11-01

Nurse educators recognize that many nursing students have difficulty in making decisions in clinical practice. The ability to make effective, informed decisions in clinical practice requires that nursing students know and apply the processes of critical thinking. Critical thinking is a skill that develops over time and requires the conscious application of this process. There are a number of models in the nursing literature to assist students in the critical thinking process; however, these models tend to focus solely on decision making in hospital settings and are often complex to actualize. In this paper, Paul's Model of Critical Thinking is examined for its application to nursing education. I will demonstrate how the model can be used by clinical nurse educators to assist students to develop critical thinking skills in all health care settings in a way that makes critical thinking skills accessible to students. Copyright © 2012 Elsevier Ltd. All rights reserved.

Teaching the Ethics of Biology.

ERIC Educational Resources Information Center

Johansen, Carol K.; Harris, David E.

2000-01-01

Points out the challenges of educating students about bioethics and the limited training of many biologists on ethics. Discusses the basic principles of ethics and ethical decision making as applied to biology. Explains the models of ethical decision making that are often difficult for students to determine where to begin analyzing. (Contains 28…

Computer-Assisted Community Planning and Decision Making.

ERIC Educational Resources Information Center

College of the Atlantic, Bar Harbor, ME.

The College of the Atlantic (COA) developed a broad-based, interdisciplinary curriculum in ecological policy and community planning and decision-making that incorporates two primary computer-based tools: ARC/INFO Geographic Information System (GIS) and STELLA, a systems-dynamics modeling tool. Students learn how to use and apply these tools…

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making.

PubMed

Knight, Gwenan M; Dharan, Nila J; Fox, Gregory J; Stennis, Natalie; Zwerling, Alice; Khurana, Renuka; Dowdy, David W

2016-01-01

The dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy), the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively re-evaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

USGS Publications Warehouse

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

2002-01-01

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

A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

PubMed

Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J

2015-03-15

This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.

Use of Cost-Utility Decision Models in Business Education.

ERIC Educational Resources Information Center

Lewis, Darrell R.

1989-01-01

Explains how cost-utility analysis can be applied to the selection of curriculum and instructional methods. Describes the use of multiattribute utility models of decision making as a tool for more informed judgment in educational administration. (SK)

Brain mechanisms for perceptual and reward-related decision-making.

PubMed

Deco, Gustavo; Rolls, Edmund T; Albantakis, Larissa; Romo, Ranulfo

2013-04-01

Phenomenological models of decision-making, including the drift-diffusion and race models, are compared with mechanistic, biologically plausible models, such as integrate-and-fire attractor neuronal network models. The attractor network models show how decision confidence is an emergent property; and make testable predictions about the neural processes (including neuronal activity and fMRI signals) involved in decision-making which indicate that the medial prefrontal cortex is involved in reward value-based decision-making. Synaptic facilitation in these models can help to account for sequential vibrotactile decision-making, and for how postponed decision-related responses are made. The randomness in the neuronal spiking-related noise that makes the decision-making probabilistic is shown to be increased by the graded firing rate representations found in the brain, to be decreased by the diluted connectivity, and still to be significant in biologically large networks with thousands of synapses onto each neuron. The stability of these systems is shown to be influenced in different ways by glutamatergic and GABAergic efficacy, leading to a new field of dynamical neuropsychiatry with applications to understanding schizophrenia and obsessive-compulsive disorder. The noise in these systems is shown to be advantageous, and to apply to similar attractor networks involved in short-term memory, long-term memory, attention, and associative thought processes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Planning a Stigmatized Nonvisible Illness Disclosure: Applying the Disclosure Decision-Making Model

PubMed Central

Choi, Soe Yoon; Venetis, Maria K.; Greene, Kathryn; Magsamen-Conrad, Kate; Checton, Maria G.; Banerjee, Smita C.

2016-01-01

This study applied the disclosure decision-making model (DD-MM) to explore how individuals plan to disclose nonvisible illness (Study 1), compared to planning to disclose personal information (Study 2). Study 1 showed that perceived stigma from the illness negatively predicted disclosure efficacy; closeness predicted anticipated response (i.e., provision of support) although it did not influence disclosure efficacy; disclosure efficacy led to reduced planning, with planning leading to scheduling. Study 2 demonstrated that when information was considered to be intimate, it negatively influenced disclosure efficacy. Unlike the model with stigma (Study 1), closeness positively predicted both anticipated response and disclosure efficacy. The rest of the hypothesized relationships showed a similar pattern to Study 1: disclosure efficacy reduced planning, which then positively influenced scheduling. Implications of understanding stages of planning for stigmatized information are discussed. PMID:27662447

Planning a Stigmatized Nonvisible Illness Disclosure: Applying the Disclosure Decision-Making Model.

PubMed

Choi, Soe Yoon; Venetis, Maria K; Greene, Kathryn; Magsamen-Conrad, Kate; Checton, Maria G; Banerjee, Smita C

2016-11-16

This study applied the disclosure decision-making model (DD-MM) to explore how individuals plan to disclose nonvisible illness (Study 1), compared to planning to disclose personal information (Study 2). Study 1 showed that perceived stigma from the illness negatively predicted disclosure efficacy; closeness predicted anticipated response (i.e., provision of support) although it did not influence disclosure efficacy; disclosure efficacy led to reduced planning, with planning leading to scheduling. Study 2 demonstrated that when information was considered to be intimate, it negatively influenced disclosure efficacy. Unlike the model with stigma (Study 1), closeness positively predicted both anticipated response and disclosure efficacy. The rest of the hypothesized relationships showed a similar pattern to Study 1: disclosure efficacy reduced planning, which then positively influenced scheduling. Implications of understanding stages of planning for stigmatized information are discussed.

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

Wieder, William R.; Allison, Steven D.; Davidson, Eric A.

Microbes influence soil organic matter (SOM) decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) may make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here, we review the diversity, advantages, and pitfalls of simulating soilmore » biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models we suggest: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.« less

Make Your Own Digital Thermometer!

ERIC Educational Resources Information Center

Sorey, Timothy; Willard, Teri; Kim, Bom

2010-01-01

In the hands-on, guided-inquiry lesson presented in this article, high school students create, calibrate, and apply an affordable scientific-grade instrument (Lapp and Cyrus 2000). In just four class periods, they build a homemade integrated circuit (IC) digital thermometer, apply a math model to calibrate their instrument, and ask a researchable…

Student Learning in an International Context: Examining Motivations for Education Transfer

ERIC Educational Resources Information Center

Roberts, Darbi

2016-01-01

This chapter examines the underlying motivations behind why institutions and organizations decide to apply particular policies and practices. By applying a lens of five diffusion models--learning, imitation, competition, normative, and coercion--to understand these motivations, decision makers and implementers will make better choices for…

An uncertainty analysis of wildfire modeling [Chapter 13

Treesearch

Karin Riley; Matthew Thompson

2017-01-01

Before fire models can be understood, evaluated, and effectively applied to support decision making, model-based uncertainties must be analyzed. In this chapter, we identify and classify sources of uncertainty using an established analytical framework, and summarize results graphically in an uncertainty matrix. Our analysis facilitates characterization of the...

The Vroom and Yetton Normative Leadership Model Applied to Public School Case Examples.

ERIC Educational Resources Information Center

Sample, John

This paper seeks to familiarize school administrators with the Vroom and Yetton Normative Leadership model by presenting its essential components and providing original case studies for its application to school settings. The five decision-making methods of the Vroom and Yetton model, including two "autocratic," two…

Making Connections by Using Molecular Models in Geometry.

ERIC Educational Resources Information Center

Pacyga, Robert

1995-01-01

Describes two activities to analyze unit-cell structures from a geometric viewpoint and invites students to apply their mathematical understanding to scientific phenomena. Students form models of the simple cube, a building block of crystalline structures, and a methane molecule. (MKR)

Validation workflow for a clinical Bayesian network model in multidisciplinary decision making in head and neck oncology treatment.

PubMed

Cypko, Mario A; Stoehr, Matthaeus; Kozniewski, Marcin; Druzdzel, Marek J; Dietz, Andreas; Berliner, Leonard; Lemke, Heinz U

2017-11-01

Oncological treatment is being increasingly complex, and therefore, decision making in multidisciplinary teams is becoming the key activity in the clinical pathways. The increased complexity is related to the number and variability of possible treatment decisions that may be relevant to a patient. In this paper, we describe validation of a multidisciplinary cancer treatment decision in the clinical domain of head and neck oncology. Probabilistic graphical models and corresponding inference algorithms, in the form of Bayesian networks, can support complex decision-making processes by providing a mathematically reproducible and transparent advice. The quality of BN-based advice depends on the quality of the model. Therefore, it is vital to validate the model before it is applied in practice. For an example BN subnetwork of laryngeal cancer with 303 variables, we evaluated 66 patient records. To validate the model on this dataset, a validation workflow was applied in combination with quantitative and qualitative analyses. In the subsequent analyses, we observed four sources of imprecise predictions: incorrect data, incomplete patient data, outvoting relevant observations, and incorrect model. Finally, the four problems were solved by modifying the data and the model. The presented validation effort is related to the model complexity. For simpler models, the validation workflow is the same, although it may require fewer validation methods. The validation success is related to the model's well-founded knowledge base. The remaining laryngeal cancer model may disclose additional sources of imprecise predictions.

Facilitators and constraints at each stage of the migration decision process.

PubMed

Kley, Stefanie

2017-10-01

Behavioural models of migration emphasize the importance of migration decision-making for the explanation of subsequent behaviour. But empirical migration research regularly finds considerable gaps between those who intend to migrate and those who actually realize their intention. This paper applies the Theory of Planned Behaviour, enriched by the Rubicon model, to test specific hypotheses about distinct effects of facilitators and constraints on specific stages of migration decision-making and behaviour. The data come from a tailor-made panel survey based on random samples of people drawn from two German cities in 2006-07. The results show that in conventional models the effects of facilitators and constraints on migration decision-making are likely to be underestimated. Splitting the process of migration decision-making into a pre-decisional and a pre-actional phase helps to avoid bias in the estimated effects of facilitators and constraints on both migration decision-making and migration behaviour.

A new multiscale model to describe a modified Hall-Petch relation at different scales for nano and micro materials

NASA Astrophysics Data System (ADS)

Fadhil, Sadeem Abbas; Alrawi, Aoday Hashim; Azeez, Jazeel H.; Hassan, Mohsen A.

2018-04-01

In the present work, a multiscale model is presented and used to modify the Hall-Petch relation for different scales from nano to micro. The modified Hall-Petch relation is derived from a multiscale equation that determines the cohesive energy between the atoms and their neighboring grains. This brings with it a new term that was originally ignored even in the atomistic models. The new term makes it easy to combine all other effects to derive one modified equation for the Hall-Petch relation that works for all scales together, without the need to divide the scales into two scales, each scale with a different equation, as it is usually done in other works. Due to that, applying the new relation does not require a previous knowledge of the grain size distribution. This makes the new derived relation more consistent and easier to be applied for all scales. The new relation is used to fit the data for Copper and Nickel and it is applied well for the whole range of grain sizes from nano to micro scales.

Predictive Uncertainty And Parameter Sensitivity Of A Sediment-Flux Model: Nitrogen Flux and Sediment Oxygen Demand

EPA Science Inventory

Estimating model predictive uncertainty is imperative to informed environmental decision making and management of water resources. This paper applies the Generalized Sensitivity Analysis (GSA) to examine parameter sensitivity and the Generalized Likelihood Uncertainty Estimation...

Adverse outcome pathways linked to population models as an applied framework for investigating effects of chemical stressors

EPA Science Inventory

In addressing Beneficial Use Impairments (BUIs) at a Great Lakes Area of Concern (AOC), recovery from loss of fish and wildlife populations exposed to stressors is targeted for use in decision making. We describe a framework that can be applied in conjunction with field monitori...

Surveillance theory applied to virus detection: a case for targeted discovery

USGS Publications Warehouse

Bogich, Tiffany L.; Anthony, Simon J.; Nichols, James D.

2013-01-01

Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.

Order reduction for a model of marine bacteriophage evolution

NASA Astrophysics Data System (ADS)

Pagliarini, Silvia; Korobeinikov, Andrei

2017-02-01

A typical mechanistic model of viral evolution necessary includes several time scales which can differ by orders of magnitude. Such a diversity of time scales makes analysis of these models difficult. Reducing the order of a model is highly desirable when handling such a model. A typical approach applied to such slow-fast (or singularly perturbed) systems is the time scales separation technique. Constructing the so-called quasi-steady-state approximation is the usual first step in applying the technique. While this technique is commonly applied, in some cases its straightforward application can lead to unsatisfactory results. In this paper we construct the quasi-steady-state approximation for a model of evolution of marine bacteriophages based on the Beretta-Kuang model. We show that for this particular model the quasi-steady-state approximation is able to produce only qualitative but not quantitative fit.

Real-time emergency forecasting technique for situation management systems

NASA Astrophysics Data System (ADS)

Kopytov, V. V.; Kharechkin, P. V.; Naumenko, V. V.; Tretyak, R. S.; Tebueva, F. B.

2018-05-01

The article describes the real-time emergency forecasting technique that allows increasing accuracy and reliability of forecasting results of any emergency computational model applied for decision making in situation management systems. Computational models are improved by the Improved Brown’s method applying fractal dimension to forecast short time series data being received from sensors and control systems. Reliability of emergency forecasting results is ensured by the invalid sensed data filtering according to the methods of correlation analysis.

An entropic barriers diffusion theory of decision-making in multiple alternative tasks

PubMed Central

Sigman, Mariano; Cecchi, Guillermo A.

2018-01-01

We present a theory of decision-making in the presence of multiple choices that departs from traditional approaches by explicitly incorporating entropic barriers in a stochastic search process. We analyze response time data from an on-line repository of 15 million blitz chess games, and show that our model fits not just the mean and variance, but the entire response time distribution (over several response-time orders of magnitude) at every stage of the game. We apply the model to show that (a) higher cognitive expertise corresponds to the exploration of more complex solution spaces, and (b) reaction times of users at an on-line buying website can be similarly explained. Our model can be seen as a synergy between diffusion models used to model simple two-choice decision-making and planning agents in complex problem solving. PMID:29499036

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

NASA Astrophysics Data System (ADS)

Faghihinia, Elahe; Mollaverdi, Naser

2012-08-01

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

Planning Single-Event Nutrition Education: A New Model

ERIC Educational Resources Information Center

Brown, Lora Beth

2011-01-01

A theoretical model for planning single-event nutrition education contrasts a Practical, Foods, and Positive (PFP) emphasis to an Abstract, Nutrient, and Negative (ANN) focus on nutrition topics. Use of this model makes messages more appealing to consumers and may increase the likelihood that people will apply the nutrition information in their…

Families and Deinstitutionalization: An Application of Bronfenbrenner's Social Ecology Model.

ERIC Educational Resources Information Center

Berry, Judy O.

1995-01-01

Applied Bronfenbrenner's social ecology model to families that include a member with a developmental disability and who are making the transition from institution to community. Presents an overview of the model as well as a discussion of counselors' use of it in providing services to families in this situation. (RJM)

Graph theory applied to noise and vibration control in statistical energy analysis models.

PubMed

Guasch, Oriol; Cortés, Lluís

2009-06-01

A fundamental aspect of noise and vibration control in statistical energy analysis (SEA) models consists in first identifying and then reducing the energy flow paths between subsystems. In this work, it is proposed to make use of some results from graph theory to address both issues. On the one hand, linear and path algebras applied to adjacency matrices of SEA graphs are used to determine the existence of any order paths between subsystems, counting and labeling them, finding extremal paths, or determining the power flow contributions from groups of paths. On the other hand, a strategy is presented that makes use of graph cut algorithms to reduce the energy flow from a source subsystem to a receiver one, modifying as few internal and coupling loss factors as possible.

Emotion and the law: a framework for inquiry.

PubMed

Wiener, Richard L; Bornstein, Brian H; Voss, Amy

2006-04-01

This paper draws on research in social and cognitive psychology to show how theories of judgment and decision making that incorporate decision makers' affective responses apply to legal contexts. It takes 2 widely used models of decision making, the rational actor and lens models, and illustrates their utility for understanding legal judgments by using them to interpret research findings on juror decision making, people's obedience to the law (e.g., paying taxes), and eyewitness memory. The paper concludes with a discussion of the advantages of modifying existing approaches to information processing to include the influence of affect on how legal actors reach judgments about law and legal process.

Assimilating multi-source uncertainties of a parsimonious conceptual hydrological model using hierarchical Bayesian modeling

Treesearch

Wei Wu; James Clark; James Vose

2010-01-01

Hierarchical Bayesian (HB) modeling allows for multiple sources of uncertainty by factoring complex relationships into conditional distributions that can be used to draw inference and make predictions. We applied an HB model to estimate the parameters and state variables of a parsimonious hydrological model – GR4J – by coherently assimilating the uncertainties from the...

Becoming Syntactic

ERIC Educational Resources Information Center

Chang, Franklin; Dell, Gary S.; Bock, Kathryn

2006-01-01

Psycholinguistic research has shown that the influence of abstract syntactic knowledge on performance is shaped by particular sentences that have been experienced. To explore this idea, the authors applied a connectionist model of sentence production to the development and use of abstract syntax. The model makes use of (a) error-based learning to…

Safety Assessment of Dangerous Goods Transport Enterprise Based on the Relative Entropy Aggregation in Group Decision Making Model

PubMed Central

Wu, Jun; Li, Chengbing; Huo, Yueying

2014-01-01

Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises. PMID:25477954

Safety assessment of dangerous goods transport enterprise based on the relative entropy aggregation in group decision making model.

PubMed

Wu, Jun; Li, Chengbing; Huo, Yueying

2014-01-01

Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises.

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

NASA Technical Reports Server (NTRS)

Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

Abstraction of an Affective-Cognitive Decision Making Model Based on Simulated Behaviour and Perception Chains

NASA Astrophysics Data System (ADS)

Sharpanskykh, Alexei; Treur, Jan

Employing rich internal agent models of actors in large-scale socio-technical systems often results in scalability issues. The problem addressed in this paper is how to improve computational properties of a complex internal agent model, while preserving its behavioral properties. The problem is addressed for the case of an existing affective-cognitive decision making model instantiated for an emergency scenario. For this internal decision model an abstracted behavioral agent model is obtained, which ensures a substantial increase of the computational efficiency at the cost of approximately 1% behavioural error. The abstraction technique used can be applied to a wide range of internal agent models with loops, for example, involving mutual affective-cognitive interactions.

Cognitive Modeling of Video Game Player User Experience

NASA Technical Reports Server (NTRS)

Bohil, Corey J.; Biocca, Frank A.

2010-01-01

This paper argues for the use of cognitive modeling to gain a detailed and dynamic look into user experience during game play. Applying cognitive models to game play data can help researchers understand a player's attentional focus, memory status, learning state, and decision strategies (among other things) as these cognitive processes occurred throughout game play. This is a stark contrast to the common approach of trying to assess the long-term impact of games on cognitive functioning after game play has ended. We describe what cognitive models are, what they can be used for and how game researchers could benefit by adopting these methods. We also provide details of a single model - based on decision field theory - that has been successfUlly applied to data sets from memory, perception, and decision making experiments, and has recently found application in real world scenarios. We examine possibilities for applying this model to game-play data.

ePCR: an R-package for survival and time-to-event prediction in advanced prostate cancer, applied to real-world patient cohorts.

PubMed

Laajala, Teemu D; Murtojärvi, Mika; Virkki, Arho; Aittokallio, Tero

2018-06-15

Prognostic models are widely used in clinical decision-making, such as risk stratification and tailoring treatment strategies, with the aim to improve patient outcomes while reducing overall healthcare costs. While prognostic models have been adopted into clinical use, benchmarking their performance has been difficult due to lack of open clinical datasets. The recent DREAM 9.5 Prostate Cancer Challenge carried out an extensive benchmarking of prognostic models for metastatic Castration-Resistant Prostate Cancer (mCRPC), based on multiple cohorts of open clinical trial data. We make available an open-source implementation of the top-performing model, ePCR, along with an extended toolbox for its further re-use and development, and demonstrate how to best apply the implemented model to real-world data cohorts of advanced prostate cancer patients. The open-source R-package ePCR and its reference documentation are available at the Central R Archive Network (CRAN): https://CRAN.R-project.org/package=ePCR. R-vignette provides step-by-step examples for the ePCR usage. Supplementary data are available at Bioinformatics online.

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.

Sharp Truncation of an Electric Field: An Idealized Model that Warrants Caution

NASA Astrophysics Data System (ADS)

Tu, Hong; Zhu, Jiongming

2016-03-01

In physics, idealized models are often used to simplify complex situations. The motivation of the idealization is to make the real complex system tractable by adopting certain simplifications. In this treatment some unnecessary, negligible aspects are stripped away (so-called Aristotelian idealization), or some deliberate distortions are involved (so-called Galilean idealization). The most important principle in using an idealized model is to make sure that all the neglected aspects do not affect our analysis or result. Point charges, rigid bodies, simple pendulums, frictionless planes, and isolated systems are all frequently used idealized models. However, when they are applied to certain uncommon models, extra precautions should be taken. The possibilities and necessities of adopting the idealizations have to be considered carefully. Sometimes some factors neglected or ignored in the idealization could completely change the result, even make the treatment unphysical and conclusions unscientific.

A conceptual review of decision making in social dilemmas: applying a logic of appropriateness.

PubMed

Weber, J Mark; Kopelman, Shirli; Messick, David M

2004-01-01

Despite decades of experimental social dilemma research, "theoretical integration has proven elusive" (Smithson & Foddy, 1999, p. 14). To advance a theory of decision making in social dilemmas, this article provides a conceptual review of the literature that applies a "logic of appropriateness" (March, 1994) framework. The appropriateness framework suggests that people making decisions ask themselves (explicitly or implicitly), "What does a person like me do in a situation like this? " This question identifies 3 significant factors: recognition and classification of the kind of situation encountered, the identity of the individual making the decision, and the application of rules or heuristics in guiding behavioral choice. In contrast with dominant rational choice models, the appropriateness framework proposed accommodates the inherently social nature of social dilemmas, and the role of rule and heuristic based processing. Implications for the interpretation of past findings and the direction of future research are discussed.

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

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

Burns, B.A.

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

Time Horizons, Discounting, and Intertemporal Choice

ERIC Educational Resources Information Center

Streich, Philip; Levy, Jack S.

2007-01-01

Although many decisions involve a stream of payoffs over time, political scientists have given little attention to how actors make the required tradeoffs between present and future payoffs, other than applying the standard exponential discounting model from economics. After summarizing the basic discounting model, we identify some of its leading…

Bayesian Monte Carlo and Maximum Likelihood Approach for Uncertainty Estimation and Risk Management: Application to Lake Oxygen Recovery Model

EPA Science Inventory

Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood e...

Teaching, Learning and Evaluation Techniques in the Engineering Courses.

ERIC Educational Resources Information Center

Vermaas, Luiz Lenarth G.; Crepaldi, Paulo Cesar; Fowler, Fabio Roberto

This article presents some techniques of professional formation from the Petra Model that can be applied in Engineering Programs. It shows its philosophy, teaching methods for listening, making abstracts, studying, researching, team working and problem solving. Some questions regarding planning and evaluation, based in the model are, as well,…

Turbomachinery Heat Transfer and Loss Modeling for 3D Navier-Stokes Codes

NASA Technical Reports Server (NTRS)

DeWitt, Kenneth; Ameri, Ali

2005-01-01

This report's contents focus on making use of NASA Glenn on-site computational facilities,to develop, validate, and apply models for use in advanced 3D Navier-Stokes Computational Fluid Dynamics (CFD) codes to enhance the capability to compute heat transfer and losses in turbomachiney.

Visual Basic, Excel-based fish population modeling tool - The pallid sturgeon example

USGS Publications Warehouse

Moran, Edward H.; Wildhaber, Mark L.; Green, Nicholas S.; Albers, Janice L.

2016-02-10

The model presented in this report is a spreadsheet-based model using Visual Basic for Applications within Microsoft Excel (http://dx.doi.org/10.5066/F7057D0Z) prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service. It uses the same model structure and, initially, parameters as used by Wildhaber and others (2015) for pallid sturgeon. The difference between the model structure used for this report and that used by Wildhaber and others (2015) is that variance is not partitioned. For the model of this report, all variance is applied at the iteration and time-step levels of the model. Wildhaber and others (2015) partition variance into parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level and temporal variance (uncertainty caused by random environmental fluctuations with time) applied at the time-step level. They included implicit individual variance (uncertainty caused by differences between individuals) within the time-step level.The interface developed for the model of this report is designed to allow the user the flexibility to change population model structure and parameter values and uncertainty separately for every component of the model. This flexibility makes the modeling tool potentially applicable to any fish species; however, the flexibility inherent in this modeling tool makes it possible for the user to obtain spurious outputs. The value and reliability of the model outputs are only as good as the model inputs. Using this modeling tool with improper or inaccurate parameter values, or for species for which the structure of the model is inappropriate, could lead to untenable management decisions. By facilitating fish population modeling, this modeling tool allows the user to evaluate a range of management options and implications. The goal of this modeling tool is to be a user-friendly modeling tool for developing fish population models useful to natural resource managers to inform their decision-making processes; however, as with all population models, caution is needed, and a full understanding of the limitations of a model and the veracity of user-supplied parameters should always be considered when using such model output in the management of any species.

Linear models to perform treaty verification tasks for enhanced information security

DOE PAGES

MacGahan, Christopher J.; Kupinski, Matthew A.; Brubaker, Erik M.; ...

2016-11-12

Linear mathematical models were applied to binary-discrimination tasks relevant to arms control verification measurements in which a host party wishes to convince a monitoring party that an item is or is not treaty accountable. These models process data in list-mode format and can compensate for the presence of variability in the source, such as uncertain object orientation and location. The Hotelling observer applies an optimal set of weights to binned detector data, yielding a test statistic that is thresholded to make a decision. The channelized Hotelling observer applies a channelizing matrix to the vectorized data, resulting in a lower dimensionalmore » vector available to the monitor to make decisions. We demonstrate how incorporating additional terms in this channelizing-matrix optimization offers benefits for treaty verification. We present two methods to increase shared information and trust between the host and monitor. The first method penalizes individual channel performance in order to maximize the information available to the monitor while maintaining optimal performance. Second, we present a method that penalizes predefined sensitive information while maintaining the capability to discriminate between binary choices. Data used in this study was generated using Monte Carlo simulations for fission neutrons, accomplished with the GEANT4 toolkit. Custom models for plutonium inspection objects were measured in simulation by a radiation imaging system. Model performance was evaluated and presented using the area under the receiver operating characteristic curve.« less

Linear models to perform treaty verification tasks for enhanced information security

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

MacGahan, Christopher J.; Kupinski, Matthew A.; Brubaker, Erik M.

Linear mathematical models were applied to binary-discrimination tasks relevant to arms control verification measurements in which a host party wishes to convince a monitoring party that an item is or is not treaty accountable. These models process data in list-mode format and can compensate for the presence of variability in the source, such as uncertain object orientation and location. The Hotelling observer applies an optimal set of weights to binned detector data, yielding a test statistic that is thresholded to make a decision. The channelized Hotelling observer applies a channelizing matrix to the vectorized data, resulting in a lower dimensionalmore » vector available to the monitor to make decisions. We demonstrate how incorporating additional terms in this channelizing-matrix optimization offers benefits for treaty verification. We present two methods to increase shared information and trust between the host and monitor. The first method penalizes individual channel performance in order to maximize the information available to the monitor while maintaining optimal performance. Second, we present a method that penalizes predefined sensitive information while maintaining the capability to discriminate between binary choices. Data used in this study was generated using Monte Carlo simulations for fission neutrons, accomplished with the GEANT4 toolkit. Custom models for plutonium inspection objects were measured in simulation by a radiation imaging system. Model performance was evaluated and presented using the area under the receiver operating characteristic curve.« less

Linear models to perform treaty verification tasks for enhanced information security

NASA Astrophysics Data System (ADS)

MacGahan, Christopher J.; Kupinski, Matthew A.; Brubaker, Erik M.; Hilton, Nathan R.; Marleau, Peter A.

2017-02-01

Linear mathematical models were applied to binary-discrimination tasks relevant to arms control verification measurements in which a host party wishes to convince a monitoring party that an item is or is not treaty accountable. These models process data in list-mode format and can compensate for the presence of variability in the source, such as uncertain object orientation and location. The Hotelling observer applies an optimal set of weights to binned detector data, yielding a test statistic that is thresholded to make a decision. The channelized Hotelling observer applies a channelizing matrix to the vectorized data, resulting in a lower dimensional vector available to the monitor to make decisions. We demonstrate how incorporating additional terms in this channelizing-matrix optimization offers benefits for treaty verification. We present two methods to increase shared information and trust between the host and monitor. The first method penalizes individual channel performance in order to maximize the information available to the monitor while maintaining optimal performance. Second, we present a method that penalizes predefined sensitive information while maintaining the capability to discriminate between binary choices. Data used in this study was generated using Monte Carlo simulations for fission neutrons, accomplished with the GEANT4 toolkit. Custom models for plutonium inspection objects were measured in simulation by a radiation imaging system. Model performance was evaluated and presented using the area under the receiver operating characteristic curve.

Fit of Item Response Theory Models: A Survey of Data from Several Operational Tests. Research Report. ETS RR-11-29

ERIC Educational Resources Information Center

Sinharay, Sandip; Haberman, Shelby J.; Jia, Helena

2011-01-01

Standard 3.9 of the "Standards for Educational and Psychological Testing" (American Educational Research Association, American Psychological Association, & National Council for Measurement in Education, 1999) demands evidence of model fit when an item response theory (IRT) model is used to make inferences from a data set. We applied two recently…

A marketing model: applications for dietetic professionals.

PubMed

Parks, S C; Moody, D L

1986-01-01

Traditionally, dietitians have communicated the availability of their services to the "public at large." The expectation was that the public would respond favorably to nutrition programs simply because there was a consumer need for them. Recently, however, both societal and consumer needs have changed dramatically, making old communication strategies ineffective and obsolete. The marketing discipline has provided a new model and new decision-making tools for many health professionals to use to more effectively make their services known to multiple consumer groups. This article provides one such model as applied to the dietetic profession. The model explores a definition of the business of dietetics, how to conduct an analysis of the environment, and, finally, the use of both in the choice of new target markets. Further, the model discusses the major components of developing a marketing strategy that will help the practitioner to be competitive in the marketplace. Presented are strategies for defining and re-evaluating the mission of the profession, for using future trends to identify new markets and roles for the profession, and for developing services that make the profession more competitive by better meeting the needs of the consumer.

Theories of Health Care Decision Making at the End of Life: A Meta-Ethnography.

PubMed

Kim, Kyounghae; Heinze, Katherine; Xu, Jiayun; Kurtz, Melissa; Park, Hyunjeong; Foradori, Megan; Nolan, Marie T

2017-08-01

The aim of this meta-ethnography is to appraise the types and uses of theories relative to end-of-life decision making and to develop a conceptual framework to describe end-of-life decision making among patients with advanced cancers, heart failure, and amyotrophic lateral sclerosis (ALS) and their caregivers or providers. We used PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases to extract English-language articles published between January 2002 and April 2015. Forty-three articles were included. The most common theories included decision-making models ( n = 14) followed by family-centered ( n = 11) and behavioral change models ( n = 7). A conceptual framework was developed using themes including context of decision making, communication and negotiation of decision making, characteristics of decision makers, goals of decision making, options and alternatives, and outcomes. Future research should enhance and apply these theories to guide research to develop patient-centered decision-making programs that facilitate informed and shared decision making at the end of life among patients with advanced illness and their caregivers.

REVA CLIENT PARTNERSHIPS

EPA Science Inventory

EPA's Regional Vulnerability Assessment (ReVA) program is an applied research program that is focused on the synthesis and presentation of existing environmental data and model results to inform multicriteria environmental decision-making through a comprehensive analysis of infor...

Financial Management and Control for Decision Making in Urban Local Bodies in India Using Statistical Techniques

NASA Astrophysics Data System (ADS)

Bhattacharyya, Sidhakam; Bandyopadhyay, Gautam

2010-10-01

The council of most of the Urban Local Bodies (ULBs) has a limited scope for decision making in the absence of appropriate financial control mechanism. The information about expected amount of own fund during a particular period is of great importance for decision making. Therefore, in this paper, efforts are being made to present set of findings and to establish a model of estimating receipts of own sources and payments thereof using multiple regression analysis. Data for sixty months from a reputed ULB in West Bengal have been considered for ascertaining the regression models. This can be used as a part of financial management and control procedure by the council to estimate the effect on own fund. In our study we have considered two models using multiple regression analysis. "Model I" comprises of total adjusted receipt as the dependent variable and selected individual receipts as the independent variables. Similarly "Model II" consists of total adjusted payments as the dependent variable and selected individual payments as independent variables. The resultant of Model I and Model II is the surplus or deficit effecting own fund. This may be applied for decision making purpose by the council.

The Relationship between Teachers' and Principals' Decision-Making Power: Is It a Win-Win Situation or a Zero-Sum Game?

ERIC Educational Resources Information Center

Shen, Jianping; Xia, Jiangang

2012-01-01

Is the power relationship between public school teachers and principals a win-win situation or a zero-sum game? By applying hierarchical linear modeling to the 1999-2000 nationally representative Schools and Staffing Survey data, we found that both the win-win and zero-sum-game theories had empirical evidence. The decision-making areas…

Incompetent Patients, Substitute Decision Making, and Quality of Life: Some Ethical Considerations

PubMed Central

Kluge, Eike-Henner W.

2008-01-01

One of the most difficult situations facing physicians involves decision making by substitute decision makers for patients who have never been competent. This paper begins with a brief examination of the ethics of substitute decision making for previously competent patients. It then applies the results to substitute decision making for patients who have never been competent, and critically analyzes 5 models of substitute decision making for such patients, showing why each either contravenes basic ethical principles or fails to guarantee the use of ethically appropriate values. It concludes by sketching a modified objective reasonable person standard for substitute decision making that avoids valuational difficulties and allows for a protocol that satisfies ethical principles. PMID:19099031

Science Inquiry into Local Animals: Structure and Function Explored through Model Making

ERIC Educational Resources Information Center

Rule, Audrey C.; Tallakson, Denise A.; Glascock, Alex L.; Chao, Astoria

2015-01-01

This article describes an arts- and spatial thinking skill--integrated inquiry project applied to life science concepts from the Next Generation Science Standards for fourth grade students that focuses on two unifying or crosscutting themes: (1) structure (or "form") and function and (2) use of models. Students made observations and…

The Application of Continuous Quality Improvement Models and Methods to Higher Education: Can We Learn from Business?

ERIC Educational Resources Information Center

Downey, Thomas E.

Continuous quality improvement (CQI) models, which were first applied in business, are critical to making new technology-based learning paradigms and flexible learning environments a reality. The following are among the factors that have facilitated CQI's application in education: increased operating costs; increased competition from private…

Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Wagler, Amy E.

2014-01-01

Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…

How to Run a University

ERIC Educational Resources Information Center

Evans, G. R.

2006-01-01

The Lambert Review of Business-University Collaboration proposed a business model for universities in 2003. Pressure to change university governance to make it match the business model remains strong, and it is being most actively applied to Oxford and Cambridge. The Oxford and Cambridge governance debates (which began in the 1990s) open up the…

Kinetic theory of situated agents applied to pedestrian flow in a corridor

NASA Astrophysics Data System (ADS)

Rangel-Huerta, A.; Muñoz-Meléndez, A.

2010-03-01

A situated agent-based model for simulation of pedestrian flow in a corridor is presented. In this model, pedestrians choose their paths freely and make decisions based on local criteria for solving collision conflicts. The crowd consists of multiple walking agents equipped with a function of perception as well as a competitive rule-based strategy that enables pedestrians to reach free access areas. Pedestrians in our model are autonomous entities capable of perceiving and making decisions. They apply socially accepted conventions, such as avoidance rules, as well as individual preferences such as the use of specific exit points, or the execution of eventual comfort turns resulting in spontaneous changes of walking speed. Periodic boundary conditions were considered in order to determine the density-average walking speed, and the density-average activity with respect to specific parameters: comfort angle turn and frequency of angle turn of walking agents. The main contribution of this work is an agent-based model where each pedestrian is represented as an autonomous agent. At the same time the pedestrian crowd dynamics is framed by the kinetic theory of biological systems.

Decision Making Under Objective Risk Conditions-a Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences.

PubMed

Schiebener, Johannes; Brand, Matthias

2015-06-01

While making decisions under objective risk conditions, the probabilities of the consequences of the available options are either provided or calculable. Brand et al. (Neural Networks 19:1266-1276, 2006) introduced a model describing the neuro-cognitive processes involved in such decisions. In this model, executive functions associated with activity in the fronto-striatal loop are important for developing and applying decision-making strategies, and for verifying, adapting, or revising strategies according to feedback. Emotional rewards and punishments learned from such feedback accompany these processes. In this literature review, we found support for the role of executive functions, but also found evidence for the importance of further cognitive abilities in decision making. Moreover, in addition to reflective processing (driven by cognition), decisions can be guided by impulsive processing (driven by anticipation of emotional reward and punishment). Reflective and impulsive processing may interact during decision making, affecting the evaluation of available options, as both processes are affected by feedback. Decision-making processes are furthermore modulated by individual attributes (e.g., age), and external influences (e.g., stressors). Accordingly, we suggest a revised model of decision making under objective risk conditions.

Evidence-based dentistry: a model for clinical practice.

PubMed

Faggion, Clóvis M; Tu, Yu-Kang

2007-06-01

Making decisions in dentistry should be based on the best evidence available. The objective of this study was to demonstrate a practical procedure and model that clinicians can use to apply the results of well-conducted studies to patient care by critically appraising the evidence with checklists and letter grade scales. To demonstrate application of this model for critically appraising the quality of research evidence, a hypothetical case involving an adult male with chronic periodontitis is used as an example. To determine the best clinical approach for this patient, a four-step, evidence-based model is demonstrated, consisting of the following: definition of a research question using the PICO format, search and selection of relevant literature, critical appraisal of identified research reports using checklists, and the application of evidence. In this model, the quality of research evidence was assessed quantitatively based on different levels of quality that are assigned letter grades of A, B, and C by evaluating the studies against the QUOROM (Quality of Reporting Meta-Analyses) and CONSORT (Consolidated Standards of Reporting Trials) checklists in a tabular format. For this hypothetical periodontics case, application of the model identified the best available evidence for clinical decision making, i.e., one randomized controlled trial and one systematic review of randomized controlled trials. Both studies showed similar answers for the research question. The use of a letter grade scale allowed an objective analysis of the quality of evidence. A checklist-driven model that assesses and applies evidence to dental practice may substantially improve dentists' decision making skill.

Classifying clinical decision making: a unifying approach.

PubMed

Buckingham, C D; Adams, A

2000-10-01

This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.

Bayesian outcome-based strategy classification.

PubMed

Lee, Michael D

2016-03-01

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

Mapping Venus: Modeling the Magellan Mission.

ERIC Educational Resources Information Center

Richardson, Doug

1997-01-01

Provides details of an activity designed to help students understand the relationship between astronomy and geology. Applies concepts of space research and map-making technology to the construction of a topographic map of a simulated section of Venus. (DDR)

Latent Growth and Dynamic Structural Equation Models.

PubMed

Grimm, Kevin J; Ram, Nilam

2018-05-07

Latent growth models make up a class of methods to study within-person change-how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.

[Modeling in value-based medicine].

PubMed

Neubauer, A S; Hirneiss, C; Kampik, A

2010-03-01

Modeling plays an important role in value-based medicine (VBM). It allows decision support by predicting potential clinical and economic consequences, frequently combining different sources of evidence. Based on relevant publications and examples focusing on ophthalmology the key economic modeling methods are explained and definitions are given. The most frequently applied model types are decision trees, Markov models, and discrete event simulation (DES) models. Model validation includes besides verifying internal validity comparison with other models (external validity) and ideally validation of its predictive properties. The existing uncertainty with any modeling should be clearly stated. This is true for economic modeling in VBM as well as when using disease risk models to support clinical decisions. In economic modeling uni- and multivariate sensitivity analyses are usually applied; the key concepts here are tornado plots and cost-effectiveness acceptability curves. Given the existing uncertainty, modeling helps to make better informed decisions than without this additional information.

A spiral model of musical decision-making.

PubMed

Bangert, Daniel; Schubert, Emery; Fabian, Dorottya

2014-01-01

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

A spiral model of musical decision-making

PubMed Central

Bangert, Daniel; Schubert, Emery; Fabian, Dorottya

2014-01-01

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

Measurement of flying and diving metabolic rate in wild animals: Review and recommendations.

PubMed

Elliott, Kyle H

2016-12-01

Animals' abilities to fly long distances and dive to profound depths fascinate earthbound researchers. Due to the difficulty of making direct measurements during flying and diving, many researchers resort to modeling so as to estimate metabolic rate during each of those activities in the wild, but those models can be inaccurate. Fortunately, the miniaturization, customization and commercialization of biologgers has allowed researchers to increasingly follow animals on their journeys, unravel some of their mysteries and test the accuracy of biomechanical models. I provide a review of the measurement of flying and diving metabolic rate in the wild, paying particular attention to mass loss, doubly-labelled water, heart rate and accelerometry. Biologgers can impact animal behavior and influence the very measurements they are designed to make, and I provide seven guidelines for the ethical use of biologgers. If biologgers are properly applied, quantification of metabolic rate across a range of species could produce robust allometric relationships that could then be generally applied. As measuring flying and diving metabolic rate in captivity is difficult, and often not directly translatable to field conditions, I suggest that applying multiple techniques in the field to reinforce one another may be a viable alternative. The coupling of multi-sensor biologgers with biomechanical modeling promises to improve precision in the measurement of flying and diving metabolic rate in wild animals. Copyright © 2016 Elsevier Inc. All rights reserved.

Review: Groundwater flow and transport modeling of karst aquifers, with particular reference to the North Coast Limestone aquifer system of Puerto Rico

PubMed Central

Ghasemizadeh, Reza; Hellweger, Ferdinand; Butscher, Christoph; Padilla, Ingrid; Vesper, Dorothy; Field, Malcolm; Alshawabkeh, Akram

2013-01-01

Karst systems have a high degree of heterogeneity and anisotropy, which makes them behave very differently from other aquifers. Slow seepage through the rock matrix and fast flow through conduits and fractures result in a high variation in spring response to precipitation events. Contaminant storage occurs in the rock matrix and epikarst, but contaminant transport occurs mostly along preferential pathways that are typically inaccessible locations, which makes modeling of karst systems challenging. Computer models for understanding and predicting hydraulics and contaminant transport in aquifers make assumptions about the distribution and hydraulic properties of geologic features that may not always apply to karst aquifers. This paper reviews the basic concepts, mathematical descriptions, and modeling approaches for karst systems. The North Coast Limestone aquifer system of Puerto Rico (USA) is introduced as a case study to illustrate and discuss the application of groundwater models in karst aquifer systems to evaluate aquifer contamination. PMID:23645996

The application of the heuristic-systematic processing model to treatment decision making about prostate cancer.

PubMed

Steginga, Suzanne K; Occhipinti, Stefano

2004-01-01

The study investigated the utility of the Heuristic-Systematic Processing Model as a framework for the investigation of patient decision making. A total of 111 men recently diagnosed with localized prostate cancer were assessed using Verbal Protocol Analysis and self-report measures. Study variables included men's use of nonsystematic and systematic information processing, desire for involvement in decision making, and the individual differences of health locus of control, tolerance of ambiguity, and decision-related uncertainty. Most men (68%) preferred that decision making be shared equally between them and their doctor. Men's use of the expert opinion heuristic was related to men's verbal reports of decisional uncertainty and having a positive orientation to their doctor and medical care; a desire for greater involvement in decision making was predicted by a high internal locus of health control. Trends were observed for systematic information processing to increase when the heuristic strategy used was negatively affect laden and when men were uncertain about the probabilities for cure and side effects. There was a trend for decreased systematic processing when the expert opinion heuristic was used. Findings were consistent with the Heuristic-Systematic Processing Model and suggest that this model has utility for future research in applied decision making about health.

Of mental models, assumptions and heuristics: The case of acids and acid strength

NASA Astrophysics Data System (ADS)

McClary, Lakeisha Michelle

This study explored what cognitive resources (i.e., units of knowledge necessary to learn) first-semester organic chemistry students used to make decisions about acid strength and how those resources guided the prediction, explanation and justification of trends in acid strength. We were specifically interested in the identifying and characterizing the mental models, assumptions and heuristics that students relied upon to make their decisions, in most cases under time constraints. The views about acids and acid strength were investigated for twenty undergraduate students. Data sources for this study included written responses and individual interviews. The data was analyzed using a qualitative methodology to answer five research questions. Data analysis regarding these research questions was based on existing theoretical frameworks: problem representation (Chi, Feltovich & Glaser, 1981), mental models (Johnson-Laird, 1983); intuitive assumptions (Talanquer, 2006), and heuristics (Evans, 2008). These frameworks were combined to develop the framework from which our data were analyzed. Results indicated that first-semester organic chemistry students' use of cognitive resources was complex and dependent on their understanding of the behavior of acids. Expressed mental models were generated using prior knowledge and assumptions about acids and acid strength; these models were then employed to make decisions. Explicit and implicit features of the compounds in each task mediated participants' attention, which triggered the use of a very limited number of heuristics, or shortcut reasoning strategies. Many students, however, were able to apply more effortful analytic reasoning, though correct trends were predicted infrequently. Most students continued to use their mental models, assumptions and heuristics to explain a given trend in acid strength and to justify their predicted trends, but the tasks influenced a few students to shift from one model to another model. An emergent finding from this project was that the problem representation greatly influenced students' ability to make correct predictions in acid strength. Many students, however, were able to apply more effortful analytic reasoning, though correct trends were predicted infrequently. Most students continued to use their mental models, assumptions and heuristics to explain a given trend in acid strength and to justify their predicted trends, but the tasks influenced a few students to shift from one model to another model. An emergent finding from this project was that the problem representation greatly influenced students' ability to make correct predictions in acid strength.

Teaching critical thinking.

PubMed

Holmes, N G; Wieman, Carl E; Bonn, D A

2015-09-08

The ability to make decisions based on data, with its inherent uncertainties and variability, is a complex and vital skill in the modern world. The need for such quantitative critical thinking occurs in many different contexts, and although it is an important goal of education, that goal is seldom being achieved. We argue that the key element for developing this ability is repeated practice in making decisions based on data, with feedback on those decisions. We demonstrate a structure for providing suitable practice that can be applied in any instructional setting that involves the acquisition of data and relating that data to scientific models. This study reports the results of applying that structure in an introductory physics laboratory course. Students in an experimental condition were repeatedly instructed to make and act on quantitative comparisons between datasets, and between data and models, an approach that is common to all science disciplines. These instructions were slowly faded across the course. After the instructions had been removed, students in the experimental condition were 12 times more likely to spontaneously propose or make changes to improve their experimental methods than a control group, who performed traditional experimental activities. The students in the experimental condition were also four times more likely to identify and explain a limitation of a physical model using their data. Students in the experimental condition also showed much more sophisticated reasoning about their data. These differences between the groups were seen to persist into a subsequent course taken the following year.

Teaching critical thinking

PubMed Central

Holmes, N. G.; Wieman, Carl E.; Bonn, D. A.

2015-01-01

The ability to make decisions based on data, with its inherent uncertainties and variability, is a complex and vital skill in the modern world. The need for such quantitative critical thinking occurs in many different contexts, and although it is an important goal of education, that goal is seldom being achieved. We argue that the key element for developing this ability is repeated practice in making decisions based on data, with feedback on those decisions. We demonstrate a structure for providing suitable practice that can be applied in any instructional setting that involves the acquisition of data and relating that data to scientific models. This study reports the results of applying that structure in an introductory physics laboratory course. Students in an experimental condition were repeatedly instructed to make and act on quantitative comparisons between datasets, and between data and models, an approach that is common to all science disciplines. These instructions were slowly faded across the course. After the instructions had been removed, students in the experimental condition were 12 times more likely to spontaneously propose or make changes to improve their experimental methods than a control group, who performed traditional experimental activities. The students in the experimental condition were also four times more likely to identify and explain a limitation of a physical model using their data. Students in the experimental condition also showed much more sophisticated reasoning about their data. These differences between the groups were seen to persist into a subsequent course taken the following year. PMID:26283351

A two-dimensional model study of the QBO signal in SAGE II NO{sub 2} and O{sub 3}

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

Chipperfield, M.P.; Gray, L.J.; Kinnersley, J.S.

1994-04-01

The authors present a model study of the quasi biennial oscillation signal in observed nitrogen dioxide and ozone data collected between 1984 and 1991 by SAGE II. This 2D model is applied on a grid from pole to pole, from the ground to 80 km altitude. The QBO signal is forced into the model by making the equatorial winds in the model relax toward observations from Singapore.

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.

How to Make a Math Modeling Class from Scratch in Six (Not-So) Easy Steps

ERIC Educational Resources Information Center

Gerhardt, Ira

2017-01-01

The recent introduction of a new course in mathematical modeling at Manhattan College has provided students with a valuable opportunity to gain practical experience utilizing tools in applying their mathematical abilities to a real-world problem. This paper describes the steps taken to create this class, from obtaining a real-world partner…

Utilizing the Active and Collaborative Learning Model in the Introductory Physics Course

ERIC Educational Resources Information Center

Nam, Nguyen Hoai

2014-01-01

Model of active and collaborative learning (ACLM) applied in training specific subject makes clear advantage due to the goals of knowledge, skills that students got to develop successful future job. The author exploits the learning management system (LMS) of Hanoi National University of Education (HNUE) to establish a learning environment in the…

Applying Risk and Resilience Metrics to Energy Investments

DTIC Science & Technology

2015-12-01

the model as a positive aspect, though the user can easily devalue risk and resiliency while increasing the value of the cost and policy categories to... policy or position of the Department of Defense or the U.S. Government. IRB Protocol number ____N/A____. 12a. DISTRIBUTION / AVAILABILITY STATEMENT...decision making model. The model developed for this project includes cost metrics and policy mandates that the current model considers and adds the

The New AVA Statement of Professional Ethics in Volunteer Administration.

ERIC Educational Resources Information Center

Seel, Keith

1996-01-01

Core ethical values of the Association for Volunteer Administration are citizenship and philanthropy, respect, responsibility, caring, justice and fairness, and trustworthiness. An ethical decision-making model shows how to apply these standards to actual cases. (SK)

IT vendor selection model by using structural equation model & analytical hierarchy process

NASA Astrophysics Data System (ADS)

Maitra, Sarit; Dominic, P. D. D.

2012-11-01

Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

Shared Decision-Making in Youth Mental Health Care: Using the Evidence to Plan Treatments Collaboratively.

PubMed

Langer, David A; Jensen-Doss, Amanda

2016-12-02

The shared decision-making (SDM) model is one in which providers and consumers of health care come together as collaborators in determining the course of care. The model is especially relevant to youth mental health care, when planning a treatment frequently entails coordinating both youth and parent perspectives, preferences, and goals. The present article first provides the historical context of the SDM model and the rationale for increasing our field's use of SDM when planning psychosocial treatments for youth and families. Having established the potential utility of SDM, the article then discusses how to apply the SDM model to treatment planning for youth psychotherapy, proposing a set of steps consistent with the model and considerations when conducting SDM with youth and families.

Shared Decision-Making in Youth Mental Health Care: Using the Evidence to Plan Treatments Collaboratively

PubMed Central

Langer, David A.; Jensen-Doss, Amanda

2017-01-01

The shared decision-making (SDM) model is one in which providers and consumers of health care come together as collaborators in determining the course of care. The model is especially relevant to youth mental health care, when planning a treatment frequently entails coordinating both youth and parent perspectives, preferences, and goals. The present paper first provides the historical context of the SDM model and the rationale for increasing our field's use of SDM when planning psychosocial treatments for youth and families. Having established the potential utility of SDM, the paper then discusses how to apply the SDM model to treatment planning for youth psychotherapy, proposing a set of steps consistent with the model and considerations when conducting SDM with youth and families. PMID:27911081

The Selection of an Appropriate Count Data Model for Modelling Health Insurance and Health Care Demand: Case of Indonesia

PubMed Central

Hidayat, Budi; Pokhrel, Subhash

2010-01-01

We apply several estimators to Indonesian household data to estimate the relationship between health insurance and the number of outpatient visits to public and private providers. Once endogeneity of insurance is taken into account, there is a 63 percent increase in the average number of public visits by the beneficiaries of mandatory insurance for civil servants. Individuals’ decisions to make first contact with private providers is affected by private insurance membership. However, insurance status does not make any difference for the number of future outpatient visits. PMID:20195429

Conceptual compression for pattern recognition in 3D model output

NASA Astrophysics Data System (ADS)

Prudden, Rachel; Robinson, Niall; Arribas, Alberto

2017-04-01

The problem of data compression is closely related to the idea of comprehension. If you understand a scene at a qualitative level, this should enable you to make reasonable predictions about its contents, meaning that less extra information is needed to encode it precisely. These ideas have already been applied in the field of image compression; see for example the work on conceptual compression by Google DeepMind. Applying similar methods to multidimensional atmospheric data could have significant benefits. Beyond reducing storage demands, the ability to recognise complex features would make it far easier to interpret and search large volumes of meteorological data. Our poster will present some early work in this area.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

PubMed

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks.

A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

PubMed Central

Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

2017-01-01

Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks. PMID:28824512

Multiple R&D projects scheduling optimization with improved particle swarm algorithm.

PubMed

Liu, Mengqi; Shan, Miyuan; Wu, Juan

2014-01-01

For most enterprises, in order to win the initiative in the fierce competition of market, a key step is to improve their R&D ability to meet the various demands of customers more timely and less costly. This paper discusses the features of multiple R&D environments in large make-to-order enterprises under constrained human resource and budget, and puts forward a multi-project scheduling model during a certain period. Furthermore, we make some improvements to existed particle swarm algorithm and apply the one developed here to the resource-constrained multi-project scheduling model for a simulation experiment. Simultaneously, the feasibility of model and the validity of algorithm are proved in the experiment.

Microstructure and rheology of thermoreversible nanoparticle gels.

PubMed

Ramakrishnan, S; Zukoski, C F

2006-08-29

Naïve mode coupling theory is applied to particles interacting with short-range Yukawa attractions. Model results for the location of the gel line and the modulus of the resulting gels are reduced to algebraic equations capturing the effects of the range and strength of attraction. This model is then applied to thermo reversible gels composed of octadecyl silica particles suspended in decalin. The application of the model to the experimental system requires linking the experimental variable controlling strength of attraction, temperature, to the model strength of attraction. With this link, the model predicts temperature and volume fraction dependencies of gelation and modulus with five parameters: particle size, particle volume fraction, overlap volume of surface hairs, and theta temperature. In comparing model predictions with experimental results, we first observe that in these thermal gels there is no evidence of clustering as has been reported in depletion gels. One consequence of this observation is that there are no additional adjustable parameters required to make quantitative comparisons between experimental results and model predictions. Our results indicate that the naïve mode coupling approach taken here in conjunction with a model linking temperature to strength of attraction provides a robust approach for making quantitative predictions of gel mechanical properties. Extension of model predictions to additional experimental systems requires linking experimental variables to the Yukawa strength and range of attraction.

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

PubMed

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Power to the people: To what extent has public involvement in applied health research achieved this?

PubMed

Green, Gill

2016-01-01

Public involvement is required for applied health research funded in the UK. One of the largest funders, the National Institute of Health Research (NIHR), makes it clear that it values the knowledge of patients and the public. As a result, there are now many resources to make sure that the public voice is included in decision-making about research. However, there is concern that the public voice still has limited impact on research decision-making. This article asks to what extent has power shifted from the scientific research community to the public? It looks at how much power and impact patients and members of the public have about research by asking: How do the public contribute to deciding which research areas and which research projects should be funded? How do they influence how the research is carried out? The article argues that there is evidence that the public voice is present in research decision-making. However, there is less evidence of a change in the power dynamic between the scientific research community and the public. The public involved in research are not always equal partners. The scientific research community still has the loudest voice and patients and the public do not always feel sufficiently empowered to challenge it. Public involvement in applied health research is a pre-requisite for funding from many funding bodies. In particular the National Institute of Health Research (NIHR) in the UK, clearly states that it values lay knowledge and there is an expectation that members of the public will participate as research partners in research. As a result a large public involvement infrastructure has emerged to facilitate this. However, there is concern that despite the flurry of activity in promoting public involvement, lay knowledge is marginalised and has limited impact on research decision-making. This article asks to what extent has power shifted from the scientific research community to the public? It discusses the meaning of power and models of public involvement and examines the development of public involvement in applied health research. It identifies public involvement in a range of decision-making: identifying priority areas for commissioning research; making decisions about which projects are funded; decisions about details of research design. Whilst there is evidence that the public voice is present in the composition of research proposals submitted to NIHR and in the decision-making about which projects are funded and how they are carried out, there is less evidence of a change in the power dynamic manifest in social relations between the scientific research community and the public. As a result the biomedical model remains dominant and largely unchallenged in research decision-making.

Optimal experimental design in an epidermal growth factor receptor signalling and down-regulation model.

PubMed

Casey, F P; Baird, D; Feng, Q; Gutenkunst, R N; Waterfall, J J; Myers, C R; Brown, K S; Cerione, R A; Sethna, J P

2007-05-01

We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor signalling, trafficking and down-regulation. The model incorporates the role of a recently discovered protein complex made up of the E3 ubiquitin ligase, Cbl, the guanine exchange factor (GEF), Cool-1 (beta -Pix) and the Rho family G protein Cdc42. The complex has been suggested to be important in disrupting receptor down-regulation. We demonstrate that the model interactions can accurately reproduce the experimental observations, that they can be used to make predictions with accompanying uncertainties, and that we can apply ideas of optimal experimental design to suggest new experiments that reduce the uncertainty on unmeasurable components of the system.

An effective model for ergonomic optimization applied to a new automotive assembly line

NASA Astrophysics Data System (ADS)

Duraccio, Vincenzo; Elia, Valerio; Forcina, Antonio

2016-06-01

An efficient ergonomic optimization can lead to a significant improvement in production performance and a considerable reduction of costs. In the present paper new model for ergonomic optimization is proposed. The new approach is based on the criteria defined by National Institute of Occupational Safety and Health and, adapted to Italian legislation. The proposed model provides an ergonomic optimization, by analyzing ergonomic relations between manual work in correct conditions. The model includes a schematic and systematic analysis method of the operations, and identifies all possible ergonomic aspects to be evaluated. The proposed approach has been applied to an automotive assembly line, where the operation repeatability makes the optimization fundamental. The proposed application clearly demonstrates the effectiveness of the new approach.

Optimization of a middle atmosphere diagnostic scheme

NASA Astrophysics Data System (ADS)

Akmaev, Rashid A.

1997-06-01

A new assimilative diagnostic scheme based on the use of a spectral model was recently tested on the CIRA-86 empirical model. It reproduced the observed climatology with an annual global rms temperature deviation of 3.2 K in the 15-110 km layer. The most important new component of the scheme is that the zonal forcing necessary to maintain the observed climatology is diagnosed from empirical data and subsequently substituted into the simulation model at the prognostic stage of the calculation in an annual cycle mode. The simulation results are then quantitatively compared with the empirical model, and the above mentioned rms temperature deviation provides an objective measure of the `distance' between the two climatologies. This quantitative criterion makes it possible to apply standard optimization procedures to the whole diagnostic scheme and/or the model itself. The estimates of the zonal drag have been improved in this study by introducing a nudging (Newtonian-cooling) term into the thermodynamic equation at the diagnostic stage. A proper optimal adjustment of the strength of this term makes it possible to further reduce the rms temperature deviation of simulations down to approximately 2.7 K. These results suggest that direct optimization can successfully be applied to atmospheric model parameter identification problems of moderate dimensionality.

Modelling decremental ramps using 2- and 3-parameter "critical power" models.

PubMed

Morton, R Hugh; Billat, Veronique

2013-01-01

The "Critical Power" (CP) model of human bioenergetics provides a valuable way to identify both limits of tolerance to exercise and mechanisms that underpin that tolerance. It applies principally to cycling-based exercise, but with suitable adjustments for analogous units it can be applied to other exercise modalities; in particular to incremental ramp exercise. It has not yet been applied to decremental ramps which put heavy early demand on the anaerobic energy supply system. This paper details cycling-based bioenergetics of decremental ramps using 2- and 3-parameter CP models. It derives equations that, for an individual of known CP model parameters, define those combinations of starting intensity and decremental gradient which will or will not lead to exhaustion before ramping to zero; and equations that predict time to exhaustion on those decremental ramps that will. These are further detailed with suitably chosen numerical and graphical illustrations. These equations can be used for parameter estimation from collected data, or to make predictions when parameters are known.

Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

PubMed

Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V

2016-01-01

Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

Stress analysis and buckling of J-stiffened graphite-epoxy panel

NASA Technical Reports Server (NTRS)

Davis, R. C.

1980-01-01

A graphite epoxy shear panel with bonded on J stiffeners was investigated. The panel, loaded to buckling in a picture frame shear test is described. Two finite element models, each of which included the doubler material bonded to the panel skin under the stiffeners and at the panel edges, were used to make a stress analysis of the panel. The shear load distributions in the panel from two commonly used boundary conditions, applied shear load and applied displacement, were compared with the results from one of the finite element models that included the picture frame test fixture.

Examination of Moral Decision-Making Attitudes of Elite Male Basketball Players and Wrestlers According to Variables of Sport Experience and Mother, Father Education

ERIC Educational Resources Information Center

Arslan, Fethi; Ziyagil, Mehmet Akif; Bastik, Canan

2018-01-01

The purpose of this research was to examine the extent to which sport moral decision-making attitudes were applied by the athletes, and the factors that caused it. The research was based on the causal comparative research model. The research group consisted of a total of 475 athletes, of which 195 were basketball athletes randomly selected from…

Organizational Linkages: Understanding the Productivity Paradox,

DTIC Science & Technology

1994-01-01

students were asked to make a decision regarding a production scheduling. Some used a Lotus spreadsheet’s what-if capacity, which enabled them to...the degree to which managers and MBA students believed that they make better decisions using what-if spreadsheet models, despite the fact that their...for this system is Naylor et al.’s (1980) view of behavior in organizations. When Pritchard and his students (Pritchard et al., 1988) applied this

Comparing decision making between cancer patients and the general population: thoughts, emotions, or social influence?

PubMed

Yang, Z Janet; McComas, Katherine A; Gay, Geri K; Leonard, John P; Dannenberg, Andrew J; Dillon, Hildy

2012-01-01

This study extends a risk information seeking and processing model to explore the relative effect of cognitive processing strategies, positive and negative emotions, and normative beliefs on individuals' decision making about potential health risks. Most previous research based on this theoretical framework has examined environmental risks. Applying this risk communication model to study health decision making presents an opportunity to explore theoretical boundaries of the model, while also bringing this research to bear on a pressing medical issue: low enrollment in clinical trials. Comparative analysis of data gathered from 2 telephone surveys of a representative national sample (n = 500) and a random sample of cancer patients (n = 411) indicated that emotions played a more substantive role in cancer patients' decisions to enroll in a potential trial, whereas cognitive processing strategies and normative beliefs had greater influences on the decisions of respondents from the national sample.

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol.

PubMed

Freebairn, L; Atkinson, J; Kelly, P; McDonnell, G; Rychetnik, L

2016-09-21

Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making. The study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants' engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change. The study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings.

A simplified conjoint recognition paradigm for the measurement of gist and verbatim memory.

PubMed

Stahl, Christoph; Klauer, Karl Christoph

2008-05-01

The distinction between verbatim and gist memory traces has furthered the understanding of numerous phenomena in various fields, such as false memory research, research on reasoning and decision making, and cognitive development. To measure verbatim and gist memory empirically, an experimental paradigm and multinomial measurement model has been proposed but rarely applied. In the present article, a simplified conjoint recognition paradigm and multinomial model is introduced and validated as a measurement tool for the separate assessment of verbatim and gist memory processes. A Bayesian metacognitive framework is applied to validate guessing processes. Extensions of the model toward incorporating the processes of phantom recollection and erroneous recollection rejection are discussed.

A simple quantitative model of macromolecular crowding effects on protein folding: Application to the murine prion protein(121-231)

NASA Astrophysics Data System (ADS)

Bergasa-Caceres, Fernando; Rabitz, Herschel A.

2013-06-01

A model of protein folding kinetics is applied to study the effects of macromolecular crowding on protein folding rate and stability. Macromolecular crowding is found to promote a decrease of the entropic cost of folding of proteins that produces an increase of both the stability and the folding rate. The acceleration of the folding rate due to macromolecular crowding is shown to be a topology-dependent effect. The model is applied to the folding dynamics of the murine prion protein (121-231). The differential effect of macromolecular crowding as a function of protein topology suffices to make non-native configurations relatively more accessible.

Alternative projections of the impacts of private investment on southern forests: a comparison of two large-scale forest sector models of the United States.

Treesearch

Ralph Alig; Darius Adams; John Mills; Richard Haynes; Peter Ince; Robert Moulton

2001-01-01

The TAMM/NAPAP/ATLAS/AREACHANGE(TNAA) system and the Forest and Agriculture Sector Optimization Model (FASOM) are two large-scale forestry sector modeling systems that have been employed to analyze the U.S. forest resource situation. The TNAA system of static, spatial equilibrium models has been applied to make SO-year projections of the U.S. forest sector for more...

Tell Me about Fred's Fat Foot Again: Four Tips for Successful PA Lessons

ERIC Educational Resources Information Center

Murray, Bruce A.

2012-01-01

This teaching tip applies research on phoneme awareness (PA) to propose an instructional model for teaching PA. Research suggests children need to learn the identifying features of phonemes to recognize them in spoken words. In the model, teachers focus on one phoneme at a time; make it memorable to children through sound analogies supported by…

Developing the Next Generation of Responsible Professionals: Wisdom and Ethics Trump Knowledge and IQ

ERIC Educational Resources Information Center

Sternberg, Robert J.

2017-01-01

In this article, I describe the ACCEL (active concerned citizenship and ethical leadership) model for university education. I then apply it to the teaching of psychology. The goal of the model is to develop university students who are active concerned citizens and ethical leaders, where leaders are viewed as people who make a positive, meaningful,…

Of Models and Mechanisms: Towards an Understanding of How Theatre-Making Works as an "Intervention" in Individual Health and Wellness

ERIC Educational Resources Information Center

Etheridge Woodson, Stephani; Szkupinski Quiroga, Seline; Underiner, Tamara; Farid Karimi, Robert

2017-01-01

Growing from a multi-year and multidisciplinary research and applied arts investigative team based in North America, this essay presents a model of how performative engagements contribute to individual behavioural change in wellness practices. To be even more specific, this essay analyses and theorises the mechanisms involved in the application of…

Integrated Flood Forecast and Virtual Dam Operation System for Water Resources and Flood Risk Management

NASA Astrophysics Data System (ADS)

Shibuo, Yoshihiro; Ikoma, Eiji; Lawford, Peter; Oyanagi, Misa; Kanauchi, Shizu; Koudelova, Petra; Kitsuregawa, Masaru; Koike, Toshio

2014-05-01

While availability of hydrological- and hydrometeorological data shows growing tendency and advanced modeling techniques are emerging, such newly available data and advanced models may not always be applied in the field of decision-making. In this study we present an integrated system of ensemble streamflow forecast (ESP) and virtual dam simulator, which is designed to support river and dam manager's decision making. The system consists of three main functions: real time hydrological model, ESP model, and dam simulator model. In the real time model, the system simulates current condition of river basins, such as soil moisture and river discharges, using LSM coupled distributed hydrological model. The ESP model takes initial condition from the real time model's output and generates ESP, based on numerical weather prediction. The dam simulator model provides virtual dam operation and users can experience impact of dam control on remaining reservoir volume and downstream flood under the anticipated flood forecast. Thus the river and dam managers shall be able to evaluate benefit of priori dam release and flood risk reduction at the same time, on real time basis. Furthermore the system has been developed under the concept of data and models integration, and it is coupled with Data Integration and Analysis System (DIAS) - a Japanese national project for integrating and analyzing massive amount of observational and model data. Therefore it has advantage in direct use of miscellaneous data from point/radar-derived observation, numerical weather prediction output, to satellite imagery stored in data archive. Output of the system is accessible over the web interface, making information available with relative ease, e.g. from ordinary PC to mobile devices. We have been applying the system to the Upper Tone region, located northwest from Tokyo metropolitan area, and we show application example of the system in recent flood events caused by typhoons.

Value judgements in the decision-making process for the elderly patient.

PubMed

Ubachs-Moust, J; Houtepen, R; Vos, R; ter Meulen, R

2008-12-01

The question of whether old age should or should not play a role in medical decision-making for the elderly patient is regularly debated in ethics and medicine. In this paper we investigate exactly how age influences the decision-making process. To explore the normative argumentation in the decisions regarding an elderly patient we make use of the argumentation model advanced by Toulmin. By expanding the model in order to identify normative components in the argumentation process it is possible to analyse the way that age-related value judgements influence the medical decision-making process. We apply the model to practice descriptions made by medical students after they had attended consultations and meetings in medical practice during their clinical training. Our results show the pervasive character of age-related value judgements. They influence the physician's decision in several ways and at several points in the decision-making process. Such explicit value judgements were not exclusively used for arguments against further diagnosis or treatment of older patients. We found no systematic "ageist" pattern in the clinical decisions by physicians. Since age plays such an important, yet hidden role in the medical decision-making process, we make a plea for revealing such normative argumentation in order to gain transparency and accountability in this process. An explicit deliberative approach will make the medical decision-making process more transparent and improve the physician-patient relationship, creating confidence and trust, which are at the heart of medical practice.

Strategies for Teaching Regional Climate Modeling: Online Professional Development for Scientists and Decision Makers

NASA Astrophysics Data System (ADS)

Walton, P.; Yarker, M. B.; Mesquita, M. D. S.; Otto, F. E. L.

2014-12-01

There is a clear role for climate science in supporting decision making at a range of scales and in a range of contexts: from Global to local, from Policy to Industry. However, clear a role climate science can play, there is also a clear discrepancy in the understanding of how to use the science and associated tools (such as climate models). Despite there being a large body of literature on the science there is clearly a need to provide greater support in how to apply appropriately. However, access to high quality professional development courses can be problematic, due to geographic, financial and time constraints. In attempt to address this gap we independently developed two online professional courses that focused on helping participants use and apply two regional climate models, WRF and PRECIS. Both courses were designed to support participants' learning through tutor led programs that covered the basic climate scientific principles of regional climate modeling and how to apply model outputs. The fundamental differences between the two courses are: 1) the WRF modeling course expected participants to design their own research question that was then run on a version of the model, whereas 2) the PRECIS course concentrated on the principles of regional modeling and how the climate science informed the modeling process. The two courses were developed to utilise the cost and time management benefits associated with eLearning, with the recognition that this mode of teaching can also be accessed internationally, providing professional development courses in countries that may not be able to provide their own. The development teams saw it as critical that the courses reflected sound educational theory, to ensure that participants had the maximum opportunity to learn successfully. In particular, the role of reflection is central to both course structures to help participants make sense of the science in relation to their own situation. This paper details the different structures of both courses, evaluating the advantages and disadvantages of each, along with the educational approaches used. We conclude by proposing a framework for the develop of educationally robust online professional development programs that actively supports decision makers in understanding, developing and applying regional climate models.

Global canopy interception from satellite observations

USDA-ARS?s Scientific Manuscript database

A new methodology for retrieving rainfall interception rates from multi satellite observations is presented. The approach makes use of the daily productof the Global Precipitation Climatology Project (GPCP) as driving data and applies Gash’s analytical model to derive interception rates at global sc...

Determinants of Dentists' Geographic Distribution.

ERIC Educational Resources Information Center

Beazoglou, Tryfon J.; And Others

1992-01-01

A model for explaining the geographic distribution of dentists' practice locations is presented and applied to particular market areas in Connecticut. Results show geographic distribution is significantly related to a few key variables, including demography, disposable income, and housing prices. Implications for helping students make practice…

Evaluating the impact of grade crossing safety factors through signal detection theory

DOT National Transportation Integrated Search

2012-10-22

The purpose of this effort was to apply signal detection theory to descriptively model the impact : of five grade crossing safety factors to understand their effect on driver decision making. The : safety factors consisted of: improving commercial mo...

Application of Multi-Criteria Decision Making (MCDM) Technique for Gradation of Jute Fibres

NASA Astrophysics Data System (ADS)

Choudhuri, P. K.

2014-12-01

Multi-Criteria Decision Making is a branch of Operation Research (OR) having a comparatively short history of about 40 years. It is being popularly used in the field of engineering, banking, fixing policy matters etc. It can also be applied for taking decisions in daily life like selecting a car to purchase, selecting bride or groom and many others. Various MCDM methods namely Weighted Sum Model (WSM), Weighted Product Model (WPM), Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) and Elimination and Choice Translating Reality (ELECTRE) are there to solve many decision making problems, each having its own limitations. However it is very difficult to decide which MCDM method is the best. MCDM methods are prospective quantitative approaches for solving decision problems involving finite number of alternatives and criteria. Very few research works in textiles have been carried out with the help of this technique particularly where decision taking among several alternatives becomes the major problem based on some criteria which are conflicting in nature. Gradation of jute fibres on the basis of the criteria like strength, root content, defects, colour, density, fineness etc. is an important task to perform. The MCDM technique provides enough scope to be applied for the gradation of jute fibres or ranking among several varieties keeping in view a particular object and on the basis of some selection criteria and their relative weightage. The present paper is an attempt to explore the scope of applying the multiplicative AHP method of multi-criteria decision making technique to determine the quality values of selected jute fibres on the basis of some above stated important criteria and ranking them accordingly. A good agreement in ranking is observed between the existing Bureau of Indian Standards (BIS) grading and proposed method.

Applying a family systems lens to proxy decision making in clinical practice and research.

PubMed

Rolland, John S; Emanuel, Linda L; Torke, Alexia M

2017-03-01

When patients are incapacitated and face serious illness, family members must make medical decisions for the patient. Medical decision sciences give only modest attention to the relationships among patients and their family members, including impact that these relationships have on the decision-making process. A review of the literature reveals little effort to systematically apply a theoretical framework to the role of family interactions in proxy decision making. A family systems perspective can provide a useful lens through which to understand the dynamics of proxy decision making. This article considers the mutual impact of family systems on the processes and outcomes of proxy decision making. The article first reviews medical decision science's evolution and focus on proxy decision making and then reviews a family systems approach, giving particular attention to Rolland's Family Systems Illness Model. A case illustrates how clinical practice and how research would benefit from bringing family systems thinking to proxy decisions. We recommend including a family systems approach in medical decision science research and clinical practices around proxy decisions making. We propose that clinical decisions could be less conflicted and less emotionally troubling for families and clinicians if family systems approaches were included. This perspective opens new directions for research and novel approaches to clinical care. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Vibration suppression in flexible structures via the sliding-mode control approach

NASA Technical Reports Server (NTRS)

Drakunov, S.; Oezguener, Uemit

1994-01-01

Sliding mode control became very popular recently because it makes the closed loop system highly insensitive to external disturbances and parameter variations. Sliding algorithms for flexible structures have been used previously, but these were based on finite-dimensional models. An extension of this approach for differential-difference systems is obtained. That makes if possible to apply sliding-mode control algorithms to the variety of nondispersive flexible structures which can be described as differential-difference systems. The main idea of using this technique for dispersive structures is to reduce the order of the controlled part of the system by applying an integral transformation. We can say that transformation 'absorbs' the dispersive properties of the flexible structure as the controlled part becomes dispersive.

Software Reliability 2002

NASA Technical Reports Server (NTRS)

Wallace, Dolores R.

2003-01-01

In FY01 we learned that hardware reliability models need substantial changes to account for differences in software, thus making software reliability measurements more effective, accurate, and easier to apply. These reliability models are generally based on familiar distributions or parametric methods. An obvious question is 'What new statistical and probability models can be developed using non-parametric and distribution-free methods instead of the traditional parametric method?" Two approaches to software reliability engineering appear somewhat promising. The first study, begin in FY01, is based in hardware reliability, a very well established science that has many aspects that can be applied to software. This research effort has investigated mathematical aspects of hardware reliability and has identified those applicable to software. Currently the research effort is applying and testing these approaches to software reliability measurement, These parametric models require much project data that may be difficult to apply and interpret. Projects at GSFC are often complex in both technology and schedules. Assessing and estimating reliability of the final system is extremely difficult when various subsystems are tested and completed long before others. Parametric and distribution free techniques may offer a new and accurate way of modeling failure time and other project data to provide earlier and more accurate estimates of system reliability.

Applying Risk Prediction Models to Optimize Lung Cancer Screening: Current Knowledge, Challenges, and Future Directions.

PubMed

Sakoda, Lori C; Henderson, Louise M; Caverly, Tanner J; Wernli, Karen J; Katki, Hormuzd A

2017-12-01

Risk prediction models may be useful for facilitating effective and high-quality decision-making at critical steps in the lung cancer screening process. This review provides a current overview of published lung cancer risk prediction models and their applications to lung cancer screening and highlights both challenges and strategies for improving their predictive performance and use in clinical practice. Since the 2011 publication of the National Lung Screening Trial results, numerous prediction models have been proposed to estimate the probability of developing or dying from lung cancer or the probability that a pulmonary nodule is malignant. Respective models appear to exhibit high discriminatory accuracy in identifying individuals at highest risk of lung cancer or differentiating malignant from benign pulmonary nodules. However, validation and critical comparison of the performance of these models in independent populations are limited. Little is also known about the extent to which risk prediction models are being applied in clinical practice and influencing decision-making processes and outcomes related to lung cancer screening. Current evidence is insufficient to determine which lung cancer risk prediction models are most clinically useful and how to best implement their use to optimize screening effectiveness and quality. To address these knowledge gaps, future research should be directed toward validating and enhancing existing risk prediction models for lung cancer and evaluating the application of model-based risk calculators and its corresponding impact on screening processes and outcomes.

On Roles of Models in Information Systems

NASA Astrophysics Data System (ADS)

Sølvberg, Arne

The increasing penetration of computers into all aspects of human activity makes it desirable that the interplay among software, data and the domains where computers are applied is made more transparent. An approach to this end is to explicitly relate the modeling concepts of the domains, e.g., natural science, technology and business, to the modeling concepts of software and data. This may make it simpler to build comprehensible integrated models of the interactions between computers and non-computers, e.g., interaction among computers, people, physical processes, biological processes, and administrative processes. This chapter contains an analysis of various facets of the modeling environment for information systems engineering. The lack of satisfactory conceptual modeling tools seems to be central to the unsatisfactory state-of-the-art in establishing information systems. The chapter contains a proposal for defining a concept of information that is relevant to information systems engineering.

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

NASA Astrophysics Data System (ADS)

Kou, Meng; Lu, Na

2018-01-01

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

The mechanisms of feature inheritance as predicted by a systems-level model of visual attention and decision making.

PubMed

Hamker, Fred H

2008-07-15

Feature inheritance provides evidence that properties of an invisible target stimulus can be attached to a following mask. We apply a systemslevel model of attention and decision making to explore the influence of memory and feedback connections in feature inheritance. We find that the presence of feedback loops alone is sufficient to account for feature inheritance. Although our simulations do not cover all experimental variations and focus only on the general principle, our result appears of specific interest since the model was designed for a completely different purpose than to explain feature inheritance. We suggest that feedback is an important property in visual perception and provide a description of its mechanism and its role in perception.

An effective model for ergonomic optimization applied to a new automotive assembly line

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

Duraccio, Vincenzo; Elia, Valerio; Forcina, Antonio

2016-06-08

An efficient ergonomic optimization can lead to a significant improvement in production performance and a considerable reduction of costs. In the present paper new model for ergonomic optimization is proposed. The new approach is based on the criteria defined by National Institute of Occupational Safety and Health and, adapted to Italian legislation. The proposed model provides an ergonomic optimization, by analyzing ergonomic relations between manual work in correct conditions. The model includes a schematic and systematic analysis method of the operations, and identifies all possible ergonomic aspects to be evaluated. The proposed approach has been applied to an automotive assemblymore » line, where the operation repeatability makes the optimization fundamental. The proposed application clearly demonstrates the effectiveness of the new approach.« less

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

NASA Technical Reports Server (NTRS)

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

1978-01-01

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

Quasar microlensing models with constraints on the Quasar light curves

NASA Astrophysics Data System (ADS)

Tie, S. S.; Kochanek, C. S.

2018-01-01

Quasar microlensing analyses implicitly generate a model of the variability of the source quasar. The implied source variability may be unrealistic yet its likelihood is generally not evaluated. We used the damped random walk (DRW) model for quasar variability to evaluate the likelihood of the source variability and applied the revized algorithm to a microlensing analysis of the lensed quasar RX J1131-1231. We compared estimates of the size of the quasar disc and the average stellar mass of the lens galaxy with and without applying the DRW likelihoods for the source variability model and found no significant effect on the estimated physical parameters. The most likely explanation is that unreliastic source light-curve models are generally associated with poor microlensing fits that already make a negligible contribution to the probability distributions of the derived parameters.

Matrix population models from 20 studies of perennial plant populations

USGS Publications Warehouse

Ellis, Martha M.; Williams, Jennifer L.; Lesica, Peter; Bell, Timothy J.; Bierzychudek, Paulette; Bowles, Marlin; Crone, Elizabeth E.; Doak, Daniel F.; Ehrlen, Johan; Ellis-Adam, Albertine; McEachern, Kathryn; Ganesan, Rengaian; Latham, Penelope; Luijten, Sheila; Kaye, Thomas N.; Knight, Tiffany M.; Menges, Eric S.; Morris, William F.; den Nijs, Hans; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F.; Shelly, J. Stephen; Stanley, Amanda; Thorpe, Andrea; Tamara, Ticktin; Valverde, Teresa; Weekley, Carl W.

2012-01-01

Demographic transition matrices are one of the most commonly applied population models for both basic and applied ecological research. The relatively simple framework of these models and simple, easily interpretable summary statistics they produce have prompted the wide use of these models across an exceptionally broad range of taxa. Here, we provide annual transition matrices and observed stage structures/population sizes for 20 perennial plant species which have been the focal species for long-term demographic monitoring. These data were assembled as part of the "Testing Matrix Models" working group through the National Center for Ecological Analysis and Synthesis (NCEAS). In sum, these data represent 82 populations with >460 total population-years of data. It is our hope that making these data available will help promote and improve our ability to monitor and understand plant population dynamics.

Matrix population models from 20 studies of perennial plant populations

USGS Publications Warehouse

Ellis, Martha M.; Williams, Jennifer L.; Lesica, Peter; Bell, Timothy J.; Bierzychudek, Paulette; Bowles, Marlin; Crone, Elizabeth E.; Doak, Daniel F.; Ehrlen, Johan; Ellis-Adam, Albertine; McEachern, Kathryn; Ganesan, Rengaian; Latham, Penelope; Luijten, Sheila; Kaye, Thomas N.; Knight, Tiffany M.; Menges, Eric S.; Morris, William F.; den Nijs, Hans; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F.; Shelly, J. Stephen; Stanley, Amanda; Thorpe, Andrea; Tamara, Ticktin; Valverde, Teresa; Weekley, Carl W.

2012-01-01

Demographic transition matrices are one of the most commonly applied population models for both basic and applied ecological research. The relatively simple framework of these models and simple, easily interpretable summary statistics they produce have prompted the wide use of these models across an exceptionally broad range of taxa. Here, we provide annual transition matrices and observed stage structures/population sizes for 20 perennial plant species which have been the focal species for long-term demographic monitoring. These data were assembled as part of the 'Testing Matrix Models' working group through the National Center for Ecological Analysis and Synthesis (NCEAS). In sum, these data represent 82 populations with >460 total population-years of data. It is our hope that making these data available will help promote and improve our ability to monitor and understand plant population dynamics.

Science to Improve Nutrient Management Practices, Metrics of Benefits, Accountability, and Communication (Project SSWR 4.03)

EPA Science Inventory

This project will demonstrate transferable modeling techniques and monitoring approaches to enable water resource professionals to make comparisons among nutrient reduction management scenarios across urban and agricultural areas. It will produce the applied science to allow bett...

Applying analysis tools in planning for operations : case study #4 -- application of microsimulation in combination with travel demand models

DOT National Transportation Integrated Search

2009-09-01

More and more, transportation system operators are seeing the benefits of strengthening links between planning and operations. A critical element in improving transportation decision-making and the effectiveness of transportation systems related to o...

Developing and Applying Synthesis Models of Emerging Space Systems

DTIC Science & Technology

2016-03-01

enables the exploration of small satellite physical trade -offs early in the conceptual design phase of the DOD space acquisition process. Early...provide trade space insights that can assist DOD space acquisition professionals in making better decisions in the conceptual design phase. More informed

Data-based hybrid tension estimation and fault diagnosis of cold rolling continuous annealing processes.

PubMed

Liu, Qiang; Chai, Tianyou; Wang, Hong; Qin, Si-Zhao Joe

2011-12-01

The continuous annealing process line (CAPL) of cold rolling is an important unit to improve the mechanical properties of steel strips in steel making. In continuous annealing processes, strip tension is an important factor, which indicates whether the line operates steadily. Abnormal tension profile distribution along the production line can lead to strip break and roll slippage. Therefore, it is essential to estimate the whole tension profile in order to prevent the occurrence of faults. However, in real annealing processes, only a limited number of strip tension sensors are installed along the machine direction. Since the effects of strip temperature, gas flow, bearing friction, strip inertia, and roll eccentricity can lead to nonlinear tension dynamics, it is difficult to apply the first-principles induced model to estimate the tension profile distribution. In this paper, a novel data-based hybrid tension estimation and fault diagnosis method is proposed to estimate the unmeasured tension between two neighboring rolls. The main model is established by an observer-based method using a limited number of measured tensions, speeds, and currents of each roll, where the tension error compensation model is designed by applying neural networks principal component regression. The corresponding tension fault diagnosis method is designed using the estimated tensions. Finally, the proposed tension estimation and fault diagnosis method was applied to a real CAPL in a steel-making company, demonstrating the effectiveness of the proposed method.

History matching through dynamic decision-making

PubMed Central

Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson

2017-01-01

History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413

A Comparative Study of the Effects of a Developmentally Based Instructional Model on Young Children with Autism and Young Children with Other Disorders of Behavior and Development.

ERIC Educational Resources Information Center

Rogers, Sally J.; DiLalla, David L.

1991-01-01

This study, which applied an instructional model based on Piaget's theory of cognitive development, pragmatics theory of language development, and Mahler's theory of development of interpersonal relationships, found that 49 preschool children with autism did not make less progress than a comparison group of 27 children with other…

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

None

An OpenStudio Measure is a script that can manipulate an OpenStudio model and associated data to apply energy conservation measures (ECMs), run supplemental simulations, or visualize simulation results. The OpenStudio software development kit (SDK) and accessibility of the Ruby scripting language makes measure authorship accessible to both software developers and energy modelers. This paper discusses the life cycle of an OpenStudio Measure from development, testing, and distribution, to application.

Decision-case mix model for analyzing variation in cesarean rates.

PubMed

Eldenburg, L; Waller, W S

2001-01-01

This article contributes a decision-case mix model for analyzing variation in c-section rates. Like recent contributions to the literature, the model systematically takes into account the effect of case mix. Going beyond past research, the model highlights differences in physician decision making in response to obstetric factors. Distinguishing the effects of physician decision making and case mix is important in understanding why c-section rates vary and in developing programs to effect change in physician behavior. The model was applied to a sample of deliveries at a hospital where physicians exhibited considerable variation in their c-section rates. Comparing groups with a low versus high rate, the authors' general conclusion is that the difference in physician decision tendencies (to perform a c-section), in response to specific obstetric factors, is at least as important as case mix in explaining variation in c-section rates. The exact effects of decision making versus case mix depend on how the model application defines the obstetric condition of interest and on the weighting of deliveries by their estimated "risk of Cesarean." The general conclusion is supported by an additional analysis that uses the model's elements to predict individual physicians' annual c-section rates.

Bayesian inversion of marine CSEM data from the Scarborough gas field using a transdimensional 2-D parametrization

NASA Astrophysics Data System (ADS)

Ray, Anandaroop; Key, Kerry; Bodin, Thomas; Myer, David; Constable, Steven

2014-12-01

We apply a reversible-jump Markov chain Monte Carlo method to sample the Bayesian posterior model probability density function of 2-D seafloor resistivity as constrained by marine controlled source electromagnetic data. This density function of earth models conveys information on which parts of the model space are illuminated by the data. Whereas conventional gradient-based inversion approaches require subjective regularization choices to stabilize this highly non-linear and non-unique inverse problem and provide only a single solution with no model uncertainty information, the method we use entirely avoids model regularization. The result of our approach is an ensemble of models that can be visualized and queried to provide meaningful information about the sensitivity of the data to the subsurface, and the level of resolution of model parameters. We represent models in 2-D using a Voronoi cell parametrization. To make the 2-D problem practical, we use a source-receiver common midpoint approximation with 1-D forward modelling. Our algorithm is transdimensional and self-parametrizing where the number of resistivity cells within a 2-D depth section is variable, as are their positions and geometries. Two synthetic studies demonstrate the algorithm's use in the appraisal of a thin, segmented, resistive reservoir which makes for a challenging exploration target. As a demonstration example, we apply our method to survey data collected over the Scarborough gas field on the Northwest Australian shelf.

The environmental management problem of Pohorje, Slovenia: A new group approach within ANP - SWOT framework.

PubMed

Grošelj, Petra; Zadnik Stirn, Lidija

2015-09-15

Environmental management problems can be dealt with by combining participatory methods, which make it possible to include various stakeholders in a decision-making process, and multi-criteria methods, which offer a formal model for structuring and solving a problem. This paper proposes a three-phase decision making approach based on the analytic network process and SWOT (strengths, weaknesses, opportunities and threats) analysis. The approach enables inclusion of various stakeholders or groups of stakeholders in particular stages of decision making. The structure of the proposed approach is composed of a network consisting of an objective cluster, a cluster of strategic goals, a cluster of SWOT factors and a cluster of alternatives. The application of the suggested approach is applied to a management problem of Pohorje, a mountainous area in Slovenia. Stakeholders from sectors that are important for Pohorje (forestry, agriculture, tourism and nature protection agencies) who can offer a wide range of expert knowledge were included in the decision-making process. The results identify the alternative of "sustainable development" as the most appropriate for development of Pohorje. The application in the paper offers an example of employing the new approach to an environmental management problem. This can also be applied to decision-making problems in various other fields. Copyright © 2015 Elsevier Ltd. All rights reserved.

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

NASA Astrophysics Data System (ADS)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

NASA Technical Reports Server (NTRS)

Lin, Qian; Allebach, Jan P.

1990-01-01

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

Deep generative learning for automated EHR diagnosis of traditional Chinese medicine.

PubMed

Liang, Zhaohui; Liu, Jun; Ou, Aihua; Zhang, Honglai; Li, Ziping; Huang, Jimmy Xiangji

2018-05-04

Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the decision procedure of healthcare activities. Well-developed information infrastructure, such as hospital information systems and disease surveillance systems, provides abundant data for CAMDM. However, the complexity of EMR data with abstract medical knowledge makes the conventional model incompetent for the analysis. Thus a deep belief networks (DBN) based model is proposed to simulate the information analysis and decision-making procedure in medical practice. The purpose of this paper is to evaluate a deep learning architecture as an effective solution for CAMDM. A two-step model is applied in our study. At the first step, an optimized seven-layer deep belief network (DBN) is applied as an unsupervised learning algorithm to perform model training to acquire feature representation. Then a support vector machine model is adopted to DBN at the second step of the supervised learning. There are two data sets used in the experiments. One is a plain text data set indexed by medical experts. The other is a structured dataset on primary hypertension. The data are randomly divided to generate the training set for the unsupervised learning and the testing set for the supervised learning. The model performance is evaluated by the statistics of mean and variance, the average precision and coverage on the data sets. Two conventional shallow models (support vector machine / SVM and decision tree / DT) are applied as the comparisons to show the superiority of our proposed approach. The deep learning (DBN + SVM) model outperforms simple SVM and DT on two data sets in terms of all the evaluation measures, which confirms our motivation that the deep model is good at capturing the key features with less dependence when the index is built up by manpower. Our study shows the two-step deep learning model achieves high performance for medical information retrieval over the conventional shallow models. It is able to capture the features of both plain text and the highly-structured database of EMR data. The performance of the deep model is superior to the conventional shallow learning models such as SVM and DT. It is an appropriate knowledge-learning model for information retrieval of EMR system. Therefore, deep learning provides a good solution to improve the performance of CAMDM systems. Copyright © 2018. Published by Elsevier B.V.

Development of an Optimal Water Allocation Decision Tool for the Major Crops During the Water Deficit Period in the Southeast U.S.

NASA Technical Reports Server (NTRS)

Paudel, Krishna P.; Limaye, Ashutosh; Hatch, Upton; Cruise, James; Musleh, Fuad

2005-01-01

We developed a dynamic model to optimize irrigation application in three major crops (corn, cotton and peanuts) grown in the Southeast USA. Water supply amount is generated from an engineering model which is then combined with economic models to find the optimal amount of irrigation water to apply on each crop field during the six critical water deficit weeks in summer. Results indicate that water is applied on the crop with the highest marginal value product of irrigation. Decision making tool such as the one developed here would help farmers and policy makers to find the maximum profitable solution when water shortage is a serious concern.

End-of-life decision making is more than rational.

PubMed

Eliott, Jaklin A; Olver, Ian N

2005-01-01

Most medical models of end-of-life decision making by patients assume a rational autonomous adult obtaining and deliberating over information to arrive at some conclusion. If the patient is deemed incapable of this, family members are often nominated as substitutes, with assumptions that the family are united and rational. These are problematic assumptions. We interviewed 23 outpatients with cancer about the decision not to resuscitate a patient following cardiopulmonary arrest and examined their accounts of decision making using discourse analytical techniques. Our analysis suggests that participants access two different interpretative repertoires regarding the construct of persons, invoking a 'modernist' repertoire to assert the appropriateness of someone, a patient or family, making a decision, and a 'romanticist' repertoire when identifying either a patient or family as ineligible to make the decision. In determining the appropriateness of an individual to make decisions, participants informally apply 'Sanity' and 'Stability' tests, assessing both an inherent ability to reason (modernist repertoire) and the presence of emotion (romanticist repertoire) which might impact on the decision making process. Failure to pass the tests respectively excludes or excuses individuals from decision making. The absence of the romanticist repertoire in dominant models of patient decision making has ethical implications for policy makers and medical practitioners dealing with dying patients and their families.

Comparative analysis of used car price evaluation models

NASA Astrophysics Data System (ADS)

Chen, Chuancan; Hao, Lulu; Xu, Cong

2017-05-01

An accurate used car price evaluation is a catalyst for the healthy development of used car market. Data mining has been applied to predict used car price in several articles. However, little is studied on the comparison of using different algorithms in used car price estimation. This paper collects more than 100,000 used car dealing records throughout China to do empirical analysis on a thorough comparison of two algorithms: linear regression and random forest. These two algorithms are used to predict used car price in three different models: model for a certain car make, model for a certain car series and universal model. Results show that random forest has a stable but not ideal effect in price evaluation model for a certain car make, but it shows great advantage in the universal model compared with linear regression. This indicates that random forest is an optimal algorithm when handling complex models with a large number of variables and samples, yet it shows no obvious advantage when coping with simple models with less variables.

Prehospital Trauma Triage Decision-making: A Model of What Happens between the 9-1-1 Call and the Hospital.

PubMed

Jones, Courtney Marie Cora; Cushman, Jeremy T; Lerner, E Brooke; Fisher, Susan G; Seplaki, Christopher L; Veazie, Peter J; Wasserman, Erin B; Dozier, Ann; Shah, Manish N

2016-01-01

We describe the decision-making process used by emergency medical services (EMS) providers in order to understand how 1) injured patients are evaluated in the prehospital setting; 2) field triage criteria are applied in-practice; and 3) selection of a destination hospital is determined. We conducted separate focus groups with advanced and basic life support providers from rural and urban/suburban regions. Four exploratory focus groups were conducted to identify overarching themes and five additional confirmatory focus groups were conducted to verify initial focus group findings and provide additional detail regarding trauma triage decision-making and application of field triage criteria. All focus groups were conducted by a public health researcher with formal training in qualitative research. A standardized question guide was used to facilitate discussion at all focus groups. All focus groups were audio-recorded and transcribed. Responses were coded and categorized into larger domains to describe how EMS providers approach trauma triage and apply the Field Triage Decision Scheme. We conducted 9 focus groups with 50 EMS providers. Participants highlighted that trauma triage is complex and there is often limited time to make destination decisions. Four overarching domains were identified within the context of trauma triage decision-making: 1) initial assessment; 2) importance of speed versus accuracy; 3) usability of current field triage criteria; and 4) consideration of patient and emergency care system-level factors. Field triage is a complex decision-making process which involves consideration of many patient and system-level factors. The decision model presented in this study suggests that EMS providers place significant emphasis on speed of decisions, relying on initial impressions and immediately observable information, rather than precise measurement of vital signs or systematic application of field triage criteria.

Being reflexive in qualitative grounded theory: discussion and application of a model of reflexivity.

PubMed

Engward, Hilary; Davis, Geraldine

2015-07-01

A discussion of the meaning of reflexivity in research with the presentation of examples of how a model of reflexivity was used in a grounded theory research project. Reflexivity requires the researcher to make transparent the decisions they make in the research process and is therefore important in developing quality in nursing research. The importance of being reflexive is highlighted in the literature in relation to nursing research, however, practical guidance as to how to go about doing research reflexively is not always clearly articulated. This is a discussion paper. The concept of reflexivity in research is explored using the Alvesson and Skoldberg model of reflexivity and practical examples of how a researcher developed reflexivity in a grounded theory project are presented. Nurse researchers are encouraged to explore and apply the concept of reflexivity in their research practices to develop transparency in the research process and to increase robustness in their research. The Alvesson and Skoldberg model is of value in applying reflexivity in qualitative nursing research, particularly in grounded theory research. Being reflexive requires the researcher to be completely open about decisions that are made in the research process. The Alvesson and Skolberg model of reflexivity is a useful model that can enhance reflexivity in the research process. It can be a useful practical tool to develop reflexivity in grounded theory research. © 2015 John Wiley & Sons Ltd.

Empirical and Face Validity of Software Maintenance Defect Models Used at the Jet Propulsion Laboratory

NASA Technical Reports Server (NTRS)

Taber, William; Port, Dan

2014-01-01

At the Mission Design and Navigation Software Group at the Jet Propulsion Laboratory we make use of finite exponential based defect models to aid in maintenance planning and management for our widely used critical systems. However a number of pragmatic issues arise when applying defect models for a post-release system in continuous use. These include: how to utilize information from problem reports rather than testing to drive defect discovery and removal effort, practical model calibration, and alignment of model assumptions with our environment.

Modeling and Simulation of U-tube Steam Generator

NASA Astrophysics Data System (ADS)

Zhang, Mingming; Fu, Zhongguang; Li, Jinyao; Wang, Mingfei

2018-03-01

The U-tube natural circulation steam generator was mainly researched with modeling and simulation in this article. The research is based on simuworks system simulation software platform. By analyzing the structural characteristics and the operating principle of U-tube steam generator, there are 14 control volumes in the model, including primary side, secondary side, down channel and steam plenum, etc. The model depends completely on conservation laws, and it is applied to make some simulation tests. The results show that the model is capable of simulating properly the dynamic response of U-tube steam generator.

A Threshold Model of Content Knowledge Transfer for Socioscientific Argumentation

ERIC Educational Resources Information Center

Sadler, Troy D.; Fowler, Samantha R.

2006-01-01

This study explores how individuals make use of scientific content knowledge for socioscientific argumentation. More specifically, this mixed-methods study investigates how learners apply genetics content knowledge as they justify claims relative to genetic engineering. Interviews are conducted with 45 participants, representing three distinct…

ECOSYSTEM SERVICES AND BEYOND: INTEGRATION OF ECOSYSTEM SCIENCE AND MULTIMEDIA EXPOSURE MODELING FOR ENVIRONMENTAL PROTECTION

EPA Science Inventory

Decision-making for ecosystem protection and resource management requires an integrative science and technology applied with a sufficiently comprehensive systems approach. Single media (e.g., air, soil and water) approaches that evaluate aspects of an ecosystem in a stressor-by-...

14 CFR 49.43 - Eligibility for recording: general requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Identified Aircraft Engines and Propellers § 49.43 Eligibility for recording: general requirements. A..., 49.13, and 49.17, the following requirements are met: (a) It affects and describes an aircraft engine or propeller to which this subpart applies, specifically identified by make, model, horsepower, and...

14 CFR 49.43 - Eligibility for recording: general requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Identified Aircraft Engines and Propellers § 49.43 Eligibility for recording: general requirements. A..., 49.13, and 49.17, the following requirements are met: (a) It affects and describes an aircraft engine or propeller to which this subpart applies, specifically identified by make, model, horsepower, and...

14 CFR 49.43 - Eligibility for recording: general requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Identified Aircraft Engines and Propellers § 49.43 Eligibility for recording: general requirements. A..., 49.13, and 49.17, the following requirements are met: (a) It affects and describes an aircraft engine or propeller to which this subpart applies, specifically identified by make, model, horsepower, and...

14 CFR 49.43 - Eligibility for recording: general requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Identified Aircraft Engines and Propellers § 49.43 Eligibility for recording: general requirements. A..., 49.13, and 49.17, the following requirements are met: (a) It affects and describes an aircraft engine or propeller to which this subpart applies, specifically identified by make, model, horsepower, and...

14 CFR 49.43 - Eligibility for recording: general requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Identified Aircraft Engines and Propellers § 49.43 Eligibility for recording: general requirements. A..., 49.13, and 49.17, the following requirements are met: (a) It affects and describes an aircraft engine or propeller to which this subpart applies, specifically identified by make, model, horsepower, and...

Adaptive automation of human-machine system information-processing functions.

PubMed

Kaber, David B; Wright, Melanie C; Prinzel, Lawrence J; Clamann, Michael P

2005-01-01

The goal of this research was to describe the ability of human operators to interact with adaptive automation (AA) applied to various stages of complex systems information processing, defined in a model of human-automation interaction. Forty participants operated a simulation of an air traffic control task. Automated assistance was adaptively applied to information acquisition, information analysis, decision making, and action implementation aspects of the task based on operator workload states, which were measured using a secondary task. The differential effects of the forms of automation were determined and compared with a manual control condition. Results of two 20-min trials of AA or manual control revealed a significant effect of the type of automation on performance, particularly during manual control periods as part of the adaptive conditions. Humans appear to better adapt to AA applied to sensory and psychomotor information-processing functions (action implementation) than to AA applied to cognitive functions (information analysis and decision making), and AA is superior to completely manual control. Potential applications of this research include the design of automation to support air traffic controller information processing.

Measurements in Quantum Mechanics and von NEUMANN's Model

NASA Astrophysics Data System (ADS)

Mello, Pier A.; Johansen, Lars M.

2010-12-01

Many textbooks on Quantum Mechanics are not very precise as to the meaning of making a measurement: as a consequence, they frequently make assertions which are not based on a dynamical description of the measurement process. A model proposed by von Neumann allows a dynamical description of measurement in Quantum Mechanics, including the measuring instrument in the formalism. In this article we apply von Neumann's model to illustrate the measurement of an observable by means of a measuring instrument and show how various results, which are sometimens postulated without a dynamical basis, actually emerge. We also investigate the more complex, intriguing and fundamental problem of two successive measurements in Quantum Mechanics, extending von Neumann's model to two measuring instruments. We present a description which allows obtaining, in a unified way, various results that have been given in the literature.

Zero-sum politics, the Herbert thesis, and the Ryan White CARE Act: lessons learned from the local side of AIDS.

PubMed

Slack, J

2001-01-01

This study examines the dynamics of grass-roots decision-making processes involved in the implementation of the Ryan White CARE Act. Providing social services to persons with HIV/AIDS, the CARE act requires participation of all relevant groups, including representatives of the HIV/AIDS and gay communities. Decision-making behavior is explored by applying a political (zero-sum) model and a bureaucratic (the Herbert Thesis) model. Using qualitative research techniques, the Kern County (California) Consortium is used as a case study. Findings shed light on the decision-making behavior of social service organizations characterized by intense advocacy and structured on the basis of volunteerism and non-hierarchical relationships. Findings affirm bureaucratic behavior predicted by the Herbert Thesis and also discern factors which seem to trigger more conflictual zero-sum behavior.

Dual processing model of medical decision-making.

PubMed

Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

2012-09-03

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

Time series modelling of global mean temperature for managerial decision-making.

PubMed

Romilly, Peter

2005-07-01

Climate change has important implications for business and economic activity. Effective management of climate change impacts will depend on the availability of accurate and cost-effective forecasts. This paper uses univariate time series techniques to model the properties of a global mean temperature dataset in order to develop a parsimonious forecasting model for managerial decision-making over the short-term horizon. Although the model is estimated on global temperature data, the methodology could also be applied to temperature data at more localised levels. The statistical techniques include seasonal and non-seasonal unit root testing with and without structural breaks, as well as ARIMA and GARCH modelling. A forecasting evaluation shows that the chosen model performs well against rival models. The estimation results confirm the findings of a number of previous studies, namely that global mean temperatures increased significantly throughout the 20th century. The use of GARCH modelling also shows the presence of volatility clustering in the temperature data, and a positive association between volatility and global mean temperature.

Markov Decision Process Measurement Model.

PubMed

LaMar, Michelle M

2018-03-01

Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.

Representing Heterogeneity in Structural Relationships Among Multiple Choice Variables Using a Latent Segmentation Approach

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

Garikapati, Venu; Astroza, Sebastian; Pendyala, Ram M.

Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to depict relationships among activity-travel choices in travel demand model systems ignores the possibility that some choices are made jointly as a bundle as well as the possible presence of structural heterogeneity in the population with respect to decision-making processes. As different segments in the population may adopt and follow different causalmore » decision-making mechanisms when making selected choices jointly, it would be of value to develop simultaneous equations model systems relating multiple endogenous choice variables that are able to identify population subgroups following alternative causal decision structures. Because the segments are not known a priori, they are considered latent and determined endogenously within a joint modeling framework proposed in this paper. The methodology is applied to a national mobility survey data set to identify population segments that follow different causal structures relating residential location choice, vehicle ownership, and car-share and mobility service usage. It is found that the model revealing three distinct latent segments best describes the data, confirming the efficacy of the modeling approach and the existence of structural heterogeneity in decision-making in the population. Future versions of activity-travel model systems should strive to incorporate such structural heterogeneity to better reflect varying decision processes across population subgroups.« less

Decision-making in healthcare: a practical application of partial least square path modelling to coverage of newborn screening programmes.

PubMed

Fischer, Katharina E

2012-08-02

Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare. Empirical approaches that applied PLS-PM to decision-making in healthcare were identified through a systematic literature search. PLS-PM was used as an estimation technique for a structural equation model that specified hypotheses between the components of decision processes and the reasonableness of decision-making in terms of medical, economic and other ethical criteria. The model was estimated for a sample of 55 coverage decisions on the extension of newborn screening programmes in Europe. Results were evaluated by standard reliability and validity measures for PLS-PM. After modification by dropping two indicators that showed poor measures in the measurement models' quality assessment and were not meaningful for newborn screening, the structural equation model estimation produced plausible results. The presence of three influences was supported: the links between both stakeholder participation or transparency and the reasonableness of decision-making; and the effect of transparency on the degree of scientific rigour of assessment. Reliable and valid measurement models were obtained to describe the composites of 'transparency', 'participation', 'scientific rigour' and 'reasonableness'. The structural equation model was among the first applications of PLS-PM to coverage decision-making. It allowed testing of hypotheses in situations where there are links between several non-observable constructs. PLS-PM was compatible in accounting for the complexity of coverage decisions to obtain a more realistic perspective for empirical analysis. The model specification can be used for hypothesis testing by using larger sample sizes and for data in the full domain of health technologies.

The impact of stakeholder involvement in hospital policy decision-making: a study of the hospital's business processes.

PubMed

Malfait, Simon; Van Hecke, Ann; Hellings, Johan; De Bodt, Griet; Eeckloo, Kristof

2017-02-01

In many health care systems, strategies are currently deployed to engage patients and other stakeholders in decisions affecting hospital services. In this paper, a model for stakeholder involvement is presented and evaluated in three Flemish hospitals. In the model, a stakeholder committee advises the hospital's board of directors on themes of strategic importance. To study the internal hospital's decision processes in order to identify the impact of a stakeholder involvement committee on strategic themes in the hospital decision processes. A retrospective analysis of the decision processes was conducted in three hospitals that implemented a stakeholder committee. The analysis consisted of process and outcome evaluation. Fifteen themes were discussed in the stakeholder committees, whereof 11 resulted in a considerable change. None of these were on a strategic level. The theoretical model was not applied as initially developed, but was altered by each hospital. Consequentially, the decision processes differed between the hospitals. Despite alternation of the model, the stakeholder committee showed a meaningful impact in all hospitals on the operational level. As a result of the differences in decision processes, three factors could be identified as facilitators for success: (1) a close interaction with the board of executives, (2) the inclusion of themes with a more practical and patient-oriented nature, and (3) the elaboration of decisions on lower echelons of the organization. To effectively influence the organization's public accountability, hospitals should involve stakeholders in the decision-making process of the organization. The model of a stakeholder committee was not applied as initially developed and did not affect the strategic decision-making processes in the involved hospitals. Results show only impact at the operational level in the participating hospitals. More research is needed connecting stakeholder involvement with hospital governance.

An Empirical Study of the Application of Decision Making Model Using Judgement in the Allocation of Resources to Competing Educational Programs. Final Report.

ERIC Educational Resources Information Center

Tuscher, Leroy J.

The purpose of the study was to provide "baseline" data for determining the feasibility of further investigation into the use of quantitive judgmental data in evaluating school programs for determining program budget allocations. The specific objectives were to: 1) Apply a Cost-Utility Model to a "real world" situation in a public secondary…

Reply to comment by Jonathan J. Rhodes on "Modeling of the interactions between forest vegetation, disturbances, and sediment yields"

Treesearch

Charles H. Luce; David G. Tarboton; Erkan Istanbulluoglu; Robert T. Pack

2005-01-01

Rhodes [2005] brings up some excellent points in his comments on the work of Istanbulluoglu et al. [2004]. We appreciate the opportunity to respond because it is likely that other readers will also wonder how they can apply the relatively simple analysis to important policy questions. Models necessarily reduce the complexity of the problem to make it tractable and...

A new method for qualitative simulation of water resources systems: 1. Theory

NASA Astrophysics Data System (ADS)

Camara, A. S.; Pinheiro, M.; Antunes, M. P.; Seixas, M. J.

1987-11-01

A new dynamic modeling methodology, SLIN (Simulação Linguistica), allowing for the analysis of systems defined by linguistic variables, is presented. SLIN applies a set of logical rules avoiding fuzzy theoretic concepts. To make the transition from qualitative to quantitative modes, logical rules are used as well. Extensions of the methodology to simulation-optimization applications and multiexpert system modeling are also discussed.

Professional responsibility and decision-making in the context of a disease-focused model of nursing care: The difficulties experienced by Spanish nurses.

PubMed

Rodrigo, Olga; Caïs, Jordi; Monforte-Royo, Cristina

2017-10-01

When, in 1977, nurse education in Spain was transferred to universities a more patient-centred, the Anglo-American philosophy of care was introduced into a context in which nurses had traditionally prioritised their technical skills. This paper examines the characteristics of the nurse's professional role in Spain, where the model of nursing practice has historically placed them in a position akin to that of physician assistants. The study design was qualitative and used the method of analytic induction. Participants were selected by means of theoretical sampling and then underwent in-depth interviews. The resulting material was analysed using an approach based on the principles of grounded theory. Strategies were applied to ensure the credibility, transferability, dependability and confirmability of the findings. The main conclusion is that nurses in Spain continue to work within a disease-focused model of care, making it difficult for them to take responsibility for decision-making. © 2017 John Wiley & Sons Ltd.

Modelling and Simulating Electronics Knowledge: Conceptual Understanding and Learning through Active Agency

ERIC Educational Resources Information Center

Twissell, Adrian

2018-01-01

Abstract electronics concepts are difficult to develop because the phenomena of interest cannot be readily observed. Visualisation skills support learning about electronics and can be applied at different levels of representation and understanding (observable, symbolic and abstract). Providing learners with opportunities to make transitions…

Professional Development of Officers Study. Volume 3 - Systems Wide Issues

DTIC Science & Technology

1985-02-21

Ivancevich , and Donnelly. 1979: tegrate the elements of the command, create con- Gannon. 1977; Schroder, Driver, and Streufert, ditions that make them work...of Leaders Using Fiedler’s Contin- Brown and Company, 1977. gency Model". Journal of Applied Psychology, Gibson, James L., Ivancevich , John M. and Don

Using LabVIEW for Applying Mathematical Models in Representing Phenomena

ERIC Educational Resources Information Center

Faraco, G.; Gabriele, L.

2007-01-01

Simulations make it possible to explore physical and biological phenomena, where conducting the real experiment is impracticable or difficult. The implementation of a software program describing and simulating a given physical situation encourages the understanding of a phenomenon itself. Fifty-nine students, enrolled at the Mathematical Methods…

Integrating effects based monitoring with adverse outcome pathways and population models

EPA Science Inventory

In addressing Beneficial Use Impairments (BUIs) at a Great Lakes Area of Concern (AOC), recovery from loss of fish and wildlife populations exposed to stressors is targeted for use in decision making. We describe a framework that can be applied in utilizing field monitoring effo...

Lewin's Impact on Education: Instilling Cooperation and Conflict Management Skills in School Children.

ERIC Educational Resources Information Center

Maruyama, Geoffrey

1992-01-01

A Lewinian orientation to educational problems fits current innovative thinking in education (e.g., models for making education multicultural), and provides the bases of important applied work on cooperative learning techniques and constructive ways of structuring conflict within educational settings. Lewinian field theory provides a broad…

A Systems Approach to Creativity Based on Jungian Typology.

ERIC Educational Resources Information Center

Krippner, Stanley

1983-01-01

Two dimensions of Carl Jung's psychological system (preference for information and choice of decision making processes) are applied to creativity research. Examples of four personality types (sensing- thinking, sensing-feeling, intuition-feeling, and intuition-thinking) are represented by prominent social scientists. A systems model of science is…

76 FR 13072 - Airworthiness Directives; Saab AB, Saab Aerosystems Model SAAB 2000 Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-10

... important to the structural integrity of the horizontal stabilizer. Corrosion damage in these areas, if not... structural integrity of the horizontal stabilizer. Corrosion damage in these areas, if not detected and... convoluted tubing on the harness, applying corrosion prevention compound to the inspected area, making sure...

75 FR 77796 - Airworthiness Directives; Saab AB, Saab Aerosystems Model SAAB 2000 Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-14

... of the horizontal stabilizer. Corrosion damage in these areas, if not detected and corrected, can... of the horizontal stabilizer. Corrosion damage in these areas, if not detected and corrected, can... convoluted tubing on the harness, applying corrosion prevention compound to the inspected area, making sure...

Project-Based Learning in International Financial Management

ERIC Educational Resources Information Center

Young, John H.; Legister, Allison P.

2018-01-01

This exploratory study measures the effectiveness of the signature project-based learning model to assess the enhancement of student engagement. The goal of the signature project is to prepare students to apply critical thinking and collaborative skills; making connections between global financial issues and textbook concepts in application to a…

A Digital Ecosystems Model of Assessment Feedback on Student Learning

ERIC Educational Resources Information Center

Gomez, Stephen; Andersson, Holger; Park, Julian; Maw, Stephen; Crook, Anne; Orsmond, Paul

2013-01-01

The term ecosystem has been used to describe complex interactions between living organisms and the physical world. The principles underlying ecosystems can also be applied to complex human interactions in the digital world. As internet technologies make an increasing contribution to teaching and learning practice in higher education, the…

Modeling virtual organizations with Latent Dirichlet Allocation: a case for natural language processing.

PubMed

Gross, Alexander; Murthy, Dhiraj

2014-10-01

This paper explores a variety of methods for applying the Latent Dirichlet Allocation (LDA) automated topic modeling algorithm to the modeling of the structure and behavior of virtual organizations found within modern social media and social networking environments. As the field of Big Data reveals, an increase in the scale of social data available presents new challenges which are not tackled by merely scaling up hardware and software. Rather, they necessitate new methods and, indeed, new areas of expertise. Natural language processing provides one such method. This paper applies LDA to the study of scientific virtual organizations whose members employ social technologies. Because of the vast data footprint in these virtual platforms, we found that natural language processing was needed to 'unlock' and render visible latent, previously unseen conversational connections across large textual corpora (spanning profiles, discussion threads, forums, and other social media incarnations). We introduce variants of LDA and ultimately make the argument that natural language processing is a critical interdisciplinary methodology to make better sense of social 'Big Data' and we were able to successfully model nested discussion topics from forums and blog posts using LDA. Importantly, we found that LDA can move us beyond the state-of-the-art in conventional Social Network Analysis techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bayesian statistics in medicine: a 25 year review.

PubMed

Ashby, Deborah

2006-11-15

This review examines the state of Bayesian thinking as Statistics in Medicine was launched in 1982, reflecting particularly on its applicability and uses in medical research. It then looks at each subsequent five-year epoch, with a focus on papers appearing in Statistics in Medicine, putting these in the context of major developments in Bayesian thinking and computation with reference to important books, landmark meetings and seminal papers. It charts the growth of Bayesian statistics as it is applied to medicine and makes predictions for the future. From sparse beginnings, where Bayesian statistics was barely mentioned, Bayesian statistics has now permeated all the major areas of medical statistics, including clinical trials, epidemiology, meta-analyses and evidence synthesis, spatial modelling, longitudinal modelling, survival modelling, molecular genetics and decision-making in respect of new technologies.

Capability of GPGPU for Faster Thermal Analysis Used in Data Assimilation

NASA Astrophysics Data System (ADS)

Takaki, Ryoji; Akita, Takeshi; Shima, Eiji

A thermal mathematical model plays an important role in operations on orbit as well as spacecraft thermal designs. The thermal mathematical model has some uncertain thermal characteristic parameters, such as thermal contact resistances between components, effective emittances of multilayer insulation (MLI) blankets, discouraging make up efficiency and accuracy of the model. A particle filter which is one of successive data assimilation methods has been applied to construct spacecraft thermal mathematical models. This method conducts a lot of ensemble computations, which require large computational power. Recently, General Purpose computing in Graphics Processing Unit (GPGPU) has been attracted attention in high performance computing. Therefore GPGPU is applied to increase the computational speed of thermal analysis used in the particle filter. This paper shows the speed-up results by using GPGPU as well as the application method of GPGPU.

Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model

PubMed Central

Dou, Fei; Jia, Limin; Wang, Li; Xu, Jie; Huang, Yakun

2014-01-01

Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning. Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors. In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved. An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM. For this applied case, the proposed model performs better than the k-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models. PMID:25431586

An application of the transtheoretical model to becoming vegan.

PubMed

Mendes, Elisabeth

2013-01-01

This article applies the transtheoretical model TM to veganism. By and large, the TM is a model of behavioral change that incorporates different stages to describe how an individual moves from an unhealthy behavior to a healthy one. The TM construes change as a five-stage process. The five stages of change are (a) precontemplation, (b) contemplation, (c) preparation, (d) action, and (e) maintenance. In this analysis, the model is applied to a person's determination to become vegan. A person chooses to become a vegan by eliminating all animal products from his or her diets; he or she does this by progressing through the stages, as prescribed by the model. The different changes people make to their life are described in detail. It is also possible to measure the success of a person's progression based on positive health changes that he or she experiences.

Highway traffic estimation of improved precision using the derivative-free nonlinear Kalman Filter

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Zervos, Nikolaos; Melkikh, Alexey

2015-12-01

The paper proves that the PDE dynamic model of the highway traffic is a differentially flat one and by applying spatial discretization its shows that the model's transformation into an equivalent linear canonical state-space form is possible. For the latter representation of the traffic's dynamics, state estimation is performed with the use of the Derivative-free nonlinear Kalman Filter. The proposed filter consists of the Kalman Filter recursion applied on the transformed state-space model of the highway traffic. Moreover, it makes use of an inverse transformation, based again on differential flatness theory which enables to obtain estimates of the state variables of the initial nonlinear PDE model. By avoiding approximate linearizations and the truncation of nonlinear terms from the PDE model of the traffic's dynamics the proposed filtering methods outperforms, in terms of accuracy, other nonlinear estimators such as the Extended Kalman Filter. The article's theoretical findings are confirmed through simulation experiments.

Translational Models of Gambling-Related Decision-Making.

PubMed

Winstanley, Catharine A; Clark, Luke

Gambling is a harmless, recreational pastime that is ubiquitous across cultures. However, for some, gambling becomes a maladaptive and compulsive, and this syndrome is conceptualized as a behavioural addiction. Laboratory models that capture the key cognitive processes involved in gambling behaviour, and that can be translated across species, have the potential to make an important contribution to both decision neuroscience and the study of addictive disorders. The Iowa gambling task has been widely used to assess human decision-making under uncertainty, and this paradigm can be successfully modelled in rodents. Similar neurobiological processes underpin choice behaviour in humans and rats, and thus, a preference for the disadvantageous "high-risk, high-reward" options may reflect meaningful vulnerability for mental health problems. However, the choice behaviour operationalized by these tasks does not necessarily approximate the vulnerability to gambling disorder (GD) per se. We consider a number of psychological challenges that apply to modelling gambling in a translational way, and evaluate the success of the existing models. Heterogeneity in the structure of gambling games, as well as in the motivations of individuals with GD, is highlighted. The potential issues with extrapolating too directly from established animal models of drug dependency are discussed, as are the inherent difficulties in validating animal models of GD in the absence of any approved treatments for GD. Further advances in modelling the cognitive biases endemic in human decision-making, which appear to be exacerbated in GD, may be a promising line of research.

A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

NASA Astrophysics Data System (ADS)

Bascetin, A.

2007-04-01

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.

A system dynamics optimization framework to achieve population desired of average weight target

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Zulkepli, Jafri Haji; Zaibidi, Nerda Zura

2017-11-01

Obesity is becoming a serious problem in Malaysia as it has been rated as the highest among Asian countries. The aim of the paper is to propose a system dynamics (SD) optimization framework to achieve population desired weight target based on the changes in physical activity behavior and its association to weight and obesity. The system dynamics approach of stocks and flows diagram was used to quantitatively model the impact of both behavior on the population's weight and obesity trends. This work seems to bring this idea together and highlighting the interdependence of the various aspects of eating and physical activity behavior on the complex of human weight regulation system. The model was used as an experimentation vehicle to investigate the impacts of changes in physical activity on weight and prevalence of obesity implications. This framework paper provides evidence on the usefulness of SD optimization as a strategic decision making approach to assist in decision making related to obesity prevention. SD applied in this research is relatively new in Malaysia and has a high potential to apply to any feedback models that address the behavior cause to obesity.

Naturalistic Decision Making for Power System Operators

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

Greitzer, Frank L.; Podmore, Robin; Robinson, Marck

2010-02-01

Motivation – Investigations of large-scale outages in the North American interconnected electric system often attribute the causes to three T’s: Trees, Training and Tools. To document and understand the mental processes used by expert operators when making critical decisions, a naturalistic decision making (NDM) model was developed. Transcripts of conversations were analyzed to reveal and assess NDM-based performance criteria. Findings/Design – An item analysis indicated that the operators’ Situation Awareness Levels, mental models, and mental simulations can be mapped at different points in the training scenario. This may identify improved training methods or analytical/ visualization tools. Originality/Value – This studymore » applies for the first time, the concepts of Recognition Primed Decision Making, Situation Awareness Levels and Cognitive Task Analysis to training of electric power system operators. Take away message – The NDM approach provides a viable framework for systematic training management to accelerate learning in simulator-based training scenarios for power system operators and teams.« less

Using structured decision making to manage disease risk for Montana wildlife

USGS Publications Warehouse

Mitchell, Michael S.; Gude, Justin A.; Anderson, Neil J.; Ramsey, Jennifer M.; Thompson, Michael J.; Sullivan, Mark G.; Edwards, Victoria L.; Gower, Claire N.; Cochrane, Jean Fitts; Irwin, Elise R.; Walshe, Terry

2013-01-01

We used structured decision-making to develop a 2-part framework to assist managers in the proactive management of disease outbreaks in Montana, USA. The first part of the framework is a model to estimate the probability of disease outbreak given field observations available to managers. The second part of the framework is decision analysis that evaluates likely outcomes of management alternatives based on the estimated probability of disease outbreak, and applies managers' values for different objectives to indicate a preferred management strategy. We used pneumonia in bighorn sheep (Ovis canadensis) as a case study for our approach, applying it to 2 populations in Montana that differed in their likelihood of a pneumonia outbreak. The framework provided credible predictions of both probability of disease outbreaks, as well as biological and monetary consequences of management actions. The structured decision-making approach to this problem was valuable for defining the challenges of disease management in a decentralized agency where decisions are generally made at the local level in cooperation with stakeholders. Our approach provides local managers with the ability to tailor management planning for disease outbreaks to local conditions. Further work is needed to refine our disease risk models and decision analysis, including robust prediction of disease outbreaks and improved assessment of management alternatives.

Prostate Cancer Probability Prediction By Machine Learning Technique.

PubMed

Jović, Srđan; Miljković, Milica; Ivanović, Miljan; Šaranović, Milena; Arsić, Milena

2017-11-26

The main goal of the study was to explore possibility of prostate cancer prediction by machine learning techniques. In order to improve the survival probability of the prostate cancer patients it is essential to make suitable prediction models of the prostate cancer. If one make relevant prediction of the prostate cancer it is easy to create suitable treatment based on the prediction results. Machine learning techniques are the most common techniques for the creation of the predictive models. Therefore in this study several machine techniques were applied and compared. The obtained results were analyzed and discussed. It was concluded that the machine learning techniques could be used for the relevant prediction of prostate cancer.

Making see and treat work for patients and staff.

PubMed

Parker, Louise

2004-02-01

Every department is at a different stage in the development of see and treat. Teams have been established in various ways and are experiencing different dilemmas in making see and treat work best. It is not enough to pick up an established see and treat model, place it in an emergency department and sit back and watch the results. There is no 'magic wand'; no single determining factor to make see and treat work well. Influencing factors need to be understood, applied locally and reviewed regularly to assess success. The NHS Modernisation Agency publishes its survey report, See and Treat: Making it work for patients and staff, on February 4. For Further details, access www.modern.nhs.uk/emergency

A Practical Philosophy of Complex Climate Modelling

NASA Technical Reports Server (NTRS)

Schmidt, Gavin A.; Sherwood, Steven

2014-01-01

We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

New Techniques for Deep Learning with Geospatial Data using TensorFlow, Earth Engine, and Google Cloud Platform

NASA Astrophysics Data System (ADS)

Hancher, M.

2017-12-01

Recent years have seen promising results from many research teams applying deep learning techniques to geospatial data processing. In that same timeframe, TensorFlow has emerged as the most popular framework for deep learning in general, and Google has assembled petabytes of Earth observation data from a wide variety of sources and made them available in analysis-ready form in the cloud through Google Earth Engine. Nevertheless, developing and applying deep learning to geospatial data at scale has been somewhat cumbersome to date. We present a new set of tools and techniques that simplify this process. Our approach combines the strengths of several underlying tools: TensorFlow for its expressive deep learning framework; Earth Engine for data management, preprocessing, postprocessing, and visualization; and other tools in Google Cloud Platform to train TensorFlow models at scale, perform additional custom parallel data processing, and drive the entire process from a single familiar Python development environment. These tools can be used to easily apply standard deep neural networks, convolutional neural networks, and other custom model architectures to a variety of geospatial data structures. We discuss our experiences applying these and related tools to a range of machine learning problems, including classic problems like cloud detection, building detection, land cover classification, as well as more novel problems like illegal fishing detection. Our improved tools will make it easier for geospatial data scientists to apply modern deep learning techniques to their own problems, and will also make it easier for machine learning researchers to advance the state of the art of those techniques.

Ocean Tide Loading Computation

NASA Technical Reports Server (NTRS)

Agnew, Duncan Carr

2005-01-01

September 15,2003 through May 15,2005 This grant funds the maintenance, updating, and distribution of programs for computing ocean tide loading, to enable the corrections for such loading to be more widely applied in space- geodetic and gravity measurements. These programs, developed under funding from the CDP and DOSE programs, incorporate the most recent global tidal models developed from Topex/Poscidon data, and also local tide models for regions around North America; the design of the algorithm and software makes it straightforward to combine local and global models.

A Model for Assessing the Liability of Seemingly Correct Software

NASA Technical Reports Server (NTRS)

Voas, Jeffrey M.; Voas, Larry K.; Miller, Keith W.

1991-01-01

Current research on software reliability does not lend itself to quantitatively assessing the risk posed by a piece of life-critical software. Black-box software reliability models are too general and make too many assumptions to be applied confidently to assessing the risk of life-critical software. We present a model for assessing the risk caused by a piece of software; this model combines software testing results and Hamlet's probable correctness model. We show how this model can assess software risk for those who insure against a loss that can occur if life-critical software fails.

An algebraic cluster model based on the harmonic oscillator basis

NASA Technical Reports Server (NTRS)

Levai, Geza; Cseh, J.

1995-01-01

We discuss the semimicroscopic algebraic cluster model introduced recently, in which the internal structure of the nuclear clusters is described by the harmonic oscillator shell model, while their relative motion is accounted for by the Vibron model. The algebraic formulation of the model makes extensive use of techniques associated with harmonic oscillators and their symmetry group, SU(3). The model is applied to some cluster systems and is found to reproduce important characteristics of nuclei in the sd-shell region. An approximate SU(3) dynamical symmetry is also found to hold for the C-12 + C-12 system.

Analysis and Modeling of Ground Operations at Hub Airports

NASA Technical Reports Server (NTRS)

Atkins, Stephen (Technical Monitor); Andersson, Kari; Carr, Francis; Feron, Eric; Hall, William D.

2000-01-01

Building simple and accurate models of hub airports can considerably help one understand airport dynamics, and may provide quantitative estimates of operational airport improvements. In this paper, three models are proposed to capture the dynamics of busy hub airport operations. Two simple queuing models are introduced to capture the taxi-out and taxi-in processes. An integer programming model aimed at representing airline decision-making attempts to capture the dynamics of the aircraft turnaround process. These models can be applied for predictive purposes. They may also be used to evaluate control strategies for improving overall airport efficiency.

Developing and Transitioning Numerical Air Quality Models to Improve Air Quality and Public Health Decision-Making in El Salvador and Costa Rica As Part of the Servir Applied Sciences Team

NASA Astrophysics Data System (ADS)

Thomas, A.; Huff, A. K.; Gomori, S. G.; Sadoff, N.

2014-12-01

In order to enhance the capacity for air quality modeling and improve air quality monitoring and management in the SERVIR Mesoamerica region, members of SERVIR's Applied Sciences Team (AST) are developing national numerical air quality models for El Salvador and Costa Rica. We are working with stakeholders from the El Salvador Ministry of the Environment and Natural Resources (MARN); National University of Costa Rica (UNA); the Costa Rica Ministry of the Environment, Energy, and Telecommunications (MINAET); and Costa Rica National Meteorological Institute (IMN), who are leaders in air quality monitoring and management in the Mesoamerica region. Focusing initially on these institutions will build sustainability in regional modeling activities by developing air quality modeling capability that can be shared with other countries in Mesoamerica. The air quality models are based on the Community Multi-scale Air Quality (CMAQ) model and incorporate meteorological inputs from the Weather Research and Forecasting (WRF) model, as well as national emissions inventories from El Salvador and Costa Rica. The models are being optimized for urban air quality, which is a priority of decision-makers in Mesoamerica. Once experimental versions of the modeling systems are complete, they will be transitioned to servers run by stakeholders in El Salvador and Costa Rica. The numerical air quality models will provide decision support for stakeholders to identify 1) high-priority areas for expanding national ambient air monitoring networks, 2) needed revisions to national air quality regulations, and 3) gaps in national emissions inventories. This project illustrates SERVIR's goal of the transition of science to support decision-making through capacity building in Mesoamerica, and it aligns with the Group on Earth Observations' health societal benefit theme. This presentation will describe technical aspects of the development of the models and outline key steps in our successful collaboration with the Mesoamerican stakeholders, including the processes of identifying and engaging decision-makers, understanding their requirements and limitations, communicating status updates on a regular basis, and providing sufficient training for end users to be able to utilize the models in a decision-making context.

40 CFR 1068.15 - What general provisions apply for EPA decision-making?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 32 2010-07-01 2010-07-01 false What general provisions apply for EPA decision-making? 1068.15 Section 1068.15 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Miscellaneous Provisions § 1068.15 What general provisions apply for EPA decision-making? (a) The Administrator...

Modelling carbon dioxide emissions from agricultural soils in Canada.

PubMed

Yadav, Dhananjay; Wang, Junye

2017-11-01

Agricultural soils are a leading source of atmospheric greenhouse gas (GHG) emissions and are major contributors to global climate change. Carbon dioxide (CO 2 ) makes up 20% of the total GHG emitted from agricultural soil. Therefore, an evaluation of CO 2 emissions from agricultural soil is necessary in order to make mitigation strategies for environmental efficiency and economic planning possible. However, quantification of CO 2 emissions through experimental methods is constrained due to the large time and labour requirements for analysis. Therefore, a modelling approach is needed to achieve this objective. In this paper, the DeNitrification-DeComposition (DNDC), a process-based model, was modified to predict CO 2 emissions for Canada from regional conditions. The modified DNDC model was applied at three experimental sites in the province of Saskatchewan. The results indicate that the simulations of the modified DNDC model are in good agreement with observations. The agricultural management of fertilization and irrigation were evaluated using scenario analysis. The simulated total annual CO 2 flux changed on average by ±13% and ±1% following a ±50% variance of the total amount of N applied by fertilising and the total amount of water through irrigation applications, respectively. Therefore, careful management of irrigation and applications of fertiliser can help to reduce CO 2 emissions from the agricultural sector. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Decision-making in healthcare: a practical application of partial least square path modelling to coverage of newborn screening programmes

PubMed Central

2012-01-01

Background Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare. Methods Empirical approaches that applied PLS-PM to decision-making in healthcare were identified through a systematic literature search. PLS-PM was used as an estimation technique for a structural equation model that specified hypotheses between the components of decision processes and the reasonableness of decision-making in terms of medical, economic and other ethical criteria. The model was estimated for a sample of 55 coverage decisions on the extension of newborn screening programmes in Europe. Results were evaluated by standard reliability and validity measures for PLS-PM. Results After modification by dropping two indicators that showed poor measures in the measurement models’ quality assessment and were not meaningful for newborn screening, the structural equation model estimation produced plausible results. The presence of three influences was supported: the links between both stakeholder participation or transparency and the reasonableness of decision-making; and the effect of transparency on the degree of scientific rigour of assessment. Reliable and valid measurement models were obtained to describe the composites of ‘transparency’, ‘participation’, ‘scientific rigour’ and ‘reasonableness’. Conclusions The structural equation model was among the first applications of PLS-PM to coverage decision-making. It allowed testing of hypotheses in situations where there are links between several non-observable constructs. PLS-PM was compatible in accounting for the complexity of coverage decisions to obtain a more realistic perspective for empirical analysis. The model specification can be used for hypothesis testing by using larger sample sizes and for data in the full domain of health technologies. PMID:22856325

Decision making in cancer primary prevention and chemoprevention.

PubMed

Gorin, Sherri Sheinfeld; Wang, Catharine; Raich, Peter; Bowen, Deborah J; Hay, Jennifer

2006-12-01

We know very little about how individuals decide to undertake, maintain, or discontinue cancer primary prevention or chemoprevention. The aims of this article are to (a) examine whether and, if so, how traditional health behavior change models are relevant for decision making in this area; (b) review the application of decision aids to forming specific, personal choices between options; and (c) identify the challenges of evaluating these decision processes to suggest areas for future research. Theoretical models and frameworks derived from the health behavior change and decision-making fields were applied to cancer primary prevention choices. Decision aids for the human papillomavirus (HPV) vaccine, Hormone Replacement Therapy (HRT), and tamoxifen were systematically examined. Traditional concepts such as decisional balance and cues to action are relevant to understanding cancer primary prevention choices; Motivational Interviewing, Self-Determination Theory, and the Preventive Health Model may also explain the facilitators of decision making. There are no well-tested HPV vaccine decision aids, although there have been some studies on aids for HPV testing. There are several effective decision aids for HRT and tamoxifen; evidence-based decision aid components have also been identified. Additional theory-based empirical research on decision making in cancer primary prevention and chemoprevention, particularly at the interface of psychology and behavioral economics, is suggested.

Decision science: a scientific approach to enhance public health budgeting.

PubMed

Honoré, Peggy A; Fos, Peter J; Smith, Torney; Riley, Michael; Kramarz, Kim

2010-01-01

The allocation of resources for public health programming is a complicated and daunting responsibility. Financial decision-making processes within public health agencies are especially difficult when not supported with techniques for prioritizing and ranking alternatives. This article presents a case study of a decision analysis software model that was applied to the process of identifying funding priorities for public health services in the Spokane Regional Health District. Results on the use of this decision support system provide insights into how decision science models, which have been used for decades in business and industry, can be successfully applied to public health budgeting as a means of strengthening agency financial management processes.

Fireworks algorithm for mean-VaR/CVaR models

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Liu, Zhifeng

2017-10-01

Intelligent algorithms have been widely applied to portfolio optimization problems. In this paper, we introduce a novel intelligent algorithm, named fireworks algorithm, to solve the mean-VaR/CVaR model for the first time. The results show that, compared with the classical genetic algorithm, fireworks algorithm not only improves the optimization accuracy and the optimization speed, but also makes the optimal solution more stable. We repeat our experiments at different confidence levels and different degrees of risk aversion, and the results are robust. It suggests that fireworks algorithm has more advantages than genetic algorithm in solving the portfolio optimization problem, and it is feasible and promising to apply it into this field.

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.

A participatory model for improving occupational health and safety: improving informal sector working conditions in Thailand.

PubMed

Manothum, Aniruth; Rukijkanpanich, Jittra; Thawesaengskulthai, Damrong; Thampitakkul, Boonwa; Chaikittiporn, Chalermchai; Arphorn, Sara

2009-01-01

The purpose of this study was to evaluate the implementation of an Occupational Health and Safety Management Model for informal sector workers in Thailand. The studied model was characterized by participatory approaches to preliminary assessment, observation of informal business practices, group discussion and participation, and the use of environmental measurements and samples. This model consisted of four processes: capacity building, risk analysis, problem solving, and monitoring and control. The participants consisted of four local labor groups from different regions, including wood carving, hand-weaving, artificial flower making, and batik processing workers. The results demonstrated that, as a result of applying the model, the working conditions of the informal sector workers had improved to meet necessary standards. This model encouraged the use of local networks, which led to cooperation within the groups to create appropriate technologies to solve their problems. The authors suggest that this model could effectively be applied elsewhere to improve informal sector working conditions on a broader scale.

An interval-valued 2-tuple linguistic group decision-making model based on the Choquet integral operator

NASA Astrophysics Data System (ADS)

Liu, Bingsheng; Fu, Meiqing; Zhang, Shuibo; Xue, Bin; Zhou, Qi; Zhang, Shiruo

2018-01-01

The Choquet integral (IL) operator is an effective approach for handling interdependence among decision attributes in complex decision-making problems. However, the fuzzy measures of attributes and attribute sets required by IL are difficult to achieve directly, which limits the application of IL. This paper proposes a new method for determining fuzzy measures of attributes by extending Marichal's concept of entropy for fuzzy measure. To well represent the assessment information, interval-valued 2-tuple linguistic context is utilised to represent information. Then, we propose a Choquet integral operator in an interval-valued 2-tuple linguistic environment, which can effectively handle the correlation between attributes. In addition, we apply these methods to solve multi-attribute group decision-making problems. The feasibility and validity of the proposed operator is demonstrated by comparisons with other models in illustrative example part.

The Social Process of Analyzing Real Water Resource Systems Plans and Management Policies

NASA Astrophysics Data System (ADS)

Loucks, Daniel

2016-04-01

Developing and applying systems analysis methods for improving the development and management of real world water resource systems, I have learned, is primarily a social process. This talk is a call for more recognition of this reality in the modeling approaches we propose in the papers and books we publish. The mathematical models designed to inform planners and managers of water systems that we see in many of our journals often seem more complex than they need be. They also often seem not as connected to reality as they could be. While it may be easier to publish descriptions of complex models than simpler ones, and while adding complexity to models might make them better able to mimic or resemble the actual complexity of the real physical and/or social systems or processes being analyzed, the usefulness of such models often can be an illusion. Sometimes the important features of reality that are of concern or interest to those who make decisions can be adequately captured using relatively simple models. Finding the right balance for the particular issues being addressed or the particular decisions that need to be made is an art. When applied to real world problems or issues in specific basins or regions, systems modeling projects often involve more attention to the social aspects than the mathematical ones. Mathematical models addressing connected interacting interdependent components of complex water systems are in fact some of the most useful methods we have to study and better understand the systems we manage around us. They can help us identify and evaluate possible alternative solutions to problems facing humanity today. The study of real world systems of interacting components using mathematical models is commonly called applied systems analyses. Performing such analyses with decision makers rather than of decision makers is critical if the needed trust between project personnel and their clients is to be developed. Using examples from recent and ongoing modeling projects in different parts of the world, this talk will attempt to show the dependency on the degree of project success with the degree of attention given to the communication between project personnel, the stakeholders and decision making institutions. It will also highlight how initial project terms-of-reference and expected outcomes can change, sometimes in surprising ways, during the course of such projects. Changing project objectives often result from changing stakeholder values, emphasizing the need for analyses that can adapt to this uncertainty.

An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning

PubMed Central

Balasubramani, Pragathi P.; Chakravarthy, V. Srinivasa; Ravindran, Balaraman; Moustafa, Ahmed A.

2014-01-01

Although empirical and neural studies show that serotonin (5HT) plays many functional roles in the brain, prior computational models mostly focus on its role in behavioral inhibition. In this study, we present a model of risk based decision making in a modified Reinforcement Learning (RL)-framework. The model depicts the roles of dopamine (DA) and serotonin (5HT) in Basal Ganglia (BG). In this model, the DA signal is represented by the temporal difference error (δ), while the 5HT signal is represented by a parameter (α) that controls risk prediction error. This formulation that accommodates both 5HT and DA reconciles some of the diverse roles of 5HT particularly in connection with the BG system. We apply the model to different experimental paradigms used to study the role of 5HT: (1) Risk-sensitive decision making, where 5HT controls risk assessment, (2) Temporal reward prediction, where 5HT controls time-scale of reward prediction, and (3) Reward/Punishment sensitivity, in which the punishment prediction error depends on 5HT levels. Thus the proposed integrated RL model reconciles several existing theories of 5HT and DA in the BG. PMID:24795614

Strategy on energy saving reconstruction of distribution networks based on life cycle cost

NASA Astrophysics Data System (ADS)

Chen, Xiaofei; Qiu, Zejing; Xu, Zhaoyang; Xiao, Chupeng

2017-08-01

Because the actual distribution network reconstruction project funds are often limited, the cost-benefit model and the decision-making method are crucial for distribution network energy saving reconstruction project. From the perspective of life cycle cost (LCC), firstly the research life cycle is determined for the energy saving reconstruction of distribution networks with multi-devices. Then, a new life cycle cost-benefit model for energy-saving reconstruction of distribution network is developed, in which the modification schemes include distribution transformers replacement, lines replacement and reactive power compensation. In the operation loss cost and maintenance cost area, the operation cost model considering the influence of load season characteristics and the maintenance cost segmental model of transformers are proposed. Finally, aiming at the highest energy saving profit per LCC, a decision-making method is developed while considering financial and technical constraints as well. The model and method are applied to a real distribution network reconstruction, and the results prove that the model and method are effective.

Pedestrians’ behavior in emergency evacuation: Modeling and simulation

NASA Astrophysics Data System (ADS)

Wang, Lei; Zheng, Jie-Hui; Zhang, Xiao-Shuang; Zhang, Jian-Lin; Wang, Qiu-Zhen; Zhang, Qian

2016-11-01

The social force model has been widely used to simulate pedestrian evacuation by analyzing attractive, repulsive, driving, and fluctuating forces among pedestrians. Many researchers have improved its limitations in simulating behaviors of large-scale population. This study modifies the well-accepted social force model by considering the impacts of interaction among companions and further develops a comprehensive model by combining that with a multi-exit utility function. Then numerical simulations of evacuations based on the comprehensive model are implemented in the waiting hall of the Wulin Square Subway Station in Hangzhou, China. The results provide safety thresholds of pedestrian density and panic levels in different operation situations. In spite of the operation situation and the panic level, a larger friend-group size results in lower evacuation efficiency. Our study makes important contributions to building a comprehensive multi-exit social force model and to applying it to actual scenarios, which produces data to facilitate decision making in contingency plans and emergency treatment. Project supported by the National Natural Science Foundation of China (Grant No. 71471163).

A new mathematical modeling approach for the energy of threonine molecule

NASA Astrophysics Data System (ADS)

Sahiner, Ahmet; Kapusuz, Gulden; Yilmaz, Nurullah

2017-07-01

In this paper, we propose an improved new methodology in energy conformation problems for finding optimum energy values. First, we construct the Bezier surfaces near local minimizers based on the data obtained from Density Functional Theory (DFT) calculations. Second, we blend the constructed surfaces in order to obtain a single smooth model. Finally, we apply the global optimization algorithm to find two torsion angles those make the energy of the molecule minimum.

Multi-objective optimization of GENIE Earth system models.

PubMed

Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J

2009-07-13

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

Integrated catchment modelling within a strategic planning and decision making process: Werra case study

NASA Astrophysics Data System (ADS)

Dietrich, Jörg; Funke, Markus

Integrated water resources management (IWRM) redefines conventional water management approaches through a closer cross-linkage between environment and society. The role of public participation and socio-economic considerations becomes more important within the planning and decision making process. In this paper we address aspects of the integration of catchment models into such a process taking the implementation of the European Water Framework Directive (WFD) as an example. Within a case study situated in the Werra river basin (Central Germany), a systems analytic decision process model was developed. This model uses the semantics of the Unified Modeling Language (UML) activity model. As an example application, the catchment model SWAT and the water quality model RWQM1 were applied to simulate the effect of phosphorus emissions from non-point and point sources on water quality. The decision process model was able to guide the participants of the case study through the interdisciplinary planning and negotiation of actions. Further improvements of the integration framework include tools for quantitative uncertainty analyses, which are crucial for real life application of models within an IWRM decision making toolbox. For the case study, the multi-criteria assessment of actions indicates that the polluter pays principle can be met at larger scales (sub-catchment or river basin) without significantly compromising cost efficiency for the local situation.

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

PubMed

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

2017-04-01

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

Coupling machine learning with mechanistic models to study runoff production and river flow at the hillslope scale

NASA Astrophysics Data System (ADS)

Marçais, J.; Gupta, H. V.; De Dreuzy, J. R.; Troch, P. A. A.

2016-12-01

Geomorphological structure and geological heterogeneity of hillslopes are major controls on runoff responses. The diversity of hillslopes (morphological shapes and geological structures) on one hand, and the highly non linear runoff mechanism response on the other hand, make it difficult to transpose what has been learnt at one specific hillslope to another. Therefore, making reliable predictions on runoff appearance or river flow for a given hillslope is a challenge. Applying a classic model calibration (based on inverse problems technique) requires doing it for each specific hillslope and having some data available for calibration. When applied to thousands of cases it cannot always be promoted. Here we propose a novel modeling framework based on coupling process based models with data based approach. First we develop a mechanistic model, based on hillslope storage Boussinesq equations (Troch et al. 2003), able to model non linear runoff responses to rainfall at the hillslope scale. Second we set up a model database, representing thousands of non calibrated simulations. These simulations investigate different hillslope shapes (real ones obtained by analyzing 5m digital elevation model of Brittany and synthetic ones), different hillslope geological structures (i.e. different parametrizations) and different hydrologic forcing terms (i.e. different infiltration chronicles). Then, we use this model library to train a machine learning model on this physically based database. Machine learning model performance is then assessed by a classic validating phase (testing it on new hillslopes and comparing machine learning with mechanistic outputs). Finally we use this machine learning model to learn what are the hillslope properties controlling runoffs. This methodology will be further tested combining synthetic datasets with real ones.

Applying policy network theory to policy-making in China: the case of urban health insurance reform.

PubMed

Zheng, Haitao; de Jong, Martin; Koppenjan, Joop

2010-01-01

In this article, we explore whether policy network theory can be applied in the People's Republic of China (PRC). We carried out a literature review of how this approach has already been dealt with in the Chinese policy sciences thus far. We then present the key concepts and research approach in policy networks theory in the Western literature and try these on a Chinese case to see the fit. We follow this with a description and analysis of the policy-making process regarding the health insurance reform in China from 1998 until the present. Based on this case study, we argue that this body of theory is useful to describe and explain policy-making processes in the Chinese context. However, limitations in the generic model appear in capturing the fundamentally different political and administrative systems, crucially different cultural values in the applicability of some research methods common in Western countries. Finally, we address which political and cultural aspects turn out to be different in the PRC and how they affect methodological and practical problems that PRC researchers will encounter when studying decision-making processes.

Five reasons not to use numerical models in water resource management (Arne Richter Award Lecture for OYS)

NASA Astrophysics Data System (ADS)

Pianosi, Francesca

2015-04-01

Sustainable water resource management in a quickly changing world poses new challenges to hydrology and decision sciences. Systems analysis can contribute to promote sustainable practices by providing the theoretical background and the operational tools for an objective and transparent appraisal of policy options for water resource systems (WRS) management. Traditionally, limited availability of data and computing resources imposed to use oversimplified WRS models, with little consideration of modeling uncertainties and of the non-stationarity and feedbacks between WRS drivers, and a priori aggregation of costs and benefits. Nowadays we increasingly recognize the inadequacy of these simplifications, and consider them among the reasons for the limited use of model-generated information in actual decision-making processes. On the other hand, fast-growing availability of data and computing resources are opening up unprecedented possibilities in the way we build and apply numerical models. In this talk I will discuss my experiences and ideas on how we can exploit this potential to improve model-informed decision-making while facing the challenges of uncertainty, non-stationarity, feedbacks and conflicting objectives. In particular, through practical examples of WRS design and operation problems, my talk will aim at stimulating discussion about the impact of uncertainty on decisions: can inaccurate and imprecise predictions still carry valuable information for decision-making? Does uncertainty in predictions necessarily limit our ability to make 'good' decisions? Or can uncertainty even be of help for decision-making, for instance by reducing the projected conflict between competing water use? Finally, I will also discuss how the traditionally separate disciplines of numerical modelling, optimization, and uncertainty and sensitivity analysis have in my experience been just different facets of the same 'systems approach'.

Adopting and Teaching Evidence-Based Practice in Master's-Level Social Work Programs

ERIC Educational Resources Information Center

Drake, Brett; Hovmand, Peter; Jonson-Reid, Melissa; Zayas, Luis H.

2007-01-01

This article makes specific suggestions for teaching evidence-based practice (EBP) in the master's-in-social-work (MSW) curriculum. The authors use the model of EBP as it was originally conceived: a process for posing empirically answerable questions, finding and evaluating the best available evidence, and applying that evidence in conjunction…

76 FR 80831 - Clarification of Policy Regarding Approved Training Programs

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-27

... approval multiple curriculums for a particular crewmember position and aircraft make/model/variant. For example, a part 135 certificate holder may have a an initial new-hire curriculum designed to meet the... may then also apply for a reduced new hire curriculum for pilots that have previous experience as a...

77 FR 7010 - Clarification of Policy Regarding Approved Training Programs; Correction

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-10

... approval multiple curriculums for a particular crewmember position and aircraft make/model/variant. For example, a part 135 certificate holder may have a an initial new-hire curriculum designed to meet the... certificate holder may then also apply for a reduced new hire curriculum for pilots that have previous...

Taking Charge of Professional Development: A Practical Model for Your School

ERIC Educational Resources Information Center

Semadeni, Joseph

2009-01-01

Overcome budget cuts, lack of leadership, top-down mandates, and other obstacles to professional development by using this book's take-charge approach. Joseph H. Semadeni guides you through a systemic method to professional development that: (1) Motivates teachers to continuously learn and apply best practices; (2) Makes adult learning activities…

Social Sense-making in Mathematics: Children's Ideas of Negative Numbers.

ERIC Educational Resources Information Center

Mukhopadhyay, Swapna; And Others

This study investigated children's ability to interpret a natural social situation, depicted in a narrative story, and to use their understanding of that situation to generate and apply a mental model of debts and assets in solving problems including negative quantities. Fifty-one American students from a parochial school in a predominantly middle…

Quantitative microbial risk assessment for spray irrigation of dairy manure based on an empirical fate and transport model

USDA-ARS?s Scientific Manuscript database

Background: Spray irrigation for land-applying livestock manure is increasing in the United States as farms become larger and economies of scale make manure irrigation affordable. However, human health risks from exposure to zoonotic pathogens aerosolized during manure irrigation are not well-unders...

Characterization of early gonadal development in smallmouth bass (Micropterus dolomieu) and effects of ethinyl estradiol on gonadal differentiation

EPA Science Inventory

Teleosts vary widely in patterns of gonadal sex differentiation, which might lead to differences in how gonadal development is affected by the presence of estrogenic compounds. This makes it difficult to apply our knowledge of model species such as medaka and fathead minnow to o...

Modelling Agency in HIV Treatment Decision-Making

ERIC Educational Resources Information Center

Moore, Alison

2005-01-01

In applying linguistics to the task of analysing how agentivity is construed through verbal interaction, scholars often equate social agency with grammatical agency, and in particular with the grammar of transitivity. The difficulty I want to address in this paper is that we may miss other important, systematic and contrastive patterning in the…

Causal Inferences with Group Based Trajectory Models

ERIC Educational Resources Information Center

Haviland, Amelia M.; Nagin, Daniel S.

2005-01-01

A central theme of research on human development and psychopathology is whether a therapeutic intervention or a turning-point event, such as a family break-up, alters the trajectory of the behavior under study. This paper lays out and applies a method for using observational longitudinal data to make more confident causal inferences about the…

Regime Switching State-Space Models Applied to Psychological Processes: Handling Missing Data and Making Inferences

ERIC Educational Resources Information Center

Hamaker, E. L.; Grasman, R. P. P. P.

2012-01-01

Many psychological processes are characterized by recurrent shifts between distinct regimes or states. Examples that are considered in this paper are the switches between different states associated with premenstrual syndrome, hourly fluctuations in affect during a major depressive episode, and shifts between a "hot hand" and a…

75 FR 17887 - Airworthiness Directives; The Boeing Company Model 767 Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-08

... torque to the nut and bolt of the main track downstop assembly. The corrective actions include: Installing a bolt and spacer with a new nut (including applying torque to make sure that it has been.... Tightening the existing nut. Boeing Special Attention Service Bulletin 767-57-0118, dated October 8, 2009...

Application of the remote-sensing communication model to a time-sensitive wildfire remote-sensing system

Treesearch

Christopher D. Lippitt; Douglas A. Stow; Philip J. Riggan

2016-01-01

Remote sensing for hazard response requires a priori identification of sensor, transmission, processing, and distribution methods to permit the extraction of relevant information in timescales sufficient to allow managers to make a given time-sensitive decision. This study applies and demonstrates the utility of the Remote Sensing Communication...

Applying PRECEDE-PROCEED to Develop an Intuitive Eating Nondieting Approach to Weight Management Pilot Program

ERIC Educational Resources Information Center

Cole, Renee E.; Horacek, Tanya

2009-01-01

Objective: To describe the use of a consolidated version of the PRECEDE-PROCEED participatory program planning model to collaboratively design an intuitive eating program with Fort Drum military spouses tailored to their readiness to reject the dieting mentality and make healthful lifestyle modifications. Design: A consolidated version of…

Downscaled rainfall projections in south Florida using self-organizing maps.

PubMed

Sinha, Palash; Mann, Michael E; Fuentes, Jose D; Mejia, Alfonso; Ning, Liang; Sun, Weiyi; He, Tao; Obeysekera, Jayantha

2018-04-20

We make future projections of seasonal precipitation characteristics in southern Florida using a statistical downscaling approach based on Self Organized Maps. Our approach is applied separately to each three-month season: September-November; December-February; March-May; and June-August. We make use of 19 different simulations from the Coupled Model Inter-comparison Project, phase 5 (CMIP5) and generate an ensemble of 1500 independent daily precipitation surrogates for each model simulation, yielding a grand ensemble of 28,500 total realizations for each season. The center and moments (25%ile and 75%ile) of this distribution are used to characterize most likely scenarios and their associated uncertainties. This approach is applied to 30-year windows of daily mean precipitation for both the CMIP5 historical simulations (1976-2005) and the CMIP5 future (RCP 4.5) projections. For the latter case, we examine both the "near future" (2021-2050) and "far future" (2071-2100) periods for three scenarios (RCP2.6, RCP4.5, and RCP8.5). Copyright © 2018 Elsevier B.V. All rights reserved.

Applying a sociolinguistic model to the analysis of informed consent documents.

PubMed

Granero-Molina, José; Fernández-Sola, Cayetano; Aguilera-Manrique, Gabriel

2009-11-01

Information on the risks and benefits related to surgical procedures is essential for patients in order to obtain their informed consent. Some disciplines, such as sociolinguistics, offer insights that are helpful for patient-professional communication in both written and oral consent. Communication difficulties become more acute when patients make decisions through an informed consent document because they may sign this with a lack of understanding and information, and consequently feel deprived of their freedom to make their choice about different treatments or surgery. This article discusses findings from documentary analysis using the sociolinguistic SPEAKING model, which was applied to the general and specific informed consent documents required for laparoscopic surgery of the bile duct at Torrecárdenas Hospital, Almería, Spain. The objective of this procedure was to identify flaws when information was provided, together with its readability, its voluntary basis, and patients' consent. The results suggest potential linguistic communication difficulties, different languages being used, cultural clashes, asymmetry of communication between professionals and patients, assignment of rights on the part of patients, and overprotection of professionals and institutions.

Micromechanics-Based Inelastic Finite Element Analysis Accomplished Via Seamless Integration of MAC/GMC

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Trowbridge, D.

2001-01-01

A critical issue in the micromechanics-based analysis of composite structures becomes the availability of a computationally efficient homogenization technique: one that is 1) Capable of handling the sophisticated, physically based, viscoelastoplastic constitutive and life models for each constituent; 2) Able to generate accurate displacement and stress fields at both the macro and the micro levels; 3) Compatible with the finite element method. The Generalized Method of Cells (GMC) developed by Paley and Aboudi is one such micromechanical model that has been shown to predict accurately the overall macro behavior of various types of composites given the required constituent properties. Specifically, the method provides "closed-form" expressions for the macroscopic composite response in terms of the properties, size, shape, distribution, and response of the individual constituents or phases that make up the material. Furthermore, expressions relating the internal stress and strain fields in the individual constituents in terms of the macroscopically applied stresses and strains are available through strain or stress concentration matrices. These expressions make possible the investigation of failure processes at the microscopic level at each step of an applied load history.

Complexity reduction of rate-equations models for two-choice decision-making.

PubMed

Carrillo, José Antonio; Cordier, Stéphane; Deco, Gustavo; Mancini, Simona

2013-01-01

We are concerned with the complexity reduction of a stochastic system of differential equations governing the dynamics of a neuronal circuit describing a decision-making task. This reduction is based on the slow-fast behavior of the problem and holds on the whole phase space and not only locally around the spontaneous state. Macroscopic quantities, such as performance and reaction times, computed applying this reduction are in agreement with previous works in which the complexity reduction is locally performed at the spontaneous point by means of a Taylor expansion.

A note on powers in finite fields

NASA Astrophysics Data System (ADS)

Aabrandt, Andreas; Lundsgaard Hansen, Vagn

2016-08-01

The study of solutions to polynomial equations over finite fields has a long history in mathematics and is an interesting area of contemporary research. In recent years, the subject has found important applications in the modelling of problems from applied mathematical fields such as signal analysis, system theory, coding theory and cryptology. In this connection, it is of interest to know criteria for the existence of squares and other powers in arbitrary finite fields. Making good use of polynomial division in polynomial rings over finite fields, we have examined a classical criterion of Euler for squares in odd prime fields, giving it a formulation that is apt for generalization to arbitrary finite fields and powers. Our proof uses algebra rather than classical number theory, which makes it convenient when presenting basic methods of applied algebra in the classroom.

Biology as population dynamics: heuristics for transmission risk.

PubMed

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

Population-type models, accounting for phenomena such as population lifetimes, mixing patterns, recruitment patterns, genetic evolution and environmental conditions, can be usefully applied to the biology of HIV infection and viral replication. A simple dynamic model can explore the effect of a vaccine-like stimulus on the mortality and infectiousness, which formally looks like fertility, of invading virions; the mortality of freshly infected cells; and the availability of target cells, all of which impact on the probability of infection. Variations on this model could capture the importance of the timing and duration of different key events in viral transmission, and hence be applied to questions of mucosal immunology. The dynamical insights and assumptions of such models are compatible with the continuum of between- and within-individual risks in sexual violence and may be helpful in making sense of the sparse data available on the association between HIV transmission and sexual violence. © 2012 John Wiley & Sons A/S.

Model Checking JAVA Programs Using Java Pathfinder

NASA Technical Reports Server (NTRS)

Havelund, Klaus; Pressburger, Thomas

2000-01-01

This paper describes a translator called JAVA PATHFINDER from JAVA to PROMELA, the "programming language" of the SPIN model checker. The purpose is to establish a framework for verification and debugging of JAVA programs based on model checking. This work should be seen in a broader attempt to make formal methods applicable "in the loop" of programming within NASA's areas such as space, aviation, and robotics. Our main goal is to create automated formal methods such that programmers themselves can apply these in their daily work (in the loop) without the need for specialists to manually reformulate a program into a different notation in order to analyze the program. This work is a continuation of an effort to formally verify, using SPIN, a multi-threaded operating system programmed in Lisp for the Deep-Space 1 spacecraft, and of previous work in applying existing model checkers and theorem provers to real applications.

ISG hybrid powertrain: a rule-based driver model incorporating look-ahead information

NASA Astrophysics Data System (ADS)

Shen, Shuiwen; Zhang, Junzhi; Chen, Xiaojiang; Zhong, Qing-Chang; Thornton, Roger

2010-03-01

According to European regulations, if the amount of regenerative braking is determined by the travel of the brake pedal, more stringent standards must be applied, otherwise it may adversely affect the existing vehicle safety system. The use of engine or vehicle speed to derive regenerative braking is one way to avoid strict design standards, but this introduces discontinuity in powertrain torque when the driver releases the acceleration pedal or applies the brake pedal. This is shown to cause oscillations in the pedal input and powertrain torque when a conventional driver model is adopted. Look-ahead information, together with other predicted vehicle states, are adopted to control the vehicle speed, in particular, during deceleration, and to improve the driver model so that oscillations can be avoided. The improved driver model makes analysis and validation of the control strategy for an integrated starter generator (ISG) hybrid powertrain possible.

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

PubMed

Murshid, Mohsen Ali; Mohaidin, Zurina

2017-01-01

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

Landslide Hazard from Coupled Inherent and Dynamic Probabilities

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.; Nudurupati, S. S.

2015-12-01

Landslide hazard research has typically been conducted independently from hydroclimate research. We sought to unify these two lines of research to provide regional scale landslide hazard information for risk assessments and resource management decision-making. Our approach couples an empirical inherent landslide probability, based on a frequency ratio analysis, with a numerical dynamic probability, generated by combining subsurface water recharge and surface runoff from the Variable Infiltration Capacity (VIC) macro-scale land surface hydrologic model with a finer resolution probabilistic slope stability model. Landslide hazard mapping is advanced by combining static and dynamic models of stability into a probabilistic measure of geohazard prediction in both space and time. This work will aid resource management decision-making in current and future landscape and climatic conditions. The approach is applied as a case study in North Cascade National Park Complex in northern Washington State.

Thermal Vacuum Test Correlation of a Zero Propellant Load Case Thermal Capacitance Propellant Gauging Analytical Model

NASA Technical Reports Server (NTRS)

Mckim, Stephen A.

2016-01-01

This thesis describes the development and correlation of a thermal model that forms the foundation of a thermal capacitance spacecraft propellant load estimator. Specific details of creating the thermal model for the diaphragm propellant tank used on NASA's Magnetospheric Multiscale spacecraft using ANSYS and the correlation process implemented are presented. The thermal model was correlated to within plus or minus 3 degrees Celsius of the thermal vacuum test data, and was determined sufficient to make future propellant predictions on MMS. The model was also found to be relatively sensitive to uncertainties in applied heat flux and mass knowledge of the tank. More work is needed to improve temperature predictions in the upper hemisphere of the propellant tank where predictions were found to be 2 to 2.5 C lower than the test data. A road map for applying the model to predict propellant loads on the actual MMS spacecraft toward its end of life in 2017-2018 is also presented.

A systems engineering approach to AIS accreditation

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

Harris, L.M.; Hunteman, W.J.

1994-04-01

The systems engineering model provides the vehicle for communication between the developer and the customer by presenting system facts and demonstrating the system in an organized form. The same model provides implementors with views of the system`s function and capability. The authors contend that the process of obtaining accreditation for a classified Automated Information System (AIS) adheres to the typical systems engineering model. The accreditation process is modeled as a ``roadmap`` with the customer represented by the Designed Accrediting Authority. The ``roadmap`` model reduces the amount of accreditation knowledge required of an AIS developer and maximizes the effectiveness of participationmore » in the accreditation process by making the understanding of accreditation a natural consequence of applying the model. This paper identifies ten ``destinations`` on the ``road`` to accreditation. The significance of each ``destination`` is explained, as are the potential consequences of its exclusion. The ``roadmap,`` which has been applied to a range of information systems throughout the DOE community, establishes a paradigm for the certification and accreditation of classified AISs.« less

Real estate value prediction using multivariate regression models

NASA Astrophysics Data System (ADS)

Manjula, R.; Jain, Shubham; Srivastava, Sharad; Rajiv Kher, Pranav

2017-11-01

The real estate market is one of the most competitive in terms of pricing and the same tends to vary significantly based on a lot of factors, hence it becomes one of the prime fields to apply the concepts of machine learning to optimize and predict the prices with high accuracy. Therefore in this paper, we present various important features to use while predicting housing prices with good accuracy. We have described regression models, using various features to have lower Residual Sum of Squares error. While using features in a regression model some feature engineering is required for better prediction. Often a set of features (multiple regressions) or polynomial regression (applying a various set of powers in the features) is used for making better model fit. For these models are expected to be susceptible towards over fitting ridge regression is used to reduce it. This paper thus directs to the best application of regression models in addition to other techniques to optimize the result.

Decision-making in Swiss home-like childbirth: A grounded theory study.

PubMed

Meyer, Yvonne; Frank, Franziska; Schläppy Muntwyler, Franziska; Fleming, Valerie; Pehlke-Milde, Jessica

2017-12-01

Decision-making in midwifery, including a claim for shared decision-making between midwives and women, is of major significance for the health of mother and child. Midwives have little information about how to share decision-making responsibilities with women, especially when complications arise during birth. To increase understanding of decision-making in complex home-like birth settings by exploring midwives' and women's perspectives and to develop a dynamic model integrating participatory processes for making shared decisions. The study, based on grounded theory methodology, analysed 20 interviews of midwives and 20 women who had experienced complications in home-like births. The central phenomenon that arose from the data was "defining/redefining decision as a joint commitment to healthy childbirth". The sub-indicators that make up this phenomenon were safety, responsibility, mutual and personal commitments. These sub-indicators were also identified to influence temporal conditions of decision-making and to apply different strategies for shared decision-making. Women adopted strategies such as delegating a decision, making the midwife's decision her own, challenging a decision or taking a decision driven by the dynamics of childbirth. Midwives employed strategies such as remaining indecisive, approving a woman's decision, making an informed decision or taking the necessary decision. To respond to recommendations for shared responsibility for care, midwives need to strengthen their shared decision-making skills. The visual model of decision-making in childbirth derived from the data provides a framework for transferring clinical reasoning into practice. Copyright © 2017 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

A Conceptual Analytics Model for an Outcome-Driven Quality Management Framework as Part of Professional Healthcare Education.

PubMed

Hervatis, Vasilis; Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil

2015-10-06

Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators' decision making. A deductive case study approach was applied to develop the conceptual model. The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach.

A Conceptual Analytics Model for an Outcome-Driven Quality Management Framework as Part of Professional Healthcare Education

PubMed Central

Loe, Alan; Barman, Linda; O'Donoghue, John; Zary, Nabil

2015-01-01

Background Preparing the future health care professional workforce in a changing world is a significant undertaking. Educators and other decision makers look to evidence-based knowledge to improve quality of education. Analytics, the use of data to generate insights and support decisions, have been applied successfully across numerous application domains. Health care professional education is one area where great potential is yet to be realized. Previous research of Academic and Learning analytics has mainly focused on technical issues. The focus of this study relates to its practical implementation in the setting of health care education. Objective The aim of this study is to create a conceptual model for a deeper understanding of the synthesizing process, and transforming data into information to support educators’ decision making. Methods A deductive case study approach was applied to develop the conceptual model. Results The analytics loop works both in theory and in practice. The conceptual model encompasses the underlying data, the quality indicators, and decision support for educators. Conclusions The model illustrates how a theory can be applied to a traditional data-driven analytics approach, and alongside the context- or need-driven analytics approach. PMID:27731840

Effects of surface dielectric barrier discharge on aerodynamic characteristic of train

NASA Astrophysics Data System (ADS)

Dong, Lei; Gao, Guoqiang; Peng, Kaisheng; Wei, Wenfu; Li, Chunmao; Wu, Guangning

2017-07-01

High-speed railway today has become an indispensable means of transportation due to its remarkable advantages, including comfortability, convenience and less pollution. The increase in velocity makes the air drag become the main source of energy consumption, leading to receiving more and more concerns. The surface dielectric barrier discharge has shown some unique characteristics in terms of active airflow control. In this paper, the influences of surface dielectric barrier discharge on the aerodynamic characteristics of a scaled train model have been studied. Aspects of the discharge power consumption, the temperature distribution, the velocity of induced flow and the airflow field around the train model were considered. The applied AC voltage was set in the range of 20 kV to 28 kV, with a fixed frequency of 9 kHz. Results indicated that the discharge power consumption, the maximum temperature and the induced flow velocity increased with increasing applied voltage. Mechanisms of applied voltage influencing these key parameters were discussed from the point of the equivalent circuit. The airflow field around the train model with different applied voltages was observed by the smoke visualization experiment. Finally, the effects of surface dielectric barrier discharge on the train drag reduction with different applied voltages were analyzed.

Arranging ISO 13606 archetypes into a knowledge base.

PubMed

Kopanitsa, Georgy

2014-01-01

To enable the efficient reuse of standard based medical data we propose to develop a higher level information model that will complement the archetype model of ISO 13606. This model will make use of the relationships that are specified in UML to connect medical archetypes into a knowledge base within a repository. UML connectors were analyzed for their ability to be applied in the implementation of a higher level model that will establish relationships between archetypes. An information model was developed using XML Schema notation. The model allows linking different archetypes of one repository into a knowledge base. Presently it supports several relationships and will be advanced in future.

Application of agent-based system for bioprocess description and process improvement.

PubMed

Gao, Ying; Kipling, Katie; Glassey, Jarka; Willis, Mark; Montague, Gary; Zhou, Yuhong; Titchener-Hooker, Nigel J

2010-01-01

Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which demonstrate how such a framework may enable the better integration of process operations by providing a plant-wide process description to facilitate process improvement. Copyright 2009 American Institute of Chemical Engineers

Dual processing model of medical decision-making

PubMed Central

2012-01-01

Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the large extent dominated by expected utility theory. The model also provides a platform for reconciling two groups of competing dual processing theories (parallel competitive with default-interventionalist theories). PMID:22943520

Making sense of sparse rating data in collaborative filtering via topographic organization of user preference patterns.

PubMed

Polcicová, Gabriela; Tino, Peter

2004-01-01

We introduce topographic versions of two latent class models (LCM) for collaborative filtering. Latent classes are topologically organized on a square grid. Topographic organization of latent classes makes orientation in rating/preference patterns captured by the latent classes easier and more systematic. The variation in film rating patterns is modelled by multinomial and binomial distributions with varying independence assumptions. In the first stage of topographic LCM construction, self-organizing maps with neural field organized according to the LCM topology are employed. We apply our system to a large collection of user ratings for films. The system can provide useful visualization plots unveiling user preference patterns buried in the data, without loosing potential to be a good recommender model. It appears that multinomial distribution is most adequate if the model is regularized by tight grid topologies. Since we deal with probabilistic models of the data, we can readily use tools from probability and information theories to interpret and visualize information extracted by our system.

3D-Lab: a collaborative web-based platform for molecular modeling.

PubMed

Grebner, Christoph; Norrby, Magnus; Enström, Jonatan; Nilsson, Ingemar; Hogner, Anders; Henriksson, Jonas; Westin, Johan; Faramarzi, Farzad; Werner, Philip; Boström, Jonas

2016-09-01

The use of 3D information has shown impact in numerous applications in drug design. However, it is often under-utilized and traditionally limited to specialists. We want to change that, and present an approach making 3D information and molecular modeling accessible and easy-to-use 'for the people'. A user-friendly and collaborative web-based platform (3D-Lab) for 3D modeling, including a blazingly fast virtual screening capability, was developed. 3D-Lab provides an interface to automatic molecular modeling, like conformer generation, ligand alignments, molecular dockings and simple quantum chemistry protocols. 3D-Lab is designed to be modular, and to facilitate sharing of 3D-information to promote interactions between drug designers. Recent enhancements to our open-source virtual reality tool Molecular Rift are described. The integrated drug-design platform allows drug designers to instantaneously access 3D information and readily apply advanced and automated 3D molecular modeling tasks, with the aim to improve decision-making in drug design projects.

Selecting Design Parameters for Flying Vehicles

NASA Astrophysics Data System (ADS)

Makeev, V. I.; Strel'nikova, E. A.; Trofimenko, P. E.; Bondar', A. V.

2013-09-01

Studying the influence of a number of design parameters of solid-propellant rockets on the longitudinal and lateral dispersion is an important applied problem. A mathematical model of a rigid body of variable mass moving in a disturbed medium exerting both wave drag and friction is considered. The model makes it possible to determine the coefficients of aerodynamic forces and moments, which affect the motion of vehicles, and to assess the effect of design parameters on their accuracy

System and Method for Providing Model-Based Alerting of Spatial Disorientation to a Pilot

NASA Technical Reports Server (NTRS)

Johnson, Steve (Inventor); Conner, Kevin J (Inventor); Mathan, Santosh (Inventor)

2015-01-01

A system and method monitor aircraft state parameters, for example, aircraft movement and flight parameters, applies those inputs to a spatial disorientation model, and makes a prediction of when pilot may become spatially disoriented. Once the system predicts a potentially disoriented pilot, the sensitivity for alerting the pilot to conditions exceeding a threshold can be increased and allow for an earlier alert to mitigate the possibility of an incorrect control input.

A Study on the Application of the Extended Matrices Based on TRIZ in Constructing a Collaborative Model of Enterprise Network

NASA Astrophysics Data System (ADS)

Yang, Yan; Shao, Yunfei; Tang, Xiaowo

Based on mass related literature on enterprise network, the key influence factors are reduced to Trust, Control, Relationship and Interaction. Meanwhile, the specific contradiction matrices, judgment matrices and strategy collections based on TRIZ are constructed which make the connotation of contradiction matrices in TRIZ extended. Finally they are applied to the construction of the collaborative model on enterprise network based on Multi Agent System (MAS).

Inverse scattering method and soliton double solution family for the general symplectic gravity model

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

Gao Yajun

A previously established Hauser-Ernst-type extended double-complex linear system is slightly modified and used to develop an inverse scattering method for the stationary axisymmetric general symplectic gravity model. The reduction procedures in this inverse scattering method are found to be fairly simple, which makes the inverse scattering method applied fine and effective. As an application, a concrete family of soliton double solutions for the considered theory is obtained.

Motivation for health information seeking and processing about clinical trial enrollment.

PubMed

Yang, Z Janet; McComas, Katherine; Gay, Geri; Leonard, John P; Dannenberg, Andrew J; Dillon, Hildy

2010-07-01

Low patient accrual in clinical trials poses serious concerns for the advancement of medical science in the United States. Past research has identified health communication as a crucial step in overcoming barriers to enrollment. However, few communication scholars have studied this problem from a sociopsychological perspective to understand what motivates people to look for or pay attention to information about clinical trial enrollment. This study applies the model of Risk Information Seeking and Processing (RISP) to this context of health decision making. By recognizing the uncertainties embedded in clinical trials, we view clinical trial enrollment as a case study of risk. With data from a random-digit-dial telephone survey of 500 adults living in the United States, we used structural equation modeling to test the central part of the RISP model. In particular, we examined the role of optimistic feelings, as a type of positive affect, in motivating information seeking and processing. Our results indicated that rather than exerting an indirect influence on information seeking through motivating a psychological need for more information, optimistic feelings have more direct relationships with information seeking and processing. Similarly, informational subjective norms also exhibit a more direct relationship with information seeking and processing. These results suggest merit in applying the RISP model to study health decision making related to clinical trial enrollment. Our findings also render practical implications on how to improve communication about clinical trial enrollment.

Numerical modeling of solar irradiance on earth's surface

NASA Astrophysics Data System (ADS)

Mera, E.; Gutierez, L.; Da Silva, L.; Miranda, E.

2016-05-01

Modeling studies and estimation of solar radiation in base area, touch from the problems of estimating equation of time, distance equation solar space, solar declination, calculation of surface irradiance, considering that there are a lot of studies you reported the inability of these theoretical equations to be accurate estimates of radiation, many authors have proceeded to make corrections through calibrations with Pyranometers field (solarimeters) or the use of satellites, this being very poor technique last because there a differentiation between radiation and radiant kinetic effects. Because of the above and considering that there is a weather station properly calibrated ground in the Susques Salar in the Jujuy Province, Republic of Argentina, proceeded to make the following modeling of the variable in question, it proceeded to perform the following process: 1. Theoretical Modeling, 2. graphic study of the theoretical and actual data, 3. Adjust primary calibration data through data segmentation on an hourly basis, through horizontal and adding asymptotic constant, 4. Analysis of scatter plot and contrast series. Based on the above steps, the modeling data obtained: Step One: Theoretical data were generated, Step Two: The theoretical data moved 5 hours, Step Three: an asymptote of all negative emissivity values applied, Solve Excel algorithm was applied to least squares minimization between actual and modeled values, obtaining new values of asymptotes with the corresponding theoretical reformulation of data. Add a constant value by month, over time range set (4:00 pm to 6:00 pm). Step Four: The modeling equation coefficients had monthly correlation between actual and theoretical data ranging from 0.7 to 0.9.

Methods of mathematical modeling using polynomials of algebra of sets

NASA Astrophysics Data System (ADS)

Kazanskiy, Alexandr; Kochetkov, Ivan

2018-03-01

The article deals with the construction of discrete mathematical models for solving applied problems arising from the operation of building structures. Security issues in modern high-rise buildings are extremely serious and relevant, and there is no doubt that interest in them will only increase. The territory of the building is divided into zones for which it is necessary to observe. Zones can overlap and have different priorities. Such situations can be described using formulas algebra of sets. Formulas can be programmed, which makes it possible to work with them using computer models.

Stakeholder involvement in agri-environmental policy making--learning from a local- and a state-level approach in Germany.

PubMed

Prager, Katrin; Freese, Jan

2009-02-01

Recent European regulations for rural development emphasise the requirement to involve stakeholder groups and other appropriate bodies in the policy-making process. This paper presents two cases involving stakeholder participation in agri-environmental development and policy making, targeted at different policy-making levels. One study was undertaken in Lower Saxony where a local partnership developed and tested an agri-environmental prescription, which was later included in the state's menu of agri-environmental schemes. In Sachsen-Anhalt, state-facilitated stakeholder workshops including a mathematical model were used to optimise the programme planning and budget allocation at the state level. Both studies aimed at improving the acceptance of agri-environmental schemes. The authors gauge the effectiveness of the two approaches and discuss what lessons can be learned. The experience suggests that the approaches can complement one another and could also be applied to rural policy making.

Decision making: the neuroethological turn

PubMed Central

Pearson, John M.; Watson, Karli K.; Platt, Michael L.

2014-01-01

Neuroeconomics applies models from economics and psychology to inform neurobiological studies of choice. This approach has revealed neural signatures of concepts like value, risk, and ambiguity, which are known to influence decision-making. Such observations have led theorists to hypothesize a single, unified decision process that mediates choice behavior via a common neural currency for outcomes like food, money, or social praise. In parallel, recent neuroethological studies of decision-making have focused on natural behaviors like foraging, mate choice, and social interactions. These decisions strongly impact evolutionary fitness and thus are likely to have played a key role in shaping the neural circuits that mediate decision-making. This approach has revealed a suite of computational motifs that appear to be shared across a wide variety of organisms. We argue that the existence of deep homologies in the neural circuits mediating choice may have profound implications for understanding human decision-making in health and disease. PMID:24908481

Partial automation of database processing of simulation outputs from L-systems models of plant morphogenesis.

PubMed

Chen, Yi- Ping Phoebe; Hanan, Jim

2002-01-01

Models of plant architecture allow us to explore how genotype environment interactions effect the development of plant phenotypes. Such models generate masses of data organised in complex hierarchies. This paper presents a generic system for creating and automatically populating a relational database from data generated by the widely used L-system approach to modelling plant morphogenesis. Techniques from compiler technology are applied to generate attributes (new fields) in the database, to simplify query development for the recursively-structured branching relationship. Use of biological terminology in an interactive query builder contributes towards making the system biologist-friendly.

A class of multi-period semi-variance portfolio for petroleum exploration and development

NASA Astrophysics Data System (ADS)

Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

2012-10-01

Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

THE IMPACT OF RACISM ON CLINICIAN COGNITION, BEHAVIOR, AND CLINICAL DECISION MAKING

PubMed Central

van Ryn, Michelle; Burgess, Diana J.; Dovidio, John F.; Phelan, Sean M.; Saha, Somnath; Malat, Jennifer; Griffin, Joan M.; Fu, Steven S.; Perry, Sylvia

2014-01-01

Over the past two decades, thousands of studies have demonstrated that Blacks receive lower quality medical care than Whites, independent of disease status, setting, insurance, and other clinically relevant factors. Despite this, there has been little progress towards eradicating these inequities. Almost a decade ago we proposed a conceptual model identifying mechanisms through which clinicians’ behavior, cognition, and decision making might be influenced by implicit racial biases and explicit racial stereotypes, and thereby contribute to racial inequities in care. Empirical evidence has supported many of these hypothesized mechanisms, demonstrating that White medical care clinicians: (1) hold negative implicit racial biases and explicit racial stereotypes, (2) have implicit racial biases that persist independently of and in contrast to their explicit (conscious) racial attitudes, and (3) can be influenced by racial bias in their clinical decision making and behavior during encounters with Black patients. This paper applies evidence from several disciplines to further specify our original model and elaborate on the ways racism can interact with cognitive biases to affect clinicians’ behavior and decisions and in turn, patient behavior and decisions. We then highlight avenues for intervention and make specific recommendations to medical care and grant-making organizations. PMID:24761152

Modeling trade-offs between plant fiber and toxins: a framework for quantifying risks perceived by foraging herbivores.

PubMed

Camp, Meghan J; Shipley, Lisa A; Johnson, Timothy R; Forbey, Jennifer Sorensen; Rachlow, Janet L; Crowell, Miranda M

2015-12-01

When selecting habitats, herbivores must weigh multiple risks, such as predation, starvation, toxicity, and thermal stress, forcing them to make fitness trade-offs. Here, we applied the method of paired comparisons (PC) to investigate how herbivores make trade-offs between habitat features that influence selection of food patches. The method of PC measures utility and the inverse of utility, relative risk, and makes trade-offs and indifferences explicit by forcing animals to make choices between two patches with different types of risks. Using a series of paired-choice experiments to titrate the equivalence curve and find the marginal rate of substitution for one risk over the other, we evaluated how toxin-tolerant (pygmy rabbit Brachylagus idahoensis) and fiber-tolerant (mountain cottontail rabbit Sylviagus nuttallii) herbivores differed in their hypothesized perceived risk of fiber and toxins in food. Pygmy rabbits were willing to consume nearly five times more of the toxin 1,8-cineole in their diets to avoid consuming higher levels of fiber than were mountain cottontails. Fiber posed a greater relative risk for pygmy rabbits than cottontails and cineole a greater risk for cottontails than pygmy rabbits. Our flexible modeling approach can be used to (1) quantify how animals evaluate and trade off multiple habitat attributes when the benefits and risks are difficult to quantify, and (2) integrate diverse risks that influence fitness and habitat selection into a single index of habitat value. This index potentially could be applied to landscapes to predict habitat selection across several scales.

Zero-truncated panel Poisson mixture models: Estimating the impact on tourism benefits in Fukushima Prefecture.

PubMed

Narukawa, Masaki; Nohara, Katsuhito

2018-04-01

This study proposes an estimation approach to panel count data, truncated at zero, in order to apply a contingent behavior travel cost method to revealed and stated preference data collected via a web-based survey. We develop zero-truncated panel Poisson mixture models by focusing on respondents who visited a site. In addition, we introduce an inverse Gaussian distribution to unobserved individual heterogeneity as an alternative to a popular gamma distribution, making it possible to capture effectively the long tail typically observed in trip data. We apply the proposed method to estimate the impact on tourism benefits in Fukushima Prefecture as a result of the Fukushima Nuclear Power Plant No. 1 accident. Copyright © 2018 Elsevier Ltd. All rights reserved.

Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty.

PubMed

Svensson, Fredrik; Aniceto, Natalia; Norinder, Ulf; Cortes-Ciriano, Isidro; Spjuth, Ola; Carlsson, Lars; Bender, Andreas

2018-05-29

Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delivers predictions that are guaranteed to be correct to the selected extent. In this study, we apply conformal regression to model molecular properties and bioactivity values and investigate different ways to scale the resultant prediction intervals to create as efficient (i.e., narrow) regressors as possible. Different algorithms to estimate the prediction uncertainty were used to normalize the prediction ranges, and the different approaches were evaluated on 29 publicly available data sets. Our results show that the most efficient conformal regressors are obtained when using the natural exponential of the ensemble standard deviation from the underlying random forest to scale the prediction intervals, but other approaches were almost as efficient. This approach afforded an average prediction range of 1.65 pIC50 units at the 80% confidence level when applied to bioactivity modeling. The choice of nonconformity function has a pronounced impact on the average prediction range with a difference of close to one log unit in bioactivity between the tightest and widest prediction range. Overall, conformal regression is a robust approach to generate bioactivity predictions with associated confidence.

Determination of Scaled Wind Turbine Rotor Characteristics from Three Dimensional RANS Calculations

NASA Astrophysics Data System (ADS)

Burmester, S.; Gueydon, S.; Make, M.

2016-09-01

Previous studies have shown the importance of 3D effects when calculating the performance characteristics of a scaled down turbine rotor [1-4]. In this paper the results of 3D RANS (Reynolds-Averaged Navier-Stokes) computations by Make and Vaz [1] are taken to calculate 2D lift and drag coefficients. These coefficients are assigned to FAST (Blade Element Momentum Theory (BEMT) tool from NREL) as input parameters. Then, the rotor characteristics (power and thrust coefficients) are calculated using BEMT. This coupling of RANS and BEMT was previously applied by other parties and is termed here the RANS-BEMT coupled approach. Here the approach is compared to measurements carried out in a wave basin at MARIN applying Froude scaled wind, and the direct 3D RANS computation. The data of both a model and full scale wind turbine are used for the validation and verification. The flow around a turbine blade at full scale has a more 2D character than the flow properties around a turbine blade at model scale (Make and Vaz [1]). Since BEMT assumes 2D flow behaviour, the results of the RANS-BEMT coupled approach agree better with the results of the CFD (Computational Fluid Dynamics) simulation at full- than at model-scale.

Super-resolution reconstruction of hyperspectral images.

PubMed

Akgun, Toygar; Altunbasak, Yucel; Mersereau, Russell M

2005-11-01

Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images. Improving their resolution has a high payoff, but applying super-resolution techniques separately to every spectral band is problematic for two main reasons. First, the number of spectral bands can be in the hundreds, which increases the computational load excessively. Second, considering the bands separately does not make use of the information that is present across them. Furthermore, separate band super-resolution does not make use of the inherent low dimensionality of the spectral data, which can effectively be used to improve the robustness against noise. In this paper, we introduce a novel super-resolution method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then, a method for applying super resolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene as a combination of a small number of spectral basis functions.

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2013 CFR

2013-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2014 CFR

2014-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2012 CFR

2012-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

Simulating post-wildfire forest trajectories under alternative climate and management scenarios

Treesearch

Alicia Azpeleta Tarancon; Peter Z. Fule; Kristen L. Shive; Carolyn H. Sieg; Andrew Sanchez Meador; Barbara Strom

2014-01-01

Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned...

Researching Multimodal Texts: Applying a Dynamic Model.

ERIC Educational Resources Information Center

Clancy, Susan; Lowrie, Tom

The arrival of the digital age requires new approaches to understand the literacies used in making meanings from multimodal communications, and a rethinking of the ways in which research into these areas can be used to support learners in the 21st century. This presentation examines the range of literacies children have developed and used to make…

Team Learning to Narrow the Gap between Healthcare Knowledge and Practice

ERIC Educational Resources Information Center

Anand, Tejwansh S.

2014-01-01

This study explored team-based learning in teams of healthcare professionals working on making meaning of evidence-based clinical guidelines in their field to apply them within their practice setting. The research based team learning models posited by Kasl, Marsick, and Dechant (1997) and Edmondson, Dillon, and Roloff (2007) were used as the…

Applying the Participatory Action Research Model to the Study of Social Inclusion at Worksites.

ERIC Educational Resources Information Center

Park, Hyun-Sook; Gonsier-Gerdin, Jean; Hoffman, Stacey; Whaley, Susan; Yount, Michael

1998-01-01

A study used participatory action research (PAR) to explore social inclusion/relationships at worksites of 10 students (ages 17-21). The participatory intervention process assisted teachers and job coaches in making constructive changes in transition work experience programs to provide social opportunities for students and help them become part of…

Reflective Ethical Inquiry: Preparing Students for Life. IDEA Paper #54

ERIC Educational Resources Information Center

Qualters, Donna M.; McDaniels, Melissa; Cohen, Perrin

2013-01-01

Although universities often teach ethics courses, they do not always teach students how to apply ethical course content to ethical dilemmas they encounter on a day-to-day basis. The Awareness-Investigation-Responding (AIR) model of ethical inquiry bridges this gap by scaffolding the reflective process and empowering students to make more caring,…

Are Retrenchment Decisions Rational? The Role of Information in Times of Budgetary Stress.

ERIC Educational Resources Information Center

Ashar, Hanna; Shapiro, Jonathan Z.

1990-01-01

Analysis of the relationship between performance data and changes in faculty size of 40 departments in a College of Arts and Sciences during a time of financial stress found that the rational choice model was applied to decision making. There was a systematic relationship between objective, evaluative data and policy decisions. (MLW)

Exploring the Gas Chemistry of Old Submarine Technologies Using Plastic Bottles as Reaction Vessels and Models

ERIC Educational Resources Information Center

Horikoshi, Ryo; Takeiri, Fumitaka; Kobayashi, Yoji; Kageyama, Hiroshi

2016-01-01

We describe an activity that is suitable for high school students and makes use of plastic bottles. This activity allows students to familiarize themselves with gas chemistry by introducing technologies that were applied in old submarine systems. Plastic bottles, which are representative of submarines, are used as reaction vessels. Three simple…

MANUAL OF LECTURE DEMONSTRATIONS, LABORATORY EXPERIMENTS, AND OBSERVATIONAL EQUIPMENT FOR TEACHING ELEMENTARY METEOROLOGY IN SCHOOLS AND COLLEGES.

ERIC Educational Resources Information Center

NEUBERGER, HANS; NICHOLAS, GEORGE

INCLUDED IN THIS MANUAL WRITTEN FOR SECONDARY SCHOOL AND COLLEGE TEACHERS ARE DESCRIPTIONS OF DEMONSTRATION MODELS, EXPERIMENTS PERTAINING TO SOME OF THE FUNDAMENTAL AND APPLIED METEOROLOGICAL CONCEPTS, AND INSTRUCTIONS FOR MAKING SIMPLE WEATHER OBSERVATIONS. THE CRITERIA FOR SELECTION OF TOPICS WERE EASE AND COST OF CONSTRUCTING APPARATUS AS WELL…

School Choice and the Decision-Making of School Leaders

ERIC Educational Resources Information Center

Kalmar, William F., Jr.

2014-01-01

Almost since the time public schools first opened in the United States there have been those seeking to reform them. One of the most persistent cries for reform has been the call to apply the free market economic model of competition through consumer choice on the public school system. Schools, consumer choice supporters posit, when faced with the…

An Empirical Model for the Use of Biglan's Disciplinary Categories. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Muffo, John A.; Langston, Ira W., IV

The Biglan method of grouping academic disciplines for comparative purposes is discussed as well as an empirically-based system for making internal comparisons among different academic units. The clusters of disciplines developed by Biglan (pure and applied, soft and hard, life and nonlife) are useful guides in working with data involving…

Applying Models to National Surveys of Undergraduate Science Students: What Affects Ratings of Satisfaction?

ERIC Educational Resources Information Center

Langan, Anthony Mark; Dunleavy, Peter; Fielding, Alan

2013-01-01

Many countries use national-level surveys to capture student opinions about their university experiences. It is necessary to interpret survey results in an appropriate context to inform decision-making at many levels. To provide context to national survey outcomes, we describe patterns in the ratings of science and engineering subjects from the…

When Moral Awareness Isn't Enough: Teaching Our Students to Recognize Social Influence

ERIC Educational Resources Information Center

Baker, Diane F.

2014-01-01

The traditional case-based method used to teach ethics in business classrooms gives students valuable practice identifying and applying key moral principles. This approach builds on a rational model of decision making and emphasizes moral awareness and moral judgment, encouraging students to describe moral dilemmas and assess the consequences of…

Reward Rate Optimization in Two-Alternative Decision Making: Empirical Tests of Theoretical Predictions

ERIC Educational Resources Information Center

Simen, Patrick; Contreras, David; Buck, Cara; Hu, Peter; Holmes, Philip; Cohen, Jonathan D.

2009-01-01

The drift-diffusion model (DDM) implements an optimal decision procedure for stationary, 2-alternative forced-choice tasks. The height of a decision threshold applied to accumulating information on each trial determines a speed-accuracy tradeoff (SAT) for the DDM, thereby accounting for a ubiquitous feature of human performance in speeded response…

Reviews of Selected Books and Articles on Gaming and Simulation.

ERIC Educational Resources Information Center

Shubik, Martin; Brewer, Garry D.

This annotated bibliography represents the initial step taken by the authors to apply standards of excellence to the evaluation of literature in the fields of gaming, simulation, and model-building. It aims at helping persons interested in these subjects deal with the flood of literature on these topics by making value judgments, based on the…

A Navajo Paradigm for Long Life Happiness--and for Reversing Navajo Language Shift.

ERIC Educational Resources Information Center

House, Deborah

1997-01-01

Describes a Navajo model by which individuals may assume responsibility for reversing Navajo language shift. Argues that reversing Navajo language shift requires that Navajos acknowledge the problem, that Navajo principles of balance and the natural order be applied to the problem, and that Navajo individuals and families make a commitment to…

Towards more accurate life cycle risk management through integration of DDP and PRA

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Paulos, Todd; Meshkat, Leila; Feather, Martin

2003-01-01

The focus of this paper is on the integration of PRA and DDP. The intent is twofold: to extend risk-based decision though more of the lifecycle, and to lead to improved risk modeling (hence better informed decision making) wherever it is applied, most especially in the early phases as designs begin to mature.

Students' Development and Use of Models to Explain Electrostatic Interactions

NASA Astrophysics Data System (ADS)

Mayer, Kristin Elizabeth

The National Research Council (2012) recently published A Framework for K-12 Science Education that describes a vision for science classrooms where students engage in three dimensions--scientific and engineering practices, crosscutting concepts, and disciplinary core ideas--to explain phenomena or observations they can make about the universe around them. This vision of science instruction is a significant shift from current classroom instruction. This dissertation provides detailed examples of how students developed and used models to build causal explanations of phenomena. I co-taught classes that focused on having students develop and revise models of electric fields and atomic structure using a curriculum that was designed to align with the three-dimensional vision of learning. I developed case studies of eleven students from these classes. I analyzed the students' responses and interviewed the students throughout the school year. By comparing and contrasting the analysis across the analysis of students' interviews, I identified four themes: 1) students could apply their ideas to explain novel and abstract phenomena; 2) students struggled to connect changes in their atomic models to evidence, but ended up with dynamic models of atomic structure that they could apply to explain phenomena; 3) students developed models of atomic structure that they applied to explain phenomena, but they did not use models of electric fields in this way; and 4) too much focus on details interfered with students' ability to apply their models to explain new phenomena. This dissertation highlights the importance of focusing on phenomena in classrooms that aim at aligning with three-dimensional learning. Students struggled to focus on specific content and apply their ideas to explain phenomena at the same time. In order to apply ideas to new context, students had to shift their focus from recalling ideas to applying the ideas they do have. A focus on phenomena allowed students to show their understanding through applying their ideas to new context. During this transition, students struggled, and in particular, had a hard time using evidence from experiments to justify the changes they made to their models of atomic structure. While the changes students made looked unproductive at times, by the end of the semester, students had developed models of atomic structure that incorporated relationships among charged components that they could apply to explain complex phenomena. Asking students to explore and evaluate their own ideas supported their development of models that they could apply to explain new context they experience in their future.

A Novel Group Decision-Making Method Based on Sensor Data and Fuzzy Information.

PubMed

Bai, Yu-Ting; Zhang, Bai-Hai; Wang, Xiao-Yi; Jin, Xue-Bo; Xu, Ji-Ping; Su, Ting-Li; Wang, Zhao-Yang

2016-10-28

Algal bloom is a typical phenomenon of the eutrophication of rivers and lakes and makes the water dirty and smelly. It is a serious threat to water security and public health. Most scholars studying solutions for this pollution have studied the principles of remediation approaches, but few have studied the decision-making and selection of the approaches. Existing research uses simplex decision-making information which is highly subjective and uses little of the data from water quality sensors. To utilize these data and solve the rational decision-making problem, a novel group decision-making method is proposed using the sensor data with fuzzy evaluation information. Firstly, the optimal similarity aggregation model of group opinions is built based on the modified similarity measurement of Vague values. Secondly, the approaches' ability to improve the water quality indexes is expressed using Vague evaluation methods. Thirdly, the water quality sensor data are analyzed to match the features of the alternative approaches with grey relational degrees. This allows the best remediation approach to be selected to meet the current water status. Finally, the selection model is applied to the remediation of algal bloom in lakes. The results show this method's rationality and feasibility when using different data from different sources.

Beyond a code of ethics: phenomenological ethics for everyday practice.

PubMed

Greenfield, Bruce; Jensen, Gail M

2010-06-01

Physical therapy, like all health-care professions, governs itself through a code of ethics that defines its obligations of professional behaviours. The code of ethics provides professions with a consistent and common moral language and principled guidelines for ethical actions. Yet, and as argued in this paper, professional codes of ethics have limits applied to ethical decision-making in the presence of ethical dilemmas. Part of the limitations of the codes of ethics is that there is no particular hierarchy of principles that govern in all situations. Instead, the exigencies of clinical practice, the particularities of individual patient's illness experiences and the transformative nature of chronic illnesses and disabilities often obscure the ethical concerns and issues embedded in concrete situations. Consistent with models of expert practice, and with contemporary models of patient-centred care, we advocate and describe in this paper a type of interpretative and narrative approach to moral practice and ethical decision-making based on phenomenology. The tools of phenomenology that are well defined in research are applied and examined in a case that illustrates their use in uncovering the values and ethical concerns of a patient. Based on the deconstruction of this case on a phenomenologist approach, we illustrate how such approaches for ethical understanding can help assist clinicians and educators in applying principles within the context and needs of each patient. (c) 2010 John Wiley & Sons, Ltd.

Collective behaviour in vertebrates: a sensory perspective

PubMed Central

Collignon, Bertrand; Fernández-Juricic, Esteban

2016-01-01

Collective behaviour models can predict behaviours of schools, flocks, and herds. However, in many cases, these models make biologically unrealistic assumptions in terms of the sensory capabilities of the organism, which are applied across different species. We explored how sensitive collective behaviour models are to these sensory assumptions. Specifically, we used parameters reflecting the visual coverage and visual acuity that determine the spatial range over which an individual can detect and interact with conspecifics. Using metric and topological collective behaviour models, we compared the classic sensory parameters, typically used to model birds and fish, with a set of realistic sensory parameters obtained through physiological measurements. Compared with the classic sensory assumptions, the realistic assumptions increased perceptual ranges, which led to fewer groups and larger group sizes in all species, and higher polarity values and slightly shorter neighbour distances in the fish species. Overall, classic visual sensory assumptions are not representative of many species showing collective behaviour and constrain unrealistically their perceptual ranges. More importantly, caution must be exercised when empirically testing the predictions of these models in terms of choosing the model species, making realistic predictions, and interpreting the results. PMID:28018616

Perception, Action, and Cognition of Football Referees in Extreme Temperatures: Impact on Decision Performance.

PubMed

Gaoua, Nadia; de Oliveira, Rita F; Hunter, Steve

2017-01-01

Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini) review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee's responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees' decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies.

Perception, Action, and Cognition of Football Referees in Extreme Temperatures: Impact on Decision Performance

PubMed Central

Gaoua, Nadia; de Oliveira, Rita F.; Hunter, Steve

2017-01-01

Different professional domains require high levels of physical performance alongside fast and accurate decision-making. Construction workers, police officers, firefighters, elite sports men and women, the military and emergency medical professionals are often exposed to hostile environments with limited options for behavioral coping strategies. In this (mini) review we use football refereeing as an example to discuss the combined effect of intense physical activity and extreme temperatures on decision-making and suggest an explicative model. In professional football competitions can be played in temperatures ranging from -5°C in Norway to 30°C in Spain for example. Despite these conditions, the referee’s responsibility is to consistently apply the laws fairly and uniformly, and to ensure the rules are followed without waning or adversely influencing the competitiveness of the play. However, strenuous exercise in extreme environments imposes increased physiological and psychological stress that can affect decision-making. Therefore, the physical exertion required to follow the game and the thermal strain from the extreme temperatures may hinder the ability of referees to make fast and accurate decisions. Here, we review literature on the physical and cognitive requirements of football refereeing and how extreme temperatures may affect referees’ decisions. Research suggests that both hot and cold environments have a negative impact on decision-making but data specific to decision-making is still lacking. A theoretical model of decision-making under the constraint of intense physical activity and thermal stress is suggested. Future naturalistic studies are needed to validate this model and provide clear recommendations for mitigating strategies. PMID:28912742

Twice random, once mixed: applying mixed models to simultaneously analyze random effects of language and participants.

PubMed

Janssen, Dirk P

2012-03-01

Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F(1) and F(2)) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the DJMIXED: add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.

A Pruning Neural Network Model in Credit Classification Analysis

PubMed Central

Tang, Yajiao; Ji, Junkai; Dai, Hongwei; Yu, Yang; Todo, Yuki

2018-01-01

Nowadays, credit classification models are widely applied because they can help financial decision-makers to handle credit classification issues. Among them, artificial neural networks (ANNs) have been widely accepted as the convincing methods in the credit industry. In this paper, we propose a pruning neural network (PNN) and apply it to solve credit classification problem by adopting the well-known Australian and Japanese credit datasets. The model is inspired by synaptic nonlinearity of a dendritic tree in a biological neural model. And it is trained by an error back-propagation algorithm. The model is capable of realizing a neuronal pruning function by removing the superfluous synapses and useless dendrites and forms a tidy dendritic morphology at the end of learning. Furthermore, we utilize logic circuits (LCs) to simulate the dendritic structures successfully which makes PNN be implemented on the hardware effectively. The statistical results of our experiments have verified that PNN obtains superior performance in comparison with other classical algorithms in terms of accuracy and computational efficiency. PMID:29606961

Stereo Sound Field Controller Design Using Partial Model Matching on the Frequency Domain

NASA Astrophysics Data System (ADS)

Kumon, Makoto; Miike, Katsuhiro; Eguchi, Kazuki; Mizumoto, Ikuro; Iwai, Zenta

The objective of sound field control is to make the acoustic characteristics of a listening room close to those of the desired system. Conventional methods apply feedforward controllers, such as digital filters, to achieve this objective. However, feedback controllers are also necessary in order to attenuate noise or to compensate the uncertainty of the acoustic characteristics of the listening room. Since acoustic characteristics are well modeled on the frequency domain, it is efficient to design controllers with respect to frequency responses, but it is difficult to design a multi input multi output (MIMO) control system on a wide frequency domain. In the present study, a partial model matching method on the frequency domain was adopted because this method requires only sampled data, rather than complex mathematical models of the plant, in order to design controllers for MIMO systems. The partial model matching method was applied to design two-degree-of-freedom controllers for acoustic equalization and noise reduction. Experiments demonstrated effectiveness of the proposed method.

Computer models of complex multiloop branched pipeline systems

NASA Astrophysics Data System (ADS)

Kudinov, I. V.; Kolesnikov, S. V.; Eremin, A. V.; Branfileva, A. N.

2013-11-01

This paper describes the principal theoretical concepts of the method used for constructing computer models of complex multiloop branched pipeline networks, and this method is based on the theory of graphs and two Kirchhoff's laws applied to electrical circuits. The models make it possible to calculate velocities, flow rates, and pressures of a fluid medium in any section of pipeline networks, when the latter are considered as single hydraulic systems. On the basis of multivariant calculations the reasons for existing problems can be identified, the least costly methods of their elimination can be proposed, and recommendations for planning the modernization of pipeline systems and construction of their new sections can be made. The results obtained can be applied to complex pipeline systems intended for various purposes (water pipelines, petroleum pipelines, etc.). The operability of the model has been verified on an example of designing a unified computer model of the heat network for centralized heat supply of the city of Samara.

A systematic and critical review of the evolving methods and applications of value of information in academia and practice.

PubMed

Steuten, Lotte; van de Wetering, Gijs; Groothuis-Oudshoorn, Karin; Retèl, Valesca

2013-01-01

This article provides a systematic and critical review of the evolving methods and applications of value of information (VOI) in academia and practice and discusses where future research needs to be directed. Published VOI studies were identified by conducting a computerized search on Scopus and ISI Web of Science from 1980 until December 2011 using pre-specified search terms. Only full-text papers that outlined and discussed VOI methods for medical decision making, and studies that applied VOI and explicitly discussed the results with a view to informing healthcare decision makers, were included. The included papers were divided into methodological and applied papers, based on the aim of the study. A total of 118 papers were included of which 50 % (n = 59) are methodological. A rapidly accumulating literature base on VOI from 1999 onwards for methodological papers and from 2005 onwards for applied papers is observed. Expected value of sample information (EVSI) is the preferred method of VOI to inform decision making regarding specific future studies, but real-life applications of EVSI remain scarce. Methodological challenges to VOI are numerous and include the high computational demands, dealing with non-linear models and interdependency between parameters, estimations of effective time horizons and patient populations, and structural uncertainties. VOI analysis receives increasing attention in both the methodological and the applied literature bases, but challenges to applying VOI in real-life decision making remain. For many technical and methodological challenges to VOI analytic solutions have been proposed in the literature, including leaner methods for VOI. Further research should also focus on the needs of decision makers regarding VOI.

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

PubMed

Dhukaram, Anandhi Vivekanandan; Baber, Chris

2015-06-01

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

Model-based reasoning in the physics laboratory: Framework and initial results

NASA Astrophysics Data System (ADS)

Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.

2015-12-01

[This paper is part of the Focused Collection on Upper Division Physics Courses.] We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable process, within physics education, it has been preferentially applied to the iterative development of broadly applicable principles (e.g., Newton's laws of motion in introductory mechanics). A significant feature of the new framework is that measurement tools (in addition to the physical system being studied) are subjected to the process of modeling. Think-aloud interviews were used to refine the framework and demonstrate its utility by documenting examples of model-based reasoning in the laboratory. When applied to the think-aloud interviews, the framework captures and differentiates students' model-based reasoning and helps identify areas of future research. The interviews showed how students productively applied similar facets of modeling to the physical system and measurement tools: construction, prediction, interpretation of data, identification of model limitations, and revision. Finally, we document students' challenges in explicitly articulating assumptions when constructing models of experimental systems and further challenges in model construction due to students' insufficient prior conceptual understanding. A modeling perspective reframes many of the seemingly arbitrary technical details of measurement tools and apparatus as an opportunity for authentic and engaging scientific sense making.

Bayesian GGE biplot models applied to maize multi-environments trials.

PubMed

de Oliveira, L A; da Silva, C P; Nuvunga, J J; da Silva, A Q; Balestre, M

2016-06-17

The additive main effects and multiplicative interaction (AMMI) and the genotype main effects and genotype x environment interaction (GGE) models stand out among the linear-bilinear models used in genotype x environment interaction studies. Despite the advantages of their use to describe genotype x environment (AMMI) or genotype and genotype x environment (GGE) interactions, these methods have known limitations that are inherent to fixed effects models, including difficulty in treating variance heterogeneity and missing data. Traditional biplots include no measure of uncertainty regarding the principal components. The present study aimed to apply the Bayesian approach to GGE biplot models and assess the implications for selecting stable and adapted genotypes. Our results demonstrated that the Bayesian approach applied to GGE models with non-informative priors was consistent with the traditional GGE biplot analysis, although the credible region incorporated into the biplot enabled distinguishing, based on probability, the performance of genotypes, and their relationships with the environments in the biplot. Those regions also enabled the identification of groups of genotypes and environments with similar effects in terms of adaptability and stability. The relative position of genotypes and environments in biplots is highly affected by the experimental accuracy. Thus, incorporation of uncertainty in biplots is a key tool for breeders to make decisions regarding stability selection and adaptability and the definition of mega-environments.

Building and executing a research agenda toward conducting implementation science in medical education.

PubMed

Carney, Patricia A; Crites, Gerald E; Miller, Karen H; Haight, Michelle; Stefanidis, Dimitrios; Cichoskikelly, Eileen; Price, David W; Akinola, Modupeola O; Scott, Victoria C; Kalishman, Summers

2016-01-01

Implementation science (IS) is the study of methods that successfully integrate best evidence into practice. Although typically applied in healthcare settings to improve patient care and subsequent outcomes, IS also has immediate and practical applications to medical education toward improving physician training and educational outcomes. The objective of this article is to illustrate how to build a research agenda that focuses on applying IS principles in medical education. We examined the literature to construct a rationale for using IS to improve medical education. We then used a generalizable scenario to step through a process for applying IS to improve team-based care. IS provides a valuable approach to medical educators and researchers for making improvements in medical education and overcoming institution-based challenges. It encourages medical educators to systematically build upon the research outcomes of others to guide decision-making while evaluating the successes of best practices in individual environments and generate additional research questions and findings. IS can act as both a driver and a model for educational research to ensure that best educational practices are easier and faster to implement widely.

Simulation of California's Major Reservoirs Outflow Using Data Mining Technique

NASA Astrophysics Data System (ADS)

Yang, T.; Gao, X.; Sorooshian, S.

2014-12-01

The reservoir's outflow is controlled by reservoir operators, which is different from the upstream inflow. The outflow is more important than the reservoir's inflow for the downstream water users. In order to simulate the complicated reservoir operation and extract the outflow decision making patterns for California's 12 major reservoirs, we build a data-driven, computer-based ("artificial intelligent") reservoir decision making tool, using decision regression and classification tree approach. This is a well-developed statistical and graphical modeling methodology in the field of data mining. A shuffled cross validation approach is also employed to extract the outflow decision making patterns and rules based on the selected decision variables (inflow amount, precipitation, timing, water type year etc.). To show the accuracy of the model, a verification study is carried out comparing the model-generated outflow decisions ("artificial intelligent" decisions) with that made by reservoir operators (human decisions). The simulation results show that the machine-generated outflow decisions are very similar to the real reservoir operators' decisions. This conclusion is based on statistical evaluations using the Nash-Sutcliffe test. The proposed model is able to detect the most influential variables and their weights when the reservoir operators make an outflow decision. While the proposed approach was firstly applied and tested on California's 12 major reservoirs, the method is universally adaptable to other reservoir systems.

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.

Fuzzy sets, rough sets, and modeling evidence: Theory and Application. A Dempster-Shafer based approach to compromise decision making with multiattributes applied to product selection

NASA Technical Reports Server (NTRS)

Dekorvin, Andre

1992-01-01

The Dempster-Shafer theory of evidence is applied to a multiattribute decision making problem whereby the decision maker (DM) must compromise with available alternatives, none of which exactly satisfies his ideal. The decision mechanism is constrained by the uncertainty inherent in the determination of the relative importance of each attribute element and the classification of existing alternatives. The classification of alternatives is addressed through expert evaluation of the degree to which each element is contained in each available alternative. The relative importance of each attribute element is determined through pairwise comparisons of the elements by the decision maker and implementation of a ratio scale quantification method. Then the 'belief' and 'plausibility' that an alternative will satisfy the decision maker's ideal are calculated and combined to rank order the available alternatives. Application to the problem of selecting computer software is given.

A constitutive model for developing blood clots with various compositions and their nonlinear viscoelastic behavior.

PubMed

van Kempen, Thomas H S; Donders, Wouter P; van de Vosse, Frans N; Peters, Gerrit W M

2016-04-01

The mechanical properties determine to a large extent the functioning of a blood clot. These properties depend on the composition of the clot and have been related to many diseases. However, the various involved components and their complex interactions make it difficult at this stage to fully understand and predict properties as a function of the components. Therefore, in this study, a constitutive model is developed that describes the viscoelastic behavior of blood clots with various compositions. Hereto, clots are formed from whole blood, platelet-rich plasma and platelet-poor plasma to study the influence of red blood cells, platelets and fibrin, respectively. Rheological experiments are performed to probe the mechanical behavior of the clots during their formation. The nonlinear viscoelastic behavior of the mature clots is characterized using a large amplitude oscillatory shear deformation. The model is based on a generalized Maxwell model that accurately describes the results for the different rheological experiments by making the moduli and viscosities a function of time and the past and current deformation. Using the same model with different parameter values enables a description of clots with different compositions. A sensitivity analysis is applied to study the influence of parameter variations on the model output. The relative simplicity and flexibility make the model suitable for numerical simulations of blood clots and other materials showing similar behavior.

Modelling approach for the rainfall erosivity index in sub-humid urban areas in northern Algeria

NASA Astrophysics Data System (ADS)

Touaibia, I.; Abderrahmane Guenim, N.; Touaibia, B.

2014-09-01

This work presents an approach for storm water erosivity index modelling in the absence of measurement in an urban area, in a sub-humid climate. In torrential storms, floods, loaded with sediments, obstruct storm water drainage. With the aim of estimating the amount of sediment that can be deposited on a stretch of road, adjacent to the study area, the erosivity index is determined from a count of 744 rain showers recorded over a period of 19 years. The Universal Soil Loss Equation (USLE) of Wischmeier and Smith is applied, where only the index of erosivity is calculated; it is based on the intensity of the rain starting the process of erosion in the basin. Functional relations are required between this factor and the explanatory variables. A power type regression model is reached, making it possible to bring a decision-making aid in absences of measurements.

Performance measurement integrated information framework in e-Manufacturing

NASA Astrophysics Data System (ADS)

Teran, Hilaida; Hernandez, Juan Carlos; Vizán, Antonio; Ríos, José

2014-11-01

The implementation of Internet technologies has led to e-Manufacturing technologies becoming more widely used and to the development of tools for compiling, transforming and synchronising manufacturing data through the Web. In this context, a potential area for development is the extension of virtual manufacturing to performance measurement (PM) processes, a critical area for decision making and implementing improvement actions in manufacturing. This paper proposes a PM information framework to integrate decision support systems in e-Manufacturing. Specifically, the proposed framework offers a homogeneous PM information exchange model that can be applied through decision support in e-Manufacturing environment. Its application improves the necessary interoperability in decision-making data processing tasks. It comprises three sub-systems: a data model, a PM information platform and PM-Web services architecture. A practical example of data exchange for measurement processes in the area of equipment maintenance is shown to demonstrate the utility of the model.

A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses

PubMed Central

Zhang, Chao; Li, Deyu; Yan, Yan

2015-01-01

In medical science, disease diagnosis is one of the difficult tasks for medical experts who are confronted with challenges in dealing with a lot of uncertain medical information. And different medical experts might express their own thought about the medical knowledge base which slightly differs from other medical experts. Thus, to solve the problems of uncertain data analysis and group decision making in disease diagnoses, we propose a new rough set model called dual hesitant fuzzy multigranulation rough set over two universes by combining the dual hesitant fuzzy set and multigranulation rough set theories. In the framework of our study, both the definition and some basic properties of the proposed model are presented. Finally, we give a general approach which is applied to a decision making problem in disease diagnoses, and the effectiveness of the approach is demonstrated by a numerical example. PMID:26858772

Application of a computational decision model to examine acute drug effects on human risk taking.

PubMed

Lane, Scott D; Yechiam, Eldad; Busemeyer, Jerome R

2006-05-01

In 3 previous experiments, high doses of alcohol, marijuana, and alprazolam acutely increased risky decision making by adult humans in a 2-choice (risky vs. nonrisky) laboratory task. In this study, a computational modeling analysis known as the expectancy valence model (J. R. Busemeyer & J. C. Stout, 2002) was applied to individual-participant data from these studies, for the highest administered dose of all 3 drugs and corresponding placebo doses, to determine changes in decision-making processes that may be uniquely engendered by each drug. The model includes 3 parameters: responsiveness to rewards and losses (valence or motivation); the rate of updating expectancies about the value of risky alternatives (learning/memory); and the consistency with which trial-by-trial choices match expected outcomes (sensitivity). Parameter estimates revealed 3 key outcomes: Alcohol increased responsiveness to risky rewards and decreased responsiveness to risky losses (motivation) but did not alter expectancy updating (learning/memory); both marijuana and alprazolam produced increases in risk taking that were related to learning/memory but not motivation; and alcohol and marijuana (but not alprazolam) produced more random response patterns that were less consistently related to expected outcomes on the 2 choices. No significant main effects of gender or dose by gender interactions were obtained, but 2 dose by gender interactions approached significance. These outcomes underscore the utility of using a computational modeling approach to deconstruct decision-making processes and thus better understand drug effects on risky decision making in humans.

Simulation tools for developing policies for complex systems: modeling the health and safety of refugee communities.

PubMed

Anderson, James; Chaturvedi, Alok; Cibulskis, Mike

2007-12-01

The U.S. Committee for Refugees and Immigrants estimated that there were over 33 million refugees and internally displaced persons (IDPs) in the world at the beginning of 2005. IDP/Refugee communities behave in complex ways making it difficult to make policy decisions regarding the provision of humanitarian aid and health and safety. This paper reports the construction of an agent-based model that has been used to study humanitarian assistance policies executed by governments and NGOs that provide for the health and safety of refugee communities. Agent-based modeling (ABM) was chosen because the more widely used alternatives impose unrealistic restrictions and assumptions on the system being modeled and primarily apply to aggregate data. We created intelligent agents representing institutions, organizations, individuals, infrastructure, and governments and analyzed the resulting interactions and emergent behavior using a Central Composite Design of Experiments with five factors. The resulting model allows policy makers and analysts to create scenarios, to make rapid changes in parameters, and provides a test bed for concepts and strategies. Policies can be examined to see how refugee communities might respond to alternative courses of action and how these actions are likely to affect the health and well-being of the community.

Criteria for assessing problem solving and decision making in complex environments

NASA Technical Reports Server (NTRS)

Orasanu, Judith

1993-01-01

Training crews to cope with unanticipated problems in high-risk, high-stress environments requires models of effective problem solving and decision making. Existing decision theories use the criteria of logical consistency and mathematical optimality to evaluate decision quality. While these approaches are useful under some circumstances, the assumptions underlying these models frequently are not met in dynamic time-pressured operational environments. Also, applying formal decision models is both labor and time intensive, a luxury often lacking in operational environments. Alternate approaches and criteria are needed. Given that operational problem solving and decision making are embedded in ongoing tasks, evaluation criteria must address the relation between those activities and satisfaction of broader task goals. Effectiveness and efficiency become relevant for judging reasoning performance in operational environments. New questions must be addressed: What is the relation between the quality of decisions and overall performance by crews engaged in critical high risk tasks? Are different strategies most effective for different types of decisions? How can various decision types be characterized? A preliminary model of decision types found in air transport environments will be described along with a preliminary performance model based on an analysis of 30 flight crews. The performance analysis examined behaviors that distinguish more and less effective crews (based on performance errors). Implications for training and system design will be discussed.

The process of processing: exploring the validity of Neisser's perceptual cycle model with accounts from critical decision-making in the cockpit.

PubMed

Plant, Katherine L; Stanton, Neville A

2015-01-01

The perceptual cycle model (PCM) has been widely applied in ergonomics research in domains including road, rail and aviation. The PCM assumes that information processing occurs in a cyclical manner drawing on top-down and bottom-up influences to produce perceptual exploration and actions. However, the validity of the model has not been addressed. This paper explores the construct validity of the PCM in the context of aeronautical decision-making. The critical decision method was used to interview 20 helicopter pilots about critical decision-making. The data were qualitatively analysed using an established coding scheme, and composite PCMs for incident phases were constructed. It was found that the PCM provided a mutually exclusive and exhaustive classification of the information-processing cycles for dealing with critical incidents. However, a counter-cycle was also discovered which has been attributed to skill-based behaviour, characteristic of experts. The practical applications and future research questions are discussed. Practitioner Summary: This paper explores whether information processing, when dealing with critical incidents, occurs in the manner anticipated by the perceptual cycle model. In addition to the traditional processing cycle, a reciprocal counter-cycle was found. This research can be utilised by those who use the model as an accident analysis framework.

Real-life decision making in college students. II: Do individual differences show reliable effects?

PubMed

Galotti, Kathleen M; Tandler, Jane M; Wiener, Hillary J D

2014-01-01

First-year undergraduates participated in a short-term longitudinal study of real-life decision making over their first 14 months of college. They were surveyed about 7 different decisions: choosing courses for upcoming terms (on 3 different occasions), choosing an academic major (twice), planning for the upcoming summer, and planning for sophomore-year housing. They also completed a survey of self-reported decision-making styles and the Need for Cognition survey (Cacioppo & Petty, 1982) to assess their focus on rationality and enjoyment of analytic thinking. Results showed few statistically significant correlations between stylistic measures and behavioral measures of decision making, in either the amount of information considered or the way in which the information integration tracked predictions of linear models of decision making applied to each participant's data. However, there were consistent correlations, across the 7 decisions, between stylistic measures and affective reactions to, or retrospective descriptions of, episodes of decision making. We suggest that decision-making styles instruments may better reflect the construction of narratives of self as a decision maker more than they do actual behavior during decision making.

Hypothesis testing in functional linear regression models with Neyman's truncation and wavelet thresholding for longitudinal data.

PubMed

Yang, Xiaowei; Nie, Kun

2008-03-15

Longitudinal data sets in biomedical research often consist of large numbers of repeated measures. In many cases, the trajectories do not look globally linear or polynomial, making it difficult to summarize the data or test hypotheses using standard longitudinal data analysis based on various linear models. An alternative approach is to apply the approaches of functional data analysis, which directly target the continuous nonlinear curves underlying discretely sampled repeated measures. For the purposes of data exploration, many functional data analysis strategies have been developed based on various schemes of smoothing, but fewer options are available for making causal inferences regarding predictor-outcome relationships, a common task seen in hypothesis-driven medical studies. To compare groups of curves, two testing strategies with good power have been proposed for high-dimensional analysis of variance: the Fourier-based adaptive Neyman test and the wavelet-based thresholding test. Using a smoking cessation clinical trial data set, this paper demonstrates how to extend the strategies for hypothesis testing into the framework of functional linear regression models (FLRMs) with continuous functional responses and categorical or continuous scalar predictors. The analysis procedure consists of three steps: first, apply the Fourier or wavelet transform to the original repeated measures; then fit a multivariate linear model in the transformed domain; and finally, test the regression coefficients using either adaptive Neyman or thresholding statistics. Since a FLRM can be viewed as a natural extension of the traditional multiple linear regression model, the development of this model and computational tools should enhance the capacity of medical statistics for longitudinal data.

Artificial Intelligence for VHSIC Systems Design (AIVD) User Reference Manual

DTIC Science & Technology

1988-12-01

The goal of this program was to develop prototype tools which would use artificial intelligence techniques to extend the Architecture Design and Assessment (ADAS) software capabilities. These techniques were applied in a number of ways to increase the productivity of ADAS users. AIM will reduce the amount of time spent on tedious, negative, and error-prone steps. It will also provide f documentation that will assist users in varifying that the models they build are correct Finally, AIVD will help make ADAS models more reusable.

Registered nurses' decision-making regarding documentation in patients' progress notes.

PubMed

Tower, Marion; Chaboyer, Wendy; Green, Quentine; Dyer, Kirsten; Wallis, Marianne

2012-10-01

To examine registered nurses' decision-making when documenting care in patients' progress notes. What constitutes effective nursing documentation is supported by available guidelines. However, ineffective documentation continues to be cited as a major cause of adverse events for patients. Decision-making in clinical practice is a complex process. To make an effective decision, the decision-maker must be situationally aware. The concept of situation awareness and its implications for making safe decisions has been examined extensively in air safety and more recently is being applied to health. The study was situated in a naturalistic paradigm. Purposive sampling was used to recruit 17 registered nurses who used think-aloud research methods when making decisions about documenting information in patients' progress notes. Follow-up interviews were conducted to validate interpretations. Data were analysed systematically for evidence of cues that demonstrated situation awareness as nurses made decisions about documentation. Three distinct decision-making scenarios were illuminated from the analysis: the newly admitted patient, the patient whose condition was as expected and the discharging patient. Nurses used mental models for decision-making in documenting in progress notes, and the cues nurses used to direct their assessment of patients' needs demonstrated situation awareness at different levels. Nurses demonstrate situation awareness at different levels in their decision-making processes. While situation awareness is important, it is also important to use an appropriate decision-making framework. Cognitive continuum theory is suggested as a decision-making model that could support situation awareness when nurses made decisions about documenting patient care. Because nurses are key decision-makers, it is imperative that effective decisions are made that translate into safe clinical care. Including situation awareness training, combined with employing cognitive continuum theory as a decision-making framework, provides a powerful means of guiding nurses' decision-making. © 2012 Blackwell Publishing Ltd.

Network approaches for expert decisions in sports.

PubMed

Glöckner, Andreas; Heinen, Thomas; Johnson, Joseph G; Raab, Markus

2012-04-01

This paper focuses on a model comparison to explain choices based on gaze behavior via simulation procedures. We tested two classes of models, a parallel constraint satisfaction (PCS) artificial neuronal network model and an accumulator model in a handball decision-making task from a lab experiment. Both models predict action in an option-generation task in which options can be chosen from the perspective of a playmaker in handball (i.e., passing to another player or shooting at the goal). Model simulations are based on a dataset of generated options together with gaze behavior measurements from 74 expert handball players for 22 pieces of video footage. We implemented both classes of models as deterministic vs. probabilistic models including and excluding fitted parameters. Results indicated that both classes of models can fit and predict participants' initially generated options based on gaze behavior data, and that overall, the classes of models performed about equally well. Early fixations were thereby particularly predictive for choices. We conclude that the analyses of complex environments via network approaches can be successfully applied to the field of experts' decision making in sports and provide perspectives for further theoretical developments. Copyright © 2011 Elsevier B.V. All rights reserved.

Modeling thermal sensation in a Mediterranean climate—a comparison of linear and ordinal models

NASA Astrophysics Data System (ADS)

Pantavou, Katerina; Lykoudis, Spyridon

2014-08-01

A simple thermo-physiological model of outdoor thermal sensation adjusted with psychological factors is developed aiming to predict thermal sensation in Mediterranean climates. Microclimatic measurements simultaneously with interviews on personal and psychological conditions were carried out in a square, a street canyon and a coastal location of the greater urban area of Athens, Greece. Multiple linear and ordinal regression were applied in order to estimate thermal sensation making allowance for all the recorded parameters or specific, empirically selected, subsets producing so-called extensive and empirical models, respectively. Meteorological, thermo-physiological and overall models - considering psychological factors as well - were developed. Predictions were improved when personal and psychological factors were taken into account as compared to meteorological models. The model based on ordinal regression reproduced extreme values of thermal sensation vote more adequately than the linear regression one, while the empirical model produced satisfactory results in relation to the extensive model. The effects of adaptation and expectation on thermal sensation vote were introduced in the models by means of the exposure time, season and preference related to air temperature and irradiation. The assessment of thermal sensation could be a useful criterion in decision making regarding public health, outdoor spaces planning and tourism.

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

PubMed

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

2014-01-01

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

Risk-based decision making for terrorism applications.

PubMed

Dillon, Robin L; Liebe, Robert M; Bestafka, Thomas

2009-03-01

This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.

MODEM: A comprehensive approach to modelling outcome and costs impacts of interventions for dementia. Protocol paper.

PubMed

Comas-Herrera, Adelina; Knapp, Martin; Wittenberg, Raphael; Banerjee, Sube; Bowling, Ann; Grundy, Emily; Jagger, Carol; Farina, Nicolas; Lombard, Daniel; Lorenz, Klara; McDaid, David

2017-01-11

The MODEM project (A comprehensive approach to MODelling outcome and costs impacts of interventions for DEMentia) explores how changes in arrangements for the future treatment and care of people living with dementia, and support for family and other unpaid carers, could result in better outcomes and more efficient use of resources. MODEM starts with a systematic mapping of the literature on effective and (potentially) cost-effective interventions in dementia care. Those findings, as well as data from a cohort, will then be used to model the quality of life and cost impacts of making these evidence-based interventions more widely available in England over the period from now to 2040. Modelling will use a suite of models, combining microsimulation and macrosimulation methods, modelling the costs and outcomes of care, both for an individual over the life-course from the point of dementia diagnosis, and for individuals and England as a whole in a particular year. Project outputs will include an online Dementia Evidence Toolkit, making evidence summaries and a literature database available free to anyone, papers in academic journals and other written outputs, and a MODEM Legacy Model, which will enable local commissioners of services to apply the model to their own populations. Modelling the effects of evidence-based cost-effective interventions and making this information widely available has the potential to improve the health and quality of life both of people with dementia and their carers, while ensuring that resources are used efficiently.

Everyday ethics and help-seeking in early rheumatoid arthritis

PubMed Central

Townsend, A.; Adam, P.; Cox, S.M.; Li, L.C.

2018-01-01

Background Sociological understandings of chronic illness have revealed tensions and complexities around help-seeking. Although ethics underpins healthcare, its application in the area of chronic illness is limited. Here we apply an ethical framework to interview accounts and identify ethical challenges in the early rheumatoid arthritis (RA) experience. Methods In-depth interviews were conducted with eight participants who had been diagnosed with RA in the 12 months prior to recruitment. Applying the concepts of autonomous decision-making and procedural justice highlighted ethical concerns which arose throughout the help-seeking process. Analysis was based on the constant-comparison approach. Results Individuals described decision-making, illness actions and the medical encounter. The process was complicated by inadequate knowledge about symptoms, common-sense understandings about the GP appointment, difficulties concerning access to specialists, and patient–practitioner interactions. Autonomous decision-making and procedural justice were compromised. The accounts revealed contradictions between the policy ideals of active self-management, patient-centred care and shared decision-making, and the everyday experiences of individuals. Conclusions For ethical healthcare there is a need for: public knowledge about early RA symptoms; more effective patient–practitioner communication; and increased support during the wait between primary and secondary care. Healthcare facilities and the government may consider different models to deliver services to people requiring rheumatology consults. PMID:20610465

Design Optimization of Microalloyed Steels Using Thermodynamics Principles and Neural-Network-Based Modeling

NASA Astrophysics Data System (ADS)

Mohanty, Itishree; Chintha, Appa Rao; Kundu, Saurabh

2018-06-01

The optimization of process parameters and composition is essential to achieve the desired properties with minimal additions of alloying elements in microalloyed steels. In some cases, it may be possible to substitute such steels for those which are more richly alloyed. However, process control involves a larger number of parameters, making the relationship between structure and properties difficult to assess. In this work, neural network models have been developed to estimate the mechanical properties of steels containing Nb + V or Nb + Ti. The outcomes have been validated by thermodynamic calculations and plant data. It has been shown that subtle thermodynamic trends can be captured by the neural network model. Some experimental rolling data have also been used to support the model, which in addition has been applied to calculate the costs of optimizing microalloyed steel. The generated pareto fronts identify many combinations of strength and elongation, making it possible to select composition and process parameters for a range of applications. The ANN model and the optimization model are being used for prediction of properties in a running plant and for development of new alloys, respectively.

A user-friendly mathematical modelling web interface to assist local decision making in the fight against drug-resistant tuberculosis.

PubMed

Ragonnet, Romain; Trauer, James M; Denholm, Justin T; Marais, Ben J; McBryde, Emma S

2017-05-30

Multidrug-resistant and rifampicin-resistant tuberculosis (MDR/RR-TB) represent an important challenge for global tuberculosis (TB) control. The high rates of MDR/RR-TB observed among re-treatment cases can arise from diverse pathways: de novo amplification during initial treatment, inappropriate treatment of undiagnosed MDR/RR-TB, relapse despite appropriate treatment, or reinfection with MDR/RR-TB. Mathematical modelling allows quantification of the contribution made by these pathways in different settings. This information provides valuable insights for TB policy-makers, allowing better contextualised solutions. However, mathematical modelling outputs need to consider local data and be easily accessible to decision makers in order to improve their usefulness. We present a user-friendly web-based modelling interface, which can be used by people without technical knowledge. Users can input their own parameter values and produce estimates for their specific setting. This innovative tool provides easy access to mathematical modelling outputs that are highly relevant to national TB control programs. In future, the same approach could be applied to a variety of modelling applications, enhancing local decision making.

Geomorphological hazard and tourist vulnerability along Portofino Park trails (Italy)

NASA Astrophysics Data System (ADS)

Brandolini, P.; Faccini, F.; Piccazzo, M.

2006-06-01

The many trails existing in the coastal area of Portofino Promontory are used by tourists for trekking or as pathways to small villages and beaches. The aim of this paper is to define geomorphological hazard and tourist vulnerability in this area, within the framework of the management and planning of hiking activities in Portofino Natural Park. In particular, processes triggered by gravity, running waters and wave motion, affecting the slopes and the cliff, are considered. The typology of the trails and trail maintenance are also taken into account in relation to weather conditions that can make the excursion routes dangerous for tourists. In conclusion, an operative model is applied for the definition of possible risk scenarios. This model is founded on an inventory and the quantification of geomorphological hazards and tourist vulnerability, in comparison with trail rescue data. The model can be applied to other environments and tourist areas.

Improving Psychological Measurement: Does It Make a Difference? A Comment on Nesselroade and Molenaar (2016).

PubMed

Maydeu-Olivares, Alberto

2016-01-01

Nesselroade and Molenaar advocate the use of an idiographic filter approach. This is a fixed-effects approach, which may limit the number of individuals that can be simultaneously modeled, and it is not clear how to model the presence of subpopulations. Most important, Nesselroade and Molenaar's proposal appears to be best suited for modeling long time series on a few variables for a few individuals. Long time series are not common in psychological applications. Can it be applied to the usual longitudinal data we face? These are characterized by short time series (four to five points in time), hundreds of individuals, and dozens of variables. If so, what do we gain? Applied settings most often involve between-individual decisions. I conjecture that their approach will not outperform common, simpler, methods. However, when intraindividual decisions are involved, their approach may have an edge.

General mental ability and two types of adaptation to unforeseen change: applying discontinuous growth models to the task-change paradigm.

PubMed

Lang, Jonas W B; Bliese, Paul D

2009-03-01

The present research provides new insights into the relationship between general mental ability (GMA) and adaptive performance by applying a discontinuous growth modeling framework to a study of unforeseen change on a complex decision-making task. The proposed framework provides a way to distinguish 2 types of adaptation (transition adaptation and reacquisition adaptation) from 2 common performance components (skill acquisition and basal task performance). Transition adaptation refers to an immediate loss of performance following a change, whereas reacquisition adaptation refers to the ability to relearn a changed task over time. Analyses revealed that GMA was negatively related to transition adaptation and found no evidence for a relationship between GMA and reacquisition adaptation. The results are integrated within the context of adaptability research, and implications of using the described discontinuous growth modeling framework to study adaptability are discussed. (c) 2009 APA, all rights reserved.

Complete Hamiltonian analysis of cosmological perturbations at all orders

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

Nandi, Debottam; Shankaranarayanan, S., E-mail: debottam@iisertvm.ac.in, E-mail: shanki@iisertvm.ac.in

2016-06-01

In this work, we present a consistent Hamiltonian analysis of cosmological perturbations at all orders. To make the procedure transparent, we consider a simple model and resolve the 'gauge-fixing' issues and extend the analysis to scalar field models and show that our approach can be applied to any order of perturbation for any first order derivative fields. In the case of Galilean scalar fields, our procedure can extract constrained relations at all orders in perturbations leading to the fact that there is no extra degrees of freedom due to the presence of higher time derivatives of the field in themore » Lagrangian. We compare and contrast our approach to the Lagrangian approach (Chen et al. [2006]) for extracting higher order correlations and show that our approach is efficient and robust and can be applied to any model of gravity and matter fields without invoking slow-roll approximation.« less

The FluxCompensator: Making Radiative Transfer Models of Hydrodynamical Simulations Directly Comparable to Real Observations

NASA Astrophysics Data System (ADS)

Koepferl, Christine M.; Robitaille, Thomas P.

2017-11-01

When modeling astronomical objects throughout the universe, it is important to correctly treat the limitations of the data, for instance finite resolution and sensitivity. In order to simulate these effects, and to make radiative transfer models directly comparable to real observations, we have developed an open-source Python package called the FluxCompensator that enables the post-processing of the output of 3D Monte Carlo radiative transfer codes, such as Hyperion. With the FluxCompensator, realistic synthetic observations can be generated by modeling the effects of convolution with arbitrary point-spread functions, transmission curves, finite pixel resolution, noise, and reddening. Pipelines can be applied to compute synthetic observations that simulate observatories, such as the Spitzer Space Telescope or the Herschel Space Observatory. Additionally, this tool can read in existing observations (e.g., FITS format) and use the same settings for the synthetic observations. In this paper, we describe the package as well as present examples of such synthetic observations.

The Risk Assessment Study for Electric Power Marketing Competitiveness Based on Cloud Model and TOPSIS

NASA Astrophysics Data System (ADS)

Li, Cunbin; Wang, Yi; Lin, Shuaishuai

2017-09-01

With the rapid development of the energy internet and the deepening of the electric power reform, the traditional marketing mode of electric power does not apply to most of electric power enterprises, so must seek a breakthrough, however, in the face of increasingly complex marketing information, how to make a quick, reasonable transformation, makes the electric power marketing competitiveness assessment more accurate and objective becomes a big problem. In this paper, cloud model and TOPSIS method is proposed. Firstly, build the electric power marketing competitiveness evaluation index system. Then utilize the cloud model to transform the qualitative evaluation of the marketing data into quantitative values and use the entropy weight method to weaken the subjective factors of evaluation index weight. Finally, by TOPSIS method the closeness degrees of alternatives are obtained. This method provides a novel solution for the electric power marketing competitiveness evaluation. Through the case analysis the effectiveness and feasibility of this model are verified.

The study on stage financing model of IT project investment.

PubMed

Chen, Si-hua; Xu, Sheng-hua; Lee, Changhoon; Xiong, Neal N; He, Wei

2014-01-01

Stage financing is the basic operation of venture capital investment. In investment, usually venture capitalists use different strategies to obtain the maximum returns. Due to its advantages to reduce the information asymmetry and agency cost, stage financing is widely used by venture capitalists. Although considerable attentions are devoted to stage financing, very little is known about the risk aversion strategies of IT projects. This paper mainly addresses the problem of risk aversion of venture capital investment in IT projects. Based on the analysis of characteristics of venture capital investment of IT projects, this paper introduces a real option pricing model to measure the value brought by the stage financing strategy and design a risk aversion model for IT projects. Because real option pricing method regards investment activity as contingent decision, it helps to make judgment on the management flexibility of IT projects and then make a more reasonable evaluation about the IT programs. Lastly by being applied to a real case, it further illustrates the effectiveness and feasibility of the model.

The Study on Stage Financing Model of IT Project Investment

PubMed Central

Xu, Sheng-hua; Xiong, Neal N.

2014-01-01

Stage financing is the basic operation of venture capital investment. In investment, usually venture capitalists use different strategies to obtain the maximum returns. Due to its advantages to reduce the information asymmetry and agency cost, stage financing is widely used by venture capitalists. Although considerable attentions are devoted to stage financing, very little is known about the risk aversion strategies of IT projects. This paper mainly addresses the problem of risk aversion of venture capital investment in IT projects. Based on the analysis of characteristics of venture capital investment of IT projects, this paper introduces a real option pricing model to measure the value brought by the stage financing strategy and design a risk aversion model for IT projects. Because real option pricing method regards investment activity as contingent decision, it helps to make judgment on the management flexibility of IT projects and then make a more reasonable evaluation about the IT programs. Lastly by being applied to a real case, it further illustrates the effectiveness and feasibility of the model. PMID:25147845

The effects of nutrition labeling on consumer food choice: a psychological experiment and computational model.

PubMed

Helfer, Peter; Shultz, Thomas R

2014-12-01

The widespread availability of calorie-dense food is believed to be a contributing cause of an epidemic of obesity and associated diseases throughout the world. One possible countermeasure is to empower consumers to make healthier food choices with useful nutrition labeling. An important part of this endeavor is to determine the usability of existing and proposed labeling schemes. Here, we report an experiment on how four different labeling schemes affect the speed and nutritional value of food choices. We then apply decision field theory, a leading computational model of human decision making, to simulate the experimental results. The psychology experiment shows that quantitative, single-attribute labeling schemes have greater usability than multiattribute and binary ones, and that they remain effective under moderate time pressure. The computational model simulates these psychological results and provides explanatory insights into them. This work shows how experimental psychology and computational modeling can contribute to the evaluation and improvement of nutrition-labeling schemes. © 2014 New York Academy of Sciences.

The FluxCompensator: Making Radiative Transfer Models of Hydrodynamical Simulations Directly Comparable to Real Observations

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

Koepferl, Christine M.; Robitaille, Thomas P., E-mail: koepferl@usm.lmu.de

When modeling astronomical objects throughout the universe, it is important to correctly treat the limitations of the data, for instance finite resolution and sensitivity. In order to simulate these effects, and to make radiative transfer models directly comparable to real observations, we have developed an open-source Python package called the FluxCompensator that enables the post-processing of the output of 3D Monte Carlo radiative transfer codes, such as Hyperion. With the FluxCompensator, realistic synthetic observations can be generated by modeling the effects of convolution with arbitrary point-spread functions, transmission curves, finite pixel resolution, noise, and reddening. Pipelines can be applied tomore » compute synthetic observations that simulate observatories, such as the Spitzer Space Telescope or the Herschel Space Observatory . Additionally, this tool can read in existing observations (e.g., FITS format) and use the same settings for the synthetic observations. In this paper, we describe the package as well as present examples of such synthetic observations.« less

Fiber-optical sensor with intensity compensation model in college teaching of physics experiment

NASA Astrophysics Data System (ADS)

Su, Liping; Zhang, Yang; Li, Kun; Zhang, Yu

2017-08-01

Optical fiber sensor technology is one of the main contents of modern information technology, which has a very important position in modern science and technology. Fiber optic sensor experiment can improve students' enthusiasm and broaden their horizons in college physics experiment. In this paper the main structure and working principle of fiberoptical sensor with intensity compensation model are introduced. And thus fiber-optical sensor with intensity compensation model is applied to measure micro displacement of Young's modulus measurement experiment and metal linear expansion coefficient measurement experiment in the college physics experiment. Results indicate that the measurement accuracy of micro displacement is higher than that of the traditional methods using fiber-optical sensor with intensity compensation model. Meanwhile this measurement method makes the students understand on the optical fiber, sensor and nature of micro displacement measurement method and makes each experiment strengthen relationship and compatibility, which provides a new idea for the reform of experimental teaching.

R&D for computational cognitive and social models : foundations for model evaluation through verification and validation (final LDRD report).

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

Slepoy, Alexander; Mitchell, Scott A.; Backus, George A.

2008-09-01

Sandia National Laboratories is investing in projects that aim to develop computational modeling and simulation applications that explore human cognitive and social phenomena. While some of these modeling and simulation projects are explicitly research oriented, others are intended to support or provide insight for people involved in high consequence decision-making. This raises the issue of how to evaluate computational modeling and simulation applications in both research and applied settings where human behavior is the focus of the model: when is a simulation 'good enough' for the goals its designers want to achieve? In this report, we discuss two years' worthmore » of review and assessment of the ASC program's approach to computational model verification and validation, uncertainty quantification, and decision making. We present a framework that extends the principles of the ASC approach into the area of computational social and cognitive modeling and simulation. In doing so, we argue that the potential for evaluation is a function of how the modeling and simulation software will be used in a particular setting. In making this argument, we move from strict, engineering and physics oriented approaches to V&V to a broader project of model evaluation, which asserts that the systematic, rigorous, and transparent accumulation of evidence about a model's performance under conditions of uncertainty is a reasonable and necessary goal for model evaluation, regardless of discipline. How to achieve the accumulation of evidence in areas outside physics and engineering is a significant research challenge, but one that requires addressing as modeling and simulation tools move out of research laboratories and into the hands of decision makers. This report provides an assessment of our thinking on ASC Verification and Validation, and argues for further extending V&V research in the physical and engineering sciences toward a broader program of model evaluation in situations of high consequence decision-making.« less

An integrated fuzzy approach for strategic alliance partner selection in third-party logistics.

PubMed

Erkayman, Burak; Gundogar, Emin; Yilmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

PubMed Central

Gundogar, Emin; Yılmaz, Aysegul

2012-01-01

Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model. PMID:23365520

Arranging ISO 13606 archetypes into a knowledge base using UML connectors.

PubMed

Kopanitsa, Georgy

2014-01-01

To enable the efficient reuse of standard based medical data we propose to develop a higher-level information model that will complement the archetype model of ISO 13606. This model will make use of the relationships that are specified in UML to connect medical archetypes into a knowledge base within a repository. UML connectors were analysed for their ability to be applied in the implementation of a higher-level model that will establish relationships between archetypes. An information model was developed using XML Schema notation. The model allows linking different archetypes of one repository into a knowledge base. Presently it supports several relationships and will be advanced in future.

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

NASA Astrophysics Data System (ADS)

Doherty, John; Simmons, Craig T.

2013-11-01

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

Application of fuzzy AHP method to IOCG prospectivity mapping: A case study in Taherabad prospecting area, eastern Iran

NASA Astrophysics Data System (ADS)

Najafi, Ali; Karimpour, Mohammad Hassan; Ghaderi, Majid

2014-12-01

Using fuzzy analytical hierarchy process (AHP) technique, we propose a method for mineral prospectivity mapping (MPM) which is commonly used for exploration of mineral deposits. The fuzzy AHP is a popular technique which has been applied for multi-criteria decision-making (MCDM) problems. In this paper we used fuzzy AHP and geospatial information system (GIS) to generate prospectivity model for Iron Oxide Copper-Gold (IOCG) mineralization on the basis of its conceptual model and geo-evidence layers derived from geological, geochemical, and geophysical data in Taherabad area, eastern Iran. The FuzzyAHP was used to determine the weights belonging to each criterion. Three geoscientists knowledge on exploration of IOCG-type mineralization have been applied to assign weights to evidence layers in fuzzy AHP MPM approach. After assigning normalized weights to all evidential layers, fuzzy operator was applied to integrate weighted evidence layers. Finally for evaluating the ability of the applied approach to delineate reliable target areas, locations of known mineral deposits in the study area were used. The results demonstrate the acceptable outcomes for IOCG exploration.

Making a Virtue out of a Necessity: Part Time Work as a Site for Undergraduate Work-Based Learning

ERIC Educational Resources Information Center

Shaw, Sue; Ogilvie, Chrissy

2010-01-01

Purpose: This paper seeks to challenge the view that student part time employment detracts from academic attainment and presents evidence that when linked to formal undergraduate study provides rich learning experiences. It also explores the extent to which formerly accepted pre-requisites for work based learning (WBL) apply in this model and how…

Estimating Demand for Higher Education Services. Planning for Higher Education; Vol. 3; No. 3; June 1974.

ERIC Educational Resources Information Center

Kicinski, Walter T.; Soss, Neal M.

Changing patterns of demand for higher education services have generated considerable interest in research into the factors governing the choices students make when they apply to colleges and universities. During 1973, the staff of the State Budget Division of New York State undertook the task of creating a general model of the demand for college…

Make a Drawing. Effects of Strategic Knowledge, Drawing Accuracy, and Type of Drawing on Students' Mathematical Modelling Performance

ERIC Educational Resources Information Center

Rellensmann, Johanna; Schukajlow, Stanislaw; Leopold, Claudia

2017-01-01

Drawing strategies are widely used as a powerful tool for promoting students' learning and problem solving. In this article, we report the results of an inferential mediation analysis that was applied to investigate the roles that strategic knowledge about drawing and the accuracy of different types of drawings play in mathematical modelling…

B-Learning at Universities in Andalusia (Spain): From Traditional to Student-Centred Learning

ERIC Educational Resources Information Center

Morueta, Ramon Tirado; Gomez, Jose Ignacio Aguaded; Gomez, Angel Hernando

2012-01-01

In this paper, the authors examine the rates at which blended learning (b-learning) has been adopted at universities in the region of Andalusia (Spain), as well as the educational model applied to its usage. The authors explore the influence of teachers' perceptions of their competence in the use they make of digital material and to measure…

Combining Group-Based Trajectory Modeling and Propensity Score Matching for Causal Inferences in Nonexperimental Longitudinal Data

ERIC Educational Resources Information Center

Haviland, Amelia; Nagin, Daniel S.; Rosenbaum, Paul R.; Tremblay, Richard E.

2008-01-01

A central theme of research on human development and psychopathology is whether a therapeutic intervention or a turning-point event, such as a family break-up, alters the trajectory of the behavior under study. This article describes and applies a method for using observational longitudinal data to make more transparent causal inferences about the…

27 CFR 53.104 - Limitation on amount of tax applicable to certain leases.

Code of Federal Regulations, 2010 CFR

2010-04-01

... making the lease, the lessor is engaged in the business of selling in arm's length transactions the same type and model of article. In case of a lease to which section 4217(b) of the Code does not apply, tax...) Lessor engaged in business of selling. The lessor will be regarded as being engaged in the business of...

Using Screening Level Environmental Life Cycle Assessment to Aid Decision Making: A Case Study of a College Annual Report

ERIC Educational Resources Information Center

Ingwersen, Wesley W.; Curran, Mary Ann; Gonzalez, Michael A.; Hawkins, Troy R.

2012-01-01

Purpose: The purpose of this study is to compare the life cycle environmental impacts of the University of Cincinnati College of Engineering and Applied Sciences' current printed annual report to a version distributed via the internet. Design/methodology/approach: Life cycle environmental impacts of both versions of the report are modeled using…

Using the Sacramento soil moisture accounting model to provide short-term forecasts of surface runoff for daily decision making in nutrient management

USDA-ARS?s Scientific Manuscript database

Managing the timing of fertilizer and manure application is critical to protecting water quality in agricultural watersheds. When fertilizers and manures are applied at inopportune times (e.g., just prior to a rainfall event that produces surface runoff) the risk of surface water contamination is un...

The Psychological Four-Color Mapping Problem

ERIC Educational Resources Information Center

Francis, Gregory; Bias, Keri; Shive, Joshua

2010-01-01

Mathematicians have proven that four colors are sufficient to color 2-D maps so that no neighboring regions share the same color. Here we consider the psychological 4-color problem: Identifying which 4 colors should be used to make a map easy to use. We build a model of visual search for this design task and demonstrate how to apply it to the task…

Aligning Coordination Class Theory with a New Context: Applying a Theory of Individual Learning to Group Learning

ERIC Educational Resources Information Center

Barth-Cohen, Lauren A.; Wittmann, Michael C.

2017-01-01

This article presents an empirical analysis of conceptual difficulties encountered and ways students made progress in learning at both individual and group levels in a classroom environment in which the students used an embodied modeling activity to make sense of a specific scientific scenario. The theoretical framework, coordination class theory,…

Applying fire spread simulators in New Zealand and Australia: Results from an international seminar

Treesearch

Tonja Opperman; Jim Gould; Mark Finney; Cordy Tymstra

2006-01-01

There is currently no spatial wildfire spread and growth simulation model used commonly across New Zealand or Australia. Fire management decision-making would be enhanced through the use of spatial fire simulators. Various groups from around the world met in January 2006 to evaluate the applicability of different spatial fire spread applications for common use in both...

Can It Be Done Better for Less: A Model for Effective Applied Behavior Analysis Training in School Districts

ERIC Educational Resources Information Center

Thomas, C. A.

2005-01-01

At a time when special education budgets are constrained and the demand for behavior analysis services continue to increase within school settings a clear implemental system to train the trainers is not only necessary but essential. This paper discusses one possible system for making behavior analysis services and behavior analysis training…

Microfluidic generation of aqueous two-phase system (ATPS) droplets by controlled pulsating inlet pressures.

PubMed

Moon, Byeong-Ui; Jones, Steven G; Hwang, Dae Kun; Tsai, Scott S H

2015-06-07

We present a technique that generates droplets using ultralow interfacial tension aqueous two-phase systems (ATPS). Our method combines a classical microfluidic flow focusing geometry with precisely controlled pulsating inlet pressure, to form monodisperse ATPS droplets. The dextran (DEX) disperse phase enters through the central inlet with variable on-off pressure cycles controlled by a pneumatic solenoid valve. The continuous phase polyethylene glycol (PEG) solution enters the flow focusing junction through the cross channels at a fixed flow rate. The on-off cycles of the applied pressure, combined with the fixed flow rate cross flow, make it possible for the ATPS jet to break up into droplets. We observe different droplet formation regimes with changes in the applied pressure magnitude and timing, and the continuous phase flow rate. We also develop a scaling model to predict the size of the generated droplets, and the experimental results show a good quantitative agreement with our scaling model. Additionally, we demonstrate the potential for scaling-up of the droplet production rate, with a simultaneous two-droplet generating geometry. We anticipate that this simple and precise approach to making ATPS droplets will find utility in biological applications where the all-biocompatibility of ATPS is desirable.

Advancements in Risk-Informed Performance-Based Asset Management for Commercial Nuclear Power Plants

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

Liming, James K.; Ravindra, Mayasandra K.

2006-07-01

Over the past several years, ABSG Consulting Inc. (ABS Consulting) and the South Texas Project Nuclear Operating Company (STPNOC) have developed a decision support process and associated software for risk-informed, performance-based asset management (RIPBAM) of nuclear power plant facilities. RIPBAM applies probabilistic risk assessment (PRA) tools and techniques in the realm of plant physical and financial asset management. The RIPBAM process applies a tiered set of models and supporting performance measures (or metrics) that can ultimately be applied to support decisions affecting the allocation and management of plant resources (e.g., funding, staffing, scheduling, etc.). In general, the ultimate goal ofmore » the RIPBAM process is to continually support decision-making to maximize a facility's net present value (NPV) and long-term profitability for its owners. While the initial applications of RIPBAM have been for nuclear power stations, the methodology can easily be adapted to other types of power station or complex facility decision-making support. RIPBAM can also be designed to focus on performance metrics other than NPV and profitability (e.g., mission reliability, operational availability, probability of mission success per dollar invested, etc.). Recent advancements in the RIPBAM process focus on expanding the scope of previous RIPBAM applications to include not only operations, maintenance, and safety issues, but also broader risk perception components affecting plant owner (stockholder), operator, and regulator biases. Conceptually, RIPBAM is a comprehensive risk-informed cash flow model for decision support. It originated as a tool to help manage plant refueling outage scheduling, and was later expanded to include the full spectrum of operations and maintenance decision support. However, it differs from conventional business modeling tools in that it employs a systems engineering approach with broadly based probabilistic analysis of organizational 'value streams'. The scope of value stream inclusion in the process can be established by the user, but in its broadest applications, RIPBAM can be used to address how risk perceptions of plant owners and regulators are impacted by plant performance. Plant staffs can expand and refine RIPBAM models scope via a phased program of activities over time. This paper shows how the multi-metric uncertainty analysis feature of RIPBAM can apply a wide spectrum of decision-influencing factors to support decisions designed to maximize the probability of achieving, maintaining, and improving upon plant goals and objectives. In this paper, the authors show how this approach can be extremely valuable to plant owners and operators in supporting plant value-impacting decision-making processes. (authors)« less

Timing analysis by model checking

NASA Technical Reports Server (NTRS)

Naydich, Dimitri; Guaspari, David

2000-01-01

The safety of modern avionics relies on high integrity software that can be verified to meet hard real-time requirements. The limits of verification technology therefore determine acceptable engineering practice. To simplify verification problems, safety-critical systems are commonly implemented under the severe constraints of a cyclic executive, which make design an expensive trial-and-error process highly intolerant of change. Important advances in analysis techniques, such as rate monotonic analysis (RMA), have provided a theoretical and practical basis for easing these onerous restrictions. But RMA and its kindred have two limitations: they apply only to verifying the requirement of schedulability (that tasks meet their deadlines) and they cannot be applied to many common programming paradigms. We address both these limitations by applying model checking, a technique with successful industrial applications in hardware design. Model checking algorithms analyze finite state machines, either by explicit state enumeration or by symbolic manipulation. Since quantitative timing properties involve a potentially unbounded state variable (a clock), our first problem is to construct a finite approximation that is conservative for the properties being analyzed-if the approximation satisfies the properties of interest, so does the infinite model. To reduce the potential for state space explosion we must further optimize this finite model. Experiments with some simple optimizations have yielded a hundred-fold efficiency improvement over published techniques.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

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

Terrain modeling for microwave landing system

NASA Technical Reports Server (NTRS)

Poulose, M. M.

1991-01-01

A powerful analytical approach for evaluating the terrain effects on a microwave landing system (MLS) is presented. The approach combines a multiplate model with a powerful and exhaustive ray tracing technique and an accurate formulation for estimating the electromagnetic fields due to the antenna array in the presence of terrain. Both uniform theory of diffraction (UTD) and impedance UTD techniques have been employed to evaluate these fields. Innovative techniques are introduced at each stage to make the model versatile to handle most general terrain contours and also to reduce the computational requirement to a minimum. The model is applied to several terrain geometries, and the results are discussed.

Transmission dynamics of cholera: Mathematical modeling and control strategies

NASA Astrophysics Data System (ADS)

Sun, Gui-Quan; Xie, Jun-Hui; Huang, Sheng-He; Jin, Zhen; Li, Ming-Tao; Liu, Liqun

2017-04-01

Cholera, as an endemic disease around the world, has generated great threat to human society and caused enormous morbidity and mortality with weak surveillance system. In this paper, we propose a mathematical model to describe the transmission of Cholera. Moreover, basic reproduction number and the global dynamics of the dynamical model are obtained. Then we apply our model to characterize the transmission process of Cholera in China. It was found that, in order to avoid its outbreak in China, it may be better to increase immunization coverage rate and make effort to improve environmental management especially for drinking water. Our results may provide some new insights for elimination of Cholera.

Automating Risk Analysis of Software Design Models

PubMed Central

Ruiz, Guifré; Heymann, Elisa; César, Eduardo; Miller, Barton P.

2014-01-01

The growth of the internet and networked systems has exposed software to an increased amount of security threats. One of the responses from software developers to these threats is the introduction of security activities in the software development lifecycle. This paper describes an approach to reduce the need for costly human expertise to perform risk analysis in software, which is common in secure development methodologies, by automating threat modeling. Reducing the dependency on security experts aims at reducing the cost of secure development by allowing non-security-aware developers to apply secure development with little to no additional cost, making secure development more accessible. To automate threat modeling two data structures are introduced, identification trees and mitigation trees, to identify threats in software designs and advise mitigation techniques, while taking into account specification requirements and cost concerns. These are the components of our model for automated threat modeling, AutSEC. We validated AutSEC by implementing it in a tool based on data flow diagrams, from the Microsoft security development methodology, and applying it to VOMS, a grid middleware component, to evaluate our model's performance. PMID:25136688

Developmental Changes in Learning: Computational Mechanisms and Social Influences

PubMed Central

Bolenz, Florian; Reiter, Andrea M. F.; Eppinger, Ben

2017-01-01

Our ability to learn from the outcomes of our actions and to adapt our decisions accordingly changes over the course of the human lifespan. In recent years, there has been an increasing interest in using computational models to understand developmental changes in learning and decision-making. Moreover, extensions of these models are currently applied to study socio-emotional influences on learning in different age groups, a topic that is of great relevance for applications in education and health psychology. In this article, we aim to provide an introduction to basic ideas underlying computational models of reinforcement learning and focus on parameters and model variants that might be of interest to developmental scientists. We then highlight recent attempts to use reinforcement learning models to study the influence of social information on learning across development. The aim of this review is to illustrate how computational models can be applied in developmental science, what they can add to our understanding of developmental mechanisms and how they can be used to bridge the gap between psychological and neurobiological theories of development. PMID:29250006

Automating risk analysis of software design models.

PubMed

Frydman, Maxime; Ruiz, Guifré; Heymann, Elisa; César, Eduardo; Miller, Barton P

2014-01-01

The growth of the internet and networked systems has exposed software to an increased amount of security threats. One of the responses from software developers to these threats is the introduction of security activities in the software development lifecycle. This paper describes an approach to reduce the need for costly human expertise to perform risk analysis in software, which is common in secure development methodologies, by automating threat modeling. Reducing the dependency on security experts aims at reducing the cost of secure development by allowing non-security-aware developers to apply secure development with little to no additional cost, making secure development more accessible. To automate threat modeling two data structures are introduced, identification trees and mitigation trees, to identify threats in software designs and advise mitigation techniques, while taking into account specification requirements and cost concerns. These are the components of our model for automated threat modeling, AutSEC. We validated AutSEC by implementing it in a tool based on data flow diagrams, from the Microsoft security development methodology, and applying it to VOMS, a grid middleware component, to evaluate our model's performance.

Accuracy of parameterized proton range models; A comparison

NASA Astrophysics Data System (ADS)

Pettersen, H. E. S.; Chaar, M.; Meric, I.; Odland, O. H.; Sølie, J. R.; Röhrich, D.

2018-03-01

An accurate calculation of proton ranges in phantoms or detector geometries is crucial for decision making in proton therapy and proton imaging. To this end, several parameterizations of the range-energy relationship exist, with different levels of complexity and accuracy. In this study we compare the accuracy of four different parameterizations models for proton range in water: Two analytical models derived from the Bethe equation, and two different interpolation schemes applied to range-energy tables. In conclusion, a spline interpolation scheme yields the highest reproduction accuracy, while the shape of the energy loss-curve is best reproduced with the differentiated Bragg-Kleeman equation.

An Inherited Efficiencies Model of Non-Genomic Evolution

NASA Technical Reports Server (NTRS)

New, Michael H.; Pohorille, Andrew

1999-01-01

A model for the evolution of biological systems in the absence of a nucleic acid-like genome is proposed and applied to model the earliest living organisms -- protocells composed of membrane encapsulated peptides. Assuming that the peptides can make and break bonds between amino acids, and bonds in non-functional peptides are more likely to be destroyed than in functional peptides, it is demonstrated that the catalytic capabilities of the system as a whole can increase. This increase is defined to be non-genomic evolution. The relationship between the proposed mechanism for evolution and recent experiments on self-replicating peptides is discussed.

Adding Value to the Network: Exploring the Software as a Service and Platform as a Service Models for Mobile Operators

NASA Astrophysics Data System (ADS)

Gonçalves, Vânia

The environments of software development and software provision are shifting to Web-based platforms supported by Platform/Software as a Service (PaaS/SaaS) models. This paper will make the case that there is equally an opportunity for mobile operators to identify additional sources of revenue by exposing network functionalities through Web-based service platforms. By elaborating on the concepts, benefits and risks of SaaS and PaaS, several factors that should be taken into consideration in applying these models to the telecom world are delineated.

Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

PubMed Central

2014-01-01

This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions). PMID:25152926

Applying Self-Determination Theory to Adolescent Sexual-Risk Behavior and Knowledge: A Structural Equation Model [Formula: see text].

PubMed

Riley, Bettina H; McDermott, Ryon C

2018-05-01

National health priorities identify adolescent sexual-risk behavior outcomes as research and intervention targets for mental health. Reduce sexual-risk behavioral outcomes by applying self-determination theory to focus on decision-making autonomy. This study examined late adolescents' recollections of parental autonomy support/sexual-risk communication experiences and autonomy motivation as predictors of sexual-risk behaviors/knowledge. A convenience sample ( N = 249) of 19- and 20-year-old university students completed self-report questionnaires. Structural equation modeling with latent variables examined direct/indirect effects in the hypothesized model. Parents contributed uniquely through sexual-risk communication and/or autonomy support to late adolescents' autonomous motivation. The final model evidenced acceptable fit and explained 12% of the variation in adolescent sexual-risk behavior, 7% in adolescent autonomous motivation, and 2% in adolescent sexual-risk knowledge. Psychiatric mental health nurses should conduct further research and design interventions promoting parent autonomy support and adolescent autonomous motivation to reduce sexual risk-behavior and increase sexual-risk knowledge.

Direct methanol fuel cells: A database-driven design procedure

NASA Astrophysics Data System (ADS)

Flipsen, S. F. J.; Spitas, C.

2011-10-01

To test the feasibility of DMFC systems in preliminary stages of the design process the design engineer can make use of heuristic models identifying the opportunity of DMFC systems in a specific application. In general these models are to generic and have a low accuracy. To improve the accuracy a second-order model is proposed in this paper. The second-order model consists of an evolutionary algorithm written in Mathematica, which selects a component-set satisfying the fuel-cell systems' performance requirements, places the components in 3D space and optimizes for volume. The results are presented as a 3D draft proposal together with a feasibility metric. To test the algorithm the design of DMFC system applied in the MP3 player is evaluated. The results show that volume and costs are an issue for the feasibility of the fuel-cell power-system applied in the MP3 player. The generated designs and the algorithm are evaluated and recommendations are given.

Design and Fabrication of Flying Saucer Utilizing Coanda Effect

NASA Astrophysics Data System (ADS)

Aabid, Abdul; Khan, S. A.

2018-05-01

Coanda effect is used in several engineering applications with distinctive designs and structures. It is also applied in aircrafts flying at low speeds for a comfortable ride. In this paper, we have designed and modelled Coanda effect in terms of a flying saucer. The fabrication was done by means of structural and electronic components. Electrical motor was used as a propeller to take off and land vertically (VTOL) along with hovering capability. The rotor disc diameter is smaller than the bulbous body unlike a helicopter which makes to fly very stable. Control flaps were used to regulate the path by altering the flow over the streamlined body. The model was then tested with a remote control. Numerical Simulation of the tesla turbine was done using ANSYS 14.5 software and displacements were obtained by applying different forces on designed model. CATIA V5 was used to analyse the shaft of the model to get minimum value of torque at which the shaft starts to deform.

Time-series modeling and prediction of global monthly absolute temperature for environmental decision making

NASA Astrophysics Data System (ADS)

Ye, Liming; Yang, Guixia; Van Ranst, Eric; Tang, Huajun

2013-03-01

A generalized, structural, time series modeling framework was developed to analyze the monthly records of absolute surface temperature, one of the most important environmental parameters, using a deterministicstochastic combined (DSC) approach. Although the development of the framework was based on the characterization of the variation patterns of a global dataset, the methodology could be applied to any monthly absolute temperature record. Deterministic processes were used to characterize the variation patterns of the global trend and the cyclic oscillations of the temperature signal, involving polynomial functions and the Fourier method, respectively, while stochastic processes were employed to account for any remaining patterns in the temperature signal, involving seasonal autoregressive integrated moving average (SARIMA) models. A prediction of the monthly global surface temperature during the second decade of the 21st century using the DSC model shows that the global temperature will likely continue to rise at twice the average rate of the past 150 years. The evaluation of prediction accuracy shows that DSC models perform systematically well against selected models of other authors, suggesting that DSC models, when coupled with other ecoenvironmental models, can be used as a supplemental tool for short-term (˜10-year) environmental planning and decision making.

Settlement Dynamics and Hierarchy from Agent Decision-Making: a Method Derived from Entropy Maximization.

PubMed

Altaweel, Mark

2015-01-01

This paper presents an agent-based complex system simulation of settlement structure change using methods derived from entropy maximization modeling. The approach is applied to model the movement of people and goods in urban settings to study how settlement size hierarchy develops. While entropy maximization is well known for assessing settlement structure change over different spatiotemporal settings, approaches have rarely attempted to develop and apply this methodology to understand how individual and household decisions may affect settlement size distributions. A new method developed in this paper allows individual decision-makers to chose where to settle based on social-environmental factors, evaluate settlements based on geography and relative benefits, while retaining concepts derived from entropy maximization with settlement size affected by movement ability and site attractiveness feedbacks. To demonstrate the applicability of the theoretical and methodological approach, case study settlement patterns from the Middle Bronze (MBA) and Iron Ages (IA) in the Iraqi North Jazirah Survey (NJS) are used. Results indicate clear differences in settlement factors and household choices in simulations that lead to settlement size hierarchies comparable to the two evaluated periods. Conflict and socio-political cohesion, both their presence and absence, are suggested to have major roles in affecting the observed settlement hierarchy. More broadly, the model is made applicable for different empirically based settings, while being generalized to incorporate data uncertainty, making the model useful for understanding urbanism from top-down and bottom-up perspectives.

Species relationships and divergence times in beeches: new insights from the inclusion of 53 young and old fossils in a birth-death clock model.

PubMed

Renner, S S; Grimm, Guido W; Kapli, Paschalia; Denk, Thomas

2016-07-19

The fossilized birth-death (FBD) model can make use of information contained in multiple fossils representing the same clade, and we here apply this model to infer divergence times in beeches (genus Fagus), using 53 fossils and nuclear sequences for all nine species. We also apply FBD dating to the fern clade Osmundaceae, with about 12 living species and 36 fossils. Fagus nuclear sequences cannot be aligned with those of other Fagaceae, and we therefore use Bayes factors to choose among alternative root positions. The crown group of Fagus is dated to 53 (62-43) Ma; divergence of the sole American species to 44 (51-39) Ma and divergence between Central European F. sylvatica and Eastern Mediterranean F. orientalis to 8.7 (20-1.8) Ma, unexpectedly old. The FBD model can accommodate fossils as sampled ancestors or as extinct or unobserved lineages; however, this makes its raw output, which shows all fossils on short or long branches, problematic to interpret. We use hand-drawn depictions and a bipartition network to illustrate the uncertain placements of fossils. Inferred speciation and extinction rates imply approximately 5× higher evolutionary turnover in Fagus than in Osmundaceae, fitting a hypothesized low turnover in plants adapted to low-nutrient conditions.This article is part of the themed issue 'Dating species divergences using rocks and clocks'. © 2016 The Author(s).

Metaheuristic simulation optimisation for the stochastic multi-retailer supply chain

NASA Astrophysics Data System (ADS)

Omar, Marina; Mustaffa, Noorfa Haszlinna H.; Othman, Siti Norsyahida

2013-04-01

Supply Chain Management (SCM) is an important activity in all producing facilities and in many organizations to enable vendors, manufacturers and suppliers to interact gainfully and plan optimally their flow of goods and services. A simulation optimization approach has been widely used in research nowadays on finding the best solution for decision-making process in Supply Chain Management (SCM) that generally faced a complexity with large sources of uncertainty and various decision factors. Metahueristic method is the most popular simulation optimization approach. However, very few researches have applied this approach in optimizing the simulation model for supply chains. Thus, this paper interested in evaluating the performance of metahueristic method for stochastic supply chains in determining the best flexible inventory replenishment parameters that minimize the total operating cost. The simulation optimization model is proposed based on the Bees algorithm (BA) which has been widely applied in engineering application such as training neural networks for pattern recognition. BA is a new member of meta-heuristics. BA tries to model natural behavior of honey bees in food foraging. Honey bees use several mechanisms like waggle dance to optimally locate food sources and to search new ones. This makes them a good candidate for developing new algorithms for solving optimization problems. This model considers an outbound centralised distribution system consisting of one supplier and 3 identical retailers and is assumed to be independent and identically distributed with unlimited supply capacity at supplier.

Species relationships and divergence times in beeches: new insights from the inclusion of 53 young and old fossils in a birth–death clock model

PubMed Central

Kapli, Paschalia; Denk, Thomas

2016-01-01

The fossilized birth–death (FBD) model can make use of information contained in multiple fossils representing the same clade, and we here apply this model to infer divergence times in beeches (genus Fagus), using 53 fossils and nuclear sequences for all nine species. We also apply FBD dating to the fern clade Osmundaceae, with about 12 living species and 36 fossils. Fagus nuclear sequences cannot be aligned with those of other Fagaceae, and we therefore use Bayes factors to choose among alternative root positions. The crown group of Fagus is dated to 53 (62–43) Ma; divergence of the sole American species to 44 (51–39) Ma and divergence between Central European F. sylvatica and Eastern Mediterranean F. orientalis to 8.7 (20–1.8) Ma, unexpectedly old. The FBD model can accommodate fossils as sampled ancestors or as extinct or unobserved lineages; however, this makes its raw output, which shows all fossils on short or long branches, problematic to interpret. We use hand-drawn depictions and a bipartition network to illustrate the uncertain placements of fossils. Inferred speciation and extinction rates imply approximately 5× higher evolutionary turnover in Fagus than in Osmundaceae, fitting a hypothesized low turnover in plants adapted to low-nutrient conditions. This article is part of the themed issue ‘Dating species divergences using rocks and clocks’. PMID:27325832

A novel computer based expert decision making model for prostate cancer disease management.

PubMed

Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D

2005-12-01

We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42% concordance. This study successfully validated the usefulness of a computer based prostate cancer management decision making model to produce individualized, rational, clinically appropriate disease management decisions without physician bias.

Experimental study and analytical model of deformation of magnetostrictive films as applied to mirrors for x-ray space telescopes.

PubMed

Wang, Xiaoli; Knapp, Peter; Vaynman, S; Graham, M E; Cao, Jian; Ulmer, M P

2014-09-20

The desire for continuously gaining new knowledge in astronomy has pushed the frontier of engineering methods to deliver lighter, thinner, higher quality mirrors at an affordable cost for use in an x-ray observatory. To address these needs, we have been investigating the application of magnetic smart materials (MSMs) deposited as a thin film on mirror substrates. MSMs have some interesting properties that make the application of MSMs to mirror substrates a promising solution for making the next generation of x-ray telescopes. Due to the ability to hold a shape with an impressed permanent magnetic field, MSMs have the potential to be the method used to make light weight, affordable x-ray telescope mirrors. This paper presents the experimental setup for measuring the deformation of the magnetostrictive bimorph specimens under an applied magnetic field, and the analytical and numerical analysis of the deformation. As a first step in the development of tools to predict deflections, we deposited Terfenol-D on the glass substrates. We then made measurements that were compared with the results from the analytical and numerical analysis. The surface profiles of thin-film specimens were measured under an external magnetic field with white light interferometry (WLI). The analytical model provides good predictions of film deformation behavior under various magnetic field strengths. This work establishes a solid foundation for further research to analyze the full three-dimensional deformation behavior of magnetostrictive thin films.

25 CFR 516.2 - When may a person to whom this part applies give testimony, make a statement or submit to interview?

Code of Federal Regulations, 2010 CFR

2010-04-01

... testimony, make a statement or submit to interview? 516.2 Section 516.2 Indians NATIONAL INDIAN GAMING... whom this part applies give testimony, make a statement or submit to interview? (a) No person to whom... regulation, shall provide testimony, make a statement or submit to interview. (b) Whenever a subpoena...

The application of sensitivity analysis to models of large scale physiological systems

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1974-01-01

A survey of the literature of sensitivity analysis as it applies to biological systems is reported as well as a brief development of sensitivity theory. A simple population model and a more complex thermoregulatory model illustrate the investigatory techniques and interpretation of parameter sensitivity analysis. The role of sensitivity analysis in validating and verifying models, and in identifying relative parameter influence in estimating errors in model behavior due to uncertainty in input data is presented. This analysis is valuable to the simulationist and the experimentalist in allocating resources for data collection. A method for reducing highly complex, nonlinear models to simple linear algebraic models that could be useful for making rapid, first order calculations of system behavior is presented.

Mathematical modeling and simulation of aquatic and aerial animal locomotion

NASA Astrophysics Data System (ADS)

Hou, T. Y.; Stredie, V. G.; Wu, T. Y.

2007-08-01

In this paper, we investigate the locomotion of fish and birds by applying a new unsteady, flexible wing theory that takes into account the strong nonlinear dynamics semi-analytically. We also make extensive comparative study between the new approach and the modified vortex blob method inspired from Chorin's and Krasny's work. We first implement the modified vortex blob method for two examples and then discuss the numerical implementation of the nonlinear analytical mathematical model of Wu. We will demonstrate that Wu's method can capture the nonlinear effects very well by applying it to some specific cases and by comparing with the experiments available. In particular, we apply Wu's method to analyze Wagner's result for a wing abruptly undergoing an increase in incidence angle. Moreover, we study the vorticity generated by a wing in heaving, pitching and bending motion. In both cases, we show that the new method can accurately represent the vortex structure behind a flying wing and its influence on the bound vortex sheet on the wing.

Predictive models in cancer management: A guide for clinicians.

PubMed

Kazem, Mohammed Ali

2017-04-01

Predictive tools in cancer management are used to predict different outcomes including survival probability or risk of recurrence. The uptake of these tools by clinicians involved in cancer management has not been as common as other clinical tools, which may be due to the complexity of some of these tools or a lack of understanding of how they can aid decision-making in particular clinical situations. The aim of this article is to improve clinicians' knowledge and understanding of predictive tools used in cancer management, including how they are built, how they can be applied to medical practice, and what their limitations may be. Literature review was conducted to investigate the role of predictive tools in cancer management. All predictive models share similar characteristics, but depending on the type of the tool its ability to predict an outcome will differ. Each type has its own pros and cons, and its generalisability will depend on the cohort used to build the tool. These factors will affect the clinician's decision whether to apply the model to their cohort or not. Before a model is used in clinical practice, it is important to appreciate how the model is constructed, what its use may add over and above traditional decision-making tools, and what problems or limitations may be associated with it. Understanding all the above is an important step for any clinician who wants to decide whether or not use predictive tools in their practice. Copyright © 2016 Royal College of Surgeons of Edinburgh (Scottish charity number SC005317) and Royal College of Surgeons in Ireland. Published by Elsevier Ltd. All rights reserved.

A Unified Statistical Rain-Attenuation Model for Communication Link Fade Predictions and Optimal Stochastic Fade Control Design Using a Location-Dependent Rain-Statistic Database

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1990-01-01

A static and dynamic rain-attenuation model is presented which describes the statistics of attenuation on an arbitrarily specified satellite link for any location for which there are long-term rainfall statistics. The model may be used in the design of the optimal stochastic control algorithms to mitigate the effects of attenuation and maintain link reliability. A rain-statistics data base is compiled, which makes it possible to apply the model to any location in the continental U.S. with a resolution of 0-5 degrees in latitude and longitude. The model predictions are compared with experimental observations, showing good agreement.

The UK Earth System Model project

NASA Astrophysics Data System (ADS)

Tang, Yongming

2016-04-01

In this talk we will describe the development and current status of the UK Earth System Model (UKESM). This project is a NERC/Met Office collaboration and has two objectives; to develop and apply a world-leading Earth System Model, and to grow a community of UK Earth System Model scientists. We are building numerical models that include all the key components of the global climate system, and contain the important process interactions between global biogeochemistry, atmospheric chemistry and the physical climate system. UKESM will be used to make key CMIP6 simulations as well as long-time (e.g. millennium) simulations, large ensemble experiments and investigating a range of future carbon emission scenarios.

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

PubMed

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

2015-06-01

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

Thermodynamic view on decision-making process: emotions as a potential power vector of realization of the choice.

PubMed

Pakhomov, Anton; Sudin, Natalya

2013-12-01

This research is devoted to possible mechanisms of decision-making in frames of thermodynamic principles. It is also shown that the decision-making system in reply to emotion includes vector component which seems to be often a necessary condition to transfer system from one state to another. The phases of decision-making system can be described as supposed to be nonequilibrium and irreversible to which thermodynamics laws are applied. The mathematical model of a decision choice, proceeding from principles of the nonlinear dynamics considering instability of movement and bifurcation is offered. The thermodynamic component of decision-making process on the basis of vector transfer of energy induced by emotion at the given time is surveyed. It is proposed a three-modular model of decision making based on principles of thermodynamics. Here it is suggested that at entropy impact due to effect of emotion, on the closed system-the human brain,-initially arises chaos, then after fluctuations of possible alternatives which were going on-reactions of brain zones in reply to external influence, an order is forming and there is choice of alternatives, according to primary entrance conditions and a state of the closed system. Entropy calculation of a choice expectation of negative and positive emotion shows judgment possibility of existence of "the law of emotion conservation" in accordance with several experimental data.

Networks and games for precision medicine.

PubMed

Biane, Célia; Delaplace, Franck; Klaudel, Hanna

2016-12-01

Recent advances in omics technologies provide the leverage for the emergence of precision medicine that aims at personalizing therapy to patient. In this undertaking, computational methods play a central role for assisting physicians in their clinical decision-making by combining data analysis and systems biology modelling. Complex diseases such as cancer or diabetes arise from the intricate interplay of various biological molecules. Therefore, assessing drug efficiency requires to study the effects of elementary perturbations caused by diseases on relevant biological networks. In this paper, we propose a computational framework called Network-Action Game applied to best drug selection problem combining Game Theory and discrete models of dynamics (Boolean networks). Decision-making is modelled using Game Theory that defines the process of drug selection among alternative possibilities, while Boolean networks are used to model the effects of the interplay between disease and drugs actions on the patient's molecular system. The actions/strategies of disease and drugs are focused on arc alterations of the interactome. The efficiency of this framework has been evaluated for drug prediction on a model of breast cancer signalling. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Method for optimizing resource allocation in a government organization. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Afarin, James

1994-01-01

The managers in Federal agencies are challenged to control the extensive activities in government and still provide high-quality products and services to the American taxpayers. Considering today's complex social and economic environment and the $3.8 billion daily cost of operating the Federal Government, it is evident that there is a need to develop decision-making tools for accurate resource allocation and total quality management. The goal of this thesis is to provide a methodical process that will aid managers in Federal Government to make budgetary decisions based on the cost of services, the agency's objectives, and the customers' perception of the agency's product. A general resource allocation procedure was developed in this study that can be applied to any government organization. A government organization, hereafter the 'organization,' is assumed to be a multidivision enterprise. This procedure was applied to a small organization for the proof of the concept. This organization is the Technical Services Directorate (TSD) at the NASA Lewis Research Center in Cleveland, Ohio. As part of the procedure, a nonlinear programming model was developed to account for the resources of the organization, the outputs produced by the organization, the decision-maker's views, and the customers' satisfaction with the organization. The information on the resources of the organization was acquired from current budget levels of the organization and the human resources assigned to the divisions. The outputs of the organization were defined and measured by identifying metrics that assess the outputs, the most challenging task in this study. The decision-maker's views are represented in the model as weights assigned to the various outputs and were quantified by using the analytic hierarchy process. The customer's opinions regarding the outputs of the organization were collected through questionnaires that were designed for each division individually. Following the philosophy of total quality management, information on customers' satisfaction is presented in the model as the quality of output. The model is a nonlinear one whose objective is to maximize customers' satisfaction such that the total cost of operation does not exceed the organization's budget. This model represents a structured approach or policy mechanism, at the agency level, to make capital investment decisions based on the priorities of the agency and the quality of outputs. This procedure applied to TSD resulted in a resources allocation scheme that was reasonable and acceptable to the decision-makers and, as expected, dependent on the assumptions and accuracy of the data used in the model.

Developing Viable Financing Models for Space Tourism

NASA Astrophysics Data System (ADS)

Eilingsfeld, F.; Schaetzler, D.

2002-01-01

Increasing commercialization of space services and the impending release of government's control of space access promise to make space ventures more attractive. Still, many investors shy away from going into the space tourism market as long as they do not feel secure that their return expectations will be met. First and foremost, attracting investors from the capital markets requires qualifying financing models. Based on earlier research on the cost of capital for space tourism, this paper gives a brief run-through of commercial, technical and financial due diligence aspects. After that, a closer look is taken at different valuation techniques as well as alternative ways of streamlining financials. Experience from earlier ventures has shown that the high cost of capital represents a significant challenge. Thus, the sophistication and professionalism of business plans and financial models needs to be very high. Special emphasis is given to the optimization of the debt-to-equity ratio over time. The different roles of equity and debt over a venture's life cycle are explained. Based on the latter, guidelines for the design of an optimized loan structure are given. These are then applied to simulating the financial performance of a typical space tourism venture over time, including the calculation of Weighted Average Cost of Capital (WACC) and Net Present Value (NPV). Based on a concluding sensitivity analysis, the lessons learned are presented. If applied properly, these will help to make space tourism economically viable.

Model unification and scale-adaptivity in the Eddy-Diffusivity Mass-Flux (EDMF) approach

NASA Astrophysics Data System (ADS)

Neggers, R.; Siebesma, P.

2011-12-01

It has long been understood that the turbulent-convective transport of heat, moisture and momentum plays an important role in the dynamics and climate of the earth's atmosphere. Accordingly, the representation of these processes in General Circulation Models (GCMs) has always been an active research field. Turbulence and convection act on temporal and spatial scales that are unresolved by most present-day GCMs, and have to be represented through parametric relations. Over the years a variety of schemes has been successfully developed. Although differing widely in their details, only two basic transport models stand at the basis of most of these schemes. The first is the diffusive transport model, which can only act down-gradient. An example is the turbulent mixing at small scales. The second is the advective transport model, which can act both down-gradient and counter-gradient. A good example is the transport of heat and moisture by convective updrafts that overshoot into stable layers of air. In practice, diffusive models often make use of a K-profile method or a prognostic TKE budget, while advective models make use of a rising (and entraining) plume budget. While most transport schemes classicaly apply either the diffusive model or advective model, the relatively recently introduced Eddy-Diffusivity Mass-Flux (EDMF) approach aims to combine both techniques. By applying advection and diffusion simultaneously, one can make use of the benefits of both approaches. Since its emergence about a decade ago, the EDMF approach has been successfully applied in both research and operational circulation models. This presentation is dedicated to the EDMF framework. Apart from a short introduction to the EDMF concept and a short overview of its current implementations, our main goal is to elaborate on the opportunities EDMF brings in addressing some long-standing problems in the parameterization of turbulent-convective transport. The first problem is the need for a unified approach in the parameterization of distinct transport regimes. The main objections to a separate representation of regimes are i) artificially discrete regime-transitions, and ii) superfluous and intransparent coding. For a unified approach we need to establish what complexity is sufficient to achieve general applicability. We argue that adding only little complexity already enables the standard EDMF framework to represent multiple boundary-layer transport regimes and smooth transitions between those. The second long-standing problem is that the ever increasing computational capacity and speed has lead to increasingly fine discretizations in GCMs, which requires scale-adaptivity in a sub-grid transport model. It is argued that a flexible partitioning between advection and diffusion within EDMF, as well as the potential to introduce stochastic elements in the advective part of EDMF, creates opportunities to introduce such adaptivity. In the final part of the presentation we will attempt to give an overview of currently ongoing developments of the EDMF framework, both concerning model formulation as well as evaluation efforts of key assumptions against observational datasets and large-eddy simulation results.

An Agent-based Model for Groundwater Allocation and Management at the Bakken Shale in Western North Dakota

NASA Astrophysics Data System (ADS)

Lin, T.; Lin, Z.; Lim, S.

2017-12-01

We present an integrated modeling framework to simulate groundwater level change under the dramatic increase of hydraulic fracturing water use in the Bakken Shale oil production area. The framework combines the agent-based model (ABM) with the Fox Hills-Hell Creek (FH-HC) groundwater model. In development of the ABM, institution theory is used to model the regulation policies from the North Dakota State Water Commission, while evolutionary programming and cognitive maps are used to model the social structure that emerges from the behavior of competing individual water businesses. Evolutionary programming allows individuals to select an appropriate strategy when annually applying for potential water use permits; whereas cognitive maps endow agent's ability and willingness to compete for more water sales. All agents have their own influence boundaries that inhibit their competitive behavior toward their neighbors but not to non-neighbors. The decision-making process is constructed and parameterized with both quantitative and qualitative information, i.e., empirical water use data and knowledge gained from surveys with stakeholders. By linking institution theory, evolutionary programming, and cognitive maps, our approach addresses a higher complexity of the real decision making process. Furthermore, this approach is a new exploration for modeling the dynamics of Coupled Human and Natural System. After integrating ABM with the FH-HC model, drought and limited water accessibility scenarios are simulated to predict FH-HC ground water level changes in the future. The integrated modeling framework of ABM and FH-HC model can be used to support making scientifically sound policies in water allocation and management.

Decision insight into stakeholder conflict for ERN.

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

Siirola, John; Tidwell, Vincent Carroll; Benz, Zachary O.

Participatory modeling has become an important tool in facilitating resource decision making and dispute resolution. Approaches to modeling that are commonly used in this context often do not adequately account for important human factors. Current techniques provide insights into how certain human activities and variables affect resource outcomes; however, they do not directly simulate the complex variables that shape how, why, and under what conditions different human agents behave in ways that affect resources and human interactions related to them. Current approaches also do not adequately reveal how the effects of individual decisions scale up to have systemic level effectsmore » in complex resource systems. This lack of integration prevents the development of more robust models to support decision making and dispute resolution processes. Development of integrated tools is further hampered by the fact that collection of primary data for decision-making modeling is costly and time consuming. This project seeks to develop a new approach to resource modeling that incorporates both technical and behavioral modeling techniques into a single decision-making architecture. The modeling platform is enhanced by use of traditional and advanced processes and tools for expedited data capture. Specific objectives of the project are: (1) Develop a proof of concept for a new technical approach to resource modeling that combines the computational techniques of system dynamics and agent based modeling, (2) Develop an iterative, participatory modeling process supported with traditional and advance data capture techniques that may be utilized to facilitate decision making, dispute resolution, and collaborative learning processes, and (3) Examine potential applications of this technology and process. The development of this decision support architecture included both the engineering of the technology and the development of a participatory method to build and apply the technology. Stakeholder interaction with the model and associated data capture was facilitated through two very different modes of engagement, one a standard interface involving radio buttons, slider bars, graphs and plots, while the other utilized an immersive serious gaming interface. The decision support architecture developed through this project was piloted in the Middle Rio Grande Basin to examine how these tools might be utilized to promote enhanced understanding and decision-making in the context of complex water resource management issues. Potential applications of this architecture and its capacity to lead to enhanced understanding and decision-making was assessed through qualitative interviews with study participants who represented key stakeholders in the basin.« less

Accelerating quality improvement within your organization: Applying the Model for Improvement.

PubMed

Crowl, Ashley; Sharma, Anita; Sorge, Lindsay; Sorensen, Todd

2015-01-01

To discuss the fundamentals of the Model for Improvement and how the model can be applied to quality improvement activities associated with medication use, including understanding the three essential questions that guide quality improvement, applying a process for actively testing change within an organization, and measuring the success of these changes on care delivery. PubMed from 1990 through April 2014 using the search terms quality improvement, process improvement, hospitals, and primary care. At the authors' discretion, studies were selected based on their relevance in demonstrating the quality improvement process and tests of change within an organization. Organizations are continuously seeking to enhance quality in patient care services, and much of this work focuses on improving care delivery processes. Yet change in these systems is often slow, which can lead to frustration or apathy among frontline practitioners. Adopting and applying the Model for Improvement as a core strategy for quality improvement efforts can accelerate the process. While the model is frequently well known in hospitals and primary care settings, it is not always familiar to pharmacists. In addition, while some organizations may be familiar with the "plan, do, study, act" (PDSA) cycles-one element of the Model for Improvement-many do not apply it effectively. The goal of the model is to combine a continuous process of small tests of change (PDSA cycles) within an overarching aim with a longitudinal measurement process. This process differs from other forms of improvement work that plan and implement large-scale change over an extended period, followed by months of data collection. In this scenario it may take months or years to determine whether an intervention will have a positive impact. By following the Model for Improvement, frontline practitioners and their organizational leaders quickly identify strategies that make a positive difference and result in a greater degree of success.

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.

The information-anchoring model of first offers: When moving first helps versus hurts negotiators.

PubMed

Loschelder, David D; Trötschel, Roman; Swaab, Roderick I; Friese, Malte; Galinsky, Adam D

2016-07-01

Does making the first offer increase or impair a negotiator's outcomes? Past research has found evidence supporting both claims. To reconcile these contradictory findings, we developed and tested an integrative model-the Information-Anchoring Model of First Offers. The model predicts when and why making the first offer helps versus hurts. We suggest that first offers have 2 effects. First, they serve as anchors that pull final settlements toward the initial first-offer value; this anchor function often produces a first-mover advantage. Second, first offers can convey information on the senders' priorities, which makes the sender vulnerable to exploitation and increases the risk of a first-mover disadvantage. To test this model, 3 experiments manipulated the information that senders communicated in their first offer. When senders did not reveal their priorities, the first-mover advantage was replicated. However, when first offers revealed senders' priorities explicitly, implicitly, or both, a first-mover disadvantage emerged. Negotiators' social value orientation moderated this effect: A first-mover disadvantage occurred when senders faced proself recipients who exploited priority information, but not with prosocial recipients. Moderated mediation analyses supported the model assumptions: Proself recipients used their integrative insight to feign priorities in their low-priority issues and thereby claimed more individual value than senders. The final discussion reviews theoretical and applied implications of the Information-Anchoring Model of First Offers. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Short communication: Prediction of retention pay-off using a machine learning algorithm.

PubMed

Shahinfar, Saleh; Kalantari, Afshin S; Cabrera, Victor; Weigel, Kent

2014-05-01

Replacement decisions have a major effect on dairy farm profitability. Dynamic programming (DP) has been widely studied to find the optimal replacement policies in dairy cattle. However, DP models are computationally intensive and might not be practical for daily decision making. Hence, the ability of applying machine learning on a prerun DP model to provide fast and accurate predictions of nonlinear and intercorrelated variables makes it an ideal methodology. Milk class (1 to 5), lactation number (1 to 9), month in milk (1 to 20), and month of pregnancy (0 to 9) were used to describe all cows in a herd in a DP model. Twenty-seven scenarios based on all combinations of 3 levels (base, 20% above, and 20% below) of milk production, milk price, and replacement cost were solved with the DP model, resulting in a data set of 122,716 records, each with a calculated retention pay-off (RPO). Then, a machine learning model tree algorithm was used to mimic the evaluated RPO with DP. The correlation coefficient factor was used to observe the concordance of RPO evaluated by DP and RPO predicted by the model tree. The obtained correlation coefficient was 0.991, with a corresponding value of 0.11 for relative absolute error. At least 100 instances were required per model constraint, resulting in 204 total equations (models). When these models were used for binary classification of positive and negative RPO, error rates were 1% false negatives and 9% false positives. Applying this trained model from simulated data for prediction of RPO for 102 actual replacement records from the University of Wisconsin-Madison dairy herd resulted in a 0.994 correlation with 0.10 relative absolute error rate. Overall results showed that model tree has a potential to be used in conjunction with DP to assist farmers in their replacement decisions. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Modeling Infrared Signal Reflections to Characterize Indoor Multipath Propagation

PubMed Central

De-La-Llana-Calvo, Álvaro; Lázaro-Galilea, José Luis; Gardel-Vicente, Alfredo; Rodríguez-Navarro, David; Bravo-Muñoz, Ignacio; Tsirigotis, Georgios; Iglesias-Miguel, Juan

2017-01-01

In this paper, we propose a model to characterize Infrared (IR) signal reflections on any kind of surface material, together with a simplified procedure to compute the model parameters. The model works within the framework of Local Positioning Systems (LPS) based on IR signals (IR-LPS) to evaluate the behavior of transmitted signal Multipaths (MP), which are the main cause of error in IR-LPS, and makes several contributions to mitigation methods. Current methods are based on physics, optics, geometry and empirical methods, but these do not meet our requirements because of the need to apply several different restrictions and employ complex tools. We propose a simplified model based on only two reflection components, together with a method for determining the model parameters based on 12 empirical measurements that are easily performed in the real environment where the IR-LPS is being applied. Our experimental results show that the model provides a comprehensive solution to the real behavior of IR MP, yielding small errors when comparing real and modeled data (the mean error ranges from 1% to 4% depending on the environment surface materials). Other state-of-the-art methods yielded mean errors ranging from 15% to 40% in test measurements. PMID:28406436

A componential model of human interaction with graphs: 1. Linear regression modeling

NASA Technical Reports Server (NTRS)

Gillan, Douglas J.; Lewis, Robert

1994-01-01

Task analyses served as the basis for developing the Mixed Arithmetic-Perceptual (MA-P) model, which proposes (1) that people interacting with common graphs to answer common questions apply a set of component processes-searching for indicators, encoding the value of indicators, performing arithmetic operations on the values, making spatial comparisons among indicators, and repsonding; and (2) that the type of graph and user's task determine the combination and order of the components applied (i.e., the processing steps). Two experiments investigated the prediction that response time will be linearly related to the number of processing steps according to the MA-P model. Subjects used line graphs, scatter plots, and stacked bar graphs to answer comparison questions and questions requiring arithmetic calculations. A one-parameter version of the model (with equal weights for all components) and a two-parameter version (with different weights for arithmetic and nonarithmetic processes) accounted for 76%-85% of individual subjects' variance in response time and 61%-68% of the variance taken across all subjects. The discussion addresses possible modifications in the MA-P model, alternative models, and design implications from the MA-P model.

Data to Decisions: Creating a Culture of Model-Driven Drug Discovery.

PubMed

Brown, Frank K; Kopti, Farida; Chang, Charlie Zhenyu; Johnson, Scott A; Glick, Meir; Waller, Chris L

2017-09-01

Merck & Co., Inc., Kenilworth, NJ, USA, is undergoing a transformation in the way that it prosecutes R&D programs. Through the adoption of a "model-driven" culture, enhanced R&D productivity is anticipated, both in the form of decreased attrition at each stage of the process and by providing a rational framework for understanding and learning from the data generated along the way. This new approach focuses on the concept of a "Design Cycle" that makes use of all the data possible, internally and externally, to drive decision-making. These data can take the form of bioactivity, 3D structures, genomics, pathway, PK/PD, safety data, etc. Synthesis of high-quality data into models utilizing both well-established and cutting-edge methods has been shown to yield high confidence predictions to prioritize decision-making and efficiently reposition resources within R&D. The goal is to design an adaptive research operating plan that uses both modeled data and experiments, rather than just testing, to drive project decision-making. To support this emerging culture, an ambitious information management (IT) program has been initiated to implement a harmonized platform to facilitate the construction of cross-domain workflows to enable data-driven decision-making and the construction and validation of predictive models. These goals are achieved through depositing model-ready data, agile persona-driven access to data, a unified cross-domain predictive model lifecycle management platform, and support for flexible scientist-developed workflows that simplify data manipulation and consume model services. The end-to-end nature of the platform, in turn, not only supports but also drives the culture change by enabling scientists to apply predictive sciences throughout their work and over the lifetime of a project. This shift in mindset for both scientists and IT was driven by an early impactful demonstration of the potential benefits of the platform, in which expert-level early discovery predictive models were made available from familiar desktop tools, such as ChemDraw. This was built using a workflow-driven service-oriented architecture (SOA) on top of the rigorous registration of all underlying model entities.

Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats.

PubMed

Hales, Claire A; Robinson, Emma S J; Houghton, Conor J

2016-01-01

Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142), and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward.

Assessing the fit of site-occupancy models

USGS Publications Warehouse

MacKenzie, D.I.; Bailey, L.L.

2004-01-01

Few species are likely to be so evident that they will always be detected at a site when present. Recently a model has been developed that enables estimation of the proportion of area occupied, when the target species is not detected with certainty. Here we apply this modeling approach to data collected on terrestrial salamanders in the Plethodon glutinosus complex in the Great Smoky Mountains National Park, USA, and wish to address the question 'how accurately does the fitted model represent the data?' The goodness-of-fit of the model needs to be assessed in order to make accurate inferences. This article presents a method where a simple Pearson chi-square statistic is calculated and a parametric bootstrap procedure is used to determine whether the observed statistic is unusually large. We found evidence that the most global model considered provides a poor fit to the data, hence estimated an overdispersion factor to adjust model selection procedures and inflate standard errors. Two hypothetical datasets with known assumption violations are also analyzed, illustrating that the method may be used to guide researchers to making appropriate inferences. The results of a simulation study are presented to provide a broader view of the methods properties.

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

PubMed Central

Mohaidin, Zurina

2017-01-01

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

Modeling as an Anchoring Scientific Practice for Explaining Friction Phenomena

NASA Astrophysics Data System (ADS)

Neilson, Drew; Campbell, Todd

2017-12-01

Through examining the day-to-day work of scientists, researchers in science studies have revealed how models are a central sense-making practice of scientists as they construct and critique explanations about how the universe works. Additionally, they allow predictions to be made using the tenets of the model. Given this, alongside research suggesting that engaging students in developing and using models can have a positive effect on learning in science classrooms, the recent national standards documents in science education have identified developing and using models as an important practice students should engage in as they apply and refine their ideas with peers and teachers in explaining phenomena or solving problems in classrooms. This article details how students can be engaged in developing and using models to help them make sense of friction phenomena in a high school conceptual physics classroom in ways that align with visions for teaching and learning outlined in the Next Generation Science Standards. This particular unit has been refined over several years to build on what was initially an inquiry-based unit we have described previously. In this latest iteration of the friction unit, students developed and refined models through engaging in small group and whole class discussions and investigations.

Theory, development, and applicability of the surface water hydrologic model CASC2D

NASA Astrophysics Data System (ADS)

Downer, Charles W.; Ogden, Fred L.; Martin, William D.; Harmon, Russell S.

2002-02-01

Numerical tests indicate that Hortonian runoff mechanisms benefit from scaling effects that non-Hortonian runoff mechanisms do not share. This potentially makes Hortonian watersheds more amenable to physically based modelling provided that the physically based model employed properly accounts for rainfall distribution and initial soil moisture conditions, to which these types of model are highly sensitive. The distributed Hortonian runoff model CASC2D has been developed and tested for the US Army over the past decade. The purpose of the model is to provide the Army with superior predictions of runoff and stream-flow compared with the standard lumped parameter model HEC-1. The model is also to be used to help minimize negative effects on the landscape caused by US armed forces training activities. Development of the CASC2D model is complete and the model has been tested and applied at several locations. These applications indicate that the model can realistically reproduce hydrographs when properly applied. These applications also indicate that there may be many situations where the model is inadequate. Because of this, the Army is pursuing development of a new model, GSSHA, that will provide improved numerical stability and incorporate additional stream-flow-producing mechanisms and improved hydraulics.

Robust Mosaicking of Stereo Digital Elevation Models from the Ames Stereo Pipeline

NASA Technical Reports Server (NTRS)

Kim, Tae Min; Moratto, Zachary M.; Nefian, Ara Victor

2010-01-01

Robust estimation method is proposed to combine multiple observations and create consistent, accurate, dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce higher-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data than is currently possible. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. However, the DEMs currently produced by the ASP often contain errors and inconsistencies due to image noise, shadows, etc. The proposed method addresses this problem by making use of multiple observations and by considering their goodness of fit to improve both the accuracy and robustness of the estimate. The stepwise regression method is applied to estimate the relaxed weight of each observation.

Assessing neural activity related to decision-making through flexible odds ratio curves and their derivatives.

PubMed

Roca-Pardiñas, Javier; Cadarso-Suárez, Carmen; Pardo-Vazquez, Jose L; Leboran, Victor; Molenberghs, Geert; Faes, Christel; Acuña, Carlos

2011-06-30

It is well established that neural activity is stochastically modulated over time. Therefore, direct comparisons across experimental conditions and determination of change points or maximum firing rates are not straightforward. This study sought to compare temporal firing probability curves that may vary across groups defined by different experimental conditions. Odds-ratio (OR) curves were used as a measure of comparison, and the main goal was to provide a global test to detect significant differences of such curves through the study of their derivatives. An algorithm is proposed that enables ORs based on generalized additive models, including factor-by-curve-type interactions to be flexibly estimated. Bootstrap methods were used to draw inferences from the derivatives curves, and binning techniques were applied to speed up computation in the estimation and testing processes. A simulation study was conducted to assess the validity of these bootstrap-based tests. This methodology was applied to study premotor ventral cortex neural activity associated with decision-making. The proposed statistical procedures proved very useful in revealing the neural activity correlates of decision-making in a visual discrimination task. Copyright © 2011 John Wiley & Sons, Ltd.

Monitoring and Simulating Water, Carbon and Nitrogen Dynamics over Catchments in Eastern Asia

NASA Astrophysics Data System (ADS)

Wang, Q.; Xiao, Q.; Liu, C.; Watanabe, M.

2006-05-01

There is an emergency need to support decision-making in water environment management in Eastern Asia. For sound management and decision making of sustainable water use, the catchment ecosystem assessment, emphasizing biophysical and biogeochemical processes and human interactions, is a key task. For this task, an integrated ecosystem model has been developed to estimate the spatial and temporal distributions of the water, carbon and nutrient cycles over catchment scales. The model integrated both a distributed hydrologic model (Nakayama and Watanabe, 2004) and an ecosystem model, BIOME-BGC (Running and Coughlan, 1988), which has been modified and validated for various ecosystems by using the APEIS-FLUX datasets in China (Wang and Watanabe, 2005). The model has been applied to catchments in China, such as the Changjiang River and the Yellow River. The MODIS satellite data products, such as leaf area index (LAI), vegetation index (VI) and land surface temperature (LST) were used as the input parameters. By using the integrated model, the future changes in water, carbon and nitrogen cycle can be predicted based on scenarios, such as the decrease in crop production due to water shortage, and the increase in temperature and CO2 concentration, as well as the land use/cover changes. The model was validated by the measured values of soil moisture, and river flow discharge throughout the year, showing that this model achieves a fairly high accuracy. As an example, we applied the integrated model to simulate the daily water vapor, carbon and nitrogen fluxes over the Changjiang River Basin. The Changjiang River is ranked third in length and is the largest river in terms of water discharge over the Euro-Asian continent. The drainage basin of the Changjiang supplies 5-10% of the total world population with water resources and nutrition and irrigates 40% of China's national crop production. Moreover, the materials carried by the Changjiang River have a significant influence on the coastal environment. Simulation results showed that enhanced atmospheric CO2 concentrations and especially increased nitrogen application had a marked effect on the simulated water and carbon sequestration capacity and played a prominent role in increasing this capacity. Finally, the model has been applied to evaluate the impact of land cover change from 1980 to 2000 on water, carbon and nitrogen fluxes over larger river basins in China.

Item Randomized-Response Models for Measuring Noncompliance: Risk-Return Perceptions, Social Influences, and Self-Protective Responses

ERIC Educational Resources Information Center

Bockenholt, Ulf; Van Der Heijden, Peter G. M.

2007-01-01

Randomized response (RR) is a well-known method for measuring sensitive behavior. Yet this method is not often applied because: (i) of its lower efficiency and the resulting need for larger sample sizes which make applications of RR costly; (ii) despite its privacy-protection mechanism the RR design may not be followed by every respondent; and…

Developing Army Leaders through Increased Rigor in Professional Military Training and Education

DTIC Science & Technology

2017-06-09

leadership. Research Methodology An applied, exploratory, qualitative research methodology via a structured and focused case study comparison was...research methodology via a structured and focused case study comparison. Finally, it will discuss how the methodology will be conducted to make...development models; it serves as the base data for case study comparison. 48 Research Methodology and Data Analysis A qualitative research

An expert judgment model applied to estimating the safety effect of a bicycle facility.

PubMed

Leden, L; Gårder, P; Pulkkinen, U

2000-07-01

This paper presents a risk index model that can be used for assessing the safety effect of countermeasures. The model estimates risk in a multiplicative way, which makes it possible to analyze the impact of different factors separately. Expert judgments are incorporated through a Bayesian error model. The variance of the risk estimate is determined by Monte-Carlo simulation. The model was applied to assess the safety effect of a new design of a bicycle crossing. The intent was to gain safety by raising the crossings to reduce vehicle speeds and by making the crossings more visible by painting them in a bright color. Before the implementations, bicyclists were riding on bicycle crossings of conventional Swedish type, i.e. similar to crosswalks but delineated by white squares rather than solid lines or zebra markings. Automobile speeds were reduced as anticipated. However, it seems as if the positive effect of this was more or less canceled out by increased bicycle speeds. The safety per bicyclist was still improved by approximately 20%. This improvement was primarily caused by an increase in bicycle flow, since the data show that more bicyclists at a given location seem to benefit their safety. The increase in bicycle flow was probably caused by the new layout of the crossings since bicyclists perceived them as safer and causing less delay. Some future development work is suggested. Pros and cons with the used methodology are discussed. The most crucial parameter to be added is probably a model describing the interaction between motorists and bicyclists, for example, how risk is influenced by the lateral position of the bicyclist in relation to the motorist. It is concluded that the interaction seems to be optimal when both groups share the roadway.

Application of decentralized cooperative problem solving in dynamic flexible scheduling

NASA Astrophysics Data System (ADS)

Guan, Zai-Lin; Lei, Ming; Wu, Bo; Wu, Ya; Yang, Shuzi

1995-08-01

The object of this study is to discuss an intelligent solution to the problem of task-allocation in shop floor scheduling. For this purpose, the technique of distributed artificial intelligence (DAI) is applied. Intelligent agents (IAs) are used to realize decentralized cooperation, and negotiation is realized by using message passing based on the contract net model. Multiple agents, such as manager agents, workcell agents, and workstation agents, make game-like decisions based on multiple criteria evaluations. This procedure of decentralized cooperative problem solving makes local scheduling possible. And by integrating such multiple local schedules, dynamic flexible scheduling for the whole shop floor production can be realized.

[The role of gut instinct is an important subject].

PubMed

Snoek, Jos W

2010-01-01

The role of gut instinct in general practice is an important topic. The reliance on gut instinct by experienced doctors is thought to be a form of intuitive decision-making which fits in with System 1 processes in the dual process model in higher cognition. Special mention is made of the theories on intuitive decision-making by the famous Dutch psychologist De Groot, who, when investigating thought processes of chess masters more than half a century ago, developed a fundamental theory on intuitive heuristics. Further studies on the determinants and conditions under which heuristics, such as the reliance on gut instinct, are applied in clinical practice are very welcome.

Laser-Induced-Emission Spectroscopy In Hg/Ar Discharge

NASA Technical Reports Server (NTRS)

Maleki, Lutfollah; Blasenheim, Barry J.; Janik, Gary R.

1992-01-01

Laser-induced-emission (LIE) spectroscopy used to probe low-pressure mercury/argon discharge to determine influence of mercury atoms in metastable 6(Sup3)P(Sub2) state on emission of light from discharge. LIE used to study all excitation processes affected by metastable population, including possible effects on excitation of atoms, ions, and buffer gas. Technique applied to emissions of other plasmas. Provides data used to make more-accurate models of such emissions, exploited by lighting and laser industries and by laboratories studying discharges. Also useful in making quantitative measurements of relative rates and cross sections of direct and two-step collisional processes involving metastable level.

Linear and evolutionary polynomial regression models to forecast coastal dynamics: Comparison and reliability assessment

NASA Astrophysics Data System (ADS)

Bruno, Delia Evelina; Barca, Emanuele; Goncalves, Rodrigo Mikosz; de Araujo Queiroz, Heithor Alexandre; Berardi, Luigi; Passarella, Giuseppe

2018-01-01

In this paper, the Evolutionary Polynomial Regression data modelling strategy has been applied to study small scale, short-term coastal morphodynamics, given its capability for treating a wide database of known information, non-linearly. Simple linear and multilinear regression models were also applied to achieve a balance between the computational load and reliability of estimations of the three models. In fact, even though it is easy to imagine that the more complex the model, the more the prediction improves, sometimes a "slight" worsening of estimations can be accepted in exchange for the time saved in data organization and computational load. The models' outcomes were validated through a detailed statistical, error analysis, which revealed a slightly better estimation of the polynomial model with respect to the multilinear model, as expected. On the other hand, even though the data organization was identical for the two models, the multilinear one required a simpler simulation setting and a faster run time. Finally, the most reliable evolutionary polynomial regression model was used in order to make some conjecture about the uncertainty increase with the extension of extrapolation time of the estimation. The overlapping rate between the confidence band of the mean of the known coast position and the prediction band of the estimated position can be a good index of the weakness in producing reliable estimations when the extrapolation time increases too much. The proposed models and tests have been applied to a coastal sector located nearby Torre Colimena in the Apulia region, south Italy.

Mapping urban environmental noise: a land use regression method.

PubMed

Xie, Dan; Liu, Yi; Chen, Jining

2011-09-01

Forecasting and preventing urban noise pollution are major challenges in urban environmental management. Most existing efforts, including experiment-based models, statistical models, and noise mapping, however, have limited capacity to explain the association between urban growth and corresponding noise change. Therefore, these conventional methods can hardly forecast urban noise at a given outlook of development layout. This paper, for the first time, introduces a land use regression method, which has been applied for simulating urban air quality for a decade, to construct an urban noise model (LUNOS) in Dalian Municipality, Northwest China. The LUNOS model describes noise as a dependent variable of surrounding various land areas via a regressive function. The results suggest that a linear model performs better in fitting monitoring data, and there is no significant difference of the LUNOS's outputs when applied to different spatial scales. As the LUNOS facilitates a better understanding of the association between land use and urban environmental noise in comparison to conventional methods, it can be regarded as a promising tool for noise prediction for planning purposes and aid smart decision-making.

A farm-level precision land management framework based on integer programming

PubMed Central

Li, Qi; Hu, Guiping; Jubery, Talukder Zaki; Ganapathysubramanian, Baskar

2017-01-01

Farmland management involves several planning and decision making tasks including seed selection and irrigation management. A farm-level precision farmland management model based on mixed integer linear programming is proposed in this study. Optimal decisions are designed for pre-season planning of crops and irrigation water allocation. The model captures the effect of size and shape of decision scale as well as special irrigation patterns. The authors illustrate the model with a case study on a farm in the state of California in the U.S. and show the model can capture the impact of precision farm management on profitability. The results show that threefold increase of annual net profit for farmers could be achieved by carefully choosing irrigation and seed selection. Although farmers could increase profits by applying precision management to seed or irrigation alone, profit increase is more significant if farmers apply precision management on seed and irrigation simultaneously. The proposed model can also serve as a risk analysis tool for farmers facing seasonal irrigation water limits as well as a quantitative tool to explore the impact of precision agriculture. PMID:28346499

Evaluating the risk of water distribution system failure: A shared frailty model

NASA Astrophysics Data System (ADS)

Clark, Robert M.; Thurnau, Robert C.

2011-12-01

Condition assessment (CA) Modeling is drawing increasing interest as a technique that can assist in managing drinking water infrastructure. This paper develops a model based on the application of a Cox proportional hazard (PH)/shared frailty model and applies it to evaluating the risk of failure in drinking water networks using data from the Laramie Water Utility (located in Laramie, Wyoming, USA). Using the risk model a cost/ benefit analysis incorporating the inspection value method (IVM), is used to assist in making improved repair, replacement and rehabilitation decisions for selected drinking water distribution system pipes. A separate model is developed to predict failures in prestressed concrete cylinder pipe (PCCP). Various currently available inspection technologies are presented and discussed.

"An integrative formal model of motivation and decision making: The MGPM*": Correction to Ballard et al. (2016).

PubMed

2017-02-01

Reports an error in "An integrative formal model of motivation and decision making: The MGPM*" by Timothy Ballard, Gillian Yeo, Shayne Loft, Jeffrey B. Vancouver and Andrew Neal ( Journal of Applied Psychology , 2016[Sep], Vol 101[9], 1240-1265). Equation A3 contained an error. This correct equation is provided in the erratum. (The following abstract of the original article appeared in record 2016-28692-001.) 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) 2017 APA, all rights reserved).

Agrochemical fate models applied in agricultural areas from Colombia

NASA Astrophysics Data System (ADS)

Garcia-Santos, Glenda; Yang, Jing; Andreoli, Romano; Binder, Claudia

2010-05-01

The misuse application of pesticides in mainly agricultural catchments can lead to severe problems for humans and environment. Especially in developing countries where there is often found overuse of agrochemicals and incipient or lack of water quality monitoring at local and regional levels, models are needed for decision making and hot spots identification. However, the complexity of the water cycle contrasts strongly with the scarce data availability, limiting the number of analysis, techniques, and models available to researchers. Therefore there is a strong need for model simplification able to appropriate model complexity and still represent the processes. We have developed a new model so-called Westpa-Pest to improve water quality management of an agricultural catchment located in the highlands of Colombia. Westpa-Pest is based on the fully distributed hydrologic model Wetspa and a fate pesticide module. We have applied a multi-criteria analysis for model selection under the conditions and data availability found in the region and compared with the new developed Westpa-Pest model. Furthermore, both models were empirically calibrated and validated. The following questions were addressed i) what are the strengths and weaknesses of the models?, ii) which are the most sensitive parameters of each model?, iii) what happens with uncertainties in soil parameters?, and iv) how sensitive are the transfer coefficients?

Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework

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

Cappelli, M.; Gadomski, A. M.; Sepiellis, M.

In the field of nuclear power plant (NPP) safety modeling, the perception of the role of socio-cognitive engineering (SCE) is continuously increasing. Today, the focus is especially on the identification of human and organization decisional errors caused by operators and managers under high-risk conditions, as evident by analyzing reports on nuclear incidents occurred in the past. At present, the engineering and social safety requirements need to enlarge their domain of interest in such a way to include all possible losses generating events that could be the consequences of an abnormal state of a NPP. Socio-cognitive modeling of Integrated Nuclear Safetymore » Management (INSM) using the TOGA meta-theory has been discussed during the ICCAP 2011 Conference. In this paper, more detailed aspects of the cognitive decision-making and its possible human errors and organizational vulnerability are presented. The formal TOGA-based network model for cognitive decision-making enables to indicate and analyze nodes and arcs in which plant operators and managers errors may appear. The TOGA's multi-level IPK (Information, Preferences, Knowledge) model of abstract intelligent agents (AIAs) is applied. In the NPP context, super-safety approach is also discussed, by taking under consideration unexpected events and managing them from a systemic perspective. As the nature of human errors depends on the specific properties of the decision-maker and the decisional context of operation, a classification of decision-making using IPK is suggested. Several types of initial situations of decision-making useful for the diagnosis of NPP operators and managers errors are considered. The developed models can be used as a basis for applications to NPP educational or engineering simulators to be used for training the NPP executive staff. (authors)« less

Fish Oncology: Diseases, Diagnostics, and Therapeutics.

PubMed

Vergneau-Grosset, Claire; Nadeau, Marie-Eve; Groff, Joseph M

2017-01-01

The scientific literature contains a wealth of information concerning spontaneous fish neoplasms, although ornamental fish oncology is still in its infancy. The occurrence of fish neoplasms has often been associated with oncogenic viruses and environmental insults, making them useful markers for environmental contaminants. The use of fish, including zebrafish, as models of human carcinogenesis has been developed and knowledge gained from these models may also be applied to ornamental fish, although more studies are required. This review summarizes information available about fish oncology pertaining to veterinary clinicians. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis of Panel Data

NASA Astrophysics Data System (ADS)

Hsiao, Cheng

2003-02-01

Panel data models have become increasingly popular among applied researchers due to their heightened capacity for capturing the complexity of human behavior, as compared to cross-sectional or time series data models. This second edition represents a substantial revision of the highly successful first edition (1986). Recent advances in panel data research are presented in an accessible manner and are carefully integrated with the older material. The thorough discussion of theory and the judicious use of empirical examples make this book useful to graduate students and advanced researchers in economics, business, sociology and political science.

Application of simple negative feedback model for avalanche photodetectors investigation

NASA Astrophysics Data System (ADS)

Kushpil, V. V.

2009-10-01

A simple negative feedback model based on Miller's formula is used to investigate the properties of Avalanche Photodetectors (APDs). The proposed method can be applied to study classical APD as well as new type of devices, which are operating in the Internal Negative Feedback (INF) regime. The method shows a good sensitivity to technological APD parameters making it possible to use it as a tool to analyse various APD parameters. It also allows better understanding of the APD operation conditions. The simulations and experimental data analysis for different types of APDs are presented.

Extrapolation to Nonequilibrium from Coarse-Grained Response Theory

NASA Astrophysics Data System (ADS)

Basu, Urna; Helden, Laurent; Krüger, Matthias

2018-05-01

Nonlinear response theory, in contrast to linear cases, involves (dynamical) details, and this makes application to many-body systems challenging. From the microscopic starting point we obtain an exact response theory for a small number of coarse-grained degrees of freedom. With it, an extrapolation scheme uses near-equilibrium measurements to predict far-from-equilibrium properties (here, second order responses). Because it does not involve system details, this approach can be applied to many-body systems. It is illustrated in a four-state model and in the near critical Ising model.

Identification of stochastic interactions in nonlinear models of structural mechanics

NASA Astrophysics Data System (ADS)

Kala, Zdeněk

2017-07-01

In the paper, the polynomial approximation is presented by which the Sobol sensitivity analysis can be evaluated with all sensitivity indices. The nonlinear FEM model is approximated. The input area is mapped using simulations runs of Latin Hypercube Sampling method. The domain of the approximation polynomial is chosen so that it were possible to apply large number of simulation runs of Latin Hypercube Sampling method. The method presented also makes possible to evaluate higher-order sensitivity indices, which could not be identified in case of nonlinear FEM.

Building and executing a research agenda toward conducting implementation science in medical education

PubMed Central

Carney, Patricia A.; Crites, Gerald E.; Miller, Karen H.; Haight, Michelle; Stefanidis, Dimitrios; Cichoskikelly, Eileen; Price, David W.; Akinola, Modupeola O.; Scott, Victoria C.; Kalishman, Summers

2016-01-01

Background Implementation science (IS) is the study of methods that successfully integrate best evidence into practice. Although typically applied in healthcare settings to improve patient care and subsequent outcomes, IS also has immediate and practical applications to medical education toward improving physician training and educational outcomes. The objective of this article is to illustrate how to build a research agenda that focuses on applying IS principles in medical education. Approach We examined the literature to construct a rationale for using IS to improve medical education. We then used a generalizable scenario to step through a process for applying IS to improve team-based care. Perspectives IS provides a valuable approach to medical educators and researchers for making improvements in medical education and overcoming institution-based challenges. It encourages medical educators to systematically build upon the research outcomes of others to guide decision-making while evaluating the successes of best practices in individual environments and generate additional research questions and findings. Conclusions IS can act as both a driver and a model for educational research to ensure that best educational practices are easier and faster to implement widely. PMID:27565131

A systematic approach to embedded biomedical decision making.

PubMed

Song, Zhe; Ji, Zhongkai; Ma, Jian-Guo; Sputh, Bernhard; Acharya, U Rajendra; Faust, Oliver

2012-11-01

An embedded decision making is a key feature for many biomedical systems. In most cases human life directly depends on correct decisions made by these systems, therefore they have to work reliably. This paper describes how we applied systems engineering principles to design a high performance embedded classification system in a systematic and well structured way. We introduce the structured design approach by discussing requirements capturing, specifications refinement, implementation and testing. Thereby, we follow systems engineering principles and execute each of these processes as formal as possible. The requirements, which motivate the system design, describe an automated decision making system for diagnostic support. These requirements are refined into the implementation of a support vector machine (SVM) algorithm which enables us to integrate automated decision making in embedded systems. With a formal model we establish functionality, stability and reliability of the system. Furthermore, we investigated different parallel processing configurations of this computationally complex algorithm. We found that, by adding SVM processes, an almost linear speedup is possible. Once we established these system properties, we translated the formal model into an implementation. The resulting implementation was tested using XMOS processors with both normal and failure cases, to build up trust in the implementation. Finally, we demonstrated that our parallel implementation achieves the speedup, predicted by the formal model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

USGS River Ecosystem Modeling: Where Are We, How Did We Get Here, and Where Are We Going?

USGS Publications Warehouse

Hanson, Leanne; Schrock, Robin; Waddle, Terry; Duda, Jeffrey J.; Lellis, Bill

2009-01-01

This report developed as an outcome of the USGS River Ecosystem Modeling Work Group, convened on February 11, 2008 as a preconference session to the second USGS Modeling Conference in Orange Beach, Ala. Work Group participants gained an understanding of the types of models currently being applied to river ecosystem studies within the USGS, learned how model outputs are being used by a Federal land management agency, and developed recommendations for advancing the state of the art in river ecosystem modeling within the USGS. During a break-out session, participants restated many of the recommendations developed at the first USGS Modeling Conference in 2006 and in previous USGS needs assessments. All Work Group recommendations require organization and coordination across USGS disciplines and regions, and include (1) enhancing communications, (2) increasing efficiency through better use of current human and technologic resources, and (3) providing a national infrastructure for river ecosystem modeling resources, making it easier to integrate modeling efforts. By implementing these recommendations, the USGS will benefit from enhanced multi-disciplinary, integrated models for river ecosystems that provide valuable risk assessment and decision support tools for adaptive management of natural and managed riverine ecosystems. These tools generate key information that resource managers need and can use in making decisions about river ecosystem resources.

Seeking for the rational basis of the median model: the optimal combination of multi-model ensemble results

NASA Astrophysics Data System (ADS)

Riccio, A.; Giunta, G.; Galmarini, S.

2007-04-01

In this paper we present an approach for the statistical analysis of multi-model ensemble results. The models considered here are operational long-range transport and dispersion models, also used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides. We first introduce the theoretical basis (with its roots sinking into the Bayes theorem) and then apply this approach to the analysis of model results obtained during the ETEX-1 exercise. We recover some interesting results, supporting the heuristic approach called "median model", originally introduced in Galmarini et al. (2004a, b). This approach also provides a way to systematically reduce (and quantify) model uncertainties, thus supporting the decision-making process and/or regulatory-purpose activities in a very effective manner.

Seeking for the rational basis of the Median Model: the optimal combination of multi-model ensemble results

NASA Astrophysics Data System (ADS)

Riccio, A.; Giunta, G.; Galmarini, S.

2007-12-01

In this paper we present an approach for the statistical analysis of multi-model ensemble results. The models considered here are operational long-range transport and dispersion models, also used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides. We first introduce the theoretical basis (with its roots sinking into the Bayes theorem) and then apply this approach to the analysis of model results obtained during the ETEX-1 exercise. We recover some interesting results, supporting the heuristic approach called "median model", originally introduced in Galmarini et al. (2004a, b). This approach also provides a way to systematically reduce (and quantify) model uncertainties, thus supporting the decision-making process and/or regulatory-purpose activities in a very effective manner.

Stimulating household flood risk mitigation investments through insurance and subsidies: an Agent-Based Modelling approach

NASA Astrophysics Data System (ADS)

Haer, Toon; Botzen, Wouter; de Moel, Hans; Aerts, Jeroen

2015-04-01

In the period 1998-2009, floods triggered roughly 52 billion euro in insured economic losses making floods the most costly natural hazard in Europe. Climate change and socio/economic trends are expected to further aggrevate floods losses in many regions. Research shows that flood risk can be significantly reduced if households install protective measures, and that the implementation of such measures can be stimulated through flood insurance schemes and subsidies. However, the effectiveness of such incentives to stimulate implementation of loss-reducing measures greatly depends on the decision process of individuals and is hardly studied. In our study, we developed an Agent-Based Model that integrates flood damage models, insurance mechanisms, subsidies, and household behaviour models to assess the effectiveness of different economic tools on stimulating households to invest in loss-reducing measures. Since the effectiveness depends on the decision making process of individuals, the study compares different household decision models ranging from standard economic models, to economic models for decision making under risk, to more complex decision models integrating economic models and risk perceptions, opinion dynamics, and the influence of flood experience. The results show the effectiveness of incentives to stimulate investment in loss-reducing measures for different household behavior types, while assuming climate change scenarios. It shows how complex decision models can better reproduce observed real-world behaviour compared to traditional economic models. Furthermore, since flood events are included in the simulations, the results provide an analysis of the dynamics in insured and uninsured losses for households, the costs of reducing risk by implementing loss-reducing measures, the capacity of the insurance market, and the cost of government subsidies under different scenarios. The model has been applied to the City of Rotterdam in The Netherlands.

Comprehensible knowledge model creation for cancer treatment decision making.

PubMed

Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

2017-03-01

A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Carbon Cycle Science in Support of Decision-Making

NASA Astrophysics Data System (ADS)

Brown, M. E.; West, T. O.; McGlynn, E.; Gurwick, N. P.; Duren, R. M.; Ocko, I.; Paustian, K.

2016-12-01

There has been an extensive amount of basic and applied research conducted on biogeochemical cycles, land cover change, watershed to earth system modeling, climate change, and energy efficiency. Concurrently, there continues to be interest in how to best reduce net carbon emissions, including maintaining or augmenting global carbon stocks and decreasing fossil fuel emissions. Decisions surrounding reductions in net emissions should be grounded in, and informed by, existing scientific knowledge and analyses in order to be most effective. The translation of scientific research to decision-making is rarely direct, and often requires coordination of objectives or intermediate research steps. For example, complex model output may need to be simplified to provide mean estimates for given activities; biogeochemical models used for climate change prediction may need to be altered to estimate net carbon flux associated with particular activities; or scientific analyses may need to aggregate and analyze data in a different manner to address specific questions. In the aforementioned cases, expertise and capabilities of researchers and decision-makers are both needed, and early coordination and communication is most effective. Initial analysis of existing science and current decision-making needs indicate that (a) knowledge that is co-produced by scientists and decision-makers has a higher probability of being usable for decision making, (b) scientific work in the past decade to integrate activity data into models has resulted in more usable information for decision makers, (c) attribution and accounting of carbon cycle fluxes is key to using carbon cycle science for decision-making, and (d) stronger, long-term links among research on climate and management of carbon-related sectors (e.g., energy, land use, industry, and buildings) are needed to adequately address current issues.

Like Hercules and the Hydra: Trade-offs and strategies in ecological model-building and experimental design.

PubMed

Inkpen, S Andrew

2016-06-01

Experimental ecologists often invoke trade-offs to describe the constraints they encounter when choosing between alternative experimental designs, such as between laboratory, field, and natural experiments. In making these claims, they tend to rely on Richard Levins' analysis of trade-offs in theoretical model-building. But does Levins' framework apply to experiments? In this paper, I focus this question on one desideratum widely invoked in the modelling literature: generality. Using the case of generality, I assess whether Levins-style treatments of modelling provide workable resources for assessing trade-offs in experimental design. I argue that, of four strategies modellers employ to increase generality, only one may be unproblematically applied to experimental design. Furthermore, modelling desiderata do not have obvious correlates in experimental design, and when we define these desiderata in a way that seem consistent with ecologists' usage, the trade-off framework falls apart. I conclude that a Levins-inspired framework for modelling does not provide the content for a similar approach to experimental practice; this does not, however, mean that it cannot provide the form. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting the incidence of hand, foot and mouth disease in Sichuan province, China using the ARIMA model.

PubMed

Liu, L; Luan, R S; Yin, F; Zhu, X P; Lü, Q

2016-01-01

Hand, foot and mouth disease (HFMD) is an infectious disease caused by enteroviruses, which usually occurs in children aged <5 years. In China, the HFMD situation is worsening, with increasing number of cases nationwide. Therefore, monitoring and predicting HFMD incidence are urgently needed to make control measures more effective. In this study, we applied an autoregressive integrated moving average (ARIMA) model to forecast HFMD incidence in Sichuan province, China. HFMD infection data from January 2010 to June 2014 were used to fit the ARIMA model. The coefficient of determination (R 2), normalized Bayesian Information Criterion (BIC) and mean absolute percentage of error (MAPE) were used to evaluate the goodness-of-fit of the constructed models. The fitted ARIMA model was applied to forecast the incidence of HMFD from April to June 2014. The goodness-of-fit test generated the optimum general multiplicative seasonal ARIMA (1,0,1) × (0,1,0)12 model (R 2 = 0·692, MAPE = 15·982, BIC = 5·265), which also showed non-significant autocorrelations in the residuals of the model (P = 0·893). The forecast incidence values of the ARIMA (1,0,1) × (0,1,0)12 model from July to December 2014 were 4103-9987, which were proximate forecasts. The ARIMA model could be applied to forecast HMFD incidence trend and provide support for HMFD prevention and control. Further observations should be carried out continually into the time sequence, and the parameters of the models could be adjusted because HMFD incidence will not be absolutely stationary in the future.

Characteristic density contrasts in the evolution of superclusters. The case of A2142 supercluster

NASA Astrophysics Data System (ADS)

Gramann, Mirt; Einasto, Maret; Heinämäki, Pekka; Teerikorpi, Pekka; Saar, Enn; Nurmi, Pasi; Einasto, Jaan

2015-09-01

Context. The formation and evolution of the cosmic web in which galaxy superclusters are the largest relatively isolated objects is governed by a gravitational attraction of dark matter and antigravity of dark energy (cosmological constant). Aims: We study the characteristic density contrasts in the spherical collapse model for several epochs in the supercluster evolution and their dynamical state. Methods: We analysed the density contrasts for the turnaround, future collapse, and zero gravity in different ΛCDM models and applied them to study the dynamical state of the supercluster A2142 with an almost spherical main body, making it a suitable test object to apply a model that assumes sphericity. Results: We present characteristic density contrasts in the spherical collapse model for different cosmological parameters. The analysis of the supercluster A2142 shows that its high-density core has already started to collapse. The zero-gravity line outlines the outer region of the main body of the supercluster. In the course of future evolution, the supercluster may split into several collapsing systems. Conclusions: The various density contrasts presented in our study and applied to the supercluster A2142 offer a promising way to characterise the dynamical state and expected future evolution of galaxy superclusters.

Scenario driven data modelling: a method for integrating diverse sources of data and data streams

PubMed Central

2011-01-01

Background Biology is rapidly becoming a data intensive, data-driven science. It is essential that data is represented and connected in ways that best represent its full conceptual content and allows both automated integration and data driven decision-making. Recent advancements in distributed multi-relational directed graphs, implemented in the form of the Semantic Web make it possible to deal with complicated heterogeneous data in new and interesting ways. Results This paper presents a new approach, scenario driven data modelling (SDDM), that integrates multi-relational directed graphs with data streams. SDDM can be applied to virtually any data integration challenge with widely divergent types of data and data streams. In this work, we explored integrating genetics data with reports from traditional media. SDDM was applied to the New Delhi metallo-beta-lactamase gene (NDM-1), an emerging global health threat. The SDDM process constructed a scenario, created a RDF multi-relational directed graph that linked diverse types of data to the Semantic Web, implemented RDF conversion tools (RDFizers) to bring content into the Sematic Web, identified data streams and analytical routines to analyse those streams, and identified user requirements and graph traversals to meet end-user requirements. Conclusions We provided an example where SDDM was applied to a complex data integration challenge. The process created a model of the emerging NDM-1 health threat, identified and filled gaps in that model, and constructed reliable software that monitored data streams based on the scenario derived multi-relational directed graph. The SDDM process significantly reduced the software requirements phase by letting the scenario and resulting multi-relational directed graph define what is possible and then set the scope of the user requirements. Approaches like SDDM will be critical to the future of data intensive, data-driven science because they automate the process of converting massive data streams into usable knowledge. PMID:22165854

Toward a normalized clinical drug knowledge base in China-applying the RxNorm model to Chinese clinical drugs.

PubMed

Wang, Li; Zhang, Yaoyun; Jiang, Min; Wang, Jingqi; Dong, Jiancheng; Liu, Yun; Tao, Cui; Jiang, Guoqian; Zhou, Yi; Xu, Hua

2018-07-01

In recent years, electronic health record systems have been widely implemented in China, making clinical data available electronically. However, little effort has been devoted to making drug information exchangeable among these systems. This study aimed to build a Normalized Chinese Clinical Drug (NCCD) knowledge base, by applying and extending the information model of RxNorm to Chinese clinical drugs. Chinese drugs were collected from 4 major resources-China Food and Drug Administration, China Health Insurance Systems, Hospital Pharmacy Systems, and China Pharmacopoeia-for integration and normalization in NCCD. Chemical drugs were normalized using the information model in RxNorm without much change. Chinese patent drugs (i.e., Chinese herbal extracts), however, were represented using an expanded RxNorm model to incorporate the unique characteristics of these drugs. A hybrid approach combining automated natural language processing technologies and manual review by domain experts was then applied to drug attribute extraction, normalization, and further generation of drug names at different specification levels. Lastly, we reported the statistics of NCCD, as well as the evaluation results using several sets of randomly selected Chinese drugs. The current version of NCCD contains 16 976 chemical drugs and 2663 Chinese patent medicines, resulting in 19 639 clinical drugs, 250 267 unique concepts, and 2 602 760 relations. By manual review of 1700 chemical drugs and 250 Chinese patent drugs randomly selected from NCCD (about 10%), we showed that the hybrid approach could achieve an accuracy of 98.60% for drug name extraction and normalization. Using a collection of 500 chemical drugs and 500 Chinese patent drugs from other resources, we showed that NCCD achieved coverages of 97.0% and 90.0% for chemical drugs and Chinese patent drugs, respectively. Evaluation results demonstrated the potential to improve interoperability across various electronic drug systems in China.

Applying Research to Making Life-Affecting Judgments and Decisions

ERIC Educational Resources Information Center

Gibbs, Leonard

2007-01-01

This keynote address argues that in order for baccalaureate and masters degree students to apply research to make better judgments and decisions in their life-affecting practice and in response to the information revolution, the helping professions need to redesign (from the bottom up) not overhaul (make a few changes in) the way research methods…

Thermal Hardware for the Thermal Analyst

NASA Technical Reports Server (NTRS)

Steinfeld, David

2015-01-01

The presentation will be given at the 26th Annual Thermal Fluids Analysis Workshop (TFAWS 2015) hosted by the Goddard Space Flight Center (GSFC) Thermal Engineering Branch (Code 545). NCTS 21070-1. Most Thermal analysts do not have a good background into the hardware which thermally controls the spacecraft they design. SINDA and Thermal Desktop models are nice, but knowing how this applies to the actual thermal hardware (heaters, thermostats, thermistors, MLI blanketing, optical coatings, etc...) is just as important. The course will delve into the thermal hardware and their application techniques on actual spacecraft. Knowledge of how thermal hardware is used and applied will make a thermal analyst a better engineer.

PHM Enabled Autonomous Propellant Loading Operations

NASA Technical Reports Server (NTRS)

Walker, Mark; Figueroa, Fernando

2017-01-01

The utility of Prognostics and Health Management (PHM) software capability applied to Autonomous Operations (AO) remains an active research area within aerospace applications. The ability to gain insight into which assets and subsystems are functioning properly, along with the derivation of confident predictions concerning future ability, reliability, and availability, are important enablers for making sound mission planning decisions. When coupled with software that fully supports mission planning and execution, an integrated solution can be developed that leverages state assessment and estimation for the purposes of delivering autonomous operations. The authors have been applying this integrated, model-based approach to the autonomous loading of cryogenic spacecraft propellants at Kennedy Space Center.

Property and women's alienation from their own reproductive labour.

PubMed

Dickenson, D L

2001-06-01

There is an urgent need for reconstructing models of property to make them more women-friendly. However, we need not start from scratch: both 'canonical' and feminist authors can sometimes provide concepts which we can refine and apply towards women's propertylessness. This paper looks in particular at women's alienation from their reproductive labour, building on Marx and Delphy. Developing an economic and political rather than a psychological reading of alienation, it then considers how the refined and revised concept can be applied to concrete examples in global justice for women: in particular, the commercialisation of embryonic and fetal tissue in the new stem cell technologies.

Normative evidence accumulation in unpredictable environments

PubMed Central

Glaze, Christopher M; Kable, Joseph W; Gold, Joshua I

2015-01-01

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals. DOI: http://dx.doi.org/10.7554/eLife.08825.001 PMID:26322383