Weighing conservation objectives: maximum expected coverage versus endangered species protection

Treesearch

Jeffrey L. Arthur; Jeffrey D. Camm; Robert G. Haight; Claire A. Montgomery; Stephen Polasky

2004-01-01

Decision makers involved in land acquisition and protection often have multiple conservation objectives and are uncertain about the occurrence of species or other features in candidate sites. Model informing decisions on selection of sites for reserves need to provide information about cost-efficient trade-offs between objectives and account for incidence uncertainty...

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.

SYSTEMATIC PROCEDURE FOR DESIGNING PROCESSES WITH MULTIPLE ENVIRONMENTAL OBJECTIVES

EPA Science Inventory

Evaluation of multiple objectives is very important in designing environmentally benign processes. It requires a systematic procedure for solving multiobjective decision-making problems, due to the complex nature of the problems, the need for complex assessments, and complicated ...

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…

Decision Making in Adults with ADHD

ERIC Educational Resources Information Center

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

2012-01-01

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

Multiple degree of freedom object recognition using optical relational graph decision nets

NASA Technical Reports Server (NTRS)

Casasent, David P.; Lee, Andrew J.

1988-01-01

Multiple-degree-of-freedom object recognition concerns objects with no stable rest position with all scale, rotation, and aspect distortions possible. It is assumed that the objects are in a fairly benign background, so that feature extractors are usable. In-plane distortion invariance is provided by use of a polar-log coordinate transform feature space, and out-of-plane distortion invariance is provided by linear discriminant function design. Relational graph decision nets are considered for multiple-degree-of-freedom pattern recognition. The design of Fisher (1936) linear discriminant functions and synthetic discriminant function for use at the nodes of binary and multidecision nets is discussed. Case studies are detailed for two-class and multiclass problems. Simulation results demonstrate the robustness of the processors to quantization of the filter coefficients and to noise.

Using structured decision making with landowners to address private forest management and parcelization: balancing multiple objectives and incorporating uncertainty

Treesearch

Paige F. B. Ferguson; Michael J. Conroy; John F. Chamblee; Jeffrey Hepinstall-Cymerman

2015-01-01

Parcelization and forest fragmentation are of concern for ecological, economic, and social reasons. Efforts to keep large, private forests intact may be supported by a decision-making process that incorporates landowners’ objectives and uncertainty. We used structured decision making (SDM) with owners of large, private forests in Macon County, North Carolina....

Integrating forest stand projections with wildlife occupancy models to develop a decision support tool

Treesearch

Michelle F. Tacconelli; Edward F. Loewenstein

2012-01-01

Natural resource managers must often balance multiple objectives on a single property. When these objectives are seemingly conflicting, the manager’s job can be extremely difficult and complex. This paper presents a decision support tool, designed to aid land managers in optimizing wildlife habitat needs while accomplishing additional objectives such as ecosystem...

Developing inventory and monitoring programs based on multiple objectives

NASA Astrophysics Data System (ADS)

Schmoldt, Daniel L.; Peterson, David L.; Silsbee, David G.

1994-09-01

Resource inventory and monitoring (I&M) programs in national parks combine multiple objectives in order to create a plan of action over a finite time horizon. Because all program activities are constrained by time and money, it is critical to plan I&M activities that make the best use of available agency resources. However, multiple objectives complicate a relatively straightforward allocation process. The analytic hierarchy process (AHP) offers a structure for multiobjective decision making so that decision-makers’ preferences can be formally incorporated in seeking potential solutions. Within the AHP, inventory and monitoring program objectives and decision criteria are organized into a hierarchy. Pairwise comparisons among decision elements at any level of the hierarchy provide a ratio scale ranking of those elements. The resulting priority values for all projects are used as each project’s contribution to the value of an overall I&M program. These priorities, along with budget and personnel constraints, are formulated as a zero/one integer programming problem that can be solved to select those projects that produce the best program. An extensive example illustrates how this approach is being applied to I&M projects in national parks in the Pacific Northwest region of the United States. The proposed planning process provides an analytical framework for multicriteria decisionmaking that is rational, consistent, explicit, and defensible.

Decision-making for foot-and-mouth disease control: Objectives matter

USGS Publications Warehouse

Probert, William J. M.; Shea, Katriona; Fonnesbeck, Christopher J.; Runge, Michael C.; Carpenter, Tim E.; Durr, Salome; Garner, M. Graeme; Harvey, Neil; Stevenson, Mark A.; Webb, Colleen T.; Werkman, Marleen; Tildesley, Michael J.; Ferrari, Matthew J.

2016-01-01

Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making.

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

USGS Publications Warehouse

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

Treesearch

Erin J. Belval; Yu Wei; Michael Bevers

2015-01-01

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

A Multi-criterial Decision Support System for Forest Management

Treesearch

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

1999-01-01

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

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

EPA Pesticide Factsheets

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

Embedding Human Expert Cognition Into Autonomous UAS Trajectory Planning.

PubMed

Narayan, Pritesh; Meyer, Patrick; Campbell, Duncan

2013-04-01

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

Multi-objective optimisation and decision-making of space station logistics strategies

NASA Astrophysics Data System (ADS)

Zhu, Yue-he; Luo, Ya-zhong

2016-10-01

Space station logistics strategy optimisation is a complex engineering problem with multiple objectives. Finding a decision-maker-preferred compromise solution becomes more significant when solving such a problem. However, the designer-preferred solution is not easy to determine using the traditional method. Thus, a hybrid approach that combines the multi-objective evolutionary algorithm, physical programming, and differential evolution (DE) algorithm is proposed to deal with the optimisation and decision-making of space station logistics strategies. A multi-objective evolutionary algorithm is used to acquire a Pareto frontier and help determine the range parameters of the physical programming. Physical programming is employed to convert the four-objective problem into a single-objective problem, and a DE algorithm is applied to solve the resulting physical programming-based optimisation problem. Five kinds of objective preference are simulated and compared. The simulation results indicate that the proposed approach can produce good compromise solutions corresponding to different decision-makers' preferences.

Creating ensembles of oblique decision trees with evolutionary algorithms and sampling

DOEpatents

Cantu-Paz, Erick [Oakland, CA; Kamath, Chandrika [Tracy, CA

2006-06-13

A decision tree system that is part of a parallel object-oriented pattern recognition system, which in turn is part of an object oriented data mining system. A decision tree process includes the step of reading the data. If necessary, the data is sorted. A potential split of the data is evaluated according to some criterion. An initial split of the data is determined. The final split of the data is determined using evolutionary algorithms and statistical sampling techniques. The data is split. Multiple decision trees are combined in ensembles.

Defining ecological and economical hydropoweroperations: a framework for managing dam releasesto meet multiple conflicting objectives

USGS Publications Warehouse

Irwin, Elise R.

2014-01-01

Hydroelectric dams are a flexible source of power, provide flood control, and contribute to the economic growth of local communities through real-estate and recreation. Yet the impoundment of rivers can alter and fragment miles of critical riverine habitat needed for other competing needs such as downstream consumptive water use, fish and wildlife population viability, or other forms of recreation. Multiple conflicting interests can compromise progressive management especially with recognized uncertainties related to whether management actions will fulfill the objectives of policy makers, resource managers and/or facility owners. Decision analytic tools were used in a stakeholder-driven process to develop and implement a template for evaluation and prediction of the effects of water resource management of multiple-use systems under the context provided by R.L. Harris Dam on the Tallapoosa River, Alabama, USA. The approach provided a transparent and structured framework for decision-making and incorporated both existing and new data to meet multiple management objectives. Success of the template has been evaluated by the stakeholder governing body in an adaptive resource management framework since 2005 and is ongoing. Consequences of management of discharge at the dam were evaluated annually relative to stakeholder satisfaction to allow for adjustment of both management scenarios and objectives. This template can be applied to attempt to resolve conflict inherent in many dam-regulated systems where management decisions impact diverse values of stakeholders.

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

Treesearch

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

2011-01-01

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

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

PubMed

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

2016-01-01

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

Analyzing public inputs to multiple objective decisions on national forests using conjoint analysis

Treesearch

Donald F. Dennis

1998-01-01

Faced with multiple objectives, national forest managers and planners need a means to solicit and analyze public preferences and values. A conjoint ranking survey was designed to solicit public preferences for various levels of timber harvesting, wildlife habitats, hiking trails, snowmobile use, and off-road-vehicle (ORV) access on the Green Mountain National Forest....

Recent advances in applying decision science to managing national forests

Treesearch

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

2012-01-01

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

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

DTIC Science & Technology

2012-03-22

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

Battling Arrow's Paradox to Discover Robust Water Management Alternatives

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Systematic procedure for designing processes with multiple environmental objectives.

PubMed

Kim, Ki-Joo; Smith, Raymond L

2005-04-01

Evaluation of multiple objectives is very important in designing environmentally benign processes. It requires a systematic procedure for solving multiobjective decision-making problems due to the complex nature of the problems, the need for complex assessments, and the complicated analysis of multidimensional results. In this paper, a novel systematic procedure is presented for designing processes with multiple environmental objectives. This procedure has four steps: initialization, screening, evaluation, and visualization. The first two steps are used for systematic problem formulation based on mass and energy estimation and order of magnitude analysis. In the third step, an efficient parallel multiobjective steady-state genetic algorithm is applied to design environmentally benign and economically viable processes and to provide more accurate and uniform Pareto optimal solutions. In the last step a new visualization technique for illustrating multiple objectives and their design parameters on the same diagram is developed. Through these integrated steps the decision-maker can easily determine design alternatives with respect to his or her preferences. Most importantly, this technique is independent of the number of objectives and design parameters. As a case study, acetic acid recovery from aqueous waste mixtures is investigated by minimizing eight potential environmental impacts and maximizing total profit. After applying the systematic procedure, the most preferred design alternatives and their design parameters are easily identified.

Solving multi-objective optimization problems in conservation with the reference point method

PubMed Central

Dujardin, Yann; Chadès, Iadine

2018-01-01

Managing the biodiversity extinction crisis requires wise decision-making processes able to account for the limited resources available. In most decision problems in conservation biology, several conflicting objectives have to be taken into account. Most methods used in conservation either provide suboptimal solutions or use strong assumptions about the decision-maker’s preferences. Our paper reviews some of the existing approaches to solve multi-objective decision problems and presents new multi-objective linear programming formulations of two multi-objective optimization problems in conservation, allowing the use of a reference point approach. Reference point approaches solve multi-objective optimization problems by interactively representing the preferences of the decision-maker with a point in the criteria (objectives) space, called the reference point. We modelled and solved the following two problems in conservation: a dynamic multi-species management problem under uncertainty and a spatial allocation resource management problem. Results show that the reference point method outperforms classic methods while illustrating the use of an interactive methodology for solving combinatorial problems with multiple objectives. The method is general and can be adapted to a wide range of ecological combinatorial problems. PMID:29293650

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

PubMed

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

2016-01-01

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

Equity trade-offs in conservation decision making.

PubMed

Law, Elizabeth A; Bennett, Nathan J; Ives, Christopher D; Friedman, Rachel; Davis, Katrina J; Archibald, Carla; Wilson, Kerrie A

2018-04-01

Conservation decisions increasingly involve multiple environmental and social objectives, which result in complex decision contexts with high potential for trade-offs. Improving social equity is one such objective that is often considered an enabler of successful outcomes and a virtuous ideal in itself. Despite its idealized importance in conservation policy, social equity is often highly simplified or ill-defined and is applied uncritically. What constitutes equitable outcomes and processes is highly normative and subject to ethical deliberation. Different ethical frameworks may lead to different conceptions of equity through alternative perspectives of what is good or right. This can lead to different and potentially conflicting equity objectives in practice. We promote a more transparent, nuanced, and pluralistic conceptualization of equity in conservation decision making that particularly recognizes where multidimensional equity objectives may conflict. To help identify and mitigate ethical conflicts and avoid cases of good intentions producing bad outcomes, we encourage a more analytical incorporation of equity into conservation decision making particularly during mechanistic integration of equity objectives. We recommend that in conservation planning motivations and objectives for equity be made explicit within the problem context, methods used to incorporate equity objectives be applied with respect to stated objectives, and, should objectives dictate, evaluation of equity outcomes and adaptation of strategies be employed during policy implementation. © 2017 Society for Conservation Biology.

Decision Topology Assessment in Engineering Design Under Uncertainity

DTIC Science & Technology

2014-01-01

those of the United States Government or the DoA, and shall not be used for advertising or product endorsement purposes. REFERENCES 1. Clemen ...Raiffa, H., 1994, Decisions with Multiple Objectives, Cambridge University Press, Cambridge, United Kingdom. 6. Lewis, K., W. Chen, and L.C. Schmidt

Multiple objective optimization in reliability demonstration test

DOE PAGES

Lu, Lu; Anderson-Cook, Christine Michaela; Li, Mingyang

2016-10-01

Reliability demonstration tests are usually performed in product design or validation processes to demonstrate whether a product meets specified requirements on reliability. For binomial demonstration tests, the zero-failure test has been most commonly used due to its simplicity and use of minimum sample size to achieve an acceptable consumer’s risk level. However, this test can often result in unacceptably high risk for producers as well as a low probability of passing the test even when the product has good reliability. This paper explicitly explores the interrelationship between multiple objectives that are commonly of interest when planning a demonstration test andmore » proposes structured decision-making procedures using a Pareto front approach for selecting an optimal test plan based on simultaneously balancing multiple criteria. Different strategies are suggested for scenarios with different user priorities and graphical tools are developed to help quantify the trade-offs between choices and to facilitate informed decision making. As a result, potential impacts of some subjective user inputs on the final decision are studied to offer insights and useful guidance for general applications.« less

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

PubMed

Malakooti, Behnam; Yang, Ziyong

2004-02-01

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

A leader-follower-interactive method for regional water resources management with considering multiple water demands and eco-environmental constraints

NASA Astrophysics Data System (ADS)

Chen, Yizhong; Lu, Hongwei; Li, Jing; Ren, Lixia; He, Li

2017-05-01

This study presents the mathematical formulation and implementations of a synergistic optimization framework based on an understanding of water availability and reliability together with the characteristics of multiple water demands. This framework simultaneously integrates a set of leader-followers-interactive objectives established by different decision makers during the synergistic optimization. The upper-level model (leader's one) determines the optimal pollutants discharge to satisfy the environmental target. The lower-level model (follower's one) accepts the dispatch requirement from the upper-level one and dominates the optimal water-allocation strategy to maximize economic benefits representing the regional authority. The complicated bi-level model significantly improves upon the conventional programming methods through the mutual influence and restriction between the upper- and lower-level decision processes, particularly when limited water resources are available for multiple completing users. To solve the problem, a bi-level interactive solution algorithm based on satisfactory degree is introduced into the decision-making process for measuring to what extent the constraints are met and the objective reaches its optima. The capabilities of the proposed model are illustrated through a real-world case study of water resources management system in the district of Fengtai located in Beijing, China. Feasible decisions in association with water resources allocation, wastewater emission and pollutants discharge would be sequentially generated for balancing the objectives subject to the given water-related constraints, which can enable Stakeholders to grasp the inherent conflicts and trade-offs between the environmental and economic interests. The performance of the developed bi-level model is enhanced by comparing with single-level models. Moreover, in consideration of the uncertainty in water demand and availability, sensitivity analysis and policy analysis are employed for identifying their impacts on the final decisions and improving the practical applications.

An Analysis of the Multiple Objective Capital Budgeting Problem via Fuzzy Linear Integer (0-1) Programming.

DTIC Science & Technology

1980-05-31

34 International Journal of Man- Machine Studies , Vol. 9, No. 1, 1977, pp. 1-68. [16] Zimmermann, H. J., Theory and Applications of Fuzzy Sets, Institut...Boston, Inc., Hingham, MA, 1978. [18] Yager, R. R., "Multiple Objective Decision-Making Using Fuzzy Sets," International Journal of Man- Machine Studies ...Professor of Industria Engineering ... iv t TABLE OF CONTENTS page ABSTRACT .. .. . ...... . .... ...... ........ iii LIST OF TABLES

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

PubMed Central

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

2017-01-01

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

Multi-Objective Reinforcement Learning for Cognitive Radio-Based Satellite Communications

NASA Technical Reports Server (NTRS)

Ferreira, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

2016-01-01

Previous research on cognitive radios has addressed the performance of various machine-learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different cross-layer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3.5 times for clear sky conditions and 6.8 times for rain conditions.

Multi-Objective Reinforcement Learning for Cognitive Radio Based Satellite Communications

NASA Technical Reports Server (NTRS)

Ferreira, Paulo; Paffenroth, Randy; Wyglinski, Alexander; Hackett, Timothy; Bilen, Sven; Reinhart, Richard; Mortensen, Dale John

2016-01-01

Previous research on cognitive radios has addressed the performance of various machine learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different crosslayer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3:5 times for clear sky conditions and 6:8 times for rain conditions.

Managing and learning with multiple models: Objectives and optimization algorithms

USGS Publications Warehouse

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

2011-01-01

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

The quandaries and promise of risk management: a scientist's perspective on integration of science and management.

Treesearch

B.G. Marcot

2007-01-01

This paper briefly lists constraints and problems of traditional approaches to natural resource risk analysis and risk management. Such problems include disparate definitions of risk, multiple and conflicting objectives and decisions, conflicting interpretations of uncertainty, and failure of articulating decision criteria, risk attitudes, modeling assumptions, and...

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

PubMed

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

2011-06-01

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

Nutzwertanalyse

Treesearch

A. Henne

1978-01-01

Nutzwertanalyse (NUWA) is a psychometric instrument for finding the test compromise in the multiple use planning of forestry, when the multiple objectives cannot be expressed in the same physical or monetary unit. It insures a systematic assessment of the consequences of proposed alternatives and thoroughly documents the decision process. The method leads to a ranking...

Compromise Programming in forest management

Treesearch

Boris A. Poff; Aregai Tecle; Daniel G. Neary; Brian Geils

2010-01-01

Multi-objective decision-making (MODM) is an appropriate approach for evaluating a forest management scenario involving multiple interests. Today's land managers must accommodate commercial as well as non-commercial objectives that may be expressed quantitatively and/or qualitatively, and respond to social, political, economic and cultural changes. The spatial and...

Practical Strategies for Integrating Final Ecosystem Goods and ...

EPA Pesticide Factsheets

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

A Structured approach to incidental take decision making

USGS Publications Warehouse

McGowan, Conor P.

2013-01-01

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

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

Yılmaz Balaman, Şebnem; Selim, Hasan

2015-09-01

The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

USGS Publications Warehouse

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

2017-08-23

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

Multi-objective, multiple participant decision support for water management in the Andarax catchment, Almeria

NASA Astrophysics Data System (ADS)

van Cauwenbergh, N.; Pinte, D.; Tilmant, A.; Frances, I.; Pulido-Bosch, A.; Vanclooster, M.

2008-04-01

Water management in the Andarax river basin (Almeria, Spain) is a multi-objective, multi-participant, long-term decision-making problem that faces several challenges. Adequate water allocation needs informed decisions to meet increasing socio-economic demands while respecting the environmental integrity of this basin. Key players in the Andarax water sector include the municipality of Almeria, the irrigators involved in the intensive greenhouse agricultural sector, and booming second residences. A decision support system (DSS) is developed to rank different sustainable planning and management alternatives according to their socio-economic and environmental performance. The DSS is intimately linked to sustainability indicators and is designed through a public participation process. Indicators are linked to criteria reflecting stakeholders concerns in the 2005 field survey, such as fulfilling water demand, water price, technical and economical efficiency, social and environmental impacts. Indicators can be partly quantified after simulating the operation of the groundwater reservoir over a 20-year planning period and partly through a parallel expert evaluation process. To predict the impact of future water demand in the catchment, several development scenarios are designed to be evaluated in the DSS. The successive multi-criteria analysis of the performance indicators permits the ranking of the different management alternatives according to the multiple objectives formulated by the different sectors/participants. This allows more informed and transparent decision-making processes for the Andarax river basin, recognizing both the socio-economic and environmental dimensions of water resources management.

Much Needed Structure [Structured Decision-Making with DMRCS. Define-Measure-Reduce-Combine-Select

DOE PAGES

Anderson-Cook, Christine M.; Lu, Lu

2015-10-01

We have described a new DMRCS process for structured decision making, which mirrors the approach of the DMAIC process which has become so popular within Lean Six Sigma. By dividing a complex often unstructured process into distinct steps, we hope to have made the task of balancing multiple competing objectives less daunting.

A Multi-criteria Decision Analysis System for Prioritizing Sites and Types of Low Impact Development Practices

NASA Astrophysics Data System (ADS)

Song, Jae Yeol; Chung, Eun-Sung

2017-04-01

This study developed a multi-criteria decision analysis framework to prioritize sites and types of low impact development (LID) practices. This framework was systemized as a web-based system coupled with the Storm Water Management Model (SWMM) from the Environmental Protection Agency (EPA). Using the technique for order of preference by similarity to ideal solution (TOPSIS), which is a type of multi-criteria decision-making (MCDM) method, multiple types and sites of designated LID practices are prioritized. This system is named the Water Management Prioritization Module (WMPM) and is an improved version of the Water Management Analysis Module (WMAM) that automatically generates and simulates multiple scenarios of LID design and planning parameters for a single LID type. WMPM can simultaneously determine the priority of multiple LID types and sites. In this study, an infiltration trench and permeable pavement were considered for multiple sub-catchments in South Korea to demonstrate the WMPM procedures. The TOPSIS method was manually incorporated to select the vulnerable target sub-catchments and to prioritize the LID planning scenarios for multiple types and sites considering socio-economic, hydrologic and physical-geometric factors. In this application, the Delphi method and entropy theory were used to determine the subjective and objective weights, respectively. Comparing the ranks derived by this system, two sub-catchments, S16 and S4, out of 18 were considered to be the most suitable places for installing an infiltration trench and porous pavement to reduce the peak and total flow, respectively, considering both socio-economic factors and hydrological effectiveness. WMPM can help policy-makers to objectively develop urban water plans for sustainable development. Keywords: Low Impact Development, Multi-Criteria Decision Analysis, SWMM, TOPSIS, Water Management Prioritization Module (WMPM)

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

PubMed

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

2018-01-01

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

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

Capacity planning for electronic waste management facilities under uncertainty: multi-objective multi-time-step model development.

PubMed

Poonam Khanijo Ahluwalia; Nema, Arvind K

2011-07-01

Selection of optimum locations for locating new facilities and decision regarding capacities at the proposed facilities is a major concern for municipal authorities/managers. The decision as to whether a single facility is preferred over multiple facilities of smaller capacities would vary with varying priorities to cost and associated risks such as environmental or health risk or risk perceived by the society. Currently management of waste streams such as that of computer waste is being done using rudimentary practices and is flourishing as an unorganized sector, mainly as backyard workshops in many cities of developing nations such as India. Uncertainty in the quantification of computer waste generation is another major concern due to the informal setup of present computer waste management scenario. Hence, there is a need to simultaneously address uncertainty in waste generation quantities while analyzing the tradeoffs between cost and associated risks. The present study aimed to address the above-mentioned issues in a multi-time-step, multi-objective decision-support model, which can address multiple objectives of cost, environmental risk, socially perceived risk and health risk, while selecting the optimum configuration of existing and proposed facilities (location and capacities).

A multiple-objective optimal exploration strategy

USGS Publications Warehouse

Christakos, G.; Olea, R.A.

1988-01-01

Exploration for natural resources is accomplished through partial sampling of extensive domains. Such imperfect knowledge is subject to sampling error. Complex systems of equations resulting from modelling based on the theory of correlated random fields are reduced to simple analytical expressions providing global indices of estimation variance. The indices are utilized by multiple objective decision criteria to find the best sampling strategies. The approach is not limited by geometric nature of the sampling, covers a wide range in spatial continuity and leads to a step-by-step procedure. ?? 1988.

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

Methodology for fleet deployment decisions. Final report

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

Stremel, J.; Matousek, M.

1995-01-01

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

Addressing wild turkey population declines using structured decision making

USGS Publications Warehouse

Robinson, Kelly F.; Fuller, Angela K.; Schiavone, Michael V.; Swift, Bryan L.; Diefenbach, Duane R.; Siemer, William F.; Decker, Daniel J.

2017-01-01

We present a case study from New York, USA, of the use of structured decision making (SDM) to identify fall turkey harvest regulations that best meet stakeholder objectives, in light of recent apparent declines in abundance of wild turkeys in the northeastern United States. We used the SDM framework to incorporate the multiple objectives associated with turkey hunting, stakeholder desires, and region-specific ecological and environmental factors that could influence fall harvest. We identified a set of 4 fall harvest regulations, composed of different season lengths and bag limits, and evaluated their relative achievement of the objectives. We used a stochastic turkey population model, statistical modeling, and expert elicitation to evaluate the consequences of each harvest regulation on each of the objectives. We conducted a statewide mail survey of fall turkey hunters in New York to gather the necessary information to evaluate tradeoffs among multiple objectives associated with hunter satisfaction. The optimal fall harvest regulation was a 2-week season and allowed for the harvest of 1 bird/hunter. This regulation was the most conservative of those evaluated, reflecting the concerns about recent declines in turkey abundance among agency wildlife biologists and the hunting public. Depending on the region of the state, the 2-week, 1-bird regulation was predicted to result in 7–32% more turkeys on the landscape after 5 years. The SDM process provided a transparent framework for setting fall turkey harvest regulations and reduced potential stakeholder conflict by explicitly taking the multiple objectives of different stakeholder groups into account.

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

PubMed

Veloso, Mário

2014-09-01

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

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization.

PubMed

Yang, Shaofu; Liu, Qingshan; Wang, Jun

2018-04-01

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

Participatory modeling and structured decision making

USGS Publications Warehouse

Robinson, Kelly F.; Fuller, Angela K.

2016-01-01

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

Integrated models to support multiobjective ecological restoration decisions.

PubMed

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

2017-12-01

Many objectives motivate ecological restoration, including improving vegetation condition, increasing the range and abundance of threatened species, and improving species richness and diversity. Although models have been used to examine the outcomes of ecological restoration, few researchers have attempted to develop models to account for multiple, potentially competing objectives. We developed a combined state-and-transition, species-distribution model to predict the effects of restoration actions on vegetation condition and extent, bird diversity, and the distribution of several bird species in southeastern Australian woodlands. The actions reflected several management objectives. We then validated the models against an independent data set and investigated how the best management decision might change when objectives were valued differently. We also used model results to identify effective restoration options for vegetation and bird species under a constrained budget. In the examples we evaluated, no one action (improving vegetation condition and extent, increasing bird diversity, or increasing the probability of occurrence for threatened species) provided the best outcome across all objectives. In agricultural lands, the optimal management actions for promoting the occurrence of the Brown Treecreeper (Climacteris picumnus), an iconic threatened species, resulted in little improvement in the extent of the vegetation and a high probability of decreased vegetation condition. This result highlights that the best management action in any situation depends on how much the different objectives are valued. In our example scenario, no management or weed control were most likely to be the best management options to satisfy multiple restoration objectives. Our approach to exploring trade-offs in management outcomes through integrated modeling and structured decision-support approaches has wide application for situations in which trade-offs exist between competing conservation objectives. © 2017 Society for Conservation Biology.

Seismic slope-performance analysis: from hazard map to decision support system

USGS Publications Warehouse

Miles, Scott B.; Keefer, David K.; Ho, Carlton L.

1999-01-01

In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.

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

PubMed Central

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

2010-01-01

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

Green supplier selection: a new genetic/immune strategy with industrial application

NASA Astrophysics Data System (ADS)

Kumar, Amit; Jain, Vipul; Kumar, Sameer; Chandra, Charu

2016-10-01

With the onset of the 'climate change movement', organisations are striving to include environmental criteria into the supplier selection process. This article hybridises a Green Data Envelopment Analysis (GDEA)-based approach with a new Genetic/Immune Strategy for Data Envelopment Analysis (GIS-DEA). A GIS-DEA approach provides a different view to solving multi-criteria decision making problems using data envelopment analysis (DEA) by considering DEA as a multi-objective optimisation problem with efficiency as one objective and proximity of solution to decision makers' preferences as the other objective. The hybrid approach called GIS-GDEA is applied here to a well-known automobile spare parts manufacturer in India and the results presented. User validation developed based on specific set of criteria suggests that the supplier selection process with GIS-GDEA is more practical than other approaches in a current industrial scenario with multiple decision makers.

Age Effects and Heuristics in Decision Making*

PubMed Central

Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

2011-01-01

Using controlled experiments, we examine how individuals make choices when faced with multiple options. Choice tasks are designed to mimic the selection of health insurance, prescription drug, or retirement savings plans. In our experiment, available options can be objectively ranked allowing us to examine optimal decision making. First, the probability of a person selecting the optimal option declines as the number of options increases, with the decline being more pronounced for older subjects. Second, heuristics differ by age with older subjects relying more on suboptimal decision rules. In a heuristics validation experiment, older subjects make worse decisions than younger subjects. PMID:22544977

Age Effects and Heuristics in Decision Making.

PubMed

Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael

2012-05-01

Using controlled experiments, we examine how individuals make choices when faced with multiple options. Choice tasks are designed to mimic the selection of health insurance, prescription drug, or retirement savings plans. In our experiment, available options can be objectively ranked allowing us to examine optimal decision making. First, the probability of a person selecting the optimal option declines as the number of options increases, with the decline being more pronounced for older subjects. Second, heuristics differ by age with older subjects relying more on suboptimal decision rules. In a heuristics validation experiment, older subjects make worse decisions than younger subjects.

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

USGS Publications Warehouse

Williams, Perry J.; Kendall, William L.

2017-01-01

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

A Novel Hybrid MADM Based Competence Set Expansions of a SOC Design Service Firm

NASA Astrophysics Data System (ADS)

Huang, Chi-Yo; Tzeng, Gwo-Hshiung; Lue, Yeou-Feng; Chuang, Hsiu-Tyan

As the IC (integrated circuit) industry migrates to the System-on-Chip (SOC) era, a novel business model, the SOC design service (DS), is emerging. However, how to expand a firm’s innovation competences while satisfying multiple objectives including highest quality, lowest cost, and fastest time to market as well as most revenues for economics of scale are always problems for a design service firm. Therefore, attempts to expand the innovation competences, and thus the competitiveness, of latecomers in the SOC DS industry have already become the most critical issue facing the top managers of SOC design service firms. In this paper, a novel multiple attribute decision making (MADM) analytic framework based on the concept of competence set expansion, as well as MADM methods consisting with DEMATEL, ANP and multiple objective decision making (MODM) will be proposed in order to define a path for expanding a late-coming SOC DS firm’s innovation capabilities. An empirical study on expanding innovation competence sets, of a late-coming Taiwanese DS firm then will be presented.

Using the Analytic Hierarchy Process for Decision-Making in Ecosystem Management

Treesearch

Daniel L. Schmoldt; David L. Peterson

1997-01-01

Land management activities on public lands combine multiple objectives in order to create a plan of action over a finite time horizon. Because management activities are constrained by time and money, it is critical to make the best use of available agency resources. The Analytic Hierarchy Process (AHP) offers a structure for multi-objective decisionmaking so that...

Carbon concentrations and carbon pool distributions in dry, moist, and cold mid-aged forests of the Rocky Mountains

Treesearch

Theresa B. Jain; Russell T. Graham; David Adams

2010-01-01

Although "carbon” management may not be a primary objective in forest management, influencing the distribution, composition, growth, and development of biomass to fulfill multiple objectives is; therefore, given a changing climate, managing carbon could influence future management decisions. Also, typically, the conversion from total biomass to total carbon is 50...

A parametric LQ approach to multiobjective control system design

NASA Technical Reports Server (NTRS)

Kyr, Douglas E.; Buchner, Marc

1988-01-01

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

Enhanced Decision Analysis Support System.

DTIC Science & Technology

1981-03-01

autorrares "i., the method for determining preferences when multiple and competing attributes are involved. Worth assessment is used as the model which...1967 as a method for determining preferenoe when multiple and competing attributes are involved (Rf 10). The tern worth can be - equated to other... competing objectives. After some discussion, the group decided that the problem could best be decided using the worth assessment procedure. They

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

PubMed

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

2013-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2007-06-01

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

Making objective decisions in mechanical engineering problems

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

PubMed

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

2010-02-01

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

MAGDM linear-programming models with distinct uncertain preference structures.

PubMed

Xu, Zeshui S; Chen, Jian

2008-10-01

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

Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space

PubMed Central

McCaffrey, Nikki; Agar, Meera; Harlum, Janeane; Karnon, Jonathon; Currow, David; Eckermann, Simon

2015-01-01

Introduction Comparing multiple, diverse outcomes with cost-effectiveness analysis (CEA) is important, yet challenging in areas like palliative care where domains are unamenable to integration with survival. Generic multi-attribute utility values exclude important domains and non-health outcomes, while partial analyses—where outcomes are considered separately, with their joint relationship under uncertainty ignored—lead to incorrect inference regarding preferred strategies. Objective The objective of this paper is to consider whether such decision making can be better informed with alternative presentation and summary measures, extending methods previously shown to have advantages in multiple strategy comparison. Methods Multiple outcomes CEA of a home-based palliative care model (PEACH) relative to usual care is undertaken in cost disutility (CDU) space and compared with analysis on the cost-effectiveness plane. Summary measures developed for comparing strategies across potential threshold values for multiple outcomes include: expected net loss (ENL) planes quantifying differences in expected net benefit; the ENL contour identifying preferred strategies minimising ENL and their expected value of perfect information; and cost-effectiveness acceptability planes showing probability of strategies minimising ENL. Results Conventional analysis suggests PEACH is cost-effective when the threshold value per additional day at home ( 1) exceeds $1,068 or dominated by usual care when only the proportion of home deaths is considered. In contrast, neither alternative dominate in CDU space where cost and outcomes are jointly considered, with the optimal strategy depending on threshold values. For example, PEACH minimises ENL when 1=$2,000 and 2=$2,000 (threshold value for dying at home), with a 51.6% chance of PEACH being cost-effective. Conclusion Comparison in CDU space and associated summary measures have distinct advantages to multiple domain comparisons, aiding transparent and robust joint comparison of costs and multiple effects under uncertainty across potential threshold values for effect, better informing net benefit assessment and related reimbursement and research decisions. PMID:25751629

Integrating regional conservation priorities for multiple objectives into national policy

PubMed Central

Beger, Maria; McGowan, Jennifer; Treml, Eric A.; Green, Alison L.; White, Alan T.; Wolff, Nicholas H.; Klein, Carissa J.; Mumby, Peter J.; Possingham, Hugh P.

2015-01-01

Multinational conservation initiatives that prioritize investment across a region invariably navigate trade-offs among multiple objectives. It seems logical to focus where several objectives can be achieved efficiently, but such multi-objective hotspots may be ecologically inappropriate, or politically inequitable. Here we devise a framework to facilitate a regionally cohesive set of marine-protected areas driven by national preferences and supported by quantitative conservation prioritization analyses, and illustrate it using the Coral Triangle Initiative. We identify areas important for achieving six objectives to address ecosystem representation, threatened fauna, connectivity and climate change. We expose trade-offs between areas that contribute substantially to several objectives and those meeting one or two objectives extremely well. Hence there are two strategies to guide countries choosing to implement regional goals nationally: multi-objective hotspots and complementary sets of single-objective priorities. This novel framework is applicable to any multilateral or global initiative seeking to apply quantitative information in decision making. PMID:26364769

Clinical and practical considerations in the pharmacologic management of narcolepsy.

PubMed

Thorpy, Michael J; Dauvilliers, Yves

2015-01-01

Despite published treatment recommendations and the availability of approved and off-label pharmacologic therapies for narcolepsy, the clinical management of this incurable, chronic neurologic disorder remains challenging. While treatment is generally symptomatically driven, decisions regarding which drug(s) to use need to take into account a variety of factors that may affect adherence, efficacy, and tolerability. Type 1 narcolepsy (predominantly excessive daytime sleepiness with cataplexy) or type 2 narcolepsy (excessive daytime sleepiness without cataplexy) may drive treatment decisions, with consideration given either to a single drug that targets multiple symptoms or to multiple drugs that each treat a specific symptom. Other drug-related characteristics that affect drug choice are dosing regimens, tolerability, and potential drug-drug interactions. Additionally, the patient should be an active participant in treatment decisions, and the main symptomatic complaints, treatment goals, psychosocial setting, and use of lifestyle substances (ie, alcohol, nicotine, caffeine, and cannabis) need to be discussed with respect to treatment decisions. Although there is a lack of narcolepsy-specific instruments for monitoring therapeutic effects, clinically relevant subjective and objective measures of daytime sleepiness (eg, Epworth Sleepiness Scale and Maintenance of Wakefulness Test) can be used to provide guidance on whether treatment goals are being met. These considerations are discussed with the objective of providing clinically relevant recommendations for making treatment decisions that can enhance the effective management of patients with narcolepsy. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

A decision tool for selecting trench cap designs

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

Paige, G.B.; Stone, J.J.; Lane, L.J.

1995-12-31

A computer based prototype decision support system (PDSS) is being developed to assist the risk manager in selecting an appropriate trench cap design for waste disposal sites. The selection of the {open_quote}best{close_quote} design among feasible alternatives requires consideration of multiple and often conflicting objectives. The methodology used in the selection process consists of: selecting and parameterizing decision variables using data, simulation models, or expert opinion; selecting feasible trench cap design alternatives; ordering the decision variables and ranking the design alternatives. The decision model is based on multi-objective decision theory and uses a unique approach to order the decision variables andmore » rank the design alternatives. Trench cap designs are evaluated based on federal regulations, hydrologic performance, cover stability and cost. Four trench cap designs, which were monitored for a four year period at Hill Air Force Base in Utah, are used to demonstrate the application of the PDSS and evaluate the results of the decision model. The results of the PDSS, using both data and simulations, illustrate the relative advantages of each of the cap designs and which cap is the {open_quotes}best{close_quotes} alternative for a given set of criteria and a particular importance order of those decision criteria.« less

The experiences of family members in the nursing home to hospital transfer decision.

PubMed

Abrahamson, Kathleen; Bernard, Brittany; Magnabosco, Lara; Nazir, Arif; Unroe, Kathleen T

2016-11-15

The objective of this study was to better understand the experiences of family members in the nursing home to hospital transfer decision making process. Semi-structured interviews were conducted with 20 family members who had recently been involved in a nursing home to hospital transfer decision. Family members perceived themselves to play an advocacy role in their resident's care and interview themes clustered within three over-arching categories: Family perception of the nursing home's capacity to provide medical care: Resident and family choices; and issues at 'hand-off' and the hospital. Multiple sub-themes were also identified. Findings from this study contribute to knowledge surrounding the nursing home transfer decision by illuminating the experiences of family members in the transfer decision process.

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

NASA Astrophysics Data System (ADS)

Dasarathy, Belur V.

1998-03-01

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

Structured decision making as a framework for large-scale wildlife harvest management decisions

USGS Publications Warehouse

Robinson, Kelly F.; Fuller, Angela K.; Hurst, Jeremy E.; Swift, Bryan L.; Kirsch, Arthur; Farquhar, James F.; Decker, Daniel J.; Siemer, William F.

2016-01-01

Fish and wildlife harvest management at large spatial scales often involves making complex decisions with multiple objectives and difficult tradeoffs, population demographics that vary spatially, competing stakeholder values, and uncertainties that might affect management decisions. Structured decision making (SDM) provides a formal decision analytic framework for evaluating difficult decisions by breaking decisions into component parts and separating the values of stakeholders from the scientific evaluation of management actions and uncertainty. The result is a rigorous, transparent, and values-driven process. This decision-aiding process provides the decision maker with a more complete understanding of the problem and the effects of potential management actions on stakeholder values, as well as how key uncertainties can affect the decision. We use a case study to illustrate how SDM can be used as a decision-aiding tool for management decision making at large scales. We evaluated alternative white-tailed deer (Odocoileus virginianus) buck-harvest regulations in New York designed to reduce harvest of yearling bucks, taking into consideration the values of the state wildlife agency responsible for managing deer, as well as deer hunters. We incorporated tradeoffs about social, ecological, and economic management concerns throughout the state. Based on the outcomes of predictive models, expert elicitation, and hunter surveys, the SDM process identified management alternatives that optimized competing objectives. The SDM process provided biologists and managers insight about aspects of the buck-harvest decision that helped them adopt a management strategy most compatible with diverse hunter values and management concerns.

Whole Watershed Restoration Planning Tools for Estimating Tradeoffs Among Multiple Objectives

EPA Science Inventory

We developed a set of decision support tools to assist whole watershed restoration planning in the Pacific Northwest. Here we describe how these tools are being integrated and applied in collaboration with tribes and community stakeholders to address restoration of hydrological ...

A Practical Approach to Address Uncertainty in Stakeholder Deliberations.

PubMed

Gregory, Robin; Keeney, Ralph L

2017-03-01

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

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

PubMed

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

2009-06-01

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

Reactivation of Reward-Related Patterns from Single Past Episodes Supports Memory-Based Decision Making.

PubMed

Wimmer, G Elliott; Büchel, Christian

2016-03-09

Rewarding experiences exert a strong influence on later decision making. While decades of neuroscience research have shown how reinforcement gradually shapes preferences, decisions are often influenced by single past experiences. Surprisingly, relatively little is known about the influence of single learning episodes. Although recent work has proposed a role for episodes in decision making, it is largely unknown whether and how episodic experiences contribute to value-based decision making and how the values of single episodes are represented in the brain. In multiple behavioral experiments and an fMRI experiment, we tested whether and how rewarding episodes could support later decision making. Participants experienced episodes of high reward or low reward in conjunction with incidental, trial-unique neutral pictures. In a surprise test phase, we found that participants could indeed remember the associated level of reward, as evidenced by accurate source memory for value and preferences to re-engage with rewarded objects. Further, in a separate experiment, we found that high-reward objects shown as primes before a gambling task increased financial risk taking. Neurally, re-exposure to objects in the test phase led to significant reactivation of reward-related patterns. Importantly, individual variability in the strength of reactivation predicted value memory performance. Our results provide a novel demonstration that affect-related neural patterns are reactivated during later experience. Reactivation of value information represents a mechanism by which memory can guide decision making. Copyright © 2016 the authors 0270-6474/16/362868-13$15.00/0.

Resolving future fire management conflicts using multicriteria decision making.

PubMed

Driscoll, Don A; Bode, Michael; Bradstock, Ross A; Keith, David A; Penman, Trent D; Price, Owen F

2016-02-01

Management strategies to reduce the risks to human life and property from wildfire commonly involve burning native vegetation. However, planned burning can conflict with other societal objectives such as human health and biodiversity conservation. These conflicts are likely to intensify as fire regimes change under future climates and as growing human populations encroach farther into fire-prone ecosystems. Decisions about managing fire risks are therefore complex and warrant more sophisticated approaches than are typically used. We applied a multicriteria decision making approach (MCDA) with the potential to improve fire management outcomes to the case of a highly populated, biodiverse, and flammable wildland-urban interface. We considered the effects of 22 planned burning options on 8 objectives: house protection, maximizing water quality, minimizing carbon emissions and impacts on human health, and minimizing declines of 5 distinct species types. The MCDA identified a small number of management options (burning forest adjacent to houses) that performed well for most objectives, but not for one species type (arboreal mammal) or for water quality. Although MCDA made the conflict between objectives explicit, resolution of the problem depended on the weighting assigned to each objective. Additive weighting of criteria traded off the arboreal mammal and water quality objectives for other objectives. Multiplicative weighting identified scenarios that avoided poor outcomes for any objective, which is important for avoiding potentially irreversible biodiversity losses. To distinguish reliably among management options, future work should focus on reducing uncertainty in outcomes across a range of objectives. Considering management actions that have more predictable outcomes than landscape fuel management will be important. We found that, where data were adequate, an MCDA can support decision making in the complex and often conflicted area of fire management. © 2015 Society for Conservation Biology.

Top-down modulation of visual processing and knowledge after 250 ms supports object constancy of category decisions

PubMed Central

Schendan, Haline E.; Ganis, Giorgio

2015-01-01

People categorize objects more slowly when visual input is highly impoverished instead of optimal. While bottom-up models may explain a decision with optimal input, perceptual hypothesis testing (PHT) theories implicate top-down processes with impoverished input. Brain mechanisms and the time course of PHT are largely unknown. This event-related potential study used a neuroimaging paradigm that implicated prefrontal cortex in top-down modulation of occipitotemporal cortex. Subjects categorized more impoverished and less impoverished real and pseudo objects. PHT theories predict larger impoverishment effects for real than pseudo objects because top-down processes modulate knowledge only for real objects, but different PHT variants predict different timing. Consistent with parietal-prefrontal PHT variants, around 250 ms, the earliest impoverished real object interaction started on an N3 complex, which reflects interactive cortical activity for object cognition. N3 impoverishment effects localized to both prefrontal and occipitotemporal cortex for real objects only. The N3 also showed knowledge effects by 230 ms that localized to occipitotemporal cortex. Later effects reflected (a) word meaning in temporal cortex during the N400, (b) internal evaluation of prior decision and memory processes and secondary higher-order memory involving anterotemporal parts of a default mode network during posterior positivity (P600), and (c) response related activity in posterior cingulate during an anterior slow wave (SW) after 700 ms. Finally, response activity in supplementary motor area during a posterior SW after 900 ms showed impoverishment effects that correlated with RTs. Convergent evidence from studies of vision, memory, and mental imagery which reflects purely top-down inputs, indicates that the N3 reflects the critical top-down processes of PHT. A hybrid multiple-state interactive, PHT and decision theory best explains the visual constancy of object cognition. PMID:26441701

How stakeholder roles, power, and negotiation impact natural resource policy: A political economy view

USGS Publications Warehouse

Caughlan, L.

2002-01-01

Natural resource management decisions are complicated by multiple property rights, management objectives, and stakeholders with varying degrees of influence over the decision making process. In order to make efficient decisions, managers must incorporate the opinions and values of the involved stakeholders as well as understand the complex institutional constraints and opportunities that influence the decision-making process. Often this type of information is not understood until after a decision has been made, which can result in wasted time and effort.The purpose of my dissertation was to show how institutional frameworks and stakeholder involvement influence the various phases of the resource management decision-making process in a public choice framework. The intent was to assist decision makers and stakeholders by developing a methodology for formally incorporating stakeholders'' objectives and influence into the resource management planning process and to predict the potential success of rent-seeking activity based on stakeholder preferences and level of influence. Concepts from decision analysis, institutional analysis, and public choice economics were used in designing this interdisciplinary framework. The framework was then applied to an actual case study concerning elk and bison management on the National Elk Refuge and Grand Teton National Park near Jackson, Wyoming. The framework allowed for the prediction of the level of support and conflict for all relevant policy decisions, and the identification of each stakeholder''s level of support or opposition for each management decision.

Dynamic Network Selection for Multicast Services in Wireless Cooperative Networks

NASA Astrophysics Data System (ADS)

Chen, Liang; Jin, Le; He, Feng; Cheng, Hanwen; Wu, Lenan

In next generation mobile multimedia communications, different wireless access networks are expected to cooperate. However, it is a challenging task to choose an optimal transmission path in this scenario. This paper focuses on the problem of selecting the optimal access network for multicast services in the cooperative mobile and broadcasting networks. An algorithm is proposed, which considers multiple decision factors and multiple optimization objectives. An analytic hierarchy process (AHP) method is applied to schedule the service queue and an artificial neural network (ANN) is used to improve the flexibility of the algorithm. Simulation results show that by applying the AHP method, a group of weight ratios can be obtained to improve the performance of multiple objectives. And ANN method is effective to adaptively adjust weight ratios when users' new waiting threshold is generated.

Multi-Objective Programming for Lot-Sizing with Quantity Discount

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

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

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

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

A negotiation methodology and its application to cogeneration planning

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

Wang, S.M.; Liu, C.C.; Luu, S.

Power system planning has become a complex process in utilities today. This paper presents a methodology for integrated planning with multiple objectives. The methodology uses a graphical representation (Goal-Decision Network) to capture the planning knowledge. The planning process is viewed as a negotiation process that applies three negotiation operators to search for beneficial decisions in a GDN. Also, the negotiation framework is applied to the problem of planning for cogeneration interconnection. The simulation results are presented to illustrate the cogeneration planning process.

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

NASA Astrophysics Data System (ADS)

Colas, Francis; Bessière, Pierre; Girard, Benoît

2011-03-01

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

Who to Blame: Irrational Decision-Makers or Stupid Modelers? (Arne Richter Award for Outstanding Young Scientists Lecture)

NASA Astrophysics Data System (ADS)

Madani, Kaveh

2016-04-01

Water management benefits from a suite of modelling tools and techniques that help simplifying and understanding the complexities involved in managing water resource systems. Early water management models were mainly concerned with optimizing a single objective, related to the design, operations or management of water resource systems (e.g. economic cost, hydroelectricity production, reliability of water deliveries). Significant improvements in methodologies, computational capacity, and data availability over the last decades have resulted in developing more complex water management models that can now incorporate multiple objectives, various uncertainties, and big data. These models provide an improved understanding of complex water resource systems and provide opportunities for making positive impacts. Nevertheless, there remains an alarming mismatch between the optimal solutions developed by these models and the decisions made by managers and stakeholders of water resource systems. Modelers continue to consider decision makers as irrational agents who fail to implement the optimal solutions developed by sophisticated and mathematically rigours water management models. On the other hand, decision makers and stakeholders accuse modelers of being idealist, lacking a perfect understanding of reality, and developing 'smart' solutions that are not practical (stable). In this talk I will have a closer look at the mismatch between the optimality and stability of solutions and argue that conventional water resources management models suffer inherently from a full-cooperation assumption. According to this assumption, water resources management decisions are based on group rationality where in practice decisions are often based on individual rationality, making the group's optimal solution unstable for individually rational decision makers. I discuss how game theory can be used as an appropriate framework for addressing the irrational "rationality assumption" of water resources management models and for better capturing the social aspects of decision making in water management systems with multiple stakeholders.

Understanding user needs for carbon monitoring information

NASA Astrophysics Data System (ADS)

Duren, R. M.; Macauley, M.; Gurney, K. R.; Saatchi, S. S.; Woodall, C. W.; Larsen, K.; Reidmiller, D.; Hockstad, L.; Weitz, M.; Croes, B.; Down, A.; West, T.; Mercury, M.

2015-12-01

The objectives of the Understanding User Needs project for NASA's Carbon Monitoring System (CMS) program are to: 1) engage the user community and identify needs for policy-relevant carbon monitoring information, 2) evaluate current and planned CMS data products with regard to their value for decision making, and 3) explore alternative methods for visualizing and communicating carbon monitoring information and associated uncertainties to decision makers and other stakeholders. To meet these objectives and help establish a sustained link between science and decision-making we have established a multi-disciplinary team that combines expertise in carbon-cycle science, engineering, economics, and carbon management and policy. We will present preliminary findings regarding emerging themes and needs for carbon information that may warrant increased attention by the science community. We will also demonstrate a new web-based tool that offers a common framework for facilitating user evaluation of carbon data products from multiple CMS projects.

A multiple-point spatially weighted k-NN method for object-based classification

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

2016-10-01

Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

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

PubMed Central

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

2015-01-01

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

An environmental decision framework applied to marine engine control technologies.

PubMed

Corbett, James J; Chapman, David

2006-06-01

This paper develops a decision framework for considering emission control technologies on marine engines, informed by standard decision theory, with an open structure that may be adapted by operators with specific vessel and technology attributes different from those provided here. Attributes relate objectives important to choosing control technologies with specific alternatives that may meet several of the objectives differently. The transparent framework enables multiple stakeholders to understand how different subjective judgments and varying attribute properties may result in different technology choices. Standard scoring techniques ensure that attributes are not biased by subjective scoring and that weights are the primary quantitative input where subjective preferences are exercised. An expected value decision structure is adopted that considers probabilities (likelihood) that a given alternative can meet its claims; alternative decision criteria are discussed. Capital and annual costs are combined using a net present value approach. An iterative approach is advocated that allows for screening and disqualifying alternatives that do not meet minimum conditions for acceptance, such as engine warranty or U.S. Coast Guard requirements. This decision framework assists vessel operators in considering explicitly important attributes and in representing choices clearly to other stakeholders concerned about reducing air pollution from vessels. This general decision structure may also be applied similarly to other environmental controls in marine applications.

System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Goienetxea Uriarte, A.; Ruiz Zúñiga, E.; Urenda Moris, M.; Ng, A. H. C.

2015-05-01

Discrete Event Simulation (DES) is nowadays widely used to support decision makers in system analysis and improvement. However, the use of simulation for improving stochastic logistic processes is not common among healthcare providers. The process of improving healthcare systems involves the necessity to deal with trade-off optimal solutions that take into consideration a multiple number of variables and objectives. Complementing DES with Multi-Objective Optimization (SMO) creates a superior base for finding these solutions and in consequence, facilitates the decision-making process. This paper presents how SMO has been applied for system improvement analysis in a Swedish Emergency Department (ED). A significant number of input variables, constraints and objectives were considered when defining the optimization problem. As a result of the project, the decision makers were provided with a range of optimal solutions which reduces considerably the length of stay and waiting times for the ED patients. SMO has proved to be an appropriate technique to support healthcare system design and improvement processes. A key factor for the success of this project has been the involvement and engagement of the stakeholders during the whole process.

Robustness analysis of a green chemistry-based model for the ...

EPA Pesticide Factsheets

This paper proposes a robustness analysis based on Multiple Criteria Decision Aiding (MCDA). The ensuing model was used to assess the implementation of green chemistry principles in the synthesis of silver nanoparticles. Its recommendations were also compared to an earlier developed model for the same purpose to investigate concordance between the models and potential decision support synergies. A three-phase procedure was adopted to achieve the research objectives. Firstly, an ordinal ranking of the evaluation criteria used to characterize the implementation of green chemistry principles was identified through relative ranking analysis. Secondly, a structured selection process for an MCDA classification method was conducted, which ensued in the identification of Stochastic Multi-Criteria Acceptability Analysis (SMAA). Lastly, the agreement of the classifications by the two MCDA models and the resulting synergistic role of decision recommendations were studied. This comparison showed that the results of the two models agree between 76% and 93% of the simulation set-ups and it confirmed that different MCDA models provide a more inclusive and transparent set of recommendations. This integrative research confirmed the beneficial complementary use of MCDA methods to aid responsible development of nanosynthesis, by accounting for multiple objectives and helping communication of complex information in a comprehensive and traceable format, suitable for stakeholders and

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Evolutionary Agent-based Models to design distributed water management strategies

NASA Astrophysics Data System (ADS)

Giuliani, M.; Castelletti, A.; Reed, P. M.

2012-12-01

There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a synthetic case study, representing a Y-shaped system composed by two regulated lakes, whose releases merge just upstream of a city. Each reservoir is operated by an agent in order to prevent floods along the lake shores (local objective). However, the optimal operation of the reservoirs with respect to the local objectives is conflicting with the minimization of floods in the city (global objective). The evolution of the Agent-based Model from individualistic management strategies of the reservoirs toward a global compromise that reduces the costs for the city is analysed.

Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems

USGS Publications Warehouse

Neckles, Hilary A.; Lyons, James E.; Guntenspergen, Glenn R.; Shriver, W. Gregory; Adamowicz, Susan C.

2015-01-01

Most salt marshes in the USA have been degraded by human activities, and coastal managers are faced with complex choices among possible actions to restore or enhance ecosystem integrity. We applied structured decision making (SDM) to guide selection of monitoring variables and management priorities for salt marshes within the National Wildlife Refuge System in the northeastern USA. In general, SDM is a systematic process for decomposing a decision into its essential elements. We first engaged stakeholders in clarifying regional salt marsh decision problems, defining objectives and attributes to evaluate whether objectives are achieved, and developing a pool of alternative management actions for achieving objectives. Through this process, we identified salt marsh attributes that were applicable to monitoring National Wildlife Refuges on a regional scale and that targeted management needs. We then analyzed management decisions within three salt marsh units at Prime Hook National Wildlife Refuge, coastal Delaware, as a case example of prioritizing management alternatives. Values for salt marsh attributes were estimated from 2 years of baseline monitoring data and expert opinion. We used linear value modeling to aggregate multiple attributes into a single performance score for each alternative, constrained optimization to identify alternatives that maximized total management benefits subject to refuge-wide cost constraints, and used graphical analysis to identify the optimal set of alternatives for the refuge. SDM offers an efficient, transparent approach for integrating monitoring into management practice and improving the quality of management decisions.

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

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

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

2016-08-15

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

Use of structured decision-making to explicitly incorporate environmental process understanding in management of coastal restoration projects: Case study on barrier islands of the northern Gulf of Mexico.

PubMed

Dalyander, P Soupy; Meyers, Michelle; Mattsson, Brady; Steyer, Gregory; Godsey, Elizabeth; McDonald, Justin; Byrnes, Mark; Ford, Mark

2016-12-01

Coastal ecosystem management typically relies on subjective interpretation of scientific understanding, with limited methods for explicitly incorporating process knowledge into decisions that must meet multiple, potentially competing stakeholder objectives. Conversely, the scientific community lacks methods for identifying which advancements in system understanding would have the highest value to decision-makers. A case in point is barrier island restoration, where decision-makers lack tools to objectively use system understanding to determine how to optimally use limited contingency funds when project construction in this dynamic environment does not proceed as expected. In this study, collaborative structured decision-making (SDM) was evaluated as an approach to incorporate process understanding into mid-construction decisions and to identify priority gaps in knowledge from a management perspective. The focus was a barrier island restoration project at Ship Island, Mississippi, where sand will be used to close an extensive breach that currently divides the island. SDM was used to estimate damage that may occur during construction, and guide repair decisions within the confines of limited availability of sand and funding to minimize adverse impacts to project objectives. Sand was identified as more limiting than funds, and unrepaired major breaching would negatively impact objectives. Repairing minor damage immediately was determined to be generally more cost effective (depending on the longshore extent) than risking more damage to a weakened project. Key gaps in process-understanding relative to project management were identified as the relationship of island width to breach formation; the amounts of sand lost during breaching, lowering, or narrowing of the berm; the potential for minor breaches to self-heal versus developing into a major breach; and the relationship between upstream nourishment and resiliency of the berm to storms. This application is a prototype for using structured decision-making in support of engineering projects in dynamic environments where mid-construction decisions may arise; highlights uncertainty about barrier island physical processes that limit the ability to make robust decisions; and demonstrates the potential for direct incorporation of process-based models in a formal adaptive management decision framework. Published by Elsevier Ltd.

Use of structured decision-making to explicitly incorporate environmental process understanding in management of coastal restoration projects: Case study on barrier islands of the northern Gulf of Mexico

USGS Publications Warehouse

Dalyander, P. Soupy; Meyers, Michelle B.; Mattsson, Brady; Steyer, Gregory; Godsey, Elizabeth; McDonald, Justin; Byrnes, Mark R.; Ford, Mark

2016-01-01

Coastal ecosystem management typically relies on subjective interpretation of scientific understanding, with limited methods for explicitly incorporating process knowledge into decisions that must meet multiple, potentially competing stakeholder objectives. Conversely, the scientific community lacks methods for identifying which advancements in system understanding would have the highest value to decision-makers. A case in point is barrier island restoration, where decision-makers lack tools to objectively use system understanding to determine how to optimally use limited contingency funds when project construction in this dynamic environment does not proceed as expected. In this study, collaborative structured decision-making (SDM) was evaluated as an approach to incorporate process understanding into mid-construction decisions and to identify priority gaps in knowledge from a management perspective. The focus was a barrier island restoration project at Ship Island, Mississippi, where sand will be used to close an extensive breach that currently divides the island. SDM was used to estimate damage that may occur during construction, and guide repair decisions within the confines of limited availability of sand and funding to minimize adverse impacts to project objectives. Sand was identified as more limiting than funds, and unrepaired major breaching would negatively impact objectives. Repairing minor damage immediately was determined to be generally more cost effective (depending on the longshore extent) than risking more damage to a weakened project. Key gaps in process-understanding relative to project management were identified as the relationship of island width to breach formation; the amounts of sand lost during breaching, lowering, or narrowing of the berm; the potential for minor breaches to self-heal versus developing into a major breach; and the relationship between upstream nourishment and resiliency of the berm to storms. This application is a prototype for using structured decision-making in support of engineering projects in dynamic environments where mid-construction decisions may arise; highlights uncertainty about barrier island physical processes that limit the ability to make robust decisions; and demonstrates the potential for direct incorporation of process-based models in a formal adaptive management decision framework.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Influence of age, sex, and education on the Visual Object and Space Perception Battery (VOSP) in a healthy normal elderly population.

PubMed

Herrera-Guzmán, I; Peña-Casanova, J; Lara, J P; Gudayol-Ferré, E; Böhm, P

2004-08-01

The assessment of visual perception and cognition forms an important part of any general cognitive evaluation. We have studied the possible influence of age, sex, and education on a normal elderly Spanish population (90 healthy subjects) in performance in visual perception tasks. To evaluate visual perception and cognition, we have used the subjects performance with The Visual Object and Space Perception Battery (VOSP). The test consists of 8 subtests: 4 measure visual object perception (Incomplete Letters, Silhouettes, Object Decision, and Progressive Silhouettes) while the other 4 measure visual space perception (Dot Counting, Position Discrimination, Number Location, and Cube Analysis). The statistical procedures employed were either simple or multiple linear regression analyses (subtests with normal distribution) and Mann-Whitney tests, followed by ANOVA with Scheffe correction (subtests without normal distribution). Age and sex were found to be significant modifying factors in the Silhouettes, Object Decision, Progressive Silhouettes, Position Discrimination, and Cube Analysis subtests. Educational level was found to be a significant predictor of function for the Silhouettes and Object Decision subtests. The results of the sample were adjusted in line with the differences observed. Our study also offers preliminary normative data for the administration of the VOSP to an elderly Spanish population. The results are discussed and compared with similar studies performed in different cultural backgrounds.

Recent advances in applying decision science to managing national forests

USGS Publications Warehouse

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

2012-01-01

Management of federal public forests to meet sustainability goals and multiple use regulations is an immense challenge. To succeed, we suggest use of formal decision science procedures and tools in the context of structured decision making (SDM). SDM entails four stages: problem structuring (framing the problem and defining objectives and evaluation criteria), problem analysis (defining alternatives, evaluating likely consequences, identifying key uncertainties, and analyzing tradeoffs), decision point (identifying the preferred alternative), and implementation and monitoring the preferred alternative with adaptive management feedbacks. We list a wide array of models, techniques, and tools available for each stage, and provide three case studies of their selected use in National Forest land management and project plans. Successful use of SDM involves participation by decision-makers, analysts, scientists, and stakeholders. We suggest specific areas for training and instituting SDM to foster transparency, rigor, clarity, and inclusiveness in formal decision processes regarding management of national forests.

Incentives for Optimal Multi-level Allocation of HIV Prevention Resources

PubMed Central

Malvankar, Monali M.; Zaric, Gregory S.

2013-01-01

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

Improving the Performance of Highly Constrained Water Resource Systems using Multiobjective Evolutionary Algorithms and RiverWare

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Zagona, E. A.

2015-12-01

Instead of building new infrastructure to increase their supply reliability, water resource managers are often tasked with better management of current systems. The managers often have existing simulation models that aid their planning, and lack methods for efficiently generating and evaluating planning alternatives. This presentation discusses how multiobjective evolutionary algorithm (MOEA) decision support can be used with the sophisticated water infrastructure model, RiverWare, in highly constrained water planning environments. We first discuss a study that performed a many-objective tradeoff analysis of water supply in the Tarrant Regional Water District (TRWD) in Texas. RiverWare is combined with the Borg MOEA to solve a seven objective problem that includes systemwide performance objectives and individual reservoir storage reliability. Decisions within the formulation balance supply in multiple reservoirs and control pumping between the eastern and western parts of the system. The RiverWare simulation model is forced by two stochastic hydrology scenarios to inform how management changes in wet versus dry conditions. The second part of the presentation suggests how a broader set of RiverWare-MOEA studies can inform tradeoffs in other systems, especially in political situations where multiple actors are in conflict over finite water resources. By incorporating quantitative representations of diverse parties' objectives during the search for solutions, MOEAs may provide support for negotiations and lead to more widely beneficial water management outcomes.

Managing expectations from our land: 3 is the magic number.

NASA Astrophysics Data System (ADS)

Creamer, Rachel; Schulte, Rogier; O'Sullivan, Lilian; Staes, Jan; Vrebos, Dirk; Jones, Arwyn

2017-04-01

In recent years, sustainable food production has risen to the top of the EU policy agenda. Europe's land is now expected to provide multiple ecosystem services (soil functions) for society. These include: i) food production, ii) carbon storage, iii) the provision of clean water, iv) habitats for biodiversity and v) nutrient cycling. A tension exists between the demand for and supply of these soil functions on our land. We cannot expect all soil functions to be delivered simultaneously to optimal capacity, but with careful decision making we can optimise our soils to provide multiple functions. Our societal demands also vary in spatial extent, for example we may require nutrient cycling and food production to be focussed at local scale, but carbon sequestration may be a national target to reduce greenhouse gas emissions. Every day, farmers make decisions on how they manage their land and soil. At the same time, national and European policy makers make long-term decisions on how to manage their soil resources at larger scales. Therefore, the contemporary challenge for researchers and stakeholders is to link the decision making on land management across scales, so that the practicalities of how farmers make decisions is reflected in policy formation and that policies enable farmers to make decisions that meet EU policy objectives. LANDMARK (LAND Management: Assessment, Research, Knowledge base) is a Horizon 2020 consortium of 22 partner institutes from 14 EU countries plus Switzerland, China and Brazil. The primary objective of the LANDMARK project is to provide a policy framework for Functional Land Management at EU level. This implies the identification of policy instruments that could guide the management of soil functions at the appropriate scale. This presentation will provide an overview of the challenge faced across these scales, from local to European, it will demonstrate how local decision making must try and account for the delivery of at least three soil functions to contribute to sustainable soil management.

A hybrid credibility-based fuzzy multiple objective optimisation to differential pricing and inventory policies with arbitrage consideration

NASA Astrophysics Data System (ADS)

Ghasemy Yaghin, R.; Fatemi Ghomi, S. M. T.; Torabi, S. A.

2015-10-01

In most markets, price differentiation mechanisms enable manufacturers to offer different prices for their products or services in different customer segments; however, the perfect price discrimination is usually impossible for manufacturers. The importance of accounting for uncertainty in such environments spurs an interest to develop appropriate decision-making tools to deal with uncertain and ill-defined parameters in joint pricing and lot-sizing problems. This paper proposes a hybrid bi-objective credibility-based fuzzy optimisation model including both quantitative and qualitative objectives to cope with these issues. Taking marketing and lot-sizing decisions into account simultaneously, the model aims to maximise the total profit of manufacturer and to improve service aspects of retailing simultaneously to set different prices with arbitrage consideration. After applying appropriate strategies to defuzzify the original model, the resulting non-linear multi-objective crisp model is then solved by a fuzzy goal programming method. An efficient stochastic search procedure using particle swarm optimisation is also proposed to solve the non-linear crisp model.

Classifying four-category visual objects using multiple ERP components in single-trial ERP.

PubMed

Qin, Yu; Zhan, Yu; Wang, Changming; Zhang, Jiacai; Yao, Li; Guo, Xiaojuan; Wu, Xia; Hu, Bin

2016-08-01

Object categorization using single-trial electroencephalography (EEG) data measured while participants view images has been studied intensively. In previous studies, multiple event-related potential (ERP) components (e.g., P1, N1, P2, and P3) were used to improve the performance of object categorization of visual stimuli. In this study, we introduce a novel method that uses multiple-kernel support vector machine to fuse multiple ERP component features. We investigate whether fusing the potential complementary information of different ERP components (e.g., P1, N1, P2a, and P2b) can improve the performance of four-category visual object classification in single-trial EEGs. We also compare the classification accuracy of different ERP component fusion methods. Our experimental results indicate that the classification accuracy increases through multiple ERP fusion. Additional comparative analyses indicate that the multiple-kernel fusion method can achieve a mean classification accuracy higher than 72 %, which is substantially better than that achieved with any single ERP component feature (55.07 % for the best single ERP component, N1). We compare the classification results with those of other fusion methods and determine that the accuracy of the multiple-kernel fusion method is 5.47, 4.06, and 16.90 % higher than those of feature concatenation, feature extraction, and decision fusion, respectively. Our study shows that our multiple-kernel fusion method outperforms other fusion methods and thus provides a means to improve the classification performance of single-trial ERPs in brain-computer interface research.

Preparing future fisheries professionals to make good decisions

USGS Publications Warehouse

Colvin, Michael E.; Peterson, James T.

2017-01-01

Future fisheries professionals will face decision-making challenges in an increasingly complex field of fisheries management. Though fisheries students are well trained in the use of the scientific method to understand the natural world, they are rarely exposed to structured decision making (SDM) as part of an undergraduate or graduate education. Specifically, SDM encourages users (e.g., students, managers) to think critically and communicate the problem and then identify specific, measurable objectives as they relate to the problem. Next, users must think critically and creatively about management alternatives that can be used to meet the objectives—there must be more than one alternative or there is no decision to be made. Lastly, the management alternatives are evaluated with regard to how likely they are to succeed in terms of multiple, possibly completing, objectives, such as how stakeholder groups value outcomes of management actions versus monetary cost. We believe that exposure to SDM and its elements is an important part of preparing future fisheries professional to meet the challenges they may face. These challenges include reduced budgets, the growth of potentially competing natural resource interest groups, and stakeholder desire to be involved in management decisions affecting public trust resources, just to name a few.

Interactive Reference Point Procedure Based on the Conic Scalarizing Function

PubMed Central

2014-01-01

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

Modeling Choice Under Uncertainty in Military Systems Analysis

DTIC Science & Technology

1991-11-01

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

Cover estimations using object-based image analysis rule sets developed across multiple scales in pinyon-juniper woodlands

USDA-ARS?s Scientific Manuscript database

Numerous studies have been conducted that evaluate the utility of remote sensing for monitoring and assessing vegetation and ground cover to support land management decisions and complement ground-measurements. However, few land cover comparisons have been made using high-resolution imagery and obj...

How Question Types Reveal Student Thinking: An Experimental Comparison of Multiple-True-False and Free-Response Formats

ERIC Educational Resources Information Center

Hubbard, Joanna K.; Potts, Macy A.; Couch, Brian A.

2017-01-01

Assessments represent an important component of undergraduate courses because they affect how students interact with course content and gauge student achievement of course objectives. To make decisions on assessment design, instructors must understand the affordances and limitations of available question formats. Here, we use a crossover…

The Program Evaluator's Role in Cross-Project Pollination.

ERIC Educational Resources Information Center

Yasgur, Bruce J.

An expanded duties role of the multiple-program evaluator as an integral part of the ongoing decision-making process in all projects served is defended. Assumptions discussed included that need for projects with related objectives to pool resources and avoid duplication of effort and the evaluator's unique ability to provide an objective…

Forest Management Under Uncertainty for Multiple Bird Population Objectives

Treesearch

Clinton T. Moore; W. Todd Plummer; Michael J. Conroy

2005-01-01

We advocate adaptive programs of decision making and monitoring for the management of forest birds when responses by populations to management, and particularly management trade-offs among populations, are uncertain. Models are necessary components of adaptive management. Under this approach, uncertainty about the behavior of a managed system is explicitly captured in...

The Liberation Procedure Decision-Making Experience for People With Multiple Sclerosis

PubMed Central

Murray, Cynthia L.; Ploughman, Michelle; Harris, Chelsea; Hogan, Stephen; Murdoch, Michelle; Stefanelli, Mark

2014-01-01

Despite the absence of scientific evidence demonstrating the efficacy of the “liberation procedure” in treating multiple sclerosis (MS), thousands of MS patients worldwide have undergone the procedure. The study objective was to explore the experience of liberation procedure decision making for individuals with MS. Fifteen adults in Newfoundland and Labrador, Canada, each participated in an in-depth interview. The data analysis revealed three groups of people: “waiters,” “early embracers,” and “late embracers.” Using van Manen’s hermeneutic phenomenological approach, we identified three themes each in the stories of the early and late embracers and four themes in the waiters’ stories. A characteristic of the late embracers and waiters was skepticism, whereas desperation set the embracers apart from the waiters. With a deeper understanding of the experience, nurses can be more attuned to the perspectives of MS patients while helping them make informed decisions about undergoing the liberation procedure. PMID:28462292

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

PubMed

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

Pasam, Gopi Krishna; Manohar, T. Gowri

2016-09-01

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

Model for Bi-objective emergency rescue vehicle routing optimization

NASA Astrophysics Data System (ADS)

Yang, Yuhang

2017-03-01

Vehicle routing problem is an important research topic in management science. In this paper, one vehicle can rescue multiple disaster points and two optimization objectives are rescue time and rescue effect. Rescue effect is expressed as the ratio of unloaded material to arrival time when rescue vehicles participate in rescue every time. In this paper, the corresponding emergency rescue model is established and the effectiveness of the model is verified by simulated annealing algorithm. It can provide the basis for practical decision-making.

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

PubMed

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

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

PubMed Central

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

2014-01-01

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

Estimating and controlling workplace risk: an approach for occupational hygiene and safety professionals.

PubMed

Toffel, Michael W; Birkner, Lawrence R

2002-07-01

The protection of people and physical assets is the objective of health and safety professionals and is accomplished through the paradigm of anticipation, recognition, evaluation, and control of risks in the occupational environment. Risk assessment concepts are not only used by health and safety professionals, but also by business and financial planners. Since meeting health and safety objectives requires financial resources provided by business and governmental managers, the hypothesis addressed here is that health and safety risk decisions should be made with probabilistic processes used in financial decision-making and which are familiar and recognizable to business and government planners and managers. This article develops the processes and demonstrates the use of incident probabilities, historic outcome information, and incremental impact analysis to estimate risk of multiple alternatives in the chemical process industry. It also analyzes how the ethical aspects of decision-making can be addressed in formulating health and safety risk management plans. It is concluded that certain, easily understood, and applied probabilistic risk assessment methods used by business and government to assess financial and outcome risk have applicability to improving workplace health and safety in three ways: 1) by linking the business and health and safety risk assessment processes to securing resources, 2) by providing an additional set of tools for health and safety risk assessment, and 3) by requiring the risk assessor to consider multiple risk management alternatives.

Intelligent reservoir operation system based on evolving artificial neural networks

NASA Astrophysics Data System (ADS)

Chaves, Paulo; Chang, Fi-John

2008-06-01

We propose a novel intelligent reservoir operation system based on an evolving artificial neural network (ANN). Evolving means the parameters of the ANN model are identified by the GA evolutionary optimization technique. Accordingly, the ANN model should represent the operational strategies of reservoir operation. The main advantages of the Evolving ANN Intelligent System (ENNIS) are as follows: (i) only a small number of parameters to be optimized even for long optimization horizons, (ii) easy to handle multiple decision variables, and (iii) the straightforward combination of the operation model with other prediction models. The developed intelligent system was applied to the operation of the Shihmen Reservoir in North Taiwan, to investigate its applicability and practicability. The proposed method is first built to a simple formulation for the operation of the Shihmen Reservoir, with single objective and single decision. Its results were compared to those obtained by dynamic programming. The constructed network proved to be a good operational strategy. The method was then built and applied to the reservoir with multiple (five) decision variables. The results demonstrated that the developed evolving neural networks improved the operation performance of the reservoir when compared to its current operational strategy. The system was capable of successfully simultaneously handling various decision variables and provided reasonable and suitable decisions.

Aircraft accident investigation: the decision-making in initial action scenario.

PubMed

Barreto, Marcia M; Ribeiro, Selma L O

2012-01-01

In the complex aeronautical environment, the efforts in terms of operational safety involve the adoption of proactive and reactive measures. The process of investigation begins right after the occurrence of the aeronautical accident, through the initial action. Thus, it is in the crisis scenario, that the person responsible for the initial action makes decisions and gathers the necessary information for the subsequent phases of the investigation process. Within this scenario, which is a natural environment, researches have shown the fragility of rational models of decision making. The theoretical perspective of naturalistic decision making constitutes a breakthrough in the understanding of decision problems demanded by real world. The proposal of this study was to verify if the initial action, after the occurrence of an accident, and the decision-making strategies, used by the investigators responsible for this activity, are characteristic of the naturalistic decision making theoretical approach. To attend the proposed objective a descriptive research was undertaken with a sample of professionals that work in this activity. The data collected through individual interviews were analyzed and the results demonstrated that the initial action environment, which includes restricted time, dynamic conditions, the presence of multiple actors, stress and insufficient information is characteristic of the naturalistic decision making. They also demonstrated that, when the investigators make their decisions, they use their experience and the mental simulation, intuition, improvisation, metaphors and analogues cases, as strategies, all of them related to the naturalistic approach of decision making, in order to satisfy the needs of the situation and reach the objectives of the initial action in the accident scenario.

Evidence-based medicine, the research-practice gap, and biases in medical and surgical decision making in dermatology.

PubMed

Eaglstein, William H

2010-10-01

The objectives of this article are to promote a better understanding of a group of biases that influence therapeutic decision making by physicians/dermatologists and to raise the awareness that these biases contribute to a research-practice gap that has an impact on physicians and treatment solutions. The literature included a wide range of peer-reviewed articles dealing with biases in decision making, evidence-based medicine, randomized controlled clinical trials, and the research-practice gap. Bias against new therapies, bias in favor of indirect harm or omission, and bias against change when multiple new choices are offered may unconsciously affect therapeutic decision making. Although there is no comprehensive understanding or theory as to how choices are made by physicians, recognition of certain cognition patterns and their associated biases will help narrow the research-practice gap and optimize decision making regarding therapeutic choices.

Managing United States public lands in response to climate change: a view from the ground up.

PubMed

Ellenwood, Mikaela S; Dilling, Lisa; Milford, Jana B

2012-05-01

Federal land managers are faced with the task of balancing multiple uses and goals when making decisions about land use and the activities that occur on public lands. Though climate change is now well recognized by federal agencies and their local land and resource managers, it is not yet clear how issues related to climate change will be incorporated into on-the-ground decision making within the framework of multiple use objectives. We conducted a case study of a federal land management agency field office, the San Juan Public Lands Center in Durango, CO, U.S.A., to understand from their perspective how decisions are currently made, and how climate change and carbon management are being factored into decision making. We evaluated three major management sectors in which climate change or carbon management may intersect other use goals: forests, biofuels, and grazing. While land managers are aware of climate change and eager to understand more about how it might affect land resources, the incorporation of climate change considerations into everyday decision making is currently quite limited. Climate change is therefore on the radar screen, but remains a lower priority than other issues. To assist the office in making decisions that are based on sound scientific information, further research is needed into how management activities influence carbon storage and resilience of the landscape under climate change.

How parents and physicians experience end-of-life decision-making for children with profound intellectual and multiple disabilities.

PubMed

Zaal-Schuller, I H; Willems, D L; Ewals, F V P M; van Goudoever, J B; de Vos, M A

2016-12-01

End-of-life decisions (EoLD) often concern children with profound intellectual and multiple disabilities (PIMD). Yet, little is known about how parents and physicians discuss and make these decisions. The objective of this research was to investigate the experiences of the parents and the involved physician during the end-of-life decision-making (EoLDM) process for children with PIMD. In a retrospective, qualitative study, we conducted semi-structured interviews with the physicians and parents of 14 children with PIMD for whom an EoLD was made within the past two years. A long-lasting relationship appeared to facilitate the EoLDM process, although previous negative healthcare encounters could also lead to distrust. Parents and physicians encountered disagreements during the EoLDM process, but these disagreements could also improve the decision-making process. Most parents, as well as most physicians, considered the parents to be the experts on their child. In making an EoLD, both parents and physicians preferred a shared decision-making approach, although they differed in what they actually meant by this concept. The EoLDM process for children with PIMD can be improved if physicians are more aware of the specific situation and of the roles and expectations of the parents of children with PIMD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hazardous fuels management in mixed red pine and eastern white pine forest in the northern Lake States: A synthesis of knowledge

Treesearch

Eric Toman; David M. Hix; P. Charles Goebel; Stanley D. Gehrt; Robyn S. Wilson; Jennifer A. Sherry; Alexander Silvis; Priscilla Nyamai; Roger A. Williams; Sarah McCaffrey

2014-01-01

Fuels reduction decisions are made within a larger context of resource management characterized by multiple objectives including ecosystem restoration, wildlife management, commodity production (from timber to nontraditional forest products), and provision of recreation opportunities and amenity values. Implementation of fuels treatments is strongly influenced by their...

An economic analysis of harvest behavior: integrating forest and ownership characteristics

Treesearch

Donald F. Dennis

1989-01-01

This study provides insight into the determinants of timber supply from private forests through development of both theoretical and empirical models of harvest behavior. A microeconomic model encompasses the multiple objective nature of private ownership by examining the harvest decision for landowners who derive utility from forest amenities and from income used for...

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.

"Notice of Violation of IEEE Publication Principles" Multiobjective Reinforcement Learning: A Comprehensive Overview.

PubMed

Liu, Chunming; Xu, Xin; Hu, Dewen

2013-04-29

Reinforcement learning is a powerful mechanism for enabling agents to learn in an unknown environment, and most reinforcement learning algorithms aim to maximize some numerical value, which represents only one long-term objective. However, multiple long-term objectives are exhibited in many real-world decision and control problems; therefore, recently, there has been growing interest in solving multiobjective reinforcement learning (MORL) problems with multiple conflicting objectives. The aim of this paper is to present a comprehensive overview of MORL. In this paper, the basic architecture, research topics, and naive solutions of MORL are introduced at first. Then, several representative MORL approaches and some important directions of recent research are reviewed. The relationships between MORL and other related research are also discussed, which include multiobjective optimization, hierarchical reinforcement learning, and multi-agent reinforcement learning. Finally, research challenges and open problems of MORL techniques are highlighted.

Interpretable Decision Sets: A Joint Framework for Description and Prediction

PubMed Central

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

2016-01-01

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

The pros and cons of funnel plots as an aid to risk communication and patient decision making.

PubMed

Rakow, Tim; Wright, Rebecca J; Spiegelhalter, David J; Bull, Catherine

2015-05-01

Funnel plots, which simultaneously display a sample statistic and the corresponding sample size for multiple cases, have a range of applications. In medicine, they are used to display treatment outcome rates and caseload volume by institution, which can inform strategic decisions about health care delivery. We investigated lay people's understanding of such plots and explored their suitability as an aid to individual treatment decisions. In two studies, 172 participants answered objective questions about funnel plots representing the surgical outcomes (survival or mortality rates) of institutions varying in caseload, and indicated their preferred institutions. Accuracy for extracting objective information was high, unless question phrasing was inconsistent with the plot's survival/mortality framing, or participants had low numeracy levels. Participants integrated caseload-volume and outcome-rate data when forming preferences, but were influenced by reference lines on the plot to make inappropriate discriminations between institutions with similar outcome rates. With careful choice of accompanying language, funnel plots can be readily understood and are therefore a useful tool for communicating risk. However, they are less effective as a decision aid for individual patient's treatment decisions, and we recommend refinements to the standard presentation of the plots if they are to be used for that purpose. © 2014 The British Psychological Society.

Pareto frontier analyses based decision making tool for transportation of hazardous waste.

PubMed

Das, Arup; Mazumder, T N; Gupta, A K

2012-08-15

Transportation of hazardous wastes through a region poses immense threat on the development along its road network. The risk to the population, exposed to such activities, has been documented in the past. However, a comprehensive framework for routing hazardous wastes has often been overlooked. A regional Hazardous Waste Management scheme should incorporate a comprehensive framework for hazardous waste transportation. This framework would incorporate the various stakeholders involved in decision making. Hence, a multi-objective approach is required to safeguard the interest of all the concerned stakeholders. The objective of this study is to design a methodology for routing of hazardous wastes between the generating units and the disposal facilities through a capacity constrained network. The proposed methodology uses posteriori method with multi-objective approach to find non-dominated solutions for the system consisting of multiple origins and destinations. A case study of transportation of hazardous wastes in Kolkata Metropolitan Area has also been provided to elucidate the methodology. Copyright © 2012 Elsevier B.V. All rights reserved.

A Markovian state-space framework for integrating flexibility into space system design decisions

NASA Astrophysics Data System (ADS)

Lafleur, Jarret M.

The past decades have seen the state of the art in aerospace system design progress from a scope of simple optimization to one including robustness, with the objective of permitting a single system to perform well even in off-nominal future environments. Integrating flexibility, or the capability to easily modify a system after it has been fielded in response to changing environments, into system design represents a further step forward. One challenge in accomplishing this rests in that the decision-maker must consider not only the present system design decision, but also sequential future design and operation decisions. Despite extensive interest in the topic, the state of the art in designing flexibility into aerospace systems, and particularly space systems, tends to be limited to analyses that are qualitative, deterministic, single-objective, and/or limited to consider a single future time period. To address these gaps, this thesis develops a stochastic, multi-objective, and multi-period framework for integrating flexibility into space system design decisions. Central to the framework are five steps. First, system configuration options are identified and costs of switching from one configuration to another are compiled into a cost transition matrix. Second, probabilities that demand on the system will transition from one mission to another are compiled into a mission demand Markov chain. Third, one performance matrix for each design objective is populated to describe how well the identified system configurations perform in each of the identified mission demand environments. The fourth step employs multi-period decision analysis techniques, including Markov decision processes from the field of operations research, to find efficient paths and policies a decision-maker may follow. The final step examines the implications of these paths and policies for the primary goal of informing initial system selection. Overall, this thesis unifies state-centric concepts of flexibility from economics and engineering literature with sequential decision-making techniques from operations research. The end objective of this thesis’ framework and its supporting tools is to enable selection of the next-generation space systems today, tailored to decision-maker budget and performance preferences, that will be best able to adapt and perform in a future of changing environments and requirements. Following extensive theoretical development, the framework and its steps are applied to space system planning problems of (1) DARPA-motivated multiple- or distributed-payload satellite selection and (2) NASA human space exploration architecture selection.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

NASA Astrophysics Data System (ADS)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU evaluate tradeoffs in a continually changing world.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

PubMed Central

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Estimating Classification Accuracy for Complex Decision Rules Based on Multiple Scores

ERIC Educational Resources Information Center

Douglas, Karen M.; Mislevy, Robert J.

2010-01-01

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

The ASLOTS concept: An interactive, adaptive decision support concept for Final Approach Spacing of Aircraft (FASA). FAA-NASA Joint University Program

NASA Technical Reports Server (NTRS)

Simpson, Robert W.

1993-01-01

This presentation outlines a concept for an adaptive, interactive decision support system to assist controllers at a busy airport in achieving efficient use of multiple runways. The concept is being implemented as a computer code called FASA (Final Approach Spacing for Aircraft), and will be tested and demonstrated in ATCSIM, a high fidelity simulation of terminal area airspace and airport surface operations. Objectives are: (1) to provide automated cues to assist controllers in the sequencing and spacing of landing and takeoff aircraft; (2) to provide the controller with a limited ability to modify the sequence and spacings between aircraft, and to insert takeoffs and missed approach aircraft in the landing flows; (3) to increase spacing accuracy using more complex and precise separation criteria while reducing controller workload; and (4) achieve higher operational takeoff and landing rates on multiple runways in poor visibility.

Multiple response optimization for higher dimensions in factors and responses

DOE PAGES

Lu, Lu; Chapman, Jessica L.; Anderson-Cook, Christine M.

2016-07-19

When optimizing a product or process with multiple responses, a two-stage Pareto front approach is a useful strategy to evaluate and balance trade-offs between different estimated responses to seek optimum input locations for achieving the best outcomes. After objectively eliminating non-contenders in the first stage by looking for a Pareto front of superior solutions, graphical tools can be used to identify a final solution in the second subjective stage to compare options and match with user priorities. Until now, there have been limitations on the number of response variables and input factors that could effectively be visualized with existing graphicalmore » summaries. We present novel graphical tools that can be more easily scaled to higher dimensions, in both the input and response spaces, to facilitate informed decision making when simultaneously optimizing multiple responses. A key aspect of these graphics is that the potential solutions can be flexibly sorted to investigate specific queries, and that multiple aspects of the solutions can be simultaneously considered. As a result, recommendations are made about how to evaluate the impact of the uncertainty associated with the estimated response surfaces on decision making with higher dimensions.« less

Two approaches to incorporate clinical data uncertainty into multiple criteria decision analysis for benefit-risk assessment of medicinal products.

PubMed

Wen, Shihua; Zhang, Lanju; Yang, Bo

2014-07-01

The Problem formulation, Objectives, Alternatives, Consequences, Trade-offs, Uncertainties, Risk attitude, and Linked decisions (PrOACT-URL) framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. The objective of this article was to provide solutions to incorporate the uncertainty from clinical data into the MCDA model when evaluating the overall benefit-risk profiles among different treatment options. Two statistical approaches, the δ-method approach and the Monte-Carlo approach, were proposed to construct the confidence interval of the overall benefit-risk score from the MCDA model as well as other probabilistic measures for comparing the benefit-risk profiles between treatment options. Both approaches can incorporate the correlation structure between clinical parameters (criteria) in the MCDA model and are straightforward to implement. The two proposed approaches were applied to a case study to evaluate the benefit-risk profile of an add-on therapy for rheumatoid arthritis (drug X) relative to placebo. It demonstrated a straightforward way to quantify the impact of the uncertainty from clinical data to the benefit-risk assessment and enabled statistical inference on evaluating the overall benefit-risk profiles among different treatment options. The δ-method approach provides a closed form to quantify the variability of the overall benefit-risk score in the MCDA model, whereas the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for statistical inference. The obtained confidence intervals and other probabilistic measures from the two approaches enhance the benefit-risk decision making of medicinal products. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina

USGS Publications Warehouse

Tavernia, Brian G.; Stanton, John D.; Lyons, James E.

2017-11-22

Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective weights and budgets were developed. Given the large number of possible portfolios (1614), a heuristic genetic algorithm was used to identify a management action portfolio that maximized use-day objectives while respecting budget constraints. The genetic algorithm identified a portfolio of management actions for each of the five scenarios, enabling refuge staff to explore the sensitivity of their management decisions to objective weights and budget constraints.The decision framework developed here provides a transparent, defensible, and testable foundation for decision making at MNWR. The BBN model explicitly structures and parameterizes a mental model previously used by an expert to assign management actions to the impoundments. With ongoing IWMM monitoring, predictions from the model can be tested, and model parameters updated, to reflect empirical observations. This framework is intended to be a living document that can be updated to reflect changes in the decision context (for example, new objectives or constraints, or new models to compete with the current BBN model). Rather than a mandate to refuge staff, this framework is intended to be a decision support tool; tool outputs can become part of the deliberations of refuge staff when making difficult management decisions for multiple objectives.

The effects of normal aging on multiple aspects of financial decision-making

PubMed Central

Bangma, Dorien F.; Fuermaier, Anselm B. M.; Tucha, Lara; Tucha, Oliver; Koerts, Janneke

2017-01-01

Objectives Financial decision-making (FDM) is crucial for independent living. Due to cognitive decline that accompanies normal aging, older adults might have difficulties in some aspects of FDM. However, an improved knowledge, personal experience and affective decision-making, which are also related to normal aging, may lead to a stable or even improved age-related performance in some other aspects of FDM. Therefore, the present explorative study examines the effects of normal aging on multiple aspects of FDM. Methods One-hundred and eighty participants (range 18–87 years) were assessed with eight FDM tests and several standard neuropsychological tests. Age effects were evaluated using hierarchical multiple regression analyses. The validity of the prediction models was examined by internal validation (i.e. bootstrap resampling procedure) as well as external validation on another, independent, sample of participants (n = 124). Multiple regression and correlation analyses were applied to investigate the mediation effect of standard measures of cognition on the observed effects of age on FDM. Results On a relatively basic level of FDM (e.g., paying bills or using FDM styles) no significant effects of aging were found. However more complex FDM, such as making decisions in accordance with specific rules, becomes more difficult with advancing age. Furthermore, an older age was found to be related to a decreased sensitivity for impulsive buying. These results were confirmed by the internal and external validation analyses. Mediation effects of numeracy and planning were found to explain parts of the association between one aspect of FDM (i.e. Competence in decision rules) and age; however, these cognitive domains were not able to completely explain the relation between age and FDM. Conclusion Normal aging has a negative influence on a complex aspect of FDM, however, other aspects appear to be unaffected by normal aging or improve. PMID:28792973

Time to decision: the drivers of innovation adoption decisions

NASA Astrophysics Data System (ADS)

Ciganek, Andrew Paul; (Dave) Haseman, William; Ramamurthy, K.

2014-03-01

Organisations desire timeliness. Timeliness facilitates a better responsiveness to changes in an organisation's external environment to either attain or maintain competitiveness. Despite its importance, decision timeliness has not been explicitly examined. Decision timeliness is measured in this study as the time taken to commit to a decision. The research objective is to identify the drivers of decision timeliness in the context of adopting service-oriented architecture (SOA), an innovation for enterprise computing. A research model rooted in the technology-organisation-environment (TOE) framework is proposed and tested with data collected in a large-scale study. The research variables have been examined before in the context of adoption, but their applicability to the timeliness of innovation decision-making has not received much attention and their salience is unclear. The results support multiple hypothesised relationships, including the finding that a risk-oriented organisational culture as well as normative and coercive pressures accelerates decision timeliness. Top management support as well as the traditional innovation attributes (compatibility, relative advantage and complexity/ease-of-use) were not found to be significant when examining their influence on decision timeliness, which appears inconsistent with generally accepted knowledge and deserves further examination.

Evaluation of Ensemble Water Supply and Demands Forecasts for Water Management in the Klamath River Basin

NASA Astrophysics Data System (ADS)

Broman, D.; Gangopadhyay, S.; McGuire, M.; Wood, A.; Leady, Z.; Tansey, M. K.; Nelson, K.; Dahm, K.

2017-12-01

The Upper Klamath River Basin in south central Oregon and north central California is home to the Klamath Irrigation Project, which is operated by the Bureau of Reclamation and provides water to around 200,000 acres of agricultural lands. The project is managed in consideration of not only water deliveries to irrigators, but also wildlife refuge water demands, biological opinion requirements for Endangered Species Act (ESA) listed fish, and Tribal Trust responsibilities. Climate change has the potential to impact water management in terms of volume and timing of water and the ability to meet multiple objectives. Current operations use a spreadsheet-based decision support tool, with water supply forecasts from the National Resources Conservation Service (NRCS) and California-Nevada River Forecast Center (CNRFC). This tool is currently limited in its ability to incorporate in ensemble forecasts, which offer the potential for improved operations by quantifying forecast uncertainty. To address these limitations, this study has worked to develop a RiverWare based water resource systems model, flexible enough to use across multiple decision time-scales, from short-term operations out to long-range planning. Systems model development has been accompanied by operational system development to handle data management and multiple modeling components. Using a set of ensemble hindcasts, this study seeks to answer several questions: A) Do a new set of ensemble streamflow forecasts have additional skill beyond what?, and allow for improved decision making under changing conditions? B) Do net irrigation water requirement forecasts developed in this project to quantify agricultural demands and reservoir evaporation forecasts provide additional benefits to decision making beyond water supply forecasts? C) What benefit do ensemble forecasts have in the context of water management decisions?

Using decision analysis to support proactive management of emerging infectious wildlife diseases

USGS Publications Warehouse

Grant, Evan H. Campbell; Muths, Erin L.; Katz, Rachel A.; Canessa, Stefano; Adams, Michael J.; Ballard, Jennifer R.; Berger, Lee; Briggs, Cheryl J.; Coleman, Jeremy; Gray, Matthew J.; Harris, M. Camille; Harris, Reid N.; Hossack, Blake R.; Huyvaert, Kathryn P.; Kolby, Jonathan E.; Lips, Karen R.; Lovich, Robert E.; McCallum, Hamish I.; Mendelson, Joseph R.; Nanjappa, Priya; Olson, Deanna H.; Powers, Jenny G.; Richgels, Katherine L. D.; Russell, Robin E.; Schmidt, Benedikt R.; Spitzen-van der Sluijs, Annemarieke; Watry, Mary Kay; Woodhams, Douglas C.; White, C. LeAnn

2017-01-01

Despite calls for improved responses to emerging infectious diseases in wildlife, management is seldom considered until a disease has been detected in affected populations. Reactive approaches may limit the potential for control and increase total response costs. An alternative, proactive management framework can identify immediate actions that reduce future impacts even before a disease is detected, and plan subsequent actions that are conditional on disease emergence. We identify four main obstacles to developing proactive management strategies for the newly discovered salamander pathogen Batrachochytrium salamandrivorans (Bsal). Given that uncertainty is a hallmark of wildlife disease management and that associated decisions are often complicated by multiple competing objectives, we advocate using decision analysis to create and evaluate trade-offs between proactive (pre-emergence) and reactive (post-emergence) management options. Policy makers and natural resource agency personnel can apply principles from decision analysis to improve strategies for countering emerging infectious diseases.

Structured decision making for conservation of bull trout (Salvelinus confluentus) in Long Creek, Klamath River Basin, south-central Oregon

USGS Publications Warehouse

Benjamin, Joseph R.; McDonnell, Kevin; Dunham, Jason B.; Brignon, William R.; Peterson, James T.

2017-06-21

With the decline of bull trout (Salvelinus confluentus), managers face multiple, and sometimes contradictory, management alternatives for species recovery. Moreover, effective decision-making involves all stakeholders influenced by the decisions (such as Tribal, State, Federal, private, and non-governmental organizations) because they represent diverse objectives, jurisdictions, policy mandates, and opinions of the best management strategy. The process of structured decision making is explicitly designed to address these elements of the decision making process. Here we report on an application of structured decision making to a population of bull trout believed threatened by high densities of nonnative brook trout (S. fontinalis) and habitat fragmentation in Long Creek, a tributary to the Sycan River in the Klamath River Basin, south-central Oregon. This involved engaging stakeholders to identify (1) their fundamental objectives for the conservation of bull trout, (2) feasible management alternatives to achieve their objectives, and (3) biological information and assumptions to incorporate in a decision model. Model simulations suggested an overarching theme among the top decision alternatives, which was a need to simultaneously control brook trout and ensure that the migratory tactic of bull trout can be expressed. More specifically, the optimal management decision, based on the estimated adult abundance at year 10, was to combine the eradication of brook trout from Long Creek with improvement of downstream conditions (for example, connectivity or habitat conditions). Other top decisions included these actions independently, as well as electrofishing removal of brook trout. In contrast, translocating bull trout to a different stream or installing a barrier to prevent upstream spread of brook trout had minimal or negative effects on the bull trout population. Moreover, sensitivity analyses suggested that these actions were consistently identified as optimal across a large range of parameter values. Taken together, these results support the conclusion that management actions focused on controlling brook trout and enhancing migrant bull trout are more likely to yield more adult bull trout within the 10-year time frame specified by stakeholders.

Confronting dynamics and uncertainty in optimal decision making for conservation

USGS Publications Warehouse

Williams, Byron K.; Johnson, Fred A.

2013-01-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making--a careful consideration of values, actions, and outcomes.

Confronting dynamics and uncertainty in optimal decision making for conservation

NASA Astrophysics Data System (ADS)

Williams, Byron K.; Johnson, Fred A.

2013-06-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a critically endangered population through captive breeding, control of invasive species, construction of biodiversity reserves, design of landscapes to increase habitat connectivity, and resource exploitation. Although these decision making problems and their solutions present significant challenges, we suggest that a systematic and effective approach to dynamic decision making in conservation need not be an onerous undertaking. The requirements are shared with any systematic approach to decision making—a careful consideration of values, actions, and outcomes.

Factors affecting self-regulatory driving practices among older adults.

PubMed

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

2014-01-01

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

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

PubMed Central

2016-01-01

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

Use of multicriteria decision analysis to address conservation conflicts.

PubMed

Davies, A L; Bryce, R; Redpath, S M

2013-10-01

Conservation conflicts are increasing on a global scale and instruments for reconciling competing interests are urgently needed. Multicriteria decision analysis (MCDA) is a structured, decision-support process that can facilitate dialogue between groups with differing interests and incorporate human and environmental dimensions of conflict. MCDA is a structured and transparent method of breaking down complex problems and incorporating multiple objectives. The value of this process for addressing major challenges in conservation conflict management is that MCDA helps in setting realistic goals; entails a transparent decision-making process; and addresses mistrust, differing world views, cross-scale issues, patchy or contested information, and inflexible legislative tools. Overall we believe MCDA provides a valuable decision-support tool, particularly for increasing awareness of the effects of particular values and choices for working toward negotiated compromise, although an awareness of the effect of methodological choices and the limitations of the method is vital before applying it in conflict situations. © 2013 Society for Conservation Biology.

Efficient group decision making in workshop settings

Treesearch

Daniel L. Schmoldt; David L. Peterson

2001-01-01

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

Robust visual tracking via multiple discriminative models with object proposals

NASA Astrophysics Data System (ADS)

Zhang, Yuanqiang; Bi, Duyan; Zha, Yufei; Li, Huanyu; Ku, Tao; Wu, Min; Ding, Wenshan; Fan, Zunlin

2018-04-01

Model drift is an important reason for tracking failure. In this paper, multiple discriminative models with object proposals are used to improve the model discrimination for relieving this problem. Firstly, the target location and scale changing are captured by lots of high-quality object proposals, which are represented by deep convolutional features for target semantics. And then, through sharing a feature map obtained by a pre-trained network, ROI pooling is exploited to wrap the various sizes of object proposals into vectors of the same length, which are used to learn a discriminative model conveniently. Lastly, these historical snapshot vectors are trained by different lifetime models. Based on entropy decision mechanism, the bad model owing to model drift can be corrected by selecting the best discriminative model. This would improve the robustness of the tracker significantly. We extensively evaluate our tracker on two popular benchmarks, the OTB 2013 benchmark and UAV20L benchmark. On both benchmarks, our tracker achieves the best performance on precision and success rate compared with the state-of-the-art trackers.

MONSS: A multi-objective nonlinear simplex search approach

NASA Astrophysics Data System (ADS)

Zapotecas-Martínez, Saúl; Coello Coello, Carlos A.

2016-01-01

This article presents a novel methodology for dealing with continuous box-constrained multi-objective optimization problems (MOPs). The proposed algorithm adopts a nonlinear simplex search scheme in order to obtain multiple elements of the Pareto optimal set. The search is directed by a well-distributed set of weight vectors, each of which defines a scalarization problem that is solved by deforming a simplex according to the movements described by Nelder and Mead's method. Considering an MOP with n decision variables, the simplex is constructed using n+1 solutions which minimize different scalarization problems defined by n+1 neighbor weight vectors. All solutions found in the search are used to update a set of solutions considered to be the minima for each separate problem. In this way, the proposed algorithm collectively obtains multiple trade-offs among the different conflicting objectives, while maintaining a proper representation of the Pareto optimal front. In this article, it is shown that a well-designed strategy using just mathematical programming techniques can be competitive with respect to the state-of-the-art multi-objective evolutionary algorithms against which it was compared.

Objective Ratings of Relationship Skills across Multiple Domains as Predictors of Marital Satisfaction Trajectories

PubMed Central

Lawrence, Erika; Pederson, Ashley; Bunde, Mali; Barry, Robin A.; Brock, Rebecca L.; Fazio, Emily; Mulryan, Lorin; Hunt, Sara; Madsen, Lisa; Dzankovic, Sandra

2008-01-01

Expanding upon social-learning and vulnerability-stress-adaptation approaches to marriage, the impact of multiple dyadic behaviors on marital satisfaction trajectories was examined in 101 couples. Semi-structured interviews were administered separately to husbands and wives at 3 months of marriage. Interviewers generated objective ratings for five domains: emotional closeness/intimacy, sexual intimacy/sensuality, interspousal support, decision-making/relational control, and communication/conflict management. Marital satisfaction was assessed four times over three years. Dyadic behaviors were associated with initial levels and rates of change in satisfaction, demonstrating the unique contributions of each relational skill on marital development. For husbands, sexual intimacy was the strongest predictor of change whereas for wives, communication/conflict management was the strongest predictor of change compared to other domains. Theoretical, methodological and clinical implications are discussed. PMID:19122752

Local search heuristic for the discrete leader-follower problem with multiple follower objectives

NASA Astrophysics Data System (ADS)

Kochetov, Yury; Alekseeva, Ekaterina; Mezmaz, Mohand

2016-10-01

We study a discrete bilevel problem, called as well as leader-follower problem, with multiple objectives at the lower level. It is assumed that constraints at the upper level can include variables of both levels. For such ill-posed problem we define feasible and optimal solutions for pessimistic case. A central point of this work is a two stage method to get a feasible solution under the pessimistic case, given a leader decision. The target of the first stage is a follower solution that violates the leader constraints. The target of the second stage is a pessimistic feasible solution. Each stage calls a heuristic and a solver for a series of particular mixed integer programs. The method is integrated inside a local search based heuristic that is designed to find near-optimal leader solutions.

Forward-looking farmers owning multiple potential wetland restoration sites: implications for efficient restoration

NASA Astrophysics Data System (ADS)

Schroder (Kushch), Svetlana; Lang, Zhengxin; Rabotyagov, Sergey

2018-04-01

Wetland restoration can increase the provision of multiple non-market ecosystem services. Environmental and socio-economic factors need to be accounted for when land is withdrawn from agriculture and wetlands are restored. We build multi-objective optimization models to provide decision support for wetland restoration in the Le Sueur river watershed in Southern Minnesota. We integrate environmental objectives of sediment reduction and habitat protection with socio-economic factors associated with the overlap of private land with potential wetland restoration sites in the watershed and the costs representing forward-looking farmers voluntarily taking land out of agricultural production in favor of wetland restoration. Our results demonstrate that the inclusion of these factors early on in the restoration planning process affects both the total costs of the restoration project and the spatial distribution of optimally selected wetland restoration sites.

Analytical group decision making in natural resources: methodology and application

Treesearch

Daniel L. Schmoldt; David L. Peterson

2000-01-01

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

Achieving realistic performance and decison-making capabilities in computer-generated air forces

NASA Astrophysics Data System (ADS)

Banks, Sheila B.; Stytz, Martin R.; Santos, Eugene, Jr.; Zurita, Vincent B.; Benslay, James L., Jr.

1997-07-01

For a computer-generated force (CGF) system to be useful in training environments, it must be able to operate at multiple skill levels, exhibit competency at assigned missions, and comply with current doctrine. Because of the rapid rate of change in distributed interactive simulation (DIS) and the expanding set of performance objectives for any computer- generated force, the system must also be modifiable at reasonable cost and incorporate mechanisms for learning. Therefore, CGF applications must have adaptable decision mechanisms and behaviors and perform automated incorporation of past reasoning and experience into its decision process. The CGF must also possess multiple skill levels for classes of entities, gracefully degrade its reasoning capability in response to system stress, possess an expandable modular knowledge structure, and perform adaptive mission planning. Furthermore, correctly performing individual entity behaviors is not sufficient. Issues related to complex inter-entity behavioral interactions, such as the need to maintain formation and share information, must also be considered. The CGF must also be able to acceptably respond to unforeseen circumstances and be able to make decisions in spite of uncertain information. Because of the need for increased complexity in the virtual battlespace, the CGF should exhibit complex, realistic behavior patterns within the battlespace. To achieve these necessary capabilities, an extensible software architecture, an expandable knowledge base, and an adaptable decision making mechanism are required. Our lab has addressed these issues in detail. The resulting DIS-compliant system is called the automated wingman (AW). The AW is based on fuzzy logic, the common object database (CODB) software architecture, and a hierarchical knowledge structure. We describe the techniques we used to enable us to make progress toward a CGF entity that satisfies the requirements presented above. We present our design and implementation of an adaptable decision making mechanism that uses multi-layered, fuzzy logic controlled situational analysis. Because our research indicates that fuzzy logic can perform poorly under certain circumstances, we combine fuzzy logic inferencing with adversarial game tree techniques for decision making in strategic and tactical engagements. We describe the approach we employed to achieve this fusion. We also describe the automated wingman's system architecture and knowledge base architecture.

Collaborative Workshops for Assessment and Creation of Multi-Objective Decision Support for Multiple Sectors

NASA Astrophysics Data System (ADS)

Kasprzyk, J. R.; Smith, R.; Raseman, W. J.; DeRousseau, M. A.; Dilling, L.; Ozekin, K.; Summers, R. S.; Balaji, R.; Livneh, B.; Rosario-Ortiz, F.; Sprain, L.; Srubar, W. V., III

2017-12-01

This presentation will report on three projects that used interactive workshops with stakeholders to develop problem formulations for Multi-Objective Evolutionary Algorithm (MOEA)-based decision support in diverse fields - water resources planning, water quality engineering under climate extremes, and sustainable materials design. When combined with a simulation model of a system, MOEAs use intelligent search techniques to provide new plans or designs. This approach is gaining increasing prominence in design and planning for environmental sustainability. To use this technique, a problem formulation - objectives and constraints (quantitative measures of performance) and decision variables (actions that can be modified to improve the system) - must be identified. Although critically important for MOEA effectiveness, the problem formulations are not always developed with stakeholders' interests in mind. To ameliorate this issue, project workshops were organized to improve the tool's relevance as well as collaboratively build problem formulations that can be used in applications. There were interesting differences among the projects, which altered the findings of each workshop. Attendees ranged from a group of water managers on the Front Range of Colorado, to water utility representatives from across the country, to a set of designers, academics, and trade groups. The extent to which the workshop participants were already familiar with simulation tools contributed to their willingness to accept the solutions that were generated using the tool. Moreover, in some instances, brainstorming new objectives to include within the MOEA expanded the scope of the problem formulation, relative to the initial conception of the researchers. Through describing results across a diversity of projects, the goal of this presentation is to report on how our approach may inform future decision support collaboration with a variety of stakeholders and sectors.

Risk-based analysis and decision making in multi-disciplinary environments

NASA Technical Reports Server (NTRS)

Feather, Martin S.; Cornford, Steven L.; Moran, Kelly

2003-01-01

A risk-based decision-making process conceived of and developed at JPL and NASA, has been used to help plan and guide novel technology applications for use on spacecraft. These applications exemplify key challenges inherent in multi-disciplinary design of novel technologies deployed in mission-critical settings. 1) Cross-disciplinary concerns are numerous (e.g., spacecraft involve navigation, propulsion, telecommunications). These concems are cross-coupled and interact in multiple ways (e.g., electromagnetic interference, heat transfer). 2) Time and budget pressures constrain development, operational resources constrain the resulting system (e.g., mass, volume, power). 3) Spacecraft are critical systems that must operate correctly the first time in only partially understood environments, with no chance for repair. 4) Past experience provides only a partial guide: New mission concepts are enhanced and enabled by new technologies, for which past experience is lacking. The decision-making process rests on quantitative assessments of the relationships between three classes of information - objectives (the things the system is to accomplish and constraints on its operation and development), risks (whose occurrence detracts from objectives), and mitigations (options for reducing the likelihood and or severity of risks). The process successfully guides experts to pool their knowledge, using custom-built software to support information gathering and decision-making.

Picture reality decision, semantic categories and gender. A new set of pictures, with norms and an experimental study.

PubMed

Barbarotto, Riccardo; Laiacona, Marcella; Macchi, Valeria; Capitani, Erminio

2002-01-01

We present a new corpus of 80 pictures of unreal objects, useful for a controlled assessment of object reality decision. The new pictures were assembled from parts of the Snodgrass and Vanderwart [J. Exp. Psychol., Hum. Learning Memory 6; 1980: 174] set and were devised for the purpose of contrasting natural categories (animals, fruits and vegetables), artefacts (tools, vehicles and furniture), body parts and musical instruments. We examined 140 normal subjects in a free-choice and a multiple-choice object decision task, assembled with 80 pictures of real objects and above 80 new pictures of unreal objects in order to obtain a difficulty index for each picture. We found that the tasks were more difficult with pictures representing natural entities than with pictures of artefacts. We found a gender by category interaction, with a female superiority with some natural categories (fruits and vegetables, but not animals), and a male advantage with artefacts. On this basis, the difficulty index we calculated for each picture is separately reported for males and females. We discuss the possible origin of the gender effect, which has been found with the same categories in other tasks and has a counterpart in the different familiarity of the stimuli for males and females. In particular, we contrast explanations based on socially determined gender differences with accounts based on evolutionary pressures. We further comment on the relationship between data from normal subjects and the domain-specific account of semantic category dissociations observed in brain-damaged patients.

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

PubMed

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

2017-01-01

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

Speech and language therapists' approaches to communication intervention with children and adults with profound and multiple learning disability.

PubMed

Goldbart, Juliet; Chadwick, Darren; Buell, Susan

2014-11-01

People with profound intellectual and multiple disabilities (PMLD) have communication impairments as one defining characteristic. To explore speech and language therapists' (SLTs) decision making in communication interventions for people with PMLD, in terms of the intervention approaches used, the factors informing the decisions to use specific interventions and the extent to which the rationales underpinning these decisions related to the components of evidence based practice (EBP), namely empirical evidence, clinical experience and client/carer views and values. A questionnaire on communication assessment and intervention for people with PMLD was sent to SLTs in the UK to elicit information on: the communication intervention approaches they used; their rationales for their intervention choices; their use of published evidence to inform decision making. Intensive interaction and objects of reference were the communication interventions most often used with people with PMLD, with some differences between children and adults evident. Rationales provided conformed somewhat to the EBP framework though extension of the existing framework and addition of practical and organizational considerations led to a revised typology of rationale for decision making. Rationales most frequently related to the empowerment, development and behavioural preferences of the person with PMLD. Empirical research evidence was seldom mentioned by SLTs as informing intervention decision making leading to very diverse practice. There is a need for further research on the effectiveness of commonly used but under-evaluated interventions. There is also a need to alert SLTs to the evidence base supporting other approaches, particularly switch-based, cause and effect approaches. © 2014 Royal College of Speech and Language Therapists.

Multi-objective analysis of the conjunctive use of surface water and groundwater in a multisource water supply system

NASA Astrophysics Data System (ADS)

Vieira, João; da Conceição Cunha, Maria

2017-04-01

A multi-objective decision model has been developed to identify the Pareto-optimal set of management alternatives for the conjunctive use of surface water and groundwater of a multisource urban water supply system. A multi-objective evolutionary algorithm, Borg MOEA, is used to solve the multi-objective decision model. The multiple solutions can be shown to stakeholders allowing them to choose their own solutions depending on their preferences. The multisource urban water supply system studied here is dependent on surface water and groundwater and located in the Algarve region, southernmost province of Portugal, with a typical warm Mediterranean climate. The rainfall is low, intermittent and concentrated in a short winter, followed by a long and dry period. A base population of 450 000 inhabitants and visits by more than 13 million tourists per year, mostly in summertime, turns water management critical and challenging. Previous studies on single objective optimization after aggregating multiple objectives together have already concluded that only an integrated and interannual water resources management perspective can be efficient for water resource allocation in this drought prone region. A simulation model of the multisource urban water supply system using mathematical functions to represent the water balance in the surface reservoirs, the groundwater flow in the aquifers, and the water transport in the distribution network with explicit representation of water quality is coupled with Borg MOEA. The multi-objective problem formulation includes five objectives. Two objective evaluate separately the water quantity and the water quality supplied for the urban use in a finite time horizon, one objective calculates the operating costs, and two objectives appraise the state of the two water sources - the storage in the surface reservoir and the piezometric levels in aquifer - at the end of the time horizon. The decision variables are the volume of withdrawals from each water source in each time step (i.e., reservoir diversion and groundwater pumping). The results provide valuable information for analysing the impacts of the conjunctive use of surface water and groundwater. For example, considering a drought scenario, the results show how the same level of total water supplied can be achieved by different management alternatives with different impact on the water quality, costs, and the state of the water sources at the end of the time horizon. The results allow also the clear understanding of the potential benefits from the conjunctive use of surface water and groundwater thorough the mitigation of the variation in the availability of surface water, improving the water quantity and/or water quality delivered to the users, or the better adaptation of such systems to a changing world.

Kwajalein Infrastructure Prioritization Methodology

DTIC Science & Technology

2012-07-01

Kwajalein are failing apart and if not fixed they could hinder or ruin the base’s ability to execute their mission. The proposed model ranks different ...their perspectives. Multiple Objective Decision Analysis (MODA) was conducted to compare the different value measures together. Since each value...measure is rated differently , it would be difficult to compare them to one another if there was no way to bring them under one type of measurement or unit

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

DTIC Science & Technology

2014-12-26

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

Optimal Sensor Scheduling for Multiple Hypothesis Testing

DTIC Science & Technology

1981-09-01

Naval Research, under contract N00014-77-0532 is gratpfully acknowledged. 2 Laboratory for Information and Decision Systems , MIT Room 35-213, Cambridge...treat the more general problem [9,10]. However, two common threads connect these approaches: they obtain feedback laws mapping posterior destributions ...objective of a detection or identification algorithm is to produce correct estimates of the true state of a system . It is also bene- ficial if these

To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task

PubMed Central

Lamb, Maurice; Kallen, Rachel W.; Harrison, Steven J.; Di Bernardo, Mario; Minai, Ali; Richardson, Michael J.

2017-01-01

Humans commonly engage in tasks that require or are made more efficient by coordinating with other humans. In this paper we introduce a task dynamics approach for modeling multi-agent interaction and decision making in a pick and place task where an agent must move an object from one location to another and decide whether to act alone or with a partner. Our aims were to identify and model (1) the affordance related dynamics that define an actor's choice to move an object alone or to pass it to their co-actor and (2) the trajectory dynamics of an actor's hand movements when moving to grasp, relocate, or pass the object. Using a virtual reality pick and place task, we demonstrate that both the decision to pass or not pass an object and the movement trajectories of the participants can be characterized in terms of a behavioral dynamics model. Simulations suggest that the proposed behavioral dynamics model exhibits features observed in human participants including hysteresis in decision making, non-straight line trajectories, and non-constant velocity profiles. The proposed model highlights how the same low-dimensional behavioral dynamics can operate to constrain multiple (and often nested) levels of human activity and suggests that knowledge of what, when, where and how to move or act during pick and place behavior may be defined by these low dimensional task dynamics and, thus, can emerge spontaneously and in real-time with little a priori planning. PMID:28701975

An Intuitionistic Multiplicative ORESTE Method for Patients’ Prioritization of Hospitalization

PubMed Central

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

2018-01-01

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

Application of effective discharge analysis to environmental flow decision-making

USGS Publications Warehouse

McKay, S. Kyle; Freeman, Mary C.; Covich, A.P.

2016-01-01

Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.

Application of Effective Discharge Analysis to Environmental Flow Decision-Making.

PubMed

McKay, S Kyle; Freeman, Mary C; Covich, Alan P

2016-06-01

Well-informed river management decisions rely on an explicit statement of objectives, repeatable analyses, and a transparent system for assessing trade-offs. These components may then be applied to compare alternative operational regimes for water resource infrastructure (e.g., diversions, locks, and dams). Intra- and inter-annual hydrologic variability further complicates these already complex environmental flow decisions. Effective discharge analysis (developed in studies of geomorphology) is a powerful tool for integrating temporal variability of flow magnitude and associated ecological consequences. Here, we adapt the effectiveness framework to include multiple elements of the natural flow regime (i.e., timing, duration, and rate-of-change) as well as two flow variables. We demonstrate this analytical approach using a case study of environmental flow management based on long-term (60 years) daily discharge records in the Middle Oconee River near Athens, GA, USA. Specifically, we apply an existing model for estimating young-of-year fish recruitment based on flow-dependent metrics to an effective discharge analysis that incorporates hydrologic variability and multiple focal taxa. We then compare three alternative methods of environmental flow provision. Percentage-based withdrawal schemes outcompete other environmental flow methods across all levels of water withdrawal and ecological outcomes.

Barriers to and facilitators of implementing shared decision making and decision support in a paediatric hospital: A descriptive study

PubMed Central

Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L

2016-01-01

OBJECTIVE: To explore multiple stakeholders’ perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. METHODS: An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators’, clinicians’, parents’ and youths’ perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. RESULTS: Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders’ knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital’s culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. CONCLUSIONS: Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors’ paediatric hospital. PMID:27398058

The relationship between risk factors and aeronautical decision making in the flight training environment

NASA Astrophysics Data System (ADS)

Wetmore, Michael J.

The purpose of this applied dissertation was to investigate the relationship between risk factors and aeronautical decision making in the flight training environment using a quantitative, non-experimental, ex post facto research design. All 75 of the flight training accidents that involved a fatality from the years 2001-2003 were selected for study from the National Transportation Safety Board (NTSB) aviation accident database. Objective evidence from the Factual Reports was used to construct accident chains and to code and quantify total risk factors and total poor aeronautical decisions. The data were processed using correlational statistical tests at the 1% significance level. There was a statistically significant relationship between total risk factors per flight and poor decisions per flight. Liveware risks were the most prevalent risk factor category. More poor decisions were made during preflight than any other phase of flight. Pilots who made multiple poor decisions per flight had significantly higher risk factors per flight. A risk factor threat to decision making chart is presented for use by flight instructors and/or flight training organizations. The main threat to validity of this study was the NTSB accident investigation team investigative equality assumption.

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

NASA Astrophysics Data System (ADS)

Pontius, J.; Duncan, J.

2017-12-01

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

An algorithmic interactive planning framework in support of sustainable technologies

NASA Astrophysics Data System (ADS)

Prica, Marija D.

This thesis addresses the difficult problem of generation expansion planning that employs the most effective technologies in today's changing electric energy industry. The electrical energy industry, in both the industrialized world and in developing countries, is experiencing transformation in a number of different ways. This transformation is driven by major technological breakthroughs (such as the influx of unconventional smaller-scale resources), by industry restructuring, changing environmental objectives, and the ultimate threat of resource scarcity. This thesis proposes a possible planning framework in support of sustainable technologies where sustainability is viewed as a mix of multiple attributes ranging from reliability and environmental impact to short- and long-term efficiency. The idea of centralized peak-load pricing, which accounts for the tradeoffs between cumulative operational effects and the cost of new investments, is the key concept in support of long-term planning in the changing industry. To start with, an interactive planning framework for generation expansion is posed as a distributed decision-making model. In order to reconcile the distributed sub-objectives of different decision makers with system-wide sustainability objectives, a new concept of distributed interactive peak load pricing is proposed. To be able to make the right decisions, the decision makers must have sufficient information about the estimated long-term electricity prices. The sub-objectives of power plant owners and load-serving entities are profit maximization. Optimized long-term expansion plans based on predicted electricity prices are communicated to the system-wide planning authority as long-run bids. The long-term expansion bids are cleared by the coordinating planner so that the system-wide long-term performance criteria are satisfied. The interactions between generation owners and the coordinating planning authority are repeated annually. We view the proposed interactive planning framework as a necessary paradigm for planning in the changing industry where choice must be reconciled with societal public objectives.

Composite scores in comparative effectiveness research: counterbalancing parsimony and dimensionality in patient-reported outcomes.

PubMed

Schwartz, Carolyn E; Patrick, Donald L

2014-07-01

When planning a comparative effectiveness study comparing disease-modifying treatments, competing demands influence choice of outcomes. Current practice emphasizes parsimony, although understanding multidimensional treatment impact can help to personalize medical decision-making. We discuss both sides of this 'tug of war'. We discuss the assumptions, advantages and drawbacks of composite scores and multidimensional outcomes. We describe possible solutions to the multiple comparison problem, including conceptual hierarchy distinctions, statistical approaches, 'real-world' benchmarks of effectiveness and subgroup analysis. We conclude that comparative effectiveness research should consider multiple outcome dimensions and compare different approaches that fit the individual context of study objectives.

Multi-tasking arbitration and behaviour design for human-interactive robots

NASA Astrophysics Data System (ADS)

Kobayashi, Yuichi; Onishi, Masaki; Hosoe, Shigeyuki; Luo, Zhiwei

2013-05-01

Robots that interact with humans in household environments are required to handle multiple real-time tasks simultaneously, such as carrying objects, collision avoidance and conversation with human. This article presents a design framework for the control and recognition processes to meet these requirements taking into account stochastic human behaviour. The proposed design method first introduces a Petri net for synchronisation of multiple tasks. The Petri net formulation is converted to Markov decision processes and processed in an optimal control framework. Three tasks (safety confirmation, object conveyance and conversation) interact and are expressed by the Petri net. Using the proposed framework, tasks that normally tend to be designed by integrating many if-then rules can be designed in a systematic manner in a state estimation and optimisation framework from the viewpoint of the shortest time optimal control. The proposed arbitration method was verified by simulations and experiments using RI-MAN, which was developed for interactive tasks with humans.

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

NASA Astrophysics Data System (ADS)

Jiang, Wen; Wei, Boya

2018-02-01

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

Multirobot autonomous landmine detection using distributed multisensor information aggregation

NASA Astrophysics Data System (ADS)

Jumadinova, Janyl; Dasgupta, Prithviraj

2012-06-01

We consider the problem of distributed sensor information fusion by multiple autonomous robots within the context of landmine detection. We assume that different landmines can be composed of different types of material and robots are equipped with different types of sensors, while each robot has only one type of landmine detection sensor on it. We introduce a novel technique that uses a market-based information aggregation mechanism called a prediction market. Each robot is provided with a software agent that uses sensory input of the robot and performs calculations of the prediction market technique. The result of the agent's calculations is a 'belief' representing the confidence of the agent in identifying the object as a landmine. The beliefs from different robots are aggregated by the market mechanism and passed on to a decision maker agent. The decision maker agent uses this aggregate belief information about a potential landmine and makes decisions about which other robots should be deployed to its location, so that the landmine can be confirmed rapidly and accurately. Our experimental results show that, for identical data distributions and settings, using our prediction market-based information aggregation technique increases the accuracy of object classification favorably as compared to two other commonly used techniques.

Robustness of Multiple Objective Decision Analysis Preference Functions

DTIC Science & Technology

2002-06-01

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

Quality quandaries: Understanding aspects influencing different types of multiple response optimization

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

Anderson-Cook, Christine M.; Cao, Yongtao; Lu, Lu

In this study, optimizing with several responses can benefit from an objective approach of eliminating non-contenders, understanding trade-offs between competing responses, and then identifying a final choice that matches optimization priorities. To offer insights that help guide thoughtful decisions, we explore and summarize different patterns of solution sets and their trade-offs for different types of optimization with responses that are to be maximized and/or to achieve a target.

Forest management and economics

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

Buongiorno, J.; Gilless, J.K.

1987-01-01

This volume provides a survey of quantitative methods, guiding the reader through formulation and analysis of models that address forest management problems. The authors use simple mathematics, graphics, and short computer programs to explain each method. Emphasizing applications, they discuss linear, integer, dynamic, and goal programming; simulation; network modeling; and econometrics, as these relate to problems of determining economic harvest schedules in even-aged and uneven-aged forests, the evaluation of forest policies, multiple-objective decision making, and more.

Quality quandaries: Understanding aspects influencing different types of multiple response optimization

DOE PAGES

Anderson-Cook, Christine M.; Cao, Yongtao; Lu, Lu

2016-08-26

In this study, optimizing with several responses can benefit from an objective approach of eliminating non-contenders, understanding trade-offs between competing responses, and then identifying a final choice that matches optimization priorities. To offer insights that help guide thoughtful decisions, we explore and summarize different patterns of solution sets and their trade-offs for different types of optimization with responses that are to be maximized and/or to achieve a target.

Analyzing Decision Logs to Understand Decision Making in Serious Crime Investigations.

PubMed

Dando, Coral J; Ormerod, Thomas C

2017-12-01

Objective To study decision making by detectives when investigating serious crime through the examination of decision logs to explore hypothesis generation and evidence selection. Background Decision logs are used to record and justify decisions made during serious crime investigations. The complexity of investigative decision making is well documented, as are the errors associated with miscarriages of justice and inquests. The use of decision logs has not been the subject of an empirical investigation, yet they offer an important window into the nature of investigative decision making in dynamic, time-critical environments. Method A sample of decision logs from British police forces was analyzed qualitatively and quantitatively to explore hypothesis generation and evidence selection by police detectives. Results Analyses revealed diversity in documentation of decisions that did not correlate with case type and identified significant limitations of the decision log approach to supporting investigative decision making. Differences emerged between experienced and less experienced officers' decision log records in exploration of alternative hypotheses, generation of hypotheses, and sources of evidential inquiry opened over phase of investigation. Conclusion The practical use of decision logs is highly constrained by their format and context of use. Despite this, decision log records suggest that experienced detectives display strategic decision making to avoid confirmation and satisficing, which affect less experienced detectives. Application Potential applications of this research include both training in case documentation and the development of new decision log media that encourage detectives, irrespective of experience, to generate multiple hypotheses and optimize the timely selection of evidence to test them.

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

PubMed

Moore, Bethany; Bone, Eric A

2017-01-01

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

Factors influencing decision regret regarding placement of a PEG among substitute decision-makers of older persons in Japan: a prospective study.

PubMed

Kuraoka, Yumiko; Nakayama, Kazuhiro

2017-06-28

A tube feeding decision aid designed at the Ottawa Health Research Institute was specifically created for substitute decision-makers who must decide whether to allow placement of a percutaneous endoscopic gastrostomy (PEG) tube in a cognitively impaired older person. We developed a Japanese version and found that the decision aid promoted the decision-making process of substitute decision-makers to decrease decisional conflict and increase knowledge. However, the factors that influence decision regret among substitute decision-makers were not measured after the decision was made. The objective of this study was to explore the factors that influence decision regret among substitute decision-makers 6 months after using a decision aid for PEG placement. In this prospective study, participants comprised substitute decision-makers for 45 inpatients aged 65 years and older who were being considered for placement of a PEG tube in hospitals, nursing homes and patients' homes in Japan. The Decisional Conflict Scale (DCS) was used to evaluate decisional conflict among substitute decision-makers immediately after deciding whether to introduce tube feeding and the Decision Regret Scale (DRS) was used to evaluate decisional regret among substitute decision-makers 6 months after they made their decision. Normalized scores were evaluated and analysis of variance was used to compare groups. The results of the multiple regression analysis suggest that PEG placement (P < .01) and decision conflict (P < .001) are explanatory factors of decision regret regarding placement of a PEG among substitute decision-makers. PEG placement and decision conflict immediately after deciding whether to allow PEG placement have an influence on decision regret among substitute decision-makers after 6 months.

Integrating Multiple Criteria Evaluation and GIS in Ecotourism: a Review

NASA Astrophysics Data System (ADS)

Mohd, Z. H.; Ujang, U.

2016-09-01

The concept of 'Eco-tourism' is increasingly heard in recent decades. Ecotourism is one adventure that environmentally responsible intended to appreciate the nature experiences and cultures. Ecotourism should have low impact on environment and must contribute to the prosperity of local residents. This article reviews the use of Multiple Criteria Evaluation (MCE) and Geographic Information System (GIS) in ecotourism. Multiple criteria evaluation mostly used to land suitability analysis or fulfill specific objectives based on various attributes that exist in the selected area. To support the process of environmental decision making, the application of GIS is used to display and analysis the data through Analytic Hierarchy Process (AHP). Integration between MCE and GIS tool is important to determine the relative weight for the criteria used objectively. With the MCE method, it can resolve the conflict between recreation and conservation which is to minimize the environmental and human impact. Most studies evidences that the GIS-based AHP as a multi criteria evaluation is a strong and effective in tourism planning which can aid in the development of ecotourism industry effectively.

Space station systems analysis study. Part 1, volume 1: Executive study

NASA Technical Reports Server (NTRS)

1976-01-01

Potential space station system options were examined for a permanent, manned, orbital space facility and to provide data to NASA program planners and decision makers for their use in future program planning. There were ten space station system objectives identified. These were categorized into five major objectives and five supporting objectives. The major objectives were to support the development of: (1) satellite power systems, (2) nuclear energy plants in space, (3) space processing, (4) earth services, and (5) space cosmological research and development. The five supporting objectives, to define space facilities which would be basic building blocks for future systems, were: (1) a multidiscipline science laboratory, (2) an orbital depot to maintain, fuel, and service orbital transfer vehicles, (3) cluster support systems to provide power and data processing for multiple orbital elements, (4) a sensor development facility, and (5) the facilities necessary to enhance man's living and working in space.

Finding Kuiper Belt Objects Below the Detection Limit

NASA Astrophysics Data System (ADS)

Whidden, Peter; Kalmbach, Bryce; Bektesevic, Dino; Connolly, Andrew; Jones, Lynne; Smotherman, Hayden; Becker, Andrew

2018-01-01

We demonstrate a novel approach for uncovering the signatures of moving objects (e.g. Kuiper Belt Objects) below the detection thresholds of single astronomical images. To do so, we will employ a matched filter moving at specific rates of proposed orbits through a time-domain dataset. This is analogous to the better-known "shift-and-stack" method; however it uses neither direct shifting nor stacking of the image pixels. Instead of resampling the raw pixels to create an image stack, we will instead integrate the object detection probabilities across multiple single-epoch images to accrue support for a proposed orbit. The filtering kernel provides a measure of the probability that an object is present along a given orbit, and enables the user to make principled decisions about when the search has been successful, and when it may be terminated. The results we present here utilize GPUs to speed up the search by two orders of magnitudes over CPU implementations.

Comparing approaches for using climate projections in assessing water resources investments for systems with multiple stakeholder groups

NASA Astrophysics Data System (ADS)

Hurford, Anthony; Harou, Julien

2015-04-01

Climate change has challenged conventional methods of planning water resources infrastructure investment, relying on stationarity of time-series data. It is not clear how to best use projections of future climatic conditions. Many-objective simulation-optimisation and trade-off analysis using evolutionary algorithms has been proposed as an approach to addressing complex planning problems with multiple conflicting objectives. The search for promising assets and policies can be carried out across a range of climate projections, to identify the configurations of infrastructure investment shown by model simulation to be robust under diverse future conditions. Climate projections can be used in different ways within a simulation model to represent the range of possible future conditions and understand how optimal investments vary according to the different hydrological conditions. We compare two approaches, optimising over an ensemble of different 20-year flow and PET timeseries projections, and separately for individual future scenarios built synthetically from the original ensemble. Comparing trade-off curves and surfaces generated by the two approaches helps understand the limits and benefits of optimising under different sets of conditions. The comparison is made for the Tana Basin in Kenya, where climate change combined with multiple conflicting objectives of water management and infrastructure investment mean decision-making is particularly challenging.

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems.

PubMed

Oh, Sang-Il; Kang, Hang-Bong

2017-01-22

To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN). The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI) pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR) sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226 × 370 image, whereas the original selective search method extracted approximately 10 6 × n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset.

Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

To understand driving environments effectively, it is important to achieve accurate detection and classification of objects detected by sensor-based intelligent vehicle systems, which are significantly important tasks. Object detection is performed for the localization of objects, whereas object classification recognizes object classes from detected object regions. For accurate object detection and classification, fusing multiple sensor information into a key component of the representation and perception processes is necessary. In this paper, we propose a new object-detection and classification method using decision-level fusion. We fuse the classification outputs from independent unary classifiers, such as 3D point clouds and image data using a convolutional neural network (CNN). The unary classifiers for the two sensors are the CNN with five layers, which use more than two pre-trained convolutional layers to consider local to global features as data representation. To represent data using convolutional layers, we apply region of interest (ROI) pooling to the outputs of each layer on the object candidate regions generated using object proposal generation to realize color flattening and semantic grouping for charge-coupled device and Light Detection And Ranging (LiDAR) sensors. We evaluate our proposed method on a KITTI benchmark dataset to detect and classify three object classes: cars, pedestrians and cyclists. The evaluation results show that the proposed method achieves better performance than the previous methods. Our proposed method extracted approximately 500 proposals on a 1226×370 image, whereas the original selective search method extracted approximately 106×n proposals. We obtained classification performance with 77.72% mean average precision over the entirety of the classes in the moderate detection level of the KITTI benchmark dataset. PMID:28117742

How to Assess Vulnerabilities of Water Policies to Global Change?

NASA Astrophysics Data System (ADS)

Kumar, A.; Haasnoot, M.; Weijs, S.

2017-12-01

Water managers are confronted with uncertainties arising from hydrological, societal, economical and political drivers. To manage these uncertainties two paradigms have been identified: top-down and bottom-up approaches. Top-down or prediction-based approaches use socio-economic scenarios together with a discrete set of GCM projections (often downscaled) to assess the expected impact of drivers and policies on water resource system through various hydrological and social systems models. Adaptation strategies to alleviate these impacts are then identified and tested against the scenarios. To address GCM and downscaling uncertainties, these approaches put more focus on climate predictions, rather than the decision problem itself. Triggered by the wish to have a more scenario-neutral approach and address downscaling uncertainties, recent analyses have been shifted towards vulnerability-based (bottom-up or decision-centric) approaches. They begin at the local scale by addressing socio-economic responses to climate, often involving stakeholder's input; identify vulnerabilities under a larger sample of plausible futures and evaluate sensitivity and robustness of possible adaptation options. Several bottom-up approaches have emerged so far and are increasingly recommended. Fundamentally they share several core ideas, however, subtle differences exist in vulnerability assessment, visualization tools for exploring vulnerabilities and computational methods used for identifying robust water policies. Through this study, we try to identify how these approaches are progressing, how the climate and non-climate uncertainties are being confronted and how to integrate existing and new tools. We find that choice of a method may depend on the number of vulnerability drivers identified and type of threshold levels (environmental conditions or policy objectives) defined. Certain approaches are suited well for assessing adaptive capacities, tipping points and sequencing of decisions. However, visualization of the vulnerability domain is still challenging if multiple drivers are present. New emerging tools are focused on generating synthetic scenarios, addressing multiple objectives, linking decision-making frameworks to adaptation pathways and communicating risks to the stakeholders.

Different approaches for centralized and decentralized water system management in multiple decision makers' problems

NASA Astrophysics Data System (ADS)

Anghileri, D.; Giuliani, M.; Castelletti, A.

2012-04-01

There is a general agreement that one of the most challenging issues related to water system management is the presence of many and often conflicting interests as well as the presence of several and independent decision makers. The traditional approach to multi-objective water systems management is a centralized management, in which an ideal central regulator coordinates the operation of the whole system, exploiting all the available information and balancing all the operating objectives. Although this approach allows to obtain Pareto-optimal solutions representing the maximum achievable benefit, it is based on assumptions which strongly limits its application in real world contexts: 1) top-down management, 2) existence of a central regulation institution, 3) complete information exchange within the system, 4) perfect economic efficiency. A bottom-up decentralized approach seems therefore to be more suitable for real case applications since different reservoir operators may maintain their independence. In this work we tested the consequences of a change in the water management approach moving from a centralized toward a decentralized one. In particular we compared three different cases: the centralized management approach, the independent management approach where each reservoir operator takes the daily release decision maximizing (or minimizing) his operating objective independently from each other, and an intermediate approach, leading to the Nash equilibrium of the associated game, where different reservoir operators try to model the behaviours of the other operators. The three approaches are demonstrated using a test case-study composed of two reservoirs regulated for the minimization of flooding in different locations. The operating policies are computed by solving one single multi-objective optimal control problem, in the centralized management approach; multiple single-objective optimization problems, i.e. one for each operator, in the independent case; using techniques related to game theory for the description of the interaction between the two operators, in the last approach. Computational results shows that the Pareto-optimal control policies obtained in the centralized approach dominate the control policies of both the two cases of decentralized management and that the so called price of anarchy increases moving toward the independent management approach. However, the Nash equilibrium solution seems to be the most promising alternative because it represents a good compromise in maximizing management efficiency without limiting the behaviours of the reservoir operators.

Using features of Arden Syntax with object-oriented medical data models for guideline modeling.

PubMed

Peleg, M; Ogunyemi, O; Tu, S; Boxwala, A A; Zeng, Q; Greenes, R A; Shortliffe, E H

2001-01-01

Computer-interpretable guidelines (CIGs) can deliver patient-specific decision support at the point of care. CIGs base their recommendations on eligibility and decision criteria that relate medical concepts to patient data. CIG models use expression languages for specifying these criteria, and define models for medical data to which the expressions can refer. In developing version 3 of the GuideLine Interchange Format (GLIF3), we used existing standards as the medical data model and expression language. We investigated the object-oriented HL7 Reference Information Model (RIM) as a default data model. We developed an expression language, called GEL, based on Arden Syntax's logic grammar. Together with other GLIF constructs, GEL reconciles incompatibilities between the data models of Arden Syntax and the HL7 RIM. These incompatibilities include Arden's lack of support for complex data types and time intervals, and the mismatch between Arden's single primary time and multiple time attributes of the HL7 RIM.

Evaluation of multiple muscle loads through multi-objective optimization with prediction of subjective satisfaction level: illustration by an application to handrail position for standing.

PubMed

Chihara, Takanori; Seo, Akihiko

2014-03-01

Proposed here is an evaluation of multiple muscle loads and a procedure for determining optimum solutions to ergonomic design problems. The simultaneous muscle load evaluation is formulated as a multi-objective optimization problem, and optimum solutions are obtained for each participant. In addition, one optimum solution for all participants, which is defined as the compromise solution, is also obtained. Moreover, the proposed method provides both objective and subjective information to support the decision making of designers. The proposed method was applied to the problem of designing the handrail position for the sit-to-stand movement. The height and distance of the handrails were the design variables, and surface electromyograms of four muscles were measured. The optimization results suggest that the proposed evaluation represents the impressions of participants more completely than an independent use of muscle loads. In addition, the compromise solution is determined, and the benefits of the proposed method are examined. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Tactical decisions for changeable cuttlefish camouflage: visual cues for choosing masquerade are relevant from a greater distance than visual cues used for background matching.

PubMed

Buresch, Kendra C; Ulmer, Kimberly M; Cramer, Corinne; McAnulty, Sarah; Davison, William; Mäthger, Lydia M; Hanlon, Roger T

2015-10-01

Cuttlefish use multiple camouflage tactics to evade their predators. Two common tactics are background matching (resembling the background to hinder detection) and masquerade (resembling an uninteresting or inanimate object to impede detection or recognition). We investigated how the distance and orientation of visual stimuli affected the choice of these two camouflage tactics. In the current experiments, cuttlefish were presented with three visual cues: 2D horizontal floor, 2D vertical wall, and 3D object. Each was placed at several distances: directly beneath (in a circle whose diameter was one body length (BL); at zero BL [(0BL); i.e., directly beside, but not beneath the cuttlefish]; at 1BL; and at 2BL. Cuttlefish continued to respond to 3D visual cues from a greater distance than to a horizontal or vertical stimulus. It appears that background matching is chosen when visual cues are relevant only in the immediate benthic surroundings. However, for masquerade, objects located multiple body lengths away remained relevant for choice of camouflage. © 2015 Marine Biological Laboratory.

To analyse a trace or not? Evaluating the decision-making process in the criminal investigation.

PubMed

Bitzer, Sonja; Ribaux, Olivier; Albertini, Nicola; Delémont, Olivier

2016-05-01

In order to broaden our knowledge and understanding of the decision steps in the criminal investigation process, we started by evaluating the decision to analyse a trace and the factors involved in this decision step. This decision step is embedded in the complete criminal investigation process, involving multiple decision and triaging steps. Considering robbery cases occurring in a geographic region during a 2-year-period, we have studied the factors influencing the decision to submit biological traces, directly sampled on the scene of the robbery or on collected objects, for analysis. The factors were categorised into five knowledge dimensions: strategic, immediate, physical, criminal and utility and decision tree analysis was carried out. Factors in each category played a role in the decision to analyse a biological trace. Interestingly, factors involving information available prior to the analysis are of importance, such as the fact that a positive result (a profile suitable for comparison) is already available in the case, or that a suspect has been identified through traditional police work before analysis. One factor that was taken into account, but was not significant, is the matrix of the trace. Hence, the decision to analyse a trace is not influenced by this variable. The decision to analyse a trace first is very complex and many of the tested variables were taken into account. The decisions are often made on a case-by-case basis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Self-management priority setting and decision-making in adults with multimorbidity: A narrative review of literature

PubMed Central

Bratzke, Lisa C.; Muehrer, Rebecca J.; Kehl, Karen A.; Lee, Kyoung Suk; Ward, Earlise C.; Kwekkeboom, Kristine L.

2014-01-01

Objectives The purpose of this narrative review was to synthesize current research findings related to self-management, in order to better understand the processes of priority setting and decision-making in among adults with multimorbidity. Design A narrative literature review was undertaken, synthesizing findings from published, peer-reviewed empirical studies that addressed priority setting and/or decision-making in self-management of multimorbidity. Data sources A search of PubMed, PsychINFO, CINAHL and SocIndex databases was conducted from database inception through December 2013. References lists from selected empirical studies and systematic reviews were evaluated to identify any additional relevant articles. Review methods Full text of potentially eligible articles were reviewed and selected for inclusion if they described empirical studies that addressed priority setting or decision-making in self-management of multimorbidity among adults. Two independent reviewers read each selected article and extracted relevant data to an evidence table. Processes and factors and processes of multimorbidity self-management were identified and sorted into categories of priority setting, decision-making, and facilitators/barriers. Results Thirteen articles were selected for inclusion; most were qualitative studies describing processes, facilitators, and barriers of multimorbidity self-management. The findings revealed that patients prioritize a dominant chronic illness and re-prioritize over time as conditions and treatments change; that multiple facilitators (e.g. support programs) and barriers (e.g. lack of financial resources) impact individuals’ self-management priority setting and decision-making ability; as do individual beliefs, preferences, and attitudes (e.g., perceived personal control, preferences regarding treatment). Conclusions Health care providers need to be cognizant that individuals with multimorbidity engage in day-to-day priority setting and decision-making among their multiple chronic illnesses and respective treatments. Researchers need to develop and test interventions that support day-to-day priority setting and decision-making and improve health outcomes for individuals with multimorbidity. PMID:25468131

Keeping All the PIECES: Phylogenetically Informed Ex Situ Conservation of Endangered Species.

PubMed

Larkin, Daniel J; Jacobi, Sarah K; Hipp, Andrew L; Kramer, Andrea T

2016-01-01

Ex situ conservation in germplasm and living collections is a major focus of global plant conservation strategies. Prioritizing species for ex situ collection is a necessary component of this effort for which sound strategies are needed. Phylogenetic considerations can play an important role in prioritization. Collections that are more phylogenetically diverse are likely to encompass more ecological and trait variation, and thus provide stronger conservation insurance and richer resources for future restoration efforts. However, phylogenetic criteria need to be weighed against other, potentially competing objectives. We used ex situ collection and threat rank data for North American angiosperms to investigate gaps in ex situ coverage and phylogenetic diversity of collections and to develop a flexible framework for prioritizing species across multiple objectives. We found that ex situ coverage of 18,766 North American angiosperm taxa was low with respect to the most vulnerable taxa: just 43% of vulnerable to critically imperiled taxa were in ex situ collections, far short of a year-2020 goal of 75%. In addition, species held in ex situ collections were phylogenetically clustered (P < 0.001), i.e., collections comprised less phylogenetic diversity than would be expected had species been drawn at random. These patterns support incorporating phylogenetic considerations into ex situ prioritization in a manner balanced with other criteria, such as vulnerability. To meet this need, we present the 'PIECES' index (Phylogenetically Informed Ex situ Conservation of Endangered Species). PIECES integrates phylogenetic considerations into a flexible framework for prioritizing species across competing objectives using multi-criteria decision analysis. Applying PIECES to prioritizing ex situ conservation of North American angiosperms, we show strong return on investment across multiple objectives, some of which are negatively correlated with each other. A spreadsheet-based decision support tool for North American angiosperms is provided; this tool can be customized to align with different conservation objectives.

Keeping All the PIECES: Phylogenetically Informed Ex Situ Conservation of Endangered Species

PubMed Central

Larkin, Daniel J.; Jacobi, Sarah K.; Hipp, Andrew L.; Kramer, Andrea T.

2016-01-01

Ex situ conservation in germplasm and living collections is a major focus of global plant conservation strategies. Prioritizing species for ex situ collection is a necessary component of this effort for which sound strategies are needed. Phylogenetic considerations can play an important role in prioritization. Collections that are more phylogenetically diverse are likely to encompass more ecological and trait variation, and thus provide stronger conservation insurance and richer resources for future restoration efforts. However, phylogenetic criteria need to be weighed against other, potentially competing objectives. We used ex situ collection and threat rank data for North American angiosperms to investigate gaps in ex situ coverage and phylogenetic diversity of collections and to develop a flexible framework for prioritizing species across multiple objectives. We found that ex situ coverage of 18,766 North American angiosperm taxa was low with respect to the most vulnerable taxa: just 43% of vulnerable to critically imperiled taxa were in ex situ collections, far short of a year-2020 goal of 75%. In addition, species held in ex situ collections were phylogenetically clustered (P < 0.001), i.e., collections comprised less phylogenetic diversity than would be expected had species been drawn at random. These patterns support incorporating phylogenetic considerations into ex situ prioritization in a manner balanced with other criteria, such as vulnerability. To meet this need, we present the ‘PIECES’ index (Phylogenetically Informed Ex situ Conservation of Endangered Species). PIECES integrates phylogenetic considerations into a flexible framework for prioritizing species across competing objectives using multi-criteria decision analysis. Applying PIECES to prioritizing ex situ conservation of North American angiosperms, we show strong return on investment across multiple objectives, some of which are negatively correlated with each other. A spreadsheet-based decision support tool for North American angiosperms is provided; this tool can be customized to align with different conservation objectives. PMID:27257671

Patient Decision Making in Vestibular Schwannoma: A Survey of the Acoustic Neuroma Association.

PubMed

Moshtaghi, Omid; Goshtasbi, Khodayar; Sahyouni, Ronald; Lin, Harrison W; Djalilian, Hamid R

2018-05-01

Objective To assess the decision-making process of patients with vestibular schwannoma (VS). Study Design Patients with VS completed a voluntary survey over a 3-month period. Setting Surveys were distributed online through email, Facebook, and member website. Subjects and Methods All patients had a diagnosis of VS and were members of the Acoustic Neuroma Association (ANA). A total of 789 patients completed the online survey. Results Of the 789 participants, 474 (60%) cited physician recommendation as a significant influential factor in deciding treatment. In our sample, 629 (80%) saw multiple VS specialists and 410 (52%) sought second opinions within the same specialty. Of those who received multiple consults, 242 (59%) of patients reported receiving different opinions regarding treatment. Those undergoing observation spent significantly less time with the physician (41 minutes) compared to surgery (68 minutes) and radiation (60 minutes) patients ( P < .001). A total of 32 (4%) patients stated the physician alone made the decision for treatment, and 29 (4%) felt they did not understand all possible treatment options before final decision was made. Of the 414 patients who underwent surgery, 66 (16%) felt they were pressured by the surgeon to choose surgical treatment. Conclusion Deciding on a proper VS treatment for patients can be complicated and dependent on numerous clinical and individual factors. It is clear that many patients find it important to seek second opinions from other specialties. Moreover, second opinions within the same specialty are common, and the number of neurotologists consulted correlated with higher decision satisfaction.

Value-Based Assessment of New Medical Technologies: Towards a Robust Methodological Framework for the Application of Multiple Criteria Decision Analysis in the Context of Health Technology Assessment.

PubMed

Angelis, Aris; Kanavos, Panos

2016-05-01

In recent years, multiple criteria decision analysis (MCDA) has emerged as a likely alternative to address shortcomings in health technology assessment (HTA) by offering a more holistic perspective to value assessment and acting as an alternative priority setting tool. In this paper, we argue that MCDA needs to subscribe to robust methodological processes related to the selection of objectives, criteria and attributes in order to be meaningful in the context of healthcare decision making and fulfil its role in value-based assessment (VBA). We propose a methodological process, based on multi-attribute value theory (MAVT) methods comprising five distinct phases, outline the stages involved in each phase and discuss their relevance in the HTA process. Importantly, criteria and attributes need to satisfy a set of desired properties, otherwise the outcome of the analysis can produce spurious results and misleading recommendations. Assuming the methodological process we propose is adhered to, the application of MCDA presents three very distinct advantages to decision makers in the context of HTA and VBA: first, it acts as an instrument for eliciting preferences on the performance of alternative options across a wider set of explicit criteria, leading to a more complete assessment of value; second, it allows the elicitation of preferences across the criteria themselves to reflect differences in their relative importance; and, third, the entire process of preference elicitation can be informed by direct stakeholder engagement, and can therefore reflect their own preferences. All features are fully transparent and facilitate decision making.

Parameter Estimation of Computationally Expensive Watershed Models Through Efficient Multi-objective Optimization and Interactive Decision Analytics

NASA Astrophysics Data System (ADS)

Akhtar, Taimoor; Shoemaker, Christine

2016-04-01

Watershed model calibration is inherently a multi-criteria problem. Conflicting trade-offs exist between different quantifiable calibration criterions indicating the non-existence of a single optimal parameterization. Hence, many experts prefer a manual approach to calibration where the inherent multi-objective nature of the calibration problem is addressed through an interactive, subjective, time-intensive and complex decision making process. Multi-objective optimization can be used to efficiently identify multiple plausible calibration alternatives and assist calibration experts during the parameter estimation process. However, there are key challenges to the use of multi objective optimization in the parameter estimation process which include: 1) multi-objective optimization usually requires many model simulations, which is difficult for complex simulation models that are computationally expensive; and 2) selection of one from numerous calibration alternatives provided by multi-objective optimization is non-trivial. This study proposes a "Hybrid Automatic Manual Strategy" (HAMS) for watershed model calibration to specifically address the above-mentioned challenges. HAMS employs a 3-stage framework for parameter estimation. Stage 1 incorporates the use of an efficient surrogate multi-objective algorithm, GOMORS, for identification of numerous calibration alternatives within a limited simulation evaluation budget. The novelty of HAMS is embedded in Stages 2 and 3 where an interactive visual and metric based analytics framework is available as a decision support tool to choose a single calibration from the numerous alternatives identified in Stage 1. Stage 2 of HAMS provides a goodness-of-fit measure / metric based interactive framework for identification of a small subset (typically less than 10) of meaningful and diverse set of calibration alternatives from the numerous alternatives obtained in Stage 1. Stage 3 incorporates the use of an interactive visual analytics framework for decision support in selection of one parameter combination from the alternatives identified in Stage 2. HAMS is applied for calibration of flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville watershed in upstate New York. Results from the application of HAMS to Cannonsville indicate that efficient multi-objective optimization and interactive visual and metric based analytics can bridge the gap between the effective use of both automatic and manual strategies for parameter estimation of computationally expensive watershed models.

Planning water supply under uncertainty - benefits and limitations of RDM, Info-Gap, economic optimization and many-objective optimization

NASA Astrophysics Data System (ADS)

Matrosov, E.; Padula, S.; Huskova, I.; Harou, J. J.

2012-12-01

Population growth and the threat of drier or changed climates are likely to increase water scarcity world-wide. A combination of demand management (water conservation) and new supply infrastructure is often needed to meet future projected demands. In this case system planners must decide what to implement, when and at what capacity. Choices can range from infrastructure to policies or a mix of the two, culminating in a complex planning problem. Decision making under uncertainty frameworks can be used to help planners with this planning problem. This presentation introduces, applies and compares four decision making under uncertainty frameworks. The application is to the Thames basin water resource system which includes the city of London. The approaches covered here include least-economic cost capacity expansion optimization (EO), Robust Decision Making (RDM), Info-Gap Decision Theory (Info-gap) and many-objective evolutionary optimization (MOEO). EO searches for the least-economic cost program, i.e. the timing, sizing, and choice of supply-demand management actions/upgrades which meet projected water demands. Instead of striving for optimality, the RDM and Info-gap approaches help build plans that are robust to 'deep' uncertainty in future conditions. The MOEO framework considers multiple performance criteria and uses water systems simulators as a function evaluator for the evolutionary algorithm. Visualizations show Pareto approximate tradeoffs between multiple objectives. In this presentation we detail the application of each framework to the Thames basin (including London) water resource planning problem. Supply and demand options are proposed by the major water companies in the basin. We apply the EO method using a 29 year time horizon and an annual time step considering capital, operating (fixed and variable), social and environmental costs. The method considers all plausible combinations of supply and conservation schemes and capacities proposed by water companies and generates the least-economic cost annual plan. The RDM application uses stochastic simulation under a weekly time-step and regret analysis to choose a candidate strategy. We then use a statistical cluster algorithm to identify future states of the world under which the strategy is vulnerable. The method explicitly considers the effects of uncertainty in supply, demands and energy price on multiple performance criteria. The Info-gap approach produces robustness and opportuneness plots that show the performance of different plans under the most dire and favorable sets of future conditions. The same simulator, supply and demand options and uncertainties are considered as in the RDM application. The MOEO application considers many more combinations of supply and demand options while still employing a simulator that enables a more realistic representation of the physical system and operating rules. A computer cluster is employed to ease the computational burden. Visualization software allows decision makers to interactively view tradeoffs in many dimensions. Benefits and limitations of each framework are discussed and recommendations for future planning in the basin are provided.

Using a Multiobjective Approach to Balance Mission and Network Goals within a Delay Tolerant Network Topology

DTIC Science & Technology

2009-03-01

incorporating autonomous actions, but none appear to incorporate a cognitive aspect used to balance multiple objectives as is the focus of this work. There...routing algorithm) and/or mission type decision (orbit path change). In this component, the pseudo- cognitive aspect is implemented within the...orbit change behavior doesn’t know which orbit to choose. This is where the cognitive aspect takes over. Since the orbit change behavior doesn’t

A web-based multicriteria evaluation of spatial trade-offs between environmental and economic implications from hydraulic fracturing in a shale gas region in Ohio.

PubMed

Liu, X; Gorsevski, P V; Yacobucci, M M; Onasch, C M

2016-06-01

Planning of shale gas infrastructure and drilling sites for hydraulic fracturing has important spatial implications. The evaluation of conflicting and competing objectives requires an explicit consideration of multiple criteria as they have important environmental and economic implications. This study presents a web-based multicriteria spatial decision support system (SDSS) prototype with a flexible and user-friendly interface that could provide educational or decision-making capabilities with respect to hydraulic fracturing site selection in eastern Ohio. One of the main features of this SDSS is to emphasize potential trade-offs between important factors of environmental and economic ramifications from hydraulic fracturing activities using a weighted linear combination (WLC) method. In the prototype, the GIS-enabled analytical components allow spontaneous visualization of available alternatives on maps which provide value-added features for decision support processes and derivation of final decision maps. The SDSS prototype also facilitates nonexpert participation capabilities using a mapping module, decision-making tool, group decision module, and social media sharing tools. The logical flow of successively presented forms and standardized criteria maps is used to generate visualization of trade-off scenarios and alternative solutions tailored to individual user's preferences that are graphed for subsequent decision-making.

The Air Quality Model Evaluation International Initiative ...

EPA Pesticide Factsheets

This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through AQMEII with a particular focus on past and future analyses of deposition. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

The Global Sustainability Index: An Instrument For Assessing The Progress Towards The Sustainable Organization

NASA Astrophysics Data System (ADS)

Grecu, Valentin

2015-09-01

There is rarely an optimal solution in sustainable development but most frequently a need to build compromises between conflicting aspects such as economic, social and environmental ones and different expectations of stakeholders. Moreover, information is rarely available and precise. This paper will focus on how to use indicators to monitor sustainable development, integrating the information provided by many of them into a complex general sustainability index. Having this general indicator is essential for decision makers as it is very complicated to evaluate the performance of the organization based on multiple indicators. The objective of this paper is to find mathematical algorithms for simplifying the decision-making process by offering an instrument for the evaluation of the sustainability progress.

Network meta-analysis: an introduction for pharmacists.

PubMed

Xu, Yina; Amiche, Mohamed Amine; Tadrous, Mina

2018-05-21

Network meta-analysis is a new tool used to summarize and compare studies for multiple interventions, irrespective of whether these interventions have been directly evaluated against each other. Network meta-analysis is quickly becoming the standard in conducting therapeutic reviews and clinical guideline development. However, little guidance is available to help pharmacists review network meta-analysis studies in their practice. Major institutions such as the Cochrane Collaboration, Agency for Healthcare Research and Quality, Canadian Agency for Drugs and Technologies in Health, and National Institute for Health and Care Excellence Decision Support Unit have endorsed utilizing network meta-analysis to establish therapeutic evidence and inform decision making. Our objective is to introduce this novel technique to pharmacy practitioners, and highlight key assumptions behind network meta-analysis studies.

Local classifier weighting by quadratic programming.

PubMed

Cevikalp, Hakan; Polikar, Robi

2008-10-01

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

What is a “good” treatment decision?: Decisional control, knowledge, treatment decision-making, and quality of life in men with clinically localized prostate cancer

PubMed Central

Orom, Heather; Biddle, Caitlin; Underwood, Willie; Nelson, Christian J.; Homish, D. Lynn

2016-01-01

Objective We explored whether active patient involvement in decision making and greater patient knowledge are associated with better treatment decision making experiences and better quality of life (QOL) among men with clinically localized prostate cancer. Localized prostate cancer treatment decision-making is an advantageous model for studying patient treatment decision-making dynamics as there are multiple treatment options and a lack of empirical evidence to recommend one over the other; consequently, it is recommended that patients be fully involved in making the decision. Methods Men with newly diagnosed clinically localized prostate cancer (N=1529) completed measures of decisional control, prostate cancer knowledge, and their decision-making experience (decisional conflict, and decision-making satisfaction and difficulty) shortly after they made their treatment decision. Prostate cancer-specific QOL was assessed 6-months after treatment. Results More active involvement in decision making and greater knowledge were associated with lower decisional conflict and higher decision-making satisfaction, but greater decision-making difficulty. An interaction between decisional control and knowledge revealed that greater knowledge was only associated with greater difficulty for men actively involved in making the decision (67% of sample). Greater knowledge, but not decisional control predicted better QOL 6-months post-treatment. Conclusion Although men who are actively involved in decision making and more knowledgeable may make more informed decisions, they could benefit from decisional support (e.g., decision-making aids, emotional support from providers, strategies for reducing emotional distress) to make the process easier. Men who were more knowledgeable about prostate cancer and treatment side effects at the time they made their treatment decision may have appraised their QOL as higher because they had realistic expectations about side effects. PMID:26957566

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

PubMed

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

2015-01-01

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

Management and monitoring of the endangered Shenandoah salamander under climate change: Workshop report 10-12 April 2012

USGS Publications Warehouse

Grant, Evan H. Campbell; Wofford, John E.B.; Smith, D.R.; Dennis, J.; Hawkins-Hoffman, C.; Schaberl, J.; Foley, M.; Bogle, M.

2014-01-01

Here we report on a structured decision making (SDM) process to identify management strategies to ensure persistence of the federally endangered Shenandoah salamander (Plethodon shenandoah), given that it may be at increased extinction risk under projected climate change. The focus of this report is the second of two SDM workshops; in the first workshop, participants developed a prototype of the decision, including problem frame, management objectives and a suite of potential management strategies, predictive models to inform the decision and link alternatives with the objectives to identify potential solutions, and identified data needs to reduce key uncertainties in the decision. Participants in this second workshop included experts in National Park Service policy at multiple administrative levels, who refined objectives, further evaluated the initial management alternatives, and discussed policy constraints on implementing active management for the species and its high-elevation habitat. The conclusion of the second workshop was similar to that of the first: the current state of information and objectives suggest that there is some value in considering active management to reduce the long-term extinction risk for the species, though there are institutional conservative policies to implementing active management at range-wide scales. The workshop participants also emphasized a conservative NPS management philosophy, including caution in implementing management actions that may ultimately harm the system, a stated assumption that ecosystem changes were “natural” unless demonstrated otherwise (therefore not warranting active management to mitigate), and a need to demonstrate that extinction risk is tied to anthropogenic influence prior to taking active management to mitigate specific anthropogenic influences. Even within a protected area having minimal human disturbance, intertwined environmental variables and interspecific relationships that drive population trends challenge our ability to demonstrate direct links with (anthropogenically influenced) climate change and the decline of a species. Thus while this policy may reduce the potential for injurious management, it may also necessitate extraordinary resources to reduce uncertainty regarding fundamental drivers of species decline prior to taking action.

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Energy Decision Science and Informatics | Integrated Energy Solutions |

Science.gov Websites

Science Advanced decision science methods include multi-objective and multi-criteria decision support. Our decision science methods, including multi-objective and multi-criteria decision support. For example, we

Shared Decision Making and Other Variables as Correlates of Satisfaction with Health Care Decisions in a United States National Survey

PubMed Central

Wills, Celia E.; Holloman, Christopher; Olson, Jacklyn; Hechmer, Catherine; Miller, Carla K.; Duchemin, Anne-Marie

2012-01-01

Objective The purpose of this study was to examine the relationship between shared decision-making (SDM) and satisfaction with decision (SWD) within a larger survey of patient decision-making in health care consultations. Methods A randomly selected age-proportionate national sample of adults (aged 21–70 years) stratified on race, ethnicity, and gender (N = 488) was recruited from a health research volunteer registry and completed an online survey with reference to a recent health consultation. Measures included the Shared Decision Making-9 questionnaire (SDM-Q-9), Satisfaction With Decision (SWD) scale, sociodemographic, health, and other standardized decision-making measures. Forward selection weighted multiple regression analysis was used to model correlates of SWD. Results After controlling for sociodemographic variables, SDM-Q-9 total score was associated with SWD, adjusted R2 = .368, p < .001. Three of nine SDM-Q-9 items accounted for significant proportions of variance in SWD. Conclusion SDM was positively associated with SWD and was strongest for three areas of SDM: patients being helped in a health care consultation with understanding information, with treatment preference elicitation, and with weighing options thoroughly. Practice Implications By identifying variables such as SDM that are associated with SWD, health care interventions can better target modifiable factors to enhance satisfaction and other outcomes. PMID:22410642

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

PubMed Central

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

2018-01-01

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

Doubt and belief in physicians' ability to prognosticate during critical illness: The perspective of surrogate decision makers

PubMed Central

Zier, Lucas S.; Burack, Jeffrey H.; Micco, Guy; Chipman, Anne K.; Frank, James A.; Luce, John M.; White, Douglas B.

2009-01-01

Objectives: Although discussing a prognosis is a duty of physicians caring for critically ill patients, little is known about surrogate decision-makers' beliefs about physicians' ability to prognosticate. We sought to determine: 1) surrogates' beliefs about whether physicians can accurately prognosticate for critically ill patients; and 2) how individuals use prognostic information in their role as surrogate decision-makers. Design, Setting, and Patients: Multicenter study in intensive care units of a public hospital, a tertiary care hospital, and a veterans' hospital. We conducted semistructured interviews with 50 surrogate decision-makers of critically ill patients. We analyzed the interview transcripts using grounded theory methods to inductively develop a framework to describe surrogates' beliefs about physicians' ability to prognosticate. Validation methods included triangulation by multidisciplinary analysis and member checking. Measurements and Main Results: Overall, 88% (44 of 50) of surrogates expressed doubt about physicians' ability to prognosticate for critically ill patients. Four distinct themes emerged that explained surrogates' doubts about prognostic accuracy: a belief that God could alter the course of the illness, a belief that predicting the future is inherently uncertain, prior experiences where physicians' prognostications were inaccurate, and experiences with prognostication during the patient's intensive care unit stay. Participants also identified several factors that led to belief in physicians' prognostications, such as receiving similar prognostic estimates from multiple physicians and prior experiences with accurate prognostication. Surrogates' doubts about prognostic accuracy did not prevent them from wanting prognostic information. Instead, most surrogate decision-makers view physicians' prognostications as rough estimates that are valuable in informing decisions, but are not determinative. Surrogates identified the act of prognostic disclosure as a key step in preparing emotionally and practically for the possibility that a patient may not survive. Conclusions: Although many surrogate decision-makers harbor some doubt about the accuracy of physicians' prognostications, they highly value discussions about prognosis and use the information for multiple purposes. (Crit Care Med 2008; 36: 2341–2347) PMID:18596630

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

PubMed

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

2018-02-01

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

Improving the Efficiency of Physical Examination Services

PubMed Central

Chih, Mingchang; Bair, Aaron E.

2009-01-01

The objective of our project was to improve the efficiency of the physical examination screening service of a large hospital system. We began with a detailed simulation model to explore the relationships between four performance measures and three decision factors. We then attempted to identify the optimal physician inquiry starting time by solving a goal-programming problem, where the objective function includes multiple goals. One of our simulation results shows that the proposed optimal physician inquiry starting time decreased patient wait times by 50% without increasing overall physician utilization. Electronic supplementary material  The online version of this article (doi:10.1007/s10916-009-9271-z) contains supplementary material, which is available to authorized users. PMID:20703912

Decision Factors for Cooperative Multiple Warhead UAV Target Classification and Attack with Control Applications

DTIC Science & Technology

2004-10-01

Jeffrey P. Kharoufeh Committee Member Date /signed/ 22 Oct 04 Dr. Alan V. Lair Dean’s Representative Date /signed/ Robert A. Calico, Jr Dean...who also provided great comments on my drafts. As far as the drafts go, thanks to all the committee and the Dean’s Representative (Dr. Alan Lair ) for...11. Cozzolino, J.M. “Sequential Search for an Unknown Number of Objects of Nonuniform Size,” Operations Research, 20 :293–308 (1972). 12. de Guenin

Psychometric properties of the SDM-Q-9 questionnaire for shared decision-making in multiple sclerosis: item response theory modelling and confirmatory factor analysis.

PubMed

Ballesteros, Javier; Moral, Ester; Brieva, Luis; Ruiz-Beato, Elena; Prefasi, Daniel; Maurino, Jorge

2017-04-22

Shared decision-making is a cornerstone of patient-centred care. The 9-item Shared Decision-Making Questionnaire (SDM-Q-9) is a brief self-assessment tool for measuring patients' perceived level of involvement in decision-making related to their own treatment and care. Information related to the psychometric properties of the SDM-Q-9 for multiple sclerosis (MS) patients is limited. The objective of this study was to assess the performance of the items composing the SDM-Q-9 and its dimensional structure in patients with relapsing-remitting MS. A non-interventional, cross-sectional study in adult patients with relapsing-remitting MS was conducted in 17 MS units throughout Spain. A nonparametric item response theory (IRT) analysis was used to assess the latent construct and dimensional structure underlying the observed responses. A parametric IRT model, General Partial Credit Model, was fitted to obtain estimates of the relationship between the latent construct and item characteristics. The unidimensionality of the SDM-Q-9 instrument was assessed by confirmatory factor analysis. A total of 221 patients were studied (mean age = 42.1 ± 9.9 years, 68.3% female). Median Expanded Disability Status Scale score was 2.5 ± 1.5. Most patients reported taking part in each step of the decision-making process. Internal reliability of the instrument was high (Cronbach's α = 0.91) and the overall scale scalability score was 0.57, indicative of a strong scale. All items, except for the item 1, showed scalability indices higher than 0.30. Four items (items 6 through to 9) conveyed more than half of the SDM-Q-9 overall information (67.3%). The SDM-Q-9 was a good fit for a unidimensional latent structure (comparative fit index = 0.98, root-mean-square error of approximation = 0.07). All freely estimated parameters were statistically significant (P < 0.001). All items presented standardized parameter estimates with salient loadings (>0.40) with the exception of item 1 which presented the lowest loading (0.26). Items 6 through to 8 were the most relevant items for shared decision-making. The SDM-Q-9 presents appropriate psychometric properties and is therefore useful for assessing different aspects of shared decision-making in patients with multiple sclerosis.

Graphics to facilitate informative discussion and team decision making

DOE PAGES

Anderson-Cook, Christine M.; Lu, Lu

2018-03-25

Everyone knows the expression “A picture is worth a thousand words,” and this effectively summarizes the ability of graphical summaries to convey information and persuade. However, in many cases, the goal for the right visualization is to encourage and guide discussion while helping focus a team to make carefully considered, defensible, and data-driven decisions. The aims of graphics differ if we are trying to communicate the merits of a single choice versus outlining several contending alternatives for further comparison and discussion. These choices each have their own strengths and weaknesses depending on how we value different criteria. They also servemore » different purposes at various stages of decision making. Often the role of statisticians is not to provide a single answer but to provide rich information and summaries in a manageable and compact form to enable productive discussion among team members. Through a series of diverse examples, this work present principles and strategies for encouraging discussion and informed decision making and discuss how they can be integrated with versatile use of graphical tools for examining multiple objectives, framing trade-offs between alternatives, and examining the impact of subjective priorities and uncertainty on the final decision.« less

Classification of Parkinsonian syndromes from FDG-PET brain data using decision trees with SSM/PCA features.

PubMed

Mudali, D; Teune, L K; Renken, R J; Leenders, K L; Roerdink, J B T M

2015-01-01

Medical imaging techniques like fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to aid in the differential diagnosis of neurodegenerative brain diseases. In this study, the objective is to classify FDG-PET brain scans of subjects with Parkinsonian syndromes (Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy) compared to healthy controls. The scaled subprofile model/principal component analysis (SSM/PCA) method was applied to FDG-PET brain image data to obtain covariance patterns and corresponding subject scores. The latter were used as features for supervised classification by the C4.5 decision tree method. Leave-one-out cross validation was applied to determine classifier performance. We carried out a comparison with other types of classifiers. The big advantage of decision tree classification is that the results are easy to understand by humans. A visual representation of decision trees strongly supports the interpretation process, which is very important in the context of medical diagnosis. Further improvements are suggested based on enlarging the number of the training data, enhancing the decision tree method by bagging, and adding additional features based on (f)MRI data.

Graphics to facilitate informative discussion and team decision making

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

Anderson-Cook, Christine M.; Lu, Lu

Everyone knows the expression “A picture is worth a thousand words,” and this effectively summarizes the ability of graphical summaries to convey information and persuade. However, in many cases, the goal for the right visualization is to encourage and guide discussion while helping focus a team to make carefully considered, defensible, and data-driven decisions. The aims of graphics differ if we are trying to communicate the merits of a single choice versus outlining several contending alternatives for further comparison and discussion. These choices each have their own strengths and weaknesses depending on how we value different criteria. They also servemore » different purposes at various stages of decision making. Often the role of statisticians is not to provide a single answer but to provide rich information and summaries in a manageable and compact form to enable productive discussion among team members. Through a series of diverse examples, this work present principles and strategies for encouraging discussion and informed decision making and discuss how they can be integrated with versatile use of graphical tools for examining multiple objectives, framing trade-offs between alternatives, and examining the impact of subjective priorities and uncertainty on the final decision.« less

Resilience thinking and a decision-analytic approach to conservation: strange bedfellows or essential partners?

USGS Publications Warehouse

Johnson, Fred A.; Williams, Byron K.; Nichols, James D.

2013-01-01

There has been some tendency to view decision science and resilience theory as opposing approaches, or at least as contending perspectives, for natural resource management. Resilience proponents have been especially critical of optimization in decision science, at least for those cases where it is focused on the aggressive pursuit of efficiency. In general, optimization of resource systems is held to reduce spatial, temporal, or organizational heterogeneity that would otherwise limit efficiency, leading to homogenization of a system and making it less able to cope with unexpected changes or disturbances. For their part, decision analysts have been critical of resilience proponents for not providing much practical advice to decision makers. We believe a key source of tension between resilience thinking and application of decision science is the pursuit of efficiency in the latter (i.e., choosing the “best” management action or strategy option to maximize productivity of one or few resource components), vs. a desire in the former to keep options open (i.e., maintaining and enhancing diversity). It seems obvious, however, that with managed natural systems, there must be a principle by which to guide decision making, which at a minimumallows for a comparison of projected outcomes associated with decision alternatives. This is true even if the primary concern of decision making is the preservation of system resilience. We describe how a careful framing of conservation problems, especially in terms of management objectives and predictive models, can help reduce the purported tension between resiliencethinking and decision analysis. In particular, objective setting in conservation problems needs to be more attuned to the dynamics of ecological systems and to the possibility of deep uncertainties that underlie the risk of unintended, if not irreversible, outcomes. Resilience thinking also leads to the suggestion that model development should focus more on process rather than pattern, on multiple scales of influence, and on phenomena that can create alternative stability regimes. Although we acknowledge the inherent difficulties in modeling ecological processes, we stress that formulation of useful models need not depend on a thorough mechanistic understanding or precise parameterization, assuming that uncertainty is acknowledged and treated in a systematic manner.

Design of Experiments with Multiple Independent Variables: A Resource Management Perspective on Complete and Reduced Factorial Designs

PubMed Central

Collins, Linda M.; Dziak, John J.; Li, Runze

2009-01-01

An investigator who plans to conduct experiments with multiple independent variables must decide whether to use a complete or reduced factorial design. This article advocates a resource management perspective on making this decision, in which the investigator seeks a strategic balance between service to scientific objectives and economy. Considerations in making design decisions include whether research questions are framed as main effects or simple effects; whether and which effects are aliased (confounded) in a particular design; the number of experimental conditions that must be implemented in a particular design and the number of experimental subjects the design requires to maintain the desired level of statistical power; and the costs associated with implementing experimental conditions and obtaining experimental subjects. In this article four design options are compared: complete factorial, individual experiments, single factor, and fractional factorial designs. Complete and fractional factorial designs and single factor designs are generally more economical than conducting individual experiments on each factor. Although relatively unfamiliar to behavioral scientists, fractional factorial designs merit serious consideration because of their economy and versatility. PMID:19719358

Enhancing stakeholder involvement in environmental decision making: Active Response Geographic Information System

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

Faber, B.G.; Thomas, V.L.; Thomas, M.R.

This paper describes a spatial decision support system that facilitates land-related negotiations and resolving conflicts. This system, called Active Response Geographic Information System (AR/GIS), uses a geographic information system to examine land resource management issues which involve multiple stakeholder groups. In this process, participants are given the opportunity and tools needed to share ideas in a facilitated land resource allocation negotiation session. Participants are able to assess current land status, develop objectives, propose alternative planning scenarios, and evaluate the effects or impacts of each alternative. AR/GIS is a unique tool that puts geographic information directly at the fingertips of non-technicalmore » policy analysts, decision makers, and representatives of stakeholder groups during the negotiation process. AR/GIS enhances individual comprehension and ownership of the decision making process and increasing the efficiency and effectiveness of group debate. It is most beneficial to planning tasks which are inherently geographic in nature, which require consideration of a large number of physical constraints and economic implications, and which involve publicly sensitive tradeoffs.« less

An approach to improve the care of mid-life women through the implementation of a Women’s Health Assessment Tool/Clinical Decision Support toolkit

PubMed Central

Silvestrin, Terry M; Steenrod, Anna W; Coyne, Karin S; Gross, David E; Esinduy, Canan B; Kodsi, Angela B; Slifka, Gayle J; Abraham, Lucy; Araiza, Anna L; Bushmakin, Andrew G; Luo, Xuemei

2016-01-01

The objectives of this study are to describe the implementation process of the Women’s Health Assessment Tool/Clinical Decision Support toolkit and summarize patients’ and clinicians’ perceptions of the toolkit. The Women’s Health Assessment Tool/Clinical Decision Support toolkit was piloted at three clinical sites over a 4-month period in Washington State to evaluate health outcomes among mid-life women. The implementation involved a multistep process and engagement of multiple stakeholders over 18 months. Two-thirds of patients (n = 76/110) and clinicians (n = 8/12) participating in pilot completed feedback surveys; five clinicians participated in qualitative interviews. Most patients felt more prepared for their annual visit (69.7%) and that quality of care improved (68.4%) while clinicians reported streamlined patient visits and improved communication with patients. The Women’s Health Assessment Tool/Clinical Decision Support toolkit offers a unique approach to introduce and address some of the key health issues that affect mid-life women. PMID:27558508

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

PubMed

Liu, Hu-Chen; Wu, Jing; Li, Ping

2013-12-01

Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include "incineration", "steam sterilization", "microwave" and "landfill". The results obtained using the proposed approach are analyzed in a comparative way. Copyright © 2013. Published by Elsevier Ltd.

The Aeronautical Data Link: Decision Framework for Architecture Analysis

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Goode, Plesent W.

2003-01-01

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

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

NASA Astrophysics Data System (ADS)

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

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

Optimizing Irrigation Water Allocation under Multiple Sources of Uncertainty in an Arid River Basin

NASA Astrophysics Data System (ADS)

Wei, Y.; Tang, D.; Gao, H.; Ding, Y.

2015-12-01

Population growth and climate change add additional pressures affecting water resources management strategies for meeting demands from different economic sectors. It is especially challenging in arid regions where fresh water is limited. For instance, in the Tailanhe River Basin (Xinjiang, China), a compromise must be made between water suppliers and users during drought years. This study presents a multi-objective irrigation water allocation model to cope with water scarcity in arid river basins. To deal with the uncertainties from multiple sources in the water allocation system (e.g., variations of available water amount, crop yield, crop prices, and water price), the model employs a interval linear programming approach. The multi-objective optimization model developed from this study is characterized by integrating eco-system service theory into water-saving measures. For evaluation purposes, the model is used to construct an optimal allocation system for irrigation areas fed by the Tailan River (Xinjiang Province, China). The objective functions to be optimized are formulated based on these irrigation areas' economic, social, and ecological benefits. The optimal irrigation water allocation plans are made under different hydroclimate conditions (wet year, normal year, and dry year), with multiple sources of uncertainty represented. The modeling tool and results are valuable for advising decision making by the local water authority—and the agricultural community—especially on measures for coping with water scarcity (by incorporating uncertain factors associated with crop production planning).

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

PubMed

Dolan, James G

2010-01-01

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

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

PubMed Central

Dolan, James G.

2010-01-01

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

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

PubMed

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

2010-09-01

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

Making decisions in complex landscapes: Headwater stream management across multiple federal agencies

USGS Publications Warehouse

Katz, Rachel; Grant, Evan H. Campbell; Runge, Michael C.; Connery, Bruce; Crockett, Marquette; Herland, Libby; Johnson, Sheela; Kirk, Dawn; Wofford, Jeb; Bennett, Rick; Nislow, Keith; Norris, Marian; Hocking, Daniel; Letcher, Benjamin; Roy, Allison

2014-01-01

Headwater stream ecosystems are vulnerable to numerous threats associated with climate and land use change. In the northeastern US, many headwater stream species (e.g., brook trout and stream salamanders) are of special conservation concern and may be vulnerable to climate change influences, such as changes in stream temperature and streamflow. Federal land management agencies (e.g., US Fish and Wildlife Service, National Park Service, USDA Forest Service, Bureau of Land Management and Department of Defense) are required to adopt policies that respond to climate change and may have longer-term institutional support to enforce such policies compared to state, local, non-governmental, or private land managers. However, federal agencies largely make management decisions in regards to headwater stream ecosystems independently. This fragmentation of management resources and responsibilities across the landscape may significantly impede the efficiency and effectiveness of conservation actions, and higher degrees of collaboration may be required to achieve conservation goals. This project seeks to provide an example of cooperative landscape decision-making to address the conservation of headwater stream ecosystems. We identified shared and contrasting objectives of each federal agency and potential collaboration opportunities that may increase efficient and effective management of headwater stream ecosystems in two northeastern US watersheds. These workshops provided useful insights into the adaptive capacity of federal institutions to address threats to headwater stream ecosystems. Our ultimate goal is to provide a decision-making framework and analysis that addresses large-scale conservation threats across multiple stakeholders, as a demonstration of cooperative landscape conservation for aquatic ecosystems. Additionally, we aim to provide new scientific knowledge and a regional perspective to resource managers to help inform local management decisions.

Tactical resource allocation and elective patient admission planning in care processes.

PubMed

Hulshof, Peter J H; Boucherie, Richard J; Hans, Erwin W; Hurink, Johann L

2013-06-01

Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to meet production targets/to serve the strategically agreed number of patients, and to use resources efficiently. This paper proposes a method to develop a tactical resource allocation and elective patient admission plan. These tactical plans allocate available resources to various care processes and determine the selection of patients to be served that are at a particular stage of their care process. Our method is developed in a Mixed Integer Linear Programming (MILP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital, thereby integrating decision making for a chain of hospital resources. Computational results indicate that our method leads to a more equitable distribution of resources and provides control of patient access times, the number of patients served and the fraction of allocated resource capacity. Our approach is generic, as the base MILP and the solution approach allow for including various extensions to both the objective criteria and the constraints. Consequently, the proposed method is applicable in various settings of tactical hospital management.

A case study of resources management planning with multiple objectives and projects

NASA Astrophysics Data System (ADS)

Peterson, David L.; Silsbee, David G.; Schmoldt, Daniel L.

1994-09-01

Each National Park Service unit in the United States produces a resources management plan (RMP) every four years or less. The plans commit budgets and personnel to specific projects for four years, but they are prepared with little quantitative and analytical rigor and without formal decision-making tools. We have previously described a multiple objective planning process for inventory and monitoring programs (Schmoldt and others 1994). To test the applicability of that process for the more general needs of resources management planning, we conducted an exercise on the Olympic National Park (NP) in Washington State, USA. Eight projects were selected as typical of those considered in RMPs and five members of the Olympic NP staff used the analytic hierarchy process (AHP) to prioritize the eight projects with respect to their implicit management objectives. By altering management priorities for the park, three scenarios were generated. All three contained some similarities in rankings for the eight projects, as well as some differences. Mathematical allocations of money and people differed among these scenarios and differed substantially from what the actual 1990 Olympic NP RMP contains. Combining subjective priority measures with budget dollars and personnel time into an objective function creates a subjective economic metric for comparing different RMP’s. By applying this planning procedure, actual expenditures of budget and personnel in Olympic NP can agree more closely with the staff’s management objectives for the park.

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

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

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh

2015-01-15

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

Mapping Perceptions of Lupus Medication Decision-Making Facilitators: The Importance of Patient Context.

PubMed

Qu, Haiyan; Shewchuk, Richard M; Alarcón, Graciela; Fraenkel, Liana; Leong, Amye; Dall'Era, Maria; Yazdany, Jinoos; Singh, Jasvinder A

2016-12-01

Numerous factors can impede or facilitate patients' medication decision-making and adherence to physicians' recommendations. Little is known about how patients and physicians jointly view issues that affect the decision-making process. Our objective was to derive an empirical framework of patient-identified facilitators to lupus medication decision-making from key stakeholders (including 15 physicians, 5 patients/patient advocates, and 8 medical professionals) using a patient-centered cognitive mapping approach. We used nominal group patient panels to identify facilitators to lupus treatment decision-making. Stakeholders independently sorted the identified facilitators (n = 98) based on their similarities and rated the importance of each facilitator in patient decision-making. Data were analyzed using multidimensional scaling and hierarchical cluster analysis. A cognitive map was derived that represents an empirical framework of facilitators for lupus treatment decisions from multiple stakeholders' perspectives. The facilitator clusters were 1) hope for a normal/healthy life, 2) understand benefits and effectiveness of taking medications, 3) desire to minimize side effects, 4) medication-related data, 5) medication effectiveness for "me," 6) family focus, 7) confidence in physician, 8) medication research, 9) reassurance about medication, and 10) medication economics. Consideration of how different stakeholders perceive the relative importance of lupus medication decision-making clusters is an important step toward improving patient-physician communication and effective shared decision-making. The empirically derived framework of medication decision-making facilitators can be used as a guide to develop a lupus decision aid that focuses on improving physician-patient communication. © 2016, American College of Rheumatology.

Framing bioremediation decision making as negotiation: Rationale & guidelineFraming bioremediation decision making as negotiation: Rationale & guidelines

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

Bjornstad, David J.; Wolfe, Amy K.

Framing remediation decision making as negotiation: (1) social choice, not technology choice; (2) prompts decision makers to identify interested and affected parties, anticipate objections, effectively address and ameliorate objections, and avoid unacceptable decisions.

Reducing uncertainty about objective functions in adaptive management

USGS Publications Warehouse

Williams, B.K.

2012-01-01

This paper extends the uncertainty framework of adaptive management to include uncertainty about the objectives to be used in guiding decisions. Adaptive decision making typically assumes explicit and agreed-upon objectives for management, but allows for uncertainty as to the structure of the decision process that generates change through time. Yet it is not unusual for there to be uncertainty (or disagreement) about objectives, with different stakeholders expressing different views not only about resource responses to management but also about the appropriate management objectives. In this paper I extend the treatment of uncertainty in adaptive management, and describe a stochastic structure for the joint occurrence of uncertainty about objectives as well as models, and show how adaptive decision making and the assessment of post-decision monitoring data can be used to reduce uncertainties of both kinds. Different degrees of association between model and objective uncertainty lead to different patterns of learning about objectives. ?? 2011.

Top-down control of visual perception: attention in natural vision.

PubMed

Rolls, Edmund T

2008-01-01

Top-down perceptual influences can bias (or pre-empt) perception. In natural scenes, the receptive fields of neurons in the inferior temporal visual cortex (IT) shrink to become close to the size of objects. This facilitates the read-out of information from the ventral visual system, because the information is primarily about the object at the fovea. Top-down attentional influences are much less evident in natural scenes than when objects are shown against blank backgrounds, though are still present. It is suggested that the reduced receptive-field size in natural scenes, and the effects of top-down attention contribute to change blindness. The receptive fields of IT neurons in complex scenes, though including the fovea, are frequently asymmetric around the fovea, and it is proposed that this is the solution the IT uses to represent multiple objects and their relative spatial positions in a scene. Networks that implement probabilistic decision-making are described, and it is suggested that, when in perceptual systems they take decisions (or 'test hypotheses'), they influence lower-level networks to bias visual perception. Finally, it is shown that similar processes extend to systems involved in the processing of emotion-provoking sensory stimuli, in that word-level cognitive states provide top-down biasing that reaches as far down as the orbitofrontal cortex, where, at the first stage of affective representations, olfactory, taste, flavour, and touch processing is biased (or pre-empted) in humans.

Improvement of the F-Perceptory Approach Through Management of Fuzzy Complex Geographic Objects

NASA Astrophysics Data System (ADS)

Khalfi, B.; de Runz, C.; Faiz, S.; Akdag, H.

2015-08-01

In the real world, data is imperfect and in various ways such as imprecision, vagueness, uncertainty, ambiguity and inconsistency. For geographic data, the fuzzy aspect is mainly manifested in time, space and the function of objects and is due to a lack of precision. Therefore, the researchers in the domain emphasize the importance of modeling data structures in GIS but also their lack of adaptation to fuzzy data. The F-Perceptory approachh manages the modeling of imperfect geographic information with UML. This management is essential to maintain faithfulness to reality and to better guide the user in his decision-making. However, this approach does not manage fuzzy complex geographic objects. The latter presents a multiple object with similar or different geographic shapes. So, in this paper, we propose to improve the F-Perceptory approach by proposing to handle fuzzy complex geographic objects modeling. In a second step, we propose its transformation to the UML modeling.

Application of fuzzy theories to formulation of multi-objective design problems. [for helicopters

NASA Technical Reports Server (NTRS)

Dhingra, A. K.; Rao, S. S.; Miura, H.

1988-01-01

Much of the decision making in real world takes place in an environment in which the goals, the constraints, and the consequences of possible actions are not known precisely. In order to deal with imprecision quantitatively, the tools of fuzzy set theory can by used. This paper demonstrates the effectiveness of fuzzy theories in the formulation and solution of two types of helicopter design problems involving multiple objectives. The first problem deals with the determination of optimal flight parameters to accomplish a specified mission in the presence of three competing objectives. The second problem addresses the optimal design of the main rotor of a helicopter involving eight objective functions. A method of solving these multi-objective problems using nonlinear programming techniques is presented. Results obtained using fuzzy formulation are compared with those obtained using crisp optimization techniques. The outlined procedures are expected to be useful in situations where doubt arises about the exactness of permissible values, degree of credibility, and correctness of statements and judgements.

A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs.

PubMed

Forkan, Abdur Rahim Mohammad; Khalil, Ibrahim

2017-02-01

In home-based context-aware monitoring patient's real-time data of multiple vital signs (e.g. heart rate, blood pressure) are continuously generated from wearable sensors. The changes in such vital parameters are highly correlated. They are also patient-centric and can be either recurrent or can fluctuate. The objective of this study is to develop an intelligent method for personalized monitoring and clinical decision support through early estimation of patient-specific vital sign values, and prediction of anomalies using the interrelation among multiple vital signs. In this paper, multi-label classification algorithms are applied in classifier design to forecast these values and related abnormalities. We proposed a completely new approach of patient-specific vital sign prediction system using their correlations. The developed technique can guide healthcare professionals to make accurate clinical decisions. Moreover, our model can support many patients with various clinical conditions concurrently by utilizing the power of cloud computing technology. The developed method also reduces the rate of false predictions in remote monitoring centres. In the experimental settings, the statistical features and correlations of six vital signs are formulated as multi-label classification problem. Eight multi-label classification algorithms along with three fundamental machine learning algorithms are used and tested on a public dataset of 85 patients. Different multi-label classification evaluation measures such as Hamming score, F1-micro average, and accuracy are used for interpreting the prediction performance of patient-specific situation classifications. We achieved 90-95% Hamming score values across 24 classifier combinations for 85 different patients used in our experiment. The results are compared with single-label classifiers and without considering the correlations among the vitals. The comparisons show that multi-label method is the best technique for this problem domain. The evaluation results reveal that multi-label classification techniques using the correlations among multiple vitals are effective ways for early estimation of future values of those vitals. In context-aware remote monitoring this process can greatly help the doctors in quick diagnostic decision making. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Ohdaira, Tetsushi

2014-07-01

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

Mild Cognitive Impairment is Associated with PoorerDecision Making in Community-Based Older Persons

PubMed Central

Duke Han, S.; Boyle, Patricia A.; James, Bryan D.; Yu, Lei; Bennett, David A.

2015-01-01

Background/Objectives Financial and healthcare decision making are important for maintaining wellbeing and independence in old age. We tested the hypothesis that Mild Cognitive Impairment (MCI) is associated with poorer decision making in financial and healthcare matters. Design Community-based epidemiologic cohort study. Setting Communities throughout Northeastern Illinois. Participants Participants were 730 older nondemented persons from the Rush Memory and Aging Project. Measurements All participants underwent a detailed clinical evaluation and decision making assessment using a measure that closely approximates materials utilized in real world financial and healthcare settings. This allowed for measurement of total decision making, as well as financial and healthcare decision making. Regression models were used to examine whether the presence of MCI was associated with a lower level of decision making. In subsequent analyses, we explored the relation of specific cognitive systems (i.e., episodic memory, semantic memory, working memory, perceptual speed, and visuospatial ability) with decision making in those with MCI. Results Results showed that MCI was associated with lower decision making total scores as well as financial and healthcare scores, respectively, after accounting for the effects of age, education, and sex. The effect of MCI on total decision making was equivalent to the effect of more than 10 additional years of age. Additional models showed that when considering multiple cognitive systems, perceptual speed accounted for the most variance in decision making among participants with MCI. Conclusion Results suggest that persons with MCI may exhibit poorer financial and healthcare decision making in real world situations, and that perceptual speed may be an important contributor to poorer decision making among persons with MCI. PMID:25850350

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

PubMed

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

2013-04-15

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

The impact of social and organizational factors on workers' coping with musculoskeletal symptoms.

PubMed

Torp, S; Riise, T; Moen, B E

2001-07-01

Workers with musculoskeletal symptoms are often advised to cope with their symptoms by changing their working technique and by using lifting equipment. The main objective of this study was to test the hypothesis that negative social and organizational factors where people are employed may prevent workers from implementing these coping strategies. A total of 1,567 automobile garage workers (72%) returned a questionnaire concerning coping with musculoskeletal symptoms and social and organizational factors. When job demands, decision authority, social support, and management support related to health, environment, and safety (HES) were used as predictor variables in a multiple regression model, coping as the outcome variable was correlated with decision authority, social support, and HES-related management support (standardized beta=.079,.12, and.13, respectively). When an index for health-related support and control was added to the model, it correlated with coping (standardized beta=.36), whereas the other relationships disappeared. Decision authority and social support entail health-related support and control that, in turn, influences coping.

Neuroeconomics: A bridge for translational research

PubMed Central

Sharp, Carla; Monterosso, John; Montague, Read

2014-01-01

Neuroeconomic methods combine behavioral economic experiments to parameterize aspects of reward-related decision-making with neuroimaging techniques to record corresponding brain activity. In this introductory paper to the current special issue, we propose that neuroeconomics is a potential bridge for translational research in psychiatry for several reasons. First, neuroeconomics-derived theoretical predictions about optimal adaptation in a changing environment provide an objective metric to examine psychopathology. Second, neuroeconomics provides a ‘multi-level’ research approach that combines performance (behavioral) measures with intermediate measures between behavior and neurobiology (e.g, neuroimaging) and uses a common metaphor to describe decision-making across multiple levels of explanation. As such, ecologically valid behavioral paradigms closely mirror the physical mechanisms of reward processing. Third, neuroeconomics provides a platform for investigators from neuroscience, economics, psychiatry and social and clinical psychology to develop a common language for studying reward-related decision making in psychiatric disorders. Therefore, neuroeconomics can provide promising candidate endophenotypes that may help clarify the basis of high heritability associated with psychiatric disorders and that may, in turn, inform treatment. PMID:22727459

Color object detection using spatial-color joint probability functions.

PubMed

Luo, Jiebo; Crandall, David

2006-06-01

Object detection in unconstrained images is an important image understanding problem with many potential applications. There has been little success in creating a single algorithm that can detect arbitrary objects in unconstrained images; instead, algorithms typically must be customized for each specific object. Consequently, it typically requires a large number of exemplars (for rigid objects) or a large amount of human intuition (for nonrigid objects) to develop a robust algorithm. We present a robust algorithm designed to detect a class of compound color objects given a single model image. A compound color object is defined as having a set of multiple, particular colors arranged spatially in a particular way, including flags, logos, cartoon characters, people in uniforms, etc. Our approach is based on a particular type of spatial-color joint probability function called the color edge co-occurrence histogram. In addition, our algorithm employs perceptual color naming to handle color variation, and prescreening to limit the search scope (i.e., size and location) for the object. Experimental results demonstrated that the proposed algorithm is insensitive to object rotation, scaling, partial occlusion, and folding, outperforming a closely related algorithm based on color co-occurrence histograms by a decisive margin.

Designing and evaluating an interprofessional shared decision-making and goal-setting decision aid for patients with diabetes in clinical care - systematic decision aid development and study protocol

PubMed Central

2014-01-01

Background Care of patients with diabetes often occurs in the context of other chronic illness. Competing disease priorities and competing patient-physician priorities present challenges in the provision of care for the complex patient. Guideline implementation interventions to date do not acknowledge these intricacies of clinical practice. As a result, patients and providers are left overwhelmed and paralyzed by the sheer volume of recommendations and tasks. An individualized approach to the patient with diabetes and multiple comorbid conditions using shared decision-making (SDM) and goal setting has been advocated as a patient-centred approach that may facilitate prioritization of treatment options. Furthermore, incorporating interprofessional integration into practice may overcome barriers to implementation. However, these strategies have not been taken up extensively in clinical practice. Objectives To systematically develop and test an interprofessional SDM and goal-setting toolkit for patients with diabetes and other chronic diseases, following the Knowledge to Action framework. Methods 1. Feasibility study: Individual interviews with primary care physicians, nurses, dietitians, pharmacists, and patients with diabetes will be conducted, exploring their experiences with shared decision-making and priority-setting, including facilitators and barriers, the relevance of a decision aid and toolkit for priority-setting, and how best to integrate it into practice. 2. Toolkit development: Based on this data, an evidence-based multi-component SDM toolkit will be developed. The toolkit will be reviewed by content experts (primary care, endocrinology, geriatricians, nurses, dietitians, pharmacists, patients) for accuracy and comprehensiveness. 3. Heuristic evaluation: A human factors engineer will review the toolkit and identify, list and categorize usability issues by severity. 4. Usability testing: This will be done using cognitive task analysis. 5. Iterative refinement: Throughout the development process, the toolkit will be refined through several iterative cycles of feedback and redesign. Discussion Interprofessional shared decision-making regarding priority-setting with the use of a decision aid toolkit may help prioritize care of individuals with multiple comorbid conditions. Adhering to principles of user-centered design, we will develop and refine a toolkit to assess the feasibility of this approach. PMID:24450385

The Role of Cooperation and Information Exchange in Transnational River Basins: the Zambezi River case

NASA Astrophysics Data System (ADS)

Castelletti, A.; Giuliani, M.; Soncini-Sessa, R.

2012-12-01

The presence of multiple, institutionally independent but physically interconnected decision-makers is a distinctive features of many water resources systems, especially of transnational river basins. The adoption of a centralized approach to study the optimal operation of these systems, as mostly done in the water resources literature, is conceptually interesting to quantify the best achievable performance, but of little practical impact given the real political and institutional setting. Centralized management indeed assumes a cooperative attitude and full information exchange by the involved parties. However, when decision-makers belong to different countries or institutions, it is very likely that they act considering only their local objectives, producing global externalities that negatively impact on other objectives. In this work we adopt a Multi-Agent Systems framework, which naturally allows to represent a set of self-interested agents (decision-makers and/or stakeholders) acting in a distributed decision-making process. According to this agent-based approach, each agent represents a decision-maker, whose decisions are defined by an explicit optimization problem considering only the agent's local interests. In particular, this work assesses the role of information exchange and increasing level of cooperation among originally non-cooperative agents. The Zambezi River basin is used to illustrate the methodology: the four largest reservoirs in the basin (Ithezhithezhi, Kafue-Gorge, Kariba and Cahora Bassa) are mainly operated for maximizing the economic revenue from hydropower energy production with considerably negative effects on the aquatic ecosystem in the Zambezi delta due to the alteration of the natural flow regime. We comparatively analyse the ideal centralized solution and the current situation where all the decision-makers act independently and non-cooperatively. Indeed, although a new basin-level institution called Zambezi Watercourse Commission (ZAMCON) should be established in the next future, Zambia recently refused to sign and ratify the ZAMCON Protocol and the road toward a fully cooperative framework is still long. Results show that increasing levels of information exchange can help in mitigating the conflict generated by a non-cooperative setting as it allows the downstream agents, i.e. Mozambique country, to better adapt to the upstream management strategies. Furthermore, the role of information exchange depends on the considered objectives and it is particularly relevant for environmental interests.

Financial and Time Burdens for Medical Students Interviewing for Residency.

PubMed

Callaway, Paul; Melhado, Trisha; Walling, Anne; Groskurth, Jordan

2017-02-01

Interviewing for residency positions is increasingly stressful for students and challenging for programs. Little information is available about the costs and time invested by students in interviewing or about the key factors in decisions to accept interview offers. Our objective was to assess the time and financial costs of residency interviewing for an entire class at a regional campus and explore factors influencing student decisions to accept interviews. We used a 14-item survey administered electronically immediately following National Resident Matching Program results. The response rate was 75% (49 of 65 students). About half interviewed in primary care specialties. Thirty students (63%) applied to 20 or more programs, and 91% were offered multiple interviews out of state. Seventy percent limited interviews by time and cost. Other important factors included personal "fit," program reputation, and the quality of residents. About 50% of the students spent more than 20 days and $1,000-$5,000 interviewing; 29% reported spending over $5,000. Students used multiple funding sources, predominantly loans and savings. Primary care applicants applied to fewer out-of-state programs, reported fewer interview days and lower expenses, but received more financial support from programs. Students invested considerable time and resources in interviewing, and these factors significantly influenced their decisions about accepting interviews. The other major factors in interview decisions concerned personal comfort with the program, especially the residents. The costs and time reported in this study could be greater than other schools due to the regional campus location or lower due to the high proportion of students interviewing in primary care.

A method of decision analysis quantifying the effects of age and comorbidities on the probability of deriving significant benefit from medical treatments

PubMed Central

Bean, Nigel G.; Ruberu, Ravi P.

2017-01-01

Background The external validity, or generalizability, of trials and guidelines has been considered poor in the context of multiple morbidity. How multiple morbidity might affect the magnitude of benefit of a given treatment, and thereby external validity, has had little study. Objective To provide a method of decision analysis to quantify the effects of age and comorbidity on the probability of deriving a given magnitude of treatment benefit. Design We developed a method to calculate probabilistically the effect of all of a patient’s comorbidities on their underlying utility, or well-being, at a future time point. From this, we derived a distribution of possible magnitudes of treatment benefit at that future time point. We then expressed this distribution as the probability of deriving at least a given magnitude of treatment benefit. To demonstrate the applicability of this method of decision analysis, we applied it to the treatment of hypercholesterolaemia in a geriatric population of 50 individuals. We highlighted the results of four of these individuals. Results This method of analysis provided individualized quantifications of the effect of age and comorbidity on the probability of treatment benefit. The average probability of deriving a benefit, of at least 50% of the magnitude of benefit available to an individual without comorbidity, was only 0.8%. Conclusion The effects of age and comorbidity on the probability of deriving significant treatment benefits can be quantified for any individual. Even without consideration of other factors affecting external validity, these effects may be sufficient to guide decision-making. PMID:29090189

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Object selection costs in visual working memory: A diffusion model analysis of the focus of attention.

PubMed

Sewell, David K; Lilburn, Simon D; Smith, Philip L

2016-11-01

A central question in working memory research concerns the degree to which information in working memory is accessible to other cognitive processes (e.g., decision-making). Theories assuming that the focus of attention can only store a single object at a time require the focus to orient to a target representation before further processing can occur. The need to orient the focus of attention implies that single-object accounts typically predict response time costs associated with object selection even when working memory is not full (i.e., memory load is less than 4 items). For other theories that assume storage of multiple items in the focus of attention, predictions depend on specific assumptions about the way resources are allocated among items held in the focus, and how this affects the time course of retrieval of items from the focus. These broad theoretical accounts have been difficult to distinguish because conventional analyses fail to separate components of empirical response times related to decision-making from components related to selection and retrieval processes associated with accessing information in working memory. To better distinguish these response time components from one another, we analyze data from a probed visual working memory task using extensions of the diffusion decision model. Analysis of model parameters revealed that increases in memory load resulted in (a) reductions in the quality of the underlying stimulus representations in a manner consistent with a sample size model of visual working memory capacity and (b) systematic increases in the time needed to selectively access a probed representation in memory. The results are consistent with single-object theories of the focus of attention. The results are also consistent with a subset of theories that assume a multiobject focus of attention in which resource allocation diminishes both the quality and accessibility of the underlying representations. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Fuzzy Robust Optimization Model for Waste Allocation Planning Under Uncertainty

PubMed Central

Xu, Ye; Huang, Guohe; Xu, Ling

2014-01-01

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

Combining Interactive Infrastructure Modeling and Evolutionary Algorithm Optimization for Sustainable Water Resources Design

NASA Astrophysics Data System (ADS)

Smith, R.; Kasprzyk, J. R.; Zagona, E. A.

2013-12-01

Population growth and climate change, combined with difficulties in building new infrastructure, motivate portfolio-based solutions to ensuring sufficient water supply. Powerful simulation models with graphical user interfaces (GUI) are often used to evaluate infrastructure portfolios; these GUI based models require manual modification of the system parameters, such as reservoir operation rules, water transfer schemes, or system capacities. Multiobjective evolutionary algorithm (MOEA) based optimization can be employed to balance multiple objectives and automatically suggest designs for infrastructure systems, but MOEA based decision support typically uses a fixed problem formulation (i.e., a single set of objectives, decisions, and constraints). This presentation suggests a dynamic framework for linking GUI-based infrastructure models with MOEA search. The framework begins with an initial formulation which is solved using a MOEA. Then, stakeholders can interact with candidate solutions, viewing their properties in the GUI model. This is followed by changes in the formulation which represent users' evolving understanding of exigent system properties. Our case study is built using RiverWare, an object-oriented, data-centered model that facilitates the representation of a diverse array of water resources systems. Results suggest that assumptions within the initial MOEA search are violated after investigating tradeoffs and reveal how formulations should be modified to better capture stakeholders' preferences.

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

PubMed

Xu, Ye; Huang, Guohe; Xu, Ling

2014-10-01

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

A decision-analytic approach to predict state regulation of hydraulic fracturing.

PubMed

Linkov, Igor; Trump, Benjamin; Jin, David; Mazurczak, Marcin; Schreurs, Miranda

2014-01-01

The development of horizontal drilling and hydraulic fracturing methods has dramatically increased the potential for the extraction of previously unrecoverable natural gas. Nonetheless, the potential risks and hazards associated with such technologies are not without controversy and are compounded by frequently changing information and an uncertain landscape of international politics and laws. Where each nation has its own energy policies and laws, predicting how a state with natural gas reserves that require hydraulic fracturing will regulate the industry is of paramount importance for potential developers and extractors. We present a method for predicting hydraulic fracturing decisions using multiple-criteria decision analysis. The case study evaluates the decisions of five hypothetical countries with differing political, social, environmental, and economic priorities, choosing among four policy alternatives: open hydraulic fracturing, limited hydraulic fracturing, completely banned hydraulic fracturing, and a cap and trade program. The result is a model that identifies the preferred policy alternative for each archetypal country and demonstrates the sensitivity the decision to particular metrics. Armed with such information, observers can predict each country's likely decisions related to natural gas exploration as more data become available or political situations change. Decision analysis provides a method to manage uncertainty and address forecasting concerns where rich and objective data may be lacking. For the case of hydraulic fracturing, the various political pressures and extreme uncertainty regarding the technology's risks and benefits serve as a prime platform to demonstrate how decision analysis can be used to predict future behaviors.

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

PubMed

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

2018-01-19

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

A Systematic Design Method for Two-Variable Numeric Function Generators Using Multiple-Valued Decision Diagrams

DTIC Science & Technology

2010-08-01

R.K. Brayton , and A.L. Sangiovanni-Vincentelli, “Multi-valued decision diagrams: Theory and applications,” Multiple-Valued Logic: An International...S.N. Yanushkevich, D.M. Miller, V.P. Shmerko, and R.S. Stankovic, Decision Diagram Techniques for Micro- and Nanoelectronic De- sign, CRC Press, Taylor

Prognosis of the individual course of disease: the elements of time, heterogeneity and precision.

PubMed

Daumer, Martin; Neuhaus, Anneke; Herbert, Joseph; Ebers, George

2009-12-01

There is no gold standard in monitoring disease activity for clinical trials in multiple sclerosis. Various outcome measures, including relapses, disability and magnetic resonance imaging (MRI) measures have been used to demonstrate the efficacy of the different available therapies for multiple sclerosis. Recently, the potential limitations of these measures have received increasing attention, and these have stimulated research into more appropriate and sensitive outcome measures for clinical trials. For example, it has been shown that widely-used MRI measures add little, if any, independent information to that provided by more clinically relevant measures such as relapses and disability. Similarly, the Expanded Disability status Scale (EDSS), which is the most widely-used measure of disability related to multiple sclerosis, is insufficiently sensitive to detect robust changes in disability over the timeframes usually used in clinical trials. An alternative to the EDSS is the Multiple Sclerosis Severity Score (MSSS), a severity scale which relates clinical disability to disease duration. The MSSS was originally developed from a database of nearly ten thousand patients from eleven European countries and Australia and has since been reproduced in an independent dataset of 1134 patients from the placebo arms of randomised clinical trials. Based on the MSSS score, disease severity can be defined, which shows stability over time and may provide evidence-based decision support for patient management. Another alternative to measure disability is the objective quantification of physical activity. There is evidence that recent developments in pervasive computing using tiny accelerometers may have the potential to increase the reliability and precision of motor assessment, especially in the mid-range of the EDSS. The outcome measures discussed have potential use as online tools for evidence-based decision support which are increasingly being used in medical research and clinical decision-making. Copyright 2009 Elsevier Ltd. All rights reserved.

Changing Times, Complex Decisions: Presidential Values and Decision Making

ERIC Educational Resources Information Center

Hornak, Anne M.; Garza Mitchell, Regina L.

2016-01-01

Objective: The objective of this article is to delve more deeply into the thought processes of the key decision makers at community colleges and understand how they make decisions. Specifically, this article focuses on the role of the community college president's personal values in decision making. Method: We conducted interviews with 13…

[Improvement and process optimization transfusion in Morocco: proposal of a new organization].

PubMed

Bennis, I; Janah, S; Benajiba, M

2013-03-01

Propose a new organization for the Moroccan blood transfusion system. Through an analysis of several aspects of the current organization, both qualitatively and quantitatively (Statistics 2011), it was found that several failures of the current system prevent them from achieving it's objectives and ensuring its responsibilities. Using multiple-criteria decision analysis (ELECTRE III), a new organization based on resources pooling is proposed. This new organization concerns the status of the National Blood Transfusion Center, donor management, the geographical location of the various regional centers, logistics, inventory management and the information system. Within the new organization proposed, the number of regional Centers for blood transfusion is reduced from 16 to 7 in accordance with the existing constraints, while redefining the roles of each site. The aspects of inventory management, the information system, increasing the number of donors, the policy communication and marketing and cycle of blood collection and distribution are also redefined. This proposed new organization will provide decision makers with the necessary assistance for decision making, whit respect to the improvement of the entire system Moroccan blood transfusion system. And so help achieving the desired objectives on ensuring blood availability and it' maximum safety. The simulation of this proposal should confirm the choice that was made. Further analysis of complementary aspects such as the financial aspect or human resources, would moreover contribute to refining this proposal. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Participation in Decision Making as a Property of Complex Adaptive Systems: Developing and Testing a Measure

PubMed Central

Anderson, Ruth A.; Hsieh, Pi-Ching; Su, Hui Fang; Landerman, Lawrence R.; McDaniel, Reuben R.

2013-01-01

Objectives. To (1) describe participation in decision-making as a systems-level property of complex adaptive systems and (2) present empirical evidence of reliability and validity of a corresponding measure. Method. Study 1 was a mail survey of a single respondent (administrators or directors of nursing) in each of 197 nursing homes. Study 2 was a field study using random, proportionally stratified sampling procedure that included 195 organizations with 3,968 respondents. Analysis. In Study 1, we analyzed the data to reduce the number of scale items and establish initial reliability and validity. In Study 2, we strengthened the psychometric test using a large sample. Results. Results demonstrated validity and reliability of the participation in decision-making instrument (PDMI) while measuring participation of workers in two distinct job categories (RNs and CNAs). We established reliability at the organizational level aggregated items scores. We established validity of the multidimensional properties using convergent and discriminant validity and confirmatory factor analysis. Conclusions. Participation in decision making, when modeled as a systems-level property of organization, has multiple dimensions and is more complex than is being traditionally measured. Managers can use this model to form decision teams that maximize the depth and breadth of expertise needed and to foster connection among them. PMID:24349771

Forest management under uncertainty for multiple bird population objectives

USGS Publications Warehouse

Moore, C.T.; Plummer, W.T.; Conroy, M.J.; Ralph, C. John; Rich, Terrell D.

2005-01-01

We advocate adaptive programs of decision making and monitoring for the management of forest birds when responses by populations to management, and particularly management trade-offs among populations, are uncertain. Models are necessary components of adaptive management. Under this approach, uncertainty about the behavior of a managed system is explicitly captured in a set of alternative models. The models generate testable predictions about the response of populations to management, and monitoring data provide the basis for assessing these predictions and informing future management decisions. To illustrate these principles, we examine forest management at the Piedmont National Wildlife Refuge, where management attention is focused on the recovery of the Red-cockaded Woodpecker (Picoides borealis) population. However, managers are also sensitive to the habitat needs of many non-target organisms, including Wood Thrushes (Hylocichla mustelina) and other forest interior Neotropical migratory birds. By simulating several management policies on a set of-alternative forest and bird models, we found a decision policy that maximized a composite response by woodpeckers and Wood Thrushes despite our complete uncertainty regarding system behavior. Furthermore, we used monitoring data to update our measure of belief in each alternative model following one cycle of forest management. This reduction of uncertainty translates into a reallocation of model influence on the choice of optimal decision action at the next decision opportunity.

Participation in decision making as a property of complex adaptive systems: developing and testing a measure.

PubMed

Anderson, Ruth A; Plowman, Donde; Corazzini, Kirsten; Hsieh, Pi-Ching; Su, Hui Fang; Landerman, Lawrence R; McDaniel, Reuben R

2013-01-01

Objectives. To (1) describe participation in decision-making as a systems-level property of complex adaptive systems and (2) present empirical evidence of reliability and validity of a corresponding measure. Method. Study 1 was a mail survey of a single respondent (administrators or directors of nursing) in each of 197 nursing homes. Study 2 was a field study using random, proportionally stratified sampling procedure that included 195 organizations with 3,968 respondents. Analysis. In Study 1, we analyzed the data to reduce the number of scale items and establish initial reliability and validity. In Study 2, we strengthened the psychometric test using a large sample. Results. Results demonstrated validity and reliability of the participation in decision-making instrument (PDMI) while measuring participation of workers in two distinct job categories (RNs and CNAs). We established reliability at the organizational level aggregated items scores. We established validity of the multidimensional properties using convergent and discriminant validity and confirmatory factor analysis. Conclusions. Participation in decision making, when modeled as a systems-level property of organization, has multiple dimensions and is more complex than is being traditionally measured. Managers can use this model to form decision teams that maximize the depth and breadth of expertise needed and to foster connection among them.

78 FR 4366 - Appeal Proceedings Before the Commission

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-22

... Commission's proposals to remove certificates of self-regulation, the Chair's decisions to approve or object... proposals to remove certificates of self- regulation, the Chair's decisions to approve or object to a tribal...'s proposal to remove a certificate of self-regulation, the Chair's decision to approve or object to...

Space assets, technology and services in support of energy policy

NASA Astrophysics Data System (ADS)

Vasko, C. A.; Adriaensen, M.; Bretel, A.; Duvaux-Bechon, I.; Giannopapa, C. G.

2017-09-01

Space can be used as a tool by decision and policy makers in developing, implementing and monitoring various policy areas including resource management, environment, transport, security and energy. This paper focuses on the role of space for the energy policy. Firstly, the paper summarizes the European Union's (EU) main objectives in energy policy enclosed in the Energy Strategy 2020-2030-2050 and demonstrates how space assets can contribute to achieving those objectives. Secondly, the paper addresses how the European Space Agency (ESA) has established multiple initiatives and programs that directly finance the development of space assets, technology and applications that deliver services in support of the EU energy policy and sector. These efforts should be continued and strengthened in order to overcome identified technological challenges. The use of space assets, technology and applications, can help achieve the energy policy objectives for the next decades.

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

NASA Astrophysics Data System (ADS)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

Expert reasoning within an object-oriented framework

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

Bohn, S.J.; Pennock, K.A.

1991-10-01

A large number of contaminated waste sites across the United States await site remediation efforts. These sites can be physically complex, composed of multiple, possibly interacting, contaminants distributed throughout one or more media. The Remedial Action Assessment System (RAAS) is being designed and developed to support decisions concerning the selection of remediation alternatives. The goal of this system is to broaden the consideration of remediation alternatives, while reducing the time and cost of making these considerations. The Remedial Action Assessment System was designed and constructed using object-oriented techniques. It is a hybrid system which uses a combination of quantitative andmore » qualitative reasoning to consider and suggest remediation alternatives. the reasoning process that drives this application is centered around an object-oriented organization of remediation technology information. This paper briefly describes the waste remediation problem and then discusses the information structure and organization RAAS utilizes to address it. 4 refs., 4 figs.« less

Accurate metacognition for visual sensory memory representations.

PubMed

Vandenbroucke, Annelinde R E; Sligte, Ilja G; Barrett, Adam B; Seth, Anil K; Fahrenfort, Johannes J; Lamme, Victor A F

2014-04-01

The capacity to attend to multiple objects in the visual field is limited. However, introspectively, people feel that they see the whole visual world at once. Some scholars suggest that this introspective feeling is based on short-lived sensory memory representations, whereas others argue that the feeling of seeing more than can be attended to is illusory. Here, we investigated this phenomenon by combining objective memory performance with subjective confidence ratings during a change-detection task. This allowed us to compute a measure of metacognition--the degree of knowledge that subjects have about the correctness of their decisions--for different stages of memory. We show that subjects store more objects in sensory memory than they can attend to but, at the same time, have similar metacognition for sensory memory and working memory representations. This suggests that these subjective impressions are not an illusion but accurate reflections of the richness of visual perception.

Emergency Physicians’ Attitudes and Preferences Regarding Computed Tomography, Radiation Exposure, and Imaging Decision Support

PubMed Central

Griffey, Richard T.; Jeffe, Donna B.; Bailey, Thomas

2014-01-01

Objectives Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians’ (EPs’) preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. Methods A 42-item, Web-based survey of EPs was developed and used to measure EPs’ attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach’s alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Results Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient’s cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients’ cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients’ cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs’ greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP’s decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Conclusions Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. PMID:25125272

Optimal use of human and machine resources for Space Station assembly operations

NASA Technical Reports Server (NTRS)

Parrish, Joseph C.

1988-01-01

This paper investigates the issues involved in determining the best mix of human and machine resources for assembly of the Space Station. It presents the current Station assembly sequence, along with descriptions of the available assembly resources. A number of methodologies for optimizing the human/machine tradeoff problem have been developed, but the Space Station assembly offers some unique issues that have not yet been addressed. These include a strong constraint on available EVA time for early flights and a phased deployment of assembly resources over time. A methodology for incorporating the previously developed decision methods to the special case of the Space Station is presented. This methodology emphasizes an application of multiple qualitative and quantitative techniques, including simulation and decision analysis, for producing an objective, robust solution to the tradeoff problem.

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

PubMed Central

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

2012-01-01

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

Physician Confidence in Dental Trauma Treatment and the Introduction of a Dental Trauma Decision-Making Pathway for the Pediatric Emergency Department.

PubMed

Cully, Matthew; Cully, Jennifer; Nietert, Paul J; Titus, M Olivia

2018-04-24

The objectives of this study were to (1) survey and report the awareness and confidence of pediatric emergency medicine physicians in the management of dental trauma and (2) determine the prevalence of dental trauma decision-making pathway utilization in the pediatric emergency department. A survey was distributed through e-mail to the pediatric emergency medicine discussion list via Brown University LISTSERV. The survey study included 10 questions and was multiple-choice. The survey contained questions about physician confidence and their use of a dental trauma decision-making pathway. A total of 285 individuals responded to the survey. Somewhat confident was the most common response (61%) followed by not confident (20%) and confident (19%) by respondents in treating dental trauma. Forty-one percent of respondents felt comfortable, 39% somewhat comfortable, 19% not comfortable, and 1% not sure in replanting an avulsed tooth. Only 6% of respondents reported that their pediatric emergency department always or sometimes uses a dental trauma decision-making pathway, whereas 78% of pediatric emergency departments do not. We believe that the adoption of a decision-making pathway will provide timely management, improve emergency physician comfort, and enhance outcomes for pediatric patients presenting with a dental trauma. A future multicenter review will aim to evaluate these goals based on the utilization of our dental trauma decision-making pathway.

Implications of Preference and Problem Formulation on the Operating Policies of Complex Multi-Reservoir Systems

NASA Astrophysics Data System (ADS)

Quinn, J.; Reed, P. M.; Giuliani, M.; Castelletti, A.

2016-12-01

Optimizing the operations of multi-reservoir systems poses several challenges: 1) the high dimension of the problem's states and controls, 2) the need to balance conflicting multi-sector objectives, and 3) understanding how uncertainties impact system performance. These difficulties motivated the development of the Evolutionary Multi-Objective Direct Policy Search (EMODPS) framework, in which multi-reservoir operating policies are parameterized in a given family of functions and then optimized for multiple objectives through simulation over a set of stochastic inputs. However, properly framing these objectives remains a severe challenge and a neglected source of uncertainty. Here, we use EMODPS to optimize operating policies for a 4-reservoir system in the Red River Basin in Vietnam, exploring the consequences of optimizing to different sets of objectives related to 1) hydropower production, 2) meeting multi-sector water demands, and 3) providing flood protection to the capital city of Hanoi. We show how coordinated operation of the reservoirs can differ markedly depending on how decision makers weigh these concerns. Moreover, we illustrate how formulation choices that emphasize the mean, tail, or variability of performance across objective combinations must be evaluated carefully. Our results show that these choices can significantly improve attainable system performance, or yield severe unintended consequences. Finally, we show that satisfactory validation of the operating policies on a set of out-of-sample stochastic inputs depends as much or more on the formulation of the objectives as on effective optimization of the policies. These observations highlight the importance of carefully considering how we abstract stakeholders' objectives and of iteratively optimizing and visualizing multiple problem formulation hypotheses to ensure that we capture the most important tradeoffs that emerge from different stakeholder preferences.

Tailoring Software for Multiple Processor Systems

DTIC Science & Technology

1982-10-01

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

WEB-GIS Decision Support System for CO2 storage

NASA Astrophysics Data System (ADS)

Gaitanaru, Dragos; Leonard, Anghel; Radu Gogu, Constantin; Le Guen, Yvi; Scradeanu, Daniel; Pagnejer, Mihaela

2013-04-01

Environmental decision support systems (DSS) paradigm evolves and changes as more knowledge and technology become available to the environmental community. Geographic Information Systems (GIS) can be used to extract, assess and disseminate some types of information, which are otherwise difficult to access by traditional methods. In the same time, with the help of the Internet and accompanying tools, creating and publishing online interactive maps has become easier and rich with options. The Decision Support System (MDSS) developed for the MUSTANG (A MUltiple Space and Time scale Approach for the quaNtification of deep saline formations for CO2 storaGe) project is a user friendly web based application that uses the GIS capabilities. MDSS can be exploited by the experts for CO2 injection and storage in deep saline aquifers. The main objective of the MDSS is to help the experts to take decisions based large structured types of data and information. In order to achieve this objective the MDSS has a geospatial objected-orientated database structure for a wide variety of data and information. The entire application is based on several principles leading to a series of capabilities and specific characteristics: (i) Open-Source - the entire platform (MDSS) is based on open-source technologies - (1) database engine, (2) application server, (3) geospatial server, (4) user interfaces, (5) add-ons, etc. (ii) Multiple database connections - MDSS is capable to connect to different databases that are located on different server machines. (iii)Desktop user experience - MDSS architecture and design follows the structure of a desktop software. (iv)Communication - the server side and the desktop are bound together by series functions that allows the user to upload, use, modify and download data within the application. The architecture of the system involves one database and a modular application composed by: (1) a visualization module, (2) an analysis module, (3) a guidelines module, and (4) a risk assessment module. The Database component is build by using the PostgreSQL and PostGIS open source technology. The visualization module allows the user to view data of CO2 injection sites in different ways: (1) geospatial visualization, (2) table view, (3) 3D visualization. The analysis module will allow the user to perform certain analysis like Injectivity, Containment and Capacity analysis. The Risk Assessment module focus on the site risk matrix approach. The Guidelines module contains the methodologies of CO2 injection and storage into deep saline aquifers guidelines.

A Decision Support System for Solving Multiple Criteria Optimization Problems

ERIC Educational Resources Information Center

Filatovas, Ernestas; Kurasova, Olga

2011-01-01

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

The multiple resource inventory decision-making process

Treesearch

Victor A. Rudis

1993-01-01

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

Beyond scene gist: Objects guide search more than scene background.

PubMed

Koehler, Kathryn; Eckstein, Miguel P

2017-06-01

Although the facilitation of visual search by contextual information is well established, there is little understanding of the independent contributions of different types of contextual cues in scenes. Here we manipulated 3 types of contextual information: object co-occurrence, multiple object configurations, and background category. We isolated the benefits of each contextual cue to target detectability, its impact on decision bias, confidence, and the guidance of eye movements. We find that object-based information guides eye movements and facilitates perceptual judgments more than scene background. The degree of guidance and facilitation of each contextual cue can be related to its inherent informativeness about the target spatial location as measured by human explicit judgments about likely target locations. Our results improve the understanding of the contributions of distinct contextual scene components to search and suggest that the brain's utilization of cues to guide eye movements is linked to the cue's informativeness about the target's location. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods.

PubMed

Amini, Payam; Maroufizadeh, Saman; Samani, Reza Omani; Hamidi, Omid; Sepidarkish, Mahdi

2017-06-01

Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods. This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6-21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used. The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB ( p < 0.05). Identifying and training mothers at risk as well as improving prenatal care may reduce the PTB rate. We also recommend that statisticians utilize the logistic regression model for the classification of risk groups for PTB.

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Data to decisions.

PubMed

White, B J; Amrine, D E; Larson, R L

2018-04-14

Big data are frequently used in many facets of business and agronomy to enhance knowledge needed to improve operational decisions. Livestock operations collect data of sufficient quantity to perform predictive analytics. Predictive analytics can be defined as a methodology and suite of data evaluation techniques to generate a prediction for specific target outcomes. The objective of this manuscript is to describe the process of using big data and the predictive analytic framework to create tools to drive decisions in livestock production, health, and welfare. The predictive analytic process involves selecting a target variable, managing the data, partitioning the data, then creating algorithms, refining algorithms, and finally comparing accuracy of the created classifiers. The partitioning of the datasets allows model building and refining to occur prior to testing the predictive accuracy of the model with naive data to evaluate overall accuracy. Many different classification algorithms are available for predictive use and testing multiple algorithms can lead to optimal results. Application of a systematic process for predictive analytics using data that is currently collected or that could be collected on livestock operations will facilitate precision animal management through enhanced livestock operational decisions.

The First Flight Decision for New Human Spacecraft Vehicles - A General Approach

NASA Technical Reports Server (NTRS)

Schaible, Dawn M.; Sumrall, John Phillip

2011-01-01

Determining when it is safe to fly a crew on a launch vehicle/spacecraft for the first time, especially when the test flight is a part of the overall system certification process, has long been a challenge for program decision makers. The decision on first flight is ultimately the judgment of the program and agency management in conjunction with the design and operations team. To aid in this decision process, a NASA team undertook the task to develop a generic framework for evaluating whether any given program or commercial provider has sufficiently complete and balanced plans in place to allow crewmembers to safely fly on human spaceflight systems for the first time. It was the team s goal to establish a generic framework that could easily be applied to any new system, although the system design and intended mission would require specific assessment. Historical data shows that there are multiple approaches that have been successful in first flight with crew. These approaches have always been tailored to the specific system design, mission objectives, and launch environment. Because specific approaches may vary significantly between different system designs and situations, prescriptive instructions or thorough checklists cannot be provided ahead of time. There are, however, certain general approaches that should be applied in thinking through the decision for first flight. This paper addresses some of the most important factors to consider when developing a new system or evaluating an existing system for whether or not it is safe to fly humans to/from space. In the simplest terms, it is time to fly crew for the first time when it is safe to do so and the benefit of the crewed flight is greater than the residual risk. This is rarely a straight-forward decision. The paper describes the need for experience, sound judgment, close involvement of the technical and management teams, and established decision processes. In addition, the underlying level of confidence the manager has in making the decision will also be discussed. By applying the outlined thought processes and approaches to a specific design, test program and mission objectives, a project team will be better able to focus the debate and discussion on critical areas for consideration and added scrutiny -- allowing decision makers to adequately address the first crewed flight decision.

The Modular Modeling System (MMS): A modeling framework for water- and environmental-resources management

USGS Publications Warehouse

Leavesley, G.H.; Markstrom, S.L.; Viger, R.J.

2004-01-01

The interdisciplinary nature and increasing complexity of water- and environmental-resource problems require the use of modeling approaches that can incorporate knowledge from a broad range of scientific disciplines. The large number of distributed hydrological and ecosystem models currently available are composed of a variety of different conceptualizations of the associated processes they simulate. Assessment of the capabilities of these distributed models requires evaluation of the conceptualizations of the individual processes, and the identification of which conceptualizations are most appropriate for various combinations of criteria, such as problem objectives, data constraints, and spatial and temporal scales of application. With this knowledge, "optimal" models for specific sets of criteria can be created and applied. The U.S. Geological Survey (USGS) Modular Modeling System (MMS) is an integrated system of computer software that has been developed to provide these model development and application capabilities. MMS supports the integration of models and tools at a variety of levels of modular design. These include individual process models, tightly coupled models, loosely coupled models, and fully-integrated decision support systems. A variety of visualization and statistical tools are also provided. MMS has been coupled with the Bureau of Reclamation (BOR) object-oriented reservoir and river-system modeling framework, RiverWare, under a joint USGS-BOR program called the Watershed and River System Management Program. MMS and RiverWare are linked using a shared relational database. The resulting database-centered decision support system provides tools for evaluating and applying optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. Management issues being addressed include efficiency of water-resources management, environmental concerns such as meeting flow needs for endangered species, and optimizing operations within the constraints of multiple objectives such as power generation, irrigation, and water conservation. This decision support system approach is being developed, tested, and implemented in the Gunni-son, Yakima, San Juan, Rio Grande, and Truckee River basins of the western United States. Copyright ASCE 2004.

A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making.

PubMed

van der Lee, J H; Svrcek, W Y; Young, B R

2008-01-01

Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.

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

DTIC Science & Technology

2013-12-01

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

Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment.

PubMed

Onüt, Semih; Soner, Selin

2008-01-01

Site selection is an important issue in waste management. Selection of the appropriate solid waste site requires consideration of multiple alternative solutions and evaluation criteria because of system complexity. Evaluation procedures involve several objectives, and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision-making (MCDM) has been found to be a useful approach to solve this kind of problem. Different MCDM models have been applied to solve this problem. But most of them are basically mathematical and ignore qualitative and often subjective considerations. It is easier for a decision-maker to describe a value for an alternative by using linguistic terms. In the fuzzy-based method, the rating of each alternative is described using linguistic terms, which can also be expressed as triangular fuzzy numbers. Furthermore, there have not been any studies focused on the site selection in waste management using both fuzzy TOPSIS (technique for order preference by similarity to ideal solution) and AHP (analytical hierarchy process) techniques. In this paper, a fuzzy TOPSIS based methodology is applied to solve the solid waste transshipment site selection problem in Istanbul, Turkey. The criteria weights are calculated by using the AHP.

Enhanced quality and quantity of retrieval of Critically Appraised Topics using the CAT Crawler.

PubMed

Dong, P; Mondry, A

2004-03-01

As healthcare moves towards the implementation of Evidence-Based Medicine (EBM), Critically Appraised Topics (CATs) become useful in helping physicians to make clinical decisions. A number of academic and healthcare organizations have set up web-based CAT libraries. The primary objective of the presented work is to provide a one-stop search and download site that allows access to multiple CAT libraries. A web-based application, namely the CAT Crawler, was developed to serve physicians with an adequate access to available appraised topics on the Internet. Important information is extracted automatically and regularly from CAT websites, and consolidated by checking the uniqueness and availability. The principle of meta-search is incorporated into the implementation of the search engine, which finds relevant topics following keyword input. The retrieved result directs the physician to the original resource page. A full-text article of a particular topic can be converted into a proper format for downloading to Personal Digital Assistant (PDA) devices. In summary, the application provides physicians with a common interface to retrieve relevant CATs on particular clinical topics from multiple resources, and thus speeds up the decision making process.

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

Onuet, Semih; Soner, Selin

Site selection is an important issue in waste management. Selection of the appropriate solid waste site requires consideration of multiple alternative solutions and evaluation criteria because of system complexity. Evaluation procedures involve several objectives, and it is often necessary to compromise among possibly conflicting tangible and intangible factors. For these reasons, multiple criteria decision-making (MCDM) has been found to be a useful approach to solve this kind of problem. Different MCDM models have been applied to solve this problem. But most of them are basically mathematical and ignore qualitative and often subjective considerations. It is easier for a decision-maker tomore » describe a value for an alternative by using linguistic terms. In the fuzzy-based method, the rating of each alternative is described using linguistic terms, which can also be expressed as triangular fuzzy numbers. Furthermore, there have not been any studies focused on the site selection in waste management using both fuzzy TOPSIS (technique for order preference by similarity to ideal solution) and AHP (analytical hierarchy process) techniques. In this paper, a fuzzy TOPSIS based methodology is applied to solve the solid waste transshipment site selection problem in Istanbul, Turkey. The criteria weights are calculated by using the AHP.« less

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.

PubMed

Huang, Dongmei; Xu, Chenyixuan; Zhao, Danfeng; Song, Wei; He, Qi

2017-09-21

Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

Risk approximation in decision making: approximative numeric abilities predict advantageous decisions under objective risk.

PubMed

Mueller, Silke M; Schiebener, Johannes; Delazer, Margarete; Brand, Matthias

2018-01-22

Many decision situations in everyday life involve mathematical considerations. In decisions under objective risk, i.e., when explicit numeric information is available, executive functions and abilities to handle exact numbers and ratios are predictors of objectively advantageous choices. Although still debated, exact numeric abilities, e.g., normative calculation skills, are assumed to be related to approximate number processing skills. The current study investigates the effects of approximative numeric abilities on decision making under objective risk. Participants (N = 153) performed a paradigm measuring number-comparison, quantity-estimation, risk-estimation, and decision-making skills on the basis of rapid dot comparisons. Additionally, a risky decision-making task with exact numeric information was administered, as well as tasks measuring executive functions and exact numeric abilities, e.g., mental calculation and ratio processing skills, were conducted. Approximative numeric abilities significantly predicted advantageous decision making, even beyond the effects of executive functions and exact numeric skills. Especially being able to make accurate risk estimations seemed to contribute to superior choices. We recommend approximation skills and approximate number processing to be subject of future investigations on decision making under risk.

MULTIPLE SCALES FOR SUSTAINABLE RESULTS

EPA Science Inventory

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

Decision Making under Ambiguity and Objective Risk in Higher Age - A Review on Cognitive and Emotional Contributions.

PubMed

Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

2017-01-01

The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors - responsible for age-related differences in decision making - are additionally pointed out.

Decision Making under Ambiguity and Objective Risk in Higher Age – A Review on Cognitive and Emotional Contributions

PubMed Central

Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

2017-01-01

The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors – responsible for age-related differences in decision making – are additionally pointed out. PMID:29270145

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

ERIC Educational Resources Information Center

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

2013-01-01

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

A three-talk model for shared decision making: multistage consultation process

PubMed Central

Durand, Marie Anne; Song, Julia; Aarts, Johanna; Barr, Paul J; Berger, Zackary; Cochran, Nan; Frosch, Dominick; Galasiński, Dariusz; Gulbrandsen, Pål; Han, Paul K J; Härter, Martin; Kinnersley, Paul; Lloyd, Amy; Mishra, Manish; Perestelo-Perez, Lilisbeth; Scholl, Isabelle; Tomori, Kounosuke; Trevena, Lyndal; Witteman, Holly O; Van der Weijden, Trudy

2017-01-01

Objectives To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement. Design Multistage consultation process. Setting Key informant group, communities of interest, and survey of clinical specialties. Participants 19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties. Results After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on “team talk,” “option talk,” and “decision talk,” to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals. Conclusions The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences. PMID:29109079

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

PubMed

Laukkanen, Sanna; Kangas, Annika; Kangas, Jyrki

2002-02-01

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

Multimorbidity and Decision-Making Preferences Among Older Adults.

PubMed

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

2017-11-01

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

Perceptions of Shared Decision Making Among Patients with Spinal Cord Injuries/Disorders.

PubMed

Locatelli, Sara M; Etingen, Bella; Heinemann, Allen; Neumann, Holly DeMark; Miskovic, Ana; Chen, David; LaVela, Sherri L

2016-01-01

Background: Individuals with spinal cord injuries/disorders (SCI/D) are interested in, and benefit from, shared decision making (SDM). Objective: To explore SDM among individuals with SCI/D and how demographics and health and SCI/D characteristics are related to SDM. Method: Individuals with SCI/D who were at least 1 year post injury, resided in the Chicago metropolitan area, and received SCI care at a Veterans Affairs (VA; n = 124) or an SCI Model Systems facility ( n = 326) completed a mailed survey measuring demographics, health and SCI/D characteristics, physical and mental health status, and perceptions of care, including SDM, using the Combined Outcome Measure for Risk Communication and Treatment Decision-Making Effectiveness (COMRADE) that assesses decision-making effectiveness (effectiveness) and risk communication (communication). Bivariate analyses and multiple linear regression were used to identify variables associated with SDM. Results: Participants were mostly male (83%) and White (70%) and were an average age of 54 years ( SD = 14.3). Most had traumatic etiology, 44% paraplegia, and 49% complete injury. Veteran/civilian status and demographics were unrelated to scores. Bivariate analyses showed that individuals with tetraplegia had better effectiveness scores than those with paraplegia. Better effectiveness was correlated with better physical and mental health; better communication was correlated with better mental health. Multiple linear regressions showed that tetraplegia, better physical health, and better mental health were associated with better effectiveness, and better mental health was associated with better communication. Conclusion: SCI/D and health characteristics were the only variables associated with SDM. Interventions to increase engagement in SDM and provider attention to SDM may be beneficial, especially for individuals with paraplegia or in poorer physical and mental health.

Decision Support System For Management Of Low-Level Radioactive Waste Disposal At The Nevada Test Site

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

Shott, G.; Yucel, V.; Desotell, L.

2006-07-01

The long-term safety of U.S. Department of Energy (DOE) low-level radioactive disposal facilities is assessed by conducting a performance assessment -- a systematic analysis that compares estimated risks to the public and the environment with performance objectives contained in DOE Manual 435.1-1, Radioactive Waste Management Manual. Before site operations, facilities design features such as final inventory, waste form characteristics, and closure cover design may be uncertain. Site operators need a modeling tool that can be used throughout the operational life of the disposal site to guide decisions regarding the acceptance of problematic waste streams, new disposal cell design, environmental monitoringmore » program design, and final site closure. In response to these needs the National Nuclear Security Administration Nevada Site Office (NNSA/NSO) has developed a decision support system for the Area 5 Radioactive Waste Management Site in Frenchman Flat on the Nevada Test Site. The core of the system is a probabilistic inventory and performance assessment model implemented in the GoldSim{sup R} simulation platform. The modeling platform supports multiple graphic capabilities that allow clear documentation of the model data sources, conceptual model, mathematical implementation, and results. The combined models have the capability to estimate disposal site inventory, contaminant concentrations in environmental media, and radiological doses to members of the public engaged in various activities at multiple locations. The model allows rapid assessment and documentation of the consequences of waste management decisions using the most current site characterization information, radionuclide inventory, and conceptual model. The model is routinely used to provide annual updates of site performance, evaluate the consequences of disposal of new waste streams, develop waste concentration limits, optimize the design of new disposal cells, and assess the adequacy of environmental monitoring programs. (authors)« less

Multispecies genetic objectives in spatial conservation planning.

PubMed

Nielsen, Erica S; Beger, Maria; Henriques, Romina; Selkoe, Kimberly A; von der Heyden, Sophie

2017-08-01

Growing threats to biodiversity and global alteration of habitats and species distributions make it increasingly necessary to consider evolutionary patterns in conservation decision making. Yet, there is no clear-cut guidance on how genetic features can be incorporated into conservation-planning processes, despite multiple molecular markers and several genetic metrics for each marker type to choose from. Genetic patterns differ between species, but the potential tradeoffs among genetic objectives for multiple species in conservation planning are currently understudied. We compared spatial conservation prioritizations derived from 2 metrics of genetic diversity (nucleotide and haplotype diversity) and 2 metrics of genetic isolation (private haplotypes and local genetic differentiation) in mitochondrial DNA of 5 marine species. We compared outcomes of conservation plans based only on habitat representation with plans based on genetic data and habitat representation. Fewer priority areas were selected for conservation plans based solely on habitat representation than on plans that included habitat and genetic data. All 4 genetic metrics selected approximately similar conservation-priority areas, which is likely a result of prioritizing genetic patterns across a genetically diverse array of species. Largely, our results suggest that multispecies genetic conservation objectives are vital to creating protected-area networks that appropriately preserve community-level evolutionary patterns. © 2016 Society for Conservation Biology.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Dynamic information processing states revealed through neurocognitive models of object semantics

PubMed Central

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

Design of price incentives for adjunct policy goals in formula funding for hospitals and health services

PubMed Central

Duckett, Stephen J

2008-01-01

Background Hospital policy involves multiple objectives: efficiency of service delivery, pursuit of high quality care, promoting access. Funding policy based on hospital casemix has traditionally been considered to be only about promoting efficiency. Discussion Formula-based funding policy can be (and has been) used to pursue a range of policy objectives, not only efficiency. These are termed 'adjunct' goals. Strategies to incorporate adjunct goals into funding design must, implicitly or explicitly, address key decision choices outlined in this paper. Summary Policy must be clear and explicit about the behaviour to be rewarded; incentives must be designed so that all facilities with an opportunity to improve have an opportunity to benefit; the reward structure is stable and meaningful; and the funder monitors performance and gaming. PMID:18384694

Parallel object-oriented decision tree system

DOEpatents

Kamath,; Chandrika, Cantu-Paz [Dublin, CA; Erick, [Oakland, CA

2006-02-28

A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.

Creating ensembles of decision trees through sampling

DOEpatents

Kamath, Chandrika; Cantu-Paz, Erick

2005-08-30

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

Shared Decision Making in Vascular Surgery: An Exploratory Study.

PubMed

Santema, T B; Stubenrouch, F E; Koelemay, M J W; Vahl, A C; Vermeulen, C F W; Visser, M J T; Ubbink, D T

2016-04-01

Shared decision making (SDM) is a process in which patients and their doctors collaborate in choosing a suitable treatment option by incorporating patient values and preferences, as well as the best available evidence. Particularly in vascular surgery, several conditions seem suitable for SDM because there are multiple treatment options. The objective of this study was to assess the degree of SDM behaviour in vascular surgery. Vascular surgeons of four Dutch hospitals selected consultations with patients who were facing a treatment decision. Immediately after the consultation, patients and surgeons completed the (subjective) SDM Q-9 and SDM Q-doc questionnaires respectively, to appreciate the perceived level of SDM behaviour. Two evaluators independently and objectively rated SDM behaviour in the audiotaped consultations, using the Observing Patient Involvement (OPTION-12) scale. Nine vascular surgeons and three vascular surgeons in training conducted 54 consultations. The patients' median SDM Q-9 score was high, 93% (IQR 79-100%), and 16/54 (29.6%) of them gave the maximum score. The surgeons' median score was also high, 84% (IQR 73-92%), while 4/54 (7.4%) gave the maximum score. In contrast, mean OPTION score was 31% (SD 11%). Surgeons hardly ever asked the patients for their preferred approach to receive information, whether they had understood the provided information, and how they would like to be involved in SDM. Currently, objective SDM behaviour among vascular surgeons is limited, even though the presented disorders allow for SDM. Hence, SDM in vascular surgical consultations could be improved by increasing the patients' and surgeons' awareness and knowledge about the concept of SDM. Copyright © 2015 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Decision Support Model for Optimal Management of Coastal Gate

NASA Astrophysics Data System (ADS)

Ditthakit, Pakorn; Chittaladakorn, Suwatana

2010-05-01

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

Application of life cycle thinking in multidisciplinary multistakeholder contexts for cross-sectoral planning and implementation of sustainable development projects.

PubMed

Thabrew, Lanka; Ries, Robert

2009-07-01

Development planning and implementation is a multifaceted and multiscale task mainly because of the involvement of multiple stakeholders across sectors and disciplines. Even though top-down sectoral planning is commonly practiced, bottom-up cross-sectoral planning involving all relevant stakeholders in a transdisciplinary learning environment has been recognized as a better option, especially if the goal is to drive development projects toward sustainable implementation (Rowe and Fudge 2003; Müller et al. 2005; Global Development Research Center 2008). Even though many planning approaches have this goal, there are limited decision frameworks that are suitable for achieving consensus among stakeholders from multiple disciplines with sectoral objectives and priorities. In most instances, the upstream and downstream effects of development decisions are not thoroughly investigated or communicated with the relevant stakeholders, strongly affecting cross-sectoral integration in the real world (Wiek, Brundiers, et al. 2006). This article presents methodological aspects of developing a stakeholder based life cycle assessment framework (SBLCA) for upstream-downstream decision analysis in a multistakeholder development planning context. The applicability of the framework is demonstrated using simple examples extracted from a pilot case study conducted in Sri Lanka for sustainable posttsunami reconstruction at a village scale. The applicability of SBLCA in specific planning stages, how it promotes transdisciplinary learning and cross-sectoral stakeholder integration in phases of project cycles, and how local stakeholders can practice life cycle thinking in their village development planning and implementation are discussed.

Reasons why women have induced abortions: a synthesis of findings from 14 countries

PubMed Central

Chae, Sophia; Desai, Sheila; Crowell, Marjorie; Sedgh, Gilda

2018-01-01

Objective Many reasons inform women’s reproductive decision-making. This paper aims to present the reasons women give for obtaining induced abortions in 14 countries. Study design We examined nationally representative data from 14 countries collected in official statistics, population-based surveys, and facility-based surveys of abortion patients. In each country, we calculated the percentage distribution of women who have abortions by main reason given for the abortion. We examined these reasons across countries and within countries by women’s sociodemographic characteristics (age, marital status, educational attainment, and residence). Where data are available, we also studied the multiple reasons women give for having an abortion. Results In most countries, the most frequently cited reasons for having an abortion were socioeconomic concerns or limiting childbearing. With some exceptions, little variation existed in the reasons given by women’s sociodemographic characteristics. Data from three countries where multiple reasons could be reported in the survey showed that women often have more than one reason for having an abortion. Conclusion This study shows that women have abortions for a variety of reasons, and provides a broad picture of the circumstances that inform women’s decisions to have abortions. Implications Future research should examine in greater depth the personal, social, economic, and health factors that inform a woman’s decision to have an abortion as these reasons may shed light on the potential consequences that unintended births can have on women’s lives. PMID:28694165

Flexible Demand Management under Time-Varying Prices

NASA Astrophysics Data System (ADS)

Liang, Yong

In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic optimization problem when the objective is to minimize the expected total cost and discomfort, then since the decision maker is likely to be risk-averse, and she wants to protect herself from price spikes, we study the robust optimization problem to address the risk-aversion of the decision maker. We conduct numerical studies to evaluate the price of robustness. Next, we present a detailed model that manages multiple types of flexible demand in the absence of knowledge regarding the distributions of related stochastic processes. Specifically, we consider the case in which time-varying prices with general structures are offered to users, and an energy management system for each household makes optimal energy usage, storage, and trading decisions according to the preferences of users. Because of the uncertainties associated with electricity prices, local generation, and the arrival processes of demand, we formulate a stochastic dynamic programming model, and outline a novel and tractable ADP approach to overcome the curses of dimensionality. Then, we perform numerical studies, whose results demonstrate the effectiveness of the ADP approach. At last, we propose another approximation approach based on Q-learning. In addition, we also develop another decentralization-based heuristic. Both the Q-learning approach and the heuristic make necessary assumptions on the knowledge of information, and each of them has unique advantages. We conduct numerical studies on a testing problem. The simulation results show that both the Q-learning and the decentralization based heuristic approaches work well. Lastly, we conclude the paper with some discussions on future extension directions.

Radar based autonomous sensor module

NASA Astrophysics Data System (ADS)

Styles, Tim

2016-10-01

Most surveillance systems combine camera sensors with other detection sensors that trigger an alert to a human operator when an object is detected. The detection sensors typically require careful installation and configuration for each application and there is a significant burden on the operator to react to each alert by viewing camera video feeds. A demonstration system known as Sensing for Asset Protection with Integrated Electronic Networked Technology (SAPIENT) has been developed to address these issues using Autonomous Sensor Modules (ASM) and a central High Level Decision Making Module (HLDMM) that can fuse the detections from multiple sensors. This paper describes the 24 GHz radar based ASM, which provides an all-weather, low power and license exempt solution to the problem of wide area surveillance. The radar module autonomously configures itself in response to tasks provided by the HLDMM, steering the transmit beam and setting range resolution and power levels for optimum performance. The results show the detection and classification performance for pedestrians and vehicles in an area of interest, which can be modified by the HLDMM without physical adjustment. The module uses range-Doppler processing for reliable detection of moving objects and combines Radar Cross Section and micro-Doppler characteristics for object classification. Objects are classified as pedestrian or vehicle, with vehicle sub classes based on size. Detections are reported only if the object is detected in a task coverage area and it is classified as an object of interest. The system was shown in a perimeter protection scenario using multiple radar ASMs, laser scanners, thermal cameras and visible band cameras. This combination of sensors enabled the HLDMM to generate reliable alerts with improved discrimination of objects and behaviours of interest.

Multiple Hypothesis Tracking (MHT) for Space Surveillance: Results and Simulation Studies

NASA Astrophysics Data System (ADS)

Singh, N.; Poore, A.; Sheaff, C.; Aristoff, J.; Jah, M.

2013-09-01

With the anticipated installation of more accurate sensors and the increased probability of future collisions between space objects, the potential number of observable space objects is likely to increase by an order of magnitude within the next decade, thereby placing an ever-increasing burden on current operational systems. Moreover, the need to track closely-spaced objects due, for example, to breakups as illustrated by the recent Chinese ASAT test or the Iridium-Kosmos collision, requires new, robust, and autonomous methods for space surveillance to enable the development and maintenance of the present and future space catalog and to support the overall space surveillance mission. The problem of correctly associating a stream of uncorrelated tracks (UCTs) and uncorrelated optical observations (UCOs) into common objects is critical to mitigating the number of UCTs and is a prerequisite to subsequent space catalog maintenance. Presently, such association operations are mainly performed using non-statistical simple fixed-gate association logic. In this paper, we report on the salient features and the performance of a newly-developed statistically-robust system-level multiple hypothesis tracking (MHT) system for advanced space surveillance. The multiple-frame assignment (MFA) formulation of MHT, together with supporting astrodynamics algorithms, provides a new joint capability for space catalog maintenance, UCT/UCO resolution, and initial orbit determination. The MFA-MHT framework incorporates multiple hypotheses for report to system track data association and uses a multi-arc construction to accommodate recently developed algorithms for multiple hypothesis filtering (e.g., AEGIS, CAR-MHF, UMAP, and MMAE). This MHT framework allows us to evaluate the benefits of many different algorithms ranging from single- and multiple-frame data association to filtering and uncertainty quantification. In this paper, it will be shown that the MHT system can provide superior tracking performance compared to existing methods at a lower computational cost, especially for closely-spaced objects, in realistic multi-sensor multi-object tracking scenarios over multiple regimes of space. Specifically, we demonstrate that the prototype MHT system can accurately and efficiently process tens of thousands of UCTs and angles-only UCOs emanating from thousands of objects in LEO, GEO, MEO and HELO, many of which are closely-spaced, in real-time on a single laptop computer, thereby making it well-suited for large-scale breakup and tracking scenarios. This is possible in part because complexity reduction techniques are used to control the runtime of MHT without sacrificing accuracy. We assess the performance of MHT in relation to other tracking methods in multi-target, multi-sensor scenarios ranging from easy to difficult (i.e., widely-spaced objects to closely-spaced objects), using realistic physics and probabilities of detection less than one. In LEO, it is shown that the MHT system is able to address the challenges of processing breakups by analyzing multiple frames of data simultaneously in order to improve association decisions, reduce cross-tagging, and reduce unassociated UCTs. As a result, the multi-frame MHT system can establish orbits up to ten times faster than single-frame methods. Finally, it is shown that in GEO, MEO and HELO, the MHT system is able to address the challenges of processing angles-only optical observations by providing a unified multi-frame framework.

The role of colour in implicit and explicit memory performance.

PubMed

Vernon, David; Lloyd-Jones, Toby J

2003-07-01

We present two experiments that examine the effects of colour transformation between study and test (from black and white to colour and vice versa, of from incorrectly coloured to correctly coloured and vice versa) on implicit and explicit measures of memory for diagnostically coloured natural objects (e.g., yellow banana). For naming and coloured-object decision (i.e., deciding whether an object is correctly coloured), there were shorter response times to correctly coloured-objects than to black-and-white and incorrectly coloured-objects. Repetition priming was equivalent for the different stimulus types. Colour transformation did not influence priming of picture naming, but for coloured-object decision priming was evident only for objects remaining the same from study to test. This was the case for both naming and coloured-object decision as study tasks. When participants were asked to consciously recognize objects that they had named or made coloured-object decisions to previously, whilst ignoring their colour, colour transformation reduced recognition efficiency. We discuss these results in terms of the flexibility of object representations that mediate priming and recognition.

Distinct roles of dopamine and subthalamic nucleus in learning and probabilistic decision making.

PubMed

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

2012-12-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making predict that learning individual stimulus-response associations and rapid combination of information from multiple stimuli are dependent on different components of basal ganglia circuitry. In particular, learning and retention of memory, required for optimal response choice, are significantly reliant on dopamine, whereas integrating information probabilistically is critically dependent upon functioning of the glutamatergic subthalamic nucleus (computing the 'normalization term' in Bayes' theorem). Here, we test these theories by investigating 22 patients with Parkinson's disease either treated with deep brain stimulation to the subthalamic nucleus and dopaminergic therapy or managed with dopaminergic therapy alone. We use computerized tasks that probe three cognitive functions-information acquisition (learning), memory over a delay and information integration when multiple pieces of sequentially presented information have to be combined. Patients performed the tasks ON or OFF deep brain stimulation and/or ON or OFF dopaminergic therapy. Consistent with the computational theories, we show that stopping dopaminergic therapy impairs memory for probabilistic information over a delay, whereas deep brain stimulation to the region of the subthalamic nucleus disrupts decision making when multiple pieces of acquired information must be combined. Furthermore, we found that when participants needed to update their decision on the basis of the last piece of information presented in the decision-making task, patients with deep brain stimulation of the subthalamic nucleus region did not slow down appropriately to revise their plan, a pattern of behaviour that mirrors the impulsivity described clinically in some patients with subthalamic nucleus deep brain stimulation. Thus, we demonstrate distinct mechanisms for two important facets of human decision making: first, a role for dopamine in memory consolidation, and second, the critical importance of the subthalamic nucleus in successful decision making when multiple pieces of information must be combined.

Objectives, priorities, reliable knowledge, and science-based management of Missouri River interior least terns and piping plovers

USGS Publications Warehouse

Sherfy, Mark; Anteau, Michael J.; Shaffer, Terry; Sovada, Marsha; Stucker, Jennifer

2011-01-01

Supporting recovery of federally listed interior least tern (Sternula antillarum athalassos; tern) and piping plover (Charadrius melodus; plover) populations is a desirable goal in management of the Missouri River ecosystem. Many tools are implemented in support of this goal, including habitat management, annual monitoring, directed research, and threat mitigation. Similarly, many types of data can be used to make management decisions, evaluate system responses, and prioritize research and monitoring. The ecological importance of Missouri River recovery and the conservation status of terns and plovers place a premium on efficient and effective resource use. Efficiency is improved when a single data source informs multiple high-priority decisions, whereas effectiveness is improved when decisions are informed by reliable knowledge. Seldom will a single study design be optimal for addressing all data needs, making prioritization of needs essential. Data collection motivated by well-articulated objectives and priorities has many advantages over studies in which questions and priorities are determined retrospectively. Research and monitoring for terns and plovers have generated a wealth of data that can be interpreted in a variety of ways. The validity and strength of conclusions from analyses of these data is dependent on compatibility between the study design and the question being asked. We consider issues related to collection and interpretation of biological data, and discuss their utility for enhancing the role of science in management of Missouri River terns and plovers. A team of USGS scientists at Northern Prairie Wildlife Research Center has been conducting tern and plover research on the Missouri River since 2005. The team has had many discussions about the importance of setting objectives, identifying priorities, and obtaining reliable information to answer pertinent questions about tern and plover management on this river system. The objectives of this presentation are to summarize those conversations and to share insights about concepts that could contribute to rigorous science support for management of this river system.

Identification and Prioritization of Important Attributes of Disease-Modifying Drugs in Decision Making among Patients with Multiple Sclerosis: A Nominal Group Technique and Best-Worst Scaling

PubMed Central

Kremer, Ingrid E. H.; van der Weijden, Trudy; van de Kolk, Ilona

2016-01-01

Objectives Understanding the preferences of patients with multiple sclerosis (MS) for disease-modifying drugs and involving these patients in clinical decision making can improve the concordance between medical decisions and patient values and may, subsequently, improve adherence to disease-modifying drugs. This study aims first to identify which characteristics–or attributes–of disease-modifying drugs influence patients´ decisions about these treatments and second to quantify the attributes’ relative importance among patients. Methods First, three focus groups of relapsing-remitting MS patients were formed to compile a preliminary list of attributes using a nominal group technique. Based on this qualitative research, a survey with several choice tasks (best-worst scaling) was developed to prioritize attributes, asking a larger patient group to choose the most and least important attributes. The attributes’ mean relative importance scores (RIS) were calculated. Results Nineteen patients reported 34 attributes during the focus groups and 185 patients evaluated the importance of the attributes in the survey. The effect on disease progression received the highest RIS (RIS = 9.64, 95% confidence interval: [9.48–9.81]), followed by quality of life (RIS = 9.21 [9.00–9.42]), relapse rate (RIS = 7.76 [7.39–8.13]), severity of side effects (RIS = 7.63 [7.33–7.94]) and relapse severity (RIS = 7.39 [7.06–7.73]). Subgroup analyses showed heterogeneity in preference of patients. For example, side effect-related attributes were statistically more important for patients who had no experience in using disease-modifying drugs compared to experienced patients (p < .001). Conclusions This study shows that, on average, patients valued effectiveness and unwanted effects as most important. Clinicians should be aware of the average preferences but also that attributes of disease-modifying drugs are valued differently by different patients. Person-centred clinical decision making would be needed and requires eliciting individual preferences. PMID:27812117

Critical role for the mediodorsal thalamus in permitting rapid reward-guided updating in stochastic reward environments

PubMed Central

Chakraborty, Subhojit; Kolling, Nils; Walton, Mark E; Mitchell, Anna S

2016-01-01

Adaptive decision-making uses information gained when exploring alternative options to decide whether to update the current choice strategy. Magnocellular mediodorsal thalamus (MDmc) supports adaptive decision-making, but its causal contribution is not well understood. Monkeys with excitotoxic MDmc damage were tested on probabilistic three-choice decision-making tasks. They could learn and track the changing values in object-reward associations, but they were severely impaired at updating choices after reversals in reward contingencies or when there were multiple options associated with reward. These deficits were not caused by perseveration or insensitivity to negative feedback though. Instead, monkeys with MDmc lesions exhibited an inability to use reward to promote choice repetition after switching to an alternative option due to a diminished influence of recent past choices and the last outcome to guide future behavior. Together, these data suggest MDmc allows for the rapid discovery and persistence with rewarding options, particularly in uncertain or changing environments. DOI: http://dx.doi.org/10.7554/eLife.13588.001 PMID:27136677

Point-of-decision prompts for increasing park-based physical activity: a crowdsource analysis

PubMed Central

Wilhelm Stanis, Sonja A.; Hipp, J. Aaron

2014-01-01

Objective To examine the potential efficacy of using point-of-decision prompts to influence intentions to be active in a park setting. Methods In June 2013, participants from across the U.S. (n=250) completed an online experiment using Amazon’s Mechanical Turk and Survey Monkey. Participants were randomly exposed to a park photo containing a persuasive, theoretically-based message in the form of a sign (treatment) or an identical photo with no sign (control). Differences in intentions to engage in moderate-to-vigorous physical activity within the park were examined between the two conditions for multiple gender, age, and race groups. Results Participants who were exposed to the park photo with the sign reported significantly greater intentions to be active than those who viewed the photo without a sign. This effect was especially strong for women compared to men, but no differences were observed across age or race groups. Conclusion Point-of-decision prompts are a relatively inexpensive, simple, sustainable, and scalable strategy for evoking behavior change in parks and further testing of diverse messages in actual park settings is warranted. PMID:25204987

Predictors of hospitalised patients' preferences for physician-directed medical decision-making.

PubMed

Chung, Grace S; Lawrence, Ryan E; Curlin, Farr A; Arora, Vineet; Meltzer, David O

2012-02-01

Although medical ethicists and educators emphasise patient-centred decision-making, previous studies suggest that patients often prefer their doctors to make the clinical decisions. To examine the associations between a preference for physician-directed decision-making and patient health status and sociodemographic characteristics. Sociodemographic and clinical information from all consenting general internal medicine patients at the University of Chicago Medical Center were examined. The primary objectives were to (1) assess the extent to which patients prefer an active role in clinical decision-making, and (2) determine whether religious service attendance, the importance of religion, self-rated spirituality, Charlson Comorbidity Index, self-reported health, Vulnerable Elder Score and several demographic characteristics were associated with these preferences. Data were collected from 8308 of 11,620 possible participants. Ninety-seven per cent of respondents wanted doctors to offer them choices and to consider their opinions. However, two out of three (67%) preferred to leave medical decisions to the doctor. In multiple regression analyses, preferring to leave decisions to the doctor was associated with older age (per year, OR=1.019, 95% CI 1.003 to 1.036) and frequently attending religious services (OR=1.5, 95% CI 1.1 to 2.1, compared with never), and it was inversely associated with female sex (OR=0.6, 95% CI 0.5 to 0.8), university education (OR=0.6, 95% CI 0.4 to 0.9, compared with no high school diploma) and poor health (OR=0.6, 95% CI 0.3 to 0.9). Almost all patients want doctors to offer them choices and to consider their opinions, but most prefer to leave medical decisions to the doctor. Patients who are male, less educated, more religious and healthier are more likely to want to leave decisions to their doctors, but effects are small.

Distributed Space Mission Design for Earth Observation Using Model-Based Performance Evaluation

NASA Technical Reports Server (NTRS)

Nag, Sreeja; LeMoigne-Stewart, Jacqueline; Cervantes, Ben; DeWeck, Oliver

2015-01-01

Distributed Space Missions (DSMs) are gaining momentum in their application to earth observation missions owing to their unique ability to increase observation sampling in multiple dimensions. DSM design is a complex problem with many design variables, multiple objectives determining performance and cost and emergent, often unexpected, behaviors. There are very few open-access tools available to explore the tradespace of variables, minimize cost and maximize performance for pre-defined science goals, and therefore select the most optimal design. This paper presents a software tool that can multiple DSM architectures based on pre-defined design variable ranges and size those architectures in terms of predefined science and cost metrics. The tool will help a user select Pareto optimal DSM designs based on design of experiments techniques. The tool will be applied to some earth observation examples to demonstrate its applicability in making some key decisions between different performance metrics and cost metrics early in the design lifecycle.

Conceptual Organization at 6 and 8 Years of Age: Evidence from the Semantic Priming of Object Decisions

ERIC Educational Resources Information Center

Hashimoto, Naomi; McGregor, Karla K.; Graham, Anne

2007-01-01

Purpose: The purpose of this study was to examine children's knowledge of semantic relations. Method: In Experiment 1, the 6-year-olds, 8-year-olds, and adults participated in an object decision task. Participants in the primed group made object decisions in response to primes that were related taxonomically, thematically, or perceptually to the…

Structured decision making as a conceptual framework to identify thresholds for conservation and management

USGS Publications Warehouse

Martin, J.; Runge, M.C.; Nichols, J.D.; Lubow, B.C.; Kendall, W.L.

2009-01-01

Thresholds and their relevance to conservation have become a major topic of discussion in the ecological literature. Unfortunately, in many cases the lack of a clear conceptual framework for thinking about thresholds may have led to confusion in attempts to apply the concept of thresholds to conservation decisions. Here, we advocate a framework for thinking about thresholds in terms of a structured decision making process. The purpose of this framework is to promote a logical and transparent process for making informed decisions for conservation. Specification of such a framework leads naturally to consideration of definitions and roles of different kinds of thresholds in the process. We distinguish among three categories of thresholds. Ecological thresholds are values of system state variables at which small changes bring about substantial changes in system dynamics. Utility thresholds are components of management objectives (determined by human values) and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. The approach that we present focuses directly on the objectives of management, with an aim to providing decisions that are optimal with respect to those objectives. This approach clearly distinguishes the components of the decision process that are inherently subjective (management objectives, potential management actions) from those that are more objective (system models, estimates of system state). Optimization based on these components then leads to decision matrices specifying optimal actions to be taken at various values of system state variables. Values of state variables separating different actions in such matrices are viewed as decision thresholds. Utility thresholds are included in the objectives component, and ecological thresholds may be embedded in models projecting consequences of management actions. Decision thresholds are determined by the above-listed components of a structured decision process. These components may themselves vary over time, inducing variation in the decision thresholds inherited from them. These dynamic decision thresholds can then be determined using adaptive management. We provide numerical examples (that are based on patch occupancy models) of structured decision processes that include all three kinds of thresholds. ?? 2009 by the Ecological Society of America.

A structured analysis of uncertainty surrounding modeled impacts of groundwater-extraction rules

NASA Astrophysics Data System (ADS)

Guillaume, Joseph H. A.; Qureshi, M. Ejaz; Jakeman, Anthony J.

2012-08-01

Integrating economic and groundwater models for groundwater-management can help improve understanding of trade-offs involved between conflicting socioeconomic and biophysical objectives. However, there is significant uncertainty in most strategic decision-making situations, including in the models constructed to represent them. If not addressed, this uncertainty may be used to challenge the legitimacy of the models and decisions made using them. In this context, a preliminary uncertainty analysis was conducted of a dynamic coupled economic-groundwater model aimed at assessing groundwater extraction rules. The analysis demonstrates how a variety of uncertainties in such a model can be addressed. A number of methods are used including propagation of scenarios and bounds on parameters, multiple models, block bootstrap time-series sampling and robust linear regression for model calibration. These methods are described within the context of a theoretical uncertainty management framework, using a set of fundamental uncertainty management tasks and an uncertainty typology.

Fuzzy set methods for object recognition in space applications

NASA Technical Reports Server (NTRS)

Keller, James M.

1991-01-01

During the reporting period, the development of the theory and application of methodologies for decision making under uncertainty was addressed. Two subreports are included; the first on properties of general hybrid operators, while the second considers some new research on generalized threshold logic units. In the first part, the properties of the additive gamma-model, where the intersection part is first considered to be the product of the input values and the union part is obtained by an extension of De Morgan's law to fuzzy sets, is explored. Then the Yager's class of union and intersection is used in the additive gamma-model. The inputs are weighted to some power that represents their importance and thus their contribution to the compensation process. In the second part, the extension of binary logic synthesis methods to multiple valued logic synthesis methods to enable the synthesis of decision networks when the input/output variables are not binary is discussed.

Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

PubMed

Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

2018-03-05

This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

Multi-objective decision-making under uncertainty: Fuzzy logic methods

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1995-01-01

Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

A model of human decision making in multiple process monitoring situations

NASA Technical Reports Server (NTRS)

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

1982-01-01

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

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

PubMed

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

2014-01-01

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

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

PubMed Central

Zhou, Xiaoqiang; Yang, Tian

2014-01-01

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

The Constructive Role of Decisions: Implications from a quantum Approach

DTIC Science & Technology

2016-12-01

objectives. The first was to explore the nature of constructive influences in decision making . The second concerned understanding decision making in...Prisoner’s Dilemma. **First objective; constructive judgments. This is the idea that sometimes making a decision can alter the underlying relevant mental...the performance of the agent. 15.  SUBJECT TERMS EOARD, Quantum Probability, Human Modeling, Human Decision Making 16.  SECURITY CLASSIFICATION OF

Factors Affecting Employment Among Informal Caregivers Assisting People with Multiple Sclerosis

PubMed Central

Huang, Chunfeng; Zheng, Zhida

2013-01-01

The objective of this study was to identify characteristics of informal caregivers, caregiving, and the people with multiple sclerosis (MS) receiving assistance that are associated with reduced caregiver employment. Data were collected during telephone interviews with 530 MS caregivers, including 215 employed caregivers, with these survey data analyzed using logistic regression. Poorer cognitive ability by the care recipient to make decisions about daily tasks and more caregiving hours per week predicted reduced caregiver employment. Better physical health domains of caregiver quality of life were associated with significantly lower odds of reduced employment. Health professionals treating informal caregivers, as well as those treating people with MS, need to be aware of respite, support, and intervention programs available to MS caregivers and refer them to these programs, which could reduce the negative impact of caregiving on employment. PMID:24453784

Optimal frame-by-frame result combination strategy for OCR in video stream

NASA Astrophysics Data System (ADS)

Bulatov, Konstantin; Lynchenko, Aleksander; Krivtsov, Valeriy

2018-04-01

This paper describes the problem of combining classification results of multiple observations of one object. This task can be regarded as a particular case of a decision-making using a combination of experts votes with calculated weights. The accuracy of various methods of combining the classification results depending on different models of input data is investigated on the example of frame-by-frame character recognition in a video stream. Experimentally it is shown that the strategy of choosing a single most competent expert in case of input data without irrelevant observations has an advantage (in this case irrelevant means with character localization and segmentation errors). At the same time this work demonstrates the advantage of combining several most competent experts according to multiplication rule or voting if irrelevant samples are present in the input data.

Balancing emotion and cognition: a case for decision aiding in conservation efforts.

PubMed

Wilson, Robyn S

2008-12-01

Despite advances in the quality of participatory decision making for conservation, many current efforts still suffer from an inability to bridge the gap between science and policy. Judgment and decision-making research suggests this gap may result from a person's reliance on affect-based shortcuts in complex decision contexts. I examined the results from 3 experiments that demonstrate how affect (i.e., the instantaneous reaction one has to a stimulus) influences individual judgments in these contexts and identified techniques from the decision-aiding literature that help encourage a balance between affect-based emotion and cognition in complex decision processes. In the first study, subjects displayed a lack of focus on their stated conservation objectives and made decisions that reflected their initial affective impressions. Value-focused approaches may help individuals incorporate all the decision-relevant objectives by making the technical and value-based objectives more salient. In the second study, subjects displayed a lack of focus on statistical risk and again made affect-based decisions. Trade-off techniques may help individuals incorporate relevant technical data, even when it conflicts with their initial affective impressions or other value-based objectives. In the third study, subjects displayed a lack of trust in decision-making authorities when the decision involved a negatively affect-rich outcome (i.e., a loss). Identifying shared salient values and increasing procedural fairness may help build social trust in both decision-making authorities and the decision process.

Ignorance- versus evidence-based decision making: a decision time analysis of the recognition heuristic.

PubMed

Hilbig, Benjamin E; Pohl, Rüdiger F

2009-09-01

According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments-and its duration-is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of evidence speaking for each of the objects and that decision times thus depend on the evidential difference between objects, or the degree of conflict between options. This article presents 3 experiments that tested predictions derived from the RH against those from alternative models. All experiments used naturally recognized objects without teaching participants any information and thus provided optimal conditions for application of the RH. However, results supported the alternative, evidence-based models and often conflicted with the RH. Recognition was not the key determinant of decision times, whereas differences between objects with respect to (both positive and negative) evidence predicted effects well. In sum, alternative models that allow for the integration of different pieces of information may well provide a better account of comparative judgments. (c) 2009 APA, all rights reserved.

[Rational use of psychotropic drugs and social communication role].

PubMed

Montero, F

1994-06-01

Extra-clinical factors about the influences affecting the prescription and use of drugs are reviewed. Special attention is given to regulatory agencies, the pharmaceutical industry, and mass media. The problems and public health consequences of the irrational use of drugs are rarely documented in Latin America. Analysis of these factors, information sources, and rational use of psychotropic drugs will require multiple strategies such as social communication and policy formulation to define goals and objectives related to population information, doctors' and individual citizens' decision making processes, and participation of consumers in improving the use of psychotropic drugs.

Cloud E-Learning Service Strategies for Improving E-Learning Innovation Performance in a Fuzzy Environment by Using a New Hybrid Fuzzy Multiple Attribute Decision-Making Model

ERIC Educational Resources Information Center

Su, Chiu Hung; Tzeng, Gwo-Hshiung; Hu, Shu-Kung

2016-01-01

The purpose of this study was to address this problem by applying a new hybrid fuzzy multiple criteria decision-making model including (a) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to construct the fuzzy scope influential network relationship map (FSINRM) and determine the fuzzy influential weights of the…

Flexible high speed codec

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Patient Perspectives on Choosing Buprenorphine over Methadone in an Urban Equal Access System

PubMed Central

Gryczynski, Jan; Jaffe, Jerome H.; Schwartz, Robert P.; Dušek, Kristi A.; Gugsa, Nishan; Monroe, Cristin L.; O'Grady, Kevin E.; Olsen, Yngvild K.; Mitchell, Shannon Gwin

2014-01-01

Background Recent policy initiatives in Baltimore City, MD significantly reduced access disparities between methadone and buprenorphine in the publicly-funded treatment sector. Objectives This study examines reasons for choosing buprenorphine over methadone among patients with access to both medications. Methods This study was embedded within a larger clinical trial conducted at two outpatient substance abuse treatment programs offering buprenorphine. Qualitative and quantitative data on treatment choice were collected for new patients starting buprenorphine treatment (n=80). The sample consisted of predominantly urban African American (94%) heroin users who had prior experience with non-prescribed street buprenorphine (85%) and opioid agonist treatment (68%). Qualitative data were transcribed and coded for themes, while quantitative data were analyzed using descriptive and bivariate statistics. Results Participants typically conveyed their choice of buprenorphine treatment as a decision against methadone. Buprenorphine was perceived as a helpful medication while methadone was perceived as a harmful narcotic with multiple unwanted physical effects. Positive experiences with non-prescribed “street buprenorphine” were a central factor in participants’ decisions to seek buprenorphine treatment. Conclusions Differences in service structure between methadone and buprenorphine did not strongly influence treatment-seeking decisions in this sample. Personal experiences with medications and the street narrative surrounding them play an important role in treatment selection decisions. Scientific Significance This study characterizes important decision factors that underlie patients’ selection of buprenorphine over methadone treatment. PMID:23617873

Optimizing in a complex world: A statistician's role in decision making

DOE PAGES

Anderson-Cook, Christine M.

2016-08-09

As applied statisticians increasingly participate as active members of problem-solving and decision-making teams, our role continues to evolve. Historically, we may have been seen as those who can help with data collection strategies or answer a specific question from a set of data. Nowadays, we are or strive to be more deeply involved throughout the entire problem-solving process. An emerging role is to provide a set of leading choices from which subject matter experts and managers can choose to make informed decisions. A key to success is to provide vehicles for understanding the trade-offs between candidates and interpreting the meritsmore » of each choice in the context of the decision-makers priorities. To achieve this objective, it is helpful to be able (a) to help subject matter experts identify quantitative criteria that match their priorities, (b) eliminate non-competitive choices through the use of a Pareto front, and (c) provide summary tools from which the trade-offs between alternatives can be quantitatively evaluated and discussed. A structured but flexible process for contributing to team decisions is described for situations when all choices can easily be enumerated as well as when a search algorithm to explore a vast number of potential candidates is required. In conclusion, a collection of diverse examples ranging from model selection, through multiple response optimization, and designing an experiment illustrate the approach.« less

Optimizing in a complex world: A statistician's role in decision making

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

Anderson-Cook, Christine M.

As applied statisticians increasingly participate as active members of problem-solving and decision-making teams, our role continues to evolve. Historically, we may have been seen as those who can help with data collection strategies or answer a specific question from a set of data. Nowadays, we are or strive to be more deeply involved throughout the entire problem-solving process. An emerging role is to provide a set of leading choices from which subject matter experts and managers can choose to make informed decisions. A key to success is to provide vehicles for understanding the trade-offs between candidates and interpreting the meritsmore » of each choice in the context of the decision-makers priorities. To achieve this objective, it is helpful to be able (a) to help subject matter experts identify quantitative criteria that match their priorities, (b) eliminate non-competitive choices through the use of a Pareto front, and (c) provide summary tools from which the trade-offs between alternatives can be quantitatively evaluated and discussed. A structured but flexible process for contributing to team decisions is described for situations when all choices can easily be enumerated as well as when a search algorithm to explore a vast number of potential candidates is required. In conclusion, a collection of diverse examples ranging from model selection, through multiple response optimization, and designing an experiment illustrate the approach.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

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

2017-03-01

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

A decision support model for improving a multi-family housing complex based on CO2 emission from electricity consumption.

PubMed

Hong, Taehoon; Koo, Choongwan; Kim, Hyunjoong

2012-12-15

The number of deteriorated multi-family housing complexes in South Korea continues to rise, and consequently their electricity consumption is also increasing. This needs to be addressed as part of the nation's efforts to reduce energy consumption. The objective of this research was to develop a decision support model for determining the need to improve multi-family housing complexes. In this research, 1664 cases located in Seoul were selected for model development. The research team collected the characteristics and electricity energy consumption data of these projects in 2009-2010. The following were carried out in this research: (i) using the Decision Tree, multi-family housing complexes were clustered based on their electricity energy consumption; (ii) using Case-Based Reasoning, similar cases were retrieved from the same cluster; and (iii) using a combination of Multiple Regression Analysis, Artificial Neural Network, and Genetic Algorithm, the prediction performance of the developed model was improved. The results of this research can be used as follows: (i) as basic research data for continuously managing several energy consumption data of multi-family housing complexes; (ii) as advanced research data for predicting energy consumption based on the project characteristics; (iii) as practical research data for selecting the most optimal multi-family housing complex with the most potential in terms of energy savings; and (iv) as consistent and objective criteria for incentives and penalties. Copyright © 2012 Elsevier Ltd. All rights reserved.

CROSS: A GDSS for the Evaluation and Prioritization of Engineering Support Requests and Advanced Technology Projects at NASA

NASA Technical Reports Server (NTRS)

Tavana, Madjid; Lee, Seunghee

1996-01-01

Objective evaluation and prioritization of engineering support requests (ESRs) is a difficult task at the Kennedy Space Center (KSC) Shuttle Project Engineering Office. The difficulty arises from the complexities inherent in the evaluation process and the lack of structured information. The purpose of this project is to implement the consensus ranking organizational support system (CROSS), a multiple criteria decision support system (DSS) developed at KSC that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. CROSS utilizes the analytic hierarchy process (AHP), subjective probabilities, entropy concept, and maximize agreement heuristic (MAH) to enhance the decision maker's intuition in evaluation ESRs. Some of the preliminary goals of the project are to: (1) revisit the structure of the ground systems working team (GWST) steering committee, (2) develop a template for ESR originators to provide more comple and consistent information to the GSWT steering committee members to eliminate the need for a facilitator, (3) develop an objective and structured process for the initial screening of ESRs, (4) extensive training of the stakeholders and the GWST steering committee to eliminate the need for a facilitator, (5) automate the process as much as possible, (6) create an environment to compile project success factor data on ESRs and move towards a disciplined system that could be used to address supportability threshold issues at the KSC, and (7) investigate the possibility of an organization-wide implementation of CROSS.

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

PubMed

Eckermann, Simon; Willan, Andrew R

2011-07-01

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

Impacts of High Variable Renewable Energy Futures on Wholesale Electricity Prices, and on Electric-Sector Decision Making

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

Seel, Joachim; Mills, Andrew D.; Wiser, Ryan H.

Increasing penetrations of variable renewable energy (VRE) can affect wholesale electricity price patterns and make them meaningfully different from past, traditional price patterns. Many long-lasting decisions for supply- and demand-side electricity infrastructure and programs are based on historical observations or assume a business-as-usual future with low shares of VRE. Our motivating question is whether certain electric-sector decisions that are made based on assumptions reflecting low VRE levels will still achieve their intended objective in a high VRE future. We qualitatively describe how various decisions may change with higher shares of VRE and outline an analytical framework for quantitatively evaluating themore » impacts of VRE on long-lasting decisions. We then present results from detailed electricity market simulations with capacity expansion and unit commitment models for multiple regions of the U.S. for low and high VRE futures. We find a general decrease in average annual hourly wholesale energy prices with more VRE penetration, increased price volatility and frequency of very low-priced hours, and changing diurnal price patterns. Ancillary service prices rise substantially and peak net-load hours with high capacity value are shifted increasingly into the evening, particularly for high solar futures. While in this report we only highlight qualitatively the possible impact of these altered price patterns on other demand- and supply-side electric sector decisions, the core set of electricity market prices derived here provides a foundation for later planned quantitative evaluations of these decisions in low and high VRE futures.« less

Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2017-04-01

Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

Discovering Tradeoffs, Vulnerabilities, and Dependencies within Water Resources Systems

NASA Astrophysics Data System (ADS)

Reed, P. M.

2015-12-01

There is a growing recognition and interest in using emerging computational tools for discovering the tradeoffs that emerge across complex combinations infrastructure options, adaptive operations, and sign posts. As a field concerned with "deep uncertainties", it is logically consistent to include a more direct acknowledgement that our choices for dealing with computationally demanding simulations, advanced search algorithms, and sensitivity analysis tools are themselves subject to failures that could adversely bias our understanding of how systems' vulnerabilities change with proposed actions. Balancing simplicity versus complexity in our computational frameworks is nontrivial given that we are often exploring high impact irreversible decisions. It is not always clear that accepted models even encompass important failure modes. Moreover as they become more complex and computationally demanding the benefits and consequences of simplifications are often untested. This presentation discusses our efforts to address these challenges through our "many-objective robust decision making" (MORDM) framework for the design and management water resources systems. The MORDM framework has four core components: (1) elicited problem conception and formulation, (2) parallel many-objective search, (3) interactive visual analytics, and (4) negotiated selection of robust alternatives. Problem conception and formulation is the process of abstracting a practical design problem into a mathematical representation. We build on the emerging work in visual analytics to exploit interactive visualization of both the design space and the objective space in multiple heterogeneous linked views that permit exploration and discovery. Many-objective search produces tradeoff solutions from potentially competing problem formulations that can each consider up to ten conflicting objectives based on current computational search capabilities. Negotiated design selection uses interactive visualization, reformulation, and optimization to discover desirable designs for implementation. Multi-city urban water supply portfolio planning will be used to illustrate the MORDM framework.

Goal-Proximity Decision-Making

ERIC Educational Resources Information Center

Veksler, Vladislav D.; Gray, Wayne D.; Schoelles, Michael J.

2013-01-01

Reinforcement learning (RL) models of decision-making cannot account for human decisions in the absence of prior reward or punishment. We propose a mechanism for choosing among available options based on goal-option association strengths, where association strengths between objects represent previously experienced object proximity. The proposed…

The influence of the dorsolateral prefrontal cortex on attentional behavior and decision making. A t-DCS study on emotionally vs. functionally designed objects.

PubMed

Colombo, Barbara; Balzarotti, Stefania; Mazzucchelli, Nicla

2016-04-01

Prior research has shown that right dorsolateral prefrontal cortex may be crucial in cognitive control of affective impulses during decision making. The present study examines whether modulation of r-DLPFC with transcranial direct current stimulation influences attentional behavior and decision-making in a purchase task requiring participants to choose either emotional/attractive or functional/useful objects. 30 participants were shown sixteen pairs of emotionally or functionally designed products while their eye-movements were recorded. Participants were asked to judge aesthetics and usefulness of each object, and to decide which object of each pair they would buy. Results revealed that participants decided to buy the functionally designed objects more often regardless of condition; however, participants receiving anodal stimulation were faster in decision making. Although stimulation of r-DLPFC did not affect the actual purchasing choice and had little effect on visual exploration during decision making, it influenced perceived usefulness and attractiveness, with temporary inhibition of r-DLPFC leading to evaluate functional objects as less attractive. Finally, anodal stimulation led to judge the objects as more useful. The implications of these results are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Connecting a cognitive architecture to robotic perception

NASA Astrophysics Data System (ADS)

Kurup, Unmesh; Lebiere, Christian; Stentz, Anthony; Hebert, Martial

2012-06-01

We present an integrated architecture in which perception and cognition interact and provide information to each other leading to improved performance in real-world situations. Our system integrates the Felzenswalb et. al. object-detection algorithm with the ACT-R cognitive architecture. The targeted task is to predict and classify pedestrian behavior in a checkpoint scenario, most specifically to discriminate between normal versus checkpoint-avoiding behavior. The Felzenswalb algorithm is a learning-based algorithm for detecting and localizing objects in images. ACT-R is a cognitive architecture that has been successfully used to model human cognition with a high degree of fidelity on tasks ranging from basic decision-making to the control of complex systems such as driving or air traffic control. The Felzenswalb algorithm detects pedestrians in the image and provides ACT-R a set of features based primarily on their locations. ACT-R uses its pattern-matching capabilities, specifically its partial-matching and blending mechanisms, to track objects across multiple images and classify their behavior based on the sequence of observed features. ACT-R also provides feedback to the Felzenswalb algorithm in the form of expected object locations that allow the algorithm to eliminate false-positives and improve its overall performance. This capability is an instance of the benefits pursued in developing a richer interaction between bottom-up perceptual processes and top-down goal-directed cognition. We trained the system on individual behaviors (only one person in the scene) and evaluated its performance across single and multiple behavior sets.

Evaluating the Effectiveness of Web-based Climate Resilience Decision Support Tools: Insights from Coastal New Jersey

NASA Astrophysics Data System (ADS)

Brady, M.; Lathrop, R.; Auermuller, L. M.; Leichenko, R.

2016-12-01

Despite the recent surge of Web-based decision support tools designed to promote resiliency in U.S. coastal communities, to-date there has been no systematic study of their effectiveness. This study demonstrates a method to evaluate important aspects of effectiveness of four Web map tools designed to promote consideration of climate risk information in local decision-making and planning used in coastal New Jersey. In summer 2015, the research team conducted in-depth phone interviews with users of one regulatory and three non-regulatory Web map tools using a semi-structured questionnaire. The interview and analysis design drew from a combination of effectiveness evaluation approaches developed in software and information usability, program evaluation, and management information system (MIS) research. Effectiveness assessment results were further analyzed and discussed in terms of conceptual hierarchy of system objectives defined by respective tool developer and user organizations represented in the study. Insights from the interviews suggest that users rely on Web tools as a supplement to desktop and analog map sources because they provide relevant and up-to-date information in a highly accessible and mobile format. The users also reported relying on multiple information sources and comparison between digital and analog sources for decision support. However, with respect to this decision support benefit, users were constrained by accessibility factors such as lack of awareness and training with some tools, lack of salient information such as planning time horizons associated with future flood scenarios, and environmental factors such as mandates restricting some users to regulatory tools. Perceptions of Web tool credibility seem favorable overall, but factors including system design imperfections and inconsistencies in data and information across platforms limited trust, highlighting a need for better coordination between tools. Contributions of the study include user feedback on web-tool system designs consistent with collaborative methods for enhancing usability and a systematic look at effectiveness that includes both user perspectives and consideration of developer and organizational objectives.

How do workplaces, working practices and colleagues affect UK doctors’ career decisions? A qualitative study of junior doctors’ career decision making in the UK

PubMed Central

Pearson, Emma; Gibson, Jonathan; Checkland, Kath

2017-01-01

Objectives This study draws on an in-depth investigation of factors that influenced the career decisions of junior doctors. Setting Junior doctors in the UK can choose to enter specialty training (ST) programmes within 2 years of becoming doctors. Their specialty choices contribute to shaping the balance of the future medical workforce, with views on general practice (GP) careers of particular interest because of current recruitment difficulties. This paper examines how experiences of medical work and perceptions about specialty training shape junior doctors’ career decisions. Participants Twenty doctors in the second year of a Foundation Training Programme in England were recruited. Purposive sampling was used to achieve a diverse sample from respondents to an online survey. Results Narrative interviewing techniques encouraged doctors to reflect on how experiences during medical school and in medical workplaces had influenced their preferences and perceptions of different specialties. They also spoke about personal aspirations, work priorities and their wider future. Junior doctors’ decisions were informed by knowledge about the requirements of ST programmes and direct observation of the pressures under which ST doctors worked. When they encountered negative attitudes towards a specialty they had intended to choose, some became defensive while others kept silent. Achievement of an acceptable work-life balance was a central objective that could override other preferences. Events linked with specific specialties influenced doctors’ attitudes towards them. For example, findings confirmed that while early, positive experiences of GP work could increase its attractiveness, negative experiences in GP settings had the opposite effect. Conclusions Junior doctors’ preferences and perceptions about medical work are influenced by multiple intrinsic and extrinsic factors and experiences. This paper highlights the importance of understanding how perceptions are formed and preferences are developed, as a basis for generating learning and working environments that nurture students and motivate their professional careers. PMID:29074517

Restoration handbook for sagebrush steppe ecosystems with emphasis on greater sage-grouse habitat—Part 2. Landscape level restoration decisions

USGS Publications Warehouse

Pyke, David A.; Knick, Steven T.; Chambers, Jeanne C.; Pellant, Mike; Miller, Richard F.; Beck, Jeffrey L.; Doescher, Paul S.; Schupp, Eugene W.; Roundy, Bruce A.; Brunson, Mark; McIver, James D.

2015-12-07

Land managers do not have resources to restore all locations because of the extent of the restoration need and because some land uses are not likely to change, therefore, restoration decisions made at the landscape to regional scale may improve the effectiveness of restoration to achieve landscape and local restoration objectives. We present a landscape restoration decision tool intended to assist decision makers in determining landscape objectives, to identify and prioritize landscape areas where sites for priority restoration projects might be located, and to aid in ultimately selecting restoration sites guided by criteria used to define the landscape objectives. The landscape restoration decision tool is structured in five sections that should be addressed sequentially. Each section has a primary question or statement followed by related questions and statements to assist the user in addressing the primary question or statement. This handbook will guide decision makers through the important process steps of identifying appropriate questions, gathering appropriate data, developing landscape objectives, and prioritizing landscape patches where potential sites for restoration projects may be located. Once potential sites are selected, land managers can move to the site-specific decision tool to guide restoration decisions at the site level.

Multi-objective optimization of solid waste flows: environmentally sustainable strategies for municipalities.

PubMed

Minciardi, Riccardo; Paolucci, Massimo; Robba, Michela; Sacile, Roberto

2008-11-01

An approach to sustainable municipal solid waste (MSW) management is presented, with the aim of supporting the decision on the optimal flows of solid waste sent to landfill, recycling and different types of treatment plants, whose sizes are also decision variables. This problem is modeled with a non-linear, multi-objective formulation. Specifically, four objectives to be minimized have been taken into account, which are related to economic costs, unrecycled waste, sanitary landfill disposal and environmental impact (incinerator emissions). An interactive reference point procedure has been developed to support decision making; these methods are considered appropriate for multi-objective decision problems in environmental applications. In addition, interactive methods are generally preferred by decision makers as they can be directly involved in the various steps of the decision process. Some results deriving from the application of the proposed procedure are presented. The application of the procedure is exemplified by considering the interaction with two different decision makers who are assumed to be in charge of planning the MSW system in the municipality of Genova (Italy).

STakeholder-Objective Risk Model (STORM): Determining the aggregated risk of multiple contaminant hazards in groundwater well catchments

NASA Astrophysics Data System (ADS)

Enzenhoefer, R.; Binning, P. J.; Nowak, W.

2015-09-01

Risk is often defined as the product of probability, vulnerability and value. Drinking water supply from groundwater abstraction is often at risk due to multiple hazardous land use activities in the well catchment. Each hazard might or might not introduce contaminants into the subsurface at any point in time, which then affects the pumped quality upon transport through the aquifer. In such situations, estimating the overall risk is not trivial, and three key questions emerge: (1) How to aggregate the impacts from different contaminants and spill locations to an overall, cumulative impact on the value at risk? (2) How to properly account for the stochastic nature of spill events when converting the aggregated impact to a risk estimate? (3) How will the overall risk and subsequent decision making depend on stakeholder objectives, where stakeholder objectives refer to the values at risk, risk attitudes and risk metrics that can vary between stakeholders. In this study, we provide a STakeholder-Objective Risk Model (STORM) for assessing the total aggregated risk. Or concept is a quantitative, probabilistic and modular framework for simulation-based risk estimation. It rests on the source-pathway-receptor concept, mass-discharge-based aggregation of stochastically occuring spill events, accounts for uncertainties in the involved flow and transport models through Monte Carlo simulation, and can address different stakeholder objectives. We illustrate the application of STORM in a numerical test case inspired by a German drinking water catchment. As one may expect, the results depend strongly on the chosen stakeholder objectives, but they are equally sensitive to different approaches for risk aggregation across different hazards, contaminant types, and over time.

Multi-objective decision-making under uncertainty: Fuzzy logic methods

NASA Technical Reports Server (NTRS)

Hardy, Terry L.

1994-01-01

Selecting the best option among alternatives is often a difficult process. This process becomes even more difficult when the evaluation criteria are vague or qualitative, and when the objectives vary in importance and scope. Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

A formalized approach to making effective natural resource management decisions for Alaska National Parks

USGS Publications Warehouse

MacCluskie, Margaret C.; Romito, Angela; Peterson, James T.; Lawler, James P.

2015-01-01

A fundamental goal of the National Park Service (NPS) is the long-term protection and management of resources in the National Park System. Reaching this goal requires multiple approaches, including the conservation of essential habitats and the identification and elimination of potential threats to biota and habitats. To accomplish these goals, the NPS has implemented the Alaska Region Vital Signs Inventory and Monitoring (I&M) Program to monitor key biological, chemical, and physical components of ecosystems at more than 270 national parks. The Alaska Region has four networks—Arctic, Central, Southeast, and Southwest. By monitoring vital signs over large spatial and temporal scales, park managers are provided with information on the status and trajectory of park resources as well as a greater understanding and insight into the ecosystem dynamics. While detecting and quantifying change is important to conservation efforts, to be useful for formulating remedial actions, monitoring data must explicitly relate to management objectives and be collected in such a manner as to resolve key uncertainties about the dynamics of the system (Nichols and Williams 2006). Formal decision making frameworks (versus more traditional processes described below) allow for the explicit integration of monitoring data into decision making processes to improve the understanding of system dynamics, thereby improving future decisions (Williams 2011).

Can the democratic ideal of participatory research be achieved? An inside look at an academic-indigenous community partnership.

PubMed

Cargo, Margaret; Delormier, Treena; Lévesque, Lucie; Horn-Miller, Kahente; McComber, Alex; Macaulay, Ann C

2008-10-01

Democratic or equal participation in decision making is an ideal that community and academic stakeholders engaged in participatory research strive to achieve. This ideal, however, may compete with indigenous peoples' right to self-determination. Study objectives were to assess the perceived influence of multiple community (indigenous) and academic stakeholders engaged in the Kahnawake Schools Diabetes Prevention Project (KSDPP) across six domains of project decision making and to test the hypothesis that KSDPP would be directed by community stakeholders. Self-report surveys were completed by 51 stakeholders comprising the KSDPP Community Advisory Board (CAB), KSDPP staff, academic researchers and supervisory board members. KSDPP staff were perceived to share similar levels of influence with (i) CAB on maintaining partnership ethics and CAB activities and (ii) academic researchers on research and dissemination activities. KSDPP staff were perceived to carry significantly more influence than other stakeholders on decisions related to annual activities, program operations and intervention activities. CAB and staff were the perceived owners of KSDPP. The strong community leadership aligns KSDPP with a model of community-directed research and suggests that equitable participation-distinct from democratic or equal participation-is reflected by indigenous community partners exerting greater influence than academic partners in decision making.

Shared Decision Making at the Limit of Viability: A Blueprint for Physician Action

PubMed Central

2016-01-01

Objective To document interactions during the antenatal consultation between parents and neonatologist that parents linked to their satisfaction with their participation in shared decision making for their infant at risk of being born at the limit of viability. Methods This multiple-case ethnomethodological qualitative research study, included mothers admitted for a threatened premature delivery between 200/7 and 266/7 weeks gestation, the father, and the staff neonatologist conducting the clinical antenatal consultation. Content analysis of an audiotaped post-antenatal consultation interview with parents obtained their satisfaction scores as well as their comments on physician actions that facilitated their desired participation. Results Five cases, each called a “system—infant at risk”, included 10 parents and 6 neonatologists. From the interviews emerged a blueprint for action by physicians, including communication strategies that parents say facilitated their participation in decision making; such as building trustworthy physician-parent relationships, providing "balanced" information, offering choices, and allowing time to think. Conclusion Parent descriptions indicate that the opportunity to participate to their satisfaction in the clinical antenatal consultation depends on how the physician interacts with them. Practice implications The parent-identified communication strategies facilitate shared decision making regarding treatment in the best interest of the infant at risk to be born at the limit of viability. PMID:27893823

A three-talk model for shared decision making: multistage consultation process.

PubMed

Elwyn, Glyn; Durand, Marie Anne; Song, Julia; Aarts, Johanna; Barr, Paul J; Berger, Zackary; Cochran, Nan; Frosch, Dominick; Galasiński, Dariusz; Gulbrandsen, Pål; Han, Paul K J; Härter, Martin; Kinnersley, Paul; Lloyd, Amy; Mishra, Manish; Perestelo-Perez, Lilisbeth; Scholl, Isabelle; Tomori, Kounosuke; Trevena, Lyndal; Witteman, Holly O; Van der Weijden, Trudy

2017-11-06

Objectives  To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement. Design  Multistage consultation process. Setting  Key informant group, communities of interest, and survey of clinical specialties. Participants  19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties. Results  After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on "team talk," "option talk," and "decision talk," to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals. Conclusions  The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Invited review: Helping dairy farmers to improve economic performance utilizing data-driving decision support tools.

PubMed

Cabrera, V E

2018-01-01

The objective of this review paper is to describe the development and application of a suite of more than 40 computerized dairy farm decision support tools contained at the University of Wisconsin-Madison (UW) Dairy Management website http://DairyMGT.info. These data-driven decision support tools are aimed to help dairy farmers improve their decision-making, environmental stewardship and economic performance. Dairy farm systems are highly dynamic in which changing market conditions and prices, evolving policies and environmental restrictions together with every time more variable climate conditions determine performance. Dairy farm systems are also highly integrated with heavily interrelated components such as the dairy herd, soils, crops, weather and management. Under these premises, it is critical to evaluate a dairy farm following a dynamic integrated system approach. For this approach, it is crucial to use meaningful data records, which are every time more available. These data records should be used within decision support tools for optimal decision-making and economic performance. Decision support tools in the UW-Dairy Management website (http://DairyMGT.info) had been developed using combination and adaptation of multiple methods together with empirical techniques always with the primary goal for these tools to be: (1) highly user-friendly, (2) using the latest software and computer technologies, (3) farm and user specific, (4) grounded on the best scientific information available, (5) remaining relevant throughout time and (6) providing fast, concrete and simple answers to complex farmers' questions. DairyMGT.info is a translational innovative research website in various areas of dairy farm management that include nutrition, reproduction, calf and heifer management, replacement, price risk and environment. This paper discusses the development and application of 20 selected (http://DairyMGT.info) decision support tools.

Multi-objective decision-making model based on CBM for an aircraft fleet

NASA Astrophysics Data System (ADS)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

Computer Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2013-03-01

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

Treatment selection of early stage non-small cell lung cancer: the role of the patient in clinical decision making.

PubMed

Mokhles, S; Nuyttens, J J M E; de Mol, M; Aerts, J G J V; Maat, A P W M; Birim, Ö; Bogers, A J J C; Takkenberg, J J M

2018-01-15

The objective of this study is to investigate the role and experience of early stage non-small cell lung cancer (NSCLC) patient in decision making process concerning treatment selection in the current clinical practice. Stage I-II NSCLC patients (surgery 55 patients, SBRT 29 patients, median age 68) were included in this prospective study and completed a questionnaire that explored: (1) perceived patient knowledge of the advantages and disadvantages of the treatment options, (2) experience with current clinical decision making, and (3) the information that the patient reported to have received from their treating physician. This was assessed by multiple-choice, 1-5 Likert Scale, and open questions. The Decisional Conflict Scale was used to assess the decisional conflict. Health related quality of life (HRQoL) was measured with SF-36 questionnaire. In 19% of patients, there was self-reported perceived lack of knowledge about the advantages and disadvantages of the treatment options. Seventy-four percent of patients felt that they were sufficiently involved in decision-making by their physician, and 81% found it important to be involved in decision making. Forty percent experienced decisional conflict, and one-in-five patients to such an extent that it made them feel unsure about the decision. Subscores with regard to feeling uninformed and on uncertainty, contributed the most to decisional conflict, as 36% felt uninformed and 17% of patients were not satisfied with their decision. HRQoL was not influenced by patient experience with decision-making or patient preferences for shared decision making. Dutch early-stage NSCLC patients find it important to be involved in treatment decision making. Yet a substantial proportion experiences decisional conflict and feels uninformed. Better patient information and/or involvement in treatment-decision-making is needed in order to improve patient knowledge and hopefully reduce decisional conflict.

Fault Management in an Objectives-Based/Risk-Informed View of Safety and Mission Success

NASA Technical Reports Server (NTRS)

Groen, Frank

2012-01-01

Theme of this talk: (1) Net-benefit of activities and decisions derives from objectives (and their priority) -- similarly: need for integration, value of technology/capability. (2) Risk is a lack of confidence that objectives will be met. (2a) Risk-informed decision making requires objectives. (3) Consideration of objectives is central to recent guidance.

The Decision Path Not Taken

PubMed Central

Connor, Charles E.; Stuphorn, Veit

2017-01-01

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

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

DOEpatents

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

2005-02-22

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

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

USGS Publications Warehouse

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

2008-01-01

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

Integrated multi-choice goal programming and multi-segment goal programming for supplier selection considering imperfect-quality and price-quantity discounts in a multiple sourcing environment

NASA Astrophysics Data System (ADS)

Chang, Ching-Ter; Chen, Huang-Mu; Zhuang, Zheng-Yun

2014-05-01

Supplier selection (SS) is a multi-criteria and multi-objective problem, in which multi-segment (e.g. imperfect-quality discount (IQD) and price-quantity discount (PQD)) and multi-aspiration level problems may be significantly important; however, little attention had been given to dealing with both of them simultaneously in the past. This study proposes a model for integrating multi-choice goal programming and multi-segment goal programming to solve the above-mentioned problems by providing the following main contributions: (1) it allows decision-makers to set multiple aspiration levels on the right-hand side of each goal to suit real-world situations, (2) the PQD and IQD conditions are considered in the proposed model simultaneously and (3) the proposed model can solve a SS problem with n suppliers where each supplier offers m IQD with r PQD intervals, where only ? extra binary variables are required. The usefulness of the proposed model is explained using a real case. The results indicate that the proposed model not only can deal with a SS problem with multi-segment and multi-aspiration levels, but also can help the decision-maker to find the appropriate order quantities for each supplier by considering cost, quality and delivery.

Pharmacogenomic Approaches for Automated Medication Risk Assessment in People with Polypharmacy

PubMed Central

Liu, Jiazhen; Friedman, Carol; Finkelstein, Joseph

2018-01-01

Abstract Medication regimen may be optimized based on individual drug efficacy identified by pharmacogenomic testing. However, majority of current pharmacogenomic decision support tools provide assessment only of single drug-gene interactions without taking into account complex drug-drug and drug-drug-gene interactions which are prevalent in people with polypharmacy and can result in adverse drug events or insufficient drug efficacy. The main objective of this project was to develop comprehensive pharmacogenomic decision support for medication risk assessment in people with polypharmacy that simultaneously accounts for multiple drug and gene effects. To achieve this goal, the project addressed two aims: (1) development of comprehensive knowledge repository of actionable pharmacogenes; (2) introduction of scoring approaches reflecting potential adverse effect risk levels of complex medication regimens accounting for pharmacogenomic polymorphisms and multiple drug metabolizing pathways. After pharmacogenomic knowledge repository was introduced, a scoring algorithm has been built and pilot-tested using a limited data set. The resulting total risk score for frequently hospitalized older adults with polypharmacy (72.04±17.84) was statistically significantly different (p<0.05) from the total risk score for older adults with polypharmacy with low hospitalization rate (8.98±2.37). An initial prototype assessment demonstrated feasibility of our approach and identified steps for improving risk scoring algorithms.

Screening of pollution control and clean-up materials for river chemical spills using the multiple case-based reasoning method with a difference-driven revision strategy.

PubMed

Liu, Rentao; Jiang, Jiping; Guo, Liang; Shi, Bin; Liu, Jie; Du, Zhaolin; Wang, Peng

2016-06-01

In-depth filtering of emergency disposal technology (EDT) and materials has been required in the process of environmental pollution emergency disposal. However, an urgent problem that must be solved is how to quickly and accurately select the most appropriate materials for treating a pollution event from the existing spill control and clean-up materials (SCCM). To meet this need, the following objectives were addressed in this study. First, the material base and a case base for environment pollution emergency disposal were established to build a foundation and provide material for SCCM screening. Second, the multiple case-based reasoning model method with a difference-driven revision strategy (DDRS-MCBR) was applied to improve the original dual case-based reasoning model method system, and screening and decision-making was performed for SCCM using this model. Third, an actual environmental pollution accident from 2012 was used as a case study to verify the material base, case base, and screening model. The results demonstrated that the DDRS-MCBR method was fast, efficient, and practical. The DDRS-MCBR method changes the passive situation in which the choice of SCCM screening depends only on the subjective experience of the decision maker and offers a new approach to screening SCCM.

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

PubMed

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

2017-06-01

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

Risk evaluation and monitoring in multiple sclerosis therapeutics.

PubMed

Clanet, Michel C; Wolinsky, Jerry S; Ashton, Raymond J; Hartung, Hans-Peter; Reingold, Stephen C

2014-09-01

Risk for multiple sclerosis (MS) disease-modifying therapies (DMT) must be assessed on an ongoing basis. Early concerns regarding the first-approved DMTs for MS have been mitigated, but recently licensed therapies have been linked to possibly greater risks. The objective of this review is to discuss risk assessment in MS therapeutics based on an international workshop and comprehensive literature search and recommend strategies for risk assessment/monitoring. Assessment and perception of therapeutic risks vary between patients, doctors and regulators. Acceptability of risk depends on the magnitude of risk and the demonstrated clinical benefits of any agent. Safety signals must be distinguishable from chance occurrences in a clinical trial and in long-term use of medications. Post-marketing research is crucial for assessing longer-term safety in large patient cohorts. Reporting of adverse events is becoming more proactive, allowing more rapid identification of risks. Communication about therapeutic risks and their relationship to clinical benefit must involve patients in shared decision making. It is difficult to produce a general risk-assessment algorithm for all MS therapies. Specific algorithms are required for each DMT in every treated-patient population. New and evolving risks must be evaluated and communicated rapidly to allow patients and physicians to be well informed and able to share treatment decisions. © The Author(s) 2013.

Multiple criteria decision analysis for health technology assessment.

PubMed

Thokala, Praveen; Duenas, Alejandra

2012-12-01

Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Evaluating a Web-Based MMR Decision Aid to Support Informed Decision-Making by UK Parents: A Before-and-After Feasibility Study

ERIC Educational Resources Information Center

Jackson, Cath; Cheater, Francine M.; Peacock, Rose; Leask, Julie; Trevena, Lyndal

2010-01-01

Objective: The objective of this feasibility study was to evaluate the acceptability and potential effectiveness of a web-based MMR decision aid in supporting informed decision-making for the MMR vaccine. Design: This was a prospective before-and-after evaluation. Setting: Thirty parents of children eligible for MMR vaccination were recruited from…

Review of foreign body ingestion and esophageal food impaction management in adolescents.

PubMed

Sahn, Benjamin; Mamula, Petar; Ford, Carol A

2014-08-01

Foreign body ingestion is a common clinical scenario among patients of all ages. The immediate risk to the patient ranges from negligible to life threatening. Initial and follow-up management strategies depend on multiple patient and ingested object-related factors. Available literature on this topic tends to focus on the small child or adult, leaving the clinician caring for adolescents to extrapolate this information to guide decision making for individual patients. This article reviews foreign body ingestion literature with important implications to the adolescent patient and raises awareness of some highly dangerous objects such as large button batteries, high-powered magnets, long sharps, narcotic packages, and super absorbent objects. An additional focus includes the management of esophageal food impaction. We highlight the unique aspects to the care of the adolescent with intentional ingestion and co-morbid psychiatric illness. The article concludes by discussing the challenges to prevention of ingestion in the at-risk patient. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

[Using projective tests in forensic psychiatry may lead to wrong conclusions. Only empirically tested tests should be used].

PubMed

Trygg, L; Dåderman, A M; Wiklund, N; Meurling, A W; Lindgren, M; Lidberg, L; Levander, S

2001-06-27

The use of projective and psychometric psychological tests at the Department of Forensic Psychiatry in Stockholm (Huddinge), Sweden, was studied for a population of 60 men, including many patients with neuropsychological disabilities and multiple psychiatric disorders. The results showed that the use of projective tests like Rorschach, Object Relations Test, and House-Tree-Person was more frequent than the use of objective psychometric tests. Neuropsychological test batteries like the Halstead-Reitan Neuropsychological Test Battery or Luria-Nebraska Neuropsychological Battery were not used. The majority of patients were, however, assessed by intelligence scales like the WAIS-R. The questionable reliability and validity of the projective tests, and the risk of subjective interpretations, raise a problem when used in a forensic setting, since the courts' decisions about a sentence to prison or psychiatric care is based on the forensic psychiatric assessment. The use of objective psychometric neuropsychological tests and personality tests is recommended.

Multi-agent Water Resources Management

NASA Astrophysics Data System (ADS)

Castelletti, A.; Giuliani, M.

2011-12-01

Increasing environmental awareness and emerging trends such as water trading, energy market, deregulation and democratization of water-related services are challenging integrated water resources planning and management worldwide. The traditional approach to water management design based on sector-by-sector optimization has to be reshaped to account for multiple interrelated decision-makers and many stakeholders with increasing decision power. Centralized management, though interesting from a conceptual point of view, is unfeasible in most of the modern social and institutional contexts, and often economically inefficient. Coordinated management, where different actors interact within a full open trust exchange paradigm under some institutional supervision is a promising alternative to the ideal centralized solution and the actual uncoordinated practices. This is a significant issue in most of the Southern Alps regulated lakes, where upstream hydropower reservoirs maximize their benefit independently form downstream users; it becomes even more relevant in the case of transboundary systems, where water management upstream affects water availability downstream (e.g. the River Zambesi flowing through Zambia, Zimbabwe and Mozambique or the Red River flowing from South-Western China through Northern Vietnam. In this study we apply Multi-Agent Systems (MAS) theory to design an optimal management in a decentralized way, considering a set of multiple autonomous agents acting in the same environment and taking into account the pay-off of individual water users, which are inherently distributed along the river and need to coordinate to jointly reach their objectives. In this way each real-world actor, representing the decision-making entity (e.g. the operator of a reservoir or a diversion dam) can be represented one-to-one by a computer agent, defined as a computer system that is situated in some environment and that is capable of autonomous action in this environment in order to meet its design objectives. The proposed approach is numerically tested on a synthetic case study, characterized by two multi-purpose reservoirs in cascade, two diversion dams and four different conflicting water uses: hydropower energy production, drinking supply, flooding prevention along the reservoir shores and irrigation supply. The system is therefore composed by four agents: the two operators of the diversion dams, which are purely reactive agents since they simply respond directly to the environment, and the operators of the two reservoirs, which are more complex agents because they have an internal state and their decisions are taken according to a closed-loop control scheme. In particular, the set of agents can act considering only their own objectives or they can coordinate to jointly reach better compromise solutions. Different interaction scenarios between the two extreme behaviours of centralized management and completely non-cooperation are simulated and analysed.

Exploring Scientific Information for Policy Making under Deep Uncertainty

NASA Astrophysics Data System (ADS)

Forni, L.; Galaitsi, S.; Mehta, V. K.; Escobar, M.; Purkey, D. R.; Depsky, N. J.; Lima, N. A.

2016-12-01

Each actor evaluating potential management strategies brings her/his own distinct set of objectives to a complex decision space of system uncertainties. The diversity of these objectives require detailed and rigorous analyses that responds to multifaceted challenges. However, the utility of this information depends on the accessibility of scientific information to decision makers. This paper demonstrates data visualization tools for presenting scientific results to decision makers in two case studies, La Paz/ El Alto, Bolivia, and Yuba County,California. Visualization output from the case studies combines spatiotemporal, multivariate and multirun/multiscenario information to produce information corresponding to the objectives defined by key actors and stakeholders. These tools can manage complex data and distill scientific information into accessible formats. Using the visualizations, scientists and decision makers can navigate the decision space and potential objective trade-offs to facilitate discussion and consensus building. These efforts can support identifying stable negotiatedagreements between different stakeholders.

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

PubMed Central

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

2017-01-01

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

Factors influencing and modifying the decision to pursue genetic testing for skin cancer risk.

PubMed

Fogel, Alexander L; Jaju, Prajakta D; Li, Shufeng; Halpern-Felsher, Bonnie; Tang, Jean Y; Sarin, Kavita Y

2017-05-01

Across cancers, the decision to pursue genetic testing is influenced more by subjective than objective factors. However, skin cancer, which is more prevalent, visual, and multifactorial than many other malignancies, may offer different motivations for pursuing such testing. The primary objective was to determine factors influencing the decision to receive genetic testing for skin cancer risk. A secondary objective was to assess the impact of priming with health questions on the decision to receive testing. We distributed anonymous online surveys through ResearchMatch.org to assess participant health, demographics, motivations, and interest in pursuing genetic testing for skin cancer risk. Two surveys with identical questions but different question ordering were used to assess the secondary objective. We received 3783 responses (64% response rate), and 85.8% desired testing. Subjective factors, including curiosity, perceptions of skin cancer, and anxiety, were the most statistically significant determinants of the decision to pursue testing (P < .001), followed by history of sun exposure (odds ratio 1.85, P < .01) and history of skin cancer (odds ratio 0.5, P = .01). Age and family history of skin cancer did not influence this decision. Participants increasingly chose testing if first queried about health behaviors (P < .0001). The decision to pursue hypothetical testing may differ from in-clinic decision-making. Self-selected, online participants may differ from the general population. Surveys may be subject to response bias. The decision to pursue genetic testing for skin cancer is primarily determined by subjective factors, such as anxiety and curiosity. Health factors, including skin cancer history, also influenced decision-making. Priming with consideration of objective health factors can increase the desire to pursue testing. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Development of an algorithm to provide awareness in choosing study designs for inclusion in systematic reviews of healthcare interventions: a method study

PubMed Central

Peinemann, Frank; Kleijnen, Jos

2015-01-01

Objectives To develop an algorithm that aims to provide guidance and awareness for choosing multiple study designs in systematic reviews of healthcare interventions. Design Method study: (1) To summarise the literature base on the topic. (2) To apply the integration of various study types in systematic reviews. (3) To devise decision points and outline a pragmatic decision tree. (4) To check the plausibility of the algorithm by backtracking its pathways in four systematic reviews. Results (1) The results of our systematic review of the published literature have already been published. (2) We recaptured the experience from our four previously conducted systematic reviews that required the integration of various study types. (3) We chose length of follow-up (long, short), frequency of events (rare, frequent) and types of outcome as decision points (death, disease, discomfort, disability, dissatisfaction) and aligned the study design labels according to the Cochrane Handbook. We also considered practical or ethical concerns, and the problem of unavailable high-quality evidence. While applying the algorithm, disease-specific circumstances and aims of interventions should be considered. (4) We confirmed the plausibility of the pathways of the algorithm. Conclusions We propose that the algorithm can assist to bring seminal features of a systematic review with multiple study designs to the attention of anyone who is planning to conduct a systematic review. It aims to increase awareness and we think that it may reduce the time burden on review authors and may contribute to the production of a higher quality review. PMID:26289450

Food ordering for children in restaurants: multiple sources of influence on decision making

PubMed Central

Castro, Iana A; Williams, Christine B; Madanat, Hala; Pickrel, Julie L; Jun, Hee-Jin; Zive, Michelle; Gahagan, Sheila; Ayala, Guadalupe X

2017-01-01

Objective Restaurants are playing an increasingly important role in children’s dietary intake. Interventions to promote healthy ordering in restaurants have primarily targeted adults. Much remains unknown about how to influence ordering for and by children. Using an ecological lens, the present study sought to identify sources of influence on ordering behaviour for and by children in restaurants. Design A mixed-methods study was conducted using unobtrusive observations of dining parties with children and post-order interviews. Observational data included: child’s gender, person ordering for the child and server interactions with the dining party. Interview data included: child’s age, restaurant visit frequency, timing of child’s decision making, and factors influencing decision making. Setting Ten independent, table-service restaurants in San Diego, CA, USA participated. Subjects Complete observational and interview data were obtained from 102 dining parties with 150 children (aged 3–14 years). Results Taste preferences, family influences and menus impacted ordering. However, most children knew what they intended to order before arriving at the restaurant, especially if they dined there at least monthly. Furthermore, about one-third of children shared their meals with others and all shared meals were ordered from adult (v. children’s) menus. Parents placed most orders, although parental involvement in ordering was less frequent with older children. Servers interacted frequently with children but generally did not recommend menu items or prompt use of the children’s menu. Conclusions Interventions to promote healthy ordering should consider the multiple sources of influence that are operating when ordering for and by children in restaurants. PMID:27334904

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

Scolozzi, Rocco, E-mail: rocco.scolozzi@fmach.it; Geneletti, Davide, E-mail: geneletti@ing.unitn.it

Habitat loss and fragmentation are often concurrent to land conversion and urbanization. Simple application of GIS-based landscape pattern indicators may be not sufficient to support meaningful biodiversity impact assessment. A review of the literature reveals that habitat definition and habitat fragmentation are frequently inadequately considered in environmental assessment, notwithstanding the increasing number of tools and approaches reported in the landscape ecology literature. This paper presents an approach for assessing impacts on habitats on a local scale, where availability of species data is often limited, developed for an alpine valley in northern Italy. The perspective of the methodology is multiple scalemore » and species-oriented, and provides both qualitative and quantitative definitions of impact significance. A qualitative decision model is used to assess ecological values in order to support land-use decisions at the local level. Building on recent studies in the same region, the methodology integrates various approaches, such as landscape graphs, object-oriented rule-based habitat assessment and expert knowledge. The results provide insights into future habitat loss and fragmentation caused by land-use changes, and aim at supporting decision-making in planning and suggesting possible ecological compensation. - Highlights: Black-Right-Pointing-Pointer Many environmental assessments inadequately consider habitat loss and fragmentation. Black-Right-Pointing-Pointer Species-perspective for defining habitat quality and connectivity is claimed. Black-Right-Pointing-Pointer Species-based tools are difficult to be applied with limited availability of data. Black-Right-Pointing-Pointer We propose a species-oriented and multiple scale-based qualitative approach. Black-Right-Pointing-Pointer Advantages include being species-oriented and providing value-based information.« less

Resource Allocation and Outpatient Appointment Scheduling Using Simulation Optimization

PubMed Central

Ling, Teresa Wai Ching; Yeung, Wing Kwan

2017-01-01

This paper studies the real-life problems of outpatient clinics having the multiple objectives of minimizing resource overtime, patient waiting time, and waiting area congestion. In the clinic, there are several patient classes, each of which follows different treatment procedure flow paths through a multiphase and multiserver queuing system with scarce staff and limited space. We incorporate the stochastic factors for the probabilities of the patients being diverted into different flow paths, patient punctuality, arrival times, procedure duration, and the number of accompanied visitors. We present a novel two-stage simulation-based heuristic algorithm to assess various tactical and operational decisions for optimizing the multiple objectives. In stage I, we search for a resource allocation plan, and in stage II, we determine a block appointment schedule by patient class and a service discipline for the daily operational level. We also explore the effects of the separate strategies and their integration to identify the best possible combination. The computational experiments are designed on the basis of data from a study of an ophthalmology clinic in a public hospital. Results show that our approach significantly mitigates the undesirable outcomes by integrating the strategies and increasing the resource flexibility at the bottleneck procedures without adding resources. PMID:29104748

Resource Allocation and Outpatient Appointment Scheduling Using Simulation Optimization.

PubMed

Lin, Carrie Ka Yuk; Ling, Teresa Wai Ching; Yeung, Wing Kwan

2017-01-01

This paper studies the real-life problems of outpatient clinics having the multiple objectives of minimizing resource overtime, patient waiting time, and waiting area congestion. In the clinic, there are several patient classes, each of which follows different treatment procedure flow paths through a multiphase and multiserver queuing system with scarce staff and limited space. We incorporate the stochastic factors for the probabilities of the patients being diverted into different flow paths, patient punctuality, arrival times, procedure duration, and the number of accompanied visitors. We present a novel two-stage simulation-based heuristic algorithm to assess various tactical and operational decisions for optimizing the multiple objectives. In stage I, we search for a resource allocation plan, and in stage II, we determine a block appointment schedule by patient class and a service discipline for the daily operational level. We also explore the effects of the separate strategies and their integration to identify the best possible combination. The computational experiments are designed on the basis of data from a study of an ophthalmology clinic in a public hospital. Results show that our approach significantly mitigates the undesirable outcomes by integrating the strategies and increasing the resource flexibility at the bottleneck procedures without adding resources.

Rapid gist perception of meaningful real-life scenes: Exploring individual and gender differences in multiple categorization tasks

PubMed Central

Vanmarcke, Steven; Wagemans, Johan

2015-01-01

In everyday life, we are generally able to dynamically understand and adapt to socially (ir)elevant encounters, and to make appropriate decisions about these. All of this requires an impressive ability to directly filter and obtain the most informative aspects of a complex visual scene. Such rapid gist perception can be assessed in multiple ways. In the ultrafast categorization paradigm developed by Simon Thorpe et al. (1996), participants get a clear categorization task in advance and succeed at detecting the target object of interest (animal) almost perfectly (even with 20 ms exposures). Since this pioneering work, follow-up studies consistently reported population-level reaction time differences on different categorization tasks, indicating a superordinate advantage (animal versus dog) and effects of perceptual similarity (animals versus vehicles) and object category size (natural versus animal versus dog). In this study, we replicated and extended these separate findings by using a systematic collection of different categorization tasks (varying in presentation time, task demands, and stimuli) and focusing on individual differences in terms of e.g., gender and intelligence. In addition to replicating the main findings from the literature, we find subtle, yet consistent gender differences (women faster than men). PMID:26034569

A combined MOIP-MCDA approach to building and screening atmospheric pollution control strategies in urban regions.

PubMed

Mavrotas, George; Ziomas, Ioannis C; Diakouaki, Danae

2006-07-01

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.

A Combined MOIP-MCDA Approach to Building and Screening Atmospheric Pollution Control Strategies in Urban Regions

NASA Astrophysics Data System (ADS)

Mavrotas, George; Ziomas, Ioannis C.; Diakouaki, Danae

2006-07-01

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.

The reliability of the pass/fail decision for assessments comprised of multiple components

PubMed Central

Möltner, Andreas; Tımbıl, Sevgi; Jünger, Jana

2015-01-01

Objective: The decision having the most serious consequences for a student taking an assessment is the one to pass or fail that student. For this reason, the reliability of the pass/fail decision must be determined for high quality assessments, just as the measurement reliability of the point values. Assessments in a particular subject (graded course credit) are often composed of multiple components that must be passed independently of each other. When “conjunctively” combining separate pass/fail decisions, as with other complex decision rules for passing, adequate methods of analysis are necessary for estimating the accuracy and consistency of these classifications. To date, very few papers have addressed this issue; a generally applicable procedure was published by Douglas and Mislevy in 2010. Using the example of an assessment comprised of several parts that must be passed separately, this study analyzes the reliability underlying the decision to pass or fail students and discusses the impact of an improved method for identifying those who do not fulfill the minimum requirements. Method: The accuracy and consistency of the decision to pass or fail an examinee in the subject cluster Internal Medicine/General Medicine/Clinical Chemistry at the University of Heidelberg’s Faculty of Medicine was investigated. This cluster requires students to separately pass three components (two written exams and an OSCE), whereby students may reattempt to pass each component twice. Our analysis was carried out using the method described by Douglas and Mislevy. Results: Frequently, when complex logical connections exist between the individual pass/fail decisions in the case of low failure rates, only a very low reliability for the overall decision to grant graded course credit can be achieved, even if high reliabilities exist for the various components. For the example analyzed here, the classification accuracy and consistency when conjunctively combining the three individual parts is relatively low with κ=0.49 or κ=0.47, despite the good reliability of over 0.75 for each of the three components. The option to repeat each component twice leads to a situation in which only about half of the candidates who do not satisfy the minimum requirements would fail the overall assessment, while the other half is able to continue their studies despite having deficient knowledge and skills. Conclusion: The method put forth by Douglas and Mislevy allows the analysis of the decision accuracy and consistency for complex combinations of scores from different components. Even in the case of highly reliable components, it is not necessarily so that a reliable pass/fail decision has been reached – for instance in the case of low failure rates. Assessments must be administered with the explicit goal of identifying examinees that do not fulfill the minimum requirements. PMID:26483855

Thresholds for conservation and management: structured decision making as a conceptual framework

USGS Publications Warehouse

Nichols, James D.; Eaton, Mitchell J.; Martin, Julien; Edited by Guntenspergen, Glenn R.

2014-01-01

changes in system dynamics. They are frequently incorporated into ecological models used to project system responses to management actions. Utility thresholds are components of management objectives and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. Decision thresholds are derived from the other components of the decision process.We advocate a structured decision making (SDM) approach within which the following components are identified: objectives (possibly including utility thresholds), potential actions, models (possibly including ecological thresholds), monitoring program, and a solution algorithm (which produces decision thresholds). Adaptive resource management (ARM) is described as a special case of SDM developed for recurrent decision problems that are characterized by uncertainty. We believe that SDM, in general, and ARM, in particular, provide good approaches to conservation and management. Use of SDM and ARM also clarifies the distinct roles of ecological thresholds, utility thresholds, and decision thresholds in informed decision processes.

Image-based topology for sensor gridlocking and association

NASA Astrophysics Data System (ADS)

Stanek, Clay J.; Javidi, Bahram; Yanni, Philip

2002-07-01

Correlation engines have been evolving since the implementation of radar. In modern sensor fusion architectures, correlation and gridlock filtering are required to produce common, continuous, and unambiguous tracks of all objects in the surveillance area. The objective is to provide a unified picture of the theatre or area of interest to battlefield decision makers, ultimately enabling them to make better inferences for future action and eliminate fratricide by reducing ambiguities. Here, correlation refers to association, which in this context is track-to-track association. A related process, gridlock filtering or gridlocking, refers to the reduction in navigation errors and sensor misalignment errors so that one sensor's track data can be accurately transformed into another sensor's coordinate system. As platforms gain multiple sensors, the correlation and gridlocking of tracks become significantly more difficult. Much of the existing correlation technology revolves around various interpretations of the generalized Bayesian decision rule: choose the action that minimizes conditional risk. One implementation of this principle equates the risk minimization statement to the comparison of ratios of a priori probability distributions to thresholds. The binary decision problem phrased in terms of likelihood ratios is also known as the famed Neyman-Pearson hypothesis test. Using another restatement of the principle for a symmetric loss function, risk minimization leads to a decision that maximizes the a posteriori probability distribution. Even for deterministic decision rules, situations can arise in correlation where there are ambiguities. For these situations, a common algorithm used is a sparse assignment technique such as the Munkres or JVC algorithm. Furthermore, associated tracks may be combined with the hope of reducing the positional uncertainty of a target or object identified by an existing track from the information of several fused/correlated tracks. Gridlocking is typically accomplished with some type of least-squares algorithm, such as the Kalman filtering technique, which attempts to locate the best bias error vector estimate from a set of correlated/fused track pairs. Here, we will introduce a new approach to this longstanding problem by adapting many of the familiar concepts from pattern recognition, ones certainly familiar to target recognition applications. Furthermore, we will show how this technique can lend itself to specialized processing, such as that available through an optical or hybrid correlator.

Defining the clinical course of multiple sclerosis

PubMed Central

Reingold, Stephen C.; Cohen, Jeffrey A.; Cutter, Gary R.; Sørensen, Per Soelberg; Thompson, Alan J.; Wolinsky, Jerry S.; Balcer, Laura J.; Banwell, Brenda; Barkhof, Frederik; Bebo, Bruce; Calabresi, Peter A.; Clanet, Michel; Comi, Giancarlo; Fox, Robert J.; Freedman, Mark S.; Goodman, Andrew D.; Inglese, Matilde; Kappos, Ludwig; Kieseier, Bernd C.; Lincoln, John A.; Lubetzki, Catherine; Miller, Aaron E.; Montalban, Xavier; O'Connor, Paul W.; Petkau, John; Pozzilli, Carlo; Rudick, Richard A.; Sormani, Maria Pia; Stüve, Olaf; Waubant, Emmanuelle; Polman, Chris H.

2014-01-01

Accurate clinical course descriptions (phenotypes) of multiple sclerosis (MS) are important for communication, prognostication, design and recruitment of clinical trials, and treatment decision-making. Standardized descriptions published in 1996 based on a survey of international MS experts provided purely clinical phenotypes based on data and consensus at that time, but imaging and biological correlates were lacking. Increased understanding of MS and its pathology, coupled with general concern that the original descriptors may not adequately reflect more recently identified clinical aspects of the disease, prompted a re-examination of MS disease phenotypes by the International Advisory Committee on Clinical Trials of MS. While imaging and biological markers that might provide objective criteria for separating clinical phenotypes are lacking, we propose refined descriptors that include consideration of disease activity (based on clinical relapse rate and imaging findings) and disease progression. Strategies for future research to better define phenotypes are also outlined. PMID:24871874

A management and optimisation model for water supply planning in water deficit areas

NASA Astrophysics Data System (ADS)

Molinos-Senante, María; Hernández-Sancho, Francesc; Mocholí-Arce, Manuel; Sala-Garrido, Ramón

2014-07-01

The integrated water resources management approach has proven to be a suitable option for efficient, equitable and sustainable water management. In water-poor regions experiencing acute and/or chronic shortages, optimisation techniques are a useful tool for supporting the decision process of water allocation. In order to maximise the value of water use, an optimisation model was developed which involves multiple supply sources (conventional and non-conventional) and multiple users. Penalties, representing monetary losses in the event of an unfulfilled water demand, have been incorporated into the objective function. This model represents a novel approach which considers water distribution efficiency and the physical connections between water supply and demand points. Subsequent empirical testing using data from a Spanish Mediterranean river basin demonstrated the usefulness of the global optimisation model to solve existing water imbalances at the river basin level.

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

PubMed

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

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

PubMed

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

2013-06-01

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

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

PubMed

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

2018-07-01

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

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

PubMed

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

2011-01-10

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

Analytical group decision making in natural resources: Methodology and application

USGS Publications Warehouse

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

2000-01-01

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

Integrated Forecast-Decision Systems For River Basin Planning and Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.

2005-12-01

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

Physician styles of decision-making for a complex condition: Type 2 diabetes with co-morbid mental illness.

PubMed

Trachtenberg, Felicia L; Pober, David M; Welch, Lisa C; McKinlay, John B

Variation in physician decisions may reflect personal styles of decision-making, as opposed to singular clinical actions and these styles may be applied differently depending on patient complexity. The objective of this study is to examine clusters of physician decision-making for type 2 diabetes, overall and in the presence of a mental health co-morbidity. This randomized balanced factorial experiment presented video vignettes of a "patient" with diagnosed, but uncontrolled type 2 diabetes. "Patients" were systematically varied by age, sex, race and co-morbidity (depression, schizophrenia with normal or bizarre affect, eczema as control). Two hundred and fifty-six primary care physicians, balanced by gender and experience level, completed a structured interview about clinical management. Cluster analysis identified 3 styles of diabetes management. "Minimalists" (n=84) performed fewer exams or tests compared to "middle of the road" physicians (n=84). "Interventionists" (n=88) suggested more medications and referrals. A second cluster analysis, without control for co-morbidities, identified an additional cluster of "information seekers" (n=15) who requested more additional information and referrals. Physicians ranking schizophrenia higher than diabetes on their problem list were more likely "minimalists" and none were "interventionists" or "information seekers". Variations in clinical management encompass multiple clinical actions and physicians subtly shift these decision-making styles depending on patient co-morbidities. Physicians' practice styles may help explain persistent differences in patient care. Training and continuing education efforts to encourage physicians to implement evidence-based clinical practice should account for general styles of decision-making and for how physicians process complicating comorbidities.

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

PubMed

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

2015-03-21

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

Player-Tracking Technology: Half-Full or Half-Empty Glass?

PubMed

Buchheit, Martin; Simpson, Ben Michael

2017-04-01

With the ongoing development of microtechnology, player tracking has become one of the most important components of load monitoring in team sports. The 3 main objectives of player tracking are better understanding of practice (provide an objective, a posteriori evaluation of external load and locomotor demands of any given session or match), optimization of training-load patterns at the team level, and decision making on individual players' training programs to improve performance and prevent injuries (eg, top-up training vs unloading sequences, return to play progression). This paper discusses the basics of a simple tracking approach and the need to integrate multiple systems. The limitations of some of the most used variables in the field (including metabolic-power measures) are debated, and innovative and potentially new powerful variables are presented. The foundations of a successful player-monitoring system are probably laid on the pitch first, in the way practitioners collect their own tracking data, given the limitations of each variable, and how they report and use all this information, rather than in the technology and the variables per se. Overall, the decision to use any tracking technology or new variable should always be considered with a cost/benefit approach (ie, cost, ease of use, portability, manpower/ability to affect the training program).

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

PubMed

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

2017-08-01

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

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.

Impacts of land-use management on ecosystem services and biodiversity: an agent-based modelling approach

PubMed Central

Heckbert, Scott; Wilson, Jeffrey J.; Vandenbroeck, Andrew J. K.; Cranston, Jerome; Farr, Daniel R.

2016-01-01

The science of ecosystem service (ES) mapping has become increasingly sophisticated over the past 20 years, and examples of successfully integrating ES into management decisions at national and sub-national scales have begun to emerge. However, increasing model sophistication and accuracy—and therefore complexity—may trade-off with ease of use and applicability to real-world decision-making contexts, so it is vital to incorporate the lessons learned from implementation efforts into new model development. Using successful implementation efforts for guidance, we developed an integrated ES modelling system to quantify several ecosystem services: forest timber production and carbon storage, water purification, pollination, and biodiversity. The system is designed to facilitate uptake of ES information into land-use decisions through three principal considerations: (1) using relatively straightforward models that can be readily deployed and interpreted without specialized expertise; (2) using an agent-based modelling framework to enable the incorporation of human decision-making directly within the model; and (3) integration among all ES models to simultaneously demonstrate the effects of a single land-use decision on multiple ES. We present an implementation of the model for a major watershed in Alberta, Canada, and highlight the system’s capabilities to assess a suite of ES under future management decisions, including forestry activities under two alternative timber harvest strategies, and through a scenario modelling analysis exploring different intensities of hypothetical agricultural expansion. By using a modular approach, the modelling system can be readily expanded to evaluate additional ecosystem services or management questions of interest in order to guide land-use decisions to achieve socioeconomic and environmental objectives. PMID:28028479

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.

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

PubMed

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

2018-06-01

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

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

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Jamshidi, Mo

1997-01-01

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

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

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

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

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

Model For Marketing Strategy Decision Based On Multicriteria Decicion Making: A Case Study In Batik Madura Industry

NASA Astrophysics Data System (ADS)

Anna, I. D.; Cahyadi, I.; Yakin, A.

2018-01-01

Selection of marketing strategy is a prominent competitive advantage for small and medium enterprises business development. The selection process is is a multiple criteria decision-making problem, which includes evaluation of various attributes or criteria in a process of strategy formulation. The objective of this paper is to develop a model for the selection of a marketing strategy in Batik Madura industry. The current study proposes an integrated approach based on analytic network process (ANP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine the best strategy for Batik Madura marketing problems. Based on the results of group decision-making technique, this study selected fourteen criteria, including consistency, cost, trend following, customer loyalty, business volume, uniqueness manpower, customer numbers, promotion, branding, bussiness network, outlet location, credibility and the inovation as Batik Madura marketing strategy evaluation criteria. A survey questionnaire developed from literature review was distributed to a sample frame of Batik Madura SMEs in Pamekasan. In the decision procedure step, expert evaluators were asked to establish the decision matrix by comparing the marketing strategy alternatives under each of the individual criteria. Then, considerations obtained from ANP and TOPSIS methods were applied to build the specific criteria constraints and range of the launch strategy in the model. The model in this study demonstrates that, under current business situation, Straight-focus marketing strategy is the best marketing strategy for Batik Madura SMEs in Pamekasan.

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

PubMed

Kuhn, A; Britz, W

2012-01-01

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

Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Data and Tools for Dynamic Management and Decision Support

NASA Technical Reports Server (NTRS)

Humphries, G. R. W.; Naveen, R.; Schwaller, M.; Che-Castaldo, C.; McDowall, P.; Schrimpf, M.; Schrimpf, Michael; Lynch, H. J.

2017-01-01

The Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD) is a web-based, open access, decision-support tool designed to assist scientists, non-governmental organizations and policy-makers working to meet the management objectives as set forth by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and other components of the Antarctic Treaty System (ATS) (that is, Consultative Meetings and the ATS Committee on Environmental Protection). MAPPPD was designed specifically to complement existing efforts such as the CCAMLR Ecosystem Monitoring Program (CEMP) and the ATS site guidelines for visitors. The database underlying MAPPPD includes all publicly available (published and unpublished) count data on emperor, gentoo, Adelie) and chinstrap penguins in Antarctica. Penguin population models are used to assimilate available data into estimates of abundance for each site and year.Results are easily aggregated across multiple sites to obtain abundance estimates over any user-defined area of interest. A front end web interface located at www.penguinmap.com provides free and ready access to the most recent count and modelled data, and can act as a facilitator for data transfer between scientists and Antarctic stakeholders to help inform management decisions for the continent.

Development of an expert system for assessing trumpeter swan breeding habitat in the Northern Rocky Mountains.

USGS Publications Warehouse

Sojda, Richard S.; Cornely, John E.; Howe, Adele E.

2002-01-01

A decision support system for the management of the Rocky Mountain Population of Trumpeter Swans (Cygnus buccinators) is being developed. As part of this, three expert systems are also in development: one for assessing the quality of Trumpeter Swan breeding habitat; one for making water level recommendations in montane, palustrine wetlands; and one for assessing the contribution a particular site can make towards meeting objectives from as flyway perspective. The focus of this paper is the development of the breeding habitat expert system, which currently consists of 157 rules. Out purpose is to provide decision support for issues that appear to be beyond the capability of a single persons to conceptualize and solve. We propose that by involving multiple experts in the development and use of the systems, management will be significantly improved. The knowledge base for the expert system has been developed using standard knowledge engineering techniques with a small team of ecological experts. Knowledge was then coded using production rules organized in decision trees using a commercial expert system development shell. The final system has been deployed on the world wide web.

Orientation priming of grasping decision for drawings of objects and blocks, and words.

PubMed

Chainay, Hanna; Naouri, Lucie; Pavec, Alice

2011-05-01

This study tested the influence of orientation priming on grasping decisions. Two groups of 20 healthy participants had to select a preferred grasping orientation (horizontal, vertical) based on drawings of everyday objects, geometric blocks or object names. Three priming conditions were used: congruent, incongruent and neutral. The facilitating effects of priming were observed in the grasping decision task for drawings of objects and blocks but not object names. The visual information about congruent orientation in the prime quickened participants' responses but had no effect on response accuracy. The results are discussed in the context of the hypothesis that an object automatically potentiates grasping associated with it, and that the on-line visual information is necessary for grasping potentiation to occur. The possibility that the most frequent orientation of familiar objects might be included in object-action representation is also discussed.

Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management

PubMed Central

Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason

2016-01-01

With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM3 ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs. PMID:27983713

Bayesian methodology for the design and interpretation of clinical trials in critical care medicine: a primer for clinicians.

PubMed

Kalil, Andre C; Sun, Junfeng

2014-10-01

To review Bayesian methodology and its utility to clinical decision making and research in the critical care field. Clinical, epidemiological, and biostatistical studies on Bayesian methods in PubMed and Embase from their inception to December 2013. Bayesian methods have been extensively used by a wide range of scientific fields, including astronomy, engineering, chemistry, genetics, physics, geology, paleontology, climatology, cryptography, linguistics, ecology, and computational sciences. The application of medical knowledge in clinical research is analogous to the application of medical knowledge in clinical practice. Bedside physicians have to make most diagnostic and treatment decisions on critically ill patients every day without clear-cut evidence-based medicine (more subjective than objective evidence). Similarly, clinical researchers have to make most decisions about trial design with limited available data. Bayesian methodology allows both subjective and objective aspects of knowledge to be formally measured and transparently incorporated into the design, execution, and interpretation of clinical trials. In addition, various degrees of knowledge and several hypotheses can be tested at the same time in a single clinical trial without the risk of multiplicity. Notably, the Bayesian technology is naturally suited for the interpretation of clinical trial findings for the individualized care of critically ill patients and for the optimization of public health policies. We propose that the application of the versatile Bayesian methodology in conjunction with the conventional statistical methods is not only ripe for actual use in critical care clinical research but it is also a necessary step to maximize the performance of clinical trials and its translation to the practice of critical care medicine.

Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management.

PubMed

Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason

2016-12-15

With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM³ ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs.

A Framework for the Next Generation of Risk Science

PubMed Central

Krewski, Daniel; Andersen, Melvin E.; Paoli, Gregory M.; Chiu, Weihsueh A.; Al-Zoughool, Mustafa; Croteau, Maxine C.; Burgoon, Lyle D.; Cote, Ila

2014-01-01

Objectives: In 2011, the U.S. Environmental Protection Agency initiated the NexGen project to develop a new paradigm for the next generation of risk science. Methods: The NexGen framework was built on three cornerstones: the availability of new data on toxicity pathways made possible by fundamental advances in basic biology and toxicological science, the incorporation of a population health perspective that recognizes that most adverse health outcomes involve multiple determinants, and a renewed focus on new risk assessment methodologies designed to better inform risk management decision making. Results: The NexGen framework has three phases. Phase I (objectives) focuses on problem formulation and scoping, taking into account the risk context and the range of available risk management decision-making options. Phase II (risk assessment) seeks to identify critical toxicity pathway perturbations using new toxicity testing tools and technologies, and to better characterize risks and uncertainties using advanced risk assessment methodologies. Phase III (risk management) involves the development of evidence-based population health risk management strategies of a regulatory, economic, advisory, community-based, or technological nature, using sound principles of risk management decision making. Conclusions: Analysis of a series of case study prototypes indicated that many aspects of the NexGen framework are already beginning to be adopted in practice. Citation: Krewski D, Westphal M, Andersen ME, Paoli GM, Chiu WA, Al-Zoughool M, Croteau MC, Burgoon LD, Cote I. 2014. A framework for the next generation of risk science. Environ Health Perspect 122:796–805; http://dx.doi.org/10.1289/ehp.1307260 PMID:24727499

Age-related deficits in selective attention during encoding increase demands on episodic reconstruction during context retrieval: An ERP study.

PubMed

James, Taylor; Strunk, Jonathan; Arndt, Jason; Duarte, Audrey

2016-06-01

Previous event-related potential (ERP) and neuroimaging evidence suggests that directing attention toward single item-context associations compared to intra-item features at encoding improves context memory performance and reduces demands on strategic retrieval operations in young and older adults. In everyday situations, however, there are multiple event features competing for our attention. It is not currently known how selectively attending to one contextual feature while attempting to ignore another influences context memory performance and the processes that support successful retrieval in the young and old. We investigated this issue in the current ERP study. Young and older participants studied pictures of objects in the presence of two contextual features: a color and a scene, and their attention was directed to the object's relationship with one of those contexts. Participants made context memory decisions for both attended and unattended contexts and rated their confidence in those decisions. Behavioral results showed that while both groups were generally successful in applying selective attention during context encoding, older adults were less confident in their context memory decisions for attended features and showed greater dependence in context memory accuracy for attended and unattended contextual features (i.e., hyper-binding). ERP results were largely consistent between age groups but older adults showed a more pronounced late posterior negativity (LPN) implicated in episodic reconstruction processes. We conclude that age-related suppression deficits during encoding result in reduced selectivity in context memory, thereby increasing subsequent demands on episodic reconstruction processes when sought after details are not readily retrieved. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-criteria decision models for forestry and natural resources management: an annotated bibliography

Treesearch

Joseph E. de Steiguer; Leslie Liberti; Albert Schuler; Bruce Hansen

2003-01-01

Foresters and natural resource managers must balance conflicting objectives when developing land-management plans. Conflicts may encompass economic, environmental, social, cultural, technical, and aesthetic objectives. Selecting the best combination of management uses from numerous objectives is difficult and challenging. Multi-Criteria Decision Models (MCDM) provide a...

Solving for Efficiency or Decision Criteria: When the Non-unique Nature of Solutions Becomes a Benefit

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Ciarleglio, M.; Dulay, M.; Lowry, T. S.; Sharp, J. M.; Barnes, J. W.; Eaton, D. J.; Tidwell, V. C.

2006-12-01

Work in the literature for groundwater allocation emphasizes finding a truly optimal solution, often with the drawback of limiting the reported results to either maximizing net benefit in regional scale models or minimizing pumping costs for localized cases. From a policy perspective, limited insight can be gained from these studies because the results are restricted to a single, efficient solution and they neglect non-market values that may influence a management decision. Conversely, economically derived objective functions tend to exhibit a plateau upon nearing the optimal value. This plateau effect, or non-uniqueness, is actually a positive feature in the behavior of groundwater systems because it demonstrates that multiple management strategies, serving numerous community preferences, may be considered while still achieving similar quantitative results. An optimization problem takes the same set of initial conditions and looks for the most efficient solution while a decision problem looks at a situation and asks for a solution that meets certain user-defined criteria. In other words, the election of an alternative course of action using a decision support system will not always result in selection of the most `optimized' alternative. To broaden the analytical toolset available for science and policy interaction, we have developed a groundwater decision support system (GWDSS) that generates a suite of management alternatives by pairing a combinatorial search algorithm with a numerical groundwater model for consideration by decision makers and stakeholders. Subject to constraints as defined by community concerns, the tabu optimization engine systematically creates hypothetical management scenarios running hundreds, and even thousands, of simulations, and then saving the best performing realizations. Results of the search are then evaluated against stakeholder preference sets using ranking methods to aid in identifying a subset of alternatives for final consideration. Here we present the development of the GWDSS and its use in the decision making process for the Barton Springs segment of the Edwards Aquifer located in Austin Texas. Using hydrogeologic metrics, together with economic estimates and impervious cover valuations, representative rankings are determined. Post search multi-objective analysis reveals that some highly ranked alternatives meet the preference sets of more than one stakeholder and achieve similar quantitative aquifer performance. These results are important to both modelers and policy makers alike.

Analyzing Uncertainty and Risk in the Management of Water Resources in the State Of Texas

NASA Astrophysics Data System (ADS)

Singh, A.; Hauffpauir, R.; Mishra, S.; Lavenue, M.

2010-12-01

The State of Texas updates its state water plan every five years to determine the water demand required to meet its growing population. The plan compiles forecasts of water deficits from state-wide regional water planning groups as well as the water supply strategies to address these deficits. To date, the plan has adopted a deterministic framework, where reference values (e.g., best estimates, worst-case scenario) are used for key factors such as population growth, demand for water, severity of drought, water availability, etc. These key factors can, however, be affected by multiple sources of uncertainties such as - the impact of climate on surface water and groundwater availability, uncertainty in population projections, changes in sectoral composition of the economy, variability in water usage, feasibility of the permitting process, cost of implementation, etc. The objective of this study was to develop a generalized and scalable methodology for addressing uncertainty and risk in water resources management both at the regional and the local water planning level. The study proposes a framework defining the elements of an end-to-end system model that captures the key components of demand, supply and planning modules along with their associated uncertainties. The framework preserves the fundamental elements of the well-established planning process in the State of Texas, promoting an incremental and stakeholder-driven approach to adding different levels of uncertainty (and risk) into the decision-making environment. The uncertainty in the water planning process is broken down into two primary categories: demand uncertainty and supply uncertainty. Uncertainty in Demand is related to the uncertainty in population projections and the per-capita usage rates. Uncertainty in Supply, in turn, is dominated by the uncertainty in future climate conditions. Climate is represented in terms of time series of precipitation, temperature and/or surface evaporation flux for some future time period of interest, which can be obtained as outputs of global climate models (GCMs). These are then linked with hydrologic and water-availability models (WAMs) to estimate water availability for the worst drought conditions under each future climate scenario. Combining the demand scenarios with the water availability scenarios yields multiple scenarios for water shortage (or surplus). Given multiple shortage/surplus scenarios, various water management strategies can be assessed to evaluate the reliability of meeting projected deficits. These reliabilities are then used within a multi-criteria decision-framework to assess trade-offs between various water management objectives, thus helping to make more robust decisions while planning for the water needs of the future.

Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

PubMed

Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu

2016-08-15

Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision. Copyright © 2016 Elsevier B.V. All rights reserved.

Selecting the best rayon in customer’s perspective using fuzzy analytic hierarchy process

NASA Astrophysics Data System (ADS)

Sonjaya, E. G.; Paulus, E.; Hidayat, A.

2018-03-01

Annually, the best Rayon selection is conducted by the assessment team of PT.PLN (Persero) Cirebon with the goal to increase the spirit of company members in providing an improved service for customers. However, there is a problem in multiple criteria decision making in this case, which is the importance intensity of each criterion in the selection are often assessed subjectively. To solve this problem, Fuzzy Analytical Hierarchy Process are used to cover AHP scale deficiency in the form of ‘crisp’ numbers. So, it should be considered to use Fuzzy logic approach to handle uncertainty. Fuzzy approach, especially triangular fuzzy number towards AHP scale, are expected to minimize the handling of subjective input, which then will make a more objective result. Thus, this research was conducted to help the management or assessment team in the selection of the best Rayon with a more objective selection in according to the company criteria.

Conveying the concept of movement in music: An event-related brain potential study.

PubMed

Zhou, Linshu; Jiang, Cunmei; Wu, Yingying; Yang, Yufang

2015-10-01

This study on event-related brain potential investigated whether music can convey the concept of movement. Using a semantic priming paradigm, natural musical excerpts were presented to non-musicians, followed by semantically congruent or incongruent pictures that depicted objects either in motion or at rest. The priming effects were tested in object decision and implicit recognition tasks to distinguish the effects of automatic conceptual activation from response competition. Results showed that in both tasks, pictures that were incongruent to preceding musical excerpts elicited larger N400 than congruent pictures, suggesting that music can prime the representations of movement concepts. Results of the multiple regression analysis showed that movement expression could be well predicted by specific acoustic and musical features, indicating the associations between music per se and the processing of iconic musical meaning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lightweight Expression of Granular Objects (LEGO) Content Modeling Using the SNOMED CT Observables Model to Represent Nursing Assessment Data.

PubMed

Johnson, Christie

2016-01-01

This poster presentation presents a content modeling strategy using the SNOMED CT Observable Model to represent large amounts of detailed clinical data in a consistent and computable manner that can support multiple use cases. Lightweight Expression of Granular Objects (LEGOs) represent question/answer pairs on clinical data collection forms, where a question is modeled by a (usually) post-coordinated SNOMED CT expression. LEGOs transform electronic patient data into a normalized consumable, which means that the expressions can be treated as extensions of the SNOMED CT hierarchies for the purpose of performing subsumption queries and other analytics. Utilizing the LEGO approach for modeling clinical data obtained from a nursing admission assessment provides a foundation for data exchange across disparate information systems and software applications. Clinical data exchange of computable LEGO patient information enables the development of more refined data analytics, data storage and clinical decision support.

Approach to proliferation risk assessment based on multiple objective analysis framework

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

Andrianov, A.; Kuptsov, I.; Studgorodok 1, Obninsk, Kaluga region, 249030

2013-07-01

The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materialsmore » circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk.« less

e-Labs and Work Objects: Towards Digital Health Economies

NASA Astrophysics Data System (ADS)

Ainsworth, John D.; Buchan, Iain E.

The optimal provision of healthcare and public health services requires the synthesis of evidence from multiple disciplines. It is necessary to understand the genetic, environmental, behavioural and social determinants of disease and health-related states; to balance the effectiveness of interventions with their costs; to ensure the maximum safety and acceptability of interventions; and to provide fair access to care services for given populations. Ever expanding databases of knowledge and local health information, and the ability to employ computationally expensive methods, promises much for decisions to be both supported by best evidence and locally relevant. This promise will, however, not be realised without providing health professionals with the tools to make sense of this information rich environment and to collaborate across disciplines. We propose, as a solution to this problem, the e-Lab and Work Objects model as a sense-making platform for digital health economies - bringing together data, methods and people for timely health intelligence.

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

PubMed

Li, Guo; Lv, Fei; Guan, Xu

2014-01-01

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

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

PubMed Central

Lv, Fei; Guan, Xu

2014-01-01

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

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.

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

PubMed

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

2017-01-01

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

Setting conservation management thresholds using a novel participatory modeling approach.

PubMed

Addison, P F E; de Bie, K; Rumpff, L

2015-10-01

We devised a participatory modeling approach for setting management thresholds that show when management intervention is required to address undesirable ecosystem changes. This approach was designed to be used when management thresholds: must be set for environmental indicators in the face of multiple competing objectives; need to incorporate scientific understanding and value judgments; and will be set by participants with limited modeling experience. We applied our approach to a case study where management thresholds were set for a mat-forming brown alga, Hormosira banksii, in a protected area management context. Participants, including management staff and scientists, were involved in a workshop to test the approach, and set management thresholds to address the threat of trampling by visitors to an intertidal rocky reef. The approach involved trading off the environmental objective, to maintain the condition of intertidal reef communities, with social and economic objectives to ensure management intervention was cost-effective. Ecological scenarios, developed using scenario planning, were a key feature that provided the foundation for where to set management thresholds. The scenarios developed represented declines in percent cover of H. banksii that may occur under increased threatening processes. Participants defined 4 discrete management alternatives to address the threat of trampling and estimated the effect of these alternatives on the objectives under each ecological scenario. A weighted additive model was used to aggregate participants' consequence estimates. Model outputs (decision scores) clearly expressed uncertainty, which can be considered by decision makers and used to inform where to set management thresholds. This approach encourages a proactive form of conservation, where management thresholds and associated actions are defined a priori for ecological indicators, rather than reacting to unexpected ecosystem changes in the future. © 2015 The Authors Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Purchasing a Used Car Using Multiple Criteria Decision Making

ERIC Educational Resources Information Center

Edwards, Thomas G.; Chelst, Kenneth R.

2007-01-01

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

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

PubMed Central

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

2016-01-01

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

Optimal Contractor Selection in Construction Industry: The Fuzzy Way

NASA Astrophysics Data System (ADS)

Krishna Rao, M. V.; Kumar, V. S. S.; Rathish Kumar, P.

2018-02-01

A purely price-based approach to contractor selection has been identified as the root cause for many serious project delivery problems. Therefore, the capability of the contractor to execute the project should be evaluated using a multiple set of selection criteria including reputation, past performance, performance potential, financial soundness and other project specific criteria. An industry-wide questionnaire survey was conducted with the objective of identifying the important criteria for adoption in the selection process. In this work, a fuzzy set based model was developed for contractor prequalification/evaluation, by using effective criteria obtained from the percept of construction professionals, taking subjective judgments of decision makers also into consideration. A case study consisting of four alternatives (contractors in the present case) solicited from a public works department of Pondicherry in India, is used to illustrate the effectiveness of the proposed approach. The final selection of contractor is made based on the integrated score or Overall Evaluation Score of the decision alternative in prequalification as well as bid evaluation stages.

Pathologic C-spine fracture with low risk mechanism and normal physical exam.

PubMed

Hunter, Andrew; McGreevy, Jolion; Linden, Judith

2017-09-01

Cervical spinal fracture is a rare, but potentially disabling complication of trauma to the neck. Clinicians often rely on clinical decision rules and guidelines to decide whether or not imaging is necessary when a patient presents with neck pain. Validated clinical guidelines include the Canadian C-Spine Rule and the Nexus criteria. Studies suggest that the risks of a pathologic fracture from a simple rear end collision are negligible. We present a case of an individual who presented to an emergency department (ED) after a low speed motor vehicle collision complaining of lateral neck pain and had multiple subsequent visits for the same complaint with negative exam findings. Ultimately, he was found to have a severely pathologic cervical spine fracture with notable cord compression. Our objective is to discuss the necessity to incorporate clinical decision rules with physician gestalt and the need to take into account co-morbidities of a patient presenting after a minor MVC. Copyright © 2017 Elsevier Inc. All rights reserved.

Demands on attention and the role of response priming in visual discrimination of feature conjunctions.

PubMed

Fournier, Lisa R; Herbert, Rhonda J; Farris, Carrie

2004-10-01

This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less discriminable of these features alone was faster (conjunction benefits) when the task-relevant features differed in discriminability and were consistently mapped to responses. Conjunction benefits were attributed to asynchronous decision priming across attended, task-relevant dimensions. A failure to find conjunction benefits for disjunctive conjunctions was attributed to increased memory demands and variable feature-response mapping for 2- versus single-feature targets. Further, attentional demands were similar between single- and 2-feature targets when response mapping, memory demands, and discriminability of the task-relevant features were equated between targets. Implications of the findings for recent attention models are discussed. (c) 2004 APA, all rights reserved

Emotion and decision making: multiple modulatory neural circuits.

PubMed

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

2014-01-01

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

New Zealand's new alcohol laws: protocol for a mixed-methods evaluation.

PubMed

Maclennan, Brett; Kypri, Kypros; Connor, Jennie; Potiki, Tuari; Room, Robin

2016-01-13

Alcohol consumption is a major cause of mortality and morbidity globally. In response to strong calls from the public for alcohol law reform, the New Zealand Government recently reduced the blood alcohol limit for driving and introduced the Sale and Supply of Alcohol Act which aim to (1) improve community input into local decision-making on alcohol; (2) reduce the availability of alcohol; and (3) reduce hazardous drinking and alcohol-related harm. In this project we seek to evaluate the new laws in terms of these objectives. A policy evaluation framework is proposed to investigate the implementation and outcomes of the reforms. We will use quantitative and qualitative methods, employing a pre-post design. Participants include members of the public, local government staff, iwi (Māori tribal groups that function collectively to support their members) and community group representatives. Data will be collected via postal surveys, interviews and analysis of local government documents. Liquor licensing, police and hospital injury data will also be used. Community input into local government decision-making will be operationalised as: the number of objections per license application and the number of local governments adopting a local alcohol policy (LAP). Outcome measures will be the 'restrictiveness' of LAPs compared to previous policies, the number (per 1000 residents) and density (per square kilometre) of alcohol outlets throughout NZ, and the number of weekend late-night (i.e., post 10 pm) trading hours. For consumption and harm, outcomes will be the prevalence of hazardous drinking, harm from own and others' drinking, community amenity effects, rates of assault, and rates of alcohol-involved traffic crashes. Multiple regression will be used to model how the outcomes vary by local government area from before to after the law changes take effect. These measures will be complemented by qualitative analysis of LAP development and public participation in local decision-making on alcohol. The project will evaluate how well the reforms meet their explicit public health objectives.

Integrating modeling, monitoring, and management to reduce critical uncertainties in water resource decision making.

PubMed

Peterson, James T; Freeman, Mary C

2016-12-01

Stream ecosystems provide multiple, valued services to society, including water supply, waste assimilation, recreation, and habitat for diverse and productive biological communities. Managers striving to sustain these services in the face of changing climate, land uses, and water demands need tools to assess the potential effectiveness of alternative management actions, and often, the resulting tradeoffs between competing objectives. Integrating predictive modeling with monitoring data in an adaptive management framework provides a process by which managers can reduce model uncertainties and thus improve the scientific bases for subsequent decisions. We demonstrate an integration of monitoring data with a dynamic, metapopulation model developed to assess effects of streamflow alteration on fish occupancy in a southeastern US stream system. Although not extensive (collected over three years at nine sites), the monitoring data allowed us to assess and update support for alternative population dynamic models using model probabilities and Bayes rule. We then use the updated model weights to estimate the effects of water withdrawal on stream fish communities and demonstrate how feedback in the form of monitoring data can be used to improve water resource decision making. We conclude that investment in more strategic monitoring, guided by a priori model predictions under alternative hypotheses and an adaptive sampling design, could substantially improve the information available to guide decision-making and management for ecosystem services from lotic systems. Published by Elsevier Ltd.

Decision Support for the Capacity Management of Bronchoscopy Devices: Optimizing the Cost-Efficient Mix of Reusable and Single-Use Devices Through Mathematical Modeling.

PubMed

Edenharter, Günther M; Gartner, Daniel; Pförringer, Dominik

2017-06-01

Increasing costs of material resources challenge hospitals to stay profitable. Particularly in anesthesia departments and intensive care units, bronchoscopes are used for various indications. Inefficient management of single- and multiple-use systems can influence the hospitals' material costs substantially. Using mathematical modeling, we developed a strategic decision support tool to determine the optimum mix of disposable and reusable bronchoscopy devices in the setting of an intensive care unit. A mathematical model with the objective to minimize costs in relation to demand constraints for bronchoscopy devices was formulated. The stochastic model decides whether single-use, multi-use, or a strategically chosen mix of both device types should be used. A decision support tool was developed in which parameters for uncertain demand such as mean, standard deviation, and a reliability parameter can be inserted. Furthermore, reprocessing costs per procedure, procurement, and maintenance costs for devices can be parameterized. Our experiments show for which demand pattern and reliability measure, it is efficient to only use reusable or disposable devices and under which circumstances the combination of both device types is beneficial. To determine the optimum mix of single-use and reusable bronchoscopy devices effectively and efficiently, managers can enter their hospital-specific parameters such as demand and prices into the decision support tool.The software can be downloaded at: https://github.com/drdanielgartner/bronchomix/.

The role of health information sources in decision-making among Hispanic mothers during their children’s first 1000 days of life

PubMed Central

Criss, Shaniece; Woo Baidal, Jennifer A.; Goldman, Roberta E.; Perkins, Meghan; Cunningham, Courtney; Taveras, Elsie M.

2015-01-01

Objective This qualitative research aimed to explore how health information sources inform decision-making among Hispanic mothers during their children’s first 1000 days of life (conception-age 24 months), and to generate appropriate health information sources and communication strategies for future interventions. Methods We conducted 7 focus groups with 49 Hispanic women who were pregnant or had children < 2 years old. Domains included interpersonal and media sources, source trustworthiness, dealing with contradictory information, and how information affects decision-making. We used immersion/crystallization process for analysis. Results Trusted health information sources included health care providers, female and male family members, BabyCenter.com and other Internet sources, selected social media, and television. Some immigrant women reported preferring the Internet citing less established local support networks. Women highlighted the importance of validating health information through checking multiple sources for consistency and resolving contradictory information. Mothers expressed interest in receiving reliable website links from healthcare professionals and outreach to extended family. Conclusion Cultural factors, including immigration status, are important in understanding the use of health information sources and their role in decision-making about pregnancy and child health among Hispanic mothers. Healthcare providers and public health professionals should consider Hispanic mothers health information environment and provide culturally-relevant communication strategies and interventions during this high information-seeking time period. PMID:26122256

Decision-theoretic approach to data acquisition for transit operations planning

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

Ritchie, S.G.

The most costly element of transportation planning and modeling activities in the past has usually been that of data acquisition. This is even truer today when the unit costs of data collection are increasing rapidly and at the same time budgets are severely limited by continuing policies of fiscal austerity in the public sector. The overall objectives of this research were to improve the decisions and decision-making capabilities of transit operators or planners in short-range transit planning, and to improve the quality and cost-effectiveness of associated route or corridor-level data collection and service monitoring activities. A new approach was presentedmore » for sequentially updating the parameters of both simple and multiple linear regression models with stochastic regressors, and for determining the expected value of sample information and expected net gain of sampling for associated sample designs. A new approach was also presented for estimating and updating (both spatially and temporally) the parameters of multinomial logit discrete choice models, and for determining associated optimal sample designs for attribute-based and choice-based sampling methods. The approach provides an effective framework for addressing the issue of optimal sampling method and sample size, which to date have been largely unresolved. The application of these methodologies and the feasibility of the decision-theoretic approach was illustrated with a hypothetical case study example.« less

Natural and Artifactual Kinds: Are Children Realists or Relativists about Categories?

ERIC Educational Resources Information Center

Kalish, Charles

1998-01-01

Four studies assessed whether children and adults saw categorization decisions as objective matters of fact or as invented conventions. Found that preschoolers treated basic-level animal and human-made artifact category decisions as objective, with kinds of animals treated as more objective than kinds of artifacts. Adults' judgments were similar…

Does Evidence Matter? How Middle School Students Make Decisions About Socioscientific Issues

NASA Astrophysics Data System (ADS)

Emery, Katherine Beth

People worldwide are faced with making decisions daily. While many decisions are quick (e.g., what clothes to wear), others, such as those about environmental issues (e.g., overfishing), require more thought and have less immediate outcomes. How one makes such decisions depends on how one interprets, evaluates, and uses evidence. The central objective of this thesis was to investigate environmental science literacy in general, and specifically, to understand how evidence and other factors impact decision-making. I conducted three main studies: First, I provide an example of how decision-making practices affect environmental systems and services through a descriptive case study of Atlantic bluefin tuna overfishing. I reviewed the scientific, historical and cultural factors contributing to a paradox of marine preservation in the Mediterranean and highlighted the need for education and informed decision-making about such social and ecological issues. This study motivated me to investigate how people make decisions about environmental issues. Second, I interviewed middle school students to understand how they describe and evaluate evidence hypothetically and in practice about environmental issues---a key component of environmental literacy. Students discussed how they would evaluate evidence and then were then given a packet containing multiple excerpts of information from conflicting stakeholders about an environmental issue and asked how they would make voting or purchasing decisions about these issues. Findings showed that students' ideas about evaluating evidence (e.g., by scientific and non-scientific criteria) match their practices in part. This study was unique in that it investigated how students evaluate evidence that (1) contradicts other evidence and (2), conflicts with the student's prior positions. Finally, I investigated whether middle school students used evidence when making decisions about socioscientific issues. I hypothesized that holding a strong opinion would decrease the likelihood of changing decisions when presented with additional information. Findings indicated that most students do not change their stance after reading additional evidence. Students were more likely to change their decisions about issues that they cared least about than about issues that they cared most about. Implications for science teaching and learning are discussed.

Development of a decision aid for cardiopulmonary resuscitation and invasive mechanical ventilation in the intensive care unit employing user-centered design and a wiki platform for rapid prototyping

PubMed Central

Witteman, Holly O.; LeBlanc, Annie; Kryworuchko, Jennifer; Heyland, Daren Keith; Ebell, Mark H.; Blair, Louisa; Tapp, Diane; Dupuis, Audrey; Lavoie-Bérard, Carole-Anne; McGinn, Carrie Anna; Légaré, France; Archambault, Patrick Michel

2018-01-01

Background Upon admission to an intensive care unit (ICU), all patients should discuss their goals of care and express their wishes concerning life-sustaining interventions (e.g., cardiopulmonary resuscitation (CPR)). Without such discussions, interventions that prolong life at the cost of decreasing its quality may be used without appropriate guidance from patients. Objectives To adapt an existing decision aid about CPR to create a wiki-based decision aid individually adapted to each patient’s risk factors; and to document the use of a wiki platform for this purpose. Methods We conducted three weeks of ethnographic observation in our ICU to observe intensivists and patients discussing goals of care and to identify their needs regarding decision making. We interviewed intensivists individually. Then we conducted three rounds of rapid prototyping involving 15 patients and 11 health professionals. We recorded and analyzed all discussions, interviews and comments, and collected sociodemographic data. Using a wiki, a website that allows multiple users to contribute or edit content, we adapted the decision aid accordingly and added the Good Outcome Following Attempted Resuscitation (GO-FAR) prediction rule calculator. Results We added discussion of invasive mechanical ventilation. The final decision aid comprises values clarification, risks and benefits of CPR and invasive mechanical ventilation, statistics about CPR, and a synthesis section. We added the GO-FAR prediction calculator as an online adjunct to the decision aid. Although three rounds of rapid prototyping simplified the information in the decision aid, 60% (n = 3/5) of the patients involved in the last cycle still did not understand its purpose. Conclusions Wikis and user-centered design can be used to adapt decision aids to users’ needs and local contexts. Our wiki platform allows other centers to adapt our tools, reducing duplication and accelerating scale-up. Physicians need training in shared decision making skills about goals of care and in using the decision aid. A video version of the decision aid could clarify its purpose. PMID:29447297

An Introduction to the Mission Risk Diagnostic for Incident Management Capabilities (MRD-IMC)

DTIC Science & Technology

2014-05-01

objectives. Analysts applying the MRD- IMC evaluate a set of systemic risk factors (called drivers) to aggregate decision-making data and provide decision...function is in position to achieve its mission and objective(s) [Alberts 2012]. To accomplish this goal, analysts applying the MRD- IMC evaluate a...005 | 3 evaluation of IM processes and capabilities. The MRD- IMC comprises the following three core tasks: 1. Identify the mission and objective(s

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

PubMed

Wolf, Lisa

2013-02-01

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

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

PubMed

Li, Yan

2017-05-25

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

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

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

Open Source Platform Application to Groundwater Characterization and Monitoring

NASA Astrophysics Data System (ADS)

Ntarlagiannis, D.; Day-Lewis, F. D.; Falzone, S.; Lane, J. W., Jr.; Slater, L. D.; Robinson, J.; Hammett, S.

2017-12-01

Groundwater characterization and monitoring commonly rely on the use of multiple point sensors and human labor. Due to the number of sensors, labor, and other resources needed, establishing and maintaining an adequate groundwater monitoring network can be both labor intensive and expensive. To improve and optimize the monitoring network design, open source software and hardware components could potentially provide the platform to control robust and efficient sensors thereby reducing costs and labor. This work presents early attempts to create a groundwater monitoring system incorporating open-source software and hardware that will control the remote operation of multiple sensors along with data management and file transfer functions. The system is built around a Raspberry PI 3, that controls multiple sensors in order to perform on-demand, continuous or `smart decision' measurements while providing flexibility to incorporate additional sensors to meet the demands of different projects. The current objective of our technology is to monitor exchange of ionic tracers between mobile and immobile porosity using a combination of fluid and bulk electrical-conductivity measurements. To meet this objective, our configuration uses four sensors (pH, specific conductance, pressure, temperature) that can monitor the fluid electrical properties of interest and guide the bulk electrical measurement. This system highlights the potential of using open source software and hardware components for earth sciences applications. The versatility of the system makes it ideal for use in a large number of applications, and the low cost allows for high resolution (spatially and temporally) monitoring.

New technology implementation: Technical, economic and political factors

NASA Technical Reports Server (NTRS)

Dean, J. W., Jr.; Susman, G. I.; Porter, P. S.

1985-01-01

An analysis is presented of the process of implementing advanced manufacturing technology, based on studies of numerous organizations. This process is seen as consisting of a series of decisions with technical, economic, and political objectives. Frequency decisions involve specifications, equipment, resources/organization, and location. Problems in implementation are viewed as resulting from tradeoffs among the objectives, the tendency of decision makers to emphasize some objectives at the expense of others, and the propensity of problems to spread from one area to another. Three sets of recommendations, based on this analysis, are presented.

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 flexible object-oriented software framework for developing complex multimedia simulations.

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

Sydelko, P. J.; Dolph, J. E.; Christiansen, J. H.

Decision makers involved in brownfields redevelopment and long-term stewardship must consider environmental conditions, future-use potential, site ownership, area infrastructure, funding resources, cost recovery, regulations, risk and liability management, community relations, and expected return on investment in a comprehensive and integrated fashion to achieve desired results. Successful brownfields redevelopment requires the ability to assess the impacts of redevelopment options on multiple interrelated aspects of the ecosystem, both natural and societal. Computer-based tools, such as simulation models, databases, and geographical information systems (GISs) can be used to address brownfields planning and project execution. The transparent integration of these tools into a comprehensivemore » and dynamic decision support system would greatly enhance the brownfields assessment process. Such a system needs to be able to adapt to shifting and expanding analytical requirements and contexts. The Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-oriented framework for developing and maintaining complex multidisciplinary simulations of a wide variety of application domains. The modeling domain of a specific DIAS-based simulation is determined by (1) software objects that represent the real-world entities that comprise the problem space (atmosphere, watershed, human), and (2) simulation models and other data processing applications that express the dynamic behaviors of the domain entities. Models and applications used to express dynamic behaviors can be either internal or external to DIAS, including existing legacy models written in various languages (FORTRAN, C, etc.). The flexible design framework of DIAS makes the objects adjustable to the context of the problem without a great deal of recoding. The DIAS Spatial Data Set facility allows parameters to vary spatially depending on the simulation context according to any of a number of 1-D, 2-D, or 3-D topologies. DIAS is also capable of interacting with other GIS packages and can import many standard spatial data formats. DIAS simulation capabilities can also be extended by including societal process models. Models that implement societal behaviors of individuals and organizations within larger DIAS-based natural systems simulations allow for interaction and feedback among natural and societal processes. The ability to simulate the complex interplay of multimedia processes makes DIAS a promising tool for constructing applications for comprehensive community planning, including the assessment of multiple development and redevelopment scenarios.« less

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

PubMed

Mühlbacher, Axel C; Kaczynski, Anika

2016-02-01

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

Considering Decision Variable Diversity in Multi-Objective Optimization: Application in Hydrologic Model Calibration

NASA Astrophysics Data System (ADS)

Sahraei, S.; Asadzadeh, M.

2017-12-01

Any modern multi-objective global optimization algorithm should be able to archive a well-distributed set of solutions. While the solution diversity in the objective space has been explored extensively in the literature, little attention has been given to the solution diversity in the decision space. Selection metrics such as the hypervolume contribution and crowding distance calculated in the objective space would guide the search toward solutions that are well-distributed across the objective space. In this study, the diversity of solutions in the decision-space is used as the main selection criteria beside the dominance check in multi-objective optimization. To this end, currently archived solutions are clustered in the decision space and the ones in less crowded clusters are given more chance to be selected for generating new solution. The proposed approach is first tested on benchmark mathematical test problems. Second, it is applied to a hydrologic model calibration problem with more than three objective functions. Results show that the chance of finding more sparse set of high-quality solutions increases, and therefore the analyst would receive a well-diverse set of options with maximum amount of information. Pareto Archived-Dynamically Dimensioned Search, which is an efficient and parsimonious multi-objective optimization algorithm for model calibration, is utilized in this study.