Automatic Generation of Customized, Model Based Information Systems for Operations Management.

DTIC Science & Technology

The paper discusses the need for developing a customized, model based system to support management decision making in the field of operations ... management . It provides a critique of the current approaches available, formulates a framework to classify logistics decisions, and suggests an approach for the automatic development of logistics systems. (Author)

Modeling treatment of ischemic heart disease with partially observable Markov decision processes.

PubMed

Hauskrecht, M; Fraser, H

1998-01-01

Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead they are very often dependent and interleaved over time, mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of Partially observable Markov decision processes (POMDPs) developed and used in operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In the paper, we show how the POMDP framework could be used to model and solve the problem of the management of patients with ischemic heart disease, and point out modeling advantages of the framework over standard decision formalisms.

An Ensemble-Based Forecasting Framework to Optimize Reservoir Releases

NASA Astrophysics Data System (ADS)

Ramaswamy, V.; Saleh, F.

2017-12-01

Increasing frequency of extreme precipitation events are stressing the need to manage water resources on shorter timescales. Short-term management of water resources becomes proactive when inflow forecasts are available and this information can be effectively used in the control strategy. This work investigates the utility of short term hydrological ensemble forecasts for operational decision making during extreme weather events. An advanced automated hydrologic prediction framework integrating a regional scale hydrologic model, GIS datasets and the meteorological ensemble predictions from the European Center for Medium Range Weather Forecasting (ECMWF) was coupled to an implicit multi-objective dynamic programming model to optimize releases from a water supply reservoir. The proposed methodology was evaluated by retrospectively forecasting the inflows to the Oradell reservoir in the Hackensack River basin in New Jersey during the extreme hydrologic event, Hurricane Irene. Additionally, the flexibility of the forecasting framework was investigated by forecasting the inflows from a moderate rainfall event to provide important perspectives on using the framework to assist reservoir operations during moderate events. The proposed forecasting framework seeks to provide a flexible, assistive tool to alleviate the complexity of operational decision-making.

Decision support for green supply chain operations by integrating dynamic simulation and LCA indicators: diaper case study.

PubMed

Adhitya, Arief; Halim, Iskandar; Srinivasan, Rajagopalan

2011-12-01

As the issue of environmental sustainability is becoming an important business factor, companies are now looking for decision support tools to assess the fuller picture of the environmental impacts associated with their manufacturing operations and supply chain (SC) activities. Lifecycle assessment (LCA) is widely used to measure the environmental consequences assignable to a product. However, it is usually limited to a high-level snapshot of the environmental implications over the product value chain without consideration of the dynamics arising from the multitiered structure and the interactions along the SC. This paper proposes a framework for green supply chain management by integrating a SC dynamic simulation and LCA indicators to evaluate both the economic and environmental impacts of various SC decisions such as inventories, distribution network configuration, and ordering policy. The advantages of this framework are demonstrated through an industrially motivated case study involving diaper production. Three distinct scenarios are evaluated to highlight how the proposed approach enables integrated decision support for green SC design and operation.

Simulation and experimental studies of operators` decision styles and crew composition while using an ecological and traditional user interface for the control room of a nuclear power plant

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

Meshkati, N.; Buller, B.J.; Azadeh, M.A.

1995-04-01

The goal of this research is threefold: (1) use of the Skill-, Rule-, and Knowledge-based levels of cognitive control -- the SRK framework -- to develop an integrated information processing conceptual framework (for integration of workstation, job, and team design); (2) to evaluate the user interface component of this framework -- the Ecological display; and (3) to analyze the effect of operators` individual information processing behavior and decision styles on handling plant disturbances plus their performance on, and preference for, Traditional and Ecological user interfaces. A series of studies were conducted. In Part I, a computer simulation model and amore » mathematical model were developed. In Part II, an experiment was designed and conducted at the EBR-II plant of the Argonne National Laboratory-West in Idaho Falls, Idaho. It is concluded that: the integrated SRK-based information processing model for control room operations is superior to the conventional rule-based model; operators` individual decision styles and the combination of their styles play a significant role in effective handling of nuclear power plant disturbances; use of the Ecological interface results in significantly more accurate event diagnosis and recall of various plant parameters, faster response to plant transients, and higher ratings of subject preference; and operators` decision styles affect on both their performance and preference for the Ecological interface.« less

The Best Interest Standard: Same Name but Different Roles in Pediatric Bioethics and Child Rights Frameworks.

PubMed

Ross, Lainie Friedman; Swota, Alissa Hurwitz

2017-01-01

This article explores the intersection of pediatric bioethics and child rights by examining the best interest standard as it operates within the pediatric bioethics framework in the United States and the child rights framework based on the UN 1989 Convention on the Rights of the Child (CRC). While the "best interest of the child" standard is central to both pediatric bioethics and the child rights community, it operates only as a guidance principle, and not as an intervention principle, in decision-making within U.S. pediatric bioethics, whereas it operates as both a guidance and intervention principle in the child rights community. The differences in how the best interest standard is operationalized lead to different roles for the family, the state, and the minor in decision-making processes and outcomes. We examine the recent case of Charlie Gard to illustrate some of these differences.

Real options and asset valuation in competitive energy markets

NASA Astrophysics Data System (ADS)

Oduntan, Adekunle Richard

The focus of this work is to develop a robust valuation framework for physical power assets operating in competitive markets such as peaking or mid-merit thermal power plants and baseload power plants. The goal is to develop a modeling framework that can be adapted to different energy assets with different types of operating flexibilities and technical constraints and which can be employed for various purposes such as capital budgeting, business planning, risk management and strategic bidding planning among others. The valuation framework must also be able to capture the reality of power market rules and opportunities, as well as technical constraints of different assets. The modeling framework developed conceptualizes operating flexibilities of power assets as "switching options' whereby the asset operator decides at every decision point whether to switch from one operating mode to another mutually exclusive mode, within the limits of the equipment constraints of the asset. As a current decision to switch operating modes may affect future operating flexibilities of the asset and hence cash flows, a dynamic optimization framework is employed. The developed framework accounts for the uncertain nature of key value drivers by representing them with appropriate stochastic processes. Specifically, the framework developed conceptualizes the operation of a power asset as a multi-stage decision making problem where the operator has to make a decision at every stage to alter operating mode given currently available information about key value drivers. The problem is then solved dynamically by decomposing it into a series of two-stage sub-problems according to Bellman's optimality principle. The solution algorithm employed is the Least Squares Monte Carlo (LSM) method. The developed valuation framework was adapted for a gas-fired thermal power plant, a peaking hydroelectric power plant and a baseload power plant. This work built on previously published real options valuation methodologies for gas-fired thermal power plants by factoring in uncertainty from gas supply/consumption imbalance which is usually faced by gas-fired power generators. This source of uncertainty arises because of mismatch between natural gas and electricity wholesale markets. Natural gas markets in North America operate on a day-ahead basis while power plants are dispatched in real time. Inability of a power generator to match its gas supply and consumption in real time, leading to unauthorized gas over-run or under-run, attracts penalty charges from the gas supplier to the extent that the generator can not manage the imbalance through other means. By considering an illustrative power plant operating in Ontario, we show effects of gas-imbalance on dispatch strategies on a daily cycling operation basis and the resulting impact on net revenue. Similarly, we employ the developed valuation framework to value a peaking hydroelectric power plant. This application also builds on previous real options valuation work for peaking hydroelectric power plants by considering their operations in a joint energy and ancillary services market. Specifically, the valuation model is developed to capture the value of a peaking power plant whose owner has the flexibility to participate in a joint operating reserve market and an energy market, which is currently the case in the Ontario wholesale power market. The model factors in water inflow uncertainty into the reservoir forebay of a hydroelectric facility and also considers uncertain energy and operating reserve prices. The switching options considered include (i) a joint energy and operating reserve bid (ii) an energy only bid and (iii) a do nothing (idle) strategy. Being an energy limited power plant, by doing nothing at a decision interval, the power asset operator is able to timeshift scarce water for use at a future period when market situations are expected to be better. Finally, the developed valuation framework was employed to optimize life-cycle management decisions of a baseload power plant, such as a nuclear power plant. Given uncertainty of long-term value drivers, including power prices, equipment performance and the relationship between current life cycle spending and future equipment degradation, optimization is carried out with the objective of minimizing overall life-cycle related costs. These life-cycle costs include (i) lost revenue during planned and unplanned outages, (ii) potential costs of future equipment degradation due to inadequate preventative maintenance, and (iii) the direct costs of implementing the life-cycle projects. The switching options in this context include the option to shutdown the power plant in order to execute a given preventative maintenance and inspection project and the option to keep the option "alive" by choosing to delay a planned life-cycle activity.

Entropy-functional-based online adaptive decision fusion framework with application to wildfire detection in video.

PubMed

Gunay, Osman; Toreyin, Behçet Ugur; Kose, Kivanc; Cetin, A Enis

2012-05-01

In this paper, an entropy-functional-based online adaptive decision fusion (EADF) framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular subalgorithm. Decision values are linearly combined with weights that are updated online according to an active fusion method based on performing entropic projections onto convex sets describing subalgorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video-based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrive sequentially, and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.

Planning treatment of ischemic heart disease with partially observable Markov decision processes.

PubMed

Hauskrecht, M; Fraser, H

2000-03-01

Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead, they are very often dependent and interleaved over time. This is mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of partially observable Markov decision processes (POMDPs) developed and used in the operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In this paper, we show how the POMDP framework can be used to model and solve the problem of the management of patients with ischemic heart disease (IHD), and demonstrate the modeling advantages of the framework over standard decision formalisms.

A Decision Support Framework for Feasibility Analysis of International Space Station (ISS) Research Capability Enhancing Options

NASA Technical Reports Server (NTRS)

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

2004-01-01

The assembly and operation of the ISS has generated significant challenges that have ultimately impacted resources available to the program's primary mission: research. To address this, program personnel routinely perform trade-off studies on alternative options to enhance research. The approach, content level of analysis and resulting outputs of these studies vary due to many factors, however, complicating the Program Manager's job of selecting the best option. To address this, the program requested a framework be developed to evaluate multiple research-enhancing options in a thorough, disciplined and repeatable manner, and to identify the best option on the basis of cost, benefit and risk. The resulting framework consisted of a systematic methodology and a decision-support toolset. The framework provides quantifiable and repeatable means for ranking research-enhancing options for the complex and multiple-constraint domain of the space research laboratory. This paper describes the development, verification and validation of this framework and provides observations on its operational use.

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 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.

Human Factors of CC-130 Operations. Volume 5: Human Factors in Decision Making

DTIC Science & Technology

1998-02-01

known about human information processing and decision making. Topics for HFDM training come directly from this theoretical framework . The proposed...The proposed training can be distinguished from other approaches with similar goals (either explicit or implicit) by its base within a theoretical ... framework of human information processing. The differences lie less in the content than in the way the material is organized and shaped by theory. The

Environmental management system for transportation maintenance operations : [technical brief].

DOT National Transportation Integrated Search

2014-04-01

This report provides the framework for the environmental management system to analyze : greenhouse gas emissions from transportation maintenance operations. The system enables user : to compare different scenarios and make informed decisions to minim...

From Planetary Boundaries to national fair shares of the global safe operating space - How can the scales be bridged?

NASA Astrophysics Data System (ADS)

Häyhä, Tiina; Cornell, Sarah; Lucas, Paul; van Vuuren, Detlef; Hoff, Holger

2016-04-01

The planetary boundaries framework proposes precautionary quantitative global limits to the anthropogenic perturbation of crucial Earth system processes. In this way, it marks out a planetary 'safe operating space' for human activities. However, decisions regarding resource use and emissions are mostly made at much smaller scales, mostly by (sub-)national and regional governments, businesses, and other local actors. To operationalize the planetary boundaries, they need to be translated into and aligned with targets that are relevant at these smaller scales. In this paper, we develop a framework that addresses the three dimension of bridging across scales: biophysical, socio-economic and ethical, to provide a consistent universally applicable approach for translating the planetary boundaries into national level context-specific and fair shares of the safe operating space. We discuss our findings in the context of previous studies and their implications for future analyses and policymaking. In this way, we help link the planetary boundaries framework to widely- applied operational and policy concepts for more robust strong sustainability decision-making.

Towards decision support for waiting lists: an operations management view.

PubMed

Vissers, J M; Van Der Bij, J D; Kusters, R J

2001-06-01

This paper considers the phenomenon of waiting lists in a healthcare setting, which is characterised by limitations on the national expenditure, to explore the potentials of an operations management perspective. A reference framework for waiting list management is described, distinguishing different levels of planning in healthcare--national, regional, hospital and process--that each contributes to the existence of waiting lists through managerial decision making. In addition, different underlying mechanisms in demand and supply are distinguished, which together explain the development of waiting lists. It is our contention that within this framework a series of situation specific models should be designed to support communication and decision making. This is illustrated by the modelling of the demand for cataract treatment in a regional setting in the south-eastern part of the Netherlands. An input-output model was developed to support decisions regarding waiting lists. The model projects the demand for treatment at a regional level and makes it possible to evaluate waiting list impacts for different scenarios to meet this demand.

Many-Objective Reservoir Policy Identification and Refinement to Reduce Institutional Myopia in Water Management

NASA Astrophysics Data System (ADS)

Giuliani, M.; Herman, J. D.; Castelletti, A.; Reed, P. M.

2013-12-01

Institutional inertia strongly limits our ability to adapt water reservoir operations to better manage growing water demands as well as their associated uncertainties in a changing climate. Although it has long been recognized that these systems are generally framed in heterogeneous socio-economic contexts involving a myriad of conflicting, non-commensurable operating objectives, our broader understanding of the multiobjective consequences of current operating rules as well as their vulnerability to hydroclimatic uncertainties is severely limited. This study proposes a decision analytic framework to overcome policy inertia and myopia in complex river basin management contexts. The framework combines reservoir policy identification and many-objective optimization under uncertainty to characterize current operations and discover key tradeoffs between alternative policies for balancing evolving demands and system uncertainties. The approach is demonstrated on the Conowingo Dam, located within the Lower Susquehanna River, USA. The Lower Susquehanna River is an interstate water body that has been subject to intensive water management efforts due to the system's competing demands from urban water supply, atomic power plant cooling, hydropower production, and federally regulated environmental flows. Initially our proposed framework uses available streamflow observations to implicitly identify the Conowingo Dam's current but unknown operating policy. This baseline policy is identified by fitting radial basis functions to existing system dynamics. Our assumption in the baseline policy is that the dam operator is represented as a rational agent seeking to maximize primary operational objectives (i.e., guaranteeing the public water supply and maximizing the hydropower revenue). The quality of the identified baseline policy is evaluated by its ability to replicate historical release dynamics. Once identified, the historical baseline policy then provides a means of representing the decision preferences guiding current operations. Our results show that the estimated policy closely captures the dynamics of current releases and flows for the Lower Susquehanna. After identifying the historical baseline policy, our proposed decision analytic framework then combines evolutionary many-objective optimization with visual analytics to discover improved operating policies. Our Lower Susquehanna results confirm that the system's current history-based operations are negatively biased to overestimate the reliability of the reservoir's multi-sector services. Moreover, our proposed framework has successfully identified alternative reservoir policies that are more robust to hydroclimatic uncertainties while being capable of better addressing the tradeoffs across the Conowingo Dam's multi-sector services.

Towards Optimal Operation of the Reservoir System in Upper Yellow River: Incorporating Long- and Short-term Operations and Using Rolling Updated Hydrologic Forecast Information

NASA Astrophysics Data System (ADS)

Si, Y.; Li, X.; Li, T.; Huang, Y.; Yin, D.

2016-12-01

The cascade reservoirs in Upper Yellow River (UYR), one of the largest hydropower bases in China, play a vital role in peak load and frequency regulation for Northwest China Power Grid. The joint operation of this system has been put forward for years whereas has not come into effect due to management difficulties and inflow uncertainties, and thus there is still considerable improvement room for hydropower production. This study presents a decision support framework incorporating long- and short-term operation of the reservoir system. For long-term operation, we maximize hydropower production of the reservoir system using historical hydrological data of multiple years, and derive operating rule curves for storage reservoirs. For short-term operation, we develop a program consisting of three modules, namely hydrologic forecast module, reservoir operation module and coordination module. The coordination module is responsible for calling the hydrologic forecast module to acquire predicted inflow within a short-term horizon, and transferring the information to the reservoir operation module to generate optimal release decision. With the hydrologic forecast information updated, the rolling short-term optimization is iterated until the end of operation period, where the long-term operating curves serve as the ending storage target. As an application, the Digital Yellow River Integrated Model (referred to as "DYRIM", which is specially designed for runoff-sediment simulation in the Yellow River basin by Tsinghua University) is used in the hydrologic forecast module, and the successive linear programming (SLP) in the reservoir operation module. The application in the reservoir system of UYR demonstrates that the framework can effectively support real-time decision making, and ensure both computational accuracy and speed. Furthermore, it is worth noting that the general framework can be extended to any other reservoir system with any or combination of hydrological model(s) to forecast and any solver to optimize the operation of reservoir system.

Development the conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation

NASA Astrophysics Data System (ADS)

Milana; Khan, M. K.; Munive, J. E.

2014-07-01

The importance of maintenance has escalated significantly by the increasing of automation in manufacturing process. This condition switches traditional maintenance perspective of inevitable cost into the business competitive driver. Consequently, maintenance strategy and operation decision needs to be synchronized to business and manufacturing concerns. This paper shows the development of conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO). The framework of KBIMSO is elaborated to show the process of how the KBIMSO works to reach the maintenance decision. By considering the multi-criteria of maintenance decision making, the KB system embedded with GAP and AHP to support integrated maintenance strategy and operation which is novel in this area. The KBIMSO is useful to review the existing maintenance system and give reasonable recommendation of maintenance decisions in respect to business and manufacturing perspective.

Systematic design for trait introgression projects.

PubMed

Cameron, John N; Han, Ye; Wang, Lizhi; Beavis, William D

2017-10-01

Using an Operations Research approach, we demonstrate design of optimal trait introgression projects with respect to competing objectives. We demonstrate an innovative approach for designing Trait Introgression (TI) projects based on optimization principles from Operations Research. If the designs of TI projects are based on clear and measurable objectives, they can be translated into mathematical models with decision variables and constraints that can be translated into Pareto optimality plots associated with any arbitrary selection strategy. The Pareto plots can be used to make rational decisions concerning the trade-offs between maximizing the probability of success while minimizing costs and time. The systematic rigor associated with a cost, time and probability of success (CTP) framework is well suited to designing TI projects that require dynamic decision making. The CTP framework also revealed that previously identified 'best' strategies can be improved to be at least twice as effective without increasing time or expenses.

Combining statistical inference and decisions in ecology

USGS Publications Warehouse

Williams, Perry J.; Hooten, Mevin B.

2016-01-01

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation, and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem.

Comprehensive mitigation framework for concurrent application of multiple clinical practice guidelines.

PubMed

Wilk, Szymon; Michalowski, Martin; Michalowski, Wojtek; Rosu, Daniela; Carrier, Marc; Kezadri-Hamiaz, Mounira

2017-02-01

In this work we propose a comprehensive framework based on first-order logic (FOL) for mitigating (identifying and addressing) interactions between multiple clinical practice guidelines (CPGs) applied to a multi-morbid patient while also considering patient preferences related to the prescribed treatment. With this framework we respond to two fundamental challenges associated with clinical decision support: (1) concurrent application of multiple CPGs and (2) incorporation of patient preferences into the decision making process. We significantly expand our earlier research by (1) proposing a revised and improved mitigation-oriented representation of CPGs and secondary medical knowledge for addressing adverse interactions and incorporating patient preferences and (2) introducing a new mitigation algorithm. Specifically, actionable graphs representing CPGs allow for parallel and temporal activities (decisions and actions). Revision operators representing secondary medical knowledge support temporal interactions and complex revisions across multiple actionable graphs. The mitigation algorithm uses the actionable graphs, revision operators and available (and possibly incomplete) patient information represented in FOL. It relies on a depth-first search strategy to find a valid sequence of revisions and uses theorem proving and model finding techniques to identify applicable revision operators and to establish a management scenario for a given patient if one exists. The management scenario defines a safe (interaction-free) and preferred set of activities together with possible patient states. We illustrate the use of our framework with a clinical case study describing two patients who suffer from chronic kidney disease, hypertension, and atrial fibrillation, and who are managed according to CPGs for these diseases. While in this paper we are primarily concerned with the methodological aspects of mitigation, we also briefly discuss a high-level proof of concept implementation of the proposed framework in the form of a clinical decision support system (CDSS). The proposed mitigation CDSS "insulates" clinicians from the complexities of the FOL representations and provides semantically meaningful summaries of mitigation results. Ultimately we plan to implement the mitigation CDSS within our MET (Mobile Emergency Triage) decision support environment. Copyright © 2016 Elsevier Inc. All rights reserved.

Robustness Metrics: How Are They Calculated, When Should They Be Used and Why Do They Give Different Results?

NASA Astrophysics Data System (ADS)

McPhail, C.; Maier, H. R.; Kwakkel, J. H.; Giuliani, M.; Castelletti, A.; Westra, S.

2018-02-01

Robustness is being used increasingly for decision analysis in relation to deep uncertainty and many metrics have been proposed for its quantification. Recent studies have shown that the application of different robustness metrics can result in different rankings of decision alternatives, but there has been little discussion of what potential causes for this might be. To shed some light on this issue, we present a unifying framework for the calculation of robustness metrics, which assists with understanding how robustness metrics work, when they should be used, and why they sometimes disagree. The framework categorizes the suitability of metrics to a decision-maker based on (1) the decision-context (i.e., the suitability of using absolute performance or regret), (2) the decision-maker's preferred level of risk aversion, and (3) the decision-maker's preference toward maximizing performance, minimizing variance, or some higher-order moment. This article also introduces a conceptual framework describing when relative robustness values of decision alternatives obtained using different metrics are likely to agree and disagree. This is used as a measure of how "stable" the ranking of decision alternatives is when determined using different robustness metrics. The framework is tested on three case studies, including water supply augmentation in Adelaide, Australia, the operation of a multipurpose regulated lake in Italy, and flood protection for a hypothetical river based on a reach of the river Rhine in the Netherlands. The proposed conceptual framework is confirmed by the case study results, providing insight into the reasons for disagreements between rankings obtained using different robustness metrics.

Design and development of bio-inspired framework for reservoir operation optimization

NASA Astrophysics Data System (ADS)

Asvini, M. Sakthi; Amudha, T.

2017-12-01

Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

Commonality in Military Equipment. A Framework to Improve Acquisition Decisions

DTIC Science & Technology

2008-01-01

Improving Acquisition Decisions Chopra, Sunil , and Peter Meindl, Supply Chain Management : Strategy, Planning, Operation, Upper Saddle River, N.J...Personnel Costs in Managing Suppliers and Ordering Parts. The effort to perform these activities may be reduced and simplified through a smaller supply ...a Combined MOS on Mechanic Supply Variability

False alarms and incorrect rejections in an information security center: correlation with the frequency of incidents.

PubMed

Bruno, Thiers; Abrahão, Julia

2012-01-01

This study examines the actions taken by operators aimed at preventing and combating information security incidents at a banking organization. The work utilizes the theoretical framework of ergonomics and cognitive psychology. The method is workplace ergonomic analysis. Its focus is directed towards examining the cognitive dimension of the work environment with special attention to the occurrence of correlations between variability in incident frequency and the results of sign detection actions. It categorizes 45,142 operator decisions according to the theory of signal detection (Sternberg, 2000). It analyzes the correlation between incident proportions (indirectly associated with the cognitive efforts demanded from the operator) and operator decisions. The study demonstrated the existence of a positive correlation between incident proportions and false positive decisions (false alarms). However, this correlation could not be observed in relation to decisions of the false-negative type (incorrect rejection).

Many-objective reservoir policy identification and refinement to reduce policy inertia and myopia in water management

NASA Astrophysics Data System (ADS)

Giuliani, M.; Herman, J. D.; Castelletti, A.; Reed, P.

2014-04-01

This study contributes a decision analytic framework to overcome policy inertia and myopia in complex river basin management contexts. The framework combines reservoir policy identification, many-objective optimization under uncertainty, and visual analytics to characterize current operations and discover key trade-offs between alternative policies for balancing competing demands and system uncertainties. The approach is demonstrated on the Conowingo Dam, located within the Lower Susquehanna River, USA. The Lower Susquehanna River is an interstate water body that has been subject to intensive water management efforts due to competing demands from urban water supply, atomic power plant cooling, hydropower production, and federally regulated environmental flows. We have identified a baseline operating policy for the Conowingo Dam that closely reproduces the dynamics of current releases and flows for the Lower Susquehanna and thus can be used to represent the preferences structure guiding current operations. Starting from this baseline policy, our proposed decision analytic framework then combines evolutionary many-objective optimization with visual analytics to discover new operating policies that better balance the trade-offs within the Lower Susquehanna. Our results confirm that the baseline operating policy, which only considers deterministic historical inflows, significantly overestimates the system's reliability in meeting the reservoir's competing demands. Our proposed framework removes this bias by successfully identifying alternative reservoir policies that are more robust to hydroclimatic uncertainties while also better addressing the trade-offs across the Conowingo Dam's multisector services.

Expanding the base for teaching of percutaneous coronary interventions: the explicit approach.

PubMed

Lanzer, Peter; Prechelt, Lutz

2011-02-15

Accelerate and improve the training and learning process of operators performing percutaneous coronary interventions (PCI). Operator cognitive, in particular decision-making skills and technical skills are a major factor for the success of coronary interventions. Currently, cognitive skills are commonly developed by three methods: (1) Cognitive learning of rules for which statistical evidence is available. This is very incomprehensive and isolates cognitive learning from skill acquisition. (2) Informal tutoring received from experienced operators, and (3) personal experience by trial-and-error are both very slow. We propose in this concept article a conceptual framework to elicit, capture, and transfer expert PCI skills to complement the current approach. This includes the development of an in-depth understanding of the nature of PCI skills, terminology, and nomenclature needed to streamline communication, propensity of reproducible performance assessment, and in particular an explication of intervention planning and intra-intervention decision-making. We illustrate the impact of improved decision-making by simulation results based on a stochastic model of intervention risk. We identify several key concepts that form the basis of this conceptual framework, in particular different risk types and the notions of strategy, interventional module, and tactic. The increasing complexity of cases have brought PCI to the point where the decision-making skills of master operators need to be made explicit to make them systematically learnable such that the skills of beginner and intermediate operators can be improved much faster than is currently possible. Copyright © 2010 Wiley-Liss, Inc.

Combining statistical inference and decisions in ecology.

PubMed

Williams, Perry J; Hooten, Mevin B

2016-09-01

Statistical decision theory (SDT) is a sub-field of decision theory that formally incorporates statistical investigation into a decision-theoretic framework to account for uncertainties in a decision problem. SDT provides a unifying analysis of three types of information: statistical results from a data set, knowledge of the consequences of potential choices (i.e., loss), and prior beliefs about a system. SDT links the theoretical development of a large body of statistical methods, including point estimation, hypothesis testing, and confidence interval estimation. The theory and application of SDT have mainly been developed and published in the fields of mathematics, statistics, operations research, and other decision sciences, but have had limited exposure in ecology. Thus, we provide an introduction to SDT for ecologists and describe its utility for linking the conventionally separate tasks of statistical investigation and decision making in a single framework. We describe the basic framework of both Bayesian and frequentist SDT, its traditional use in statistics, and discuss its application to decision problems that occur in ecology. We demonstrate SDT with two types of decisions: Bayesian point estimation and an applied management problem of selecting a prescribed fire rotation for managing a grassland bird species. Central to SDT, and decision theory in general, are loss functions. Thus, we also provide basic guidance and references for constructing loss functions for an SDT problem. © 2016 by the Ecological Society of America.

Objective criteria ranking framework for renewable energy policy decisions in Nigeria

NASA Astrophysics Data System (ADS)

K, Nwofor O.; N, Dike V.

2016-08-01

We present a framework that seeks to improve the objectivity of renewable energy policy decisions in Nigeria. It consists of expert ranking of resource abundance, resource efficiency and resource environmental comfort in the choice of renewable energy options for large scale power generation. The rankings are converted to a more objective function called Resource Appraisal Function (RAF) using dependence operators derived from logical relationships amongst the various criteria. The preferred option is that with the highest average RAF coupled with the least RAF variance. The method can be extended to more options, more criteria, and more opinions and can be adapted for similar decisions in education, environment and health sectors.

Improving Civil-Military Information Sharing in Peace Support Operations Using a Service-Oriented Approach

DTIC Science & Technology

2011-06-01

solutions that operate reliable under adverse conditions including a bandwidth-limited environment, and provide them with customised information...236 Klein, G. (1998) Sources of Power: How people make decisions, MIT Press, Cambridge, Mass ., USA, 1998 NATO (2007) NATO Architecture Framework

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

PubMed

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

2017-12-01

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

Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

NASA Technical Reports Server (NTRS)

Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

1987-01-01

In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

Measuring Non-Market Values for Hydropower Production and Water Storage on the Colorado River: A White Paper Investigation

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

Lowry, Thomas Stephen; Chermak, Janie M.; Brookshire, David S.

This study presents a conceptual framework for capturing the spatial and temporal aspects of non-market dimensions of value (DOV) and how they vary as the result of policy changes for hydropower generation and developed water uses. The foundation of this project is a literature review that reveals that focused, sector specific valuations are no longer adequate if the goal is to provide decision makers with a complete understanding of their decisions. Rather, estimates of non-market values for informing decisions regarding dam operations and/or other water management alternatives must consider the entire spectrum of market and non-market values, and the tradeoffsmore » (both positive and negative) between those values over time and space, while considering shifting preferences in an uncertain environment. This document describes the history and reasoning for these conclusions and presents a conceptual framework for understanding non-market values as a function of changes to hydropower operations and water resources management.« less

A new fit-for-purpose model testing framework: Decision Crash Tests

NASA Astrophysics Data System (ADS)

Tolson, Bryan; Craig, James

2016-04-01

Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building decisions. In one case, we show the set of model building decisions has a low probability to correctly support the upgrade decision. In the other case, we show evidence suggesting another set of model building decisions has a high probability to correctly support the decision. The proposed DCT framework focuses on what model users typically care about: the management decision in question. The DCT framework will often be very strict and will produce easy to interpret results enabling clear unsuitability determinations. In the past, hydrologic modelling progress has necessarily meant new models and model building methods. Continued progress in hydrologic modelling requires finding clear evidence to motivate researchers to disregard unproductive models and methods and the DCT framework is built to produce this kind of evidence. References: Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry (2009), Crash tests for a standardized evaluation of hydrological models. Hydrology and Earth System Sciences, 13, 1757-1764. Klemeš, V. (1986), Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31 (1), 13-24.

A conceptual framework for negotiating public involvement in municipal waste management decision-making in the UK.

PubMed

Garnett, Kenisha; Cooper, Tim; Longhurst, Philip; Jude, Simon; Tyrrel, Sean

2017-08-01

The technical expertise that politicians relied on in the past to produce cost-effective and environmentally sound solutions no longer provides sufficient justification to approve waste facilities. Local authorities need to find more effective ways to involve stakeholders and communities in decision-making since public acceptance of municipal waste facilities is integral to delivering effective waste strategies. This paper presents findings from a research project that explored attitudes towards greater levels of public involvement in UK waste management decision-making. The study addressed questions of perception, interests, the decision context, the means of engagement and the necessary resources and capacity for adopting a participatory decision process. Adopting a mixed methods approach, the research produced an empirical framework for negotiating the mode and level of public involvement in waste management decision-making. The framework captures and builds on theories of public involvement and the experiences of practitioners, and offers guidance for integrating analysis and deliberation with public groups in different waste management decision contexts. Principles in the framework operate on the premise that the decision about 'more' and 'better' forms of public involvement can be negotiated, based on the nature of the waste problem and wider social context of decision-making. The collection of opinions from the wide range of stakeholders involved in the study has produced new insights for the design of public engagement processes that are context-dependent and 'fit-for-purpose'; these suggest a need for greater inclusivity in the case of contentious technologies and high levels of uncertainty regarding decision outcomes. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Quality Assurance in Victorian Schools: An Approach to School Improvement. The School Review Program in Victoria, Australia: An Evaluation.

ERIC Educational Resources Information Center

Fearnside, Rob

The Victorian school accountability framework is designed specifically for Victorian public schooling in the 1990s. These schools have three chief characteristics: (1) a high level of school autonomy in operational decisions about research allocation, human-resource management, and staff selection; (2) a common framework for curriculum and…

Establishing International Branch Campuses: A Framework for Assessing Opportunities and Risks

ERIC Educational Resources Information Center

Wilkins, Stephen

2016-01-01

At the start of 2016, there were 230 international branch campuses operating worldwide, but of the campuses that were established since the mid-1990s, around 10 per cent have failed. The purpose of this article is to propose a framework that the strategic decision makers in higher education institutions can refer to when evaluating opportunities…

Towards a Context-Aware Proactive Decision Support Framework

DTIC Science & Technology

2013-11-15

initiative that has developed text analytic technology that crosses the semantic gap into the area of event recognition and representation. The...recognizing operational context, and techniques for recognizing context shift. Additional research areas include: • Adequately capturing users...Universal Interaction Context Ontology [12] might serve as a foundation • Instantiating formal models of decision making based on information seeking

Cable Economics.

ERIC Educational Resources Information Center

Cable Television Information Center, Washington, DC.

A guide to the economic factors that influence cable television systems is presented. Designed for local officials who must have some familiarity with cable operations in order to make optimum decisions, the guide analyzes the financial framework of a cable system, not only from the operators viewpoint, but also from the perspective of the…

Naturalistic Decision Making for Power System Operators

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

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

2010-02-01

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

Operator models for delivering municipal solid waste management services in developing countries: Part B: Decision support.

PubMed

Soós, Reka; Whiteman, Andrew D; Wilson, David C; Briciu, Cosmin; Nürnberger, Sofia; Oelz, Barbara; Gunsilius, Ellen; Schwehn, Ekkehard

2017-08-01

This is the second of two papers reporting the results of a major study considering 'operator models' for municipal solid waste management (MSWM) in emerging and developing countries. Part A documents the evidence base, while Part B presents a four-step decision support system for selecting an appropriate operator model in a particular local situation. Step 1 focuses on understanding local problems and framework conditions; Step 2 on formulating and prioritising local objectives; and Step 3 on assessing capacities and conditions, and thus identifying strengths and weaknesses, which underpin selection of the operator model. Step 4A addresses three generic questions, including public versus private operation, inter-municipal co-operation and integration of services. For steps 1-4A, checklists have been developed as decision support tools. Step 4B helps choose locally appropriate models from an evidence-based set of 42 common operator models ( coms); decision support tools here are a detailed catalogue of the coms, setting out advantages and disadvantages of each, and a decision-making flowchart. The decision-making process is iterative, repeating steps 2-4 as required. The advantages of a more formal process include avoiding pre-selection of a particular com known to and favoured by one decision maker, and also its assistance in identifying the possible weaknesses and aspects to consider in the selection and design of operator models. To make the best of whichever operator models are selected, key issues which need to be addressed include the capacity of the public authority as 'client', management in general and financial management in particular.

Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

PubMed

Bennett, Casey C; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal decisions even in complex and uncertain environments. Future work is described that outlines potential lines of research and integration of machine learning algorithms for personalized medicine. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimization of urban water supply portfolios combining infrastructure capacity expansion and water use decisions

NASA Astrophysics Data System (ADS)

Medellin-Azuara, J.; Fraga, C. C. S.; Marques, G.; Mendes, C. A.

2015-12-01

The expansion and operation of urban water supply systems under rapidly growing demands, hydrologic uncertainty, and scarce water supplies requires a strategic combination of various supply sources for added reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources merits decisions of what and when to expand, and how much to use of each available sources accounting for interest rates, economies of scale and hydrologic variability. The present research provides a framework and an integrated methodology that optimizes the expansion of various water supply alternatives using dynamic programming and combining both short term and long term optimization of water use and simulation of water allocation. A case study in Bahia Do Rio Dos Sinos in Southern Brazil is presented. The framework couples an optimization model with quadratic programming model in GAMS with WEAP, a rain runoff simulation models that hosts the water supply infrastructure features and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions and (b) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion. Results also highlight the potential of various water supply alternatives including, conservation, groundwater, and infrastructural enhancements over time. The framework proves its usefulness for planning its transferability to similarly urbanized systems.

Multinational Experiment 7. Outcome 3 - Cyber Domain. Objective 3.3: Concept Framework Version 3.0

DTIC Science & Technology

2012-10-03

experimentation in order to give some parameters for Decision Makers’ actions. A.5 DIFFERENT LEGAL FRAMEWORKS The juridical framework to which we refer, in...material effects (e.g. psychological impact), economic et al, or, especially in the military field, it may affect Operational Security (OPSEC). 7...not expected at all to be run as a mechanistic tool that produces univocal outputs on the base of juridically qualified inputs, making unnecessary

Preserving Range and Airspace Access for the Air Force Mission: Striving for a Strategic Vantage Point

DTIC Science & Technology

2011-01-01

before public and private entities . This is one in a series of RAND reports that addresses improving the Air Force’s ability to connect operational...53 C. Joint Mission Framework ...by the lack of a common framework for making decisions about range use and resource allocation. This situation requires managers at all levels to

Making Financial Decisions. Financial Management Module. Operational Management Programme. Increasing Opportunities for Supervisors and Managers.

ERIC Educational Resources Information Center

Adamson, Jan; And Others

One of a series of three self-instructional units, these materials are aimed at helping British hotel and catering managers improve profits and/or reduce costs in their areas of responsibility. Following a paragraph on how to use the unit and an introduction, section 1 covers control levels as the framework for making decisions. The section…

Contract Management or Self-Operation: A Decision-Making Guide for Higher Education.

ERIC Educational Resources Information Center

Goldstein, Philip J.; And Others

This guide offers an objective framework for deciding whether self-operation or contract management (also known as privatization or "outsourcing") will best serve the goals and objectives of an individual institution of higher education. The guide is organized into four chapters. Chapter 1 briefly outlines the evolution of contract…

General Matthew B. Ridgway: Attributes of Battle Command and Decision-Making

DTIC Science & Technology

1998-02-13

information dominance require the attributes of future battle commanders be different than those of the past? This paper focuses on the intellectual and personality traits of General Matthew B. Ridgway as they apply to operational command and decision-making. These traits are considered essential for analysis and serve as a framework in which to examine their applicability to future command. The essential qualities of an operational commander are divided into two categories: intellect and personality. Each category is further divided into elemental traits. The application

An Advanced Framework for Improving Situational Awareness in Electric Power Grid Operation

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

Chen, Yousu; Huang, Zhenyu; Zhou, Ning

With the deployment of new smart grid technologies and the penetration of renewable energy in power systems, significant uncertainty and variability is being introduced into power grid operation. Traditionally, the Energy Management System (EMS) operates the power grid in a deterministic mode, and thus will not be sufficient for the future control center in a stochastic environment with faster dynamics. One of the main challenges is to improve situational awareness. This paper reviews the current status of power grid operation and presents a vision of improving wide-area situational awareness for a future control center. An advanced framework, consisting of parallelmore » state estimation, state prediction, parallel contingency selection, parallel contingency analysis, and advanced visual analytics, is proposed to provide capabilities needed for better decision support by utilizing high performance computing (HPC) techniques and advanced visual analytic techniques. Research results are presented to support the proposed vision and framework.« less

Model-theoretic framework for sensor data fusion

NASA Astrophysics Data System (ADS)

Zavoleas, Kyriakos P.; Kokar, Mieczyslaw M.

1993-09-01

The main goal of our research in sensory data fusion (SDF) is the development of a systematic approach (a methodology) to designing systems for interpreting sensory information and for reasoning about the situation based upon this information and upon available data bases and knowledge bases. To achieve such a goal, two kinds of subgoals have been set: (1) develop a theoretical framework in which rational design/implementation decisions can be made, and (2) design a prototype SDF system along the lines of the framework. Our initial design of the framework has been described in our previous papers. In this paper we concentrate on the model-theoretic aspects of this framework. We postulate that data are embedded in data models, and information processing mechanisms are embedded in model operators. The paper is devoted to analyzing the classes of model operators and their significance in SDF. We investigate transformation abstraction and fusion operators. A prototype SDF system, fusing data from range and intensity sensors, is presented, exemplifying the structures introduced. Our framework is justified by the fact that it provides modularity, traceability of information flow, and a basis for a specification language for SDF.

Development of Chemical Process Design and Control for ...

EPA Pesticide Factsheets

This contribution describes a novel process systems engineering framework that couples advanced control with sustainability evaluation and decision making for the optimization of process operations to minimize environmental impacts associated with products, materials, and energy. The implemented control strategy combines a biologically inspired method with optimal control concepts for finding more sustainable operating trajectories. The sustainability assessment of process operating points is carried out by using the U.S. E.P.A.’s Gauging Reaction Effectiveness for the ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) tool that provides scores for the selected indicators in the economic, material efficiency, environmental and energy areas. The indicator scores describe process performance on a sustainability measurement scale, effectively determining which operating point is more sustainable if there are more than several steady states for one specific product manufacturing. Through comparisons between a representative benchmark and the optimal steady-states obtained through implementation of the proposed controller, a systematic decision can be made in terms of whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous fermentation process for fuel production, whose materi

Department of Defense Energy and Logistics: Implications of Historic and Future Cost, Risk, and Capability Analysis

NASA Astrophysics Data System (ADS)

Tisa, Paul C.

Every year the DoD spends billions satisfying its large petroleum demand. This spending is highly sensitive to uncontrollable and poorly understood market forces. Additionally, while some stakeholders may not prioritize its monetary cost and risk, energy is fundamentally coupled to other critical factors. Energy, operational capability, and logistics are heavily intertwined and dependent on uncertain security environment and technology futures. These components and their relationships are less understood. Without better characterization, future capabilities may be significantly limited by present-day acquisition decisions. One attempt to demonstrate these costs and risks to decision makers has been through a metric known as the Fully Burdened Cost of Energy (FBCE). FBCE is defined as the commodity price for fuel plus many of these hidden costs. The metric encouraged a valuable conversation and is still required by law. However, most FBCE development stopped before the lessons from that conversation were incorporated. Current implementation is easy to employ but creates little value. Properly characterizing the costs and risks of energy and putting them in a useful tradespace requires a new framework. This research aims to highlight energy's complex role in many aspects of military operations, the critical need to incorporate it in decisions, and a novel framework to do so. It is broken into five parts. The first describes the motivation behind FBCE, the limits of current implementation, and outlines a new framework that aids decisions. Respectively, the second, third, and fourth present a historic analysis of the connections between military capabilities and energy, analyze the recent evolution of this conversation within the DoD, and pull the historic analysis into a revised framework. The final part quantifies the potential impacts of deeply uncertain futures and technological development and introduces an expanded framework that brings capability, energy, and their uncertainty into the same tradespace. The work presented is intended to inform better policies and investment decisions for military acquisitions. The discussion highlights areas within the DoD's understanding of energy that could improve or whose development has faltered. The new metric discussed allows the DoD to better manage and plan for long-term energy-related costs and risk.

Implications of the Naturalistic Decision Making Framework for Information Dominance.

DTIC Science & Technology

1997-07-01

Information Dominance , defined as an operational advantage obtained through superior effectiveness of informational activity. NDM is the study of how people use their experience to make decisions in field settings. Expertise was considered at both the individual and the team level of decision making. The report defines the components of expertise and identifies obstacles to the acquisition of Information Dominance . These obstacles include: (1) excessive data, (2) pre-processed data, (3) excessive procedures, (4) performing formal analyses, (5) passive

Cognitive Systems Modeling and Analysis of Command and Control Systems

NASA Technical Reports Server (NTRS)

Norlander, Arne

2012-01-01

Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.

State Decision-Makers Guide for Hazardous Waste Management: Defining Hazardous Wastes, Problem Recognition, Land Use, Facility Operations, Conceptual Framework, Policy Issues, Transportation.

ERIC Educational Resources Information Center

Corson, Alan; And Others

Presented are key issues to be addressed by state, regional, and local governments and agencies in creating effective hazardous waste management programs. Eight chapters broadly frame the topics which state-level decision makers should consider. These chapters include: (1) definition of hazardous waste; (2) problem definition and recognition; (3)…

A Bayesian paradigm for decision-making in proof-of-concept trials.

PubMed

Pulkstenis, Erik; Patra, Kaushik; Zhang, Jianliang

2017-01-01

Decision-making is central to every phase of drug development, and especially at the proof of concept stage where risk and evidence must be weighed carefully, often in the presence of significant uncertainty. The decision to proceed or not to large expensive Phase 3 trials has significant implications to both patients and sponsors alike. Recent experience has shown that Phase 3 failure rates remain high. We present a flexible Bayesian quantitative decision-making paradigm that evaluates evidence relative to achieving a multilevel target product profile. A framework for operating characteristics is provided that allows the drug developer to design a proof-of-concept trial in light of its ability to support decision-making rather than merely achieve statistical significance. Operating characteristics are shown to be superior to traditional p-value-based methods. In addition, discussion related to sample size considerations, application to interim futility analysis and incorporation of prior historical information is evaluated.

Development of Chemical Process Design and Control for Sustainability

EPA Science Inventory

This contribution describes a novel process systems engineering framework that couples advanced control with sustainability evaluation and decision making for the optimization of process operations to minimize environmental impacts associated with products, materials, and energy....

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

Kastenberg, W.E.; Apostolakis, G.; Dhir, V.K.

Severe accident management can be defined as the use of existing and/or altemative resources, systems and actors to prevent or mitigate a core-melt accident. For each accident sequence and each combination of severe accident management strategies, there may be several options available to the operator, and each involves phenomenological and operational considerations regarding uncertainty. Operational uncertainties include operator, system and instrumentation behavior during an accident. A framework based on decision trees and influence diagrams has been developed which incorporates such criteria as feasibility, effectiveness, and adverse effects, for evaluating potential severe accident management strategies. The framework is also capable ofmore » propagating both data and model uncertainty. It is applied to several potential strategies including PWR cavity flooding, BWR drywell flooding, PWR depressurization and PWR feed and bleed.« less

Cognitive Readiness Assessment and Reporting: An Open Source Mobile Framework for Operational Decision Support and Performance Improvement

ERIC Educational Resources Information Center

Heric, Matthew; Carter, Jenn

2011-01-01

Cognitive readiness (CR) and performance for operational time-critical environments are continuing points of focus for military and academic communities. In response to this need, we designed an open source interactive CR assessment application as a highly adaptive and efficient open source testing administration and analysis tool. It is capable…

On the use of Bayesian decision theory for issuing natural hazard warnings

NASA Astrophysics Data System (ADS)

Economou, T.; Stephenson, D. B.; Rougier, J. C.; Neal, R. A.; Mylne, K. R.

2016-10-01

Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.

On the use of Bayesian decision theory for issuing natural hazard warnings.

PubMed

Economou, T; Stephenson, D B; Rougier, J C; Neal, R A; Mylne, K R

2016-10-01

Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings.

On the use of Bayesian decision theory for issuing natural hazard warnings

PubMed Central

Stephenson, D. B.; Rougier, J. C.; Neal, R. A.; Mylne, K. R.

2016-01-01

Warnings for natural hazards improve societal resilience and are a good example of decision-making under uncertainty. A warning system is only useful if well defined and thus understood by stakeholders. However, most operational warning systems are heuristic: not formally or transparently defined. Bayesian decision theory provides a framework for issuing warnings under uncertainty but has not been fully exploited. Here, a decision theoretic framework is proposed for hazard warnings. The framework allows any number of warning levels and future states of nature, and a mathematical model for constructing the necessary loss functions for both generic and specific end-users is described. The approach is illustrated using one-day ahead warnings of daily severe precipitation over the UK, and compared to the current decision tool used by the UK Met Office. A probability model is proposed to predict precipitation, given ensemble forecast information, and loss functions are constructed for two generic stakeholders: an end-user and a forecaster. Results show that the Met Office tool issues fewer high-level warnings compared with our system for the generic end-user, suggesting the former may not be suitable for risk averse end-users. In addition, raw ensemble forecasts are shown to be unreliable and result in higher losses from warnings. PMID:27843399

Comparison of Selected Weather Translation Products

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak

2017-01-01

Weather is a primary contributor to the air traffic delays within the National Airspace System (NAS). At present, it is the individual decision makers who use weather information and assess its operational impact in creating effective air traffic management solutions. As a result, the estimation of the impact of forecast weather and the quality of ATM response relies on the skill and experience level of the decision maker. FAA Weather-ATM working groups have developed a Weather-ATM integration framework that consists of weather collection, weather translation, ATM impact conversion and ATM decision support. Some weather translation measures have been developed for hypothetical operations such as decentralized free flight, whereas others are meant to be relevant in current operations. This paper does comparative study of two different weather translation products relevant in current operations and finds that these products have strong correlation with each other. Given inaccuracies in prediction of weather, these differences would not be expected to be of significance in statistical study of a large number of decisions made with a look-ahead time of two hours or more.

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

NASA Technical Reports Server (NTRS)

Neilan, James H.; Cross, Charles; Rothhaar, Paul; Tran, Loc; Motter, Mark; Qualls, Garry; Trujillo, Anna; Allen, B. Danette

2016-01-01

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Cost-benefit analysis of alternative fuels and motive designs.

DOT National Transportation Integrated Search

2013-04-01

This project was funded by the Federal Railroad Administration to better understand the potential cost and benefits of using alternative fuels for U.S. freight and passenger locomotive operations. The framework for a decision model was developed by T...

Utilization of a cognitive task analysis for laparoscopic appendectomy to identify differentiated intraoperative teaching objectives.

PubMed

Smink, Douglas S; Peyre, Sarah E; Soybel, David I; Tavakkolizadeh, Ali; Vernon, Ashley H; Anastakis, Dimitri J

2012-04-01

Experts become automated when performing surgery, making it difficult to teach complex procedures to trainees. Cognitive task analysis (CTA) enables experts to articulate operative steps and cognitive decisions in complex procedures such as laparoscopic appendectomy, which can then be used to identify central teaching points. Three local surgeon experts in laparoscopic appendectomy were interviewed using critical decision method-based CTA methodology. Interview transcripts were analyzed, and a cognitive demands table (CDT) was created for each expert. The individual CDTs were reviewed by each expert for completeness and then combined into a master CDT. Percentage agreement on operative steps and decision points was calculated for each expert. The experts then participated in a consensus meeting to review the master CDT. Each surgeon expert was asked to identify in the master CDT the most important teaching objectives for junior-level and senior-level residents. The experts' responses for junior-level and senior-level residents were compared using a χ(2) test. The surgeon experts identified 24 operative steps and 27 decision points. Eighteen of the 24 operative steps (75%) were identified by all 3 surgeon experts. The percentage of operative steps identified was high for each surgeon expert (96% for surgeon 1, 79% for surgeon 2, and 83% for surgeon 3). Of the 27 decision points, only 5 (19%) were identified by all 3 surgeon experts. The percentage of decision points identified varied by surgeon expert (78% for surgeon 1, 59% for surgeon 2, and 48% for surgeon 3). When asked to identify key teaching points, the surgeon experts were more likely to identify operative steps for junior residents (9 operative steps and 6 decision points) and decision points for senior residents (4 operative steps and 13 decision points) (P < .01). CTA can deconstruct the essential operative steps and decision points associated with performing a laparoscopic appendectomy. These results provide a framework to identify key teaching principles to guide intraoperative instruction. These learning objectives could be used to guide resident level-appropriate teaching of an essential general surgery procedure. Copyright © 2012 Elsevier Inc. All rights reserved.

Water resources planning under climate change: Assessing the robustness of real options for the Blue Nile

NASA Astrophysics Data System (ADS)

Jeuland, Marc; Whittington, Dale

2014-03-01

This article presents a methodology for planning new water resources infrastructure investments and operating strategies in a world of climate change uncertainty. It combines a real options (e.g., options to defer, expand, contract, abandon, switch use, or otherwise alter a capital investment) approach with principles drawn from robust decision-making (RDM). RDM comprises a class of methods that are used to identify investment strategies that perform relatively well, compared to the alternatives, across a wide range of plausible future scenarios. Our proposed framework relies on a simulation model that includes linkages between climate change and system hydrology, combined with sensitivity analyses that explore how economic outcomes of investments in new dams vary with forecasts of changing runoff and other uncertainties. To demonstrate the framework, we consider the case of new multipurpose dams along the Blue Nile in Ethiopia. We model flexibility in design and operating decisions—the selection, sizing, and sequencing of new dams, and reservoir operating rules. Results show that there is no single investment plan that performs best across a range of plausible future runoff conditions. The decision-analytic framework is then used to identify dam configurations that are both robust to poor outcomes and sufficiently flexible to capture high upside benefits if favorable future climate and hydrological conditions should arise. The approach could be extended to explore design and operating features of development and adaptation projects other than dams.

Architectural frameworks: defining the structures for implementing learning health systems.

PubMed

Lessard, Lysanne; Michalowski, Wojtek; Fung-Kee-Fung, Michael; Jones, Lori; Grudniewicz, Agnes

2017-06-23

The vision of transforming health systems into learning health systems (LHSs) that rapidly and continuously transform knowledge into improved health outcomes at lower cost is generating increased interest in government agencies, health organizations, and health research communities. While existing initiatives demonstrate that different approaches can succeed in making the LHS vision a reality, they are too varied in their goals, focus, and scale to be reproduced without undue effort. Indeed, the structures necessary to effectively design and implement LHSs on a larger scale are lacking. In this paper, we propose the use of architectural frameworks to develop LHSs that adhere to a recognized vision while being adapted to their specific organizational context. Architectural frameworks are high-level descriptions of an organization as a system; they capture the structure of its main components at varied levels, the interrelationships among these components, and the principles that guide their evolution. Because these frameworks support the analysis of LHSs and allow their outcomes to be simulated, they act as pre-implementation decision-support tools that identify potential barriers and enablers of system development. They thus increase the chances of successful LHS deployment. We present an architectural framework for LHSs that incorporates five dimensions-goals, scientific, social, technical, and ethical-commonly found in the LHS literature. The proposed architectural framework is comprised of six decision layers that model these dimensions. The performance layer models goals, the scientific layer models the scientific dimension, the organizational layer models the social dimension, the data layer and information technology layer model the technical dimension, and the ethics and security layer models the ethical dimension. We describe the types of decisions that must be made within each layer and identify methods to support decision-making. In this paper, we outline a high-level architectural framework grounded in conceptual and empirical LHS literature. Applying this architectural framework can guide the development and implementation of new LHSs and the evolution of existing ones, as it allows for clear and critical understanding of the types of decisions that underlie LHS operations. Further research is required to assess and refine its generalizability and methods.

Plan Execution Interchange Language (PLEXIL)

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Systematic evaluation of atmospheric chemistry-transport model CHIMERE

NASA Astrophysics Data System (ADS)

Khvorostyanov, Dmitry; Menut, Laurent; Mailler, Sylvain; Siour, Guillaume; Couvidat, Florian; Bessagnet, Bertrand; Turquety, Solene

2017-04-01

Regional-scale atmospheric chemistry-transport models (CTM) are used to develop air quality regulatory measures, to support environmentally sensitive decisions in the industry, and to address variety of scientific questions involving the atmospheric composition. Model performance evaluation with measurement data is critical to understand their limits and the degree of confidence in model results. CHIMERE CTM (http://www.lmd.polytechnique.fr/chimere/) is a French national tool for operational forecast and decision support and is widely used in the international research community in various areas of atmospheric chemistry and physics, climate, and environment (http://www.lmd.polytechnique.fr/chimere/CW-articles.php). This work presents the model evaluation framework applied systematically to the new CHIMERE CTM versions in the course of the continuous model development. The framework uses three of the four CTM evaluation types identified by the Environmental Protection Agency (EPA) and the American Meteorological Society (AMS): operational, diagnostic, and dynamic. It allows to compare the overall model performance in subsequent model versions (operational evaluation), identify specific processes and/or model inputs that could be improved (diagnostic evaluation), and test the model sensitivity to the changes in air quality, such as emission reductions and meteorological events (dynamic evaluation). The observation datasets currently used for the evaluation are: EMEP (surface concentrations), AERONET (optical depths), and WOUDC (ozone sounding profiles). The framework is implemented as an automated processing chain and allows interactive exploration of the results via a web interface.

Multi-criteria development and incorporation into decision tools for health technology adoption.

PubMed

Poulin, Paule; Austen, Lea; Scott, Catherine M; Waddell, Cameron D; Dixon, Elijah; Poulin, Michelle; Lafrenière, René

2013-01-01

When introducing new health technologies, decision makers must integrate research evidence with local operational management information to guide decisions about whether and under what conditions the technology will be used. Multi-criteria decision analysis can support the adoption or prioritization of health interventions by using criteria to explicitly articulate the health organization's needs, limitations, and values in addition to evaluating evidence for safety and effectiveness. This paper seeks to describe the development of a framework to create agreed-upon criteria and decision tools to enhance a pre-existing local health technology assessment (HTA) decision support program. The authors compiled a list of published criteria from the literature, consulted with experts to refine the criteria list, and used a modified Delphi process with a group of key stakeholders to review, modify, and validate each criterion. In a workshop setting, the criteria were used to create decision tools. A set of user-validated criteria for new health technology evaluation and adoption was developed and integrated into the local HTA decision support program. Technology evaluation and decision guideline tools were created using these criteria to ensure that the decision process is systematic, consistent, and transparent. This framework can be used by others to develop decision-making criteria and tools to enhance similar technology adoption programs. The development of clear, user-validated criteria for evaluating new technologies adds a critical element to improve decision-making on technology adoption, and the decision tools ensure consistency, transparency, and real-world relevance.

Modeling Real-Time Coordination of Distributed Expertise and Event Response in NASA Mission Control Center Operations

NASA Astrophysics Data System (ADS)

Onken, Jeffrey

This dissertation introduces a multidisciplinary framework for the enabling of future research and analysis of alternatives for control centers for real-time operations of safety-critical systems. The multidisciplinary framework integrates functional and computational models that describe the dynamics in fundamental concepts of previously disparate engineering and psychology research disciplines, such as group performance and processes, supervisory control, situation awareness, events and delays, and expertise. The application in this dissertation is the real-time operations within the NASA Mission Control Center in Houston, TX. This dissertation operationalizes the framework into a model and simulation, which simulates the functional and computational models in the framework according to user-configured scenarios for a NASA human-spaceflight mission. The model and simulation generates data according to the effectiveness of the mission-control team in supporting the completion of mission objectives and detecting, isolating, and recovering from anomalies. Accompanying the multidisciplinary framework is a proof of concept, which demonstrates the feasibility of such a framework. The proof of concept demonstrates that variability occurs where expected based on the models. The proof of concept also demonstrates that the data generated from the model and simulation is useful for analyzing and comparing MCC configuration alternatives because an investigator can give a diverse set of scenarios to the simulation and the output compared in detail to inform decisions about the effect of MCC configurations on mission operations performance.

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

A Robust Decision-Making Technique for Water Management under Decadal Scale Climate Variability

NASA Astrophysics Data System (ADS)

Callihan, L.; Zagona, E. A.; Rajagopalan, B.

2013-12-01

Robust decision making, a flexible and dynamic approach to managing water resources in light of deep uncertainties associated with climate variability at inter-annual to decadal time scales, is an analytical framework that detects when a system is in or approaching a vulnerable state. It provides decision makers the opportunity to implement strategies that both address the vulnerabilities and perform well over a wide range of plausible future scenarios. A strategy that performs acceptably over a wide range of possible future states is not likely to be optimal with respect to the actual future state. The degree of success--the ability to avoid vulnerable states and operate efficiently--thus depends on the skill in projecting future states and the ability to select the most efficient strategies to address vulnerabilities. This research develops a robust decision making framework that incorporates new methods of decadal scale projections with selection of efficient strategies. Previous approaches to water resources planning under inter-annual climate variability combining skillful seasonal flow forecasts with climatology for subsequent years are not skillful for medium term (i.e. decadal scale) projections as decision makers are not able to plan adequately to avoid vulnerabilities. We address this need by integrating skillful decadal scale streamflow projections into the robust decision making framework and making the probability distribution of this projection available to the decision making logic. The range of possible future hydrologic scenarios can be defined using a variety of nonparametric methods. Once defined, an ensemble projection of decadal flow scenarios are generated from a wavelet-based spectral K-nearest-neighbor resampling approach using historical and paleo-reconstructed data. This method has been shown to generate skillful medium term projections with a rich variety of natural variability. The current state of the system in combination with the probability distribution of the projected flow ensembles enables the selection of appropriate decision options. This process is repeated for each year of the planning horizon--resulting in system outcomes that can be evaluated on their performance and resiliency. The research utilizes the RiverSMART suite of software modeling and analysis tools developed under the Bureau of Reclamation's WaterSMART initiative and built around the RiverWare modeling environment. A case study is developed for the Gunnison and Upper Colorado River Basins. The ability to mitigate vulnerability using the framework is gauged by system performance indicators that measure the ability of the system to meet various water demands (i.e. agriculture, environmental flows, hydropower etc.). Options and strategies for addressing vulnerabilities include measures such as conservation, reallocation and adjustments to operational policy. In addition to being able to mitigate vulnerabilities, options and strategies are evaluated based on benefits, costs and reliability. Flow ensembles are also simulated to incorporate mean and variance from climate change projections for the planning horizon and the above robust decision-making framework is applied to evaluate its performance under changing climate.

Naturalistic Decision Making in Power Grid Operations: Implications for Dispatcher Training and Usability Testing

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

Greitzer, Frank L.; Podmore, Robin

2008-11-17

The focus of the present study is on improved training approaches to accelerate learning and improved methods for analyzing effectiveness of tools within a high-fidelity power grid simulated environment. A theory-based model has been developed to document and understand the mental processes that an expert power system operator uses when making critical decisions. The theoretical foundation for the method is based on the concepts of situation awareness, the methods of cognitive task analysis, and the naturalistic decision making (NDM) approach of Recognition Primed Decision Making. The method has been systematically explored and refined as part of a capability demonstration ofmore » a high-fidelity real-time power system simulator under normal and emergency conditions. To examine NDM processes, we analyzed transcripts of operator-to-operator conversations during the simulated scenario to reveal and assess NDM-based performance criteria. The results of the analysis indicate that the proposed framework can be used constructively to map or assess the Situation Awareness Level of the operators at each point in the scenario. We can also identify the mental models and mental simulations that the operators employ at different points in the scenario. This report documents the method, describes elements of the model, and provides appendices that document the simulation scenario and the associated mental models used by operators in the scenario.« less

Towards a Decision Support System for Space Flight Operations

NASA Technical Reports Server (NTRS)

Meshkat, Leila; Hogle, Charles; Ruszkowski, James

2013-01-01

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the three increments of this vision. These increments include (1) hardware and software system components and interfaces with the NASA ground system, (2) uncertainty management and (3) re-planning and automated execution. Each of these increments provide value independently; but some may also enable building of a subsequent increment.

Integrated framework to capture the interdependencies between transportation and energy sectors due to policy decisions.

DOT National Transportation Integrated Search

2014-05-01

Currently, transportation and energy sectors are developed, managed, and operated independently of : one another. Due to the non-renewable nature of fossil fuels, energy security has evolved into a : strategic goal for the United States. The transpor...

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.

A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

NASA Astrophysics Data System (ADS)

Coyne, Kevin Anthony

The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional branching events and provide a better representation of the IDAC cognitive model. An operator decision-making engine capable of responding to dynamic changes in situational context was implemented. The IDAC human performance model was fully integrated with a detailed nuclear plant model in order to realistically simulate plant accident scenarios. Finally, the improved ADS-IDAC model was calibrated, validated, and updated using actual nuclear plant crew performance data. This research led to the following general conclusions: (1) A relatively small number of branching rules are capable of efficiently capturing a wide spectrum of crew-to-crew variabilities. (2) Compared to traditional static risk assessment methods, ADS-IDAC can provide a more realistic and integrated assessment of human error events by directly determining the effect of operator behaviors on plant thermal hydraulic parameters. (3) The ADS-IDAC approach provides an efficient framework for capturing actual operator performance data such as timing of operator actions, mental models, and decision-making activities.

Supporting Private Sector Decision-Making with NOAA's Interim Climate Data Records (ICDRs)

NASA Astrophysics Data System (ADS)

Privette, J. L.; Glance, W. J.; Cecil, D.; Bates, J. J.

2012-12-01

NOAA initiated its Climate Data Record Program (CDRP) in 2009 to operationally provide authoritative satellite Climate Data Records (CDRs) to the government and the private sector. The CDRs are based primarily on 35+ years of meteorological satellite and in situ data collected by NOAA and the Department of Defense. To date, the Program has transitioned 14 CDRs from research to initial operations. In the past year, the CDRP developed and implemented a framework to continuously extend historical CDRs using Interim Climate Data Records (ICDRs). ICDRs are "first batch" CDRs generated within several days of observation using official CDR algorithms and processes. ICDRs are required by decision support systems and other near-term applications which need current data that are fully consistent with homogeneous historical records. For example, an electrical power utility may need temperature and precipitation ICDRs to optimally identify, in both time and space, the "nearest" historical analog period to recent weather. The utility could then use the contemporaneous business data from that period to inform current decision-making. In addition to their homogeneity and consistency, ICDRs are more complete than operational weather products since ICDR processing can await upstream data delays that can negate data value for weather forecasting. However, the operational nature of ICDRs means their uncertainties typically can be improved through reprocessing once better sensor calibration and characterization data become available. Therefore, ICDRs may be considered valuable but temporary placeholders. However, the "trigger" for electing to update a given record involves many considerations, including cost, latency, downstream dependencies and scientific significance. This presentation provides an update on NOAA's CDR Program, focusing on the new CDRs transitioned to operations in 2012 and the ICDR framework -- including update decision criteria -- used to extend CDRs and meet the needs of near-term applications as well as climate monitoring and indicators activities.

A Rationale and Framework for Establishing a Systems Engineering Community Within the Department of the Army

DTIC Science & Technology

2011-03-01

transition into the ranks of employees. • Make contact not solely with students , but with all those who impact their decision-making: parents, teachers ...SUBTITLE A Rationale and Framework for Establishing a Systems Engineering Community Within the Department of the Army 6. AUTHOR( S ) Alan Clayton...fields the most operationally effective military force in the world. However, fielding such a force has been challenging, as seen by the multiple

Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

NASA Astrophysics Data System (ADS)

Shafiee-Jood, M.; Cai, X.

2017-12-01

Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

Defining when to offer operative treatment for intrahepatic cholangiocarcinoma: A regret-based decision curves analysis.

PubMed

Bagante, Fabio; Spolverato, Gaya; Cucchetti, Alessandro; Gani, Faiz; Popescu, Irinel; Ruzzenente, Andrea; Marques, Hugo P; Aldrighetti, Luca; Gamblin, T Clark; Maithel, Shishir K; Sandroussi, Charbel; Bauer, Todd W; Shen, Feng; Poultsides, George A; Marsh, James Wallis; Guglielmi, Alfredo; Pawlik, Timothy M

2016-07-01

Regret-based decision curve analysis (DCA) is a framework that assesses the medical decision process according to physician attitudes (expected regret) relative to disease-based factors. We sought to apply this methodology to decisions around the operative management of intrahepatic cholangiocarcinoma (ICC). Utilizing a multicentric database of 799 patients who underwent liver resection for ICC, we developed a prognostic nomogram. DCA tested 3 strategies: (1) perform an operation on all patients, (2) never perform an operation, and (3) use the nomogram to select patients for an operation. Four preoperative variables were included in the nomogram: major vascular invasion (HR = 1.36), tumor number (multifocal, HR = 1.18), tumor size (>5 cm, HR = 1.45), and suspicious lymph nodes on imaging (HR = 1.47; all P < .05). The regret-DCA was assessed using an online survey of 50 physicians, expert in the treatment of ICC. For a patient with a multifocal ICC, largest lesion measuring >5 cm, one suspicious malignant lymph node, and vascular invasion on imaging, the 1-year predicted survival was 52% according to the nomogram. Based on the therapeutic decision of the regret-DCA, 60% of physicians would advise against an operation for this scenario. Conversely, all physicians recommended an operation to a patient with an early ICC (single nodule measuring 3 cm, no suspicious lymph nodes, and no vascular invasion at imaging). By integrating a nomogram based on preoperative variables and a regret-based DCA, we were able to define the elements of how decisions rely on medical knowledge (postoperative survival predicted by a nomogram, severity disease assessment) and physician attitudes (regret of commission and omission). Copyright © 2016 Elsevier Inc. All rights reserved.

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics

PubMed Central

2017-01-01

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration. PMID:29065473

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.

PubMed

Sotelo Monge, Marco Antonio; Maestre Vidal, Jorge; García Villalba, Luis Javier

2017-10-21

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration.

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

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

Cetiner, Sacit M; Kisner, Roger A; Muhlheim, Michael David

2015-07-01

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or nomore » human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.« less

Advanced Information Technology in Simulation Based Life Cycle Design

NASA Technical Reports Server (NTRS)

Renaud, John E.

2003-01-01

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.

How to use multi-criteria decision analysis methods for reimbursement decision-making in healthcare: a step-by-step guide.

PubMed

Diaby, Vakaramoko; Goeree, Ron

2014-02-01

In recent years, the quest for more comprehensiveness, structure and transparency in reimbursement decision-making in healthcare has prompted the research into alternative decision-making frameworks. In this environment, multi-criteria decision analysis (MCDA) is arising as a valuable tool to support healthcare decision-making. In this paper, we present the main MCDA decision support methods (elementary methods, value-based measurement models, goal programming models and outranking models) using a case study approach. For each family of methods, an example of how an MCDA model would operate in a real decision-making context is presented from a critical perspective, highlighting the parameters setting, the selection of the appropriate evaluation model as well as the role of sensitivity and robustness analyses. This study aims to provide a step-by-step guide on how to use MCDA methods for reimbursement decision-making in healthcare.

Ecosystem informaties for natural history data - Developing an integrated framework for biological and geographic data

EPA Science Inventory

Threats to the ecological integrity of marine and estuarine systems operate over many spatial scales, from nutrient enrichment at watershed/estuarine linkages to invasive species and climate change at regional/global scales. Decision support tools and information systems needed t...

New framework and decision support tool to warrant detour operations during freeway corridor incident management.

DOT National Transportation Integrated Search

2013-05-01

Up to 60% of freeway delays are due to non-recurrent congestion caused by reduced capacity on a freeway section coupled with long incident : durations. In such conditions, if proper detour strategies could be implemented in time, traffic could circum...

A Framework to Improve Surgeon Communication in High-Stakes Surgical Decisions: Best Case/Worst Case.

PubMed

Taylor, Lauren J; Nabozny, Michael J; Steffens, Nicole M; Tucholka, Jennifer L; Brasel, Karen J; Johnson, Sara K; Zelenski, Amy; Rathouz, Paul J; Zhao, Qianqian; Kwekkeboom, Kristine L; Campbell, Toby C; Schwarze, Margaret L

2017-06-01

Although many older adults prefer to avoid burdensome interventions with limited ability to preserve their functional status, aggressive treatments, including surgery, are common near the end of life. Shared decision making is critical to achieve value-concordant treatment decisions and minimize unwanted care. However, communication in the acute inpatient setting is challenging. To evaluate the proof of concept of an intervention to teach surgeons to use the Best Case/Worst Case framework as a strategy to change surgeon communication and promote shared decision making during high-stakes surgical decisions. Our prospective pre-post study was conducted from June 2014 to August 2015, and data were analyzed using a mixed methods approach. The data were drawn from decision-making conversations between 32 older inpatients with an acute nonemergent surgical problem, 30 family members, and 25 surgeons at 1 tertiary care hospital in Madison, Wisconsin. A 2-hour training session to teach each study-enrolled surgeon to use the Best Case/Worst Case communication framework. We scored conversation transcripts using OPTION 5, an observer measure of shared decision making, and used qualitative content analysis to characterize patterns in conversation structure, description of outcomes, and deliberation over treatment alternatives. The study participants were patients aged 68 to 95 years (n = 32), 44% of whom had 5 or more comorbid conditions; family members of patients (n = 30); and surgeons (n = 17). The median OPTION 5 score improved from 41 preintervention (interquartile range, 26-66) to 74 after Best Case/Worst Case training (interquartile range, 60-81). Before training, surgeons described the patient's problem in conjunction with an operative solution, directed deliberation over options, listed discrete procedural risks, and did not integrate preferences into a treatment recommendation. After training, surgeons using Best Case/Worst Case clearly presented a choice between treatments, described a range of postoperative trajectories including functional decline, and involved patients and families in deliberation. Using the Best Case/Worst Case framework changed surgeon communication by shifting the focus of decision-making conversations from an isolated surgical problem to a discussion about treatment alternatives and outcomes. This intervention can help surgeons structure challenging conversations to promote shared decision making in the acute setting.

E-HOSPITAL - A Digital Workbench for Hospital Operations and Services Planning Using Information Technology and Algebraic Languages.

PubMed

Gartner, Daniel; Padman, Rema

2017-01-01

In this paper, we describe the development of a unified framework and a digital workbench for the strategic, tactical and operational hospital management plan driven by information technology and analytics. The workbench can be used not only by multiple stakeholders in the healthcare delivery setting, but also for pedagogical purposes on topics such as healthcare analytics, services management, and information systems. This tool combines the three classical hierarchical decision-making levels in one integrated environment. At each level, several decision problems can be chosen. Extensions of mathematical models from the literature are presented and incorporated into the digital platform. In a case study using real-world data, we demonstrate how we used the workbench to inform strategic capacity planning decisions in a multi-hospital, multi-stakeholder setting in the United Kingdom.

Issues in Developing a Normative Descriptive Model for Dyadic Decision Making

NASA Technical Reports Server (NTRS)

Serfaty, D.; Kleinman, D. L.

1984-01-01

Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.

Energy Systems Integration: Data Call -- Become a Data Partner

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

2017-01-01

This project aims to advance the understanding of costs associated with integrating PV onto the electric power distribution system while maintaining reliable grid operations. We have developed a bottom-up framework for calculating these costs as a function of PV penetration levels on specific feeders. This framework will used to inform and improve utility planning decisions, increase the transparency and speed associated with the interconnection process, and provide policymakers with more information on the total cost of energy from PV.

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.

Site-Based Management: Avoiding Disaster While Sharing Decision Making.

ERIC Educational Resources Information Center

Sorenson, Larry Dean

This paper argues that many site-based management practices do not represent true empowerment and are not founded on a consensual framework of values, goals, and priorities developed by educational stakeholders. In addition, they often lack clearly stated operating principles. The paper distinguishes between site-based management (SBM) and…

Integrated Strategic Planning and Analysis Network Increment 4 (ISPAN Inc 4)

DTIC Science & Technology

2016-03-01

Defense Acquisition Executive DoD - Department of Defense DoDAF - DoD Architecture Framework FD - Full Deployment FDD - Full Deployment Decision FY...Inc 4 will achieve FDD completion criteria when: 1) the system meets all the KPP thresholds as verified through an Initial Operational Test and

The GRADE Evidence to Decision (EtD) framework for health system and public health decisions.

PubMed

Moberg, Jenny; Oxman, Andrew D; Rosenbaum, Sarah; Schünemann, Holger J; Guyatt, Gordon; Flottorp, Signe; Glenton, Claire; Lewin, Simon; Morelli, Angela; Rada, Gabriel; Alonso-Coello, Pablo

2018-05-29

To describe a framework for people making and using evidence-informed health system and public health recommendations and decisions. We developed the GRADE Evidence to Decision (EtD) framework for health system and public health decisions as part of the DECIDE project, in which we simultaneously developed frameworks for these and other types of healthcare decisions, including clinical recommendations, coverage decisions and decisions about diagnostic tests. Building on GRADE EtD tables, we used an iterative approach, including brainstorming, consultation of the literature and with stakeholders, and an international survey of policy-makers. We applied the framework to diverse examples, conducted workshops and user testing with health system and public health guideline developers and policy-makers, and observed and tested its use in real-life guideline panels. All the GRADE EtD frameworks share the same basic structure, including sections for formulating the question, making an assessment and drawing conclusions. Criteria listed in the assessment section of the health system and public health framework cover the important factors for making these types of decisions; in addition to the effects and economic impact of an option, the priority of the problem, the impact of the option on equity, and its acceptability and feasibility are important considerations that can inform both whether and how to implement an option. Because health system and public health interventions are often complex, detailed implementation considerations should be made when making a decision. The certainty of the evidence is often low or very low, but decision-makers must still act. Monitoring and evaluation are therefore often important considerations for these types of decisions. We illustrate the different components of the EtD framework for health system and public health decisions by presenting their application in a framework adapted from a real-life guideline. This framework provides a structured and transparent approach to support policy-making informed by the best available research evidence, while making the basis for decisions accessible to those whom they will affect. The health system and public health EtD framework can also be used to facilitate dissemination of recommendations and enable decision-makers to adopt, and adapt, recommendations or decisions.

Automating Mission Scheduling for Space-Based Observatories

NASA Technical Reports Server (NTRS)

Pell, Barney; Muscettola, Nicola; Hansson, Othar; Mohan, Sunil

1998-01-01

In this paper we describe the use of our planning and scheduling framework, HSTS, to reduce the complexity of science mission planning. This work is part of an overall project to enable a small team of scientists to control the operations of a spacecraft. The present process is highly labor intensive. Users (scientists and operators) rely on a non-codified understanding of the different spacecraft subsystems and of their operating constraints. They use a variety of software tools to support their decision making process. This paper considers the types of decision making that need to be supported/automated, the nature of the domain constraints and the capabilities needed to address them successfully, and the nature of external software systems with which the core planning/scheduling engine needs to interact. HSTS has been applied to science scheduling for EUVE and Cassini and is being adapted to support autonomous spacecraft operations in the New Millennium initiative.

Creating a process for incorporating epidemiological modelling into outbreak management decisions.

PubMed

Akselrod, Hana; Mercon, Monica; Kirkeby Risoe, Petter; Schlegelmilch, Jeffrey; McGovern, Joanne; Bogucki, Sandy

2012-01-01

Modern computational models of infectious diseases greatly enhance our ability to understand new infectious threats and assess the effects of different interventions. The recently-released CDC Framework for Preventing Infectious Diseases calls for increased use of predictive modelling of epidemic emergence for public health preparedness. Currently, the utility of these technologies in preparedness and response to outbreaks is limited by gaps between modelling output and information requirements for incident management. The authors propose an operational structure that will facilitate integration of modelling capabilities into action planning for outbreak management, using the Incident Command System (ICS) and Synchronization Matrix framework. It is designed to be adaptable and scalable for use by state and local planners under the National Response Framework (NRF) and Emergency Support Function #8 (ESF-8). Specific epidemiological modelling requirements are described, and integrated with the core processes for public health emergency decision support. These methods can be used in checklist format to align prospective or real-time modelling output with anticipated decision points, and guide strategic situational assessments at the community level. It is anticipated that formalising these processes will facilitate translation of the CDC's policy guidance from theory to practice during public health emergencies involving infectious outbreaks.

Making the most of data: An information selection and assessment framework to improve water systems operations

NASA Astrophysics Data System (ADS)

Giuliani, M.; Pianosi, F.; Castelletti, A.

2015-11-01

Advances in Environmental monitoring systems are making a wide range of data available at increasingly higher temporal and spatial resolution. This creates an opportunity to enhance real-time understanding of water systems conditions and to improve prediction of their future evolution, ultimately increasing our ability to make better decisions. Yet, many water systems are still operated using very simple information systems, typically based on simple statistical analysis and the operator's experience. In this work, we propose a framework to automatically select the most valuable information to inform water systems operations supported by quantitative metrics to operationally and economically assess the value of this information. The Hoa Binh reservoir in Vietnam is used to demonstrate the proposed framework in a multiobjective context, accounting for hydropower production and flood control. First, we quantify the expected value of perfect information, meaning the potential space for improvement under the assumption of exact knowledge of the future system conditions. Second, we automatically select the most valuable information that could be actually used to improve the Hoa Binh operations. Finally, we assess the economic value of sample information on the basis of the resulting policy performance. Results show that our framework successfully select information to enhance the performance of the operating policies with respect to both the competing objectives, attaining a 40% improvement close to the target trade-off selected as potentially good compromise between hydropower production and flood control.

Distributed collaborative environments for predictive battlespace awareness

NASA Astrophysics Data System (ADS)

McQuay, William K.

2003-09-01

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Situational assessment is crucial in understanding the battlespace. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Decision support technologies can semi-automate activities, such as analysis and planning, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that the commander must fused. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing AFRL research efforts in applying distributed collaborative environments to predictive battlespace awareness.

Seven Basic Steps to Solving Ethical Dilemmas in Special Education: A Decision-Making Framework

ERIC Educational Resources Information Center

Stockall, Nancy; Dennis, Lindsay R.

2015-01-01

This article presents a seven-step framework for decision making to solve ethical issues in special education. The authors developed the framework from the existing literature and theoretical frameworks of justice, critique, care, and professionalism. The authors briefly discuss each theoretical framework and then describe the decision-making…

Merging building maintainability and sustainability assessment: A multicriteria decision making approach

NASA Astrophysics Data System (ADS)

Asmone, A. S.; Chew, M. Y. L.

2018-02-01

Accurately predicting maintainability has been a challenge due to the complex nature of buildings, yet it is an important research area with a rising necessity. This paper explores the use of multicriteria decision making approach for merging maintainability and sustainability elements into building grading systems to attain long-term sustainability in the building industry. The paper conducts a systematic literature review on multicriteria decision analysis approach and builds on the existing knowledge of maintainability to achieve this. A conceptual framework is developed to bridge the gap between building operations and maintenance with green facilities management by forecasting green maintainability at the design stage.

Navigating environmental, economic, and technological trade-offs in the design and operation of submerged anaerobic membrane bioreactors (AnMBRs).

PubMed

Pretel, R; Shoener, B D; Ferrer, J; Guest, J S

2015-12-15

Anaerobic membrane bioreactors (AnMBRs) enable energy recovery from wastewater while simultaneously achieving high levels of treatment. The objective of this study was to elucidate how detailed design and operational decisions of submerged AnMBRs influence the technological, environmental, and economic sustainability of the system across its life cycle. Specific design and operational decisions evaluated included: solids retention time (SRT), mixed liquor suspended solids (MLSS) concentration, sludge recycling ratio (r), flux (J), and specific gas demand per membrane area (SGD). The possibility of methane recovery (both as biogas and as soluble methane in reactor effluent) and bioenergy production, nutrient recovery, and final destination of the sludge (land application, landfill, or incineration) were also evaluated. The implications of these design and operational decisions were characterized by leveraging a quantitative sustainable design (QSD) framework which integrated steady-state performance modeling across seasonal temperatures (using pilot-scale experimental data and the simulating software DESASS), life cycle cost (LCC) analysis, and life cycle assessment (LCA). Sensitivity and uncertainty analyses were used to characterize the relative importance of individual design decisions, and to navigate trade-offs across environmental, economic, and technological criteria. Based on this analysis, there are design and operational conditions under which submerged AnMBRs could be net energy positive and contribute to the pursuit of carbon negative wastewater treatment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sustainable water management under future uncertainty with eco-engineering decision scaling

NASA Astrophysics Data System (ADS)

Poff, N. Leroy; Brown, Casey M.; Grantham, Theodore E.; Matthews, John H.; Palmer, Margaret A.; Spence, Caitlin M.; Wilby, Robert L.; Haasnoot, Marjolijn; Mendoza, Guillermo F.; Dominique, Kathleen C.; Baeza, Andres

2016-01-01

Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stakeholder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrological uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.

Adaptive Management: From More Talk to Real Action

NASA Astrophysics Data System (ADS)

Williams, Byron K.; Brown, Eleanor D.

2014-02-01

The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.

Sustainable water management under future uncertainty with eco-engineering decision scaling

USGS Publications Warehouse

Poff, N LeRoy; Brown, Casey M; Grantham, Theodore E.; Matthews, John H; Palmer, Margaret A.; Spence, Caitlin M; Wilby, Robert L.; Haasnoot, Marjolijn; Mendoza, Guillermo F; Dominique, Kathleen C; Baeza, Andres

2015-01-01

Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services. We introduce a new decision framework, eco-engineering decision scaling (EEDS), that explicitly and quantitatively explores trade-offs in stakeholder-defined engineering and ecological performance metrics across a range of possible management actions under unknown future hydrological and climate states. We illustrate its potential application through a hypothetical case study of the Iowa River, USA. EEDS holds promise as a powerful framework for operationalizing freshwater sustainability under future hydrological uncertainty by fostering collaboration across historically conflicting perspectives of water resource engineering and river conservation ecology to design and operate water infrastructure for social and environmental benefits.

Knowledge Operation Capability Evaluation Model and Strategic Orientation of Supply Chain: Exploratory Research Based on View of Ecology

NASA Astrophysics Data System (ADS)

Zhou, Wen-Yong; Song, Ze-Qian

The competitiveness of Supply Chain (SC) correlates intimately with its knowledge operation (KO). In order to realize better assessment value, this paper constructed an evaluation framework on knowledge operation of SC and a detailed index system. According to theory of ecology, expounded the evaluation orientation and future research direction from view of comprehensiveness and adaptability. Additionally, a case about Toyota recall-gate was analyzed. Through research, it provides two dimensions of results evaluating orientation which may help enterprise make right decision upon SC.

A Framework for Military Decision Making Under Risks.

DTIC Science & Technology

1996-06-01

FORCE BASE, ALABAMA JUNE 1996 -. ,l woved for publtc release; QVA , jDistribution Unlixited Disclaimer The conclusions and opinions expressed in this...followed by an assignment as the operations officer for 1 st Battalion 509th Airborne Infantry Regiment. Next, LTC Schultz was assigned to Fort...iii ACKNOWLEDGMENTS ................................ iv AB STRA CT ........................ .................. v 1 INTRODUCTION

Marketing decision support systems for strategy building.

PubMed

Rao, S K

2000-01-01

Brand teams charged with the commercialization of pharmaceutical products in the pipeline operate in an uncertain environment. Market, customer and competitive interrelationships undergo changes, often in ways that are unpredictable with conventional research practices. This article describes a framework whereby such uncertainty can be managed more effectively in the context of ongoing business needs.

Naturalistic Decision Making For Power System Operators

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

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

2009-06-23

Abstract: Motivation -- As indicated by the Blackout of 2003, the North American interconnected electric system is vulnerable to cascading outages and widespread blackouts. Investigations of large scale outages often attribute the causes to the three T’s: Trees, Training and Tools. A systematic approach has been developed to document and understand the mental processes that an expert power system operator uses when making critical decisions. The approach has been developed and refined as part of a capability demonstration of a high-fidelity real-time power system simulator under normal and emergency conditions. To examine naturalistic decision making (NDM) processes, transcripts of operator-to-operatormore » conversations are analyzed to reveal and assess NDM-based performance criteria. Findings/Design -- The results of the study indicate that we can map the Situation Awareness Level of the operators at each point in the scenario. We can also identify clearly what mental models and mental simulations are being performed at different points in the scenario. As a result of this research we expect that we can identify improved training methods and improved analytical and visualization tools for power system operators. Originality/Value -- The research applies for the first time, the concepts of Recognition Primed Decision Making, Situation Awareness Levels and Cognitive Task Analysis to training of electric power system operators. Take away message -- The NDM approach provides an ideal framework for systematic training management and mitigation to accelerate learning in team-based training scenarios with high-fidelity power grid simulators.« less

The use of a multidimensional space for fusion candidate representation in a maritime domain awareness application

NASA Astrophysics Data System (ADS)

Lefebvre, Eric; Helleur, Christopher; Kashyap, Nathan

2008-03-01

Maritime surveillance of coastal regions requires operational staff to integrate a large amount of information from a variety of military and civilian sources. The diverse nature of the information sources makes complete automation difficult. The volume of vessels tracked and the number of sources makes it difficult for the limited operation centre staff to fuse all the information manually within a reasonable timeframe. In this paper, a conceptual decision space is proposed to provide a framework for automating the process of operators integrating the sources needed to maintain Maritime Domain Awareness. The decision space contains all potential pairs of ship tracks that are candidates for fusion. The location of the candidate pairs in this defined space depends on the value of the parameters used to make a decision. In the application presented, three independent parameters are used: the source detection efficiency, the geo-feasibility, and the track quality. One of three decisions is applied to each candidate track pair based on these three parameters: 1. to accept the fusion, in which case tracks are fused in one track, 2. to reject the fusion, in which case the candidate track pair is removed from the list of potential fusion, and 3. to defer the fusion, in which case no fusion occurs but the candidate track pair remains in the list of potential fusion until sufficient information is provided. This paper demonstrates in an operational setting how a proposed conceptual space is used to optimize the different thresholds for automatic fusion decision while minimizing the list of unresolved cases when the decision is left to the operator.

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

ERIC Educational Resources Information Center

Davis, Stephen H.

2004-01-01

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

Integrated consensus-based frameworks for unmanned vehicle routing and targeting assignment

NASA Astrophysics Data System (ADS)

Barnawi, Waleed T.

Unmanned aerial vehicles (UAVs) are increasingly deployed in complex and dynamic environments to perform multiple tasks cooperatively with other UAVs that contribute to overarching mission effectiveness. Studies by the Department of Defense (DoD) indicate future operations may include anti-access/area-denial (A2AD) environments which limit human teleoperator decision-making and control. This research addresses the problem of decentralized vehicle re-routing and task reassignments through consensus-based UAV decision-making. An Integrated Consensus-Based Framework (ICF) is formulated as a solution to the combined single task assignment problem and vehicle routing problem. The multiple assignment and vehicle routing problem is solved with the Integrated Consensus-Based Bundle Framework (ICBF). The frameworks are hierarchically decomposed into two levels. The bottom layer utilizes the renowned Dijkstra's Algorithm. The top layer addresses task assignment with two methods. The single assignment approach is called the Caravan Auction Algorithm (CarA) Algorithm. This technique extends the Consensus-Based Auction Algorithm (CBAA) to provide awareness for task completion by agents and adopt abandoned tasks. The multiple assignment approach called the Caravan Auction Bundle Algorithm (CarAB) extends the Consensus-Based Bundle Algorithm (CBBA) by providing awareness for lost resources, prioritizing remaining tasks, and adopting abandoned tasks. Research questions are investigated regarding the novelty and performance of the proposed frameworks. Conclusions regarding the research questions will be provided through hypothesis testing. Monte Carlo simulations will provide evidence to support conclusions regarding the research hypotheses for the proposed frameworks. The approach provided in this research addresses current and future military operations for unmanned aerial vehicles. However, the general framework implied by the proposed research is adaptable to any unmanned vehicle. Civil applications that involve missions where human observability would be limited could benefit from the independent UAV task assignment, such as exploration and fire surveillance are also notable uses for this approach.

Accounting for reasonableness: Exploring the personal internal framework affecting decisions about cancer drug funding.

PubMed

Sinclair, Shane; Hagen, Neil A; Chambers, Carole; Manns, Braden; Simon, Anita; Browman, George P

2008-05-01

Drug decision-makers are involved in developing and implementing policy, procedure and processes to support health resource allocation regarding drug treatment formularies. A variety of approaches to decision-making, including formal decision-making frameworks, have been developed to support transparent and fair priority setting. Recently, a decision tool, 'The 6-STEPPPs Tool', was developed to assist in making decisions about new cancer drugs within the public health care system. We conducted a qualitative study, utilizing focus groups and participant observation, in order to investigate the internal frameworks that supported and challenged individual participants as they applied this decision tool within a multi-stakeholder decision process. We discovered that health care resource allocation engaged not only the minds of decision-makers but profoundly called on the often conflicting values of the heart. Objective decision-making frameworks for new drug therapies need to consider the subjective internal frameworks of decision-makers that affect decisions. Understanding the very human, internal turmoil experienced by individuals involved in health care resource allocation, sheds additional insight into how to account for reasonableness and how to better support difficult decisions through transparent, values-based resource allocation policy, procedures and processes.

Planetary micro-rover operations on Mars using a Bayesian framework for inference and control

NASA Astrophysics Data System (ADS)

Post, Mark A.; Li, Junquan; Quine, Brendan M.

2016-03-01

With the recent progress toward the application of commercially-available hardware to small-scale space missions, it is now becoming feasible for groups of small, efficient robots based on low-power embedded hardware to perform simple tasks on other planets in the place of large-scale, heavy and expensive robots. In this paper, we describe design and programming of the Beaver micro-rover developed for Northern Light, a Canadian initiative to send a small lander and rover to Mars to study the Martian surface and subsurface. For a small, hardware-limited rover to handle an uncertain and mostly unknown environment without constant management by human operators, we use a Bayesian network of discrete random variables as an abstraction of expert knowledge about the rover and its environment, and inference operations for control. A framework for efficient construction and inference into a Bayesian network using only the C language and fixed-point mathematics on embedded hardware has been developed for the Beaver to make intelligent decisions with minimal sensor data. We study the performance of the Beaver as it probabilistically maps a simple outdoor environment with sensor models that include uncertainty. Results indicate that the Beaver and other small and simple robotic platforms can make use of a Bayesian network to make intelligent decisions in uncertain planetary environments.

The Watershed and River Systems Management Program: Decision Support for Water- and Environmental-Resource Management

NASA Astrophysics Data System (ADS)

Leavesley, G.; Markstrom, S.; Frevert, D.; Fulp, T.; Zagona, E.; Viger, R.

2004-12-01

Increasing demands for limited fresh-water supplies, and increasing complexity of water-management issues, present the water-resource manager with the difficult task of achieving an equitable balance of water allocation among a diverse group of water users. The Watershed and River System Management Program (WARSMP) is a cooperative effort between the U.S. Geological Survey (USGS) and the Bureau of Reclamation (BOR) to develop and deploy a database-centered, decision-support system (DSS) to address these multi-objective, resource-management problems. The decision-support system couples the USGS Modular Modeling System (MMS) with the BOR RiverWare tools using a shared relational database. MMS is an integrated system of computer software that provides a research and operational framework to support the development and integration of a wide variety of hydrologic and ecosystem models, and their application to water- and ecosystem-resource management. RiverWare is an object-oriented reservoir and river-system modeling framework developed to provide tools for evaluating and applying water-allocation and management strategies. The modeling capabilities of MMS and Riverware include simulating watershed runoff, reservoir inflows, and the impacts of resource-management decisions on municipal, agricultural, and industrial water users, environmental concerns, power generation, and recreational interests. Forecasts of future climatic conditions are a key component in the application of MMS models to resource-management decisions. Forecast methods applied in MMS include a modified version of the National Weather Service's Extended Streamflow Prediction Program (ESP) and statistical downscaling from atmospheric models. The WARSMP DSS is currently operational in the Gunnison River Basin, Colorado; Yakima River Basin, Washington; Rio Grande Basin in Colorado and New Mexico; and Truckee River Basin in California and Nevada.

Development of a model-based flood emergency management system in Yujiang River Basin, South China

NASA Astrophysics Data System (ADS)

Zeng, Yong; Cai, Yanpeng; Jia, Peng; Mao, Jiansu

2014-06-01

Flooding is the most frequent disaster in China. It affects people's lives and properties, causing considerable economic loss. Flood forecast and operation of reservoirs are important in flood emergency management. Although great progress has been achieved in flood forecast and reservoir operation through using computer, network technology, and geographic information system technology in China, the prediction accuracy of models are not satisfactory due to the unavailability of real-time monitoring data. Also, real-time flood control scenario analysis is not effective in many regions and can seldom provide online decision support function. In this research, a decision support system for real-time flood forecasting in Yujiang River Basin, South China (DSS-YRB) is introduced in this paper. This system is based on hydrological and hydraulic mathematical models. The conceptual framework and detailed components of the proposed DSS-YRB is illustrated, which employs real-time rainfall data conversion, model-driven hydrologic forecasting, model calibration, data assimilation methods, and reservoir operational scenario analysis. Multi-tiered architecture offers great flexibility, portability, reusability, and reliability. The applied case study results show the development and application of a decision support system for real-time flood forecasting and operation is beneficial for flood control.

Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration

NASA Astrophysics Data System (ADS)

Altaleb, Hesham

With the introduction of power energy markets deregulation, innovations have transformed once a static network into a more flexible grid. Microgrids have also been deployed to serve various purposes (e.g., reliability, sustainability, etc.). With the rapid deployment of smart grid technologies, it has become possible to measure and record both, the quantity and time of the consumption of electrical power. In addition, capabilities for controlling distributed supply and demand have resulted in complex systems where inefficiencies are possible and where improvements can be made. Electric power like other volatile resources cannot be stored efficiently, therefore, managing such resource requires considerable attention. Such complex systems present a need for decisions that can streamline consumption, delay infrastructure investments, and reduce costs. When renewable power resources and the need for limiting harmful emissions are added to the equation, the search space for decisions becomes increasingly complex. As a result, the need for a comprehensive decision guidance system for electrical power resources consumption and productions becomes evident. In this dissertation, I formulate and implement a comprehensive framework that addresses different aspect of the electrical power generation and consumption using optimization models and utilizing collaboration concepts. Our solution presents a two-prong approach: managing interaction in real-time for the short-term immediate consumption of already allocated resources; and managing the operational planning for the long-run consumption. More specifically, in real-time, we present and implement a model of how to organize a secondary market for peak-demand allocation and describe the properties of the market that guarantees efficient execution and a method for the fair distribution of collaboration gains. We also propose and implement a primary market for peak demand bounds determination problem with the assumption that participants of this market have the ability to collaborate in real-time. Moreover, proposed in this dissertation is an extensible framework to facilitate C&I entities forming a consortium to collaborate on their electric power supply and demand. The collaborative framework includes the structure of market setting, bids, and market resolution that produces a schedule of how power components are controlled as well as the resulting payment. The market resolution must satisfy a number of desirable properties (i.e., feasibility, Nash equilibrium, Pareto optimality, and equal collaboration profitability) which are formally defined in the dissertation. Furthermore, to support the extensible framework components' library, power components such as utility contract, back-up power generator, renewable resource, and power consuming service are formally modeled. Finally, the validity of this framework is evaluated by a case study using simulated load scenarios to examine the ability of the framework to efficiently operate at the specified time intervals with minimal overhead cost.

Developing an Analytical Framework: Incorporating Ecosystem Services into Decision Making - Proceedings of a Workshop

USGS Publications Warehouse

Hogan, Dianna; Arthaud, Greg; Pattison, Malka; Sayre, Roger G.; Shapiro, Carl

2010-01-01

The analytical framework for understanding ecosystem services in conservation, resource management, and development decisions is multidisciplinary, encompassing a combination of the natural and social sciences. This report summarizes a workshop on 'Developing an Analytical Framework: Incorporating Ecosystem Services into Decision Making,' which focused on the analytical process and on identifying research priorities for assessing ecosystem services, their production and use, their spatial and temporal characteristics, their relationship with natural systems, and their interdependencies. Attendees discussed research directions and solutions to key challenges in developing the analytical framework. The discussion was divided into two sessions: (1) the measurement framework: quantities and values, and (2) the spatial framework: mapping and spatial relationships. This workshop was the second of three preconference workshops associated with ACES 2008 (A Conference on Ecosystem Services): Using Science for Decision Making in Dynamic Systems. These three workshops were designed to explore the ACES 2008 theme on decision making and how the concept of ecosystem services can be more effectively incorporated into conservation, restoration, resource management, and development decisions. Preconference workshop 1, 'Developing a Vision: Incorporating Ecosystem Services into Decision Making,' was held on April 15, 2008, in Cambridge, MA. In preconference workshop 1, participants addressed what would have to happen to make ecosystem services be used more routinely and effectively in conservation, restoration, resource management, and development decisions, and they identified some key challenges in developing the analytical framework. Preconference workshop 3, 'Developing an Institutional Framework: Incorporating Ecosystem Services into Decision Making,' was held on October 30, 2008, in Albuquerque, NM; participants examined the relationship between the institutional framework and the use of ecosystem services in decision making.

A conceptual evolutionary aseismic decision support framework for hospitals

NASA Astrophysics Data System (ADS)

Hu, Yufeng; Dargush, Gary F.; Shao, Xiaoyun

2012-12-01

In this paper, aconceptual evolutionary framework for aseismic decision support for hospitalsthat attempts to integrate a range of engineering and sociotechnical models is presented. Genetic algorithms are applied to find the optimal decision sets. A case study is completed to demonstrate how the frameworkmay applytoa specific hospital.The simulations show that the proposed evolutionary decision support framework is able to discover robust policy sets in either uncertain or fixed environments. The framework also qualitatively identifies some of the characteristicbehavior of the critical care organization. Thus, by utilizing the proposedframework, the decision makers are able to make more informed decisions, especially toenhance the seismic safety of the hospitals.

Decision framework for corridor planning within the roadside right-of-way.

DOT National Transportation Integrated Search

2013-08-01

A decision framework was developed for context-sensitive planning within the roadside ROW in : Michigan. This framework provides a roadside suitability assessment model that may be used to : support integrated decision-making and policy level conside...

A Hierarchical Framework for Demand-Side Frequency Control

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

Moya, Christian; Zhang, Wei; Lian, Jianming

2014-06-02

With large-scale plans to integrate renewable generation, more resources will be needed to compensate for the uncertainty associated with intermittent generation resources. Under such conditions, performing frequency control using only supply-side resources become not only prohibitively expensive but also technically difficult. It is therefore important to explore how a sufficient proportion of the loads could assume a routine role in frequency control to maintain the stability of the system at an acceptable cost. In this paper, a novel hierarchical decentralized framework for frequency based load control is proposed. The framework involves two decision layers. The top decision layer determines themore » optimal droop gain required from the aggregated load response on each bus using a robust decentralized control approach. The second layer consists of a large number of devices, which switch probabilistically during contingencies so that the aggregated power change matches the desired droop amount according to the updated gains. The proposed framework is based on the classical nonlinear multi-machine power system model, and can deal with timevarying system operating conditions while respecting the physical constraints of individual devices. Realistic simulation results based on a 68-bus system are provided to demonstrate the effectiveness of the proposed strategy.« less

Putting flow-ecology relationships into practice: A decision-support system to assess fish community response to water-management scenarios

USGS Publications Warehouse

Cartwright, Jennifer M.; Caldwell, Casey; Nebiker, Steven; Knight, Rodney

2017-01-01

This paper presents a conceptual framework to operationalize flow–ecology relationships into decision-support systems of practical use to water-resource managers, who are commonly tasked with balancing multiple competing socioeconomic and environmental priorities. We illustrate this framework with a case study, whereby fish community responses to various water-management scenarios were predicted in a partially regulated river system at a local watershed scale. This case study simulates management scenarios based on interactive effects of dam operation protocols, withdrawals for municipal water supply, effluent discharges from wastewater treatment, and inter-basin water transfers. Modeled streamflow was integrated with flow–ecology relationships relating hydrologic departure from reference conditions to fish species richness, stratified by trophic, reproductive, and habitat characteristics. Adding a hypothetical new water-withdrawal site was predicted to increase the frequency of low-flow conditions with adverse effects for several fish groups. Imposition of new reservoir release requirements was predicted to enhance flow and fish species richness immediately downstream of the reservoir, but these effects were dissipated further downstream. The framework presented here can be used to translate flow–ecology relationships into evidence-based management by developing decision-support systems for conservation of riverine biodiversity while optimizing water availability for human use.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

A new web-based framework development for fuzzy multi-criteria group decision-making.

PubMed

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

2016-01-01

Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.

Environmental Risk Assessment of dredging processes - application to Marin harbour (NW Spain)

NASA Astrophysics Data System (ADS)

Gómez, A. G.; García Alba, J.; Puente, A.; Juanes, J. A.

2014-04-01

A methodological procedure to estimate the environmental risk of dredging operations in aquatic systems has been developed. Environmental risk estimations are based on numerical models results, which provide an appropriated spatio-temporal framework analysis to guarantee an effective decision-making process. The methodological procedure has been applied on a real dredging operation in the port of Marin (NW Spain). Results from Marin harbour confirmed the suitability of the developed methodology and the conceptual approaches as a comprehensive and practical management tool.

Dynamic and adaptive policy models for coalition operations

NASA Astrophysics Data System (ADS)

Verma, Dinesh; Calo, Seraphin; Chakraborty, Supriyo; Bertino, Elisa; Williams, Chris; Tucker, Jeremy; Rivera, Brian; de Mel, Geeth R.

2017-05-01

It is envisioned that the success of future military operations depends on the better integration, organizationally and operationally, among allies, coalition members, inter-agency partners, and so forth. However, this leads to a challenging and complex environment where the heterogeneity and dynamism in the operating environment intertwines with the evolving situational factors that affect the decision-making life cycle of the war fighter. Therefore, the users in such environments need secure, accessible, and resilient information infrastructures where policy-based mechanisms adopt the behaviours of the systems to meet end user goals. By specifying and enforcing a policy based model and framework for operations and security which accommodates heterogeneous coalitions, high levels of agility can be enabled to allow rapid assembly and restructuring of system and information resources. However, current prevalent policy models (e.g., rule based event-condition-action model and its variants) are not sufficient to deal with the highly dynamic and plausibly non-deterministic nature of these environments. Therefore, to address the above challenges, in this paper, we present a new approach for policies which enables managed systems to take more autonomic decisions regarding their operations.

A Framework of Multi Objectives Negotiation for Dynamic Supply Chain Model

NASA Astrophysics Data System (ADS)

Chai, Jia Yee; Sakaguchi, Tatsuhiko; Shirase, Keiichi

Trends of globalization and advances in Information Technology (IT) have created opportunity in collaborative manufacturing across national borders. A dynamic supply chain utilizes these advances to enable more flexibility in business cooperation. This research proposes a concurrent decision making framework for a three echelons dynamic supply chain model. The dynamic supply chain is formed by autonomous negotiation among agents based on multi agents approach. Instead of generating negotiation aspects (such as amount, price and due date) arbitrary, this framework proposes to utilize the information available at operational level of an organization in order to generate realistic negotiation aspect. The effectiveness of the proposed model is demonstrated by various case studies.

Whose decision is it anyway? How clinicians support decision-making participation after acquired brain injury.

PubMed

Knox, Lucy; Douglas, Jacinta M; Bigby, Christine

2013-01-01

To raise professional awareness of factors that may influence the support offered by clinicians to people with acquired brain injury (ABI), and to consider the potential implications of these factors in terms of post-injury rehabilitation and living. A review of the literature was conducted to identify factors that determine how clinicians provide support and influence opportunities for individuals with ABI to participate in decision making across the rehabilitation continuum. Clinical case studies are used to highlight two specific issues: (1) hidden assumptions on the part of the practitioner, and (2) perceptions of risk operating in clinical practice. There are a range of factors which may influence the decision-making support provided by clinicians and, ultimately, shape lifetime outcomes for individuals with ABI. A multidimensional framework may assist clinicians to identify relevant factors and consider their potential implications including those that influence how clinicians involved in supporting decision making approach this task. Participation in decision making is an undisputed human right and central to the provision of person-centred care. Further research is required to understand how clinical practice can maximise both opportunities and support for increased decision-making participation by individuals with ABI. There is an increasing focus on the rights of all individuals to be supported to participate in decision making about their life. A number of changes associated with ABI mean that individuals with ABI will require support with decision making. Clinicians have a critical role in providing this support over the course of the rehabilitation continuum. Clinicians need to be aware of the range of factors that may influence the decision-making support they provide. A multidimensional framework may be used by clinicians to identify influences on the decision-making support they provide.

A framework for designing and analyzing binary decision-making strategies in cellular systems†

PubMed Central

Porter, Joshua R.; Andrews, Burton W.; Iglesias, Pablo A.

2015-01-01

Cells make many binary (all-or-nothing) decisions based on noisy signals gathered from their environment and processed through noisy decision-making pathways. Reducing the effect of noise to improve the fidelity of decision-making comes at the expense of increased complexity, creating a tradeoff between performance and metabolic cost. We present a framework based on rate distortion theory, a branch of information theory, to quantify this tradeoff and design binary decision-making strategies that balance low cost and accuracy in optimal ways. With this framework, we show that several observed behaviors of binary decision-making systems, including random strategies, hysteresis, and irreversibility, are optimal in an information-theoretic sense for various situations. This framework can also be used to quantify the goals around which a decision-making system is optimized and to evaluate the optimality of cellular decision-making systems by a fundamental information-theoretic criterion. As proof of concept, we use the framework to quantify the goals of the externally triggered apoptosis pathway. PMID:22370552

Scaling Up Decision Theoretic Planning to Planetary Rover Problems

NASA Technical Reports Server (NTRS)

Meuleau, Nicolas; Dearden, Richard; Washington, Rich

2004-01-01

Because of communication limits, planetary rovers must operate autonomously during consequent durations. The ability to plan under uncertainty is one of the main components of autonomy. Previous approaches to planning under uncertainty in NASA applications are not able to address the challenges of future missions, because of several apparent limits. On another side, decision theory provides a solid principle framework for reasoning about uncertainty and rewards. Unfortunately, there are several obstacles to a direct application of decision-theoretic techniques to the rover domain. This paper focuses on the issues of structure and concurrency, and continuous state variables. We describes two techniques currently under development that address specifically these issues and allow scaling-up decision theoretic solution techniques to planetary rover planning problems involving a small number of goals.

Cognitive-emotional decision making (CEDM): a framework of patient medical decision making.

PubMed

Power, Tara E; Swartzman, Leora C; Robinson, John W

2011-05-01

Assistance for patients faced with medical decisions has largely focussed on the clarification of information and personal values. Our aim is to draw on the decision research describing the role of emotion in combination with health behaviour models to provide a framework for conceptualizing patient decisions. A review of the psychological and medical decision making literature concerned with the role of emotion/affect in decision making and health behaviours. Emotion plays an influential role in decision making. Both current and anticipated emotions play a motivational role in choice. Amalgamating these findings with that of Leventhal's (1970) SRM provide a framework for thinking about the influence of emotion on a patient medical decision. Our framework suggests that a patient must cope with four sets of elements. The first two relate to the need to manage the cognitive and emotional aspects of the health threat. The second set relate to the management of the cognitive and emotional elements of the decision, itself. The framework provides a way for practitioners and researchers to frame thinking about a patient medical decision in order to assist the patient in clarifying decisional priorities. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Towards a neuro-computational account of prism adaptation.

PubMed

Petitet, Pierre; O'Reilly, Jill X; O'Shea, Jacinta

2017-12-14

Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, prism adaptation behaviour is typically explained by reference to a traditional cognitive psychology framework that distinguishes putative functions, such as 'strategic control' versus 'spatial realignment'. This theoretical framework lacks conceptual clarity, quantitative precision and explanatory power. Here, we advocate for an alternative computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route towards mechanistic neurocognitive explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework can advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond merely descriptive mapping claims that 'brain area X is (somehow) involved in psychological process Y'. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Smart Grid as Multi-layer Interacting System for Complex Decision Makings

NASA Astrophysics Data System (ADS)

Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico

This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.

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.

A risk-based framework to assess long-term effects of policy and water supply changes on water resources systems

NASA Astrophysics Data System (ADS)

Hassanzadeh, Elmira; Elshorbagy, Amin; Wheater, Howard; Gober, Patricia

2015-04-01

Climate uncertainty can affect water resources availability and management decisions. Sustainable water resources management therefore requires evaluation of policy and management decisions under a wide range of possible future water supply conditions. This study proposes a risk-based framework to integrate water supply uncertainty into a forward-looking decision making context. To apply this framework, a stochastic reconstruction scheme is used to generate a large ensemble of flow series. For the Rocky Mountain basins considered here, two key characteristics of the annual hydrograph are its annual flow volume and the timing of the seasonal flood peak. These are perturbed to represent natural randomness and potential changes due to future climate. 30-year series of perturbed flows are used as input to the SWAMP model - an integrated water resources model that simulates regional water supply-demand system and estimates economic productivity of water and other sustainability indicators, including system vulnerability and resilience. The simulation results are used to construct 2D-maps of net revenue of a particular water sector; e.g., hydropower, or for all sectors combined. Each map cell represents a risk scenario of net revenue based on a particular annual flow volume, timing of the peak flow, and 200 stochastic realizations of flow series. This framework is demonstrated for a water resources system in the Saskatchewan River Basin (SaskRB) in Saskatchewan, Canada. Critical historical drought sequences, derived from tree-ring reconstructions of several hundred years of annual river flows, are used to evaluate the system's performance (net revenue risk) under extremely low flow conditions and also to locate them on the previously produced 2D risk maps. This simulation and analysis framework is repeated under various reservoir operation strategies (e.g., maximizing flood protection or maximizing water supply security); development proposals, such as irrigation expansion; and change in energy prices. Such risk-based analysis demonstrates relative reduction/increase of risk associated with management and policy decisions and allow decision makers to explore the relative importance of policy versus natural water supply change in a water resources system.

Use of technology to support information needs for continuity of operations planning in public health: a systematic review.

PubMed

Reeder, Blaine; Turner, Anne; Demiris, George

2010-01-01

Continuity of operations planning focuses on an organization's ability to deliver essential services before, during and after an emergency. Public health leaders must make decisions based on information from many sources and their information needs are often facilitated or hindered by technology. The aim of this study is to provide a systematic review of studies of technology projects that address public health continuity of operations planning information needs and to discuss patterns, themes, and challenges to inform the design of public health continuity of operations information systems. To return a comprehensive results set in an under-explored area, we searched broadly in the Medline and EBSCOHost bibliographic databases using terms from prior work in public health emergency management and continuity of operations planning in other domains. In addition, we manually searched the citation lists of publications included for review. A total of 320 publications were reviewed. Twenty studies were identified for inclusion (twelve risk assessment decision support tools, six network and communications-enabled decision support tools, one training tool and one dedicated video-conferencing tool). Levels of implementation for information systems in the included studies range from proposed frameworks to operational systems. There is a general lack of documented efforts in the scientific literature for technology projects about public health continuity of operations planning. Available information about operational information systems suggest inclusion of public health practitioners in the design process as a factor in system success.

School and District Intervention: A Decision-Making Framework for Policymakers.

ERIC Educational Resources Information Center

Bowles, Susan A.; Churchill, Andrew M.; Effrat, Andrew; McDermott, Kathryn A.

This paper seeks to help state policymakers understand their relatively new role in improving the academic performance of local schools and districts. The first section, "Intervention Decision-Making Framework," focuses on the intervention decision making framework model, performance criteria, strategic criteria, diagnostic…

Decision making from economic and signal detection perspectives: development of an integrated framework

PubMed Central

Lynn, Spencer K.; Wormwood, Jolie B.; Barrett, Lisa F.; Quigley, Karen S.

2015-01-01

Behavior is comprised of decisions made from moment to moment (i.e., to respond one way or another). Often, the decision maker cannot be certain of the value to be accrued from the decision (i.e., the outcome value). Decisions made under outcome value uncertainty form the basis of the economic framework of decision making. Behavior is also based on perception—perception of the external physical world and of the internal bodily milieu, which both provide cues that guide decision making. These perceptual signals are also often uncertain: another person's scowling facial expression may indicate threat or intense concentration, alternatives that require different responses from the perceiver. Decisions made under perceptual uncertainty form the basis of the signals framework of decision making. Traditional behavioral economic approaches to decision making focus on the uncertainty that comes from variability in possible outcome values, and typically ignore the influence of perceptual uncertainty. Conversely, traditional signal detection approaches to decision making focus on the uncertainty that arises from variability in perceptual signals and typically ignore the influence of outcome value uncertainty. Here, we compare and contrast the economic and signals frameworks that guide research in decision making, with the aim of promoting their integration. We show that an integrated framework can expand our ability to understand a wider variety of decision-making behaviors, in particular the complexly determined real-world decisions we all make every day. PMID:26217275

A fuzzy stochastic framework for managing hydro-environmental and socio-economic interactions under uncertainty

NASA Astrophysics Data System (ADS)

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

2014-05-01

An amplified interconnectedness between a hydro-environmental and socio-economic system brings about profound challenges of water management decision making. In this contribution, we present a fuzzy stochastic approach to solve a set of decision making problems, which involve hydrologically, environmentally, and socio-economically motivated criteria subjected to uncertainty and ambiguity. The proposed methodological framework combines objective and subjective criteria in a decision making procedure for obtaining an acceptable ranking in water resources management alternatives under different type of uncertainty (subjective/objective) and heterogeneous information (quantitative/qualitative) simultaneously. The first step of the proposed approach involves evaluating the performance of alternatives with respect to different types of criteria. The ratings of alternatives with respect to objective and subjective criteria are evaluated by simulation-based optimization and fuzzy linguistic quantifiers, respectively. Subjective and objective uncertainties related to the input information are handled through linking fuzziness and randomness together. Fuzzy decision making helps entail the linguistic uncertainty and a Monte Carlo simulation process is used to map stochastic uncertainty. With this framework, the overall performance of each alternative is calculated using an Order Weighted Averaging (OWA) aggregation operator accounting for decision makers' experience and opinions. Finally, ranking is achieved by conducting pair-wise comparison of management alternatives. This has been done on the basis of the risk defined by the probability of obtaining an acceptable ranking and mean difference in total performance for the pair of management alternatives. The proposed methodology is tested in a real-world hydrosystem, to find effective and robust intervention strategies for the management of a coastal aquifer system affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. The results show that the approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Distributed collaborative decision support environments for predictive awareness

NASA Astrophysics Data System (ADS)

McQuay, William K.; Stilman, Boris; Yakhnis, Vlad

2005-05-01

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, rapidly assess the enemy"s course of action (eCOA) or possible actions and promulgate their own course of action (COA) - a need for predictive awareness. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Revolutionary new approaches to strategy generation and assessment such as Linguistic Geometry (LG) permit the rapid development of COA vs. enemy COA (eCOA). LG tools automatically generate and permit the operators to take advantage of winning strategies and tactics for mission planning and execution in near real-time. LG is predictive and employs deep "look-ahead" from the current state and provides a realistic, reactive model of adversary reasoning and behavior. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing research efforts in applying distributed collaborative environments to decision support for predictive mission awareness.

When parsimony is not enough: Considering dual processes and dual levels of influence in sexual decision making

PubMed Central

Rendina, H. Jonathon

2015-01-01

The literature on sexual decision making that has been used to understand behaviors relevant to HIV and STI risk has relied primarily on cognitive antecedents of behavior. In contrast, several prominent models of decision making outside of the sexual behavior literature rely on dual process models, in which both affective and cognitive processing are considered important precursors to behavior. Moreover, much of the literature on sexual behavior utilizes individual-level traits and characteristics to predict aggregated sexual behavior, despite decision making itself being a situational or event-level process. This paper proposes a framework for understanding sexual decision making as the result of dual processes (affective and cognitive) operating at dual level of influence (individual and situational). Finally, the paper ends with a discussion of the conceptual and methodological benefits and challenges to its use and future directions for research. PMID:26168978

Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework

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

Cappelli, M.; Gadomski, A. M.; Sepiellis, M.

In the field of nuclear power plant (NPP) safety modeling, the perception of the role of socio-cognitive engineering (SCE) is continuously increasing. Today, the focus is especially on the identification of human and organization decisional errors caused by operators and managers under high-risk conditions, as evident by analyzing reports on nuclear incidents occurred in the past. At present, the engineering and social safety requirements need to enlarge their domain of interest in such a way to include all possible losses generating events that could be the consequences of an abnormal state of a NPP. Socio-cognitive modeling of Integrated Nuclear Safetymore » Management (INSM) using the TOGA meta-theory has been discussed during the ICCAP 2011 Conference. In this paper, more detailed aspects of the cognitive decision-making and its possible human errors and organizational vulnerability are presented. The formal TOGA-based network model for cognitive decision-making enables to indicate and analyze nodes and arcs in which plant operators and managers errors may appear. The TOGA's multi-level IPK (Information, Preferences, Knowledge) model of abstract intelligent agents (AIAs) is applied. In the NPP context, super-safety approach is also discussed, by taking under consideration unexpected events and managing them from a systemic perspective. As the nature of human errors depends on the specific properties of the decision-maker and the decisional context of operation, a classification of decision-making using IPK is suggested. Several types of initial situations of decision-making useful for the diagnosis of NPP operators and managers errors are considered. The developed models can be used as a basis for applications to NPP educational or engineering simulators to be used for training the NPP executive staff. (authors)« less

A Hyperknowledge Framework of Decision Support Systems.

ERIC Educational Resources Information Center

Chang, Ai-Mei; And Others

1994-01-01

Presents a hyperknowledge framework of decision support systems (DSS). This framework formalizes specifics about system functionality, representation of knowledge, navigation of the knowledge system, and user-interface traits as elements of a DSS environment that conforms closely to human cognitive processes in decision making. (Contains 52…

Integrated Risk-Informed Decision-Making for an ALMR PRISM

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

Muhlheim, Michael David; Belles, Randy; Denning, Richard S.

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace ormore » supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi-attribute decision-making framework uses various sensor data (e.g., reactor outlet temperature, steam generator drum level) and calculates its position within the challenge state, its trajectory, and its margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. The metrics that are evaluated are based on reactor trip set points. The integration of the deterministic calculations using multi-physics analyses and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermalhydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies, and developing a user interface to mimic display panels at a modern nuclear power plant.« less

Iowa pavement asset management decision-making framework.

DOT National Transportation Integrated Search

2015-10-01

Most local agencies in Iowa currently make their pavement treatment decisions based on their limited experience due primarily to : lack of a systematic decision-making framework and a decision-aid tool. The lack of objective condition assessment data...

Barriers to implementation of risk management for federal wildland fire management agencies in the United States

Treesearch

Dave Calkin; Matthew P. Thompson; Alan A. Ager; Mark Finney

2010-01-01

In this presentation we review progress towards the implementation of a risk-based management framework for U.S. Federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical...

Public health ethics theory: review and path to convergence.

PubMed

Lee, Lisa M

2012-01-01

Public health ethics is a nascent field, emerging over the past decade as an applied field merging concepts of clinical and research ethics. Because the "patient" in public health is the population rather than the individual, existing principles might be weighted differently, or there might be different ethical principles to consider. This paper reviewed the evolution of public health ethics, the use of bioethics as its model, and the proposed frameworks for public health ethics through 2010. Review of 13 major public health ethics frameworks published over the past 15 years yields a wide variety of theoretical approaches, some similar foundational values, and a few similar operating principles. Coming to a consensus on the reach, purpose, and ends of public health is necessary if we are to agree on what ethical underpinnings drive us, what foundational values bring us to these underpinnings, and what operating principles practitioners must implement to make ethical decisions. If public health is distinct enough from clinical medicine to warrant its own set of ethical and philosophical underpinnings, then a decision must be made as to whether a single approach is warranted or we can tolerate a variety of equal but different perspectives. © 2012 American Society of Law, Medicine & Ethics, Inc.

The role of data fusion in predictive maintenance using digital twin

NASA Astrophysics Data System (ADS)

Liu, Zheng; Meyendorf, Norbert; Mrad, Nezih

2018-04-01

Modern aerospace industry is migrating from reactive to proactive and predictive maintenance to increase platform operational availability and efficiency, extend its useful life cycle and reduce its life cycle cost. Multiphysics modeling together with data-driven analytics generate a new paradigm called "Digital Twin." The digital twin is actually a living model of the physical asset or system, which continually adapts to operational changes based on the collected online data and information, and can forecast the future of the corresponding physical counterpart. This paper reviews the overall framework to develop a digital twin coupled with the industrial Internet of Things technology to advance aerospace platforms autonomy. Data fusion techniques particularly play a significant role in the digital twin framework. The flow of information from raw data to high-level decision making is propelled by sensor-to-sensor, sensor-to-model, and model-to-model fusion. This paper further discusses and identifies the role of data fusion in the digital twin framework for aircraft predictive maintenance.

A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

NASA Astrophysics Data System (ADS)

Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

2012-12-01

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.

Ensemble Flow Forecasts for Risk Based Reservoir Operations of Lake Mendocino in Mendocino County, California: A Framework for Objectively Leveraging Weather and Climate Forecasts in a Decision Support Environment

NASA Astrophysics Data System (ADS)

Delaney, C.; Hartman, R. K.; Mendoza, J.; Whitin, B.

2017-12-01

Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation and flow forecasts to inform the flood operations of reservoirs. The Ensemble Forecast Operations (EFO) alternative is a probabilistic approach of FIRO that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, release decisions are made to manage forecasted risk of reaching critical operational thresholds. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC. The ESP hindcast was developed using Global Ensemble Forecast System version 10 precipitation reforecasts processed with the Hydrologic Ensemble Forecast System to generate daily reforecasts of 61 flow ensemble members for a 15-day forecast horizon. Model simulation results demonstrate that the EFO alternative may improve water supply reliability for Lake Mendocino yet not increase flood risk for downstream areas. The developed operations framework can directly leverage improved skill in the second week of the forecast and is extendable into the S2S time domain given the demonstration of improved skill through a reliable reforecast of adequate historical duration and consistent with operationally available numerical weather predictions.

Cognitive Phenotypes and the Evolution of Animal Decisions.

PubMed

Mendelson, Tamra C; Fitzpatrick, Courtney L; Hauber, Mark E; Pence, Charles H; Rodríguez, Rafael L; Safran, Rebecca J; Stern, Caitlin A; Stevens, Jeffrey R

2016-11-01

Despite the clear fitness consequences of animal decisions, the science of animal decision making in evolutionary biology is underdeveloped compared with decision science in human psychology. Specifically, the field lacks a conceptual framework that defines and describes the relevant components of a decision, leading to imprecise language and concepts. The 'judgment and decision-making' (JDM) framework in human psychology is a powerful tool for framing and understanding human decisions, and we apply it here to components of animal decisions, which we refer to as 'cognitive phenotypes'. We distinguish multiple cognitive phenotypes in the context of a JDM framework and highlight empirical approaches to characterize them as evolvable traits. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decision making and coping in healthcare: the Coping in Deliberation (CODE) framework.

PubMed

Witt, Jana; Elwyn, Glyn; Wood, Fiona; Brain, Kate

2012-08-01

To develop a framework of decision making and coping in healthcare that describes the twin processes of appraisal and coping faced by patients making preference-sensitive healthcare decisions. We briefly review the literature for decision making theories and coping theories applicable to preference-sensitive decisions in healthcare settings. We describe first decision making, then coping and finally attempt to integrate these processes by building on current theory. Deliberation in healthcare may be described as a six step process, comprised of the presentation of a health threat, choice, options, preference construction, the decision itself and consolidation post-decision. Coping can be depicted in three stages, beginning with a threat, followed by primary and secondary appraisal and ultimately resulting in a coping effort. Drawing together concepts from prominent decision making theories and coping theories, we propose a multidimensional, interactive framework which integrates both processes and describes coping in deliberation. The proposed framework offers an insight into the complexity of decision making in preference-sensitive healthcare contexts from a patient perspective and may act as theoretical basis for decision support. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A decision modeling for phasor measurement unit location selection in smart grid systems

NASA Astrophysics Data System (ADS)

Lee, Seung Yup

As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed.

The capacity for ethical decisions: the relationship between working memory and ethical decision making.

PubMed

Martin, April; Bagdasarov, Zhanna; Connelly, Shane

2015-04-01

Although various models of ethical decision making (EDM) have implicitly called upon constructs governed by working memory capacity (WMC), a study examining this relationship specifically has not been conducted. Using a sense making framework of EDM, we examined the relationship between WMC and various sensemaking processes contributing to EDM. Participants completed an online assessment comprised of a demographic survey, intelligence test, various EDM measures, and the Automated Operation Span task to determine WMC. Results indicated that WMC accounted for unique variance above and beyond ethics education, exposure to ethical issues, and intelligence in several sensemaking processes. Additionally, a marginally significant effect of WMC was also found with reference to EDM. Individual differences in WMC appear likely to play an important role in the ethical decision-making process, and future researchers may wish to consider their potential influences.

Mapping the Delivery of Societal Benefit through the International Arctic Observations Assessment Framework

NASA Astrophysics Data System (ADS)

Lev, S. M.; Gallo, J.

2017-12-01

The international Arctic scientific community has identified the need for a sustained and integrated portfolio of pan-Arctic Earth-observing systems. In 2017, an international effort was undertaken to develop the first ever Value Tree framework for identifying common research and operational objectives that rely on Earth observation data derived from Earth-observing systems, sensors, surveys, networks, models, and databases to deliver societal benefits in the Arctic. A Value Tree Analysis is a common tool used to support decision making processes and is useful for defining concepts, identifying objectives, and creating a hierarchical framework of objectives. A multi-level societal benefit area value tree establishes the connection from societal benefits to the set of observation inputs that contribute to delivering those benefits. A Value Tree that relies on expert domain knowledge from Arctic and non-Arctic nations, international researchers, Indigenous knowledge holders, and other experts to develop a framework to serve as a logical and interdependent decision support tool will be presented. Value tree examples that map the contribution of Earth observations in the Arctic to achieving societal benefits will be presented in the context of the 2017 International Arctic Observations Assessment Framework. These case studies will highlight specific observing products and capability groups where investment is needed to contribute to the development of a sustained portfolio of Arctic observing systems.

Shared investment projects and forecasting errors: setting framework conditions for coordination and sequencing data quality activities.

PubMed

Leitner, Stephan; Brauneis, Alexander; Rausch, Alexandra

2015-01-01

In this paper, we investigate the impact of inaccurate forecasting on the coordination of distributed investment decisions. In particular, by setting up a computational multi-agent model of a stylized firm, we investigate the case of investment opportunities that are mutually carried out by organizational departments. The forecasts of concern pertain to the initial amount of money necessary to launch and operate an investment opportunity, to the expected intertemporal distribution of cash flows, and the departments' efficiency in operating the investment opportunity at hand. We propose a budget allocation mechanism for coordinating such distributed decisions The paper provides guidance on how to set framework conditions, in terms of the number of investment opportunities considered in one round of funding and the number of departments operating one investment opportunity, so that the coordination mechanism is highly robust to forecasting errors. Furthermore, we show that-in some setups-a certain extent of misforecasting is desirable from the firm's point of view as it supports the achievement of the corporate objective of value maximization. We then address the question of how to improve forecasting quality in the best possible way, and provide policy advice on how to sequence activities for improving forecasting quality so that the robustness of the coordination mechanism to errors increases in the best possible way. At the same time, we show that wrong decisions regarding the sequencing can lead to a decrease in robustness. Finally, we conduct a comprehensive sensitivity analysis and prove that-in particular for relatively good forecasters-most of our results are robust to changes in setting the parameters of our multi-agent simulation model.

Shared Investment Projects and Forecasting Errors: Setting Framework Conditions for Coordination and Sequencing Data Quality Activities

PubMed Central

Leitner, Stephan; Brauneis, Alexander; Rausch, Alexandra

2015-01-01

In this paper, we investigate the impact of inaccurate forecasting on the coordination of distributed investment decisions. In particular, by setting up a computational multi-agent model of a stylized firm, we investigate the case of investment opportunities that are mutually carried out by organizational departments. The forecasts of concern pertain to the initial amount of money necessary to launch and operate an investment opportunity, to the expected intertemporal distribution of cash flows, and the departments’ efficiency in operating the investment opportunity at hand. We propose a budget allocation mechanism for coordinating such distributed decisions The paper provides guidance on how to set framework conditions, in terms of the number of investment opportunities considered in one round of funding and the number of departments operating one investment opportunity, so that the coordination mechanism is highly robust to forecasting errors. Furthermore, we show that—in some setups—a certain extent of misforecasting is desirable from the firm’s point of view as it supports the achievement of the corporate objective of value maximization. We then address the question of how to improve forecasting quality in the best possible way, and provide policy advice on how to sequence activities for improving forecasting quality so that the robustness of the coordination mechanism to errors increases in the best possible way. At the same time, we show that wrong decisions regarding the sequencing can lead to a decrease in robustness. Finally, we conduct a comprehensive sensitivity analysis and prove that—in particular for relatively good forecasters—most of our results are robust to changes in setting the parameters of our multi-agent simulation model. PMID:25803736

OpenDA-WFLOW framework for improving hydrologic predictions using distributed hydrologic models

NASA Astrophysics Data System (ADS)

Weerts, Albrecht; Schellekens, Jaap; Kockx, Arno; Hummel, Stef

2017-04-01

Data assimilation (DA) holds considerable potential for improving hydrologic predictions (Liu et al., 2012) and increase the potential for early warning and/or smart water management. However, advances in hydrologic DA research have not yet been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. The objective of this work is to highlight the development of a generic linkage of the open source OpenDA package and the open source community hydrologic modeling framework Openstreams/WFLOW and its application in operational hydrological forecasting on various spatial scales. The coupling between OpenDA and Openstreams/wflow framework is based on the emerging standard Basic Model Interface (BMI) as advocated by CSDMS using cross-platform webservices (i.e. Apache Thrift) developed by Hut et al. (2016). The potential application of the OpenDA-WFLOW for operational hydrologic forecasting including its integration with Delft-FEWS (used by more than 40 operational forecast centers around the world (Werner et al., 2013)) is demonstrated by the presented case studies. We will also highlight the possibility to give real-time insight into the working of the DA methods applied for supporting the forecaster as mentioned as one of the burning issues by Liu et al., (2012).

Understanding Decision-Making in Specialized Domestic Violence Courts: Can Contemporary Theoretical Frameworks Help Guide These Decisions?

PubMed

Pinchevsky, Gillian M

2016-05-22

This study fills a gap in the literature by exploring the utility of contemporary courtroom theoretical frameworks-uncertainty avoidance, causal attribution, and focal concerns-for explaining decision-making in specialized domestic violence courts. Using data from two specialized domestic violence courts, this study explores the predictors of prosecutorial and judicial decision-making and the extent to which these factors are congruent with theoretical frameworks often used in studies of court processing. Findings suggest that these theoretical frameworks only partially help explain decision-making in the courts under study. A discussion of the findings and implications for future research is provided. © The Author(s) 2016.

A game theory perspective on environmental assessment: What games are played and what does this tell us about decision making rationality and legitimacy?

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

Bond, Alan; Research Unit for Environmental Sciences and Management, North-West University; Pope, Jenny

Game theory provides a useful theoretical framework to examine the decision process operating in the context of environmental assessment, and to examine the rationality and legitimacy of decision-making subject to Environmental Assessment (EA). The research uses a case study of the Environmental Impact Assessment and Sustainability Appraisal processes undertaken in England. To these are applied an analytical framework, based on the concept of decision windows to identify the decisions to be assessed. The conditions for legitimacy are defined, based on game theory, in relation to the timing of decision information, the behaviour type (competitive, reciprocal, equity) exhibited by the decisionmore » maker, and the level of public engagement; as, together, these control the type of rationality which can be brought to bear on the decision. Instrumental rationality is based on self-interest of individuals, whereas deliberative rationality seeks broader consensus and is more likely to underpin legitimate decisions. The results indicate that the Sustainability Appraisal process, conducted at plan level, is better than EIA, conducted at project level, but still fails to provide conditions that facilitate legitimacy. Game theory also suggests that Sustainability Appraisal is likely to deliver ‘least worst’ outcomes rather than best outcomes when the goals of the assessment process are considered; this may explain the propensity of such ‘least worst’ decisions in practise. On the basis of what can be learned from applying this game theory perspective, it is suggested that environmental assessment processes need to be redesigned and better integrated into decision making in order to guarantee the legitimacy of the decisions made. - Highlights: • Decision legitimacy is defined in terms of game theory. • Game theory is applied to EIA and SA decision windows. • Game theory suggests least worst outcomes prevail. • SA is more likely to be perceived legitimate than EIA.« less

Decision Modeling Framework to Minimize Arrival Delays from Ground Delay Programs

NASA Astrophysics Data System (ADS)

Mohleji, Nandita

Convective weather and other constraints create uncertainty in air transportation, leading to costly delays. A Ground Delay Program (GDP) is a strategy to mitigate these effects. Systematic decision support can increase GDP efficacy, reduce delays, and minimize direct operating costs. In this study, a decision analysis (DA) model is constructed by combining a decision tree and Bayesian belief network. Through a study of three New York region airports, the DA model demonstrates that larger GDP scopes that include more flights in the program, along with longer lead times that provide stakeholders greater notice of a pending program, trigger the fewest average arrival delays. These findings are demonstrated to result in a savings of up to $1,850 per flight. Furthermore, when convective weather is predicted, forecast weather confidences remain the same level or greater at least 70% of the time, supporting more strategic decision making. The DA model thus enables quantification of uncertainties and insights on causal relationships, providing support for future GDP decisions.

Mathematical Modelling-Based Energy System Operation Strategy Considering Energy Storage Systems

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

Ryu, Jun-Hyung; Hodge, Bri-Mathias

2016-06-25

Renewable energy resources are widely recognized as an alternative to environmentally harmful fossil fuels. More renewable energy technologies will need to penetrate into fossil fuel dominated energy systems to mitigate the globally witnessed climate changes and environmental pollutions. It is necessary to prepare for the potential problems with increased proportions of renewable energy in the energy system, to prevent higher costs and decreased reliability. Motivated by this need, this paper addresses the operation of an energy system with an energy storage system in the context of developing a decision-supporting framework.

Application of data mining in performance measures

NASA Astrophysics Data System (ADS)

Chan, Michael F. S.; Chung, Walter W.; Wong, Tai Sun

2001-10-01

This paper proposes a structured framework for exploiting data mining application for performance measures. The context is set in an airline company is illustrated for the use of such framework. The framework takes in consideration of how a knowledge worker interacts with performance information at the enterprise level to support them to make informed decision in managing the effectiveness of operations. A case study of applying data mining technology for performance data in an airline company is illustrated. The use of performance measures is specifically applied to assist in the aircraft delay management process. The increasingly dispersed and complex operations of airline operation put much strain on the part of knowledge worker in using search, acquiring and analyzing information to manage performance. One major problem faced with knowledge workers is the identification of root causes of performance deficiency. The large amount of factors involved in the analyze the root causes can be time consuming and the objective of applying data mining technology is to reduce the time and resources needed for such process. The increasing market competition for better performance management in various industries gives rises to need of the intelligent use of data. Because of this, the framework proposed here is very much generalizable to industries such as manufacturing. It could assist knowledge workers who are constantly looking for ways to improve operation effectiveness through new initiatives and the effort is required to be quickly done to gain competitive advantage in the marketplace.

Optimal joint detection and estimation that maximizes ROC-type curves

PubMed Central

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K.

2017-01-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation. PMID:27093544

Optimal Joint Detection and Estimation That Maximizes ROC-Type Curves.

PubMed

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K

2016-09-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation.

Mainstreaming Climate Change: Recent and Ongoing Efforts to Understand, Improve, and Expand Consideration of Climate Change in Federal Water Resources Planning

NASA Astrophysics Data System (ADS)

Ferguson, I. M.; McGuire, M.; Broman, D.; Gangopadhyay, S.

2017-12-01

The Bureau of Reclamation is a Federal agency tasked with developing and managing water supply and hydropower projects in the Western U.S. Climate and hydrologic variability and change significantly impact management actions and outcomes across Reclamation's programs and initiatives, including water resource planning and operations, infrastructure design and maintenance, hydropower generation, and ecosystem restoration, among others. Planning, design, and implementation of these programs therefore requires consideration of future climate and hydrologic conditions will impact program objectives. Over the past decade, Reclamation and other Federal agencies have adopted new guidelines, directives, and mandates that require consideration of climate change in water resources planning and decision making. Meanwhile, the scientific community has developed a large number of climate projections, along with an array of models, methods, and tools to facilitate consideration of climate projections in planning and decision making. However, water resources engineers, planners, and decision makers continue to face challenges regarding how best to use the available data and tools to support major decisions, including decisions regarding infrastructure investments and long-term operating criteria. This presentation will discuss recent and ongoing research towards understanding, improving, and expanding consideration of climate projections and related uncertainties in Federal water resources planning and decision making. These research efforts address a variety of challenges, including: How to choose between available climate projection datasets and related methods, models, and tools—many of which are considered experimental or research tools? How to select an appropriate decision framework when design or operating alternatives may differ between climate scenarios? How to effectively communicate results of a climate impacts analysis to decision makers? And, how to improve robustness and resilience of water resources systems in the face of significant uncertainty? Discussion will focus on the intersection between technical challenges and decision making paradigms and the need for improved scientist-decision maker engagement through the lens of this Federal water management agency.

CAreDroid: Adaptation Framework for Android Context-Aware Applications

PubMed Central

Elmalaki, Salma; Wanner, Lucas; Srivastava, Mani

2015-01-01

Context-awareness is the ability of software systems to sense and adapt to their physical environment. Many contemporary mobile applications adapt to changing locations, connectivity states, available computational and energy resources, and proximity to other users and devices. Nevertheless, there is little systematic support for context-awareness in contemporary mobile operating systems. Because of this, application developers must build their own context-awareness adaptation engines, dealing directly with sensors and polluting application code with complex adaptation decisions. In this paper, we introduce CAreDroid, which is a framework that is designed to decouple the application logic from the complex adaptation decisions in Android context-aware applications. In this framework, developers are required— only—to focus on the application logic by providing a list of methods that are sensitive to certain contexts along with the permissible operating ranges under those contexts. At run time, CAreDroid monitors the context of the physical environment and intercepts calls to sensitive methods, activating only the blocks of code that best fit the current physical context. CAreDroid is implemented as part of the Android runtime system. By pushing context monitoring and adaptation into the runtime system, CAreDroid eases the development of context-aware applications and increases their efficiency. In particular, case study applications implemented using CAre-Droid are shown to have: (1) at least half lines of code fewer and (2) at least 10× more efficient in execution time compared to equivalent context-aware applications that use only standard Android APIs. PMID:26834512

CAreDroid: Adaptation Framework for Android Context-Aware Applications.

PubMed

Elmalaki, Salma; Wanner, Lucas; Srivastava, Mani

2015-09-01

Context-awareness is the ability of software systems to sense and adapt to their physical environment. Many contemporary mobile applications adapt to changing locations, connectivity states, available computational and energy resources, and proximity to other users and devices. Nevertheless, there is little systematic support for context-awareness in contemporary mobile operating systems. Because of this, application developers must build their own context-awareness adaptation engines, dealing directly with sensors and polluting application code with complex adaptation decisions. In this paper, we introduce CAreDroid, which is a framework that is designed to decouple the application logic from the complex adaptation decisions in Android context-aware applications. In this framework, developers are required- only-to focus on the application logic by providing a list of methods that are sensitive to certain contexts along with the permissible operating ranges under those contexts. At run time, CAreDroid monitors the context of the physical environment and intercepts calls to sensitive methods, activating only the blocks of code that best fit the current physical context. CAreDroid is implemented as part of the Android runtime system. By pushing context monitoring and adaptation into the runtime system, CAreDroid eases the development of context-aware applications and increases their efficiency. In particular, case study applications implemented using CAre-Droid are shown to have: (1) at least half lines of code fewer and (2) at least 10× more efficient in execution time compared to equivalent context-aware applications that use only standard Android APIs.

Strategic Environmental Assessment of Greenhouse Gas Mitigation Options in the Canadian Agricultural Sector

NASA Astrophysics Data System (ADS)

Noble, Bram F.; Christmas, Lisa M.

2008-01-01

This article presents a methodological framework for strategic environmental assessment (SEA) application. The overall objective is to demonstrate SEA as a systematic and structured policy, plan, and program (PPP) decision support tool. In order to accomplish this objective, a stakeholder-based SEA application to greenhouse gas (GHG) mitigation policy options in Canadian agriculture is presented. Using a mail-out impact assessment exercise, agricultural producers and nonproducers from across the Canadian prairie region were asked to evaluate five competing GHG mitigation options against 13 valued environmental components (VECs). Data were analyzed using multi-criteria and exploratory analytical techniques. The results suggest considerable variation in perceived impacts and GHG mitigation policy preferences, suggesting that a blanket policy approach to GHG mitigation will create gainers and losers based on soil type and associate cropping and on-farm management practices. It is possible to identify a series of regional greenhouse gas mitigation programs that are robust, socially meaningful, and operationally relevant to both agricultural producers and policy decision makers. The assessment demonstrates the ability of SEA to address, in an operational sense, environmental problems that are characterized by conflicting interests and competing objectives and alternatives. A structured and systematic SEA methodology provides the necessary decision support framework for the consideration of impacts, and allows for PPPs to be assessed based on a much broader set of properties, objectives, criteria, and constraints whereas maintaining rigor and accountability in the assessment process.

A Planning and Decision-Making Framework for Ecological Restoration.

ERIC Educational Resources Information Center

Wyant, James G.; And Others

1995-01-01

Provides a definition for restoration ecology that is suitable for extensive terrestrial applications and presents a decision framework to help organize different phases of the decision process. Encourages a wider spectrum of participants and decisions than have been traditionally employed for restoration planning. (AIM)

Nebraska biocontainment unit design and operations.

PubMed

Lenaghan, Patricia A; Schwedhelm, Michelle

2015-06-01

Planning and design of a unique biocontainment unit specifically for care of patients with rare and highly infectious diseases presented an opportunity for nurse leaders to engage staff in crucial groundbreaking decisions. The Magnet® philosophy and framework were used to structure committees with key stakeholders and staff to ensure best and safe practices. Members of the biocontainment unit are engaged in active research and outreach training.

Pipeline Optimization Program (PLOP)

DTIC Science & Technology

2006-08-01

the framework of the Dredging Operations Decision Support System (DODSS, https://dodss.wes.army.mil/wiki/0). PLOP compiles industry standards and...efficiency point ( BEP ). In the interest of acceptable wear rate on the pump, industrial standards dictate that the flow Figure 2. Pump class as a function of...percentage of the flow rate corresponding to the BEP . Pump Acceptability Rules. The facts for pump performance, industrial standards and pipeline and

Natural Information Processing Rules: Formal Theory and Applications to Ethnography. Monographs of the Language Behavior Research Laboratory, No. 3.

ERIC Educational Resources Information Center

Geoghegan, William H.

This monograph represents the results of an attempt to construct at least one portion of a theoretical framework for describing and analyzing the performance routines used by the native actor to realize his competence to make culturally appropriate decisions. In general the concern is to describe in theoretical terms the structure and operation of…

The use of Ethics Decision-Making Frameworks by Canadian Ethics Consultants: A Qualitative Study.

PubMed

Kaposy, Chris; Brunger, Fern; Maddalena, Victor; Singleton, Richard

2016-10-01

In this study, Canadian healthcare ethics consultants describe their use of ethics decision-making frameworks. Our research finds that ethics consultants in Canada use multi-purpose ethics decision-making frameworks, as well as targeted frameworks that focus on reaching an ethical resolution to a particular healthcare issue, such as adverse event reporting, or difficult triage scenarios. Several interviewees mention the influence that the accreditation process in Canadian healthcare organizations has on the adoption and use of such frameworks. Some of the ethics consultants we interviewed also report on their reluctance to use these tools. Limited empirical work has been done previously on the use of ethics decision-making frameworks. This study begins to fill this gap in our understanding of the work of healthcare ethics consultants. © 2016 John Wiley & Sons Ltd.

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems

USGS Publications Warehouse

Wilson, Robyn S.; Hardisty, David J.; Epanchin-Niell, Rebecca S.; Runge, Michael C.; Cottingham, Kathryn L.; Urban, Dean L.; Maguire, Lynn A.; Hastings, Alan; Mumby, Peter J.; Peters, Debra P.C.

2016-01-01

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

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.

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems.

PubMed

Wilson, Robyn S; Hardisty, David J; Epanchin-Niell, Rebecca S; Runge, Michael C; Cottingham, Kathryn L; Urban, Dean L; Maguire, Lynn A; Hastings, Alan; Mumby, Peter J; Peters, Debra P C

2016-02-01

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers' actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed. © 2015 Society for Conservation Biology.

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.

How is the New Public Management applied in the occupational health care system? - decision-makers' and OH personnel's views in Finland

PubMed Central

2011-01-01

Background In many countries occupational health care system is in change. Occupational health studies are mainly focused on occupational health substance and content. This study offers new perspectives on municipal OHS and its operations from management perspective. Aim The aim of this study is to analyse how New Public Management (NPM) doctrines are applied in the Finnish occupational health care system (OHS). The main focus is to describe and compare the views of decision-makers' and OH workers within the framework of NPM. Methods The data were collected by semi-structured interviews from 17 municipal decision-makers' and 26 municipal OH workers. Data was analyzed by examining coded data in a theory-driven way according to Hood's doctrine of NPM. Results The doctrines were not as compatible with the OH personnel view as with the decision-makers' view. Decision-makers and OH personnel highlighted the strict criteria required for operation evaluation. Moreover, decision-makers strongly accentuated professional management in the public sector and the reorganization of public sector units. These were not equally relevant in OH personnel views. In OH personnel views, other doctrines (more attention to performance and accomplishments, emphasizing and augmentation of the competition and better control of public expense and means test) were not similarly in evidence, only weak evidence was observed when their importance viewed as medium by decision-makers. Neither of the respondents group kept the doctrine of management models of the private sector relevant. Conclusions The NPM and Hoods doctrine fitted well with OH research. The doctrine brought out view differences and similarities between decision-makers and OH personnel. For example, policymakers highlighted more strongly the structural change by emphasizing professional management compared to OH personnel. The need for reorganization of municipal OH, regardless of different operational preconditions, was obvious for both decision-makers and OH personnel. The adaptation of more clarify management to a municipal context is not trouble-free. The municipality systemic structure, complex operational environment, and reconciliation of political and officer authority set challenges to management of municipalities. PMID:21880141

Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations

PubMed Central

Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W.

2016-01-01

Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty’s 1–9 scale, this paper proposes a cross-ratio-based bipolar 0.1–0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness. PMID:27618082

Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

PubMed

Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W

2016-09-09

Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness.

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

PubMed

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

2010-01-01

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

RPD-based Hypothesis Reasoning for Cyber Situation Awareness

NASA Astrophysics Data System (ADS)

Yen, John; McNeese, Michael; Mullen, Tracy; Hall, David; Fan, Xiaocong; Liu, Peng

Intelligence workers such as analysts, commanders, and soldiers often need a hypothesis reasoning framework to gain improved situation awareness of the highly dynamic cyber space. The development of such a framework requires the integration of interdisciplinary techniques, including supports for distributed cognition (human-in-the-loop hypothesis generation), supports for team collaboration (identification of information for hypothesis evaluation), and supports for resource-constrained information collection (hypotheses competing for information collection resources). We here describe a cognitively-inspired framework that is built upon Klein’s recognition-primed decision model and integrates the three components of Endsley’s situation awareness model. The framework naturally connects the logic world of tools for cyber situation awareness with the mental world of human analysts, enabling the perception, comprehension, and prediction of cyber situations for better prevention, survival, and response to cyber attacks by adapting missions at the operational, tactical, and strategic levels.

A decision support tool for adaptive management of native prairie ecosystems

USGS Publications Warehouse

Hunt, Victoria M.; Jacobi, Sarah; Gannon, Jill J.; Zorn, Jennifer E.; Moore, Clinton; Lonsdorf, Eric V.

2016-01-01

The Native Prairie Adaptive Management initiative is a decision support framework that provides cooperators with management-action recommendations to help them conserve native species and suppress invasive species on prairie lands. We developed a Web-based decision support tool (DST) for the U.S. Fish and Wildlife Service and the U.S. Geological Survey initiative. The DST facilitates cross-organizational data sharing, performs analyses to improve conservation delivery, and requires no technical expertise to operate. Each year since 2012, the DST has used monitoring data to update ecological knowledge that it translates into situation-specific management-action recommendations (e.g., controlled burn or prescribed graze). The DST provides annual recommendations for more than 10,000 acres on 20 refuge complexes in four U.S. states. We describe how the DST promotes the long-term implementation of the program for which it was designed and may facilitate decision support and improve ecological outcomes of other conservation efforts.

Maternal Decision-making During Pregnancy: Parental Obligations and Cultural Differences.

PubMed

Malek, Janet

2017-08-01

Decision-making during pregnancy can be ethically complex. This paper offers a framework for maternal decision-making and clinical counseling that can be used to approach such decisions in a systematic way. Three fundamental questions are addressed: (1) Who should make decisions? (2) How should decisions be made? and (3) What is the role of the clinician? The proposed framework emphasizes the decisional authority of the pregnant woman. It draws ethical support from the concept of a good parent and the requirements of parental obligations. It also describes appropriate counseling methods for clinicians in light of those parental obligations. Finally, the paper addresses how cultural differences may shape the framework's guidance of maternal decision-making during pregnancy. Copyright © 2017. Published by Elsevier Ltd.

Conceptual framework for the mapping of management process with information technology in a business process.

PubMed

Rajarathinam, Vetrickarthick; Chellappa, Swarnalatha; Nagarajan, Asha

2015-01-01

This study on component framework reveals the importance of management process and technology mapping in a business environment. We defined ERP as a software tool, which has to provide business solution but not necessarily an integration of all the departments. Any business process can be classified as management process, operational process and the supportive process. We have gone through entire management process and were enable to bring influencing components to be mapped with a technology for a business solution. Governance, strategic management, and decision making are thoroughly discussed and the need of mapping these components with the ERP is clearly explained. Also we suggest that implementation of this framework might reduce the ERP failures and especially the ERP misfit was completely rectified.

Conceptual Framework for the Mapping of Management Process with Information Technology in a Business Process

PubMed Central

Chellappa, Swarnalatha; Nagarajan, Asha

2015-01-01

This study on component framework reveals the importance of management process and technology mapping in a business environment. We defined ERP as a software tool, which has to provide business solution but not necessarily an integration of all the departments. Any business process can be classified as management process, operational process and the supportive process. We have gone through entire management process and were enable to bring influencing components to be mapped with a technology for a business solution. Governance, strategic management, and decision making are thoroughly discussed and the need of mapping these components with the ERP is clearly explained. Also we suggest that implementation of this framework might reduce the ERP failures and especially the ERP misfit was completely rectified. PMID:25861688

Judgment and decision making.

PubMed

Mellers, B A; Schwartz, A; Cooke, A D

1998-01-01

For many decades, research in judgment and decision making has examined behavioral violations of rational choice theory. In that framework, rationality is expressed as a single correct decision shared by experimenters and subjects that satisfies internal coherence within a set of preferences and beliefs. Outside of psychology, social scientists are now debating the need to modify rational choice theory with behavioral assumptions. Within psychology, researchers are debating assumptions about errors for many different definitions of rationality. Alternative frameworks are being proposed. These frameworks view decisions as more reasonable and adaptive that previously thought. For example, "rule following." Rule following, which occurs when a rule or norm is applied to a situation, often minimizes effort and provides satisfying solutions that are "good enough," though not necessarily the best. When rules are ambiguous, people look for reasons to guide their decisions. They may also let their emotions take charge. This chapter presents recent research on judgment and decision making from traditional and alternative frameworks.

Cultural targeting and tailoring of shared decision making technology: a theoretical framework for improving the effectiveness of patient decision aids in culturally diverse groups.

PubMed

Alden, Dana L; Friend, John; Schapira, Marilyn; Stiggelbout, Anne

2014-03-01

Patient decision aids are known to positively impact outcomes critical to shared decision making (SDM), such as gist knowledge and decision preparedness. However, research on the potential improvement of these and other important outcomes through cultural targeting and tailoring of decision aids is very limited. This is the case despite extensive evidence supporting use of cultural targeting and tailoring to improve the effectiveness of health communications. Building on prominent psychological theory, we propose a two-stage framework incorporating cultural concepts into the design process for screening and treatment decision aids. The first phase recommends use of cultural constructs, such as collectivism and individualism, to differentially target patients whose cultures are known to vary on these dimensions. Decision aid targeting is operationalized through use of symbols and values that appeal to members of the given culture. Content dimensions within decision aids that appear particularly appropriate for targeting include surface level visual characteristics, language, beliefs, attitudes and values. The second phase of the framework is based on evidence that individuals vary in terms of how strongly cultural norms influence their approach to problem solving and decision making. In particular, the framework hypothesizes that differences in terms of access to cultural mindsets (e.g., access to interdependent versus independent self) can be measured up front and used to tailor decision aids. Thus, the second phase in the framework emphasizes the importance of not only targeting decision aid content, but also tailoring the information to the individual based on measurement of how strongly he/she is connected to dominant cultural mindsets. Overall, the framework provides a theory-based guide for researchers and practitioners who are interested in using cultural targeting and tailoring to develop and test decision aids that move beyond a "one-size fits all" approach and thereby, improve SDM in our multicultural world. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

District decision-making for health in low-income settings: a feasibility study of a data-informed platform for health in India, Nigeria and Ethiopia.

PubMed

Avan, Bilal Iqbal; Berhanu, Della; Umar, Nasir; Wickremasinghe, Deepthi; Schellenberg, Joanna

2016-09-01

Low-resource settings often have limited use of local data for health system planning and decision-making. To promote local data use for decision-making and priority setting, we propose an adapted framework: a data-informed platform for health (DIPH) aimed at guiding coordination, bringing together key data from the public and private sectors on inputs and processes. In working to transform this framework from a concept to a health systems initiative, we undertook a series of implementation research activities including background assessment, testing and scaling up of the intervention. This first paper of four reports the feasibility of the approach in a district health systems context in five districts of India, Nigeria and Ethiopia. We selected five districts using predefined criteria and in collaboration with governments. After scoping visits, an in-depth field visit included interviews with key health stakeholders, focus group discussions with service-delivery staff and record review. For analysis, we used five dimensions of feasibility research based on the TELOS framework: technology and systems, economic, legal and political, operational and scheduling feasibility. We found no standardized process for data-based district level decision-making, and substantial obstacles in all three countries. Compared with study areas in Ethiopia and Nigeria, the health system in Uttar Pradesh is relatively amenable to the DIPH, having relative strengths in infrastructure, technological and technical expertise, and financial resources, as well as a district-level stakeholder forum. However, a key challenge is the absence of an effective legal framework for engagement with India's extensive private health sector. While priority-setting may depend on factors beyond better use of local data, we conclude that a formative phase of intervention development and pilot-testing is warranted as a next step. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

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.

District decision-making for health in low-income settings: a feasibility study of a data-informed platform for health in India, Nigeria and Ethiopia

PubMed Central

Avan, Bilal Iqbal; Berhanu, Della; Umar, Nasir; Wickremasinghe, Deepthi; Schellenberg, Joanna

2016-01-01

Low-resource settings often have limited use of local data for health system planning and decision-making. To promote local data use for decision-making and priority setting, we propose an adapted framework: a data-informed platform for health (DIPH) aimed at guiding coordination, bringing together key data from the public and private sectors on inputs and processes. In working to transform this framework from a concept to a health systems initiative, we undertook a series of implementation research activities including background assessment, testing and scaling up of the intervention. This first paper of four reports the feasibility of the approach in a district health systems context in five districts of India, Nigeria and Ethiopia. We selected five districts using predefined criteria and in collaboration with governments. After scoping visits, an in-depth field visit included interviews with key health stakeholders, focus group discussions with service-delivery staff and record review. For analysis, we used five dimensions of feasibility research based on the TELOS framework: technology and systems, economic, legal and political, operational and scheduling feasibility. We found no standardized process for data-based district level decision-making, and substantial obstacles in all three countries. Compared with study areas in Ethiopia and Nigeria, the health system in Uttar Pradesh is relatively amenable to the DIPH, having relative strengths in infrastructure, technological and technical expertise, and financial resources, as well as a district-level stakeholder forum. However, a key challenge is the absence of an effective legal framework for engagement with India’s extensive private health sector. While priority-setting may depend on factors beyond better use of local data, we conclude that a formative phase of intervention development and pilot-testing is warranted as a next step. PMID:27591204

Stakeholders apply the GRADE evidence-to-decision framework to facilitate coverage decisions.

PubMed

Dahm, Philipp; Oxman, Andrew D; Djulbegovic, Benjamin; Guyatt, Gordon H; Murad, M Hassan; Amato, Laura; Parmelli, Elena; Davoli, Marina; Morgan, Rebecca L; Mustafa, Reem A; Sultan, Shahnaz; Falck-Ytter, Yngve; Akl, Elie A; Schünemann, Holger J

2017-06-01

Coverage decisions are complex and require the consideration of many factors. A well-defined, transparent process could improve decision-making and facilitate decision-maker accountability. We surveyed key US-based stakeholders regarding their current approaches for coverage decisions. Then, we held a workshop to test an evidence-to-decision (EtD) framework for coverage based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria. A total of 42 individuals (including 19 US stakeholders as well as international health policymakers and GRADE working group members) attended the workshop. Of the 19 stakeholders, 14 (74%) completed the survey before the workshop. Almost all of their organizations (13 of 14; 93%) used systematic reviews for coverage decision-making; few (2 of 14; 14%) developed their own evidence synthesis; a majority (9 of 14; 64%) rated the certainty of evidence (using various systems); almost all (13 of 14; 93%) denied formal consideration of resource use; and half (7 of 14; 50%) reported explicit criteria for decision-making. At the workshop, stakeholders successfully applied the EtD framework to four case studies and provided narrative feedback, which centered on contextual factors affecting coverage decisions in the United States, the need for reliable data on subgroups of patients, and the challenge of decision-making without formal consideration of resource use. Stakeholders successfully applied the EtD framework to four case studies and highlighted contextual factors affecting coverage decisions and affirmed its value. Their input informed the further development of a revised EtD framework, now publicly available (http://gradepro.org/). Published by Elsevier Inc.

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

PubMed

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

2012-02-01

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

Strategic management system in a healthcare setting--moving from strategy to results.

PubMed

Devitt, Rob; Klassen, Wolf; Martalog, Julian

2005-01-01

One of the historical challenges in the healthcare system has been the identification and collection of meaningful data to measure an organization's progress towards the achievement of its strategic goals and the concurrent alignment of internal operating practices with this strategy. Over the last 18 months the Toronto East General Hospital (TEGH) has adopted a strategic management system and organizing framework that has led to a metric-based strategic plan. It has allowed for formal and measurable linkages across a full range of internal business processes, from the annual operating plan to resource allocation decisions, to the balanced scorecard and individual performance evaluations. The Strategic Management System (SMS) aligns organizational planning and performance measurement, facilitates an appropriate balance between organizational priorities and resolving "local" problems, and encourages behaviours that are consistent with the values upon which the organization is built. The TEGH Accountability Framework serves as the foundation for the entire system. A key tool of the system is the rolling three-year strategic plan for the organization that sets out specific annual improvement targets on a number of key strategic measures. Individual program/department plans with corresponding measures ensure that the entire organization is moving forward strategically. Each year, all plans are reviewed, with course adjustments made to reflect changes in the hospital's environment and with re-calibration of performance targets for the next three years to ensure continued improvement and organizational progress. This system has been used through one annual business cycle. Results from the past year show measurable success. The hospital has improved on 12 of the 15 strategic plan metrics, including achieving the targeted 1% operating surplus while operating in an environment of tremendous change and uncertainty. This article describes the strategic management system used at TEGH and demonstrates the formal integration of the plan into its operating and decision making processes. It also provides examples of the metrics, their use in decision-making and the variance reporting and improvement mechanisms. The article also demonstrates that a measurement-oriented approach to the planning and delivery of community hospital service is both achievable and valuable in terms of accountability and organizational responsiveness.

Decision Regulation Impact Statement for Changes to the National Quality Framework

ERIC Educational Resources Information Center

Education Council, 2017

2017-01-01

The purpose of this Decision Regulation Impact Statement (Decision RIS) is to recommend preferred options for improving the National Quality Framework for Early Childhood Education and Care. The Decision RIS follows the public release of the Consultation RIS and incorporates stakeholders' views and comments received during the ten week stakeholder…

Gray marketing of pharmaceuticals.

PubMed

Chaudhry, P E; Walsh, M G

1995-01-01

Pharmaceutical marketers in the European Union are constrained by regulated prices, opening up opportunities for gray marketers. The authors investigate the legal framework that regulates gray markets by summarizing and analyzing relevant European Court of Justice decisions that favor gray marketers and actually foster parallel trade. Before marketing managers can develop effective strategies in this marketplace, they must first understand the precedents of the legal system in which they will be operating.

The marketing audit: a new perspective on library services and products.

PubMed Central

Wakeley, P J; Poole, C; Foster, E C

1988-01-01

A marketing audit enables a library to look at audiences, services, and products with a structured approach. The audit can be used to assess operations and to provide a framework for ongoing decision making, evaluation, and long-range planning. An approach to the audit process is presented and its application is demonstrated in a case study featuring the American Hospital Association Resource Center. PMID:3066426

Application of process monitoring to anomaly detection in nuclear material processing systems via system-centric event interpretation of data from multiple sensors of varying reliability

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

Garcia, Humberto E.; Simpson, Michael F.; Lin, Wen-Chiao

In this paper, we apply an advanced safeguards approach and associated methods for process monitoring to a hypothetical nuclear material processing system. The assessment regarding the state of the processing facility is conducted at a systemcentric level formulated in a hybrid framework. This utilizes architecture for integrating both time- and event-driven data and analysis for decision making. While the time-driven layers of the proposed architecture encompass more traditional process monitoring methods based on time series data and analysis, the event-driven layers encompass operation monitoring methods based on discrete event data and analysis. By integrating process- and operation-related information and methodologiesmore » within a unified framework, the task of anomaly detection is greatly improved. This is because decision-making can benefit from not only known time-series relationships among measured signals but also from known event sequence relationships among generated events. This available knowledge at both time series and discrete event layers can then be effectively used to synthesize observation solutions that optimally balance sensor and data processing requirements. The application of the proposed approach is then implemented on an illustrative monitored system based on pyroprocessing and results are discussed.« less

Developing a Decision Support System for Flood Response: NIMS/ICS Fundamentals

NASA Astrophysics Data System (ADS)

Gutenson, J. L.; Zhang, X.; Ernest, A. N. S.; Oubeidillah, A.; Zhu, L.

2015-12-01

Effective response to regional disasters such as floods requires a multipronged, non-linear approach to reduce loss of life, property and harm to the environment. These coordinated response actions are typically undertaken by multiple jurisdictions, levels of government, functional agencies and other responsible entities. A successful response is highly dependent on the effectiveness and efficiency of each coordinated response action undertaken across a broad spectrum of organizations and activities. In order to provide a unified framework for those responding to incidents or planned events, FEMA provides a common and flexible approach for managing incidents, regardless of cause, size, location or complexity, referred to as the National Incident Management System (NIMS). Integral to NIMS is the Incident Command System (ICS), which establishes a common, pre-defined organizational structure to ensure coordination and management of procedures, resources and communications, for efficient incident management. While being both efficient and rigorous, NIMS, and ICS to a lesser extent, is an inherently complex framework that requires significant amount of training for planners, responders and managers to master, especially considering the wide array of incident types that Local Emergency Planning Committees (LEPCs) must be prepared to respond to. The existing Water-Wizard Decision Support System (DSS), developed to support water distribution system recovery operations for Decontamination (Decon), Operational Optimization (WDS), and Economic Consequence Assessment (Econ), is being evolved to integrate incident response functions. Water-Wizard runs on both mobile and desktop devices, and is being extended to utilize smartphone and mobile device specific data streams (e.g GPS location) to augment its fact-base in real-time for situational-aware DSS recommendations. In addition, the structured NIMS and ICS frameworks for incident management and response are being incorporated into the Water-Wizard knowledgebase, with a mid-term goal of integrating flood-specific emergency response domain knowledge to provide a real-time flood responder decision support.

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

PubMed

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

2017-01-01

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

Decision space for health workforce management in decentralized settings: a case study in Uganda.

PubMed

Alonso-Garbayo, Alvaro; Raven, Joanna; Theobald, Sally; Ssengooba, Freddie; Nattimba, Milly; Martineau, Tim

2017-11-01

The aim of this paper is to improve understanding about how district health managers perceive and use their decision space for human resource management (HRM) and how this compares with national policies and regulatory frameworks governing HRM. The study builds upon work undertaken by PERFORM Research Consortium in Uganda using action-research to strengthen human resources management in the health sector. To assess the decision space that managers have in six areas of HRM (e.g. policy, planning, remuneration and incentives, performance management, education and information) the study compares the roles allocated by Uganda's policy and regulatory frameworks with the actual room for decision-making that district health managers perceive that they have. Results show that in some areas District Health Management Team (DHMT) members make decisions beyond their conferred authority while in others they do not use all the space allocated by policy. DHMT members operate close to the boundaries defined by public policy in planning, remuneration and incentives, policy and performance management. However, they make decisions beyond their conferred authority in the area of information and do not use all the space allocated by policy in the area of education. DHMTs' decision-making capacity to manage their workforce is influenced by their own perceived authority and sometimes it is constrained by decisions made at higher levels. We can conclude that decentralization, to improve workforce performance, needs to devolve power further down from district authorities onto district health managers. DHMTs need not only more power and authority to make decisions about their workforce but also more control over resources to be able to implement these decisions. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A proposed simulation optimization model framework for emergency department problems in public hospital

NASA Astrophysics Data System (ADS)

Ibrahim, Ireen Munira; Liong, Choong-Yeun; Bakar, Sakhinah Abu; Ahmad, Norazura; Najmuddin, Ahmad Farid

2015-12-01

The Emergency Department (ED) is a very complex system with limited resources to support increase in demand. ED services are considered as good quality if they can meet the patient's expectation. Long waiting times and length of stay is always the main problem faced by the management. The management of ED should give greater emphasis on their capacity of resources in order to increase the quality of services, which conforms to patient satisfaction. This paper is a review of work in progress of a study being conducted in a government hospital in Selangor, Malaysia. This paper proposed a simulation optimization model framework which is used to study ED operations and problems as well as to find an optimal solution to the problems. The integration of simulation and optimization is hoped can assist management in decision making process regarding their resource capacity planning in order to improve current and future ED operations.

Placing ecosystem services at the heart of urban water systems management.

PubMed

Garcia, X; Barceló, D; Comas, J; Corominas, Ll; Hadjimichael, A; Page, T J; Acuña, V

2016-09-01

Current approaches have failed to deliver a truly integrated management of the different elements of the urban water system, such as freshwater ecosystems, drinking water treatment plants, distribution networks, sewer systems and wastewater treatment plants. Because the different parts of urban water have not been well integrated, poor decisions have been made for society in general, leading to the misuse of water resources, the degradation of freshwater ecosystems and increased overall treatment costs. Some attempts to solve environmental issues have adopted the ecosystem services concept in a more integrated approach, however this has rarely strayed far away from pure policy, and has made little impact in on-the-ground operational matters. Here, we present an improved decision-making framework to integrate the management of urban water systems. This framework uses the ecosystem service concept in a practical way to make a better use of both financial and water resources, while continuing to preserve the environment. Copyright © 2016 Elsevier B.V. All rights reserved.

Diagnostic Reasoning using Prognostic Information for Unmanned Aerial Systems

NASA Technical Reports Server (NTRS)

Schumann, Johann; Roychoudhury, Indranil; Kulkarni, Chetan

2015-01-01

With increasing popularity of unmanned aircraft, continuous monitoring of their systems, software, and health status is becoming more and more important to ensure safe, correct, and efficient operation and fulfillment of missions. The paper presents integration of prognosis models and prognostic information with the R2U2 (REALIZABLE, RESPONSIVE, and UNOBTRUSIVE Unit) monitoring and diagnosis framework. This integration makes available statistically reliable health information predictions of the future at a much earlier time to enable autonomous decision making. The prognostic information can be used in the R2U2 model to improve diagnostic accuracy and enable decisions to be made at the present time to deal with events in the future. This will be an advancement over the current state of the art, where temporal logic observers can only do such valuation at the end of the time interval. Usefulness and effectiveness of this integrated diagnostics and prognostics framework was demonstrated using simulation experiments with the NASA Dragon Eye electric unmanned aircraft.

An operational information systems architecture for assessing sustainable transportation planning: principles and design.

PubMed

Borzacchiello, Maria Teresa; Torrieri, Vincenzo; Nijkamp, Peter

2009-11-01

This paper offers the description of an integrated information system framework for the assessment of transportation planning and management. After an introductory exposition, in the first part of the paper, a broad overview of international experiences regarding information systems on transportation is given, focusing in particular on the relationship between transportation system's performance monitoring and the decision-making process, and on the importance of this connection in the evaluation and planning process, in Italian and European cases. Next, the methodological design of an information system to support efficient and sustainable transportation planning and management aiming to integrate inputs from several different data sources is presented. The resulting framework deploys modular and integrated databases which include data stemming from different national or regional data banks and which integrate information belonging to different transportation fields. For this reason, it allows public administrations to account for many strategic elements that influence their decisions regarding transportation, both from a systemic and infrastructural point of view.

The Marine Strategy Framework Directive and the ecosystem-based approach – pitfalls and solutions.

PubMed

Berg, Torsten; Fürhaupter, Karin; Teixeira, Heliana; Uusitalo, Laura; Zampoukas, Nikolaos

2015-07-15

The European Marine Strategy Framework Directive aims at good environmental status (GES) in marine waters, following an ecosystem-based approach, focused on 11 descriptors related to ecosystem features, human drivers and pressures. Furthermore, 29 subordinate criteria and 56 attributes are detailed in an EU Commission Decision. The analysis of the Decision and the associated operational indicators revealed ambiguity in the use of terms, such as indicator, impact and habitat and considerable overlap of indicators assigned to various descriptors and criteria. We suggest re-arrangement and elimination of redundant criteria and attributes avoiding double counting in the subsequent indicator synthesis, a clear distinction between pressure and state descriptors and addition of criteria on ecosystem services and functioning. Moreover, we suggest the precautionary principle should be followed for the management of pressures and an evidence-based approach for monitoring state as well as reaching and maintaining GES. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Resonant Frequency Control For the PIP-II Injector Test RFQ: Control Framework and Initial Results

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

Edelen, A. L.; Biedron, S. G.; Milton, S. V.

For the PIP-II Injector Test (PI-Test) at Fermilab, a four-vane radio frequency quadrupole (RFQ) is designed to accelerate a 30-keV, 1-mA to 10-mA, H- beam to 2.1 MeV under both pulsed and continuous wave (CW) RF operation. The available headroom of the RF amplifiers limits the maximum allowable detuning to 3 kHz, and the detuning is controlled entirely via thermal regulation. Fine control over the detuning, minimal manual intervention, and fast trip recovery is desired. In addition, having active control over both the walls and vanes provides a wider tuning range. For this, we intend to use model predictive controlmore » (MPC). To facilitate these objectives, we developed a dedicated control framework that handles higher-level system decisions as well as executes control calculations. It is written in Python in a modular fashion for easy adjustments, readability, and portability. Here we describe the framework and present the first control results for the PI-Test RFQ under pulsed and CW operation.« less

Establishing Final Cleanup Decisions for the Hanford Site River Corridor

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

Lerch, J.A.; Sands, J.P.

2007-07-01

A major challenge in the River Corridor Closure Contract is establishing final cleanup decisions for the source operable units in the Hanford Site river corridor. Cleanup actions in the river corridor began in 1994 and have been performed in accordance with a 'bias for action' approach adopted by the Tri-Parties - the U.S. Department of Energy, U.S. Environmental Protection Agency, and Washington State Department of Ecology. This approach enabled early application of cleanup dollars on actual remediation of contaminated waste sites. Consequently, the regulatory framework authorizing cleanup actions at source operable units in the river corridor consists largely of interimmore » action records of decision, which were supported by qualitative risk assessments. Obtaining final cleanup decisions for the source operable units is necessary to determine whether past cleanup actions in the river corridor are protective of human health and the environment and to identify any course corrections that may be needed to ensure that ongoing and future cleanup actions are protective. Because the cleanup actions are ongoing, it is desirable to establish the final cleanup decisions as early as possible to minimize the impacts of any identified course corrections to the present cleanup approach. Development of a strategy to obtain final cleanup decisions for the source operable units in a manner that is responsive to desires for an integrated approach with the groundwater and Columbia River components while maintaining the ability to evaluate each component on its own merit represents a significant challenge. There are many different options for grouping final cleanup decisions, and each involved party or stakeholder brings slightly different interests that shape the approach. Regardless of the selected approach, there are several specific challenges and issues to be addressed before making final cleanup decisions. A multi-agency and contractor working group has been established to address these issues and develop an endorsed strategy. Ultimately, it is anticipated that the Tri-Parties will establish a set of milestones to document pathway selection and define schedule requirements. (authors)« less

A GIS-based generic real-time risk assessment framework and decision tools for chemical spills in the river basin.

PubMed

Jiang, Jiping; Wang, Peng; Lung, Wu-seng; Guo, Liang; Li, Mei

2012-08-15

This paper presents a generic framework and decision tools of real-time risk assessment on Emergency Environmental Decision Support System for response to chemical spills in river basin. The generic "4-step-3-model" framework is able to delineate the warning area and the impact on vulnerable receptors considering four types of hazards referring to functional area, societal impact, and human health and ecology system. Decision tools including the stand-alone system and software components were implemented on GIS platform. A detailed case study on the Songhua River nitrobenzene spill illustrated the goodness of the framework and tool Spill first responders and decision makers of catchment management will benefit from the rich, visual and dynamic hazard information output from the software. Copyright © 2012 Elsevier B.V. All rights reserved.

Moving beyond the cost-loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker

NASA Astrophysics Data System (ADS)

Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier Filion, Thomas-Charles

2017-06-01

A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority of, if not all, existing hydro-economic studies rely on a cost-loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known Constant Absolute Risk Aversion (CARA) utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed deterministic forecasts, forecasts based on meteorological ensembles, and a variant of the latter that also includes an estimation of state variable uncertainty. This comparison takes place for the Montmorency River, a small flood-prone watershed in southern central Quebec, Canada. The assessment of forecasts is performed for lead times of 1 to 5 days, both in terms of forecasts' quality (relative to the corresponding record of observations) and in terms of economic value, using the new proposed framework based on the CARA utility function. It is found that the economic value of a forecast for a risk-averse decision maker is closely linked to the forecast reliability in predicting the upper tail of the streamflow distribution. Hence, post-processing forecasts to avoid over-forecasting could help improve both the quality and the value of forecasts.

A risk-informed decision framework for setting environmental windows for dredging projects.

PubMed

Suedel, Burton C; Kim, Jongbum; Clarke, Douglas G; Linkov, Igor

2008-09-15

Sediment dredging is necessary to sustain navigation infrastructure in ports and harbor areas. In the United States alone between 250 and 300 million cubic yards of sediment are dredged annually. Dredging activities may cause stress on aquatic biota by locally increasing turbidity and suspended sediment concentrations, physically disturbing habitat by elevated sedimentation rates, interfering in migratory behaviors, and hydraulically entraining bottom dwelling organisms. Environmental windows are a management practice used to alleviate such stresses on resident and transient biota by placing temporal restrictions on the conduct of dredging operations. Adherence to environmental windows can significantly inflate costs for project sponsors and local stakeholders. Since their inception following passage of NEPA in 1969 the process for setting environmental windows has not followed structured procedures and represents an example of the difficulty inherent in achieving a balance between biological resource protection and cost-effective construction and maintenance of navigation infrastructure. Recent developments in the fields of risk assessment for non-chemical stressors as well as experience in implementing structured risk-informed decision-making tools for sediment and natural resource management are summarized in this paper in relation to setting environmental windows. Combining risk assessment and multi-criteria decision analysis allows development of a framework for an objective process consistent with recommendations by the National Academy of Sciences for setting environmental windows. A hypothetical application of the framework for protection of Pacific herring (Clupea pallasii) in San Francisco Bay is discussed.

"And I think that we can fix it": mental models used in high-risk surgical decision making.

PubMed

Kruser, Jacqueline M; Pecanac, Kristen E; Brasel, Karen J; Cooper, Zara; Steffens, Nicole M; McKneally, Martin F; Schwarze, Margaret L

2015-04-01

To examine how surgeons use the "fix-it" model to communicate with patients before high-risk operations. The "fix-it" model characterizes disease as an isolated abnormality that can be restored to normal form and function through medical intervention. This mental model is familiar to patients and physicians, but it is ineffective for chronic conditions and treatments that cannot achieve normalcy. Overuse may lead to permissive decision making favoring intervention. Efforts to improve surgical decision making will need to consider how mental models function in clinical practice, including "fix-it." We observed surgeons who routinely perform high-risk surgery during preoperative discussions with patients. We used qualitative content analysis to explore the use of "fix-it" in 48 audio-recorded conversations. Surgeons used the "fix-it" model for 2 separate purposes during preoperative conversations: (1) as an explanatory tool to facilitate patient understanding of disease and surgery, and (2) as a deliberation framework to assist in decision making. Although surgeons commonly used "fix-it" as an explanatory model, surgeons explicitly discussed limitations of the "fix-it" model as an independent rationale for operating as they deliberated about the value of surgery. Although the use of "fix-it" is familiar for explaining medical information to patients, surgeons recognize that the model can be problematic for determining the value of an operation. Whether patients can transition between understanding how their disease is fixed with surgery to a subsequent deliberation about whether they should have surgery is unclear and may have broader implications for surgical decision making.

77 FR 44613 - Notice of Availability of the External Review Draft of Framework for Human Health Risk Assessment...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-30

... External Review Draft of Framework for Human Health Risk Assessment To Inform Decision Making AGENCY: U.S... external review draft of ``A Framework for Human Health Risk Assessment to Inform Decision Making.'' This... a framework for conducting human health risk assessments that are responsive to the needs of...

Decision Support Framework (DSF) For Evaluating Planned Land And Resource Use Decisions: Hypothetical Application Of The DSF To Address Nutrient Loads In The Florida Keys

EPA Science Inventory

The mission of ORD's Ecosystme Services Research Program (ESRP) is to provide the information and methods needed by decision-makers to assess the benefits of ecosystem goods and services to human well-being for inclusion in management alternatives. The Decision Support Framework...

A Decision Support Framework For Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

EPA Science Inventory

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environ...

Decision Support Framework (DSF) Team Research Implementation Plan

EPA Science Inventory

The mission of ORD's Ecosystem Services Research Program (ESRP) is to provide the information and methods needed by decision-makers to assess the benefits of ecosystem goods and services to human well-being for inclusion in management alternatives. The Decision Support Framework...

Decision Support Framework (DSF) (Formerly Decision Support Platform)

EPA Science Inventory

The Science Advisory Board (SAB) provided several comments on the draft Ecosystem Services Research Program's (ESRP's) Multi-Year Plan (MYP). This presentation provides a response to comments related to the decision support framework (DSF) part of Long-Term Goal 1. The comments...

A framework for modelling the complexities of food and water security under globalisation

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; Sivapalan, Murugesu; Stehfest, Elke; van Vuuren, Detlef P.; Wassen, Martin J.; Bierkens, Marc F. P.; Dekker, Stefan C.

2018-01-01

We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.

Decision support models for solid waste management: Review and game-theoretic approaches

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

Karmperis, Athanasios C., E-mail: athkarmp@mail.ntua.gr; Army Corps of Engineers, Hellenic Army General Staff, Ministry of Defence; Aravossis, Konstantinos

Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decisionmore » support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.« less

An expanded framework to define and measure shared decision-making in dialogue: A 'top-down' and 'bottom-up' approach.

PubMed

Callon, Wynne; Beach, Mary Catherine; Links, Anne R; Wasserman, Carly; Boss, Emily F

2018-03-11

We aimed to develop a comprehensive, descriptive framework to measure shared decision making (SDM) in clinical encounters. We combined a top-down (theoretical) approach with a bottom-up approach based on audio-recorded dialogue to identify all communication processes related to decision making. We coded 55 pediatric otolaryngology visits using the framework and report interrater reliability. We identified 14 clinician behaviors and 5 patient behaviors that have not been previously described, and developed a new SDM framework that is descriptive (what does happen) rather than normative (what should happen). Through the bottom-up approach we identified three broad domains not present in other SDM frameworks: socioemotional support, understandability of clinician dialogue, and recommendation-giving. We also specify the ways in which decision-making roles are assumed implicitly rather than discussed explicitly. Interrater reliability was >75% for 92% of the coded behaviors. This SDM framework allows for a more expansive understanding and analysis of how decision making takes place in clinical encounters, including new domains and behaviors not present in existing measures. We hope that this new framework will bring attention to a broader conception of SDM and allow researchers to further explore the new domains and behaviors identified. Copyright © 2018. Published by Elsevier B.V.

Barriers and facilitators to orthopaedic surgeons’ uptake of decision aids for total knee arthroplasty: a qualitative study

PubMed Central

Nelson, Elizabeth; Scott, Anthony; French, Simon; Choong, Peter; Dowsey, Michelle

2017-01-01

Objectives The demand for total knee arthroplasty (TKA) is increasing. Differentiating who will derive a clinically meaningful improvement from TKA from others is a key challenge for orthopaedic surgeons. Decision aids can help surgeons select appropriate candidates for surgery, but their uptake has been low. The aim of this study was to explore the barriers and facilitators to decision aid uptake among orthopaedic surgeons. Design A qualitative study involving face-to-face interviews. Questions were constructed on the Theoretical Domains Framework to systematically explore barriers and facilitators. Setting One tertiary hospital in Australia. Participants Twenty orthopaedic surgeons performing TKA. Outcome measures Beliefs underlying similar interview responses were identified and grouped together as themes describing relevant barriers and facilitators to uptake of decision aids. Results While prioritising their clinical acumen, surgeons believed a decision aid could enhance communication and patient informed consent. Barriers identified included the perception that one’s patient outcomes were already optimal; a perceived lack of non-operative alternatives for the management of end-stage osteoarthritis, concerns about mandatory cut-offs for patient-centred care and concerns about the medicolegal implications of using a decision aid. Conclusions Multifaceted implementation interventions are required to ensure that orthopaedic surgeons are ready, willing and able to use a TKA decision aid. Audit/feedback to address current decision-making biases such as overconfidence may enhance readiness to uptake. Policy changes and/or incentives may enhance willingness to uptake. Finally, the design/implementation of effective non-operative treatments may enhance ability to uptake by ensuring that surgeons have the resources they need to carry out decisions. PMID:29133333

A Framework for a Decision Support System in a Hierarchical Extended Enterprise Decision Context

NASA Astrophysics Data System (ADS)

Boza, Andrés; Ortiz, Angel; Vicens, Eduardo; Poler, Raul

Decision Support System (DSS) tools provide useful information to decision makers. In an Extended Enterprise, a new goal, changes in the current objectives or small changes in the extended enterprise configuration produce a necessary adjustment in its decision system. A DSS in this context must be flexible and agile to make suitable an easy and quickly adaptation to this new context. This paper proposes to extend the Hierarchical Production Planning (HPP) structure to an Extended Enterprise decision making context. In this way, a framework for DSS in Extended Enterprise context is defined using components of HPP. Interoperability details have been reviewed to identify the impact in this framework. The proposed framework allows overcoming some interoperability barriers, identifying and organizing components for a DSS in Extended Enterprise context, and working in the definition of an architecture to be used in the design process of a flexible DSS in Extended Enterprise context which can reuse components for futures Extended Enterprise configurations.

Theory and implementation of summarization: Improving sensor interpretation for spacecraft operations

NASA Astrophysics Data System (ADS)

Swartwout, Michael Alden

New paradigms in space missions require radical changes in spacecraft operations. In the past, operations were insulated from competitive pressures of cost, quality and time by system infrastructures, technological limitations and historical precedent. However, modern demands now require that operations meet competitive performance goals. One target for improvement is the telemetry downlink, where significant resources are invested to acquire thousands of measurements for human interpretation. This cost-intensive method is used because conventional operations are not based on formal methodologies but on experiential reasoning and incrementally adapted procedures. Therefore, to improve the telemetry downlink it is first necessary to invent a rational framework for discussing operations. This research explores operations as a feedback control problem, develops the conceptual basis for the use of spacecraft telemetry, and presents a method to improve performance. The method is called summarization, a process to make vehicle data more useful to operators. Summarization enables rational trades for telemetry downlink by defining and quantitatively ranking these elements: all operational decisions, the knowledge needed to inform each decision, and all possible sensor mappings to acquire that knowledge. Summarization methods were implemented for the Sapphire microsatellite; conceptual health management and system models were developed and a degree-of-observability metric was defined. An automated tool was created to generate summarization methods from these models. Methods generated using a Sapphire model were compared against the conventional operations plan. Summarization was shown to identify the key decisions and isolate the most appropriate sensors. Secondly, a form of summarization called beacon monitoring was experimentally verified. Beacon monitoring automates the anomaly detection and notification tasks and migrates these responsibilities to the space segment. A set of experiments using Sapphire demonstrated significant cost and time savings compared to conventional operations. Summarization is based on rational concepts for defining and understanding operations. Therefore, it enables additional trade studies that were formerly not possible and also can form the basis for future detailed research into spacecraft operations.

Idaho National Laboratory Test Area North: Application of Endpoints to Guide Adaptive Remediation at a Complex Site: INL Test Area North: Application of Endpoints

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

Lee, M. Hope; Truex, Mike; Freshley, Mark

Complex sites are defined as those with difficult subsurface access, deep and/or thick zones of contamination, large areal extent, subsurface heterogeneities that limit the effectiveness of remediation, or where long-term remedies are needed to address contamination (e.g., because of long-term sources or large extent). The Test Area North at the Idaho National Laboratory, developed for nuclear fuel operations and heavy metal manufacturing, is used as a case study. Liquid wastes and sludge from experimental facilities were disposed in an injection well, which contaminated the subsurface aquifer located deep within fractured basalt. The wastes included organic, inorganic, and low-level radioactive constituents,more » with the focus of this case study on trichloroethylene. The site is used as an example of a systems-based framework that provides a structured approach to regulatory processes established for remediation under existing regulations. The framework is intended to facilitate remedy decisions and implementation at complex sites where restoration may be uncertain, require long timeframes, or involve use of adaptive management approaches. The framework facilitates site, regulator, and stakeholder interactions during the remedial planning and implementation process by using a conceptual model description as a technical foundation for decisions, identifying endpoints, which are interim remediation targets or intermediate decision points on the path to an ultimate end, and maintaining protectiveness during the remediation process. At the Test Area North, using a structured approach to implementing concepts in the endpoint framework, a three-component remedy is largely functioning as intended and is projected to meet remedial action objectives by 2095 as required. The remedy approach is being adjusted as new data become available. The framework provides a structured process for evaluating and adjusting the remediation approach, allowing site owners, regulators, and stakeholders to manage contamination at complex sites where adaptive remedies are needed.« less

A decision framework for coordinating bioterrorism planning: lessons from the BioNet program.

PubMed

Manley, Dawn K; Bravata, Dena M

2009-01-01

Effective disaster preparedness requires coordination across multiple organizations. This article describes a detailed framework developed through the BioNet program to facilitate coordination of bioterrorism preparedness planning among military and civilian decision makers. The authors and colleagues conducted a series of semistructured interviews with civilian and military decision makers from public health, emergency management, hazardous material response, law enforcement, and military health in the San Diego area. Decision makers used a software tool that simulated a hypothetical anthrax attack, which allowed them to assess the effects of a variety of response actions (eg, issuing warnings to the public, establishing prophylaxis distribution centers) on performance metrics. From these interviews, the authors characterized the information sources, technologies, plans, and communication channels that would be used for bioterrorism planning and responses. The authors used influence diagram notation to describe the key bioterrorism response decisions, the probabilistic factors affecting these decisions, and the response outcomes. The authors present an overview of the response framework and provide a detailed assessment of two key phases of the decision-making process: (1) pre-event planning and investment and (2) incident characterization and initial responsive measures. The framework enables planners to articulate current conditions; identify gaps in existing policies, technologies, information resources, and relationships with other response organizations; and explore the implications of potential system enhancements. Use of this framework could help decision makers execute a locally coordinated response by identifying the critical cues of a potential bioterrorism event, the information needed to make effective response decisions, and the potential effects of various decision alternatives.

A multimodal 3D framework for fire characteristics estimation

NASA Astrophysics Data System (ADS)

Toulouse, T.; Rossi, L.; Akhloufi, M. A.; Pieri, A.; Maldague, X.

2018-02-01

In the last decade we have witnessed an increasing interest in using computer vision and image processing in forest fire research. Image processing techniques have been successfully used in different fire analysis areas such as early detection, monitoring, modeling and fire front characteristics estimation. While the majority of the work deals with the use of 2D visible spectrum images, recent work has introduced the use of 3D vision in this field. This work proposes a new multimodal vision framework permitting the extraction of the three-dimensional geometrical characteristics of fires captured by multiple 3D vision systems. The 3D system is a multispectral stereo system operating in both the visible and near-infrared (NIR) spectral bands. The framework supports the use of multiple stereo pairs positioned so as to capture complementary views of the fire front during its propagation. Multimodal registration is conducted using the captured views in order to build a complete 3D model of the fire front. The registration process is achieved using multisensory fusion based on visual data (2D and NIR images), GPS positions and IMU inertial data. Experiments were conducted outdoors in order to show the performance of the proposed framework. The obtained results are promising and show the potential of using the proposed framework in operational scenarios for wildland fire research and as a decision management system in fighting.

Valuation of Electric Power System Services and Technologies

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

Kintner-Meyer, Michael C. W.; Homer, Juliet S.; Balducci, Patrick J.

Accurate valuation of existing and new technologies and grid services has been recognized to be important to stimulate investment in grid modernization. Clear, transparent, and accepted methods for estimating the total value (i.e., total benefits minus cost) of grid technologies and services are necessary for decision makers to make informed decisions. This applies to home owners interested in distributed energy technologies, as well as to service providers offering new demand response services, and utility executives evaluating best investment strategies to meet their service obligation. However, current valuation methods lack consistency, methodological rigor, and often the capabilities to identify and quantifymore » multiple benefits of grid assets or new and innovative services. Distributed grid assets often have multiple benefits that are difficult to quantify because of the locational context in which they operate. The value is temporally, operationally, and spatially specific. It varies widely by distribution systems, transmission network topology, and the composition of the generation mix. The Electric Power Research Institute (EPRI) recently established a benefit-cost framework that proposes a process for estimating multiple benefits of distributed energy resources (DERs) and the associated cost. This document proposes an extension of this endeavor that offers a generalizable framework for valuation that quantifies the broad set of values for a wide range of technologies (including energy efficiency options, distributed resources, transmission, and generation) as well as policy options that affect all aspects of the entire generation and delivery system of the electricity infrastructure. The extension includes a comprehensive valuation framework of monetizable and non-monetizable benefits of new technologies and services beyond the traditional reliability objectives. The benefits are characterized into the following categories: sustainability, affordability, and security, flexibility, and resilience. This document defines the elements of a generic valuation framework and process as well as system properties and metrics by which value streams can be derived. The valuation process can be applied to determine the value on the margin of incremental system changes. This process is typically performed when estimating the value of a particular project (e.g., value of a merchant generator, or a distributed photovoltaic (PV) rooftop installation). Alternatively, the framework can be used when a widespread change in the grid operation, generation mix, or transmission topology is to be valued. In this case a comprehensive system analysis is required.« less

Ethical frameworks for surrogates’ end-of-life planning experiences: A qualitative systematic review

PubMed Central

Kim, Hyejin; Deatrick, Janet A; Ulrich, Connie M

2016-01-01

Despite the growing body of knowledge about surrogate decision making, we know very little about the use of ethical frameworks including ethical theories, principles, and concepts to understand surrogates’ day-to-day experiences in end-of-life care planning for incapacitated adults. This systematic review of 30 qualitative research papers was conducted to identify the types of ethical frameworks used to address surrogates’ experiences in end-of-life care planning for incapacitated adults as well as the most common themes or patterns found in surrogate decision making research.. Seven papers explicitly identified ethical theories, principles, or concepts for their studies, such as autonomy, substituted judgment, and best interests. Themes identified about surrogate decision making included: responsibilities and goals, factors affecting surrogates’ decision making, and outcomes for surrogates. In fact, an overarching theme of “wanting to do the right thing” for incapacitated adults and/or themselves was prominent. Understanding the complexity of surrogates’ experiences of end-of-life care planning is beyond the scope of conventional ethical frameworks. Ethical frameworks that address individuality and contextual variations related to decision making may more appropriately guide surrogate decision making research that explores surrogates’ end-of-life care planning experiences. PMID:27005954

The Intelligent Technologies of Electronic Information System

NASA Astrophysics Data System (ADS)

Li, Xianyu

2017-08-01

Based upon the synopsis of system intelligence and information services, this paper puts forward the attributes and the logic structure of information service, sets forth intelligent technology framework of electronic information system, and presents a series of measures, such as optimizing business information flow, advancing data decision capability, improving information fusion precision, strengthening deep learning application and enhancing prognostic and health management, and demonstrates system operation effectiveness. This will benefit the enhancement of system intelligence.

Automated Planning and Scheduling for Space Mission Operations

NASA Technical Reports Server (NTRS)

Chien, Steve; Jonsson, Ari; Knight, Russell

2005-01-01

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.

Application of a Resilience Framework to Military Installations: A Methodology for Energy Resilience Business Case Decisions

DTIC Science & Technology

2016-09-01

Some technologies that were not included in the analysis (due to site-level evaluations), but could be added in the future, include: wind turbines ...number of entities involved in the procurement, operation, maintenance , testing, and fueling of the generators, detailed inventory and cost data is...difficult to obtain. The DPW is often understaffed, leading to uneven testing and maintenance of the equipment despite their best efforts. The

Application of a Resilience Framework to Military Installations: A Methodology for Energy Resilience Business Case Decisions

DTIC Science & Technology

2016-10-04

analysis (due to site-level evaluations), but could be added in the future, include: wind turbines (the installations we visited were not interested due...procurement, operation, maintenance , testing, and fueling of the generators, detailed inventory and cost data is difficult to obtain. The DPW is often...understaffed, leading to uneven testing and maintenance of the equipment despite their best efforts. The reliability of these generators is typically

FRAMEWORK FOR RESPONSIBLE DECISION-MAKING (FRED): A TOOL FOR ENVIRONMENTALLY PREFERABLE PRODUCTS

EPA Science Inventory

In support of the Environmentally Preferable Purchasing Program of the USEPA, a decision-making tool based on life cycle assessment has been developed. This tool, the Framework for Responsible Environmental Decision-making or FRED, streamlines LCA by choosing a minimum list of im...

FRAMEWORK FOR ENVIRONMENTAL DECISION-MAKING, FRED: A TOOL FOR ENVIRONMENTALLY-PREFERABLE PURCHASING

EPA Science Inventory

In support of the Environmentally Preferable Purchasing Program of the US EPA, the Systems Analysis Branch has developed a decision-making tool based on life cycle assessment. This tool, the Framework for Responsible Environmental Decision-making or FRED streamlines LCA by choosi...

DEVELOPMENT OF A DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN-WATERSHEDS

EPA Science Inventory

This paper will present an on-going development of an integrated decision support framework (IDSF) for cost-effective placement of best management practices (BMPs) for managing wet weather flows (WWF) in urban watersheds. This decision tool will facilitate the selection and plac...

AN INTEGRATED DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN-WATERSHEDS

EPA Science Inventory

This paper will present an on-going development of an integrated decision support framework (IDSF) for cost-effective placement of best management practices (BMPs) for managing wet weather flows (WWF) in urban watersheds. This decision tool will facilitate the selection and plac...

[GRADE Evidence to Decision (EtD) frameworks: a systematic and transparent approach to making well informed healthcare choices. 2: Clinical practice guidelines.

PubMed

Morgano, Gian Paolo; Parmelli, Elena; Amato, Laura; Iannone, Primiano; Marchetti, Marco; Moja, Lorenzo; Davoli, Marina; Schünemann, Holger

2018-05-01

In the first article in this series we described the GRADE (Grading of Recommendations Assessment, Development and Evaluation) Evidence to Decision (EtD) frameworks and their rationale for different types of decisions. In this second article, we describe the use of EtD frameworks for clinical recommendations and how it can help clinicians and patients who use those recommendations. EtD frameworks for clinical practice recommendations provide a structured and transparent approach for guideline panels. The framework helps ensure consideration of key criteria that determine whether an intervention should be recommended and that judgments are informed by the best available evidence. Frameworks are also a way for panels to make guideline users aware of the rationale (justification) for their recommendations.

Enhancing clinical decision making: development of a contiguous definition and conceptual framework.

PubMed

Tiffen, Jennifer; Corbridge, Susan J; Slimmer, Lynda

2014-01-01

Clinical decision making is a term frequently used to describe the fundamental role of the nurse practitioner; however, other terms have been used interchangeably. The purpose of this article is to begin the process of developing a definition and framework of clinical decision making. The developed definition was "Clinical decision making is a contextual, continuous, and evolving process, where data are gathered, interpreted, and evaluated in order to select an evidence-based choice of action." A contiguous framework for clinical decision making specific for nurse practitioners is also proposed. Having a clear and unique understanding of clinical decision making will allow for consistent use of the term, which is relevant given the changing educational requirements for nurse practitioners and broadening scope of practice. Copyright © 2014 Elsevier Inc. All rights reserved.

Framework for a space shuttle main engine health monitoring system

NASA Technical Reports Server (NTRS)

Hawman, Michael W.; Galinaitis, William S.; Tulpule, Sharayu; Mattedi, Anita K.; Kamenetz, Jeffrey

1990-01-01

A framework developed for a health management system (HMS) which is directed at improving the safety of operation of the Space Shuttle Main Engine (SSME) is summarized. An emphasis was placed on near term technology through requirements to use existing SSME instrumentation and to demonstrate the HMS during SSME ground tests within five years. The HMS framework was developed through an analysis of SSME failure modes, fault detection algorithms, sensor technologies, and hardware architectures. A key feature of the HMS framework design is that a clear path from the ground test system to a flight HMS was maintained. Fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and demonstrated on data from SSME ground test failures. The fault detection algorithms exhibited 100 percent detection of faults, had an extremely low false alarm rate, and were robust to sensor loss. These algorithms were incorporated into a hierarchical decision making strategy for overall assessment of SSME health. A preliminary design for a hardware architecture capable of supporting real time operation of the HMS functions was developed. Utilizing modular, commercial off-the-shelf components produced a reliable low cost design with the flexibility to incorporate advances in algorithm and sensor technology as they become available.

What makes health impact assessments successful? Factors contributing to effectiveness in Australia and New Zealand.

PubMed

Haigh, Fiona; Harris, Elizabeth; Harris-Roxas, Ben; Baum, Fran; Dannenberg, Andrew L; Harris, Mark F; Keleher, Helen; Kemp, Lynn; Morgan, Richard; Ng Chok, Harrison; Spickett, Jeff

2015-10-03

While many guidelines explain how to conduct Health Impact Assessments (HIAs), less is known about the factors that determine the extent to which HIAs affect health considerations in the decision making process. We investigated which factors are associated with increased or reduced effectiveness of HIAs in changing decisions and in the implementation of policies, programs or projects. This study builds on and tests the Harris and Harris-Roxas' conceptual framework for evaluating HIA effectiveness, which emphasises context, process and output as key domains. We reviewed 55 HIA reports in Australia and New Zealand from 2005 to 2009 and conducted surveys and interviews for 48 of these HIAs. Eleven detailed case studies were undertaken using document review and stakeholder interviews. Case study participants were selected through purposeful and snowball sampling. The data were analysed by thematic content analysis. Findings were synthesised and mapped against the conceptual framework. A stakeholder forum was utilised to test face validity and practical adequacy of the findings. We found that some features of HIA are essential, such as the stepwise but flexible process, and evidence based approach. Non-essential features that can enhance the impact of HIAs include capacity and experience; 'right person right level'; involvement of decision-makers and communities; and relationships and partnerships. There are contextual factors outside of HIA such as fit with planning and decision making context, broader global context and unanticipated events, and shared values and goals that may influence a HIA. Crosscutting factors include proactive positioning, and time and timeliness. These all operate within complex open systems, involving multiple decision-makers, levels of decision-making, and points of influence. The Harris and Harris-Roxas framework was generally supported. We have confirmed previously identified factors influencing effectiveness of HIA and identified new factors such as proactive positioning. Our findings challenge some presumptions about 'right' timing for HIA and the rationality and linearity of decision-making processes. The influence of right timing on decision making needs to be seen within the context of other factors such as proactive positioning. This research can help HIA practitioners and researchers understand and identify what can be enhanced within the HIA process. Practitioners can adapt the flexible HIA process to accommodate the external contextual factors identified in this report.

Co-Operative Advances in Behavioral Health and Performance Research and Operations

NASA Technical Reports Server (NTRS)

VanderArk, Stephen T.; Leveton, Lauren B.

2011-01-01

In organizations that engage in both operations and applied research, with operational needs guiding research questions and research informing improved operations, the ideal goal is a synergy of ideas and information. In reality, this ideal synergy is often lacking. Real-time operational needs driving day-to-day decisions, lack of communication, lag time in getting research advances plugged into operations can cause both areas to suffer from this gap between operations and research. At Johnson Space Center, the Behavior Health and Performance group (BHP) strives to bridge this gap by following a Human Research Program framework: Expectations of future operational needs identify the knowledge gaps; the gaps in turn guide research leading to a product that is transitioned into operations. Thus, the direction those of us in research take is in direct response to current and future needs of operations. Likewise, those of us in operations actively seek knowledge that is supported by evidence-based research. We make an ongoing effort to communicate across the research and operations gap by working closely with each other and making a conscious effort to keep each other informed. The objective of the proposed panel discussion is to demonstrate through the following presentations the results of a successful collaboration between research and operations and to provide ASMA members with more practical knowledge and strategies for building these bridges to serve our field of practice well. The panel will consist of six presenters from BHP operations, internal BHP research, and external research instigated by BHP who together represent the entire BHP Research Transition to Operations Framework

Bayesian Decision Theoretical Framework for Clustering

ERIC Educational Resources Information Center

Chen, Mo

2011-01-01

In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…

Educational Goods and Values: A Framework for Decision Makers

ERIC Educational Resources Information Center

Brighouse, Harry; Ladd, Helen F.; Loeb, Susanna; Swift, Adam

2016-01-01

This article articulates a framework suitable for use when making decisions about education policy. Decision makers should establish what the feasible options are and evaluate them in terms of their contribution to the development, and distribution, of educational goods in children, balanced against the negative effect of policies on important…

An Ethical Decision-Making Framework for Community College Administrators

ERIC Educational Resources Information Center

Oliver, Diane E.; Hioco, Barbara

2012-01-01

The purpose of this article is to describe a decision-making framework developed for use by community college administrators and higher education faculty members who teach graduate courses in community college administration or leadership. The rationale for developing a decision-making approach that integrates ethics and critical thinking was…

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.

Multidimensional Simulation Applied to Water Resources Management

NASA Astrophysics Data System (ADS)

Camara, A. S.; Ferreira, F. C.; Loucks, D. P.; Seixas, M. J.

1990-09-01

A framework for an integrated decision aiding simulation (IDEAS) methodology using numerical, linguistic, and pictorial entities and operations is introduced. IDEAS relies upon traditional numerical formulations, logical rules to handle linguistic entities with linguistic values, and a set of pictorial operations. Pictorial entities are defined by their shape, size, color, and position. Pictorial operators include reproduction (copy of a pictorial entity), mutation (expansion, rotation, translation, change in color), fertile encounters (intersection, reunion), and sterile encounters (absorption). Interaction between numerical, linguistic, and pictorial entities is handled through logical rules or a simplified vector calculus operation. This approach is shown to be applicable to various environmental and water resources management analyses using a model to assess the impacts of an oil spill. Future developments, including IDEAS implementation on parallel processing machines, are also discussed.

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery.

PubMed

Tian, Shu; Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

2015-01-01

The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness.

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery

PubMed Central

Yin, Xu-Cheng; Wang, Zhi-Bin; Zhou, Fang; Hao, Hong-Wei

2015-01-01

The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness. PMID:26693249

An Integrated Ensemble-Based Operational Framework to Predict Urban Flooding: A Case Study of Hurricane Sandy in the Passaic and Hackensack River Basins

NASA Astrophysics Data System (ADS)

Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.

2016-12-01

Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus improving the assessment of risks as when compared to a deterministic forecast. The work offers perspectives for short-term flood forecasts, flood mitigation strategies and best management practices for climate change scenarios.

Real-time reservoir operation considering non-stationary inflow prediction

NASA Astrophysics Data System (ADS)

Zhao, J.; Xu, W.; Cai, X.; Wang, Z.

2011-12-01

Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.

A stochastic discrete optimization model for designing container terminal facilities

NASA Astrophysics Data System (ADS)

Zukhruf, Febri; Frazila, Russ Bona; Burhani, Jzolanda Tsavalista

2017-11-01

As uncertainty essentially affect the total transportation cost, it remains important in the container terminal that incorporates several modes and transshipments process. This paper then presents a stochastic discrete optimization model for designing the container terminal, which involves the decision of facilities improvement action. The container terminal operation model is constructed by accounting the variation of demand and facilities performance. In addition, for illustrating the conflicting issue that practically raises in the terminal operation, the model also takes into account the possible increment delay of facilities due to the increasing number of equipment, especially the container truck. Those variations expectantly reflect the uncertainty issue in the container terminal operation. A Monte Carlo simulation is invoked to propagate the variations by following the observed distribution. The problem is constructed within the framework of the combinatorial optimization problem for investigating the optimal decision of facilities improvement. A new variant of glow-worm swarm optimization (GSO) is thus proposed for solving the optimization, which is rarely explored in the transportation field. The model applicability is tested by considering the actual characteristics of the container terminal.

Harmonised framework for ecological risk assessment of sediments from ports and estuarine zones of North and South Atlantic.

PubMed

Choueri, R B; Cesar, A; Abessa, D M S; Torres, R J; Riba, I; Pereira, C D S; Nascimento, M R L; Morais, R D; Mozeto, A A; DelValls, T A

2010-04-01

This paper presents a harmonised framework of sediment quality assessment and dredging material characterisation for estuaries and port zones of North and South Atlantic. This framework, based on the weight-of-evidence approach, provides a structure and a process for conducting sediment/dredging material assessment that leads to a decision. The main structure consists of "step 1" (examination of available data); "step 2" (chemical characterisation and toxicity assessment); "decision 1" (any chemical level higher than reference values? are sediments toxic?); "step 3" (assessment of benthic community structure); "step 4" (integration of the results); "decision 2" (are sediments toxic or benthic community impaired?); "step 5" (construction of the decision matrix) and "decision 3" (is there environmental risk?). The sequence of assessments may be interrupted when the information obtained is judged to be sufficient for a correct characterisation of the risk posed by the sediments/dredging material. This framework brought novel features compared to other sediment/dredging material risk assessment frameworks: data integration through multivariate analysis allows the identification of which samples are toxic and/or related to impaired benthic communities; it also discriminates the chemicals responsible for negative biological effects; and the framework dispenses the use of a reference area. We demonstrated the successful application of this framework in different port and estuarine zones of the North (Gulf of Cádiz) and South Atlantic (Santos and Paranaguá Estuarine Systems).

Lessons learned from Applications of a Decision Tree for Confronting Climate Change Uncertainty - the Short Term and the Long Term

NASA Astrophysics Data System (ADS)

Ray, P. A.; Wi, S.; Bonzanigo, L.; Taner, M. U.; Rodriguez, D.; Garcia, L.; Brown, C.

2016-12-01

The Decision Tree for Confronting Climate Change Uncertainty is a hierarchical, staged framework for accomplishing climate change risk management in water resources system investments. Since its development for the World Bank Water Group two years ago, the framework has been applied to pilot demonstration projects in Nepal (hydropower generation), Mexico (water supply), Kenya (multipurpose reservoir operation), and Indonesia (flood risks to dam infrastructure). An important finding of the Decision Tree demonstration projects has been the need to present the risks/opportunities of climate change to stakeholders and investors in proportion to risks/opportunities and hazards of other kinds. This presentation will provide an overview of tools and techniques used to quantify risks/opportunities to each of the project types listed above, with special attention to those found most useful for exploration of the risk space. Careful exploration of the risk/opportunity space shows that some interventions would be better taken now, whereas risks/opportunities of other types would be better instituted incrementally in order to maintain reversibility and flexibility. A number of factors contribute to the robustness/flexibility tradeoff: available capital, magnitude and imminence of potential risk/opportunity, modular (or not) character of investment, and risk aversion of the decision maker, among others. Finally, in each case, nuance was required in the translation of Decision Tree findings into actionable policy recommendations. Though the narrative of stakeholder solicitation, engagement, and ultimate partnership is unique to each case, summary lessons are available from the portfolio that can serve as a guideline to the community of climate change risk managers.

Systematic narrative review of decision frameworks to select the appropriate modelling approaches for health economic evaluations.

PubMed

Tsoi, B; O'Reilly, D; Jegathisawaran, J; Tarride, J-E; Blackhouse, G; Goeree, R

2015-06-17

In constructing or appraising a health economic model, an early consideration is whether the modelling approach selected is appropriate for the given decision problem. Frameworks and taxonomies that distinguish between modelling approaches can help make this decision more systematic and this study aims to identify and compare the decision frameworks proposed to date on this topic area. A systematic review was conducted to identify frameworks from peer-reviewed and grey literature sources. The following databases were searched: OVID Medline and EMBASE; Wiley's Cochrane Library and Health Economic Evaluation Database; PubMed; and ProQuest. Eight decision frameworks were identified, each focused on a different set of modelling approaches and employing a different collection of selection criterion. The selection criteria can be categorized as either: (i) structural features (i.e. technical elements that are factual in nature) or (ii) practical considerations (i.e. context-dependent attributes). The most commonly mentioned structural features were population resolution (i.e. aggregate vs. individual) and interactivity (i.e. static vs. dynamic). Furthermore, understanding the needs of the end-users and stakeholders was frequently incorporated as a criterion within these frameworks. There is presently no universally-accepted framework for selecting an economic modelling approach. Rather, each highlights different criteria that may be of importance when determining whether a modelling approach is appropriate. Further discussion is thus necessary as the modelling approach selected will impact the validity of the underlying economic model and have downstream implications on its efficiency, transparency and relevance to decision-makers.

A framework for guiding sustainability assessment and on-farm strategic decision making

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

Coteur, Ine, E-mail: ine.coteur@ilvo.vlaanderen.be; Marchand, Fleur; University of Antwerp, Ecosystem Management Research Group and IMDO, Universiteitsplein 1, 2610 Wilrijk

Responding to future challenges and societal needs, various actions are taken in agriculture to evolve towards more sustainable farming practices. These actions imply strategic choices and suppose adequate sustainability assessments to identify, measure, evaluate and communicate sustainable development. However, literature is scarce on the link between strategic decision making and sustainability assessment. As questions emerge on how, what and when to measure, the objective of this paper is to construct a framework for guiding sustainability assessment and on-farm strategic decision making. Qualitative research on own experiences from the past and a recent project revealed four categories of actual needs farmers,more » advisors and experts have regarding sustainability assessment: context, flexibility, focus on farm and farmer and communication. These stakeholders' needs are then incorporated into a two-dimensional framework that marries the intrinsic complexity of sustainability assessment tools and the time frame of strategic decision making. The framework allows a farm-specific and flexible approach leading to harmonized actions towards sustainable farming. As this framework is mainly a procedural instrument to guide the use of sustainability assessment tools within strategic decision making, it fits to incorporate, even guide, future research on sustainability assessment tools themselves and on their adoption on farms. - Highlights: • How to link sustainability assessment and on-farm strategic decision making is unclear. • Two-dimensional framework incorporating stakeholders' needs regarding sustainability assessment • Linking complexity of sustainability assessment tools and the time frame of strategic decision making • Farm-specific and flexible approach to harmonize action towards sustainable farming.« less

Health care ethics and health law in the Dutch discussion on end-of-life decisions: a historical analysis of the dynamics and development of both disciplines.

PubMed

Kater, Loes; Houtepen, Rob; De Vries, Raymond; Widdershoven, Guy

2003-12-01

Over the past three or four decades, the concept of medical ethics has changed from a limited set of standards to a broad field of debate and research. We define medical ethics as an arena of moral issues in medicine, rather than a specific discipline. This paper examines how the disciplines of health care ethics and health care law have developed and operated within this arena. Our framework highlights the aspects of jurisdiction (Abbott) and the assignment of responsibilities (Gusfield). This theoretical framework prompted us to study definitions and changing responsibilities in order to describe the development and interaction of health care ethics and health law. We have opted for the context of the Dutch debate about end-of-life decisions as a relevant case study. We argue that the specific Dutch definition of euthanasia as 'intentionally taking the life of another person by a physician, upon that person's request' can be seen as the result of the complex jurisdictional process. This illustrates the more general conclusion that the Dutch debate on end-of-life decisions and the development of the two disciplines must be understood in terms of mutual interaction.

ATR evaluation through the synthesis of multiple performance measures

NASA Astrophysics Data System (ADS)

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

2002-07-01

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

The Macro- and Micropolitics of Personnel Evaluation: A Framework.

ERIC Educational Resources Information Center

Bridges, Edwin M.; Groves, Barry R.

1999-01-01

Explicates a conceptual framework for analyzing the politics of personnel evaluation in an educational context. Using several elements of the framework, discusses the politics of teacher evaluation in California in relation to the types of personnel evaluation decisions, the actors, their access to these decisions, sources and levels of power, and…

Conceptual Frameworks for Child Care Decision-Making. White Paper

ERIC Educational Resources Information Center

Chaudry, Ajay; Henly, Julia; Meyers, Marcia

2010-01-01

This working paper is one in a series of projects initiated by the Administration for Children and Families (ACF) to improve knowledge for child care researchers and policy makers about parental child care decision making. In this paper, the authors identify three distinct conceptual frameworks for understanding child care decisions--a rational…

Making a Good Group Decision (Low Risk) in Singapore Under an Environment That Has Time and Cost Constraints

DTIC Science & Technology

2014-09-01

decision-making framework to eliminate bias and promote effective communication. Using a collaborative approach built on systems engineering and...framework to eliminate bias and promote effective communication. Using a collaborative approach built on systems engineering and decision-making...Organization .......................................................................................61 2. Bias

Comparative analysis of nursing and midwifery regulatory and professional bodies' scope of practice and associated decision-making frameworks: a discussion paper.

PubMed

Kennedy, Catriona; O'Reilly, Pauline; Fealy, Gerard; Casey, Mary; Brady, Anne-Marie; McNamara, Martin; Prizeman, Geraldine; Rohde, Daniela; Hegarty, Josephine

2015-08-01

To review, discuss and compare nursing and midwifery regulatory and professional bodies' scope of practice and associated decision-making frameworks. Scope of practice in professional nursing and midwifery is an evolving process which needs to be responsive to clinical, service, societal, demographic and fiscal changes. Codes and frameworks offer a system of rules and principles by which the nursing and midwifery professions are expected to regulate members and demonstrate responsibility to society. Discussion paper. Twelve scope of practice and associated decision-making frameworks (January 2000-March 2014). Two main approaches to the regulation of the scope of practice and associated decision-making frameworks exist internationally. The first approach is policy and regulation driven and behaviour oriented. The second approach is based on notions of autonomous decision-making, professionalism and accountability. The two approaches are not mutually exclusive, but have similar elements with a different emphasis. Both approaches lack explicit recognition of the aesthetic aspects of care and patient choice, which is a fundamental principle of evidence-based practice. Nursing organizations, regulatory authorities and nurses should recognize that scope of practice and the associated responsibility for decision-making provides a very public statement about the status of nursing in a given jurisdiction. © 2015 John Wiley & Sons Ltd.

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.

Fault trees for decision making in systems analysis

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

Lambert, Howard E.

1975-10-09

The application of fault tree analysis (FTA) to system safety and reliability is presented within the framework of system safety analysis. The concepts and techniques involved in manual and automated fault tree construction are described and their differences noted. The theory of mathematical reliability pertinent to FTA is presented with emphasis on engineering applications. An outline of the quantitative reliability techniques of the Reactor Safety Study is given. Concepts of probabilistic importance are presented within the fault tree framework and applied to the areas of system design, diagnosis and simulation. The computer code IMPORTANCE ranks basic events and cut setsmore » according to a sensitivity analysis. A useful feature of the IMPORTANCE code is that it can accept relative failure data as input. The output of the IMPORTANCE code can assist an analyst in finding weaknesses in system design and operation, suggest the most optimal course of system upgrade, and determine the optimal location of sensors within a system. A general simulation model of system failure in terms of fault tree logic is described. The model is intended for efficient diagnosis of the causes of system failure in the event of a system breakdown. It can also be used to assist an operator in making decisions under a time constraint regarding the future course of operations. The model is well suited for computer implementation. New results incorporated in the simulation model include an algorithm to generate repair checklists on the basis of fault tree logic and a one-step-ahead optimization procedure that minimizes the expected time to diagnose system failure.« less

Bumps on the road to Magnet designation: achieving organizational excellence.

PubMed

Steinbinder, Amy

2009-01-01

The chief nursing officer is in a unique position to guide his or her organization to excellence by creating a compelling vision; maintaining objectivity regarding the nursing department's accomplishments; holding senior nurse leaders accountable as Magnet champions; demonstrating strategic thinking, business planning development, operational connection, and awareness of clinical aspects of care; and establishing levels of ownership and decision making within the nursing department's operational framework. The clear definition of terms including responsibility, authority, delegation, accountability, and empowerment are necessary and, coupled with specific actions, skills, and measures of success, guide individual and group processes to achieve organizational excellence and ultimately Magnet designation.

A Simulation Based Approach for Contingency Planning for Aircraft Turnaround Operation System Activities in Airline Hubs

NASA Technical Reports Server (NTRS)

Adeleye, Sanya; Chung, Christopher

2006-01-01

Commercial aircraft undergo a significant number of maintenance and logistical activities during the turnaround operation at the departure gate. By analyzing the sequencing of these activities, more effective turnaround contingency plans may be developed for logistical and maintenance disruptions. Turnaround contingency plans are particularly important as any kind of delay in a hub based system may cascade into further delays with subsequent connections. The contingency sequencing of the maintenance and logistical turnaround activities were analyzed using a combined network and computer simulation modeling approach. Experimental analysis of both current and alternative policies provides a framework to aid in more effective tactical decision making.

Kernel-Based Approximate Dynamic Programming Using Bellman Residual Elimination

DTIC Science & Technology

2010-02-01

framework is the ability to utilize stochastic system models, thereby allowing the system to make sound decisions even if there is randomness in the system ...approximate policy when a system model is unavailable. We present theoretical analysis of all BRE algorithms proving convergence to the optimal policy in...policies based on MDPs is that there may be parameters of the system model that are poorly known and/or vary with time as the system operates. System

Joint Space Operations Center (JSpOC) Mission System Increment 2 (JMS Inc 2)

DTIC Science & Technology

2016-03-01

Defense Acquisition Executive DoD - Department of Defense DoDAF - DoD Architecture Framework FD - Full Deployment FDD - Full Deployment Decision FY...date has slipped from September 2016 to December 2016 and FDD has slipped from October 2016 to March 2017 since the last MAIS Annual Report...testing. This added test time, in combination with funding reductions and the US Government furlough and shutdown in FY13, caused a total FDD slip

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.

Visual Decision Support Tool for Supporting Asset ...

EPA Pesticide Factsheets

Abstract:Managing urban water infrastructures faces the challenge of jointly dealing with assets of diverse types, useful life, cost, ages and condition. Service quality and sustainability require sound long-term planning, well aligned with tactical and operational planning and management. In summary, the objective of an integrated approach to infrastructure asset management is to assist utilities answer the following questions:•Who are we at present?•What service do we deliver?•What do we own?•Where do we want to be in the long-term?•How do we get there?The AWARE-P approach (www.aware-p.org) offers a coherent methodological framework and a valuable portfolio of software tools. It is designed to assist water supply and wastewater utility decision-makers in their analyses and planning processes. It is based on a Plan-Do-Check-Act process and is in accordance with the key principles of the International Standards Organization (ISO) 55000 standards on asset management. It is compatible with, and complementary to WERF’s SIMPLE framework. The software assists in strategic, tactical, and operational planning, through a non-intrusive, web-based, collaborative environment where objectives and metrics drive IAM planning. It is aimed at industry professionals and managers, as well as at the consultants and technical experts that support them. It is easy to use and maximizes the value of information from multiple existing data sources, both in da

Assessing the utility of the willingness/prototype model in predicting help-seeking decisions.

PubMed

Hammer, Joseph H; Vogel, David L

2013-01-01

Prior research on professional psychological help-seeking behavior has operated on the assumption that the decision to seek help is based on intentional and reasoned processes. However, research on the dual-process prototype/willingness model (PWM; Gerrard, Gibbons, Houlihan, Stock, & Pomery, 2008) suggests health-related decisions may also involve social reaction processes that influence one's spontaneous willingness (rather than planned intention) to seek help, given conducive circumstances. The present study used structural equation modeling to evaluate the ability of these 2 information-processing pathways (i.e., the reasoned pathway and the social reaction pathway) to predict help-seeking decisions among 182 college students currently experiencing clinical levels of psychological distress. Results indicated that when both pathways were modeled simultaneously, only the social reaction pathway independently accounted for significant variance in help-seeking decisions. These findings argue for the utility of the PWM framework in the context of professional psychological help seeking and hold implications for future counseling psychology research, prevention, and practice. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Pandemic influenza preparedness: an ethical framework to guide decision-making.

PubMed

Thompson, Alison K; Faith, Karen; Gibson, Jennifer L; Upshur, Ross E G

2006-12-04

Planning for the next pandemic influenza outbreak is underway in hospitals across the world. The global SARS experience has taught us that ethical frameworks to guide decision-making may help to reduce collateral damage and increase trust and solidarity within and between health care organisations. Good pandemic planning requires reflection on values because science alone cannot tell us how to prepare for a public health crisis. In this paper, we present an ethical framework for pandemic influenza planning. The ethical framework was developed with expertise from clinical, organisational and public health ethics and validated through a stakeholder engagement process. The ethical framework includes both substantive and procedural elements for ethical pandemic influenza planning. The incorporation of ethics into pandemic planning can be helped by senior hospital administrators sponsoring its use, by having stakeholders vet the framework, and by designing or identifying decision review processes. We discuss the merits and limits of an applied ethical framework for hospital decision-making, as well as the robustness of the framework. The need for reflection on the ethical issues raised by the spectre of a pandemic influenza outbreak is great. Our efforts to address the normative aspects of pandemic planning in hospitals have generated interest from other hospitals and from the governmental sector. The framework will require re-evaluation and refinement and we hope that this paper will generate feedback on how to make it even more robust.

An integrated modeling framework for exploring flow regime and water quality changes with increasing biofuel crop production in the U.S. Corn Belt

NASA Astrophysics Data System (ADS)

Yaeger, Mary A.; Housh, Mashor; Cai, Ximing; Sivapalan, Murugesu

2014-12-01

To better address the dynamic interactions between human and hydrologic systems, we develop an integrated modeling framework that employs a System of Systems optimization model to emulate human development decisions which are then incorporated into a watershed model to estimate the resulting hydrologic impacts. The two models are run interactively to simulate the coevolution of coupled human-nature systems, such that reciprocal feedbacks between hydrologic processes and human decisions (i.e., human impacts on critical low flows and hydrologic impacts on human decisions on land and water use) can be assessed. The framework is applied to a Midwestern U.S. agricultural watershed, in the context of proposed biofuels development. This operation is illustrated by projecting three possible future coevolution trajectories, two of which use dedicated biofuel crops to reduce annual watershed nitrate export while meeting ethanol production targets. Imposition of a primary external driver (biofuel mandate) combined with different secondary drivers (water quality targets) results in highly nonlinear and multiscale responses of both the human and hydrologic systems, including multiple tradeoffs, impacting the future coevolution of the system in complex, heterogeneous ways. The strength of the hydrologic response is sensitive to the magnitude of the secondary driver; 45% nitrate reduction target leads to noticeable impacts at the outlet, while a 30% reduction leads to noticeable impacts that are mainly local. The local responses are conditioned by previous human-hydrologic modifications and their spatial relationship to the new biofuel development, highlighting the importance of past coevolutionary history in predicting future trajectories of change.

A deliberative framework to identify the need for real-life evidence building of new cancer drugs after interim funding decision.

PubMed

Leung, Leanne; de Lemos, Mário L; Kovacic, Laurel

2017-01-01

Background With the rising cost of new oncology treatments, it is no longer sustainable to base initial drug funding decisions primarily on prospective clinical trials as their performance in real-life populations are often difficult to determine. In British Columbia, an approach in evidence building is to retrospectively analyse patient outcomes using observational research on an ad hoc basis. Methods The deliberative framework was constructed in three stages: framework design, framework validation and treatment programme characterization, and key informant interview. Framework design was informed through a literature review and analyses of provincial and national decision-making processes. Treatment programmes funded between 2010 and 2013 were used for framework validation. A selection concordance rate of 80% amongst three reviewers was considered to be a validation of the framework. Key informant interviews were conducted to determine the utility of this deliberative framework. Results A multi-domain deliberative framework with 15 assessment parameters was developed. A selection concordance rate of 84.2% was achieved for content validation of the framework. Nine treatment programmes from five different tumour groups were selected for retrospective outcomes analysis. Five contributory factors to funding uncertainties were identified. Key informants agreed that the framework is a comprehensive tool that targets the key areas involved in the funding decision-making process. Conclusions The oncology-based deliberative framework can be routinely used to assess treatment programmes from the major tumour sites for retrospective outcomes analysis. Key informants indicate this is a value-added tool and will provide insight to the current prospective funding model.

Examination of the consumer decision process for residential energy use

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

Dinan, T.M.

1987-01-01

Numerous studies have examined the factors that influence consumers' energy-using behavior. A comprehensive review of these studies was conducted in which articles from different research disciplines (economics, sociology, psychology, and marketing) were examined. This paper provides a discussion of a subset of these studies, and based on findings of the review, offers recommendations for future research. The literature review revealed a need to develop an integrated framework for examining consumers' energy-using behavior. This integrated framework should simultaneously consider both price and nonprice related factors which underlie energy use decisions. It should also examined the process by which decisions are made,more » as well as the factors that affect the decision outcome. This paper provides a suggested integrated framework for future research and discusses the data required to support this framework. 23 references, 3 figures.« less

Informing the Gestalt: An Ethical Framework for Allocating Scarce Federal Public Health and Medical Resources to States During Disasters

PubMed Central

Knebel, Ann R.; Sharpe, Virginia A.; Danis, Marion; Toomey, Lauren M.; Knickerbocker, Deborah K.

2017-01-01

During catastrophic disasters, government leaders must decide how to efficiently and effectively allocate scarce public health and medical resources. The literature about triage decision making at the individual patient level is substantial, and the National Response Framework provides guidance about the distribution of responsibilities between federal and state governments. However, little has been written about the decision-making process of federal leaders in disaster situations when resources are not sufficient to meet the needs of several states simultaneously. We offer an ethical framework and logic model for decision making in such circumstances. We adapted medical triage and the federalism principle to the decision-making process for allocating scarce federal public health and medical resources. We believe that the logic model provides a values-based framework that can inform the gestalt during the iterative decision process used by federal leaders as they allocate scarce resources to states during catastrophic disasters. PMID:24612854

ENSO detection and use to inform the operation of large scale water systems

NASA Astrophysics Data System (ADS)

Pham, Vuong; Giuliani, Matteo; Castelletti, Andrea

2016-04-01

El Nino Southern Oscillation (ENSO) is a large-scale, coupled ocean-atmosphere phenomenon occurring in the tropical Pacific Ocean, and is considered one of the most significant factors causing hydro-climatic anomalies throughout the world. Water systems operations could benefit from a better understanding of this global phenomenon, which has the potential for enhancing the accuracy and lead-time of long-range streamflow predictions. In turn, these are key to design interannual water transfers in large scale water systems to contrast increasingly frequent extremes induced by changing climate. Despite the ENSO teleconnection is well defined in some locations such as Western USA and Australia, there is no consensus on how it can be detected and used in other river basins, particularly in Europe, Africa, and Asia. In this work, we contribute a general framework relying on Input Variable Selection techniques for detecting ENSO teleconnection and using this information for improving water reservoir operations. Core of our procedure is the Iterative Input variable Selection (IIS) algorithm, which is employed to find the most relevant determinants of streamflow variability for deriving predictive models based on the selected inputs as well as to find the most valuable information for conditioning operating decisions. Our framework is applied to the multipurpose operations of the Hoa Binh reservoir in the Red River basin (Vietnam), taking into account hydropower production, water supply for irrigation, and flood mitigation during the monsoon season. Numerical results show that our framework is able to quantify the relationship between the ENSO fluctuations and the Red River basin hydrology. Moreover, we demonstrate that such ENSO teleconnection represents valuable information for improving the operations of Hoa Binh reservoir.

Master Middle Ware: A Tool to Integrate Water Resources and Fish Population Dynamics Models

NASA Astrophysics Data System (ADS)

Yi, S.; Sandoval Solis, S.; Thompson, L. C.; Kilduff, D. P.

2017-12-01

Linking models that investigate separate components of ecosystem processes has the potential to unify messages regarding management decisions by evaluating potential trade-offs in a cohesive framework. This project aimed to improve the ability of riparian resource managers to forecast future water availability conditions and resultant fish habitat suitability, in order to better inform their management decisions. To accomplish this goal, we developed a middleware tool that is capable of linking and overseeing the operations of two existing models, a water resource planning tool Water Evaluation and Planning (WEAP) model and a habitat-based fish population dynamics model (WEAPhish). First, we designed the Master Middle Ware (MMW) software in Visual Basic for Application® in one Excel® file that provided a familiar framework for both data input and output Second, MMW was used to link and jointly operate WEAP and WEAPhish, using Visual Basic Application (VBA) macros to implement system level calls to run the models. To demonstrate the utility of this approach, hydrological, biological, and middleware model components were developed for the Butte Creek basin. This tributary of the Sacramento River, California is managed for both hydropower and the persistence of a threatened population of spring-run Chinook salmon (Oncorhynchus tschawytscha). While we have demonstrated the use of MMW for a particular watershed and fish population, MMW can be customized for use with different rivers and fish populations, assuming basic data requirements are met. This model integration improves on ad hoc linkages for managing data transfer between software programs by providing a consistent, user-friendly, and familiar interface across different model implementations. Furthermore, the data-viewing capabilities of MMW facilitate the rapid interpretation of model results by hydrologists, fisheries biologists, and resource managers, in order to accelerate learning and management decision making.

ReSTART: A Novel Framework for Resource-Based Triage in Mass-Casualty Events.

PubMed

Mills, Alex F; Argon, Nilay T; Ziya, Serhan; Hiestand, Brian; Winslow, James

2014-01-01

Current guidelines for mass-casualty triage do not explicitly use information about resource availability. Even though this limitation has been widely recognized, how it should be addressed remains largely unexplored. The authors present a novel framework developed using operations research methods to account for resource limitations when determining priorities for transportation of critically injured patients. To illustrate how this framework can be used, they also develop two specific example methods, named ReSTART and Simple-ReSTART, both of which extend the widely adopted triage protocol Simple Triage and Rapid Treatment (START) by using a simple calculation to determine priorities based on the relative scarcity of transportation resources. The framework is supported by three techniques from operations research: mathematical analysis, optimization, and discrete-event simulation. The authors? algorithms were developed using mathematical analysis and optimization and then extensively tested using 9,000 discrete-event simulations on three distributions of patient severity (representing low, random, and high acuity). For each incident, the expected number of survivors was calculated under START, ReSTART, and Simple-ReSTART. A web-based decision support tool was constructed to help providers make prioritization decisions in the aftermath of mass-casualty incidents based on ReSTART. In simulations, ReSTART resulted in significantly lower mortality than START regardless of which severity distribution was used (paired t test, p<.01). Mean decrease in critical mortality, the percentage of immediate and delayed patients who die, was 8.5% for low-acuity distribution (range ?2.2% to 21.1%), 9.3% for random distribution (range ?0.2% to 21.2%), and 9.1% for high-acuity distribution (range ?0.7% to 21.1%). Although the critical mortality improvement due to ReSTART was different for each of the three severity distributions, the variation was less than 1 percentage point, indicating that the ReSTART policy is relatively robust to different severity distributions. Taking resource limitations into account in mass-casualty situations, triage has the potential to increase the expected number of survivors. Further validation is required before field implementation; however, the framework proposed in here can serve as the foundation for future work in this area. 2014.

Nudges, shoves and budges: Behavioural economic policy frameworks.

PubMed

Oliver, Adam

2018-01-01

Behavioural economics-the study of human decision making and how it sometimes deviates systematically from the assumptions of standard economic theory-has attracted a lot of attention in the health policy discourse over recent years. Many appear to believe that behavioural economic findings can be used only to help inform policies that manipulate the choices made by citizens, ie, the so-called nudge policy. However, these findings can be used to inform several different policy frameworks, from seemingly innocuous liberty-preserving changes to the contexts people operate in, to the outlawing of certain corporate behaviours. This article depicts diagrammatically, with the aid of a "behavioural policy cube" and in relation to smoking cessation interventions, the conceptual parameters of several behavioural economic-informed policy frameworks, which could be easily extended to other areas of health, and indeed broader public, policy. Copyright © 2017 John Wiley & Sons, Ltd.

A systematic review and critical assessment of incentive strategies for discovery and development of novel antibiotics

PubMed Central

Renwick, Matthew J; Brogan, David M; Mossialos, Elias

2016-01-01

Despite the growing threat of antimicrobial resistance, pharmaceutical and biotechnology firms are reluctant to develop novel antibiotics because of a host of market failures. This problem is complicated by public health goals that demand antibiotic conservation and equitable patient access. Thus, an innovative incentive strategy is needed to encourage sustainable investment in antibiotics. This systematic review consolidates, classifies and critically assesses a total of 47 proposed incentives. Given the large number of possible strategies, a decision framework is presented to assist with the selection of incentives. This framework focuses on addressing market failures that result in limited investment, public health priorities regarding antibiotic stewardship and patient access, and implementation constraints and operational realities. The flexible nature of this framework allows policy makers to tailor an antibiotic incentive package that suits a country's health system structure and needs. PMID:26464014

Assessing the Value of Post-processed State-of-the-art Long-term Weather Forecast Ensembles within An Integrated Agronomic Modelling Framework

NASA Astrophysics Data System (ADS)

LI, Y.; Castelletti, A.; Giuliani, M.

2014-12-01

Over recent years, long-term climate forecast from global circulation models (GCMs) has been demonstrated to show increasing skills over the climatology, thanks to the advances in the modelling of coupled ocean-atmosphere dynamics. Improved information from long-term forecast is supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping time) and for more effectively coping with the adverse impacts of climate variability. Yet, evaluating how valuable this information can be is not straightforward and farmers' response must be taken into consideration. Indeed, while long-range forecast are traditionally evaluated in terms of accuracy by comparison of hindcast and observed values, in the context of agricultural systems, potentially useful forecast information should alter the stakeholders' expectation, modify their decisions and ultimately have an impact on their annual benefit. Therefore, it is more desirable to assess the value of those long-term forecasts via decision-making models so as to extract direct indication of probable decision outcomes from farmers, i.e. from an end-to-end perspective. In this work, we evaluate the operational value of thirteen state-of-the-art long-range forecast ensembles against climatology forecast and subjective prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of farmers' behavior. Collected ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in order to address the mismatch of the spatio-temporal scale between forecast data from GCMs and distributed crop simulation model. The agronomic model is first simulated using the forecast information (ex-ante), followed by a second run with actual climate (ex-post). Multi-year simulations are performed to account for climate variability and the value of the different climate forecast is evaluated against the perfect foresight scenario based on the expected crop productivity as well as the land-use decisions. Our results show that not all the products generate beneficial effects to farmers and that the forecast errors might be amplified by the farmers decisions.

Reactive system verification case study: Fault-tolerant transputer communication

NASA Technical Reports Server (NTRS)

Crane, D. Francis; Hamory, Philip J.

1993-01-01

A reactive program is one which engages in an ongoing interaction with its environment. A system which is controlled by an embedded reactive program is called a reactive system. Examples of reactive systems are aircraft flight management systems, bank automatic teller machine (ATM) networks, airline reservation systems, and computer operating systems. Reactive systems are often naturally modeled (for logical design purposes) as a composition of autonomous processes which progress concurrently and which communicate to share information and/or to coordinate activities. Formal (i.e., mathematical) frameworks for system verification are tools used to increase the users' confidence that a system design satisfies its specification. A framework for reactive system verification includes formal languages for system modeling and for behavior specification and decision procedures and/or proof-systems for verifying that the system model satisfies the system specifications. Using the Ostroff framework for reactive system verification, an approach to achieving fault-tolerant communication between transputers was shown to be effective. The key components of the design, the decoupler processes, may be viewed as discrete-event-controllers introduced to constrain system behavior such that system specifications are satisfied. The Ostroff framework was also effective. The expressiveness of the modeling language permitted construction of a faithful model of the transputer network. The relevant specifications were readily expressed in the specification language. The set of decision procedures provided was adequate to verify the specifications of interest. The need for improved support for system behavior visualization is emphasized.

Does the Superior Colliculus Control Perceptual Sensitivity or Choice Bias during Attention? Evidence from a Multialternative Decision Framework

PubMed Central

Steinmetz, Nicholas A.; Moore, Tirin; Knudsen, Eric I.

2017-01-01

Distinct networks in the forebrain and the midbrain coordinate to control spatial attention. The critical involvement of the superior colliculus (SC)—the central structure in the midbrain network—in visuospatial attention has been shown by four seminal, published studies in monkeys (Macaca mulatta) performing multialternative tasks. However, due to the lack of a mechanistic framework for interpreting behavioral data in such tasks, the nature of the SC's contribution to attention remains unclear. Here we present and validate a novel decision framework for analyzing behavioral data in multialternative attention tasks. We apply this framework to re-examine the behavioral evidence from these published studies. Our model is a multidimensional extension to signal detection theory that distinguishes between two major classes of attentional mechanisms: those that alter the quality of sensory information or “sensitivity,” and those that alter the selective gating of sensory information or “choice bias.” Model-based simulations and model-based analyses of data from these published studies revealed a converging pattern of results that indicated that choice-bias changes, rather than sensitivity changes, were the primary outcome of SC manipulation. Our results suggest that the SC contributes to attentional performance predominantly by generating a spatial choice bias for stimuli at a selected location, and that this bias operates downstream of forebrain mechanisms that enhance sensitivity. The findings lead to a testable mechanistic framework of how the midbrain and forebrain networks interact to control spatial attention. SIGNIFICANCE STATEMENT Attention involves the selection of the most relevant information for differential sensory processing and decision making. While the mechanisms by which attention alters sensory encoding (sensitivity control) are well studied, the mechanisms by which attention alters decisional weighting of sensory evidence (choice-bias control) are poorly understood. Here, we introduce a model of multialternative decision making that distinguishes bias from sensitivity effects in attention tasks. With our model, we simulate experimental data from four seminal studies that microstimulated or inactivated a key attention-related midbrain structure, the superior colliculus (SC). We demonstrate that the experimental effects of SC manipulation are entirely consistent with the SC controlling attention by changing choice bias, thereby shedding new light on how the brain mediates attention. PMID:28100734

Does the Superior Colliculus Control Perceptual Sensitivity or Choice Bias during Attention? Evidence from a Multialternative Decision Framework.

PubMed

Sridharan, Devarajan; Steinmetz, Nicholas A; Moore, Tirin; Knudsen, Eric I

2017-01-18

Distinct networks in the forebrain and the midbrain coordinate to control spatial attention. The critical involvement of the superior colliculus (SC)-the central structure in the midbrain network-in visuospatial attention has been shown by four seminal, published studies in monkeys (Macaca mulatta) performing multialternative tasks. However, due to the lack of a mechanistic framework for interpreting behavioral data in such tasks, the nature of the SC's contribution to attention remains unclear. Here we present and validate a novel decision framework for analyzing behavioral data in multialternative attention tasks. We apply this framework to re-examine the behavioral evidence from these published studies. Our model is a multidimensional extension to signal detection theory that distinguishes between two major classes of attentional mechanisms: those that alter the quality of sensory information or "sensitivity," and those that alter the selective gating of sensory information or "choice bias." Model-based simulations and model-based analyses of data from these published studies revealed a converging pattern of results that indicated that choice-bias changes, rather than sensitivity changes, were the primary outcome of SC manipulation. Our results suggest that the SC contributes to attentional performance predominantly by generating a spatial choice bias for stimuli at a selected location, and that this bias operates downstream of forebrain mechanisms that enhance sensitivity. The findings lead to a testable mechanistic framework of how the midbrain and forebrain networks interact to control spatial attention. Attention involves the selection of the most relevant information for differential sensory processing and decision making. While the mechanisms by which attention alters sensory encoding (sensitivity control) are well studied, the mechanisms by which attention alters decisional weighting of sensory evidence (choice-bias control) are poorly understood. Here, we introduce a model of multialternative decision making that distinguishes bias from sensitivity effects in attention tasks. With our model, we simulate experimental data from four seminal studies that microstimulated or inactivated a key attention-related midbrain structure, the superior colliculus (SC). We demonstrate that the experimental effects of SC manipulation are entirely consistent with the SC controlling attention by changing choice bias, thereby shedding new light on how the brain mediates attention. Copyright © 2017 the authors 0270-6474/17/370480-32$15.00/0.

Warfighter decision making performance analysis as an investment priority driver

NASA Astrophysics Data System (ADS)

Thornley, David J.; Dean, David F.; Kirk, James C.

2010-04-01

Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.

Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

NASA Astrophysics Data System (ADS)

Vatcha, Rashna; Lee, Seok-Won; Murty, Ajeet; Tolone, William; Wang, Xiaoyu; Dou, Wenwen; Chang, Remco; Ribarsky, William; Liu, Wanqiu; Chen, Shen-en; Hauser, Edd

2009-05-01

Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to make efficient and effective informed decisions. The management involves a multi-faceted operation that requires the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical assets, we present our on-going multi-disciplinary large-scale project that establishes the Integrated Remote Sensing and Visualization (IRSV) system with a focus on supporting bridge structure inspection and management. This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world practitioners from industry, local and federal government agencies. IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding and enforcement of complex inspection process that can bridge the gap between evidence gathering and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation, representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented Architecture (SOA) framework to compose and provide services on-demand. IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme events.

Cognitive niches: an ecological model of strategy selection.

PubMed

Marewski, Julian N; Schooler, Lael J

2011-07-01

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each strategy a cognitive niche, that is, a limited number of situations in which the strategy can be applied, simplifying strategy selection. To illustrate our proposal, we consider selection in the context of 2 theories: the simple heuristics framework and the ACT-R (adaptive control of thought-rational) architecture of cognition. From the heuristics framework, we adopt the thesis that people make decisions by selecting from a repertoire of simple decision strategies that exploit regularities in the environment and draw on cognitive capacities, such as memory and time perception. ACT-R provides a quantitative theory of how these capacities adapt to the environment. In 14 simulations and 10 experiments, we consider the choice between strategies that operate on the accessibility of memories and those that depend on elaborate knowledge about the world. Based on Internet statistics, our model quantitatively predicts people's familiarity with and knowledge of real-world objects, the distributional characteristics of the associated speed of memory retrieval, and the cognitive niches of classic decision strategies, including those of the fluency, recognition, integration, lexicographic, and sequential-sampling heuristics. In doing so, the model specifies when people will be able to apply different strategies and how accurate, fast, and effortless people's decisions will be.

Neuroscience, moral reasoning, and the law.

PubMed

Knabb, Joshua J; Welsh, Robert K; Ziebell, Joseph G; Reimer, Kevin S

2009-01-01

Modern advancements in functional magnetic resonance imaging (fMRI) technology have given neuroscientists the opportunity to more fully appreciate the brain's contribution to human behavior and decision making. Morality and moral reasoning are relative newcomers to the growing literature on decision neuroscience. With recent attention given to the salience of moral factors (e.g. moral emotions, moral reasoning) in the process of decision making, neuroscientists have begun to offer helpful frameworks for understanding the interplay between the brain, morality, and human decision making. These frameworks are relatively unfamiliar to the community of forensic psychologists, despite the fact that they offer an improved understanding of judicial decision making from a biological perspective. This article presents a framework reviewing how event-feature-emotion complexes (EFEC) are relevant to jurors and understanding complex criminal behavior. Future directions regarding converging fields of neuroscience and legal decision making are considered. Copyright 2009 John Wiley & Sons, Ltd.

Making Just Tenure and Promotion Decisions Using the Objective Knowledge Growth Framework

ERIC Educational Resources Information Center

Chitpin, Stephanie

2015-01-01

Purpose: The purpose of this paper is to utilize the Objective Knowledge Growth Framework (OKGF) to promote a better understanding of the evaluating tenure and promotion processes. Design/Methodology/Approach: A scenario is created to illustrate the concept of using OKGF. Findings: The framework aims to support decision makers in identifying the…

Economic assessment of flood forecasts for a risk-averse decision-maker

NASA Astrophysics Data System (ADS)

Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier-Filion, Thomas-Charles

2017-04-01

A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. It has also been suggested in past studies that ensemble forecasts might possess a greater economic value than deterministic forecasts. However, the vast majority of recent hydro-economic literature is based on the cost-loss ratio framework, which might be appealing for its simplicity and intuitiveness. One important drawback of the cost-loss ratio is that it implicitly assumes a risk-neutral decision maker. By definition, a risk-neutral individual is indifferent to forecasts' sharpness: as long as forecasts agree with observations on average, the risk-neutral individual is satisfied. A risk-averse individual, however, is sensitive to the level of precision (sharpness) of forecasts. This person is willing to pay to increase his or her certainty about future events. In fact, this is how insurance companies operate: the probability of seeing one's house burn down is relatively low, so the expected cost related to such event is also low. However, people are willing to buy insurance to avoid the risk, however small, of loosing everything. Similarly, in a context where people's safety and property is at stake, the typical decision maker is more risk-averse than risk-neutral. Consequently, the cost-loss ratio is not the most appropriate tool to assess the economic value of flood forecasts. This presentation describes a more realistic framework for assessing the economic value of such forecasts for flood mitigation purposes. Borrowing from economics, the Constant Absolute Risk Aversion utility function (CARA) is the central tool of this new framework. Utility functions allow explicitly accounting for the level of risk aversion of the decision maker and fully exploiting the information related to ensemble forecasts' uncertainty. Three concurrent ensemble streamflow forecasting systems are compared in terms of quality (comparison with observed values) and in terms of their economic value. This assessment is performed for lead times of one to five days. The three systems are: (1) simple statistically dressed deterministic forecasts, (2) forecasts based on meteorological ensembles and (3) a variant of the latter that also includes an estimation of state variables uncertainty. The comparison takes place on the Montmorency River, a small flood-prone watershed in south central Quebec, Canada. The results show that forecasts quality as assessed by well-known tools such as the Continuous Ranked Probability Score or the reliability diagram do not necessarily translate directly into economic value, especially if the decision maker is not risk-neutral. In addition, results show that the economic value of forecasts for a risk-averse decision maker is very much influenced by the most extreme members of ensemble forecasts (upper tail of the predictive distributions). This study provides a new basis for further improvement of our comprehension of the complex interactions between forecasts uncertainty, risk-aversion and decision-making.

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.

Considering Tangible Benefit for Interdependent Donors: Extending a Risk-Benefit Framework in Donor Selection.

PubMed

Van Pilsum Rasmussen, S E; Henderson, M L; Kahn, J; Segev, D

2017-10-01

From its infancy, live donor transplantation has operated within a framework of acceptable risk to donors. Such a framework presumes that risks of living donation are experienced by the donor while all benefits are realized by the recipient, creating an inequitable distribution that demands minimization of donor risk. We suggest that this risk-tolerance framework ignores tangible benefits to the donor. A previously proposed framework more fully considers potential benefits to the donor and argues that risks and benefits must be balanced. We expand on this approach, and posit that donors sharing a household with and/or caring for a potential transplant patient may realize tangible benefits that are absent in a more distantly related donation (e.g. cousin, nondirected). We term these donors, whose well-being is closely tied to their recipient, "interdependent donors." A flexible risk-benefit model that combines risk assessment with benefits to interdependent donors will contribute to donor evaluation and selection that more accurately reflects what is at stake for donors. In so doing, a risk-benefit framework may allow some donors to accept greater risk in donation decisions. © 2017 The American Society of Transplantation and the American Society of Transplant Surgeons.

Advanced Computational Framework for Environmental Management ZEM, Version 1.x

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

Vesselinov, Velimir V.; O'Malley, Daniel; Pandey, Sachin

2016-11-04

Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions).more » To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.« less

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

NASA Astrophysics Data System (ADS)

Hargrave, C.; Moores, M.; Deegan, T.; Gibbs, A.; Poulsen, M.; Harden, F.; Mengersen, K.

2014-03-01

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific subregions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

Forecast-Informed Reservoir Operations: Lessons Learned from a Multi-Agency Collaborative Research and Operations Effort to improve Flood Risk Management, Water Supply and Environmental Benefits

NASA Astrophysics Data System (ADS)

Talbot, C. A.; Ralph, M.; Jasperse, J.; Forbis, J.

2017-12-01

Lessons learned from the multi-agency Forecast-Informed Reservoir Operations (FIRO) effort demonstrate how research and observations can inform operations and policy decisions at Federal, State and Local water management agencies with the collaborative engagement and support of researchers, engineers, operators and stakeholders. The FIRO steering committee consists of scientists, engineers and operators from research and operational elements of the National Oceanographic and Atmospheric Administration and the US Army Corps of Engineers, researchers from the US Geological Survey and the US Bureau of Reclamation, the state climatologist from the California Department of Water Resources, the chief engineer from the Sonoma County Water Agency, and the director of the Scripps Institution of Oceanography's Center for Western Weather and Water Extremes at the University of California-San Diego. The FIRO framework also provides a means of testing and demonstrating the benefits of next-generation water cycle observations, understanding and models in water resources operations.

Using the Situated Clinical Decision-Making framework to guide analysis of nurses' clinical decision-making.

PubMed

Gillespie, Mary

2010-11-01

Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.

Optimal indolence: a normative microscopic approach to work and leisure

PubMed Central

Niyogi, Ritwik K.; Breton, Yannick-Andre; Solomon, Rebecca B.; Conover, Kent; Shizgal, Peter; Dayan, Peter

2014-01-01

Dividing limited time between work and leisure when both have their attractions is a common everyday decision. We provide a normative control-theoretic treatment of this decision that bridges economic and psychological accounts. We show how our framework applies to free-operant behavioural experiments in which subjects are required to work (depressing a lever) for sufficient total time (called the price) to receive a reward. When the microscopic benefit-of-leisure increases nonlinearly with duration, the model generates behaviour that qualitatively matches various microfeatures of subjects’ choices, including the distribution of leisure bout durations as a function of the pay-off. We relate our model to traditional accounts by deriving macroscopic, molar, quantities from microscopic choices. PMID:24284898

Shared decision-making - Rhetoric and reality: Women's experiences and perceptions of adjuvant treatment decision-making for breast cancer.

PubMed

Mahmoodi, Neda; Sargeant, Sally

2017-01-01

This interview-based study uses phenomenology as a theoretical framework and thematic analysis to challenge existing explanatory frameworks of shared decision-making, in an exploration of women's experiences and perceptions of shared decision-making for adjuvant treatment in breast cancer. Three themes emerged are as follows: (1) women's desire to participate in shared decision-making, (2) the degree to which shared decision-making is perceived to be shared and (3) to what extent are women empowered within shared decision-making. Studying breast cancer patients' subjective experiences of adjuvant treatment decision-making provides a broader perspective on patient participatory role preferences and doctor-patient power dynamics within shared decision-making for breast cancer.

A complexity science-based framework for global joint operations analysis to support force projection: LDRD Final Report

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

Lawton, Craig R.

2015-01-01

The military is undergoing a significant transformation as it modernizes for the information age and adapts to address an emerging asymmetric threat beyond traditional cold war era adversaries. Techniques such as traditional large-scale, joint services war gaming analysis are no longer adequate to support program evaluation activities and mission planning analysis at the enterprise level because the operating environment is evolving too quickly. New analytical capabilities are necessary to address modernization of the Department of Defense (DoD) enterprise. This presents significant opportunity to Sandia in supporting the nation at this transformational enterprise scale. Although Sandia has significant experience with engineeringmore » system of systems (SoS) and Complex Adaptive System of Systems (CASoS), significant fundamental research is required to develop modeling, simulation and analysis capabilities at the enterprise scale. This report documents an enterprise modeling framework which will enable senior level decision makers to better understand their enterprise and required future investments.« less

Application of Geographical Information Systems and Remote Sensing technologies for assessing and monitoring malaria risk.

PubMed

Ceccato, P; Connor, S J; Jeanne, I; Thomson, M C

2005-03-01

Despite over 30 years of scientific research, algorithm development and multitudes of publications relating Remote Sensing (RS) information with the spatial and temporal distribution of malaria, it is only in recent years that operational products have been adopted by malaria control decision-makers. The time is ripe for the wealth of research knowledge and products from developed countries be made available to the decision-makers in malarious regions of the globe where this information is urgently needed. This paper reviews the capability of RS to provide useful information for operational malaria early warning systems. It also reviews the requirements for monitoring the major components influencing emergence of malaria and provides examples of applications that have been made. Discussion of the issues that have impeded implementation on a global scale and how those barriers are disappearing with recent economic, technological and political developments are explored; and help pave the way for implementation of an integrated Malaria Early Warning System framework using RS technologies.

A Primer on Receiver Operating Characteristic Analysis and Diagnostic Efficiency Statistics for Pediatric Psychology: We Are Ready to ROC

PubMed Central

2014-01-01

Objective To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Method Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Results Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. Conclusions This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses. PMID:23965298

A primer on receiver operating characteristic analysis and diagnostic efficiency statistics for pediatric psychology: we are ready to ROC.

PubMed

Youngstrom, Eric A

2014-03-01

To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses.

A coupled human-natural system to assess the operational value of weather and climate services for agriculture

NASA Astrophysics Data System (ADS)

Li, Yu; Giuliani, Matteo; Castelletti, Andrea

2017-09-01

Recent advances in weather and climate (W&C) services are showing increasing forecast skills over seasonal and longer timescales, potentially providing valuable support in informing decisions in a variety of economic sectors. Quantifying this value, however, might not be straightforward as better forecast quality does not necessarily imply better decisions by the end users, especially when forecasts do not reach their final users, when providers are not trusted, or when forecasts are not appropriately understood. In this study, we contribute an assessment framework to evaluate the operational value of W&C services for informing agricultural practices by complementing traditional forecast quality assessments with a coupled human-natural system behavioural model which reproduces farmers' decisions. This allows a more critical assessment of the forecast value mediated by the end users' perspective, including farmers' risk attitudes and behavioural factors. The application to an agricultural area in northern Italy shows that the quality of state-of-the-art W&C services is still limited in predicting the weather and the crop yield of the incoming agricultural season, with ECMWF annual products simulated by the IFS/HOPE model resulting in the most skillful product in the study area. However, we also show that the accuracy of estimating crop yield and the probability of making optimal decisions are not necessarily linearly correlated, with the overall assessment procedure being strongly impacted by the behavioural attitudes of farmers, which can produce rank reversals in the quantification of the W&C services operational value depending on the different perceptions of risk and uncertainty.

Strategic Assessment of Risk and Risk Tolerance (StARRT) framework for return-to-play decision-making.

PubMed

Shrier, Ian

2015-10-01

The sport medicine clinician is faced with return-to-play (RTP) decisions for every patient who wants to return to activity. The complex interaction of factors related to history, physical examination, testing, activity and baseline characteristics can make RTP decision-making challenging. Further, when reasoning is not explicit, unnecessary conflict can arise among clinicians themselves, or among clinicians and patients. This conflict can have negative health consequences for the patient. In 2010, a transparent framework for RTP decisions was proposed. However, some have identified limitations to the framework and found difficulties in its implementation. This paper presents a revised framework that addresses the limitations, and provides concrete examples of how to apply it in simple and complex cases. 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.

Effect of Wind Farm Noise on Local Residents' Decision to Adopt Mitigation Measures.

PubMed

Botelho, Anabela; Arezes, Pedro; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M Costa

2017-07-11

Wind turbines' noise is frequently pointed out as the reason for local communities' objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes' noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people's decision to adopt mitigating measures, independently of the reported annoyance.

The socio-economic dimension of flood risk assessment: insights of KULTURisk framework

NASA Astrophysics Data System (ADS)

Giupponi, Carlo; Gain, Animesh; Mojtahed, Vahid; Balbi, Stefano

2013-04-01

The approaches for vulnerability and risk assessment have found different and often contrasting solutions by various schools of thought. The two most prominent communities in this field are: climate change adaptation (CCA), and disaster risk reduction (DRR). Although those communities have usually in common the aim of reducing socio-economic vulnerability and risk to natural hazards, they have usually referred to different definitions and conceptualizations. For example, the DRR community has always driven more emphasis on the concept of risk and vulnerability is considered as a physical/environmental input for the quantification of risk, while the CCA research stream, mainly under the auspices of the Intergovernmental Panel on Climate Change (IPCC), considered vulnerability as an output deriving from social conditions and processes such as adaptation or maladaptation. Recently, with the publication of the IPCC Special Report on extreme events and disasters (IPCC-SREX), the notions of vulnerability and risk are somehow integrated in order to jointly consider both climate change adaptation and disaster risk management. The IPCC-SREX indeed is expected to significantly contribute to find common language and methodological approaches across disciplines and, therefore, the opportunity emerges for proposing new operational solutions, consistent with the most recent evolution of concepts and terminology. Based on the development of the IPCC Report, the KULTURisk project developed an operational framework to support integrated assessment and decision support through the combination of contributions from diverse disciplinary knowledge, with emphasis on the social and economic dimensions. KIRAF (KULTURisk Integrated Risk Assessment Framework) is specifically aimed at comprehensively evaluate the benefits of risk mitigation measures with consideration of the dynamic context deriving from the consideration of climatic changes and their effects on natural disasters, within the policy framework of climate change adaptation (CCA). Three main innovations are proposed with respect to the current state of the art: (1) to include the social capacities of reducing risk, (2) to go beyond the estimation direct tangible costs, and (3) to provide an operational solution for decision support to assess risks, impacts and the benefits of plausible risk reduction measures, compatible with both the DRR and the CCA literatures. As stated above, the proposed framework is the inclusion of social capacities (adaptive and coping capacities) in the process of translating risk into a comprehensive cost matrix considering not only direct tangible costs (damages), but also the three other components deriving from the combination of tangible/intangible and direct/indirect costs. The proposed KIRAF approach is thus expected to provide: 1) an operational basis for multidisciplinary integration; 2) a flexible reference to deal with heterogeneous case studies and potentially various types of hazards; and 3) a means to support the assessment of alternative risk prevention measures including consideration of social and cultural dimensions.

The role of evidence, context, and facilitation in an implementation trial: implications for the development of the PARIHS framework

PubMed Central

2013-01-01

Background The case has been made for more and better theory-informed process evaluations within trials in an effort to facilitate insightful understandings of how interventions work. In this paper, we provide an explanation of implementation processes from one of the first national implementation research randomized controlled trials with embedded process evaluation conducted within acute care, and a proposed extension to the Promoting Action on Research Implementation in Health Services (PARIHS) framework. Methods The PARIHS framework was prospectively applied to guide decisions about intervention design, data collection, and analysis processes in a trial focussed on reducing peri-operative fasting times. In order to capture a holistic picture of implementation processes, the same data were collected across 19 participating hospitals irrespective of allocation to intervention. This paper reports on findings from data collected from a purposive sample of 151 staff and patients pre- and post-intervention. Data were analysed using content analysis within, and then across data sets. Results A robust and uncontested evidence base was a necessary, but not sufficient condition for practice change, in that individual staff and patient responses such as caution influenced decision making. The implementation context was challenging, in which individuals and teams were bounded by professional issues, communication challenges, power and a lack of clarity for the authority and responsibility for practice change. Progress was made in sites where processes were aligned with existing initiatives. Additionally, facilitators reported engaging in many intervention implementation activities, some of which result in practice changes, but not significant improvements to outcomes. Conclusions This study provided an opportunity for reflection on the comprehensiveness of the PARIHS framework. Consistent with the underlying tenant of PARIHS, a multi-faceted and dynamic story of implementation was evident. However, the prominent role that individuals played as part of the interaction between evidence and context is not currently explicit within the framework. We propose that successful implementation of evidence into practice is a planned facilitated process involving an interplay between individuals, evidence, and context to promote evidence-informed practice. This proposal will enhance the potential of the PARIHS framework for explanation, and ensure theoretical development both informs and responds to the evidence base for implementation. Trial registration ISRCTN18046709 - Peri-operative Implementation Study Evaluation (PoISE). PMID:23497438

Bi-Level Decision Making for Supporting Energy and Water Nexus

NASA Astrophysics Data System (ADS)

Zhang, X.; Vesselinov, V. V.

2016-12-01

The inseparable relationship between energy production and water resources has led to the emerging energy-water nexus concept, which provides a means for integrated management and decision making of these two critical resources. However, the energy-water nexus frequently involves decision makers with different and competing management objectives. Furthermore, there is a challenge that decision makers and stakeholders might be making decisions sequentially from a higher level to a lower level, instead of at the same decision level, whereby the objective of a decision maker at a higher level should be satisfied first. In this study, a bi-level decision model is advanced to handle such decision-making situations for managing the energy-water nexus. The work represents a unique contribution to developing an integrated decision-support framework/tool to quantify and analyze the tradeoffs between the two-level energy-water nexus decision makers. Here, plans for electricity generation, fuel supply, water supply, capacity expansion of the power plants and environmental impacts are optimized to provide effective decision support. The developed decision-support framework is implemented in Julia (a high-level, high-performance dynamic programming language for technical computing) and is a part of the MADS (Model Analyses & Decision Support) framework (http://mads.lanl.gov). To demonstrate the capabilities of the developed methodology, a series of analyses are performed for synthetic problems consistent with actual real-world energy-water nexus management problems.

The EPOS Legal and Governance Framework : tailoring the infrastructure to fit the needs of the EPOS services

NASA Astrophysics Data System (ADS)

Kohler, Elisabeth; Pedersen, Helle; Kontkanen, Pirjo; Korja, Annakaisa; Lauterjung, Jörn; Haslinger, Florian; Sangianantoni, Agata; Bartolini, Alessandro; Consortium, Epos

2016-04-01

One of the most important issues regarding a pan-European distributed large scale research infrastructure is the setting up of its legal and governance structure as this will shape the very operation of the undertaking, i.e. the decision-making process, the allocation of tasks and resources as well as the relationship between the different bodies. Ensuring long-term operational services requires a robust, coherent and transparent legal and governance framework across all of the EPOS TCS (Thematic Core Services) and ICS (Integrated Core Services) that is well aligned to the EPOS global architecture. The chosen model for the EPOS legal entity is the ERIC (European Research Infrastructure Consortium). While the statutory seat of EPOS-ERIC will be in Rome, Italy, most of the services will be hosted in other countries. Specific agreements between EPOS-ERIC and the legal bodies hosting EPOS services will be implemented to allow proper coordination of activities. The objective is to avoid multiple agreements and, where possible, to standardize them in order to reach a harmonized situation across all services. For the governance careful attention will be paid to the decision-making process, the type of decisions and the voting rights, the definition of responsibilities, rights and duties, the reporting mechanisms, as well as other issues like who within a TCS represents the service to the 'outside' world or who advices the TCS on which subjects. Data policy is another crucial issue as EPOS aims to provide interdisciplinary services to researchers interested in geoscience, including access to data, metadata, data products, software and IT tools. EPOS also provides access to computational resources for visualization and processing. Beyond the general principles of Open Access and Open Source the following questions have to be addressed: scope and nature of data that will be accepted; intellectual property rights in data and terms under which data will be shared; openness and availability of data; data privacy and security; publication and attribution; liability and violations or misuse of data. To support the challenges of the EPOS legal, governance, and also financial framework, EPOS will implement a sophisticated metadata catalog and associated integrated services in its ICT architecture.

The Air Force’s Individual Mobilization Augmentee Program: Is the Current Organizational Structure Viable?

DTIC Science & Technology

2012-10-01

support ongoing efforts by Lt Gen Charles Stenner to transform the Reserve into the operational, cost-effective, enhanced force that he envisions.35...Charles E. Stenner , Total Force Policy 21: A 21st Century Framework for Military Force Mix Decisions, Air Force Reserve White Paper (Washington, DC...20. Stenner , Total Force Policy 21, 3–5. 21. Readiness Management Group, RMG Individual Reserve Guide, 8–9. 22. Ibid.; and Stenner , Total Force

A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

NASA Technical Reports Server (NTRS)

Freed, Michael; Remington, Roger; Null, Cynthia H. (Technical Monitor)

1998-01-01

We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.

Energy Technology Investments: Maximizing Efficiency Through a Maritime Energy Portfolio Interface and Decision Aid

DTIC Science & Technology

2012-02-09

Investment (ROI) and Break Even Point ( BEP ). These metrics are essential for determining whether an initiative would be worth pursuing. Balanced...is Unlimited Energy Decision Framework Identify Inefficiencies 2. Perform Analyses 3. Examine Technology Candidates 1. Improve Energy...Unlimited Energy Decision Framework Identify Inefficiencies 2. Perform Analyses 3. Examine Technology Candidates 1. Improve Energy Efficiency 4

Pandemic influenza preparedness: an ethical framework to guide decision-making

PubMed Central

Thompson, Alison K; Faith, Karen; Gibson, Jennifer L; Upshur, Ross EG

2006-01-01

Background Planning for the next pandemic influenza outbreak is underway in hospitals across the world. The global SARS experience has taught us that ethical frameworks to guide decision-making may help to reduce collateral damage and increase trust and solidarity within and between health care organisations. Good pandemic planning requires reflection on values because science alone cannot tell us how to prepare for a public health crisis. Discussion In this paper, we present an ethical framework for pandemic influenza planning. The ethical framework was developed with expertise from clinical, organisational and public health ethics and validated through a stakeholder engagement process. The ethical framework includes both substantive and procedural elements for ethical pandemic influenza planning. The incorporation of ethics into pandemic planning can be helped by senior hospital administrators sponsoring its use, by having stakeholders vet the framework, and by designing or identifying decision review processes. We discuss the merits and limits of an applied ethical framework for hospital decision-making, as well as the robustness of the framework. Summary The need for reflection on the ethical issues raised by the spectre of a pandemic influenza outbreak is great. Our efforts to address the normative aspects of pandemic planning in hospitals have generated interest from other hospitals and from the governmental sector. The framework will require re-evaluation and refinement and we hope that this paper will generate feedback on how to make it even more robust. PMID:17144926

Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites.

PubMed

Khadam, Ibrahim; Kaluarachchi, Jagath J

2003-07-01

Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating non-technical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed.

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

Data and information integration framework for highway project decision making.

DOT National Transportation Integrated Search

2013-08-01

This report presents a three-tiered framework to integrate data, information, and decision-making in highway projects. The study uses the Jurans Triple Role concept and context graph to illustrate the relationship between data, information, and de...

A Risk Analysis Methodology to Address Human and Organizational Factors in Offshore Drilling Safety: With an Emphasis on Negative Pressure Test

NASA Astrophysics Data System (ADS)

Tabibzadeh, Maryam

According to the final Presidential National Commission report on the BP Deepwater Horizon (DWH) blowout, there is need to "integrate more sophisticated risk assessment and risk management practices" in the oil industry. Reviewing the literature of the offshore drilling industry indicates that most of the developed risk analysis methodologies do not fully and more importantly, systematically address the contribution of Human and Organizational Factors (HOFs) in accident causation. This is while results of a comprehensive study, from 1988 to 2005, of more than 600 well-documented major failures in offshore structures show that approximately 80% of those failures were due to HOFs. In addition, lack of safety culture, as an issue related to HOFs, have been identified as a common contributing cause of many accidents in this industry. This dissertation introduces an integrated risk analysis methodology to systematically assess the critical role of human and organizational factors in offshore drilling safety. The proposed methodology in this research focuses on a specific procedure called Negative Pressure Test (NPT), as the primary method to ascertain well integrity during offshore drilling, and analyzes the contributing causes of misinterpreting such a critical test. In addition, the case study of the BP Deepwater Horizon accident and their conducted NPT is discussed. The risk analysis methodology in this dissertation consists of three different approaches and their integration constitutes the big picture of my whole methodology. The first approach is the comparative analysis of a "standard" NPT, which is proposed by the author, with the test conducted by the DWH crew. This analysis contributes to identifying the involved discrepancies between the two test procedures. The second approach is a conceptual risk assessment framework to analyze the causal factors of the identified mismatches in the previous step, as the main contributors of negative pressure test misinterpretation. Finally, a rational decision making model is introduced to quantify a section of the developed conceptual framework in the previous step and analyze the impact of different decision making biases on negative pressure test results. Along with the corroborating findings of previous studies, the analysis of the developed conceptual framework in this paper indicates that organizational factors are root causes of accumulated errors and questionable decisions made by personnel or management. Further analysis of this framework identifies procedural issues, economic pressure, and personnel management issues as the organizational factors with the highest influence on misinterpreting a negative pressure test. It is noteworthy that the captured organizational factors in the introduced conceptual framework are not only specific to the scope of the NPT. Most of these organizational factors have been identified as not only the common contributing causes of other offshore drilling accidents but also accidents in other oil and gas related operations as well as high-risk operations in other industries. In addition, the proposed rational decision making model in this research introduces a quantitative structure for analysis of the results of a conducted NPT. This model provides a structure and some parametric derived formulas to determine a cut-off point value, which assists personnel in accepting or rejecting an implemented negative pressure test. Moreover, it enables analysts to assess different decision making biases involved in the process of interpreting a conducted negative pressure test as well as the root organizational factors of those biases. In general, although the proposed integrated research methodology in this dissertation is developed for the risk assessment of human and organizational factors contributions in negative pressure test misinterpretation, it can be generalized and be potentially useful for other well control situations, both offshore and onshore; e.g. fracking. In addition, this methodology can be applied for the analysis of any high-risk operations, in not only the oil and gas industry but also in other industries such as nuclear power plants, aviation industry, and transportation sector.

A risk-based decision support framework for selection of appropriate safety measure system for underground coal mines.

PubMed

Samantra, Chitrasen; Datta, Saurav; Mahapatra, Siba Sankar

2017-03-01

In the context of underground coal mining industry, the increased economic issues regarding implementation of additional safety measure systems, along with growing public awareness to ensure high level of workers safety, have put great pressure on the managers towards finding the best solution to ensure safe as well as economically viable alternative selection. Risk-based decision support system plays an important role in finding such solutions amongst candidate alternatives with respect to multiple decision criteria. Therefore, in this paper, a unified risk-based decision-making methodology has been proposed for selecting an appropriate safety measure system in relation to an underground coal mining industry with respect to multiple risk criteria such as financial risk, operating risk, and maintenance risk. The proposed methodology uses interval-valued fuzzy set theory for modelling vagueness and subjectivity in the estimates of fuzzy risk ratings for making appropriate decision. The methodology is based on the aggregative fuzzy risk analysis and multi-criteria decision making. The selection decisions are made within the context of understanding the total integrated risk that is likely to incur while adapting the particular safety system alternative. Effectiveness of the proposed methodology has been validated through a real-time case study. The result in the context of final priority ranking is seemed fairly consistent.

Decision-making about complementary and alternative medicine by cancer patients: integrative literature review.

PubMed

Weeks, Laura; Balneaves, Lynda G; Paterson, Charlotte; Verhoef, Marja

2014-01-01

Patients with cancer consistently report conflict and anxiety when making decisions about complementary and alternative medicine (CAM) treatment. To design evidence-informed decision-support strategies, a better understanding is needed of how the decision-making process unfolds for these patients during their experience with cancer. We undertook this study to review the research literature regarding CAM-related decision-making by patients with cancer within the context of treatment, survivorship, and palliation. We also aimed to summarize emergent concepts within a preliminary conceptual framework. We conducted an integrative literature review, searching 12 electronic databases for articles published in English that described studies of the process, context, or outcomes of CAM-related decision-making. We summarized descriptive data using frequencies and used a descriptive constant comparative method to analyze statements about original qualitative results, with the goal of identifying distinct concepts pertaining to CAM-related decision-making by patients with cancer and the relationships among these concepts. Of 425 articles initially identified, 35 met our inclusion criteria. Seven unique concepts related to CAM and cancer decision-making emerged: decision-making phases, information-seeking and evaluation, decision-making roles, beliefs, contextual factors, decision-making outcomes, and the relationship between CAM and conventional medical decision-making. CAM decision-making begins with the diagnosis of cancer and encompasses 3 distinct phases (early, mid, and late), each marked by unique aims for CAM treatment and distinct patterns of information-seeking and evaluation. Phase transitions correspond to changes in health status or other milestones within the cancer trajectory. An emergent conceptual framework illustrating relationships among the 7 central concepts is presented. CAM-related decision-making by patients with cancer occurs as a nonlinear, complex, dynamic process. The conceptual framework presented here identifies influential factors within that process, as well as patients' unique needs during different phases. The framework can guide the development and evaluation of theory-based decision-support programs that are responsive to patients' beliefs and preferences.

Generalizable open source urban water portfolio simulation framework demonstrated using a multi-objective risk-based planning benchmark problem.

NASA Astrophysics Data System (ADS)

Trindade, B. C.; Reed, P. M.

2017-12-01

The growing access and reduced cost for computing power in recent years has promoted rapid development and application of multi-objective water supply portfolio planning. As this trend continues there is a pressing need for flexible risk-based simulation frameworks and improved algorithm benchmarking for emerging classes of water supply planning and management problems. This work contributes the Water Utilities Management and Planning (WUMP) model: a generalizable and open source simulation framework designed to capture how water utilities can minimize operational and financial risks by regionally coordinating planning and management choices, i.e. making more efficient and coordinated use of restrictions, water transfers and financial hedging combined with possible construction of new infrastructure. We introduce the WUMP simulation framework as part of a new multi-objective benchmark problem for planning and management of regionally integrated water utility companies. In this problem, a group of fictitious water utilities seek to balance the use of the mentioned reliability driven actions (e.g., restrictions, water transfers and infrastructure pathways) and their inherent financial risks. Several traits of this problem make it ideal for a benchmark problem, namely the presence of (1) strong non-linearities and discontinuities in the Pareto front caused by the step-wise nature of the decision making formulation and by the abrupt addition of storage through infrastructure construction, (2) noise due to the stochastic nature of the streamflows and water demands, and (3) non-separability resulting from the cooperative formulation of the problem, in which decisions made by stakeholder may substantially impact others. Both the open source WUMP simulation framework and its demonstration in a challenging benchmarking example hold value for promoting broader advances in urban water supply portfolio planning for regions confronting change.

Mapping social-ecological vulnerability to inform local decision making.

PubMed

Thiault, Lauric; Marshall, Paul; Gelcich, Stefan; Collin, Antoine; Chlous, Frédérique; Claudet, Joachim

2018-04-01

An overarching challenge of natural resource management and biodiversity conservation is that relationships between people and nature are difficult to integrate into tools that can effectively guide decision making. Social-ecological vulnerability offers a valuable framework for identifying and understanding important social-ecological linkages, and the implications of dependencies and other feedback loops in the system. Unfortunately, its implementation at local scales has hitherto been limited due at least in part to the lack of operational tools for spatial representation of social-ecological vulnerability. We developed a method to map social-ecological vulnerability based on information on human-nature dependencies and ecosystem services at local scales. We applied our method to the small-scale fishery of Moorea, French Polynesia, by combining spatially explicit indicators of exposure, sensitivity, and adaptive capacity of both the resource (i.e., vulnerability of reef fish assemblages to fishing) and resource users (i.e., vulnerability of fishing households to the loss of fishing opportunity). Our results revealed that both social and ecological vulnerabilities varied considerably through space and highlighted areas where sources of vulnerability were high for both social and ecological subsystems (i.e., social-ecological vulnerability hotspots) and thus of high priority for management intervention. Our approach can be used to inform decisions about where biodiversity conservation strategies are likely to be more effective and how social impacts from policy decisions can be minimized. It provides a new perspective on human-nature linkages that can help guide sustainability management at local scales; delivers insights distinct from those provided by emphasis on a single vulnerability component (e.g., exposure); and demonstrates the feasibility and value of operationalizing the social-ecological vulnerability framework for policy, planning, and participatory management decisions. © 2017 Society for Conservation Biology.

A leader's framework for decision making. A leader's framework for decision making.

PubMed

Snowden, David J; Boone, Mary E

2007-11-01

Many executives are surprised when previously successful leadership approaches fail in new situations, but different contexts call for different kinds of responses. Before addressing a situation, leaders need to recognize which context governs it -and tailor their actions accordingly. Snowden and Boone have formed a new perspective on leadership and decision making that's based on complexity science. The result is the Cynefin framework, which helps executives sort issues into five contexts: Simple contexts are characterized by stability and cause-and-effect relationships that are clear to everyone. Often, the right answer is self-evident. In this realm of "known knowns," leaders must first assess the facts of a situation -that is, "sense" it -then categorize and respond to it. Complicated contexts may contain multiple right answers, and though there is a clear relationship between cause and effect, not everyone can see it. This is the realm of "known unknowns." Here, leaders must sense, analyze, and respond. In a complex context, right answers can't be ferreted out at all; rather, instructive patterns emerge if the leader conducts experiments that can safely fail. This is the realm of "unknown unknowns," where much of contemporary business operates. Leaders in this context need to probe first, then sense, and then respond. In a chaotic context, searching for right answers is pointless. The relationships between cause and effect are impossible to determine because they shift constantly and no manageable patterns exist. This is the realm of unknowables (the events of September 11, 2001, fall into this category). In this domain, a leader must first act to establish order, sense where stability is present, and then work to transform the situation from chaos to complexity. The fifth context, disorder, applies when it is unclear which of the other four contexts is predominant. The way out is to break the situation into its constituent parts and assign each to one of the other four realms. Leaders can then make decisions and intervene in contextually appropriate ways.

Dynamic decision making for dam-break emergency management - Part 1: Theoretical framework

NASA Astrophysics Data System (ADS)

Peng, M.; Zhang, L. M.

2013-02-01

An evacuation decision for dam breaks is a very serious issue. A late decision may lead to loss of lives and properties, but a very early evacuation will incur unnecessary expenses. This paper presents a risk-based framework of dynamic decision making for dam-break emergency management (DYDEM). The dam-break emergency management in both time scale and space scale is introduced first to define the dynamic decision problem. The probability of dam failure is taken as a stochastic process and estimated using a time-series analysis method. The flood consequences are taken as functions of warning time and evaluated with a human risk analysis model (HURAM) based on Bayesian networks. A decision criterion is suggested to decide whether to evacuate the population at risk (PAR) or to delay the decision. The optimum time for evacuating the PAR is obtained by minimizing the expected total loss, which integrates the time-related probabilities and flood consequences. When a delayed decision is chosen, the decision making can be updated with available new information. A specific dam-break case study is presented in a companion paper to illustrate the application of this framework to complex dam-breaching problems.

TAMU: A New Space Mission Operations Paradigm

NASA Technical Reports Server (NTRS)

Meshkat, Leila; Ruszkowski, James; Haensly, Jean; Pennington, Granvil A.; Hogle, Charles

2011-01-01

The Transferable, Adaptable, Modular and Upgradeable (TAMU) Flight Production Process (FPP) is a model-centric System of System (SoS) framework which cuts across multiple organizations and their associated facilities, that are, in the most general case, in geographically diverse locations, to develop the architecture and associated workflow processes for a broad range of mission operations. Further, TAMU FPP envisions the simulation, automatic execution and re-planning of orchestrated workflow processes as they become operational. This paper provides the vision for the TAMU FPP paradigm. This includes a complete, coherent technique, process and tool set that result in an infrastructure that can be used for full lifecycle design and decision making during any flight production process. A flight production process is the process of developing all products that are necessary for flight.

Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

NASA Astrophysics Data System (ADS)

Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul

2017-10-01

A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.

TIUPAM: A Framework for Trustworthiness-Centric Information Sharing

NASA Astrophysics Data System (ADS)

Xu, Shouhuai; Sandhu, Ravi; Bertino, Elisa

Information is essential to decision making. Nowadays, decision makers are often overwhelmed with large volumes of information, some of which may be inaccurate, incorrect, inappropriate, misleading, or maliciously introduced. With the advocated shift of information sharing paradigm from “need to know” to “need to share” this problem will be further compounded. This poses the challenge of achieving assured information sharing so that decision makers can always get and utilize the up-to-date information for making the right decisions, despite the existence of malicious attacks and without breaching privacy of honest participants. As a first step towards answering this challenge this paper proposes a systematic framework we call TIUPAM, which stands for “Trustworthiness-centric Identity, Usage, Provenance, and Attack Management.” The framework is centered at the need of trustworthiness and risk management for decision makers, and supported by four key components: identity management, usage management, provenance management and attack management. We explore the characterization of both the core functions and the supporting components in the TIUPAM framework, which may guide the design and realization of concrete schemes in the future.

Documenting moral agency: a qualitative analysis of abortion decision making for fetal indications.

PubMed

Gawron, Lori M; Watson, Katie

2017-02-01

We explored whether the decision-making process of women aborting a pregnancy for a fetal indication fit common medical ethical frameworks. We applied three ethical frameworks (principlism, care ethics, and narrative ethics) in a secondary analysis of 30 qualitative interviews from women choosing 2nd trimester abortion for fetal indications. All 30 women offered reasoning consistent with one or more ethical frameworks. Principlism themes included avoidance of personal suffering (autonomy), and sparing a child a poor quality of life and painful medical interventions (beneficence/non-maleficence). Care ethics reasoning included relational considerations of family needs and resources, and narrative ethics reasoning contextualized this experience into the patient's life story. This population's universal application of commonly accepted medical ethical frameworks supports the position that patients choosing fetal indication abortions should be treated as moral decision-makers and given the same respect as patients making decisions about other medical procedures. These findings suggest recent political efforts blocking abortion access should be reframed as attempts to undermine the moral decision-making of women. Published by Elsevier Inc.

Classifying clinical decision making: interpreting nursing intuition, heuristics and medical diagnosis.

PubMed

Buckingham, C D; Adams, A

2000-10-01

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.

A judgment and decision-making model for plant behavior.

PubMed

Karban, Richard; Orrock, John L

2018-06-12

Recently plant biologists have documented that plants, like animals, engage in many activities that can be considered as behaviors, although plant biologists currently lack a conceptual framework to understand these processes. Borrowing the well-established framework developed by psychologists, we propose that plant behaviors can be constructively modeled by identifying four distinct components: 1) a cue or stimulus that provides information, 2) a judgment whereby the plant perceives and processes this informative cue, 3) a decision whereby the plant chooses among several options based on their relative costs and benefits, and 4) action. Judgment for plants can be determined empirically by monitoring signaling associated with electrical, calcium, or hormonal fluxes. Decision-making can be evaluated empirically by monitoring gene expression or differential allocation of resources. We provide examples of the utility of this judgment and decision-making framework by considering cases in which plants either successfully or unsuccessfully induced resistance against attacking herbivores. Separating judgment from decision-making suggests new analytical paradigms (i.e., Bayesian methods for judgment and economic utility models for decision-making). Following this framework, we propose an experimental approach to plant behavior that explicitly manipulates the stimuli provided to plants, uses plants that vary in sensory abilities, and examines how environmental context affects plant responses. The concepts and approaches that follow from the judgment and decision-making framework can shape how we study and understand plant-herbivore interactions, biological invasions, plant responses to climate change, and the susceptibility of plants to evolutionary traps. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Characterizing the Leaching Behavior of Coal Combustion Residues using the Leaching Environmental Assessment Framework (LEAF) to Inform Future Management Decisions

EPA Science Inventory

Abstract for presentation on Characterizing the Leaching Behavior of Coal Combustion Residues using the Leaching Environmental Assessment Framework (LEAF) to Inform Future Management Decisions. The abstract is attached.

Cyberwar XXI: quantifying the unquantifiable: adaptive AI for next-generation conflict simulations

NASA Astrophysics Data System (ADS)

Miranda, Joseph; von Kleinsmid, Peter; Zalewski, Tony

2004-08-01

The era of the "Revolution in Military Affairs," "4th Generation Warfare" and "Asymmetric War" requires novel approaches to modeling warfare at the operational and strategic level of modern conflict. For example, "What if, in response to our planned actions, the adversary reacts in such-and-such a manner? What will our response be? What are the possible unintended consequences?" Next generation conflict simulation tools are required to help create and test novel courses of action (COA's) in support of real-world operations. Conflict simulations allow non-lethal and cost-effective exploration of the "what-if" of COA development. The challenge has been to develop an automated decision-support software tool which allows competing COA"s to be compared in simulated dynamic environments. Principal Investigator Joseph Miranda's research is based on modeling an integrated military, economic, social, infrastructure and information (PMESII) environment. The main effort was to develop an adaptive AI engine which models agents operating within an operational-strategic conflict environment. This was implemented in Cyberwar XXI - a simulation which models COA selection in a PMESII environment. Within this framework, agents simulate decision-making processes and provide predictive capability of the potential behavior of Command Entities. The 2003 Iraq is the first scenario ready for V&V testing.

The benefit of using additional hydrological information from earth observations and reanalysis data on water allocation decisions in irrigation districts

NASA Astrophysics Data System (ADS)

Kaune, Alexander; López, Patricia; Werner, Micha; de Fraiture, Charlotte

2017-04-01

Hydrological information on water availability and demand is vital for sound water allocation decisions in irrigation districts, particularly in times of water scarcity. However, sub-optimal water allocation decisions are often taken with incomplete hydrological information, which may lead to agricultural production loss. In this study we evaluate the benefit of additional hydrological information from earth observations and reanalysis data in supporting decisions in irrigation districts. Current water allocation decisions were emulated through heuristic operational rules for water scarce and water abundant conditions in the selected irrigation districts. The Dynamic Water Balance Model based on the Budyko framework was forced with precipitation datasets from interpolated ground measurements, remote sensing and reanalysis data, to determine the water availability for irrigation. Irrigation demands were estimated based on estimates of potential evapotranspiration and coefficient for crops grown, adjusted with the interpolated precipitation data. Decisions made using both current and additional hydrological information were evaluated through the rate at which sub-optimal decisions were made. The decisions made using an amended set of decision rules that benefit from additional information on demand in the districts were also evaluated. Results show that sub-optimal decisions can be reduced in the planning phase through improved estimates of water availability. Where there are reliable observations of water availability through gauging stations, the benefit of the improved precipitation data is found in the improved estimates of demand, equally leading to a reduction of sub-optimal decisions.

Practice Guidelines for Operative Performance Assessments.

PubMed

Williams, Reed G; Kim, Michael J; Dunnington, Gary L

2016-12-01

To provide recommended practice guidelines for assessing single operative performances and for combining results of operative performance assessments into estimates of overall operative performance ability. Operative performance is one defining characteristic of surgeons. Assessment of operative performance is needed to provide feedback with learning benefits to surgical residents in training and to assist in making progress decisions for residents. Operative performance assessment has been a focus of investigation over the past 20 years. This review is designed to integrate findings of this research into a set of recommended operative performance practices. Literature from surgery and from other pertinent research areas (psychology, education, business) was reviewed looking for evidence to inform practice guideline development. Guidelines were created along with a conceptual and scientific foundation for each guideline. Ten guidelines are provided for assessing individual operative performances and 10 are provided for combing data from individual operative performances into overall judgments of operative performance ability. The practice guidelines organize available information to be immediately useful to program directors, to support surgical training, and to provide a conceptual framework upon which to build as the base of pertinent knowledge expands through future research and development efforts.

Graph-based structural change detection for rotating machinery monitoring

NASA Astrophysics Data System (ADS)

Lu, Guoliang; Liu, Jie; Yan, Peng

2018-01-01

Detection of structural changes is critically important in operational monitoring of a rotating machine. This paper presents a novel framework for this purpose, where a graph model for data modeling is adopted to represent/capture statistical dynamics in machine operations. Meanwhile we develop a numerical method for computing temporal anomalies in the constructed graphs. The martingale-test method is employed for the change detection when making decisions on possible structural changes, where excellent performance is demonstrated outperforming exciting results such as the autoregressive-integrated-moving average (ARIMA) model. Comprehensive experimental results indicate good potentials of the proposed algorithm in various engineering applications. This work is an extension of a recent result (Lu et al., 2017).

Implementation of Cyber-Physical Production Systems for Quality Prediction and Operation Control in Metal Casting.

PubMed

Lee, JuneHyuck; Noh, Sang Do; Kim, Hyun-Jung; Kang, Yong-Shin

2018-05-04

The prediction of internal defects of metal casting immediately after the casting process saves unnecessary time and money by reducing the amount of inputs into the next stage, such as the machining process, and enables flexible scheduling. Cyber-physical production systems (CPPS) perfectly fulfill the aforementioned requirements. This study deals with the implementation of CPPS in a real factory to predict the quality of metal casting and operation control. First, a CPPS architecture framework for quality prediction and operation control in metal-casting production was designed. The framework describes collaboration among internet of things (IoT), artificial intelligence, simulations, manufacturing execution systems, and advanced planning and scheduling systems. Subsequently, the implementation of the CPPS in actual plants is described. Temperature is a major factor that affects casting quality, and thus, temperature sensors and IoT communication devices were attached to casting machines. The well-known NoSQL database, HBase and the high-speed processing/analysis tool, Spark, are used for IoT repository and data pre-processing, respectively. Many machine learning algorithms such as decision tree, random forest, artificial neural network, and support vector machine were used for quality prediction and compared with R software. Finally, the operation of the entire system is demonstrated through a CPPS dashboard. In an era in which most CPPS-related studies are conducted on high-level abstract models, this study describes more specific architectural frameworks, use cases, usable software, and analytical methodologies. In addition, this study verifies the usefulness of CPPS by estimating quantitative effects. This is expected to contribute to the proliferation of CPPS in the industry.

Water Resources Planning under Uncertainty: A "Real Options" Approach

NASA Astrophysics Data System (ADS)

Jeuland, M. A.; Whittington, D.

2011-12-01

This research develops a real options approach for planning new water resources developments, in infrastructure construction and system operation, under uncertainty. The approach treats the planning problem as a series of staged decisions - the selection of new projects; their scale, timing and sequencing; and finally their operating rules - each of which is characterized by varying levels of irreversibility. The performance of different configurations of the system is then assessed along the various dimensions of the decision space, using simulation methods. The methodology is then made operational using an existing hydrological simulation model that can be used to study the example of hydropower development options in the Blue Nile in Ethiopia. The model includes physical linkages between climate change and system hydrology, and allows users to test the sensitivity of the basin-wide economic consequences of dams, which consist of energy generation, changes in irrigation crop-water demand, the value of flood control, and other basin-wide impacts, to climate change or changes in runoff, as well as to other uncertainties. The analysis shows that, from an economic perspective, there is no single optimal system configuration across a range of future climate conditions deemed plausible for this basin. For example, small infrastructures perform best in scenarios with reduced runoff into the river, whereas large ones are best when runoff increases. The real options framework therefore becomes useful for helping to identify configurations that are both more robust to poor outcomes and still contain sufficient flexibility to capture high upside benefits should favorable future conditions arise. The framework could readily be extended to explore a range of features that could be usefully built into water resources projects more generally, to improve the long-term economic performance of such investments.

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.

Framework for modeling high-impact, low-frequency power grid events to support risk-informed decisions

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

Veeramany, Arun; Unwin, Stephen D.; Coles, Garill A.

2016-06-25

Natural and man-made hazardous events resulting in loss of grid infrastructure assets challenge the security and resilience of the electric power grid. However, the planning and allocation of appropriate contingency resources for such events requires an understanding of their likelihood and the extent of their potential impact. Where these events are of low likelihood, a risk-informed perspective on planning can be difficult, as the statistical basis needed to directly estimate the probabilities and consequences of their occurrence does not exist. Because risk-informed decisions rely on such knowledge, a basis for modeling the risk associated with high-impact, low-frequency events (HILFs) ismore » essential. Insights from such a model indicate where resources are most rationally and effectively expended. A risk-informed realization of designing and maintaining a grid resilient to HILFs will demand consideration of a spectrum of hazards/threats to infrastructure integrity, an understanding of their likelihoods of occurrence, treatment of the fragilities of critical assets to the stressors induced by such events, and through modeling grid network topology, the extent of damage associated with these scenarios. The model resulting from integration of these elements will allow sensitivity assessments based on optional risk management strategies, such as alternative pooling, staging and logistic strategies, and emergency contingency planning. This study is focused on the development of an end-to-end HILF risk-assessment framework. Such a framework is intended to provide the conceptual and overarching technical basis for the development of HILF risk models that can inform decision-makers across numerous stakeholder groups in directing resources optimally towards the management of risks to operational continuity.« less

Many-objective reservoir policy identification and refinement to reduce institutional myopia in water management

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Herman, Jonathan D.; Castelletti, Andrea; Reed, Patrick M.

2014-05-01

Current water reservoir operating policies are facing growing water demands as well as increasing uncertainties associated with a changing climate. However, policy inertia and myopia strongly limit the possibility of adapting current water reservoir operations to the undergoing change. Historical agreements and regulatory constraints limit the rate that reservoir operations are innovated and creates policy inertia, where water institutions are unlikely to change their current practices in absence of dramatic failures. Yet, no guarantee exists that historical management policies will not fail in coming years. In reference to policy myopia, although it has long been recognized that water reservoir systems are generally framed in heterogeneous socio-economic contexts involving a myriad of conflicting, non-commensurable operating objectives, the broader understanding of the multi-objective consequences of current operating rules as well as their vulnerability to hydroclimatic uncertainties is severely limited. This study proposes a decision analytic framework to overcome both policy inertia and myopia in complex river basin management contexts. The framework combines reservoir policy identification, many-objective optimization under uncertainty, and visual analytics to characterize current operations and discover key tradeoffs between alternative policies for balancing evolving demands and system uncertainties. The approach is demonstrated on the Conowingo Dam, located within the Lower Susquehanna River, USA. The Lower Susquehanna River is an interstate water body that has been subject to intensive water management efforts due to the system's competing demands from urban water supply, atomic power plant cooling, hydropower production, and federally regulated environmental flows. The proposed framework initially uses available streamflow observations to implicitly identify the current but unknown operating policy of Conowingo Dam. The quality of the identified baseline policy was validated by its ability to replicate historical release dynamics. Starting from this baseline policy, we then combine evolutionary many-objective optimization with visual analytics to discover new operating policies that better balance the tradeoffs within the Lower Susquehanna. Results confirm that the baseline operating policy, which only considers deterministic historical inflows, significantly overestimates the reliability of the reservoir's competing demands. The proposed framework removes this bias by successfully identifying alternative reservoir policies that are more robust to hydroclimatic uncertainties, while also better addressing the tradeoffs across the Conowingo Dam's multi-sector services.

Incorporating exposure information into the toxicological prioritization index decision support framework

EPA Science Inventory

The Toxicological Prioritization Index (ToxPi) decision support framework was previously developed to facilitate incorporation of diverse data to prioritize chemicals based on potential hazard. This ToxPi index was demonstrated by considering results of bioprofiling related to po...

A Framework for Multi-Stakeholder Decision-Making and Conflict Resolution (abstract)

EPA Science Inventory

This contribution describes the implementation of the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. It is observed that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as ran...

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

EPA Science Inventory

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

DECISION-COMPONENTS OF NICE'S TECHNOLOGY APPRAISALS ASSESSMENT FRAMEWORK.

PubMed

de Folter, Joost; Trusheim, Mark; Jonsson, Pall; Garner, Sarah

2018-01-01

Value assessment frameworks have gained prominence recently in the context of U.S. healthcare. Such frameworks set out a series of factors that are considered in funding decisions. The UK's National Institute of Health and Care Excellence (NICE) is an established health technology assessment (HTA) agency. We present a novel application of text analysis that characterizes NICE's Technology Appraisals in the context of the newer assessment frameworks and present the results in a visual way. A total of 243 documents of NICE's medicines guidance from 2007 to 2016 were analyzed. Text analysis was used to identify a hierarchical set of decision factors considered in the assessments. The frequency of decision factors stated in the documents was determined and their association with terms related to uncertainty. The results were incorporated into visual representations of hierarchical factors. We identified 125 decision factors, and hierarchically grouped these into eight domains: Clinical Effectiveness, Cost Effectiveness, Condition, Current Practice, Clinical Need, New Treatment, Studies, and Other Factors. Textual analysis showed all domains appeared consistently in the guidance documents. Many factors were commonly associated with terms relating to uncertainty. A series of visual representations was created. This study reveals the complexity and consistency of NICE's decision-making processes and demonstrates that cost effectiveness is not the only decision-criteria. The study highlights the importance of processes and methodology that can take both quantitative and qualitative information into account. Visualizations can help effectively communicate this complex information during the decision-making process and subsequently to stakeholders.

Developing evidence that is fit for purpose: a framework for payer and research dialogue.

PubMed

Sabharwal, Rajeev K; Graff, Jennifer S; Holve, Erin; Dubois, Robert W

2015-09-01

Matching the supply and demand of evidence requires an understanding of when more evidence is needed, as well as the type of evidence that will meet this need. This article describes efforts to develop and refine a decision-making framework that considers payers' perspectives on the utility of evidence generated by different types of research methods, including real-world evidence. Conceptual framework development with subsequent testing during a roundtable dialogue. The framework development process included a literature scan to identify existing frameworks and relevant articles on payer decision making. The framework was refined during a stand-alone roundtable in December 2013 hosted by the research team, which included representatives from public and private payers, pharmacy benefit management, the life sciences industry, and researchers. The roundtable discussion also included an application of the framework to 3 case studies. Application of the framework to the clinical scenarios and the resulting discussion provided key insights into when new evidence is needed to inform payer decision making and what questions should be addressed. Payers are not necessarily seeking more evidence about treatment efficacy; rather, they are seeking more evidence for relevant end points that illustrate the differences between treatment alternatives that can justify the resources required to change practice. In addition, payers are interested in obtaining new evidence that goes beyond efficacy, with an emphasis on effectiveness, longer-term safety, and delivery system impact. We believe that our decision-making framework is a useful tool to increase dialogue between evidence generators and payers, while also allowing for greater efficiency in the research process.

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

PubMed

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

2018-01-01

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

Fews-Risk: A step towards risk-based flood forecasting

NASA Astrophysics Data System (ADS)

Bachmann, Daniel; Eilander, Dirk; de Leeuw, Annemargreet; Diermanse, Ferdinand; Weerts, Albrecht; de Bruijn, Karin; Beckers, Joost; Boelee, Leonore; Brown, Emma; Hazlewood, Caroline

2015-04-01

Operational flood prediction and the assessment of flood risk are important components of flood management. Currently, the model-based prediction of discharge and/or water level in a river is common practice for operational flood forecasting. Based on the prediction of these values decisions about specific emergency measures are made within operational flood management. However, the information provided for decision support is restricted to pure hydrological or hydraulic aspects of a flood. Information about weak sections within the flood defences, flood prone areas and assets at risk in the protected areas are rarely used in a model-based flood forecasting system. This information is often available for strategic planning, but is not in an appropriate format for operational purposes. The idea of FEWS-Risk is the extension of existing flood forecasting systems with elements of strategic flood risk analysis, such as probabilistic failure analysis, two dimensional flood spreading simulation and the analysis of flood impacts and consequences. Thus, additional information is provided to the decision makers, such as: • Location, timing and probability of failure of defined sections of the flood defence line; • Flood spreading, extent and hydraulic values in the hinterland caused by an overflow or a breach flow • Impacts and consequences in case of flooding in the protected areas, such as injuries or casualties and/or damages to critical infrastructure or economy. In contrast with purely hydraulic-based operational information, these additional data focus upon decision support for answering crucial questions within an operational flood forecasting framework, such as: • Where should I reinforce my flood defence system? • What type of action can I take to mend a weak spot in my flood defences? • What are the consequences of a breach? • Which areas should I evacuate first? This presentation outlines the additional required workflows towards risk-based flood forecasting systems. In a cooperation between HR Wallingford and Deltares, the extended workflows are being integrated into the Delft-FEWS software system. Delft-FEWS provides modules for managing the data handling and forecasting process. Results of a pilot study that demonstrates the new tools are presented. The value of the newly generated information for decision support during a flood event is discussed.

An international comparison of legal frameworks for supported and substitute decision-making in mental health services.

PubMed

Davidson, Gavin; Brophy, Lisa; Campbell, Jim; Farrell, Susan J; Gooding, Piers; O'Brien, Ann-Marie

2016-01-01

There have been important recent developments in law, research, policy and practice relating to supporting people with decision-making impairments, in particular when a person's wishes and preferences are unclear or inaccessible. A driver in this respect is the United Nations Convention on the Rights of Persons with Disabilities (CRPD); the implications of the CRPD for policy and professional practices are currently debated. This article reviews and compares four legal frameworks for supported and substitute decision-making for people whose decision-making ability is impaired. In particular, it explores how these frameworks may apply to people with mental health problems. The four jurisdictions are: Ontario, Canada; Victoria, Australia; England and Wales, United Kingdom (UK); and Northern Ireland, UK. Comparisons and contrasts are made in the key areas of: the legal framework for supported and substitute decision-making; the criteria for intervention; the assessment process; the safeguards; and issues in practice. Thus Ontario has developed a relatively comprehensive, progressive and influential legal framework over the past 30 years but there remain concerns about the standardisation of decision-making ability assessments and how the laws work together. In Australia, the Victorian Law Reform Commission (2012) has recommended that the six different types of substitute decision-making under the three laws in that jurisdiction, need to be simplified, and integrated into a spectrum that includes supported decision-making. In England and Wales the Mental Capacity Act 2005 has a complex interface with mental health law. In Northern Ireland it is proposed to introduce a new Mental Capacity (Health, Welfare and Finance) Bill that will provide a unified structure for all substitute decision-making. The discussion will consider the key strengths and limitations of the approaches in each jurisdiction and identify possible ways that further progress can be made in law, policy and practice. Copyright © 2015 Elsevier Ltd. All rights reserved.

PubMed Central

Weeks, Laura; Balneaves, Lynda G; Paterson, Charlotte

2014-01-01

Background: Patients with cancer consistently report conflict and anxiety when making decisions about complementary and alternative medicine (CAM) treatment. To design evidence-informed decision-support strategies, a better understanding is needed of how the decision-making process unfolds for these patients during their experience with cancer. We undertook this study to review the research literature regarding CAM-related decisionmaking by patients with cancer within the context of treatment, survivorship, and palliation. We also aimed to summarize emergent concepts within a preliminary conceptual framework. Methods: We conducted an integrative literature review, searching 12 electronic databases for articles published in English that described studies of the process, context, or outcomes of CAM-related decision-making. We summarized descriptive data using frequencies and used a descriptive constant comparative method to analyze statements about original qualitative results, with the goal of identifying distinct concepts pertaining to CAM-related decision-making by patients with cancer and the relationships among these concepts. Results: Of 425 articles initially identified, 35 met our inclusion criteria. Seven unique concepts related to CAM and cancer decision-making emerged: decision-making phases, information-seeking and evaluation, decision-making roles, beliefs, contextual factors, decision-making outcomes, and the relationship between CAM and conventional medical decision-making. CAM decision-making begins with the diagnosis of cancer and encompasses 3 distinct phases (early, mid, and late), each marked by unique aims for CAM treatment and distinct patterns of informationseeking and evaluation. Phase transitions correspond to changes in health status or other milestones within the cancer trajectory. An emergent conceptual framework illustrating relationships among the 7 central concepts is presented. Interpretation: CAM-related decision-making by patients with cancer occurs as a nonlinear, complex, dynamic process. The conceptual framework presented here identifies influential factors within that process, as well as patients' unique needs during different phases. The framework can guide the development and evaluation of theorybased decision-support programs that are responsive to patients' beliefs and preferences. PMID:25009685

Developing a clinical utility framework to evaluate prediction models in radiogenomics

NASA Astrophysics Data System (ADS)

Wu, Yirong; Liu, Jie; Munoz del Rio, Alejandro; Page, David C.; Alagoz, Oguzhan; Peissig, Peggy; Onitilo, Adedayo A.; Burnside, Elizabeth S.

2015-03-01

Combining imaging and genetic information to predict disease presence and behavior is being codified into an emerging discipline called "radiogenomics." Optimal evaluation methodologies for radiogenomics techniques have not been established. We aim to develop a clinical decision framework based on utility analysis to assess prediction models for breast cancer. Our data comes from a retrospective case-control study, collecting Gail model risk factors, genetic variants (single nucleotide polymorphisms-SNPs), and mammographic features in Breast Imaging Reporting and Data System (BI-RADS) lexicon. We first constructed three logistic regression models built on different sets of predictive features: (1) Gail, (2) Gail+SNP, and (3) Gail+SNP+BI-RADS. Then, we generated ROC curves for three models. After we assigned utility values for each category of findings (true negative, false positive, false negative and true positive), we pursued optimal operating points on ROC curves to achieve maximum expected utility (MEU) of breast cancer diagnosis. We used McNemar's test to compare the predictive performance of the three models. We found that SNPs and BI-RADS features augmented the baseline Gail model in terms of the area under ROC curve (AUC) and MEU. SNPs improved sensitivity of the Gail model (0.276 vs. 0.147) and reduced specificity (0.855 vs. 0.912). When additional mammographic features were added, sensitivity increased to 0.457 and specificity to 0.872. SNPs and mammographic features played a significant role in breast cancer risk estimation (p-value < 0.001). Our decision framework comprising utility analysis and McNemar's test provides a novel framework to evaluate prediction models in the realm of radiogenomics.

Optimizing Negotiation Conflict in the Cloud Service Negotiation Framework Using Probabilistic Decision Making Model

PubMed Central

Rajavel, Rajkumar; Thangarathinam, Mala

2015-01-01

Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework. PMID:26543899

Optimizing Negotiation Conflict in the Cloud Service Negotiation Framework Using Probabilistic Decision Making Model.

PubMed

Rajavel, Rajkumar; Thangarathinam, Mala

2015-01-01

Optimization of negotiation conflict in the cloud service negotiation framework is identified as one of the major challenging issues. This negotiation conflict occurs during the bilateral negotiation process between the participants due to the misperception, aggressive behavior, and uncertain preferences and goals about their opponents. Existing research work focuses on the prerequest context of negotiation conflict optimization by grouping similar negotiation pairs using distance, binary, context-dependent, and fuzzy similarity approaches. For some extent, these approaches can maximize the success rate and minimize the communication overhead among the participants. To further optimize the success rate and communication overhead, the proposed research work introduces a novel probabilistic decision making model for optimizing the negotiation conflict in the long-term negotiation context. This decision model formulates the problem of managing different types of negotiation conflict that occurs during negotiation process as a multistage Markov decision problem. At each stage of negotiation process, the proposed decision model generates the heuristic decision based on the past negotiation state information without causing any break-off among the participants. In addition, this heuristic decision using the stochastic decision tree scenario can maximize the revenue among the participants available in the cloud service negotiation framework.

Controlling Methane Emissions in the Natural Gas Sector. A Review of Federal and State Regulatory Frameworks Governing Production, Gathering, Processing, Transmission, and Distribution

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

Paranhos, Elizabeth; Kozak, Tracy G.; Boyd, William

This report provides an overview of the regulatory frameworks governing natural gas supply chain infrastructure siting, construction, operation, and maintenance. Information was drawn from a number of sources, including published analyses, government reports, in addition to relevant statutes, court decisions and regulatory language, as needed. The scope includes all onshore facilities that contribute to methane emissions from the natural gas sector, focusing on three areas of state and federal regulations: (1) natural gas pipeline infrastructure siting and transportation service (including gathering, transmission, and distribution pipelines), (2) natural gas pipeline safety, and (3) air emissions associated with the natural gas supplymore » chain. In addition, the report identifies the incentives under current regulatory frameworks to invest in measures to reduce leakage, as well as the barriers facing investment in infrastructure improvement to reduce leakage. Policy recommendations regarding how federal or state authorities could regulate methane emissions are not provided; rather, existing frameworks are identified and some of the options for modifying existing regulations or adopting new regulations to reduce methane leakage are discussed.« less

Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group.

PubMed

Buehler, James W; Hopkins, Richard S; Overhage, J Marc; Sosin, Daniel M; Tong, Van

2004-05-07

The threat of terrorism and high-profile disease outbreaks has drawn attention to public health surveillance systems for early detection of outbreaks. State and local health departments are enhancing existing surveillance systems and developing new systems to better detect outbreaks through public health surveillance. However, information is limited about the usefulness of surveillance systems for outbreak detection or the best ways to support this function. This report supplements previous guidelines for evaluating public health surveillance systems. Use of this framework is intended to improve decision-making regarding the implementation of surveillance for outbreak detection. Use of a standardized evaluation methodology, including description of system design and operation, also will enhance the exchange of information regarding methods to improve early detection of outbreaks. The framework directs particular attention to the measurement of timeliness and validity for outbreak detection. The evaluation framework is designed to support assessment and description of all surveillance approaches to early detection, whether through traditional disease reporting, specialized analytic routines for aberration detection, or surveillance using early indicators of disease outbreaks, such as syndromic surveillance.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Working memory retrieval as a decision process

PubMed Central

Pearson, Benjamin; Raškevičius, Julius; Bays, Paul M.; Pertzov, Yoni; Husain, Masud

2014-01-01

Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation. PMID:24492597

Benchmarking of Decision-Support Tools Used for Tiered Sustainable Remediation Appraisal.

PubMed

Smith, Jonathan W N; Kerrison, Gavin

2013-01-01

Sustainable remediation comprises soil and groundwater risk-management actions that are selected, designed, and operated to maximize net environmental, social, and economic benefit (while assuring protection of human health and safety). This paper describes a benchmarking exercise to comparatively assess potential differences in environmental management decision making resulting from application of different sustainability appraisal tools ranging from simple (qualitative) to more quantitative (multi-criteria and fully monetized cost-benefit analysis), as outlined in the SuRF-UK framework. The appraisal tools were used to rank remedial options for risk management of a subsurface petroleum release that occurred at a petrol filling station in central England. The remediation options were benchmarked using a consistent set of soil and groundwater data for each tier of sustainability appraisal. The ranking of remedial options was very similar in all three tiers, and an environmental management decision to select the most sustainable options at tier 1 would have been the same decision at tiers 2 and 3. The exercise showed that, for relatively simple remediation projects, a simple sustainability appraisal led to the same remediation option selection as more complex appraisal, and can be used to reliably inform environmental management decisions on other relatively simple land contamination projects.

Working memory retrieval as a decision process.

PubMed

Pearson, Benjamin; Raskevicius, Julius; Bays, Paul M; Pertzov, Yoni; Husain, Masud

2014-02-03

Working memory (WM) is a core cognitive process fundamental to human behavior, yet the mechanisms underlying it remain highly controversial. Here we provide a new framework for understanding retrieval of information from WM, conceptualizing it as a decision based on the quality of internal evidence. Recent findings have demonstrated that precision of WM decreases with memory load. If WM retrieval uses a decision process that depends on memory quality, systematic changes in response time distribution should occur as a function of WM precision. We asked participants to view sample arrays and, after a delay, report the direction of change in location or orientation of a probe. As WM precision deteriorated with increasing memory load, retrieval time increased systematically. Crucially, the shape of reaction time distributions was consistent with a linear accumulator decision process. Varying either task relevance of items or maintenance duration influenced memory precision, with corresponding shifts in retrieval time. These results provide strong support for a decision-making account of WM retrieval based on noisy storage of items. Furthermore, they show that encoding, maintenance, and retrieval in WM need not be considered as separate processes, but may instead be conceptually unified as operations on the same noise-limited, neural representation.

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

PubMed

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

2010-11-15

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

PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

NASA Astrophysics Data System (ADS)

Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

2018-03-01

Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

Using structured decision making to manage disease risk for Montana wildlife

USGS Publications Warehouse

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

2013-01-01

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

GLIMPSE: a rapid decision framework for energy and environmental policy

EPA Science Inventory

Over the coming decades, new energy production technologies and the policies that oversee them will affect human health, the vitality of our ecosystems, and the stability of the global climate. The GLIMPSE decision model framework provides insights about the implications of techn...

Effect of Wind Farm Noise on Local Residents’ Decision to Adopt Mitigation Measures

PubMed Central

Botelho, Anabela; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M. Costa

2017-01-01

Wind turbines’ noise is frequently pointed out as the reason for local communities’ objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes’ noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people’s decision to adopt mitigating measures, independently of the reported annoyance. PMID:28696404

A rational framework for production decision making in blood establishments.

PubMed

Ramoa, Augusto; Maia, Salomé; Lourenço, Anália

2012-07-24

SAD_BaSe is a blood bank data analysis software, created to assist in the management of blood donations and the blood production chain in blood establishments. In particular, the system keeps track of several collection and production indicators, enables the definition of collection and production strategies, and the measurement of quality indicators required by the Quality Management System regulating the general operation of blood establishments. This paper describes the general scenario of blood establishments and its main requirements in terms of data management and analysis. It presents the architecture of SAD_BaSe and identifies its main contributions. Specifically, it brings forward the generation of customized reports driven by decision making needs and the use of data mining techniques in the analysis of donor suspensions and donation discards.

A Rational Framework for Production Decision Making in Blood Establishments.

PubMed

Ramoa, Augusto; Maia, Salomé; Lourenço, Anália

2012-12-01

SAD_BaSe is a blood bank data analysis software, created to assist in the management of blood donations and the blood production chain in blood establishments. In particular, the system keeps track of several collection and production indicators, enables the definition of collection and production strategies, and the measurement of quality indicators required by the Quality Management System regulating the general operation of blood establishments. This paper describes the general scenario of blood establishments and its main requirements in terms of data management and analysis. It presents the architecture of SAD_BaSe and identifies its main contributions. Specifically, it brings forward the generation of customized reports driven by decision making needs and the use of data mining techniques in the analysis of donor suspensions and donation discards.

Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems

PubMed Central

Menychtas, Andreas; Tsanakas, Panayiotis

2016-01-01

The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging. PMID:27222731

Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems.

PubMed

Menychtas, Andreas; Tsanakas, Panayiotis; Maglogiannis, Ilias

2016-03-01

The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging.

A Systems-Based Conceptual Framework for Assessing the Determinants of a Social License to Operate in the Mining Industry

NASA Astrophysics Data System (ADS)

Prno, Jason; Slocombe, D. Scott

2014-03-01

The concept of a "social license to operate" (SLO) was coined in the 1990s and gained popularity as one way in which "social" considerations can be addressed in mineral development decision making. The need for a SLO implies that developers require the widespread approval of local community members for their projects to avoid exposure to potentially costly conflict and business risks. Only a limited amount of scholarship exists on the topic, and there is a need for research that specifically addresses the complex and changeable nature of SLO outcomes. In response to these challenges, this paper advances a novel, systems-based conceptual framework for assessing SLO determinants and outcomes in the mining industry. Two strands of systems theory are specifically highlighted—complex adaptive systems and resilience—and the roles of context, key system variables, emergence, change, uncertainty, feedbacks, cross-scale effects, multiple stable states, thresholds, and resilience are discussed. The framework was developed from the results of a multi-year research project which involved international mining case study investigations, a comprehensive literature review, and interviews conducted with mining stakeholders and observers. The framework can help guide SLO analysis and management efforts, by encouraging users to account for important contextual and complexity-oriented elements present in SLO settings. We apply the framework to a case study in Alaska, USA before discussing its merits and challenges. We also illustrate knowledge gaps associated with applications of complex adaptive systems and resilience theories to the study of SLO dynamics, and discuss opportunities for future research.

A systems-based conceptual framework for assessing the determinants of a social license to operate in the mining industry.

PubMed

Prno, Jason; Slocombe, D Scott

2014-03-01

The concept of a "social license to operate" (SLO) was coined in the 1990s and gained popularity as one way in which "social" considerations can be addressed in mineral development decision making. The need for a SLO implies that developers require the widespread approval of local community members for their projects to avoid exposure to potentially costly conflict and business risks. Only a limited amount of scholarship exists on the topic, and there is a need for research that specifically addresses the complex and changeable nature of SLO outcomes. In response to these challenges, this paper advances a novel, systems-based conceptual framework for assessing SLO determinants and outcomes in the mining industry. Two strands of systems theory are specifically highlighted-complex adaptive systems and resilience-and the roles of context, key system variables, emergence, change, uncertainty, feedbacks, cross-scale effects, multiple stable states, thresholds, and resilience are discussed. The framework was developed from the results of a multi-year research project which involved international mining case study investigations, a comprehensive literature review, and interviews conducted with mining stakeholders and observers. The framework can help guide SLO analysis and management efforts, by encouraging users to account for important contextual and complexity-oriented elements present in SLO settings. We apply the framework to a case study in Alaska, USA before discussing its merits and challenges. We also illustrate knowledge gaps associated with applications of complex adaptive systems and resilience theories to the study of SLO dynamics, and discuss opportunities for future research.

A conceptual framework for dynamic extension of the red clearance interval as a countermeasure for red-light-running.

PubMed

Gates, Timothy J; Noyce, David A

2016-11-01

This manuscript describes the development and evaluation of a conceptual framework for real-time operation of dynamic on-demand extension of the red clearance interval as a countermeasure for red-light-running. The framework includes a decision process for determining, based on the real-time status of vehicles arriving at the intersection, when extension of the red clearance interval should occur and the duration of each extension. A zonal classification scheme was devised to assess whether an approaching vehicle requires additional time to safely clear the intersection based on the remaining phase time, type of vehicle, current speed, and current distance from the intersection. Expected performance of the conceptual framework was evaluated through modeling of replicated field operations using vehicular event data collected as part of this research. The results showed highly accurate classification of red-light-running vehicles needing additional clearance time and relatively few false extension calls from stopping vehicles, thereby minimizing the expected impacts to signal and traffic operations. Based on the recommended parameters, extension calls were predicted to occur once every 26.5cycles. Assuming a 90scycle, 1.5 extensions per hour were expected per approach, with an estimated extension time of 2.30s/h. Although field implementation was not performed, it is anticipated that long-term reductions in targeted red-light-running conflicts and crashes will likely occur if red clearance interval extension systems are implemented at locations where start-up delay on the conflicting approach is generally minimal, such as intersections with lag left-turn phasing. Copyright © 2015 Elsevier Ltd. All rights reserved.

An open source hydroeconomic model for California's water supply system: PyVIN

NASA Astrophysics Data System (ADS)

Dogan, M. S.; White, E.; Herman, J. D.; Hart, Q.; Merz, J.; Medellin-Azuara, J.; Lund, J. R.

2016-12-01

Models help operators and decision makers explore and compare different management and policy alternatives, better allocate scarce resources, and predict the future behavior of existing or proposed water systems. Hydroeconomic models are useful tools to increase benefits or decrease costs of managing water. Bringing hydrology and economics together, these models provide a framework for different disciplines that share similar objectives. This work proposes a new model to evaluate operation and adaptation strategies under existing and future hydrologic conditions for California's interconnected water system. This model combines the network structure of CALVIN, a statewide optimization model for California's water infrastructure, along with an open source solver written in the Python programming language. With the flexibilities of the model, reservoir operations, including water supply and hydropower, groundwater pumping, and the Delta water operations and requirements can now be better represented. Given time series of hydrologic inputs to the model, typical outputs include urban, agricultural and wildlife refuge water deliveries and shortage costs, conjunctive use of surface and groundwater systems, and insights into policy and management decisions, such as capacity expansion and groundwater management policies. Water market operations also represented in the model, allocating water from lower-valued users to higher-valued users. PyVIN serves as a cross-platform, extensible model to evaluate systemwide water operations. PyVIN separates data from the model structure, enabling model to be easily applied to other parts of the world where water is a scarce resource.

Understanding the Role of Numeracy in Health: Proposed Theoretical Framework and Practical Insights

PubMed Central

Lipkus, Isaac M.; Peters, Ellen

2009-01-01

Numeracy, that is how facile people are with mathematical concepts and their applications, is gaining importance in medical decision making and risk communication. This paper proposes six critical functions of health numeracy. These functions are integrated into a theoretical framework on health numeracy that has implications for risk-communication and medical-decision-making processes. We examine practical underpinnings for targeted interventions aimed at improving such processes as a function of health numeracy. It is hoped that the proposed functions and theoretical framework will spur more research to determine how an understanding of health numeracy can lead to more effective communication and decision outcomes. PMID:19834054

A Mixed Integer Efficient Global Optimization Framework: Applied to the Simultaneous Aircraft Design, Airline Allocation and Revenue Management Problem

NASA Astrophysics Data System (ADS)

Roy, Satadru

Traditional approaches to design and optimize a new system, often, use a system-centric objective and do not take into consideration how the operator will use this new system alongside of other existing systems. This "hand-off" between the design of the new system and how the new system operates alongside other systems might lead to a sub-optimal performance with respect to the operator-level objective. In other words, the system that is optimal for its system-level objective might not be best for the system-of-systems level objective of the operator. Among the few available references that describe attempts to address this hand-off, most follow an MDO-motivated subspace decomposition approach of first designing a very good system and then provide this system to the operator who decides the best way to use this new system along with the existing systems. The motivating example in this dissertation presents one such similar problem that includes aircraft design, airline operations and revenue management "subspaces". The research here develops an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem. The monolithic approach makes the problem a Mixed Integer/Discrete Non-Linear Programming (MINLP/MDNLP) problem, which are extremely difficult to solve. The presence of expensive, sophisticated engineering analyses further aggravate the problem. To tackle this challenge problem, the work here presents a new optimization framework that simultaneously solves the subspaces to capture the "synergism" in the problem that the previous decomposition approaches may not have exploited, addresses mixed-integer/discrete type design variables in an efficient manner, and accounts for computationally expensive analysis tools. The framework combines concepts from efficient global optimization, Kriging partial least squares, and gradient-based optimization. This approach then demonstrates its ability to solve an 11 route airline network problem consisting of 94 decision variables including 33 integer and 61 continuous type variables. This application problem is a representation of an interacting group of systems and provides key challenges to the optimization framework to solve the MINLP problem, as reflected by the presence of a moderate number of integer and continuous type design variables and expensive analysis tool. The result indicates simultaneously solving the subspaces could lead to significant improvement in the fleet-level objective of the airline when compared to the previously developed sequential subspace decomposition approach. In developing the approach to solve the MINLP/MDNLP challenge problem, several test problems provided the ability to explore performance of the framework. While solving these test problems, the framework showed that it could solve other MDNLP problems including categorically discrete variables, indicating that the framework could have broader application than the new aircraft design-fleet allocation-revenue management problem.

Policy Tree Optimization for Adaptive Management of Water Resources Systems

NASA Astrophysics Data System (ADS)

Herman, J. D.; Giuliani, M.

2016-12-01

Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points", which are threshold values of indicator variables that signal a change in policy. However, there remains a need for a general method to optimize the choice of indicators and their threshold values in a way that is easily interpretable for decision makers. Here we propose a conceptual framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. We demonstrate the approach using Folsom Reservoir, California as a case study, in which operating policies must balance the risk of both floods and droughts. Given a set of feature variables, such as reservoir level, inflow observations and forecasts, and time of year, the resulting policy defines the conditions under which flood control and water supply hedging operations should be triggered. Importantly, the tree-based rule sets are easy to interpret for decision making, and can be compared to historical operating policies to understand the adaptations needed under possible climate change scenarios. Several remaining challenges are discussed, including the empirical convergence properties of the method, and extensions to irreversible decisions such as infrastructure. Policy tree optimization, and corresponding open-source software, provide a generalizable, interpretable approach to designing adaptive policies under uncertainty for water resources systems.

To t-Test or Not to t-Test? A p-Values-Based Point of View in the Receiver Operating Characteristic Curve Framework.

PubMed

Vexler, Albert; Yu, Jihnhee

2018-04-13

A common statistical doctrine supported by many introductory courses and textbooks is that t-test type procedures based on normally distributed data points are anticipated to provide a standard in decision-making. In order to motivate scholars to examine this convention, we introduce a simple approach based on graphical tools of receiver operating characteristic (ROC) curve analysis, a well-established biostatistical methodology. In this context, we propose employing a p-values-based method, taking into account the stochastic nature of p-values. We focus on the modern statistical literature to address the expected p-value (EPV) as a measure of the performance of decision-making rules. During the course of our study, we extend the EPV concept to be considered in terms of the ROC curve technique. This provides expressive evaluations and visualizations of a wide spectrum of testing mechanisms' properties. We show that the conventional power characterization of tests is a partial aspect of the presented EPV/ROC technique. We desire that this explanation of the EPV/ROC approach convinces researchers of the usefulness of the EPV/ROC approach for depicting different characteristics of decision-making procedures, in light of the growing interest regarding correct p-values-based applications.

FRAMEWORK FOR RESPONSIBLE ENVIRONMENTAL DECISION-MAKING (FRED): USING LIFE CYCLE ASSESSMENT TO EVALUATE PREFERABILITY OF PRODUCTS

EPA Science Inventory

Framework for Responsible Environmental Decision-Making (FRED) demonstrates how the life-cycle concept can be used to quantify competing products' environmental performance so that this information may be integrated with considerations of total ownership cost and technical perfor...

Explicating Individual Training Decisions

ERIC Educational Resources Information Center

Walter, Marcel; Mueller, Normann

2015-01-01

In this paper, we explicate individual training decisions. For this purpose, we propose a framework based on instrumentality theory, a psychological theory of motivation that has frequently been applied to individual occupational behavior. To test this framework, we employ novel German individual data and estimate the effect of subjective expected…

A hierarchical-multiobjective framework for risk management

NASA Technical Reports Server (NTRS)

Haimes, Yacov Y.; Li, Duan

1991-01-01

A broad hierarchical-multiobjective framework is established and utilized to methodologically address the management of risk. United into the framework are the hierarchical character of decision-making, the multiple decision-makers at separate levels within the hierarchy, the multiobjective character of large-scale systems, the quantitative/empirical aspects, and the qualitative/normative/judgmental aspects. The methodological components essentially consist of hierarchical-multiobjective coordination, risk of extreme events, and impact analysis. Examples of applications of the framework are presented. It is concluded that complex and interrelated forces require an analysis of trade-offs between engineering analysis and societal preferences, as in the hierarchical-multiobjective framework, to successfully address inherent risk.

Helping Health Care Providers and Clinical Scientists Understand Apparently Irrational Policy Decisions.

PubMed

Demeter, Sandor J

2016-12-21

Health care providers (HCP) and clinical scientists (CS) are generally most comfortable using evidence-based rational decision-making models. They become very frustrated when policymakers make decisions that, on the surface, seem irrational and unreasonable. However, such decisions usually make sense when analysed properly. The goal of this paper to provide a basic theoretical understanding of major policy models, to illustrate which models are most prevalent in publicly funded health care systems, and to propose a policy analysis framework to better understand the elements that drive policy decision-making. The proposed policy framework will also assist HCP and CS achieve greater success with their own proposals.

A Framework for Sexual Decision-Making Among Female Sex Workers in Jamaica.

PubMed

Bailey, Althea; Figueroa, J Peter

2016-05-01

The Jamaican government has provided targeted HIV and sexually transmitted infection prevention, treatment, and other services for female sex workers (FSW) since 1989. HIV prevalence among FSW declined from 20 to 12% between 1989 and 1994, then to 9% in 2005, 5% in 2008, and 4.1% in 2011. This article distills the literature and two decades of experience working with FSW in Jamaica. Drawing on the constant comparative method, we put forward an innovative conceptual framework for explaining sexual decision-making and risk behaviors within both transactional and relational sexual situations. This framework helps fill the gaps in existing models that focus on individual behaviors. The model identifies interactions between environmental and structural elements of sex work, and three individual-level factors: risk perception, perceived relationship intimacy, and perceived control, as the four primary mediating factors influencing sexual decision-making among FSW. We propose that other factors such as violence, socioeconomic vulnerability, and policy/legal frameworks influence sexual decision-making through these primary mediating factors. This conceptual model may offer a useful framework for planning and evaluating prevention interventions among sex workers. However, it remains to be tested in order to establish its value.

A Framework for Multi-Stakeholder Decision-Making and ...

EPA Pesticide Factsheets

This contribution describes the implementation of the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. It is observed that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as random variables. We thus shape the dissatisfaction distribution and find an optimal compromise solution by solving a CVaR minimization problem parameterized in the probability level. This enables us to generalize multi-stakeholder settings previously proposed in the literature that minimizes 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. We demonstrate the framework in a bio-waste processing facility location case study, where we seek compromise solutions (facility locations) that balance stakeholder priorities on transportation, safety, water quality, and capital costs. This conference presentation abstract explains a new decision-making framework that computes compromise solution alternatives (reach consensus) by mitigating dissatisfactions among stakeholders as needed for SHC Decision Science and Support Tools project.

On Developing a Taxonomy for Multidisciplinary Design Optimization: A Decision-Based Perspective

NASA Technical Reports Server (NTRS)

Lewis, Kemper; Mistree, Farrokh

1995-01-01

In this paper, we approach MDO from a Decision-Based Design (DBD) perspective and explore classification schemes for designing complex systems and processes. Specifically, we focus on decisions, which are only a small portion of the Decision Support Problem (DSP) Technique, our implementation of DBD. We map coupled nonhierarchical and hierarchical representations from the DSP Technique into the Balling-Sobieski (B-S) framework (Balling and Sobieszczanski-Sobieski, 1994), and integrate domain-independent linguistic terms to complete our taxonomy. Application of DSPs to the design of complex, multidisciplinary systems include passenger aircraft, ships, damage tolerant structural and mechanical systems, and thermal energy systems. In this paper we show that Balling-Sobieski framework is consistent with that of the Decision Support Problem Technique through the use of linguistic entities to describe the same type of formulations. We show that the underlying linguistics of the solution approaches are the same and can be coalesced into a homogeneous framework with which to base the research, application, and technology MDO upon. We introduce, in the Balling-Sobieski framework, examples of multidisciplinary design, namely, aircraft, damage tolerant structural and mechanical systems, and thermal energy systems.

History matching through dynamic decision-making

PubMed Central

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

2017-01-01

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

Bayesian inference and decision theory - A framework for decision making in natural resource management

USGS Publications Warehouse

Dorazio, R.M.; Johnson, F.A.

2003-01-01

Bayesian inference and decision theory may be used in the solution of relatively complex problems of natural resource management, owing to recent advances in statistical theory and computing. In particular, Markov chain Monte Carlo algorithms provide a computational framework for fitting models of adequate complexity and for evaluating the expected consequences of alternative management actions. We illustrate these features using an example based on management of waterfowl habitat.

How does network design constrain optimal operation of intermittent water supply?

NASA Astrophysics Data System (ADS)

Lieb, Anna; Wilkening, Jon; Rycroft, Chris

2015-11-01

Urban water distribution systems do not always supply water continuously or reliably. As pipes fill and empty, pressure transients may contribute to degraded infrastructure and poor water quality. To help understand and manage this undesirable side effect of intermittent water supply--a phenomenon affecting hundreds of millions of people in cities around the world--we study the relative contributions of fixed versus dynamic properties of the network. Using a dynamical model of unsteady transition pipe flow, we study how different elements of network design, such as network geometry, pipe material, and pipe slope, contribute to undesirable pressure transients. Using an optimization framework, we then investigate to what extent network operation decisions such as supply timing and inflow rate may mitigate these effects. We characterize some aspects of network design that make them more or less amenable to operational optimization.

Coupling socioeconomic and lake systems for sustainability: a conceptual analysis using Lake St. Clair region as a case study.

PubMed

Mavrommati, Georgia; Baustian, Melissa M; Dreelin, Erin A

2014-04-01

Applying sustainability at an operational level requires understanding the linkages between socioeconomic and natural systems. We identified linkages in a case study of the Lake St. Clair (LSC) region, part of the Laurentian Great Lakes system. Our research phases included: (1) investigating and revising existing coupled human and natural systems frameworks to develop a framework for this case study; (2) testing and refining the framework by hosting a 1-day stakeholder workshop and (3) creating a causal loop diagram (CLD) to illustrate the relationships among the systems' key components. With stakeholder assistance, we identified four interrelated pathways that include water use and discharge, land use, tourism and shipping that impact the ecological condition of LSC. The interrelationships between the pathways of water use and tourism are further illustrated by a CLD with several feedback loops. We suggest that this holistic approach can be applied to other case studies and inspire the development of dynamic models capable of informing decision making for sustainability.

A Framework for Web Usage Mining in Electronic Government

NASA Astrophysics Data System (ADS)

Zhou, Ping; Le, Zhongjian

Web usage mining has been a major component of management strategy to enhance organizational analysis and decision. The literature on Web usage mining that deals with strategies and technologies for effectively employing Web usage mining is quite vast. In recent years, E-government has received much attention from researchers and practitioners. Huge amounts of user access data are produced in Electronic government Web site everyday. The role of these data in the success of government management cannot be overstated because they affect government analysis, prediction, strategies, tactical, operational planning and control. Web usage miming in E-government has an important role to play in setting government objectives, discovering citizen behavior, and determining future courses of actions. Web usage mining in E-government has not received adequate attention from researchers or practitioners. We developed a framework to promote a better understanding of the importance of Web usage mining in E-government. Using the current literature, we developed the framework presented herein, in hopes that it would stimulate more interest in this important area.

Human Exploration Framework Team: Strategy and Status

NASA Technical Reports Server (NTRS)

Muirhead, Brian K.; Sherwood, Brent; Olson, John

2011-01-01

Human Exploration Framework Team (HEFT) was formulated to create a decision framework for human space exploration that drives out the knowledge, capabilities and infrastructure NASA needs to send people to explore multiple destinations in the Solar System in an efficient, sustainable way. The specific goal is to generate an initial architecture that can evolve into a long term, enterprise-wide architecture that is the basis for a robust human space flight enterprise. This paper will discuss the initial HEFT activity which focused on starting up the cross-agency team, getting it functioning, developing a comprehensive development and analysis process and conducting multiple iterations of the process. The outcome of this process will be discussed including initial analysis of capabilities and missions for at least two decades, keeping Mars as the ultimate destination. Details are provided on strategies that span a broad technical and programmatic trade space, are analyzed against design reference missions and evaluated against a broad set of figures of merit including affordability, operational complexity, and technical and programmatic risk.

A multidisciplinary decision support system for forest fire crisis management.

PubMed

Keramitsoglou, Iphigenia; Kiranoudis, Chris T; Sarimveis, Haralambos; Sifakis, Nicolaos

2004-02-01

A wildland fire is a serious threat for forest ecosystems in Southern Europe affecting severely and irreversibly regions of significant ecological value as well as human communities. To support decision makers during large-scale forest fire incidents, a multidisciplinary system has been developed that provides rational and quantitative information based on the site-specific circumstances and the possible consequences. The system's architecture consists of several distinct supplementary modules of near real-time satellite monitoring and fire forecast using an integrated framework of satellite Remote Sensing, GIS, and RDBMS technologies equipped with interactive communication capabilities. The system may handle multiple fire ignitions and support decisions regarding dispatching of utilities, equipment, and personnel that would appropriately attack the fire front. The operational system was developed for the region of Penteli Mountain in Attika, Greece, one of the mountain areas in the country most hit by fires. Starting from a real fire incident in August 2000, a scenario is presented to illustrate the effectiveness of the proposed approach.

Ontology-Based Gap Analysis for Technology Selection: A Knowledge Management Framework for the Support of Equipment Purchasing Processes

NASA Astrophysics Data System (ADS)

Macris, Aristomenis M.; Georgakellos, Dimitrios A.

Technology selection decisions such as equipment purchasing and supplier selection are decisions of strategic importance to companies. The nature of these decisions usually is complex, unstructured and thus, difficult to be captured in a way that will be efficiently reusable. Knowledge reusability is of paramount importance since it enables users participate actively in process design/redesign activities stimulated by the changing technology selection environment. This paper addresses the technology selection problem through an ontology-based approach that captures and makes reusable the equipment purchasing process and assists in identifying (a) the specifications requested by the users' organization, (b) those offered by various candidate vendors' organizations and (c) in performing specifications gap analysis as a prerequisite for effective and efficient technology selection. This approach has practical appeal, operational simplicity, and the potential for both immediate and long-term strategic impact. An example from the iron and steel industry is also presented to illustrate the approach.

Web Tutorials on Systems Thinking Using the Driver-Pressure-State-Impact-Response (DPSIR) Framework

EPA Science Inventory

This set of tutorials provides an overview of incorporating systems thinking into decision-making, an introduction to the DPSIR framework as one approach that can assist in the decision analysis process, and an overview of DPSIR tools, including concept mapping and keyword lists,...

Channeling the Innovation Stream: A Decision Framework for Selecting Emerging Technologies

ERIC Educational Resources Information Center

Sauer, Philip S.

2010-01-01

The proliferation of emerging technologies offers opportunity but also presents challenges to defense acquisition decision makers seeking to incorporate those technologies as part of the acquisition process. Assessment frameworks and methodologies found in the literature typically address the primary focus of a sponsoring organization's interest…

DEVELOPING A CONSISTENT DECISION-MAKING FRAMEWORK BY USING THE U.S. EPA'S TRACI

EPA Science Inventory

The most effective way to achieve long-term environmental results is through the use of a consistent set of metrics and decision-making framework. The U.S. EPA has developed TRACI, the Tool for the Reduction and Assessment of Chemical and other environmental Impacts, which allows...

Evaluating Academic Journals without Impact Factors for Collection Management Decisions.

ERIC Educational Resources Information Center

Dilevko, Juris; Atkinson, Esther

2002-01-01

Discussion of evaluating academic journals for collection management decisions focuses on a methodological framework for evaluating journals not ranked by impact factors in Journal Citation Reports. Compares nonranked journals with ranked journals and then applies this framework to a case study in the field of medical science. (LRW)

Using TPACK as a Framework to Understand Teacher Candidates' Technology Integration Decisions

ERIC Educational Resources Information Center

Graham, C. R.; Borup, J.; Smith, N. B.

2012-01-01

This research uses the technological pedagogical and content knowledge (TPACK) framework as a lens for understanding how teacher candidates make decisions about the use of information and communication technology in their teaching. Pre- and post-treatment assessments required elementary teacher candidates at Brigham Young University to articulate…

Implicit Theoretical Leadership Frameworks of Higher Education Administrators.

ERIC Educational Resources Information Center

Lees, Kimberly; And Others

Colleges and universities have a unique organizational culture that influences the decision-making processes used by leaders of higher education. This paper presents findings of a study that attempted to identify the theoretical frameworks that administrators of higher education use to guide their decision-making processes. The following…

Leadership emergence: the application of the Cynefin framework during a bio-social HIV/AIDS risk-reduction pilot.

PubMed

Burman, Christopher J; Aphane, Marota A

2016-09-01

This article focuses on the utility of a knowledge management heuristic called the Cynefin framework, which was applied during an ongoing pilot intervention in the Limpopo province, South Africa. The intervention aimed to identify and then consolidate low-cost, innovative bio-social responses to reinforce the biomedical opportunities that now have the potential to "end AIDS by 2030″. The Cynefin framework is designed to enable leaders to identify specific decision-making domain typologies as a mechanism to maximise the effectiveness of leadership responses to both opportunities and challenges that emerge during interventions. In this instance the Cynefin framework was used to: (1) provide an indication to the project managers whether the early stages of the intervention had been effective; (2) provide the participants an opportunity to identify emergent knowledge action spaces (opportunities and challenges); and (3) categorise them into appropriate decision-making domains in preparation for the next phases of the intervention. A qualitative methodology was applied to collect and analyse the findings. The findings indicate that applying the Cynefin framework enabled the participants to situate knowledge action spaces into appropriate decision-making domains. From this participatory evaluation a targeted management strategy was developed for the next phases of the initiative. The article concludes by arguing that the Cynefin framework was an effective mechanism for situating emergent knowledge action spaces into appropriate decision-making domains, which enabled them to prepare for the next phases of the intervention. This process of responsive decision making could have utility in other development related interventions.

Ethical Frameworks in Public Health Decision-Making: Defending a Value-Based and Pluralist Approach.

PubMed

Grill, Kalle; Dawson, Angus

2017-12-01

A number of ethical frameworks have been proposed to support decision-making in public health and the evaluation of public health policy and practice. This is encouraging, since ethical considerations are of paramount importance in health policy. However, these frameworks have various deficiencies, in part because they incorporate substantial ethical positions. In this article, we discuss and criticise a framework developed by James Childress and Ruth Bernheim, which we consider to be the state of the art in the field. Their framework distinguishes aims, such as the promotion of public health, from constraints on the pursuit of those aims, such as the requirement to avoid limitations to liberty, or the requirement to be impartial. We show how this structure creates both theoretical and practical problems. We then go on to present and defend a more practical framework, one that is neutral in avoiding precommitment to particular values and how they ought to be weighted. We believe ethics is at the very heart of such weightings and our framework is developed to reflect this belief. It is therefore both pluralist and value-based. We compare our new framework to Childress and Bernheim's and outline its advantages. It is justified by its impetus to consider a wide range of alternatives and its tendency to direct decisions towards the best alternatives, as well as by the information provided by the ranking of alternatives and transparent explication of the judgements that motivate this ranking. The new framework presented should be useful to decision-makers in public health, as well as being a means to stimulate further reflection on the role of ethics in public health.

A Decentralized Compositional Framework for Dependable Decision Process in Self-Managed Cyber Physical Systems

PubMed Central

Hou, Kun-Mean; Zhang, Zhan

2017-01-01

Cyber Physical Systems (CPSs) need to interact with the changeable environment under various interferences. To provide continuous and high quality services, a self-managed CPS should automatically reconstruct itself to adapt to these changes and recover from failures. Such dynamic adaptation behavior introduces systemic challenges for CPS design, advice evaluation and decision process arrangement. In this paper, a formal compositional framework is proposed to systematically improve the dependability of the decision process. To guarantee the consistent observation of event orders for causal reasoning, this work first proposes a relative time-based method to improve the composability and compositionality of the timing property of events. Based on the relative time solution, a formal reference framework is introduced for self-managed CPSs, which includes a compositional FSM-based actor model (subsystems of CPS), actor-based advice and runtime decomposable decisions. To simplify self-management, a self-similar recursive actor interface is proposed for decision (actor) composition. We provide constraints and seven patterns for the composition of reliability and process time requirements. Further, two decentralized decision process strategies are proposed based on our framework, and we compare the reliability with the static strategy and the centralized processing strategy. The simulation results show that the one-order feedback strategy has high reliability, scalability and stability against the complexity of decision and random failure. This paper also shows a way to simplify the evaluation for dynamic system by improving the composability and compositionality of the subsystem. PMID:29120357

A Decentralized Compositional Framework for Dependable Decision Process in Self-Managed Cyber Physical Systems.

PubMed

Zhou, Peng; Zuo, Decheng; Hou, Kun-Mean; Zhang, Zhan

2017-11-09

Cyber Physical Systems (CPSs) need to interact with the changeable environment under various interferences. To provide continuous and high quality services, a self-managed CPS should automatically reconstruct itself to adapt to these changes and recover from failures. Such dynamic adaptation behavior introduces systemic challenges for CPS design, advice evaluation and decision process arrangement. In this paper, a formal compositional framework is proposed to systematically improve the dependability of the decision process. To guarantee the consistent observation of event orders for causal reasoning, this work first proposes a relative time-based method to improve the composability and compositionality of the timing property of events. Based on the relative time solution, a formal reference framework is introduced for self-managed CPSs, which includes a compositional FSM-based actor model (subsystems of CPS), actor-based advice and runtime decomposable decisions. To simplify self-management, a self-similar recursive actor interface is proposed for decision (actor) composition. We provide constraints and seven patterns for the composition of reliability and process time requirements. Further, two decentralized decision process strategies are proposed based on our framework, and we compare the reliability with the static strategy and the centralized processing strategy. The simulation results show that the one-order feedback strategy has high reliability, scalability and stability against the complexity of decision and random failure. This paper also shows a way to simplify the evaluation for dynamic system by improving the composability and compositionality of the subsystem.

Psychotropics without borders: ethics and legal implications of internet-based access to psychiatric medications.

PubMed

Klein, Carolina A

2011-01-01

Medical practitioners are revisiting many of the ethics and the legal implications surrounding the clinical frameworks within which we operate. In today's world, distinguishing between virtual and physical reality continues to be increasingly difficult. The physician may be found grappling with the decision of whether to continue to treat a patient who may be obtaining psychotropic medications through the Internet. This article approaches some of the clinical and legal implications and the ethics regarding the availability of prescription psychotropics over the Internet.

Group-sequential three-arm noninferiority clinical trial designs

PubMed Central

Ochiai, Toshimitsu; Hamasaki, Toshimitsu; Evans, Scott R.; Asakura, Koko; Ohno, Yuko

2016-01-01

We discuss group-sequential three-arm noninferiority clinical trial designs that include active and placebo controls for evaluating both assay sensitivity and noninferiority. We extend two existing approaches, the fixed margin and fraction approaches, into a group-sequential setting with two decision-making frameworks. We investigate the operating characteristics including power, Type I error rate, maximum and expected sample sizes, as design factors vary. In addition, we discuss sample size recalculation and its’ impact on the power and Type I error rate via a simulation study. PMID:26892481

A framework to support decision making in the selection of sustainable drainage system design alternatives.

PubMed

Wang, Mingming; Sweetapple, Chris; Fu, Guangtao; Farmani, Raziyeh; Butler, David

2017-10-01

This paper presents a new framework for decision making in sustainable drainage system (SuDS) scheme design. It integrates resilience, hydraulic performance, pollution control, rainwater usage, energy analysis, greenhouse gas (GHG) emissions and costs, and has 12 indicators. The multi-criteria analysis methods of entropy weight and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were selected to support SuDS scheme selection. The effectiveness of the framework is demonstrated with a SuDS case in China. Indicators used include flood volume, flood duration, a hydraulic performance indicator, cost and resilience. Resilience is an important design consideration, and it supports scheme selection in the case study. The proposed framework will help a decision maker to choose an appropriate design scheme for implementation without subjectivity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrative evaluation for sustainable decisions of urban wastewater system management under uncertainty

NASA Astrophysics Data System (ADS)

Hadjimichael, A.; Corominas, L.; Comas, J.

2017-12-01

With sustainable development as their overarching goal, urban wastewater system (UWS) managers need to take into account multiple social, economic, technical and environmental facets related to their decisions. In this complex decision-making environment, uncertainty can be formidable. It is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behavior. This inherent uncertainty suggests that wiser decisions would be made under an adaptive and iterative decision-making regime. No decision-support framework has been presented in the literature to effectively addresses all these needs. The objective of this work is to describe such a conceptual framework to evaluate and compare alternative solutions for various UWS challenges within an adaptive management structure. Socio-economic aspects such as externalities are taken into account, along with other traditional criteria as necessary. Robustness, reliability and resilience analyses test the performance of the system against present and future variability. A valuation uncertainty analysis incorporates uncertain valuation assumptions in the decision-making process. The framework is demonstrated with an application to a case study presenting a typical problem often faced by managers: poor river water quality, increasing population, and more stringent water quality legislation. The application of the framework made use of: i) a cost-benefit analysis including monetized environmental benefits and damages; ii) a robustness analysis of system performance against future conditions; iii) reliability and resilience analyses of the system given contextual variability; and iv) a valuation uncertainty analysis of model parameters. The results suggest that the installation of bigger volumes would give rise to increased benefits despite larger capital costs, as well as increased robustness and resilience. Population numbers appear to affect the estimated benefits most, followed by electricity prices and climate change projections. The presented framework is expected to be a valuable tool for the next generation of UWS decision-making and the application demonstrates a novel and valuable integration of metrics and methods for UWS analysis.

A conceptual framework for effectively anticipating water-quality changes resulting from changes in agricultural activities

USGS Publications Warehouse

Capel, Paul D.; Wolock, David M.; Coupe, Richard H.; Roth, Jason L.

2018-01-10

Agricultural activities can affect water quality and the health of aquatic ecosystems; many water-quality issues originate with the movement of water, agricultural chemicals, and eroded soil from agricultural areas to streams and groundwater. Most agricultural activities are designed to sustain or increase crop production, while some are designed to protect soil and water resources. Numerous soil- and water-protection practices are designed to reduce the volume and velocity of runoff and increase infiltration. This report presents a conceptual framework that combines generalized concepts on the movement of water, the environmental behavior of chemicals and eroded soil, and the designed functions of various agricultural activities, as they relate to hydrology, to create attainable expectations for the protection of—with the goal of improving—water quality through changes in an agricultural activity.The framework presented uses two types of decision trees to guide decision making toward attainable expectations regarding the effectiveness of changing agricultural activities to protect and improve water quality in streams. One decision tree organizes decision making by considering the hydrologic setting and chemical behaviors, largely at the field scale. This decision tree can help determine which agricultural activities could effectively protect and improve water quality in a stream from the movement of chemicals, or sediment, from a field. The second decision tree is a chemical fate accounting tree. This decision tree helps set attainable expectations for the permanent removal of sediment, elements, and organic chemicals—such as herbicides and insecticides—through trapping or conservation tillage practices. Collectively, this conceptual framework consolidates diverse hydrologic settings, chemicals, and agricultural activities into a single, broad context that can be used to set attainable expectations for agricultural activities. This framework also enables better decision making for future agricultural activities as a means to reduce current, and prevent new, water-quality issues.

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.

Using an ecological ethics framework to make decisions about the relocation of wildlife.

PubMed

McCoy, Earl D; Berry, Kristin

2008-12-01

Relocation is an increasingly prominent conservation tool for a variety of wildlife, but the technique also is controversial, even among conservation practitioners. An organized framework for addressing the moral dilemmas often accompanying conservation actions such as relocation has been lacking. Ecological ethics may provide such a framework and appears to be an important step forward in aiding ecological researchers and biodiversity managers to make difficult moral choices. A specific application of this framework can make the reasoning process more transparent and give more emphasis to the strong sentiments about non-human organisms held by many potential users. Providing an example of the application of the framework may also increase the appeal of the reasoning process to ecological researchers and biodiversity managers. Relocation as a conservation action can be accompanied by a variety of moral dilemmas that reflect the interconnection of values, ethical positions, and conservation decisions. A model that is designed to address moral dilemmas arising from relocation of humans provides/demonstrates/illustrates a possible way to apply the ecological ethics framework and to involve practicing conservationists in the overall decision-making process.

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

NASA Astrophysics Data System (ADS)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

Pilot/Controller Coordinated Decision Making in the Next Generation Air Transportation System

NASA Technical Reports Server (NTRS)

Bearman, Chris; Miller, Ronald c.; Orasanu, Judith M.

2011-01-01

Introduction: NextGen technologies promise to provide considerable benefits in terms of enhancing operations and improving safety. However, there needs to be a thorough human factors evaluation of the way these systems will change the way in which pilot and controllers share information. The likely impact of these new technologies on pilot/controller coordinated decision making is considered in this paper using the "operational, informational and evaluative disconnect" framework. Method: Five participant focus groups were held. Participants were four experts in human factors, between x and x research students and a technical expert. The participant focus group evaluated five key NextGen technologies to identify issues that made different disconnects more or less likely. Results: Issues that were identified were: Decision Making will not necessarily improve because pilots and controllers possess the same information; Having a common information source does not mean pilots and controllers are looking at the same information; High levels of automation may lead to disconnects between the technology and pilots/controllers; Common information sources may become the definitive source for information; Overconfidence in the automation may lead to situations where appropriate breakdowns are not initiated. Discussion: The issues that were identified lead to recommendations that need to be considered in the development of NextGen technologies. The current state of development of these technologies provides a good opportunity to utilize recommendations at an early stage so that NextGen technologies do not lead to difficulties in resolving breakdowns in coordinated decision making.

Argumentation, critical thinking, nature of science and socioscientific issues: a dialogue between two researchers

NASA Astrophysics Data System (ADS)

Yacoubian, Hagop A.; Khishfe, Rola

2018-05-01

The purpose of this paper is to compare and contrast between two theoretical frameworks for addressing nature of science (NOS) and socioscientific issues (SSI) in school science. These frameworks are critical thinking (CT) and argumentation (AR). For the past years, the first and second authors of this paper have pursued research in this area using CT and AR as theoretical frameworks, respectively. Yacoubian argues that future citizens need to develop a critical mindset as they are guided to (1) practice making judgments on what views of NOS to acquire and (2) practice making decisions on SSI through applying their NOS understandings. Khishfe asserts that AR is an important component of decision making when dealing with SSI and the practice in AR in relation to controversial issues is needed for informed decision making. She argues that AR as a framework may assist in the development of more informed understandings of NOS. In this paper, the authors delve into a dialogue for (1) elucidating strengths and potential of each framework, (2) highlighting challenges that they face in their research using the frameworks in question, (3) exploring the extent to which the frameworks can overlap, and (4) proposing directions for future research.

Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use

PubMed Central

Brown, Marshall D.; Zhu, Kehao; Janes, Holly

2016-01-01

The decision curve is a graphical summary recently proposed for assessing the potential clinical impact of risk prediction biomarkers or risk models for recommending treatment or intervention. It was applied recently in an article in Journal of Clinical Oncology to measure the impact of using a genomic risk model for deciding on adjuvant radiation therapy for prostate cancer treated with radical prostatectomy. We illustrate the use of decision curves for evaluating clinical- and biomarker-based models for predicting a man’s risk of prostate cancer, which could be used to guide the decision to biopsy. Decision curves are grounded in a decision-theoretical framework that accounts for both the benefits of intervention and the costs of intervention to a patient who cannot benefit. Decision curves are thus an improvement over purely mathematical measures of performance such as the area under the receiver operating characteristic curve. However, there are challenges in using and interpreting decision curves appropriately. We caution that decision curves cannot be used to identify the optimal risk threshold for recommending intervention. We discuss the use of decision curves for miscalibrated risk models. Finally, we emphasize that a decision curve shows the performance of a risk model in a population in which every patient has the same expected benefit and cost of intervention. If every patient has a personal benefit and cost, then the curves are not useful. If subpopulations have different benefits and costs, subpopulation-specific decision curves should be used. As a companion to this article, we released an R software package called DecisionCurve for making decision curves and related graphics. PMID:27247223

A novel framework for improvement of road accidents considering decision-making styles of drivers in a large metropolitan area.

PubMed

Azadeh, Ali; Zarrin, Mansour; Hamid, Mehdi

2016-02-01

Road accidents can be caused by different factors such as human factors. Quality of the decision-making process of drivers could have a considerable impact on preventing disasters. The main objective of this study is the analysis of factors affecting road accidents by considering the severity of accidents and decision-making styles of drivers. To this end, a novel framework is proposed based on data envelopment analysis (DEA) and statistical methods (SMs) to assess the factors affecting road accidents. In this study, for the first time, dominant decision-making styles of drivers with respect to severity of injuries are identified. To show the applicability of the proposed framework, this research employs actual data of more than 500 samples in Tehran, Iran. The empirical results indicate that the flexible decision style is the dominant style for both minor and severe levels of accident injuries. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using Decision Analysis to Improve Malaria Control Policy Making

PubMed Central

Kramer, Randall; Dickinson, Katherine L.; Anderson, Richard M.; Fowler, Vance G.; Miranda, Marie Lynn; Mutero, Clifford M.; Saterson, Kathryn A.; Wiener, Jonathan B.

2013-01-01

Malaria and other vector-borne diseases represent a significant and growing burden in many tropical countries. Successfully addressing these threats will require policies that expand access to and use of existing control methods, such as insecticide-treated bed nets and artemesinin combination therapies for malaria, while weighing the costs and benefits of alternative approaches over time. This paper argues that decision analysis provides a valuable framework for formulating such policies and combating the emergence and re-emergence of malaria and other diseases. We outline five challenges that policy makers and practitioners face in the struggle against malaria, and demonstrate how decision analysis can help to address and overcome these challenges. A prototype decision analysis framework for malaria control in Tanzania is presented, highlighting the key components that a decision support tool should include. Developing and applying such a framework can promote stronger and more effective linkages between research and policy, ultimately helping to reduce the burden of malaria and other vector-borne diseases. PMID:19356821

A framework for sensitivity analysis of decision trees.

PubMed

Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław

2018-01-01

In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.

Risk perception & strategic decision making :general insights, a framework, and specific application to electricity generation using nuclear energy.

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

Brewer, Jeffrey D.

The objective of this report is to promote increased understanding of decision making processes and hopefully to enable improved decision making regarding high-consequence, highly sophisticated technological systems. This report brings together insights regarding risk perception and decision making across domains ranging from nuclear power technology safety, cognitive psychology, economics, science education, public policy, and neural science (to name a few). It forms them into a unique, coherent, concise framework, and list of strategies to aid in decision making. It is suggested that all decision makers, whether ordinary citizens, academics, or political leaders, ought to cultivate their abilities to separate themore » wheat from the chaff in these types of decision making instances. The wheat includes proper data sources and helpful human decision making heuristics; these should be sought. The chaff includes ''unhelpful biases'' that hinder proper interpretation of available data and lead people unwittingly toward inappropriate decision making ''strategies''; obviously, these should be avoided. It is further proposed that successfully accomplishing the wheat vs. chaff separation is very difficult, yet tenable. This report hopes to expose and facilitate navigation away from decision-making traps which often ensnare the unwary. Furthermore, it is emphasized that one's personal decision making biases can be examined, and tools can be provided allowing better means to generate, evaluate, and select among decision options. Many examples in this report are tailored to the energy domain (esp. nuclear power for electricity generation). The decision making framework and approach presented here are applicable to any high-consequence, highly sophisticated technological system.« less

Fuzzy robust credibility-constrained programming for environmental management and planning.

PubMed

Zhang, Yimei; Hang, Guohe

2010-06-01

In this study, a fuzzy robust credibility-constrained programming (FRCCP) is developed and applied to the planning for waste management systems. It incorporates the concepts of credibility-based chance-constrained programming and robust programming within an optimization framework. The developed method can reflect uncertainties presented as possibility-density by fuzzy-membership functions. Fuzzy credibility constraints are transformed to the crisp equivalents with different credibility levels, and ordinary fuzzy inclusion constraints are determined by their robust deterministic constraints by setting a-cut levels. The FRCCP method can provide different system costs under different credibility levels (lambda). From the results of sensitivity analyses, the operation cost of the landfill is a critical parameter. For the management, any factors that would induce cost fluctuation during landfilling operation would deserve serious observation and analysis. By FRCCP, useful solutions can be obtained to provide decision-making support for long-term planning of solid waste management systems. It could be further enhanced through incorporating methods of inexact analysis into its framework. It can also be applied to other environmental management problems.

The next generation of command post computing

NASA Astrophysics Data System (ADS)

Arnold, Ross D.; Lieb, Aaron J.; Samuel, Jason M.; Burger, Mitchell A.

2015-05-01

The future of command post computing demands an innovative new solution to address a variety of challenging operational needs. The Command Post of the Future is the Army's primary command and control decision support system, providing situational awareness and collaborative tools for tactical decision making, planning, and execution management from Corps to Company level. However, as the U.S. Army moves towards a lightweight, fully networked battalion, disconnected operations, thin client architecture and mobile computing become increasingly essential. The Command Post of the Future is not designed to support these challenges in the coming decade. Therefore, research into a hybrid blend of technologies is in progress to address these issues. This research focuses on a new command and control system utilizing the rich collaboration framework afforded by Command Post of the Future coupled with a new user interface consisting of a variety of innovative workspace designs. This new system is called Tactical Applications. This paper details a brief history of command post computing, presents the challenges facing the modern Army, and explores the concepts under consideration for Tactical Applications that meet these challenges in a variety of innovative ways.

Evaluating Diagnostic Point-of-Care Tests in Resource-Limited Settings

PubMed Central

Drain, Paul K; Hyle, Emily P; Noubary, Farzad; Freedberg, Kenneth A; Wilson, Douglas; Bishai, William; Rodriguez, William; Bassett, Ingrid V

2014-01-01

Diagnostic point-of-care (POC) testing is intended to minimize the time to obtain a test result, thereby allowing clinicians and patients to make an expeditious clinical decision. As POC tests expand into resource-limited settings (RLS), the benefits must outweigh the costs. To optimize POC testing in RLS, diagnostic POC tests need rigorous evaluations focused on relevant clinical outcomes and operational costs, which differ from evaluations of conventional diagnostic tests. Here, we reviewed published studies on POC testing in RLS, and found no clearly defined metric for the clinical utility of POC testing. Therefore, we propose a framework for evaluating POC tests, and suggest and define the term “test efficacy” to describe a diagnostic test’s capacity to support a clinical decision within its operational context. We also proposed revised criteria for an ideal diagnostic POC test in resource-limited settings. Through systematic evaluations, comparisons between centralized diagnostic testing and novel POC technologies can be more formalized, and health officials can better determine which POC technologies represent valuable additions to their clinical programs. PMID:24332389

Decision support in vaccination policies.

PubMed

Piso, B; Wild, C

2009-10-09

Looking across boarders reveals that the national immunization programs of various countries differ in their vaccination schedules and decisions regarding the implementation and funding of new vaccines. The aim of this review is to identify decision aids and crucial criteria for a rational decision-making process on vaccine introduction and to develop a theoretical framework for decision-making based on available literature. Systematic literature search supplemented by hand-search. We identified five published decision aids for vaccine introduction and program planning in industrialized countries. Their comparison revealed an overall similarity with some differences in the approach as well as criteria. Burden of disease and vaccine characteristics play a key role in all decision aids, but authors vary in their views on the significance of cost-effectiveness analyses. Other relevant factors that should be considered before vaccine introduction are discussed to highly differing extents. These factors include the immunization program itself as well as its conformity with other programs, its feasibility, acceptability, and equity, as well as ethical, legal and political considerations. Assuming that the most comprehensive framework possible will not provide a feasible tool for decision-makers, we suggest a stepwise procedure. Though even the best rational approach and most comprehensive evaluation is limited by remaining uncertainties, frameworks provide at least a structured approach to evaluate the various aspects of vaccine implementation decision-making. This process is essential in making consistently sound decisions and will facilitate the public's confidence in the decision and its realization.

Characterizing the orthodontic patient's purchase decision: A novel approach using netnography.

PubMed

Pittman, Joseph W; Bennett, M Elizabeth; Koroluk, Lorne D; Robinson, Stacey G; Phillips, Ceib L

2017-06-01

A deeper and more thorough characterization of why patients do or do not seek orthodontic treatment is needed for effective shared decision making about receiving treatment. Previous orthodontic qualitative research has identified important dimensions that influence treatment decisions, but our understanding of patients' decisions and how they interpret benefits and barriers of treatment are lacking. The objectives of this study were to expand our current list of decision-making dimensions and to create a conceptual framework to describe the decision-making process. Discussion boards, rich in orthodontic decision-making data, were identified and analyzed with qualitative methods. An iterative process of data collection, dimension identification, and dimension refinement were performed to saturation. A conceptual framework was created to describe the decision-making process. Fifty-four dimensions captured the ideas discussed in regard to a patient's decision to receive orthodontic treatment. Ten domains were identified: function, esthetics, psychosocial benefits, diagnosis, finances, inconveniences, risks of treatment, individual aspects, societal attitudes, and child-specific influences, each containing specific descriptive and conceptual dimensions. A person's desires, self-perceptions, and viewpoints, the public's views on esthetics and orthodontics, and parenting philosophies impacted perceptions of benefits and barriers associated with orthodontic treatment. We identified an expanded list of dimensions, created a conceptual framework describing the orthodontic patient's decision-making process, and identified dimensions associated with yes and no decisions, giving doctors a better understanding of patient attitudes and expectations. Copyright © 2017 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Human-Interaction Challenges in UAV-Based Autonomous Surveillance

NASA Technical Reports Server (NTRS)

Freed, Michael; Harris, Robert; Shafto, Michael G.

2004-01-01

Autonomous UAVs provide a platform for intelligent surveillance in application domains ranging from security and military operations to scientific information gathering and land management. Surveillance tasks are often long duration, requiring that any approach be adaptive to changes in the environment or user needs. We describe a decision- theoretic model of surveillance, appropriate for use on our autonomous helicopter, that provides a basis for optimizing the value of information returned by the UAV. From this approach arise a range of challenges in making this framework practical for use by human operators lacking specialized knowledge of autonomy and mathematics. This paper describes our platform and approach, then describes human-interaction challenges arising from this approach that we have identified and begun to address.

Priority setting: what constitutes success? A conceptual framework for successful priority setting.

PubMed

Sibbald, Shannon L; Singer, Peter A; Upshur, Ross; Martin, Douglas K

2009-03-05

The sustainability of healthcare systems worldwide is threatened by a growing demand for services and expensive innovative technologies. Decision makers struggle in this environment to set priorities appropriately, particularly because they lack consensus about which values should guide their decisions. One way to approach this problem is to determine what all relevant stakeholders understand successful priority setting to mean. The goal of this research was to develop a conceptual framework for successful priority setting. Three separate empirical studies were completed using qualitative data collection methods (one-on-one interviews with healthcare decision makers from across Canada; focus groups with representation of patients, caregivers and policy makers; and Delphi study including scholars and decision makers from five countries). This paper synthesizes the findings from three studies into a framework of ten separate but interconnected elements germane to successful priority setting: stakeholder understanding, shifted priorities/reallocation of resources, decision making quality, stakeholder acceptance and satisfaction, positive externalities, stakeholder engagement, use of explicit process, information management, consideration of values and context, and revision or appeals mechanism. The ten elements specify both quantitative and qualitative dimensions of priority setting and relate to both process and outcome components. To our knowledge, this is the first framework that describes successful priority setting. The ten elements identified in this research provide guidance for decision makers and a common language to discuss priority setting success and work toward improving priority setting efforts.

Development of a decision support tool for seasonal water supply management incorporating system uncertainties and operational constraints

NASA Astrophysics Data System (ADS)

Wang, H.; Asefa, T.

2017-12-01

A real-time decision support tool (DST) for water supply system would consider system uncertainties, e.g., uncertain streamflow and demand, as well as operational constraints and infrastructure outage (e.g., pump station shutdown, an offline reservoir due to maintenance). Such DST is often used by water managers for resource allocation and delivery for customers. Although most seasonal DST used by water managers recognize those system uncertainties and operational constraints, most use only historical information or assume deterministic outlook of water supply systems. This study presents a seasonal DST that incorporates rainfall/streamflow uncertainties, seasonal demand outlook and system operational constraints. Large scale climate-information is captured through a rainfall simulator driven by a Bayesian non-homogeneous Markov Chain Monte Carlo model that allows non-stationary transition probabilities contingent on Nino 3.4 index. An ad-hoc seasonal demand forecasting model considers weather conditions explicitly and socio-economic factors implicitly. Latin Hypercube sampling is employed to effectively sample probability density functions of flow and demand. Seasonal system operation is modelled as a mixed-integer optimization problem that aims at minimizing operational costs. It embeds the flexibility of modifying operational rules at different components, e.g., surface water treatment plants, desalination facilities, and groundwater pumping stations. The proposed framework is illustrated at a wholesale water supplier in Southeastern United States, Tampa Bay Water. The use of the tool is demonstrated in proving operational guidance in a typical drawdown and refill cycle of a regional reservoir. The DST provided: 1) probabilistic outlook of reservoir storage and chance of a successful refill by the end of rainy season; 2) operational expectations for large infrastructures (e.g., high service pumps and booster stations) throughout the season. Other potential use of such DST is also discussed.

Amateur Image Pipeline Processing using Python plus PyRAF

NASA Astrophysics Data System (ADS)

Green, Wayne

2012-05-01

A template pipeline spanning observing planning to publishing is offered as a basis for establishing a long term observing program. The data reduction pipeline encapsulates all policy and procedures, providing an accountable framework for data analysis and a teaching framework for IRAF. This paper introduces the technical details of a complete pipeline processing environment using Python, PyRAF and a few other languages. The pipeline encapsulates all processing decisions within an auditable framework. The framework quickly handles the heavy lifting of image processing. It also serves as an excellent teaching environment for astronomical data management and IRAF reduction decisions.

Looking at patients' choices through the lens of expected utility: a critique and research agenda.

PubMed

Russell, Louise B; Schwartz, Alan

2012-01-01

The expected utility framework underlies much research in medical decision making. Because the framework requires decisions to be decomposed into probabilities of states and the values of those states, researchers have investigated the two components separately from each other and from patients' actual decisions. The authors propose that it would be productive to focus more research on the relationships among risk perceptions, outcome valuations, and choices in the same decision makers. They outline exploratory analyses based on two existing national surveys, the Medical Expenditure Panel Survey and the Joint Canada/United States Survey of Health.

Implementation of Cyber-Physical Production Systems for Quality Prediction and Operation Control in Metal Casting

PubMed Central

Lee, JuneHyuck; Noh, Sang Do; Kim, Hyun-Jung; Kang, Yong-Shin

2018-01-01

The prediction of internal defects of metal casting immediately after the casting process saves unnecessary time and money by reducing the amount of inputs into the next stage, such as the machining process, and enables flexible scheduling. Cyber-physical production systems (CPPS) perfectly fulfill the aforementioned requirements. This study deals with the implementation of CPPS in a real factory to predict the quality of metal casting and operation control. First, a CPPS architecture framework for quality prediction and operation control in metal-casting production was designed. The framework describes collaboration among internet of things (IoT), artificial intelligence, simulations, manufacturing execution systems, and advanced planning and scheduling systems. Subsequently, the implementation of the CPPS in actual plants is described. Temperature is a major factor that affects casting quality, and thus, temperature sensors and IoT communication devices were attached to casting machines. The well-known NoSQL database, HBase and the high-speed processing/analysis tool, Spark, are used for IoT repository and data pre-processing, respectively. Many machine learning algorithms such as decision tree, random forest, artificial neural network, and support vector machine were used for quality prediction and compared with R software. Finally, the operation of the entire system is demonstrated through a CPPS dashboard. In an era in which most CPPS-related studies are conducted on high-level abstract models, this study describes more specific architectural frameworks, use cases, usable software, and analytical methodologies. In addition, this study verifies the usefulness of CPPS by estimating quantitative effects. This is expected to contribute to the proliferation of CPPS in the industry. PMID:29734699

Consolidating strategic planning and operational frameworks for integrated vector management in Eritrea.

PubMed

Chanda, Emmanuel; Ameneshewa, Birkinesh; Mihreteab, Selam; Berhane, Araia; Zehaie, Assefash; Ghebrat, Yohannes; Usman, Abdulmumini

2015-12-02

Contemporary malaria vector control relies on the use of insecticide-based, indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs). However, malaria-endemic countries, including Eritrea, have struggled to effectively deploy these tools due technical and operational challenges, including the selection of insecticide resistance in malaria vectors. This manuscript outlines the processes undertaken in consolidating strategic planning and operational frameworks for vector control to expedite malaria elimination in Eritrea. The effort to strengthen strategic frameworks for vector control in Eritrea was the 'case' for this study. The integrated vector management (IVM) strategy was developed in 2010 but was not well executed, resulting in a rise in malaria transmission, prompting a process to redefine and relaunch the IVM strategy with integration of other vector borne diseases (VBDs) as the focus. The information sources for this study included all available data and accessible archived documentary records on malaria vector control in Eritrea. Structured literature searches of published, peer-reviewed sources using online, scientific, bibliographic databases, Google Scholar, PubMed and WHO, and a combination of search terms were utilized to gather data. The literature was reviewed and adapted to the local context and translated into the consolidated strategic framework. In Eritrea, communities are grappling with the challenge of VBDs posing public health concerns, including malaria. The global fund financed the scale-up of IRS and LLIN programmes in 2014. Eritrea is transitioning towards malaria elimination and strategic frameworks for vector control have been consolidated by: developing an integrated vector management (IVM) strategy (2015-2019); updating IRS and larval source management (LSM) guidelines; developing training manuals for IRS and LSM; training of national staff in malaria entomology and vector control, including insecticide resistance monitoring techniques; initiating the global plan for insecticide resistance management; conducting needs' assessments and developing standard operating procedure for insectaries; developing a guidance document on malaria vector control based on eco-epidemiological strata, a vector surveillance plan and harmonized mapping, data collection and reporting tools. Eritrea has successfully consolidated strategic frameworks for vector control. Rational decision-making remains critical to ensure that the interventions are effective and their choice is evidence-based, and to optimize the use of resources for vector control. Implementation of effective IVM requires proper collaboration and coordination, consistent technical and financial capacity and support to offer greater benefits.

Unique Framework Helps Louisiana Community Prioritize Its Investments in Children and Families. Research Brief

ERIC Educational Resources Information Center

Wiseman, Shelley

2010-01-01

In 2008, the Shreveport-Bossier Community Foundation selected education, health, and poverty as funding priorities. But the foundation realized that it needed more specific guidelines on how best to distribute grants. RAND developed a framework for making investment decisions that incorporates the best of traditional decision making approaches.…

Using Recommendations in Evaluation: A Decision-Making Framework for Evaluators

ERIC Educational Resources Information Center

Iriti, Jennifer E.; Bickel, William E.; Nelson, Catherine Awsumb

2005-01-01

Is it appropriate and useful for evaluators to use findings to make recommendations? If so, under what circumstances? How specific should they be? This article presents a decision-making framework for the appropriateness of recommendations in varying contexts. On the basis of reviews of evaluation theory, selected evaluation reports, and feedback…

Common Web Mapping and Mobile Device Framework for Display of NASA Real-time Data

NASA Astrophysics Data System (ADS)

Burks, J. E.

2013-12-01

Scientists have strategic goals to deliver their unique datasets and research to both collaborative partners and more broadly to the public. These datasets can have a significant impact locally and globally as has been shown by the success of the NASA Short-term Prediction Research and Transition (SPoRT) Center and SERVIR programs at Marshall Space Flight Center. Each of these respective organizations provides near real-time data at the best resolution possible to address concerns of the operational weather forecasting community (SPoRT) and to support environmental monitoring and disaster assessment (SERVIR). However, one of the biggest struggles to delivering the data to these and other Earth science community partners is formatting the product to fit into an end user's Decision Support System (DSS). The problem of delivering the data to the end-user's DSS can be a significant impediment to transitioning research to operational environments especially for disaster response where the deliver time is critical. The decision makers, in addition to the DSS, need seamless access to these same datasets from a web browser or a mobile phone for support when they are away from their DSS or for personnel out in the field. A framework has been developed for MSFC Earth Science program that can be used to easily enable seamless delivery of scientific data to end users in multiple formats. The first format is an open geospatial format, Web Mapping Service (WMS), which is easily integrated into most DSSs. The second format is a web browser display, which can be embedded within any MSFC Science web page with just a few lines of web page coding. The third format is accessible in the form of iOS and Android native mobile applications that could be downloaded from an 'app store'. The framework developed has reduced the level of effort needed to bring new and existing NASA datasets to each of these end user platforms and help extend the reach of science data.

Common Web Mapping and Mobile Device Framework for Display of NASA Real-time Data

NASA Technical Reports Server (NTRS)

Burks, Jason

2013-01-01

Scientists have strategic goals to deliver their unique datasets and research to both collaborative partners and more broadly to the public. These datasets can have a significant impact locally and globally as has been shown by the success of the NASA Short-term Prediction Research and Transition (SPoRT) Center and SERVIR programs at Marshall Space Flight Center. Each of these respective organizations provides near real-time data at the best resolution possible to address concerns of the operational weather forecasting community (SPoRT) and to support environmental monitoring and disaster assessment (SERVIR). However, one of the biggest struggles to delivering the data to these and other Earth science community partners is formatting the product to fit into an end user's Decision Support System (DSS). The problem of delivering the data to the end-user's DSS can be a significant impediment to transitioning research to operational environments especially for disaster response where the deliver time is critical. The decision makers, in addition to the DSS, need seamless access to these same datasets from a web browser or a mobile phone for support when they are away from their DSS or for personnel out in the field. A framework has been developed for MSFC Earth Science program that can be used to easily enable seamless delivery of scientific data to end users in multiple formats. The first format is an open geospatial format, Web Mapping Service (WMS), which is easily integrated into most DSSs. The second format is a web browser display, which can be embedded within any MSFC Science web page with just a few lines of web page coding. The third format is accessible in the form of iOS and Android native mobile applications that could be downloaded from an "app store". The framework developed has reduced the level of effort needed to bring new and existing NASA datasets to each of these end user platforms and help extend the reach of science data.

DARHT Multi-intelligence Seismic and Acoustic Data Analysis

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

Stevens, Garrison Nicole; Van Buren, Kendra Lu; Hemez, Francois M.

The purpose of this report is to document the analysis of seismic and acoustic data collected at the Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory for robust, multi-intelligence decision making. The data utilized herein is obtained from two tri-axial seismic sensors and three acoustic sensors, resulting in a total of nine data channels. The goal of this analysis is to develop a generalized, automated framework to determine internal operations at DARHT using informative features extracted from measurements collected external of the facility. Our framework involves four components: (1) feature extraction, (2) data fusion, (3) classification, andmore » finally (4) robustness analysis. Two approaches are taken for extracting features from the data. The first of these, generic feature extraction, involves extraction of statistical features from the nine data channels. The second approach, event detection, identifies specific events relevant to traffic entering and leaving the facility as well as explosive activities at DARHT and nearby explosive testing sites. Event detection is completed using a two stage method, first utilizing signatures in the frequency domain to identify outliers and second extracting short duration events of interest among these outliers by evaluating residuals of an autoregressive exogenous time series model. Features extracted from each data set are then fused to perform analysis with a multi-intelligence paradigm, where information from multiple data sets are combined to generate more information than available through analysis of each independently. The fused feature set is used to train a statistical classifier and predict the state of operations to inform a decision maker. We demonstrate this classification using both generic statistical features and event detection and provide a comparison of the two methods. Finally, the concept of decision robustness is presented through a preliminary analysis where uncertainty is added to the system through noise in the measurements.« less

A framework for quantifying and optimizing the value of seismic monitoring of infrastructure

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr

2017-04-01

This paper outlines a framework for quantifying and optimizing the value of information from structural health monitoring (SHM) technology deployed on large infrastructure, which may sustain damage in a series of earthquakes (the main and the aftershocks). The evolution of the damage state of the infrastructure without or with SHM is presented as a time-dependent, stochastic, discrete-state, observable and controllable nonlinear dynamical system. The pre-posterior Bayesian analysis and the decision tree are used for quantifying and optimizing the value of SHM information. An optimality problem is then formulated how to decide on the adoption of SHM and how to manage optimally the usage and operations of the possibly damaged infrastructure and its repair schedule using the information from SHM. The objective function to minimize is the expected total cost or risk.

A new approach to the design of information systems for foodservice management in health care facilities.

PubMed

Matthews, M E; Norback, J P

1984-06-01

An organizational framework for integrating foodservice data into an information system for management decision making is presented. The framework involves the application to foodservice of principles developed by the disciplines of managerial economics and accounting, mathematics, computer science, and information systems. The first step is to conceptualize a foodservice system from an input-output perspective, in which inputs are units of resources available to managers and outputs are servings of menu items. Next, methods of full cost accounting, from the management accounting literature, are suggested as a mechanism for developing and assigning costs of using resources within a foodservice operation. Then matrix multiplication is used to illustrate types of information that matrix data structures could make available for management planning and control when combined with a conversational mode of computer programming.

Research on the content framework of information disclosure mechanism in Shanxi power market

NASA Astrophysics Data System (ADS)

Sun, Yanzhang; Li, Tao; Hou, Zhehui; Cao, Xiaozhong

2018-06-01

With the further development of the power reform, establishing a sound power system with rich content and efficient operation has become an urgent need. Faced with the current circumstance of power market information disclosure in Shanxi province, this paper fully incorporates the actual situation and introduces the index into the power market information disclosure mechanism, and sets up the general information disclosure framework in Shanxi province power market on the basis of which A direct information disclosure mechanism and an indirect information disclosure mechanism were designed. Then we formulate comprehensive power index system, generation index system, transmission and distribution index system, and power utilization index system. In conclusion, the outcomes above will enrich power information disclosure mechanism in Shanxi province and will provide a platform for various market members as a guidance on setting right business decisions.

Modern and prospective technologies for weather modification activities: Developing a framework for integrating autonomous unmanned aircraft systems

NASA Astrophysics Data System (ADS)

DeFelice, T. P.; Axisa, Duncan

2017-09-01

This paper builds upon the processes and framework already established for identifying, integrating and testing an unmanned aircraft system (UAS) with sensing technology for use in rainfall enhancement cloud seeding programs to carry out operational activities or to monitor and evaluate seeding operations. We describe the development and assessment methodologies of an autonomous and adaptive UAS platform that utilizes in-situ real time data to sense, target and implement seeding. The development of a UAS platform that utilizes remote and in-situ real-time data to sense, target and implement seeding deployed with a companion UAS ensures optimal, safe, secure, cost-effective seeding operations, and the dataset to quantify the results of seeding. It also sets the path for an innovative, paradigm shifting approach for enhancing precipitation independent of seeding mode. UAS technology is improving and their application in weather modification must be explored to lay the foundation for future implementation. The broader significance lies in evolving improved technology and automating cloud seeding operations that lowers the cloud seeding operational footprint and optimizes their effectiveness and efficiency, while providing the temporal and spatial sensitivities to overcome the predictability or sparseness of environmental parameters needed to identify conditions suitable for seeding, and how such might be implemented. The dataset from the featured approach will contain data from concurrent Eulerian and Lagrangian perspectives over sub-cloud scales that will facilitate the development of cloud seeding decision support tools.

Flight deck engine advisor

NASA Technical Reports Server (NTRS)

Shontz, W. D.; Records, R. M.; Antonelli, D. R.

1992-01-01

The focus of this project is on alerting pilots to impending events in such a way as to provide the additional time required for the crew to make critical decisions concerning non-normal operations. The project addresses pilots' need for support in diagnosis and trend monitoring of faults as they affect decisions that must be made within the context of the current flight. Monitoring and diagnostic modules developed under the NASA Faultfinder program were restructured and enhanced using input data from an engine model and real engine fault data. Fault scenarios were prepared to support knowledge base development activities on the MONITAUR and DRAPhyS modules of Faultfinder. An analysis of the information requirements for fault management was included in each scenario. A conceptual framework was developed for systematic evaluation of the impact of context variables on pilot action alternatives as a function of event/fault combinations.

Vision Based Autonomous Robotic Control for Advanced Inspection and Repair

NASA Technical Reports Server (NTRS)

Wehner, Walter S.

2014-01-01

The advanced inspection system is an autonomous control and analysis system that improves the inspection and remediation operations for ground and surface systems. It uses optical imaging technology with intelligent computer vision algorithms to analyze physical features of the real-world environment to make decisions and learn from experience. The advanced inspection system plans to control a robotic manipulator arm, an unmanned ground vehicle and cameras remotely, automatically and autonomously. There are many computer vision, image processing and machine learning techniques available as open source for using vision as a sensory feedback in decision-making and autonomous robotic movement. My responsibilities for the advanced inspection system are to create a software architecture that integrates and provides a framework for all the different subsystem components; identify open-source algorithms and techniques; and integrate robot hardware.

[eHealth in Peru: implementation of policies to strengthen health information systems].

PubMed

Curioso, Walter H

2014-01-01

Health information systems play a key role in enabling high quality, complete health information to be available in a timely fashion for operational and strategic decision-making that makes it possible to save lives and improve the health and quality of life of the population. In many countries, health information systems are weak, incomplete, and fragmented. However, there is broad consensus in the literature of the need to strengthen health information systems in countries around the world. The objective of this paper is to present the essential components of the conceptual framework to strengthen health information systems in Peru. It describes the principal actions and strategies of the Ministry of Health of Peru during the process of strengthening health information systems. These systems make it possible to orient policies for appropriate decision-making in public health.

Information processing and dynamics in minimally cognitive agents.

PubMed

Beer, Randall D; Williams, Paul L

2015-01-01

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we separately analyze the operation of this agent using the mathematical tools of information theory and dynamical systems theory. Information-theoretic analysis reveals how task-relevant information flows through the system to be combined into a categorization decision. Dynamical analysis reveals the key geometrical and temporal interrelationships underlying the categorization decision. Finally, we propose a framework for directly relating these two different styles of explanation and discuss the possible implications of our analysis for some of the ongoing debates in cognitive science. Copyright © 2014 Cognitive Science Society, Inc.

Conceptual Frameworks for the Workplace Change Adoption Process: Elements Integration from Decision Making and Learning Cycle Process.

PubMed

Radin Umar, Radin Zaid; Sommerich, Carolyn M; Lavender, Steve A; Sanders, Elizabeth; Evans, Kevin D

2018-05-14

Sound workplace ergonomics and safety-related interventions may be resisted by employees, and this may be detrimental to multiple stakeholders. Understanding fundamental aspects of decision making, behavioral change, and learning cycles may provide insights into pathways influencing employees' acceptance of interventions. This manuscript reviews published literature on thinking processes and other topics relevant to decision making and incorporates the findings into two new conceptual frameworks of the workplace change adoption process. Such frameworks are useful for thinking about adoption in different ways and testing changes to traditional intervention implementation processes. Moving forward, it is recommended that future research focuses on systematic exploration of implementation process activities that integrate principles from the research literature on sensemaking, decision making, and learning processes. Such exploration may provide the groundwork for development of specific implementation strategies that are theoretically grounded and provide a revised understanding of how successful intervention adoption processes work.

Performance measurement integrated information framework in e-Manufacturing

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Needs and challenges for assessing the environmental impacts of engineered nanomaterials (ENMs)

PubMed Central

Romero-Franco, Michelle; Godwin, Hilary A; Bilal, Muhammad

2017-01-01

The potential environmental impact of nanomaterials is a critical concern and the ability to assess these potential impacts is top priority for the progress of sustainable nanotechnology. Risk assessment tools are needed to enable decision makers to rapidly assess the potential risks that may be imposed by engineered nanomaterials (ENMs), particularly when confronted by the reality of limited hazard or exposure data. In this review, we examine a range of available risk assessment frameworks considering the contexts in which different stakeholders may need to assess the potential environmental impacts of ENMs. Assessment frameworks and tools that are suitable for the different decision analysis scenarios are then identified. In addition, we identify the gaps that currently exist between the needs of decision makers, for a range of decision scenarios, and the abilities of present frameworks and tools to meet those needs. PMID:28546894

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

PubMed

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

2004-01-01

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

Improving client-centred care and services: the role of front/back-office configurations.

PubMed

Broekhuis, Manda; de Blok, Carolien; Meijboom, Bert

2009-05-01

This paper is a report of a study conducted to explore the application of designing front- and back-office work resulting in efficient client-centred care in healthcare organizations that supply home care, welfare and domestic services. Front/back-office configurations reflect a neglected domain of design decisions in the development of more client-centred processes and structures without incurring major cost increases. Based on a literature search, a framework of four front/back-office configurations was constructed. To illustrate the usefulness of this framework, a single, longitudinal case study was performed in a large organization, which provides home care, welfare and domestic services for a sustained period (2005-2006). The case study illustrates how front/back-office design decisions are related to the complexity of the clients' demands and the strategic objectives of an organization. The constructed framework guides the practical development of front/back-office designs, and shows how each design contributes differently to such performance objectives as quality, speed and efficiency. The front/back-office configurations presented comprise an important first step in elaborating client-centred care and service provision to the operational level. It helps healthcare organizations to become more responsive and to provide efficient client-centred care and services when approaching demand in a well-tuned manner. In addition to its applicability in home care, we believe that a deliberate front/back-office configuration also has potential in other fields of health care.

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

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.

Tensions between policy and practice: A qualitative analysis of decisions regarding compulsory admission to psychiatric hospital.

PubMed

Fistein, Elizabeth C; Clare, Isabel C H; Redley, Marcus; Holland, Anthony J

2016-01-01

The use of detention for psychiatric treatment is widespread and sometimes necessary. International human rights law requires a legal framework to safeguard the rights to liberty and personal integrity by preventing arbitrary detention. However, research suggests that extra-legal factors may influence decisions to detain. This article presents observational and interview data to describe how decisions to detain are made in practice in one jurisdiction (England and Wales) where a tension between policy and practice has been described. The analysis shows that practitioners mould the law into 'practical criteria' that appear to form a set of operational criteria for identifying cases to which the principle of soft paternalism may be applied. Most practitioners also appear willing, albeit often reluctantly, to depart from their usual reliance on the principle of soft paternalism and authorise detention of people with the capacity to refuse treatment, in order to prevent serious harm. We propose a potential resolution for the tension between policy and practice: two separate legal frameworks to authorise detention, one with a suitable test of capacity, used to enact soft paternalism, and the other to provide legal justification for detention for psychiatric treatment of the small number of people who retain decision-making capacity but nonetheless choose to place others at risk by refusing treatment. This separation of detention powers into two systems, according to the principle that justifies the use of detention would be intellectually coherent, consistent with human rights instruments and, being consistent with the apparent moral sentiments of practitioners, less prone to idiosyncratic interpretations in practice. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Decision-making theories and their usefulness to the midwifery profession both in terms of midwifery practice and the education of midwives.

PubMed

Jefford, Elaine; Fahy, Kathleen; Sundin, Deborah

2011-06-01

What are the strengths and limitations of existing Decision-Making Theories as a basis for guiding best practice clinical decision-making within a framework of midwifery philosophy? Each theory is compared in relation with how well they provide a teachable framework for midwifery clinical reasoning that is consistent with midwifery philosophy. Hypothetico-Deductive Theory, from which medical clinical reasoning is based; intuitive decision-making; Dual Processing Theory; The International Confederation of Midwives Clinical Decision-Making Framework; Australian Nursing and Midwifery Council Midwifery Practice Decisions Flowchart and Midwifery Practice. Best practice midwifery clinical Decision-Making Theory needs to give guidance about: (i) effective use of cognitive reasoning processes; (ii) how to include contextual and emotional factors; (iii) how to include the interests of the baby as an integral part of the woman; (iv) decision-making in partnership with woman; and (v) how to recognize/respond to clinical situations outside the midwife's legal/personal scope of practice. No existing Decision-Making Theory meets the needs of midwifery. Medical clinical reasoning has a good contribution to make in terms of cognitive reasoning processes. Two limitations of medical clinical reasoning are its reductionistic focus and privileging of reason to the exclusion of emotional and contextual factors. Hypothetico-deductive clinical reasoning is a necessary but insufficient condition for best practice clinical decision-making in midwifery. © 2011 Blackwell Publishing Asia Pty Ltd.

Advances in the Application of Decision Theory to Test-Based Decision Making.

ERIC Educational Resources Information Center

van der Linden, Wim J.

This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical Bayesian framework. Classification decisions with…

Multiple Criteria Decision Analysis (MCDA) for evaluating new medicines in Health Technology Assessment and beyond: The Advance Value Framework.

PubMed

Angelis, Aris; Kanavos, Panos

2017-09-01

Escalating drug prices have catalysed the generation of numerous "value frameworks" with the aim of informing payers, clinicians and patients on the assessment and appraisal process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions. In this paper, a Multiple Criteria Decision Analysis (MCDA) methodological process, based on Multi Attribute Value Theory (MAVT), is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down "value-focused thinking" approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers' concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory. The resulting value tree (Advance Value Tree) consists of three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative treatment options, assigning relative weights of importance to the criteria, and combining scores and weights. Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a structured and transparent way. Given its flexibility to meet diverse requirements and become readily adaptable across different settings, the Advance Value Framework could be offered as a decision-support tool for evaluators and payers to aid coverage and reimbursement of new medicines. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

NASA Astrophysics Data System (ADS)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

An online tool for Operational Probabilistic Drought Forecasting System (OPDFS): a Statistical-Dynamical Framework

NASA Astrophysics Data System (ADS)

Zarekarizi, M.; Moradkhani, H.; Yan, H.

2017-12-01

The Operational Probabilistic Drought Forecasting System (OPDFS) is an online tool recently developed at Portland State University for operational agricultural drought forecasting. This is an integrated statistical-dynamical framework issuing probabilistic drought forecasts monthly for the lead times of 1, 2, and 3 months. The statistical drought forecasting method utilizes copula functions in order to condition the future soil moisture values on the antecedent states. Due to stochastic nature of land surface properties, the antecedent soil moisture states are uncertain; therefore, data assimilation system based on Particle Filtering (PF) is employed to quantify the uncertainties associated with the initial condition of the land state, i.e. soil moisture. PF assimilates the satellite soil moisture data to Variable Infiltration Capacity (VIC) land surface model and ultimately updates the simulated soil moisture. The OPDFS builds on the NOAA's seasonal drought outlook by offering drought probabilities instead of qualitative ordinal categories and provides the user with the probability maps associated with a particular drought category. A retrospective assessment of the OPDFS showed that the forecasting of the 2012 Great Plains and 2014 California droughts were possible at least one month in advance. The OPDFS offers a timely assistance to water managers, stakeholders and decision-makers to develop resilience against uncertain upcoming droughts.

The Earth Data Analytic Services (EDAS) Framework

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch

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

Wang, Hong; Wang, Shaobu; Fan, Rui

This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it hasmore » been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient condition has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.« less

Science-based decision making in a high-risk energy production environment

NASA Astrophysics Data System (ADS)

Weiser, D. A.

2016-12-01

Energy production practices that may induce earthquakes require decisions about acceptable risk before projects begin. How much ground shaking, structural damage, infrastructure damage, or delay of geothermal power and other operations is tolerable? I review a few mitigation strategies as well as existing protocol in several U.S. states. Timely and accurate scientific information can assist in determining the costs and benefits of altering production parameters. These issues can also be addressed with probability estimates of adverse effects ("costs"), frequency of earthquakes of different sizes, and associated impacts of different magnitude earthquakes. When risk management decisions based on robust science are well-communicated to stakeholders, mitigation efforts benefit. Effective communications elements include a) the risks and benefits of different actions (e.g. using a traffic light protocol); b) the factors to consider when determining acceptable risk; and c) the probability of different magnitude events. I present a case example for The Geysers geothermal field in California, to discuss locally "acceptable" and "unacceptable" earthquakes and share nearby communities' responses to smaller and larger magnitude earthquakes. I use the USGS's "Did You Feel It?" data archive to sample how often felt events occur, and how many of those are above acceptable magnitudes (to both local residents and operators). Using this information, I develop a science-based decision-making framework, in the case of potentially risky earthquakes, for lessening seismic risk and other negative consequences. This includes assessing future earthquake probabilities based on past earthquake records. One of my goals is to help characterize uncertainties in a way that they can be managed; to this end, I present simple and accessible approaches that can be used in the decision making process.

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

Shahidehpour, Mohammad

Integrating 20% or more wind energy into the system and transmitting large sums of wind energy over long distances will require a decision making capability that can handle very large scale power systems with tens of thousands of buses and lines. There is a need to explore innovative analytical and implementation solutions for continuing reliable operations with the most economical integration of additional wind energy in power systems. A number of wind integration solution paths involve the adoption of new operating policies, dynamic scheduling of wind power across interties, pooling integration services, and adopting new transmission scheduling practices. Such practicesmore » can be examined by the decision tool developed by this project. This project developed a very efficient decision tool called Wind INtegration Simulator (WINS) and applied WINS to facilitate wind energy integration studies. WINS focused on augmenting the existing power utility capabilities to support collaborative planning, analysis, and wind integration project implementations. WINS also had the capability of simulating energy storage facilities so that feasibility studies of integrated wind energy system applications can be performed for systems with high wind energy penetrations. The development of WINS represents a major expansion of a very efficient decision tool called POwer Market Simulator (POMS), which was developed by IIT and has been used extensively for power system studies for decades. Specifically, WINS provides the following superiorities; (1) An integrated framework is included in WINS for the comprehensive modeling of DC transmission configurations, including mono-pole, bi-pole, tri-pole, back-to-back, and multi-terminal connection, as well as AC/DC converter models including current source converters (CSC) and voltage source converters (VSC); (2) An existing shortcoming of traditional decision tools for wind integration is the limited availability of user interface, i.e., decision results are often text-based demonstrations. WINS includes a powerful visualization tool and user interface capability for transmission analyses, planning, and assessment, which will be of great interest to power market participants, power system planners and operators, and state and federal regulatory entities; and (3) WINS can handle extended transmission models for wind integration studies. WINS models include limitations on transmission flow as well as bus voltage for analyzing power system states. The existing decision tools often consider transmission flow constraints (dc power flow) alone which could result in the over-utilization of existing resources when analyzing wind integration. WINS can be used to assist power market participants including transmission companies, independent system operators, power system operators in vertically integrated utilities, wind energy developers, and regulatory agencies to analyze economics, security, and reliability of various options for wind integration including transmission upgrades and the planning of new transmission facilities. WINS can also be used by industry for the offline training of reliability and operation personnel when analyzing wind integration uncertainties, identifying critical spots in power system operation, analyzing power system vulnerabilities, and providing credible decisions for examining operation and planning options for wind integration. Researches in this project on wind integration included (1) Development of WINS; (2) Transmission Congestion Analysis in the Eastern Interconnection; (3) Analysis of 2030 Large-Scale Wind Energy Integration in the Eastern Interconnection; (4) Large-scale Analysis of 2018 Wind Energy Integration in the Eastern U.S. Interconnection. The research resulted in 33 papers, 9 presentations, 9 PhD degrees, 4 MS degrees, and 7 awards. The education activities in this project on wind energy included (1) Wind Energy Training Facility Development; (2) Wind Energy Course Development.« less

Shared Decisions That Count.

ERIC Educational Resources Information Center

Schlechty, Phillip C.

1993-01-01

Advocates of participatory leadership, site-based management, and decentralization often assume that changing decision-making group composition will automatically improve the quality of decisions being made. Stakeholder satisfaction does not guarantee quality results. This article offers a framework for moving the decision-making discussion from…

Assessing the value of post-processed state-of-the-art long-term weather forecast ensembles for agricultural water management mediated by farmers' behaviours

NASA Astrophysics Data System (ADS)

Li, Yu; Giuliani, Matteo; Castelletti, Andrea

2016-04-01

Recent advances in modelling of coupled ocean-atmosphere dynamics significantly improved skills of long-term climate forecast from global circulation models (GCMs). These more accurate weather predictions are supposed to be a valuable support to farmers in optimizing farming operations (e.g. crop choice, cropping and watering time) and for more effectively coping with the adverse impacts of climate variability. Yet, assessing how actually valuable this information can be to a farmer is not straightforward and farmers' response must be taken into consideration. Indeed, in the context of agricultural systems potentially useful forecast information should alter stakeholders' expectation, modify their decisions, and ultimately produce an impact on their performance. Nevertheless, long-term forecast are mostly evaluated in terms of accuracy (i.e., forecast quality) by comparing hindcast and observed values and only few studies investigated the operational value of forecast looking at the gain of utility within the decision-making context, e.g. by considering the derivative of forecast information, such as simulated crop yields or simulated soil moisture, which are essential to farmers' decision-making process. In this study, we contribute a step further in the assessment of the operational value of long-term weather forecasts products by embedding these latter into farmers' behavioral models. This allows a more critical assessment of the forecast value mediated by the end-users' perspective, including farmers' risk attitudes and behavioral patterns. Specifically, we evaluate the operational value of thirteen state-of-the-art long-range forecast products against climatology forecast and empirical prediction (i.e. past year climate and historical average) within an integrated agronomic modeling framework embedding an implicit model of the farmers' decision-making process. Raw ensemble datasets are bias-corrected and downscaled using a stochastic weather generator, in order to address the mismatch of the spatio-temporal scale between forecast data from GCMs and our model. For each product, the experiment is composed by two cascade simulations: 1) an ex-ante simulation using forecast data, and 2) an ex-post simulation with observations. Multi-year simulations are performed to account for climate variability, and the operational value of the different forecast products is evaluated against the perfect foresight on the basis of expected crop productivity as well as the final decisions under different decision-making criterions. Our results show that not all products generate beneficial effects to farmers' performance, and the forecast errors might be amplified due to farmers' decision-making process and risk attitudes, yielding little or even worse performance compared with the empirical approaches.

Simultaneous Optimization of Decisions Using a Linear Utility Function.

ERIC Educational Resources Information Center

Vos, Hans J.

1990-01-01

An approach is presented to simultaneously optimize decision rules for combinations of elementary decisions through a framework derived from Bayesian decision theory. The developed linear utility model for selection-mastery decisions was applied to a sample of 43 first year medical students to illustrate the procedure. (SLD)

Exploring Investor Decisions in a Behavioral Finance Framework

ERIC Educational Resources Information Center

Hayes, Suzanne K.

2010-01-01

The first objective of this article is to increase awareness and understanding of individual decision-making biases. The second is to provide FCS professionals with strategies to improve consumer financial decisions. Individual decision biases are presented within the context of a seven-stage decision process. Proactive consumer educators using a…

Using ecosystem services in decision-making to support sustainable development: Critiques, model development, a case study, and perspectives.

PubMed

Zagonari, Fabio

2016-04-01

In this paper, I propose a general, consistent, and operational approach that accounts for ecosystem services in a decision-making context: I link ecosystem services to sustainable development criteria; adopt multi-criteria analysis to measure ecosystem services, with weights provided by stakeholders used to account for equity issues; apply both temporal and spatial discount rates; and adopt a technique to order performance of the possible solutions based on their similarity to an ideal solution (TOPSIS) to account for uncertainty about the parameters and functions. Applying this approach in a case study of an offshore research platform in Italy (CNR Acqua Alta) revealed that decisions depend non-linearly on the degree of loss aversion, to a smaller extent on a global focus (as opposed to a local focus), and to the smallest extent on social concerns (as opposed to economic or environmental concerns). Application of the general model to the case study leads to the conclusion that the ecosystem services framework is likely to be less useful in supporting decisions than in identifying the crucial features on which decisions depend, unless experts from different disciplines are involved, stakeholders are represented, and experts and stakeholders achieve mutual understanding. Copyright © 2016 Elsevier B.V. All rights reserved.

Providing guidance for genomics-based cancer treatment decisions: insights from stakeholder engagement for post-prostatectomy radiation therapy.

PubMed

Abe, James; Lobo, Jennifer M; Trifiletti, Daniel M; Showalter, Timothy N

2017-08-24

Despite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making. We report findings from a stakeholder engagement program that aimed to develop a framework for using Markov models with individualized model inputs, including genomics-based estimates of cancer recurrence probability, to generate personalized decision aids for prostate cancer patients faced with radiation therapy treatment decisions after prostatectomy. We engaged a total of 22 stakeholders, including: prostate cancer patients, urological surgeons, radiation oncologists, genomic testing industry representatives, and biomedical informatics faculty. Slides were at each meeting to provide background information regarding the analytical framework. Participants were invited to provide feedback during the meeting, including revising the overall project aims. Stakeholder meeting content was reviewed and summarized by stakeholder group and by theme. The majority of stakeholder suggestions focused on aspects of decision aid design and formatting. Stakeholders were enthusiastic about the potential value of using decision analysis modeling with personalized model inputs for cancer recurrence risk, as well as competing risks from age and comorbidities, to generate a patient-centered tool to assist decision-making. Stakeholders did not view privacy considerations as a major barrier to the proposed decision aid program. A common theme was that decision aids should be portable across multiple platforms (electronic and paper), should allow for interaction by the user to adjust model inputs iteratively, and available to patients both before and during consult appointments. Emphasis was placed on the challenge of explaining the model's composite result of quality-adjusted life years. A range of stakeholders provided valuable insights regarding the design of a personalized decision aid program, based upon Markov modeling with individualized model inputs, to provide a patient-centered framework to support for genomic-based treatment decisions for cancer patients. The guidance provided by our stakeholders may be broadly applicable to the communication of genomic test results to patients in a patient-centered fashion that supports effective shared decision-making that represents a spectrum of personal factors such as age, medical comorbidities, and individual priorities and values.

Designing a Clinical Framework to Guide Gross Motor Intervention Decisions for Infants and Young Children with Hypotonia

ERIC Educational Resources Information Center

Darrah, Johanna; O'Donnell, Maureen; Lam, Joyce; Story, Maureen; Wickenheiser, Diane; Xu, Kaishou; Jin, Xiaokun

2013-01-01

Clinical practice frameworks are a valuable component of clinical education, promoting informed clinical decision making based on the best available evidence and/or clinical experience. They encourage standardized intervention approaches and evaluation of practice. Based on an international project to support the development of an enhanced service…

Fire Effects Planning Framework: A user's guide

Treesearch

A. Black; T. Opperman

2005-01-01

Each decision to suppress fire reinforces a feedback cycle in which fuels continue to accumulate, risk escalates, and the tendency to suppress fires grows (Miller and others, 2003). Existing decision-support tools focus primarily on the negative consequences of fire. This guide outlines a framework managers can use to (1) identify key areas of fire risk and (2)...

Keeping Teachers in the Center: A Framework of Data-Driven Decision-Making

ERIC Educational Resources Information Center

Light, Daniel; Wexler, Dara H.; Heinze, Juliette

2004-01-01

The Education Development Center's Center for Children and Technology (CCT) conducted a three year study of a large-scale data reporting system, developed by the Grow Network for New York City's Department of Education. This paper presents a framework based on two years of research exploring the intersection of decision-support technologies,…

In Search of an Identity: Air Force Core Competencies

DTIC Science & Technology

1997-06-01

for connecting core competencies to both inside and outside the service . Core competencies have become a decision making framework for the Air Force...Proposed Intra– Service Relationship ................................................................. 76 Figure 2. Proposed Inter- service and Joint...connecting core competencies to both inside and outside the service . Core competencies have become a decision making framework for the Air Force. They

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.

A contemporary approach to validity arguments: a practical guide to Kane's framework.

PubMed

Cook, David A; Brydges, Ryan; Ginsburg, Shiphra; Hatala, Rose

2015-06-01

Assessment is central to medical education and the validation of assessments is vital to their use. Earlier validity frameworks suffer from a multiplicity of types of validity or failure to prioritise among sources of validity evidence. Kane's framework addresses both concerns by emphasising key inferences as the assessment progresses from a single observation to a final decision. Evidence evaluating these inferences is planned and presented as a validity argument. We aim to offer a practical introduction to the key concepts of Kane's framework that educators will find accessible and applicable to a wide range of assessment tools and activities. All assessments are ultimately intended to facilitate a defensible decision about the person being assessed. Validation is the process of collecting and interpreting evidence to support that decision. Rigorous validation involves articulating the claims and assumptions associated with the proposed decision (the interpretation/use argument), empirically testing these assumptions, and organising evidence into a coherent validity argument. Kane identifies four inferences in the validity argument: Scoring (translating an observation into one or more scores); Generalisation (using the score[s] as a reflection of performance in a test setting); Extrapolation (using the score[s] as a reflection of real-world performance), and Implications (applying the score[s] to inform a decision or action). Evidence should be collected to support each of these inferences and should focus on the most questionable assumptions in the chain of inference. Key assumptions (and needed evidence) vary depending on the assessment's intended use or associated decision. Kane's framework applies to quantitative and qualitative assessments, and to individual tests and programmes of assessment. Validation focuses on evaluating the key claims, assumptions and inferences that link assessment scores with their intended interpretations and uses. The Implications and associated decisions are the most important inferences in the validity argument. © 2015 John Wiley & Sons Ltd.

Validation of educational assessments: a primer for simulation and beyond.

PubMed

Cook, David A; Hatala, Rose

2016-01-01

Simulation plays a vital role in health professions assessment. This review provides a primer on assessment validation for educators and education researchers. We focus on simulation-based assessment of health professionals, but the principles apply broadly to other assessment approaches and topics. Validation refers to the process of collecting validity evidence to evaluate the appropriateness of the interpretations, uses, and decisions based on assessment results. Contemporary frameworks view validity as a hypothesis, and validity evidence is collected to support or refute the validity hypothesis (i.e., that the proposed interpretations and decisions are defensible). In validation, the educator or researcher defines the proposed interpretations and decisions, identifies and prioritizes the most questionable assumptions in making these interpretations and decisions (the "interpretation-use argument"), empirically tests those assumptions using existing or newly-collected evidence, and then summarizes the evidence as a coherent "validity argument." A framework proposed by Messick identifies potential evidence sources: content, response process, internal structure, relationships with other variables, and consequences. Another framework proposed by Kane identifies key inferences in generating useful interpretations: scoring, generalization, extrapolation, and implications/decision. We propose an eight-step approach to validation that applies to either framework: Define the construct and proposed interpretation, make explicit the intended decision(s), define the interpretation-use argument and prioritize needed validity evidence, identify candidate instruments and/or create/adapt a new instrument, appraise existing evidence and collect new evidence as needed, keep track of practical issues, formulate the validity argument, and make a judgment: does the evidence support the intended use? Rigorous validation first prioritizes and then empirically evaluates key assumptions in the interpretation and use of assessment scores. Validation science would be improved by more explicit articulation and prioritization of the interpretation-use argument, greater use of formal validation frameworks, and more evidence informing the consequences and implications of assessment.

A model of individualized canonical microcircuits supporting cognitive operations

PubMed Central

Peterson, Andre D. H.; Haueisen, Jens; Knösche, Thomas R.

2017-01-01

Major cognitive functions such as language, memory, and decision-making are thought to rely on distributed networks of a large number of basic elements, called canonical microcircuits. In this theoretical study we propose a novel canonical microcircuit model and find that it supports two basic computational operations: a gating mechanism and working memory. By means of bifurcation analysis we systematically investigate the dynamical behavior of the canonical microcircuit with respect to parameters that govern the local network balance, that is, the relationship between excitation and inhibition, and key intrinsic feedback architectures of canonical microcircuits. We relate the local behavior of the canonical microcircuit to cognitive processing and demonstrate how a network of interacting canonical microcircuits enables the establishment of spatiotemporal sequences in the context of syntax parsing during sentence comprehension. This study provides a framework for using individualized canonical microcircuits for the construction of biologically realistic networks supporting cognitive operations. PMID:29200435

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.; Hooten, Mevin B.; Dubovsky, James A.; Drewien, Roderick C.

2015-01-01

Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment.Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression.Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect.Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond.Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

Optimization and resilience in natural resources management

USGS Publications Warehouse

Williams, Byron K.; Johnson, Fred A.

2015-01-01

We consider the putative tradeoff between optimization and resilience in the management of natural resources, using a framework that incorporates different sources of uncertainty that are common in natural resources management. We address one-time decisions, and then expand the decision context to the more complex problem of iterative decision making. For both cases we focus on two key sources of uncertainty: partial observability of system state and uncertainty as to system dynamics. Optimal management strategies will vary considerably depending on the timeframe being considered and the amount and quality of information that is available to characterize system features and project the consequences of potential decisions. But in all cases an optimal decision making framework, if properly identified and focused, can be useful in recognizing sound decisions. We argue that under the conditions of deep uncertainty that characterize many resource systems, an optimal decision process that focuses on robustness does not automatically induce a loss of resilience.

Using an ecological ethics framework to make decisions about the relocation of wildlife

USGS Publications Warehouse

McCoy, E.D.; Berry, K.

2008-01-01

Relocation is an increasingly prominent conservation tool for a variety of wildlife, but the technique also is controversial, even among conservation practitioners. An organized framework for addressing the moral dilemmas often accompanying conservation actions such as relocation has been lacking. Ecological ethics may provide such a framework and appears to be an important step forward in aiding ecological researchers and biodiversity managers to make difficult moral choices. A specific application of this framework can make the reasoning process more transparent and give more emphasis to the strong sentiments about non-human organisms held by many potential users. Providing an example of the application of the framework may also increase the appeal of the reasoning process to ecological researchers and biodiversity managers. Relocation as a conservation action can be accompanied by a variety of moral dilemmas that reflect the interconnection of values, ethical positions, and conservation decisions. A model that is designed to address moral dilemmas arising from relocation of humans provides/demonstrates/illustrates a possible way to apply the ecological ethics framework and to involve practicing conservationists in the overall decision-making process. ?? 2008 Springer Science+Business Media B.V.