Watershed Management Optimization Support Tool (WMOST) v3: Theoretical Documentation

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that facilitates integrated water management at the local or small watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed context, accounting fo...

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.

An agent architecture for an integrated forest ecosystem management decision support system

Treesearch

Donald Nute; Walter D. Potter; Mayukh Dass; Astrid Glende; Frederick Maier; Hajime Uchiyama; Jin Wang; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher

2003-01-01

A wide variety of software tools are available to support decision in the management of forest ecosystems. These tools include databases, growth and yield models, wildlife models, silvicultural expert systems, financial models, geographical informations systems, and visualization tools. Typically, each of these tools has its own complex interface and data format. To...

A method for integrating multiple components in a decision support system

Treesearch

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

2005-01-01

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

Integrating climatic and fuels information into National Fire Risk Decision Support Tools

Treesearch

W. Cooke; V. Anantharaj; C. Wax; J. Choi; K. Grala; M. Jolly; G.P. Dixon; J. Dyer; D.L. Evans; G.B. Goodrich

2007-01-01

The Wildland Fire Assessment System (WFAS) is a component of the U.S. Department of Agriculture, Forest Service Decision Support Systems (DSS) that support fire potential modeling. Fire potential models for Mississippi and for Eastern fire environments have been developed as part of a National Aeronautic and Space Agency-funded study aimed at demonstrating the utility...

Developing CCUS system models to handle the complexity of multiple sources and sinks: An update on Tasks 5.3 and 5.4

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

Middleton, Richard Stephen

2017-05-22

This presentation is part of US-China Clean Coal project and describes the impact of power plant cycling, techno economic modeling of combined IGCC and CCS, integrated capacity generation decision making for power utilities, and a new decision support tool for integrated assessment of CCUS.

Extending BPM Environments of Your Choice with Performance Related Decision Support

NASA Astrophysics Data System (ADS)

Fritzsche, Mathias; Picht, Michael; Gilani, Wasif; Spence, Ivor; Brown, John; Kilpatrick, Peter

What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools, process optimizations or a combination of such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.

Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review

USDA-ARS?s Scientific Manuscript database

Decision-support systems (DDSs) are techniques that help decision makers utilize models to solve problems under complex and uncertain conditions. Predicting conditions that warrant intervention is a key tenet of the concept of integrated pest management (IPM) with the use of expert systems and pest ...

GLIMPSE: An integrated assessment model-based tool for coordinated energy and environmental planning

EPA Science Inventory

Dan Loughlin will describe the GCAM-USA integrated assessment model and how that model is being improved and integrated into the GLIMPSE decision support system. He will also demonstrate the application of the model to evaluate the emissions and health implications of hypothetica...

A novel personal health system with integrated decision support and guidance for the management of chronic liver disease.

PubMed

Kiefer, Stephan; Schäfer, Michael; Bransch, Marco; Brimmers, Peter; Bartolomé, Diego; Baños, Janie; Orr, James; Jones, Dave; Jara, Maximilian; Stockmann, Martin

2014-01-01

A personal health system platform for the management of patients with chronic liver disease that incorporates a novel approach to integrate decision support and guidance through care pathways for patients and their doctors is presented in this paper. The personal health system incorporates an integrated decision support engine that guides patients and doctors through the management of the disease by issuing tasks and providing recommendations to both the care team and the patient and by controlling the execution of a Care Flow Plan based on the results of tasks and the monitored health status of the patient. This Care Flow Plan represents a formal, business process based model of disease management designed off-line by domain experts on the basis of clinical guidelines, knowledge of care pathways and an organisational model for integrated, patient-centred care. In this way, remote monitoring and treatment are dynamically adapted to the patient's actual condition and clinical symptoms and allow flexible delivery of care with close integration of specialists, therapists and care-givers.

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.

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

NASA Astrophysics Data System (ADS)

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

2007-06-01

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

Data-Driven Decision Making in Community Colleges: An Integrative Model for Institutional Effectiveness

ERIC Educational Resources Information Center

Callery, Claude Adam

2012-01-01

This qualitative study identified the best practices utilized by community colleges to achieve systemic and cultural agreement in support of the integration of institutional effectiveness measures (key performance indicators) to inform decision making. In addition, the study identifies the relevant motives, organizational structure, and processes…

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...

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

PubMed

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

2016-09-01

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

Integrated Modeling and Simulation Verification, Validation, and Accreditation Strategy for Exploration Systems Mission Directorate

NASA Technical Reports Server (NTRS)

Hale, Joseph P.

2006-01-01

Models and simulations (M&S) are critical resources in the exploration of space. They support program management, systems engineering, integration, analysis, test, and operations and provide critical information and data supporting key analyses and decisions (technical, cost and schedule). Consequently, there is a clear need to establish a solid understanding of M&S strengths and weaknesses, and the bounds within which they can credibly support decision-making. Their usage requires the implementation of a rigorous approach to verification, validation and accreditation (W&A) and establishment of formal process and practices associated with their application. To ensure decision-making is suitably supported by information (data, models, test beds) from activities (studies, exercises) from M&S applications that are understood and characterized, ESMD is establishing formal, tailored W&A processes and practices. In addition, to ensure the successful application of M&S within ESMD, a formal process for the certification of analysts that use M&S is being implemented. This presentation will highlight NASA's Exploration Systems Mission Directorate (ESMD) management approach for M&S W&A to ensure decision-makers receive timely information on the model's fidelity, credibility, and quality.

Evaluating the State of Water Management in the Rio Grande/Bravo Basin

NASA Astrophysics Data System (ADS)

Ortiz Partida, Jose Pablo; Sandoval-Solis, Samuel; Diaz Gomez, Romina

2017-04-01

Water resource modeling tools have been developed for many different regions and sub-basins of the Rio Grande/Bravo (RGB). Each of these tools has specific objectives, whether it is to explore drought mitigation alternatives, conflict resolution, climate change evaluation, tradeoff and economic synergies, water allocation, reservoir operations, or collaborative planning. However, there has not been an effort to integrate different available tools, or to link models developed for specific reaches into a more holistic watershed decision-support tool. This project outlines promising next steps to meet long-term goals of improved decision support tools and modeling. We identify, describe, and synthesize water resources management practices in the RGB basin and available water resources models and decision support tools that represent the RGB and the distribution of water for human and environmental uses. The extent body of water resources modeling is examined from a perspective of environmental water needs and water resources management and thereby allows subsequent prioritization of future research and monitoring needs for the development of river system modeling tools. This work communicates the state of the RGB science to diverse stakeholders, researchers, and decision-makers. The products of this project represent a planning tool to support an integrated water resources management framework to maximize economic and social welfare without compromising vital ecosystems.

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.

Watershed System Model: The Essentials to Model Complex Human-Nature System at the River Basin Scale

NASA Astrophysics Data System (ADS)

Li, Xin; Cheng, Guodong; Lin, Hui; Cai, Ximing; Fang, Miao; Ge, Yingchun; Hu, Xiaoli; Chen, Min; Li, Weiyue

2018-03-01

Watershed system models are urgently needed to understand complex watershed systems and to support integrated river basin management. Early watershed modeling efforts focused on the representation of hydrologic processes, while the next-generation watershed models should represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support. We propose a new modeling framework and discuss the know-how approach to incorporate emerging knowledge into integrated models through data exchange interfaces. We argue that the modeling environment is a useful tool to enable effective model integration, as well as create domain-specific models of river basin systems. The grand challenges in developing next-generation watershed system models include but are not limited to providing an overarching framework for linking natural and social sciences, building a scientifically based decision support system, quantifying and controlling uncertainties, and taking advantage of new technologies and new findings in the various disciplines of watershed science. The eventual goal is to build transdisciplinary, scientifically sound, and scale-explicit watershed system models that are to be codesigned by multidisciplinary communities.

Bioinformatics for transporter pharmacogenomics and systems biology: data integration and modeling with UML.

PubMed

Yan, Qing

2010-01-01

Bioinformatics is the rational study at an abstract level that can influence the way we understand biomedical facts and the way we apply the biomedical knowledge. Bioinformatics is facing challenges in helping with finding the relationships between genetic structures and functions, analyzing genotype-phenotype associations, and understanding gene-environment interactions at the systems level. One of the most important issues in bioinformatics is data integration. The data integration methods introduced here can be used to organize and integrate both public and in-house data. With the volume of data and the high complexity, computational decision support is essential for integrative transporter studies in pharmacogenomics, nutrigenomics, epigenetics, and systems biology. For the development of such a decision support system, object-oriented (OO) models can be constructed using the Unified Modeling Language (UML). A methodology is developed to build biomedical models at different system levels and construct corresponding UML diagrams, including use case diagrams, class diagrams, and sequence diagrams. By OO modeling using UML, the problems of transporter pharmacogenomics and systems biology can be approached from different angles with a more complete view, which may greatly enhance the efforts in effective drug discovery and development. Bioinformatics resources of membrane transporters and general bioinformatics databases and tools that are frequently used in transporter studies are also collected here. An informatics decision support system based on the models presented here is available at http://www.pharmtao.com/transporter . The methodology developed here can also be used for other biomedical fields.

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

EPA Science Inventory

The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteo...

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients.

PubMed

Velickovski, Filip; Ceccaroni, Luigi; Roca, Josep; Burgos, Felip; Galdiz, Juan B; Marina, Nuria; Lluch-Ariet, Magí

2014-11-28

The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems.

Clinical Decision Support Systems (CDSS) for preventive management of COPD patients

PubMed Central

2014-01-01

Background The use of information and communication technologies to manage chronic diseases allows the application of integrated care pathways, and the optimization and standardization of care processes. Decision support tools can assist in the adherence to best-practice medicine in critical decision points during the execution of a care pathway. Objectives The objectives are to design, develop, and assess a clinical decision support system (CDSS) offering a suite of services for the early detection and assessment of chronic obstructive pulmonary disease (COPD), which can be easily integrated into a healthcare providers' work-flow. Methods The software architecture model for the CDSS, interoperable clinical-knowledge representation, and inference engine were designed and implemented to form a base CDSS framework. The CDSS functionalities were iteratively developed through requirement-adjustment/development/validation cycles using enterprise-grade software-engineering methodologies and technologies. Within each cycle, clinical-knowledge acquisition was performed by a health-informatics engineer and a clinical-expert team. Results A suite of decision-support web services for (i) COPD early detection and diagnosis, (ii) spirometry quality-control support, (iii) patient stratification, was deployed in a secured environment on-line. The CDSS diagnostic performance was assessed using a validation set of 323 cases with 90% specificity, and 96% sensitivity. Web services were integrated in existing health information system platforms. Conclusions Specialized decision support can be offered as a complementary service to existing policies of integrated care for chronic-disease management. The CDSS was able to issue recommendations that have a high degree of accuracy to support COPD case-finding. Integration into healthcare providers' work-flow can be achieved seamlessly through the use of a modular design and service-oriented architecture that connect to existing health information systems. PMID:25471545

An Intelligent Decision Support System for Workforce Forecast

DTIC Science & Technology

2011-01-01

ARIMA ) model to forecast the demand for construction skills in Hong Kong. This model was based...Decision Trees ARIMA Rule Based Forecasting Segmentation Forecasting Regression Analysis Simulation Modeling Input-Output Models LP and NLP Markovian...data • When results are needed as a set of easily interpretable rules 4.1.4 ARIMA Auto-regressive, integrated, moving-average ( ARIMA ) models

Efficient GIS-based model-driven method for flood risk management and its application in central China

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhou, J.; Song, L.; Zou, Q.; Guo, J.; Wang, Y.

2014-02-01

In recent years, an important development in flood management has been the focal shift from flood protection towards flood risk management. This change greatly promoted the progress of flood control research in a multidisciplinary way. Moreover, given the growing complexity and uncertainty in many decision situations of flood risk management, traditional methods, e.g., tight-coupling integration of one or more quantitative models, are not enough to provide decision support for managers. Within this context, this paper presents a beneficial methodological framework to enhance the effectiveness of decision support systems, through the dynamic adaptation of support regarding the needs of the decision-maker. In addition, we illustrate a loose-coupling technical prototype for integrating heterogeneous elements, such as multi-source data, multidisciplinary models, GIS tools and existing systems. The main innovation is the application of model-driven concepts, which put the system in a state of continuous iterative optimization. We define the new system as a model-driven decision support system (MDSS ). Two characteristics that differentiate the MDSS are as follows: (1) it is made accessible to non-technical specialists; and (2) it has a higher level of adaptability and compatibility. Furthermore, the MDSS was employed to manage the flood risk in the Jingjiang flood diversion area, located in central China near the Yangtze River. Compared with traditional solutions, we believe that this model-driven method is efficient, adaptable and flexible, and thus has bright prospects of application for comprehensive flood risk management.

What perceptions do patients have of decision making (DM)? Toward an integrative patient-centered care model. A qualitative study using focus-group interviews.

PubMed

Moreau, Alain; Carol, Laurent; Dedianne, Marie Cécile; Dupraz, Christian; Perdrix, Corinne; Lainé, Xavier; Souweine, Gilbert

2012-05-01

To understand patients' perceptions of decision making and identify relationships among decision-making models. This qualitative study was made up of four focus group interviews (elderly persons, users of health support groups, students, and rural inhabitants). Participants were asked to report their perceptions of decision making in three written clinical scenarios (hypertension, breast cancer, prostate cancer). The analysis was based on the principles of grounded theory. Most patients perceived decision making as shared decision making, a deliberative question-response interaction with the physician that allowed patients to be experts in obtaining clearer information, participating in the care process, and negotiating compromises with physician preferences. Requesting second opinions allowed patients to maintain control, even within the paternalistic model preferred by elderly persons. Facilitating factors (trust, qualitative non-verbal communication, time to think) and obstacles (serious/emergency situations, perceived inadequate scientific competence, problems making requests, fear of knowing) were also part of shared decision making. In the global concept of patient-centered care, shared decision making can be flexible and can integrate paternalistic and informative models. Physicians' expertise should be associated with biomedical and relational skills through listening to, informing, and advising patients, and by supporting patients' choices. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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.

Development and implementation of an Integrated Water Resources Management System (IWRMS)

NASA Astrophysics Data System (ADS)

Flügel, W.-A.; Busch, C.

2011-04-01

One of the innovative objectives in the EC project BRAHMATWINN was the development of a stakeholder oriented Integrated Water Resources Management System (IWRMS). The toolset integrates the findings of the project and presents it in a user friendly way for decision support in sustainable integrated water resources management (IWRM) in river basins. IWRMS is a framework, which integrates different types of basin information and which supports the development of IWRM options for climate change mitigation. It is based on the River Basin Information System (RBIS) data models and delivers a graphical user interface for stakeholders. A special interface was developed for the integration of the enhanced DANUBIA model input and the NetSyMod model with its Mulino decision support system (mulino mDss) component. The web based IWRMS contains and combines different types of data and methods to provide river basin data and information for decision support. IWRMS is based on a three tier software framework which uses (i) html/javascript at the client tier, (ii) PHP programming language to realize the application tier, and (iii) a postgresql/postgis database tier to manage and storage all data, except the DANUBIA modelling raw data, which are file based and registered in the database tier. All three tiers can reside on one or different computers and are adapted to the local hardware infrastructure. IWRMS as well as RBIS are based on Open Source Software (OSS) components and flexible and time saving access to that database is guaranteed by web-based interfaces for data visualization and retrieval. The IWRMS is accessible via the BRAHMATWINN homepage: http://www.brahmatwinn.uni-jena.de and a user manual for the RBIS is available for download as well.

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

Modeling paradigms for medical diagnostic decision support: a survey and future directions.

PubMed

Wagholikar, Kavishwar B; Sundararajan, Vijayraghavan; Deshpande, Ashok W

2012-10-01

Use of computer based decision tools to aid clinical decision making, has been a primary goal of research in biomedical informatics. Research in the last five decades has led to the development of Medical Decision Support (MDS) applications using a variety of modeling techniques, for a diverse range of medical decision problems. This paper surveys literature on modeling techniques for diagnostic decision support, with a focus on decision accuracy. Trends and shortcomings of research in this area are discussed and future directions are provided. The authors suggest that-(i) Improvement in the accuracy of MDS application may be possible by modeling of vague and temporal data, research on inference algorithms, integration of patient information from diverse sources and improvement in gene profiling algorithms; (ii) MDS research would be facilitated by public release of de-identified medical datasets, and development of opensource data-mining tool kits; (iii) Comparative evaluations of different modeling techniques are required to understand characteristics of the techniques, which can guide developers in choice of technique for a particular medical decision problem; and (iv) Evaluations of MDS applications in clinical setting are necessary to foster physicians' utilization of these decision aids.

Interactive modelling with stakeholders in two cases in flood management

NASA Astrophysics Data System (ADS)

Leskens, Johannes; Brugnach, Marcela

2013-04-01

New policies on flood management called Multi-Level Safety (MLS), demand for an integral and collaborative approach. The goal of MLS is to minimize flood risks by a coherent package of protection measures, crisis management and flood resilience measures. To achieve this, various stakeholders, such as water boards, municipalities and provinces, have to collaborate in composing these measures. Besides the many advances this integral and collaborative approach gives, the decision-making environment becomes also more complex. Participants have to consider more criteria than they used to do and have to take a wide network of participants into account, all with specific perspectives, cultures and preferences. In response, sophisticated models are developed to support decision-makers in grasping this complexity. These models provide predictions of flood events and offer the opportunity to test the effectiveness of various measures under different criteria. Recent model advances in computation speed and model flexibility allow stakeholders to directly interact with a hydrological hydraulic model during meetings. Besides a better understanding of the decision content, these interactive models are supposed to support the incorporation of stakeholder knowledge in modelling and to support mutual understanding of different perspectives of stakeholders To explore the support of interactive modelling in integral and collaborate policies, such as MLS, we tested a prototype of an interactive flood model (3Di) with respect to a conventional model (Sobek) in two cases. The two cases included the designing of flood protection measures in Amsterdam and a flood event exercise in Delft. These case studies yielded two main results. First, we observed that in the exploration phase of a decision-making process, stakeholders participated actively in interactive modelling sessions. This increased the technical understanding of complex problems and the insight in the effectiveness of various integral measures. Second, when measures became more concrete, the model played a minor role, as stakeholders were still bounded to goals, responsibilities and budgets of their own organization. Model results in this phase are mainly used in a political way to maximize the goals of particular organizations.

Development of a decision support system for analysis and solutions of prolonged standing in the workplace.

PubMed

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-06-01

Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially.

Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

PubMed Central

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-01-01

Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

Decision Making Under Uncertainty and Complexity: A Model-Based Scenario Approach to Supporting Integrated Water Resources Management

NASA Astrophysics Data System (ADS)

Liu, Y.; Gupta, H.; Wagener, T.; Stewart, S.; Mahmoud, M.; Hartmann, H.; Springer, E.

2007-12-01

Some of the most challenging issues facing contemporary water resources management are those typified by complex coupled human-environmental systems with poorly characterized uncertainties. In other words, major decisions regarding water resources have to be made in the face of substantial uncertainty and complexity. It has been suggested that integrated models can be used to coherently assemble information from a broad set of domains, and can therefore serve as an effective means for tackling the complexity of environmental systems. Further, well-conceived scenarios can effectively inform decision making, particularly when high complexity and poorly characterized uncertainties make the problem intractable via traditional uncertainty analysis methods. This presentation discusses the integrated modeling framework adopted by SAHRA, an NSF Science & Technology Center, to investigate stakeholder-driven water sustainability issues within the semi-arid southwestern US. The multi-disciplinary, multi-resolution modeling framework incorporates a formal scenario approach to analyze the impacts of plausible (albeit uncertain) alternative futures to support adaptive management of water resources systems. Some of the major challenges involved in, and lessons learned from, this effort will be discussed.

Investigating the Nexus of Climate, Energy, Water, and Land at Decision-Relevant Scales: The Platform for Regional Integrated Modeling and Analysis (PRIMA)

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

Kraucunas, Ian P.; Clarke, Leon E.; Dirks, James A.

2015-04-01

The Platform for Regional Integrated Modeling and Analysis (PRIMA) is an innovative modeling system developed at Pacific Northwest National Laboratory (PNNL) to simulate interactions among natural and human systems at scales relevant to regional decision making. PRIMA brings together state-of-the-art models of regional climate, hydrology, agriculture, socioeconomics, and energy systems using a flexible coupling approach. The platform can be customized to inform a variety of complex questions and decisions, such as the integrated evaluation of mitigation and adaptation options across a range of sectors. Research into stakeholder decision support needs underpins the platform's application to regional issues, including uncertainty characterization.more » Ongoing numerical experiments are yielding new insights into the interactions among human and natural systems on regional scales with an initial focus on the energy-land-water nexus in the upper U.S. Midwest. This paper focuses on PRIMA’s functional capabilities and describes some lessons learned to date about integrated regional modeling.« less

Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race.

PubMed

Warnke, Tom; Reinhardt, Oliver; Klabunde, Anna; Willekens, Frans; Uhrmacher, Adelinde M

2017-10-01

Individuals' decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for Linked Lives (ML3) to describe the diverse decision processes of linked lives succinctly in continuous time. The context of individuals is modelled by networks the individual is part of, such as family ties and other social networks. Central concepts, such as behaviour conditional on agent attributes, age-dependent behaviour, and stochastic waiting times, are tightly integrated in the language. Thereby, alternative decisions are modelled by concurrent processes that compete by stochastic race. Using a migration model, we demonstrate how this allows for compact description of complex decisions, here based on the Theory of Planned Behaviour. We describe the challenges for the simulation algorithm posed by stochastic race between multiple concurrent complex decisions.

The Integrated Medical Model

NASA Technical Reports Server (NTRS)

Butler, Douglas J.; Kerstman, Eric

2010-01-01

This slide presentation reviews the goals and approach for the Integrated Medical Model (IMM). The IMM is a software decision support tool that forecasts medical events during spaceflight and optimizes medical systems during simulations. It includes information on the software capabilities, program stakeholders, use history, and the software logic.

Decision Support for Integrated Energy-Water Planning

NASA Astrophysics Data System (ADS)

Tidwell, V. C.; William, H.; Klise, G.; Kobos, P. H.; Malczynski, L. A.

2008-12-01

Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 40% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. To meet their demand for water, proposed power plants must often target waterways and aquifers prone to overdraft or which may be home to environmentally sensitive species. Acquisition of water rights, permits and public support may therefore be a formidable hurdle when licensing new power plants. Given these current difficulties, what does the future hold when projected growth in population and the economy may require a 30% increase in power generation capacity by 2025? Technology solutions can only take us so far, as noted by the National Energy-Water Roadmap Exercise. This roadmap identified the need for long-term and integrated resource planning supported with scientifically credible models as a leading issue. To address this need a decision support framework is being developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to help identify potential trade-offs, and "best" alternatives among an overwhelming number of energy/water options and objectives. The decision support tool is comprised of three basic elements: a system dynamics model coupling the physical and economic systems important to integrated energy-water planning and management; an optimization toolbox; and a software wrapper that integrates the aforementioned elements along with additional external energy/water models, databases, and visualization products. An interactive interface allows direct interaction with the model and access to real-time results organized according to a variety of reference systems, e.g., from a political, watershed, or electric power grid perspective. With this unique synthesis of various perspectives, the tool may help highlight looming changes where policy, technical, economic, and data collection options may alleviate stresses within the underlying water systems that support electricity generation. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04- 94AL85000.

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.

Using an ecosystem service decision support tool to support ridge to reef management: An example of sediment reduction in west Maui, Hawaii

NASA Astrophysics Data System (ADS)

Falinski, K. A.; Oleson, K.; Htun, H.; Kappel, C.; Lecky, J.; Rowe, C.; Selkoe, K.; White, C.

2016-12-01

Faced with anthropogenic stressors and declining coral reef states, managers concerned with restoration and resilience of coral reefs are increasingly recognizing the need to take a ridge-to-reef, ecosystem-based approach. An ecosystem services framing can help managers move towards these goals, helping to illustrate trade-offs and opportunities of management actions in terms of their impacts on society. We describe a research program building a spatial ecosystem services-based decision-support tool, and being applied to guide ridge-to-reef management in a NOAA priority site in West Maui. We use multiple modeling methods to link biophysical processes to ecosystem services and their spatial flows and social values in an integrating platform. Modeled services include water availability, sediment retention, nutrient retention and carbon sequestration on land. A coral reef ecosystem service model is under development to capture the linkages between terrestrial and coastal ecosystem services. Valuation studies are underway to quantify the implications for human well-being. The tool integrates techniques from decision science to facilitate decision making. We use the sediment retention model to illustrate the types of analyses the tool can support. The case study explores the tradeoffs between road rehabilitation costs and sediment export avoided. We couple the sediment and cost models with trade-off analysis to identify optimal distributed solutions that are most cost-effective in reducing erosion, and then use those models to estimate sediment exposure to coral reefs. We find that cooperation between land owners reveals opportunities for maximizing the benefits of fixing roads and minimizes costs. This research forms the building blocks of an ecosystem service decision support tool that we intend to continue to test and apply in other Pacific Island settings.

WMOST 2.0 Download Page

EPA Pesticide Factsheets

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that facilitates integrated water management at the local or small watershed scale. WMOST models the environmental effects and costs of managemen

WMOST 3.0 Download Page

EPA Pesticide Factsheets

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that facilitates integrated water management at the local or small watershed scale. WMOST models the environmental effects and costs of management.

Integrated permanent plot and aerial monitoring for the spruce budworm decision support system

Treesearch

David A. MacLean

2000-01-01

Spruce budworm (Choristoneura fumiferana Clem.) outbreaks cause severe mortality and growth loss of spruce and fir forest over ranch of eastern North America. The Spruce Budworm Decision Support System (DSS) links prediction and interpretation models to the ARC/1NFO GIS, under an ArcView graphical user interface. It helps forest managers predict...

A web platform for integrated surface water - groundwater modeling and data management

NASA Astrophysics Data System (ADS)

Fatkhutdinov, Aybulat; Stefan, Catalin; Junghanns, Ralf

2016-04-01

Model-based decision support systems are considered to be reliable and time-efficient tools for resources management in various hydrology related fields. However, searching and acquisition of the required data, preparation of the data sets for simulations as well as post-processing, visualization and publishing of the simulations results often requires significantly more work and time than performing the modeling itself. The purpose of the developed software is to combine data storage facilities, data processing instruments and modeling tools in a single platform which potentially can reduce time required for performing simulations, hence decision making. The system is developed within the INOWAS (Innovative Web Based Decision Support System for Water Sustainability under a Changing Climate) project. The platform integrates spatially distributed catchment scale rainfall - runoff, infiltration and groundwater flow models with data storage, processing and visualization tools. The concept is implemented in a form of a web-GIS application and is build based on free and open source components, including the PostgreSQL database management system, Python programming language for modeling purposes, Mapserver for visualization and publishing the data, Openlayers for building the user interface and others. Configuration of the system allows performing data input, storage, pre- and post-processing and visualization in a single not disturbed workflow. In addition, realization of the decision support system in the form of a web service provides an opportunity to easily retrieve and share data sets as well as results of simulations over the internet, which gives significant advantages for collaborative work on the projects and is able to significantly increase usability of the decision support system.

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Human Space Flight Missions

NASA Technical Reports Server (NTRS)

Kerstman, Eric L.; Minard, Charles; FreiredeCarvalho, Mary H.; Walton, Marlei E.; Myers, Jerry G., Jr.; Saile, Lynn G.; Lopez, Vilma; Butler, Douglas J.; Johnson-Throop, Kathy A.

2011-01-01

This slide presentation reviews the Integrated Medical Model (IMM) and its use as a risk assessment and decision support tool for human space flight missions. The IMM is an integrated, quantified, evidence-based decision support tool useful to NASA crew health and mission planners. It is intended to assist in optimizing crew health, safety and mission success within the constraints of the space flight environment for in-flight operations. It uses ISS data to assist in planning for the Exploration Program and it is not intended to assist in post flight research. The IMM was used to update Probability Risk Assessment (PRA) for the purpose of updating forecasts for the conditions requiring evacuation (EVAC) or Loss of Crew Life (LOC) for the ISS. The IMM validation approach includes comparison with actual events and involves both qualitative and quantitaive approaches. The results of these comparisons are reviewed. Another use of the IMM is to optimize the medical kits taking into consideration the specific mission and the crew profile. An example of the use of the IMM to optimize the medical kits is reviewed.

System Dynamics Modeling of Transboundary Systems: The Bear River Basin Model

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

Gerald Sehlke; Jake Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and groundwater data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or groundwater modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

System Dynamics Modeling of Transboundary Systems: the Bear River Basin Model

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

Gerald Sehlke; Jacob J. Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

The Integrated Medical Model

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles; Saile, Lynn; Freiere deCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

2010-01-01

The goals of the Integrated Medical Model (IMM) are to develop an integrated, quantified, evidence-based decision support tool useful to crew health and mission planners and to help align science, technology, and operational activities intended to optimize crew health, safety, and mission success. Presentation slides address scope and approach, beneficiaries of IMM capabilities, history, risk components, conceptual models, development steps, and the evidence base. Space adaptation syndrome is used to demonstrate the model's capabilities.

An Integrated Decision Support System for Planning and Measuring Institutional Efficiency. AIR 1992 Annual Forum Paper.

ERIC Educational Resources Information Center

Minnaar, Phil C.

This paper presents a model for obtaining and organizing managment information for decision making in university planning, developed by the Bureau for Management Information of the University of South Africa. The model identifies the fundamental entities of the university as environment, finance, physical facilities, assets, personnel, and…

An integrated decision support system for diagnosing and managing patients with community-acquired pneumonia.

PubMed Central

Aronsky, D.; Haug, P. J.

1999-01-01

Decision support systems that integrate guidelines have become popular applications to reduce variation and deliver cost-effective care. However, adverse characteristics of decision support systems, such as additional and time-consuming data entry or manually identifying eligible patients, result in a "behavioral bottleneck" that prevents decision support systems to become part of the clinical routine. This paper describes the design and the implementation of an integrated decision support system that explores a novel approach for bypassing the behavioral bottleneck. The real-time decision support system does not require health care providers to enter additional data and consists of a diagnostic and a management component. Images Fig. 1 Fig. 2 Fig. 3 PMID:10566348

Operational seasonal forecasting of crop performance.

PubMed

Stone, Roger C; Meinke, Holger

2005-11-29

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.

Operational seasonal forecasting of crop performance

PubMed Central

Stone, Roger C; Meinke, Holger

2005-01-01

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production. PMID:16433097

Developing an Integrated Model Framework for the Assessment of Sustainable Agricultural Residue Removal Limits for Bioenergy Systems

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

David Muth, Jr.; Jared Abodeely; Richard Nelson

Agricultural residues have significant potential as a feedstock for bioenergy production, but removing these residues can have negative impacts on soil health. Models and datasets that can support decisions about sustainable agricultural residue removal are available; however, no tools currently exist capable of simultaneously addressing all environmental factors that can limit availability of residue. The VE-Suite model integration framework has been used to couple a set of environmental process models to support agricultural residue removal decisions. The RUSLE2, WEPS, and Soil Conditioning Index models have been integrated. A disparate set of databases providing the soils, climate, and management practice datamore » required to run these models have also been integrated. The integrated system has been demonstrated for two example cases. First, an assessment using high spatial fidelity crop yield data has been run for a single farm. This analysis shows the significant variance in sustainably accessible residue across a single farm and crop year. A second example is an aggregate assessment of agricultural residues available in the state of Iowa. This implementation of the integrated systems model demonstrates the capability to run a vast range of scenarios required to represent a large geographic region.« less

Complacency and bias in human use of automation: an attentional integration.

PubMed

Parasuraman, Raja; Manzey, Dietrich H

2010-06-01

Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation. Automation-related complacency and automation bias have typically been considered separately and independently. Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved. Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator's attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect. Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams. While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency. Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics. The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems.

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

Treesearch

Michelle F. Tacconelli; Edward F. Loewenstein

2012-01-01

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

Multifaceted Modelling of Complex Business Enterprises

PubMed Central

2015-01-01

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

Multifaceted Modelling of Complex Business Enterprises.

PubMed

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

2015-01-01

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

Biomedical Ontologies in Action: Role in Knowledge Management, Data Integration and Decision Support

PubMed Central

Bodenreider, O.

2008-01-01

Summary Objectives To provide typical examples of biomedical ontologies in action, emphasizing the role played by biomedical ontologies in knowledge management, data integration and decision support. Methods Biomedical ontologies selected for their practical impact are examined from a functional perspective. Examples of applications are taken from operational systems and the biomedical literature, with a bias towards recent journal articles. Results The ontologies under investigation in this survey include SNOMED CT, the Logical Observation Identifiers, Names, and Codes (LOINC), the Foundational Model of Anatomy, the Gene Ontology, RxNorm, the National Cancer Institute Thesaurus, the International Classification of Diseases, the Medical Subject Headings (MeSH) and the Unified Medical Language System (UMLS). The roles played by biomedical ontologies are classified into three major categories: knowledge management (indexing and retrieval of data and information, access to information, mapping among ontologies); data integration, exchange and semantic interoperability; and decision support and reasoning (data selection and aggregation, decision support, natural language processing applications, knowledge discovery). Conclusions Ontologies play an important role in biomedical research through a variety of applications. While ontologies are used primarily as a source of vocabulary for standardization and integration purposes, many applications also use them as a source of computable knowledge. Barriers to the use of ontologies in biomedical applications are discussed. PMID:18660879

The Role of Integrated Modelling and Assessment for Decision-Making: Lessons from Water Allocation Issues in Australia

NASA Astrophysics Data System (ADS)

Jakeman, A. J.; Guillaume, J. H. A.; El Sawah, S.; Hamilton, S.

2014-12-01

Integrated modelling and assessment (IMA) is best regarded as a process that can support environmental decision-making when issues are strongly contested and uncertainties pervasive. To be most useful, the process must be multi-dimensional and phased. Principally, it must be tailored to the problem context to encompass diverse issues of concern, management settings and stakeholders. This in turn requires the integration of multiple processes and components of natural and human systems and their corresponding spatial and temporal scales. Modellers therefore need to be able to integrate multiple disciplines, methods, models, tools and data, and many sources and types of uncertainty. These dimensions are incorporated into iteration between the various phases of the IMA process, including scoping, problem framing and formulation, assessing options and communicating findings. Two case studies in Australia are employed to share the lessons of how integration can be achieved in these IMA phases using a mix of stakeholder participation processes and modelling tools. One case study aims to improve the relevance of modelling by incorporating stakeholder's views of irrigated viticulture and water management decision making. It used a novel methodology with the acronym ICTAM, consisting of Interviews to elicit mental models, Cognitive maps to represent and analyse individual and group mental models, Time-sequence diagrams to chronologically structure the decision making process, an All-encompassing conceptual model, and computational Models of stakeholder decision making. The second case uses a hydro-economic river network model to examine basin-wide impacts of water allocation cuts and adoption of farm innovations. The knowledge exchange approach used in each case was designed to integrate data and knowledge bearing in mind the contextual dimensions of the problem at hand, and the specific contributions that environmental modelling was thought to be able to make.

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

USGS Publications Warehouse

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

2005-01-01

The increasing complexity of water- and environmental-resource problems require modeling approaches that incorporate knowledge from a broad range of scientific and software disciplines. To address this need, the U.S. Geological Survey (USGS) has developed the Modular Modeling System (MMS). MMS is an integrated system of computer software for model development, integration, and application. Its modular design allows a high level of flexibility and adaptability to enable modelers to incorporate their own software into a rich array of built-in models and modeling tools. These include individual process models, tightly coupled models, loosely coupled models, and fully- integrated decision support systems. A geographic information system (GIS) interface, the USGS GIS Weasel, has been integrated with MMS to enable spatial delineation and characterization of basin and ecosystem features, and to provide objective parameter-estimation methods for models using available digital data. MMS provides optimization and sensitivity-analysis tools to analyze model parameters and evaluate the extent to which uncertainty in model parameters affects uncertainty in simulation results. MMS has been coupled with the Bureau of Reclamation object-oriented reservoir and river-system modeling framework, RiverWare, to develop models to evaluate and apply optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. This decision support system approach has been developed, tested, and implemented in the Gunnison, Yakima, San Joaquin, Rio Grande, and Truckee River basins of the western United States. MMS is currently being coupled with the U.S. Forest Service model SIMulating Patterns and Processes at Landscape Scales (SIMPPLLE) to assess the effects of alternative vegetation-management strategies on a variety of hydrological and ecological responses. Initial development and testing of the MMS-SIMPPLLE integration is being conducted on the Colorado Plateau region of the western United Sates.

Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety.

PubMed

Seshia, Shashi S; Bryan Young, G; Makhinson, Michael; Smith, Preston A; Stobart, Kent; Croskerry, Pat

2018-02-01

Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care-related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive-affective biases plus cascade could advance the understanding of cognitive-affective processes that underlie decisions and organizational cultures across the continuum of care. Thematic analysis, qualitative information from several sources being used to support argumentation. Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive-affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive-affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive-affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error-provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error-provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive-affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. © 2017 The Authors. Journal of Evaluation in Clinical Practice published by John Wiley & Sons, Ltd.

Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety

PubMed Central

Bryan Young, G.; Makhinson, Michael; Smith, Preston A.; Stobart, Kent; Croskerry, Pat

2017-01-01

Abstract Introduction Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care–related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. Hypothesis A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive‐affective biases plus cascade could advance the understanding of cognitive‐affective processes that underlie decisions and organizational cultures across the continuum of care. Methods Thematic analysis, qualitative information from several sources being used to support argumentation. Discussion Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive‐affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive‐affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive‐affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error‐provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error‐provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive‐affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. Limitations The concept is abstract, the model is virtual, and the best supportive evidence is qualitative and indirect. Conclusions The proposed model may help enhance rational decision making across the continuum of care, thereby improving patient safety globally. PMID:29168290

A decision-supported outpatient practice system.

PubMed Central

Barrows, R. C.; Allen, B. A.; Smith, K. C.; Arni, V. V.; Sherman, E.

1996-01-01

We describe a Decision-supported Outpatient Practice (DOP) system developed and now in use at the Columbia-Presbyterian Medical Center. DOP is an automated ambulatory medical record system that integrates in-patient and ambulatory care data, and incorporates active and passive decision support mechanisms with a view towards improving the quality of primary care. Active decision support occurs in the form of event-driven reminders created within a remote clinical information system with its central data repository and decision support system (DSS). Novel features of DOP include patient specific health maintenance task lists calculated by the remote DSS. uses of a semantically structured controlled medical vocabulary to support clinical results review and provider data entry, and exploitation of an underlying ambulatory data model that provides for an explicit record of evolution of insight regarding patient management. Benefits, challenges, and plans are discussed. PMID:8947774

Development of a decision support system for monitoring, reporting and forecasting ecological conditions of the Appalachian Trail

USGS Publications Warehouse

Wang, Yeqiao; Nemani, Ramakrishna; Dieffenbach, Fred; Stolte, Kenneth; Holcomb, Glenn B.; Robinson, Matt; Reese, Casey C.; McNiff, Marcia; Duhaime, Roland; Tierney, Geri; Mitchell, Brian; August, Peter; Paton, Peter; LaBash, Charles

2010-01-01

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.

A green chemistry-based classification model for the synthesis of silver nanoparticles

EPA Science Inventory

The assessment of implementation of green chemistry principles in the synthesis of nanomaterials is a complex decision-making problem that necessitates integration of several evaluation criteria. Multiple Criteria Decision Aiding (MCDA) provides support for such a challenge. One ...

Tapping into community wisdom and integrating local knowledge into revitalization efforts

EPA Science Inventory

Local decision-making is sometimes considered a puzzle by research ecologists, resource managers, and policy researchers. The eternal hope is to find that model or concept that provides the “right” information to support local environmental decisions. Researchers have...

GLIMPSE: An integrated assessment model-based tool for ...

EPA Pesticide Factsheets

Dan Loughlin will describe the GCAM-USA integrated assessment model and how that model is being improved and integrated into the GLIMPSE decision support system. He will also demonstrate the application of the model to evaluate the emissions and health implications of hypothetical state-level renewable electricity standards. Introduce the GLIMPSE project to state and regional environmental modelers and analysts. Presented as part of the State Energy and Air Quality Group Webinar Series, which is organized by NESCAUM.

On the design of computer-based models for integrated environmental science.

PubMed

McIntosh, Brian S; Jeffrey, Paul; Lemon, Mark; Winder, Nick

2005-06-01

The current research agenda in environmental science is dominated by calls to integrate science and policy to better understand and manage links between social (human) and natural (nonhuman) processes. Freshwater resource management is one area where such calls can be heard. Designing computer-based models for integrated environmental science poses special challenges to the research community. At present it is not clear whether such tools, or their outputs, receive much practical policy or planning application. It is argued that this is a result of (1) a lack of appreciation within the research modeling community of the characteristics of different decision-making processes including policy, planning, and (2) participation, (3) a lack of appreciation of the characteristics of different decision-making contexts, (4) the technical difficulties in implementing the necessary support tool functionality, and (5) the socio-technical demands of designing tools to be of practical use. This article presents a critical synthesis of ideas from each of these areas and interprets them in terms of design requirements for computer-based models being developed to provide scientific information support for policy and planning. Illustrative examples are given from the field of freshwater resources management. Although computer-based diagramming and modeling tools can facilitate processes of dialogue, they lack adequate simulation capabilities. Component-based models and modeling frameworks provide such functionality and may be suited to supporting problematic or messy decision contexts. However, significant technical (implementation) and socio-technical (use) challenges need to be addressed before such ambition can be realized.

IDESSA: An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Authmann, Christian; Dreber, Niels; Hess, Bastian; Kellner, Klaus; Morgenthal, Theunis; Nauss, Thomas; Seeger, Bernhard; Tsvuura, Zivanai; Wiegand, Kerstin

2017-04-01

Bush encroachment is a syndrome of land degradation that occurs in many savannas including those of southern Africa. The increase in density, cover or biomass of woody vegetation often has negative effects on a range of ecosystem functions and services, which are hardly reversible. However, despite its importance, neither the causes of bush encroachment, nor the consequences of different resource management strategies to combat or mitigate related shifts in savanna states are fully understood. The project "IDESSA" (An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas) aims to improve the understanding of the complex interplays between land use, climate patterns and vegetation dynamics and to implement an integrative monitoring and decision-support system for the sustainable management of different savanna types. For this purpose, IDESSA follows an innovative approach that integrates local knowledge, botanical surveys, remote-sensing and machine-learning based time-series of atmospheric and land-cover dynamics, spatially explicit simulation modeling and analytical database management. The integration of the heterogeneous data will be implemented in a user oriented database infrastructure and scientific workflow system. Accessible via web-based interfaces, this database and analysis system will allow scientists to manage and analyze monitoring data and scenario computations, as well as allow stakeholders (e. g. land users, policy makers) to retrieve current ecosystem information and seasonal outlooks. We present the concept of the project and show preliminary results of the realization steps towards the integrative savanna management and decision-support system.

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.

On implementing clinical decision support: achieving scalability and maintainability by combining business rules and ontologies.

PubMed

Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya

2006-01-01

We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.

Integrating local, expert, and practical knowledge in community remediation and revitalization

EPA Science Inventory

Researchers and natural resource managers often develop tools and methods to facilitate the inclusion of science in local environmental decision-making. The eternal hope is to find that model or concept that provides the “right” information to support these decisions....

Serial, parallel and hierarchical decision making in primates

PubMed Central

Zylberberg, Ariel; Lorteije, Jeannette AM; Ouellette, Brian G; De Zeeuw, Chris I; Sigman, Mariano; Roelfsema, Pieter

2017-01-01

The study of decision-making has mainly focused on isolated decisions where choices are associated with motor actions. However, problem-solving often involves considering a hierarchy of sub-decisions. In a recent study (Lorteije et al. 2015), we reported behavioral and neuronal evidence for hierarchical decision making in a task with a small decision tree. We observed a first phase of parallel evidence integration for multiple sub-decisions, followed by a phase in which the overall strategy formed. It has been suggested that a 'flat' competition between the ultimate motor actions might also explain these results. A reanalysis of the data does not support the critical predictions of flat models. We also examined the time-course of decision making in other, related tasks and report conditions where evidence integration for successive decisions is decoupled, which excludes flat models. We conclude that the flexibility of decision-making implies that the strategies are genuinely hierarchical. DOI: http://dx.doi.org/10.7554/eLife.17331.001 PMID:28648172

Decision insight into stakeholder conflict for ERN.

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

Siirola, John; Tidwell, Vincent Carroll; Benz, Zachary O.

Participatory modeling has become an important tool in facilitating resource decision making and dispute resolution. Approaches to modeling that are commonly used in this context often do not adequately account for important human factors. Current techniques provide insights into how certain human activities and variables affect resource outcomes; however, they do not directly simulate the complex variables that shape how, why, and under what conditions different human agents behave in ways that affect resources and human interactions related to them. Current approaches also do not adequately reveal how the effects of individual decisions scale up to have systemic level effectsmore » in complex resource systems. This lack of integration prevents the development of more robust models to support decision making and dispute resolution processes. Development of integrated tools is further hampered by the fact that collection of primary data for decision-making modeling is costly and time consuming. This project seeks to develop a new approach to resource modeling that incorporates both technical and behavioral modeling techniques into a single decision-making architecture. The modeling platform is enhanced by use of traditional and advanced processes and tools for expedited data capture. Specific objectives of the project are: (1) Develop a proof of concept for a new technical approach to resource modeling that combines the computational techniques of system dynamics and agent based modeling, (2) Develop an iterative, participatory modeling process supported with traditional and advance data capture techniques that may be utilized to facilitate decision making, dispute resolution, and collaborative learning processes, and (3) Examine potential applications of this technology and process. The development of this decision support architecture included both the engineering of the technology and the development of a participatory method to build and apply the technology. Stakeholder interaction with the model and associated data capture was facilitated through two very different modes of engagement, one a standard interface involving radio buttons, slider bars, graphs and plots, while the other utilized an immersive serious gaming interface. The decision support architecture developed through this project was piloted in the Middle Rio Grande Basin to examine how these tools might be utilized to promote enhanced understanding and decision-making in the context of complex water resource management issues. Potential applications of this architecture and its capacity to lead to enhanced understanding and decision-making was assessed through qualitative interviews with study participants who represented key stakeholders in the basin.« less

Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning

PubMed Central

Maurer, Max; Lienert, Judit

2017-01-01

We compare the use of multi-criteria decision analysis (MCDA)–or more precisely, models used in multi-attribute value theory (MAVT)–to integrated assessment (IA) models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability), desirability (value), and distinguishability (value range) of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water supply planning in the case study and beyond. PMID:28481881

Towards an integrated approach to natural hazards risk assessment using GIS: with reference to bushfires.

PubMed

Chen, Keping; Blong, Russell; Jacobson, Carol

2003-04-01

This paper develops a GIS-based integrated approach to risk assessment in natural hazards, with reference to bushfires. The challenges for undertaking this approach have three components: data integration, risk assessment tasks, and risk decision-making. First, data integration in GIS is a fundamental step for subsequent risk assessment tasks and risk decision-making. A series of spatial data integration issues within GIS such as geographical scales and data models are addressed. Particularly, the integration of both physical environmental data and socioeconomic data is examined with an example linking remotely sensed data and areal census data in GIS. Second, specific risk assessment tasks, such as hazard behavior simulation and vulnerability assessment, should be undertaken in order to understand complex hazard risks and provide support for risk decision-making. For risk assessment tasks involving heterogeneous data sources, the selection of spatial analysis units is important. Third, risk decision-making concerns spatial preferences and/or patterns, and a multicriteria evaluation (MCE)-GIS typology for risk decision-making is presented that incorporates three perspectives: spatial data types, data models, and methods development. Both conventional MCE methods and artificial intelligence-based methods with GIS are identified to facilitate spatial risk decision-making in a rational and interpretable way. Finally, the paper concludes that the integrated approach can be used to assist risk management of natural hazards, in theory and in practice.

The Effects of Evidence Bounds on Decision-Making: Theoretical and Empirical Developments

PubMed Central

Zhang, Jiaxiang

2012-01-01

Converging findings from behavioral, neurophysiological, and neuroimaging studies suggest an integration-to-boundary mechanism governing decision formation and choice selection. This mechanism is supported by sequential sampling models of choice decisions, which can implement statistically optimal decision strategies for selecting between multiple alternative options on the basis of sensory evidence. This review focuses on recent developments in understanding the evidence boundary, an important component of decision-making raised by experimental findings and models. The article starts by reviewing the neurobiology of perceptual decisions and several influential sequential sampling models, in particular the drift-diffusion model, the Ornstein–Uhlenbeck model and the leaky-competing-accumulator model. In the second part, the article examines how the boundary may affect a model’s dynamics and performance and to what extent it may improve a model’s fits to experimental data. In the third part, the article examines recent findings that support the presence and site of boundaries in the brain. The article considers two questions: (1) whether the boundary is a spontaneous property of neural integrators, or is controlled by dedicated neural circuits; (2) if the boundary is variable, what could be the driving factors behind boundary changes? The review brings together studies using different experimental methods in seeking answers to these questions, highlights psychological and physiological factors that may be associated with the boundary and its changes, and further considers the evidence boundary as a generic mechanism to guide complex behavior. PMID:22870070

Operationalising uncertainty in data and models for integrated water resources management.

PubMed

Blind, M W; Refsgaard, J C

2007-01-01

Key sources of uncertainty of importance for water resources management are (1) uncertainty in data; (2) uncertainty related to hydrological models (parameter values, model technique, model structure); and (3) uncertainty related to the context and the framing of the decision-making process. The European funded project 'Harmonised techniques and representative river basin data for assessment and use of uncertainty information in integrated water management (HarmoniRiB)' has resulted in a range of tools and methods to assess such uncertainties, focusing on items (1) and (2). The project also engaged in a number of discussions surrounding uncertainty and risk assessment in support of decision-making in water management. Based on the project's results and experiences, and on the subsequent discussions a number of conclusions can be drawn on the future needs for successful adoption of uncertainty analysis in decision support. These conclusions range from additional scientific research on specific uncertainties, dedicated guidelines for operational use to capacity building at all levels. The purpose of this paper is to elaborate on these conclusions and anchoring them in the broad objective of making uncertainty and risk assessment an essential and natural part in future decision-making processes.

Gain Modulation by an Urgency Signal Controls the Speed–Accuracy Trade-Off in a Network Model of a Cortical Decision Circuit

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2011-01-01

The speed–accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time. PMID:21415911

Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit.

PubMed

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C

2011-01-01

The speed-accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time.

Surface transportation weather decision support requirements : advanced-integrated decision support using weather information for surface transportation decisions makers : draft (truncated*) version 1.0

DOT National Transportation Integrated Search

1997-09-19

This report gives an overview of the National Intelligent Transportation Infrastructure Initiative (NITI). NITI refers to the integrated electronics, communications, and hardware and software elements that are available to support Intelligent Transpo...

Stakeholder views of management and decision support tools to integrate climate change into Great Lakes Lake Whitefish management

USGS Publications Warehouse

Lynch, Abigail J.; Taylor, William W.; McCright, Aaron M.

2016-01-01

Decision support tools can aid decision making by systematically incorporating information, accounting for uncertainties, and facilitating evaluation between alternatives. Without user buy-in, however, decision support tools can fail to influence decision-making processes. We surveyed fishery researchers, managers, and fishers affiliated with the Lake Whitefish Coregonus clupeaformis fishery in the 1836 Treaty Waters of Lakes Huron, Michigan, and Superior to assess opinions of current and future management needs to identify barriers to, and opportunities for, developing a decision support tool based on Lake Whitefish recruitment projections with climate change. Approximately 64% of 39 respondents were satisfied with current management, and nearly 85% agreed that science was well integrated into management programs. Though decision support tools can facilitate science integration into management, respondents suggest that they face significant implementation barriers, including lack of political will to change management and perceived uncertainty in decision support outputs. Recommendations from this survey can inform development of decision support tools for fishery management in the Great Lakes and other regions.

Integration for Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Nickovic, S.; Huete, A.; Budge, A.; Flowers, L.

2008-01-01

The objective of the program is to assess the feasibility of combining a dust transport model with MODIS derived phenology to study pollen transport for integration with a public health decision support system. The use of pollen information has specifically be identified as a critical need by the New Mexico State Health department for inclusion in the Environmental Public Health Tracking (EPHT) program. Material and methods: Pollen can be transported great distances. Local observations of plan phenology may be consistent with the timing and source of pollen collected by pollen sampling instruments. The Dust REgional Atmospheric Model (DREAM) is an integrated modeling system designed to accurately describe the dust cycle in the atmosphere. The dust modules of the entire system incorporate the state of the art parameterization of all the major phases of the atmospheric dust life such as production, diffusion, advection, and removal. These modules also include effects of the particles size distribution on aerosol dispersion. The model was modified to use pollen sources instead of dust. Pollen release was estimated based on satellite-derived phenology of key plan species and vegetation communities. The MODIS surface reflectance product (MOD09) provided information on the start of the plant growing season, growth stage, and pollen release. The resulting deterministic model is useful for predicting and simulating pollen emission and downwind concentration to study details of phenology and meteorology and their dependencies. The proposed linkage in this project provided critical information on the location timing and modeled transport of pollen directly to the EPHT> This information is useful to support the centers for disease control and prevention (CDC)'s National EPHT and the state of New Mexico environmental public health decision support for asthma and allergies alerts.

The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation

NASA Astrophysics Data System (ADS)

Li, Hui; Hong, Lu-Yao; Zhou, Qing; Yu, Hai-Jie

2015-08-01

The business failure of numerous companies results in financial crises. The high social costs associated with such crises have made people to search for effective tools for business risk prediction, among which, support vector machine is very effective. Several modelling means, including single-technique modelling, hybrid modelling, and ensemble modelling, have been suggested in forecasting business risk with support vector machine. However, existing literature seldom focuses on the general modelling frame for business risk prediction, and seldom investigates performance differences among different modelling means. We reviewed researches on forecasting business risk with support vector machine, proposed the general assisted prediction modelling frame with hybridisation and ensemble (APMF-WHAE), and finally, investigated the use of principal components analysis, support vector machine, random sampling, and group decision, under the general frame in forecasting business risk. Under the APMF-WHAE frame with support vector machine as the base predictive model, four specific predictive models were produced, namely, pure support vector machine, a hybrid support vector machine involved with principal components analysis, a support vector machine ensemble involved with random sampling and group decision, and an ensemble of hybrid support vector machine using group decision to integrate various hybrid support vector machines on variables produced from principle components analysis and samples from random sampling. The experimental results indicate that hybrid support vector machine and ensemble of hybrid support vector machines were able to produce dominating performance than pure support vector machine and support vector machine ensemble.

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.

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.

The design of patient decision support interventions: addressing the theory-practice gap.

PubMed

Elwyn, Glyn; Stiel, Mareike; Durand, Marie-Anne; Boivin, Jacky

2011-08-01

Although an increasing number of decision support interventions for patients (including decision aids) are produced, few make explicit use of theory. We argue the importance of using theory to guide design. The aim of this work was to address this theory-practice gap and to examine how a range of selected decision-making theories could inform the design and evaluation of decision support interventions. We reviewed the decision-making literature and selected relevant theories. We assessed their key principles, theoretical pathways and predictions in order to determine how they could inform the design of two core components of decision support interventions, namely, information and deliberation components and to specify theory-based outcome measures. Eight theories were selected: (1) the expected utility theory; (2) the conflict model of decision making; (3) prospect theory; (4) fuzzy-trace theory; (5) the differentiation and consolidation theory; (6) the ecological rationality theory; (7) the rational-emotional model of decision avoidance; and finally, (8) the Attend, React, Explain, Adapt model of affective forecasting. Some theories have strong relevance to the information design (e.g. prospect theory); some are more relevant to deliberation processes (conflict theory, differentiation theory and ecological validity). None of the theories in isolation was sufficient to inform the design of all the necessary components of decision support interventions. It was also clear that most work in theory-building has focused on explaining or describing how humans think rather than on how tools could be designed to help humans make good decisions. It is not surprising therefore that a large theory-practice gap exists as we consider decision support for patients. There was no relevant theory that integrated all the necessary contributions to the task of making good decisions in collaborative interactions. Initiatives such as the International Patient Decision Aids Standards Collaboration influence standards for the design of decision support interventions. However, this analysis points to the need to undertake more work in providing theoretical foundations for these interventions. © 2010 Blackwell Publishing Ltd.

Better Assessment Science Integrating Point and Nonpoint Sources

EPA Science Inventory

Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) is not a model per se, but is a multipurpose environmental decision support system for use by regional, state, and local agencies in performing watershed- and water-quality-based studies. BASI...

An Integrated Decision-Making Model for Categorizing Weather Products and Decision Aids

NASA Technical Reports Server (NTRS)

Elgin, Peter D.; Thomas, Rickey P.

2004-01-01

The National Airspace System s capacity will experience considerable growth in the next few decades. Weather adversely affects safe air travel. The FAA and NASA are working to develop new technologies that display weather information to support situation awareness and optimize pilot decision-making in avoiding hazardous weather. Understanding situation awareness and naturalistic decision-making is an important step in achieving this goal. Information representation and situation time stress greatly influence attentional resource allocation and working memory capacity, potentially obstructing accurate situation awareness assessments. Three naturalistic decision-making theories were integrated to provide an understanding of the levels of decision making incorporated in three operational situations and two conditions. The task characteristics associated with each phase of flight govern the level of situation awareness attained and the decision making processes utilized. Weather product s attributes and situation task characteristics combine to classify weather products according to the decision-making processes best supported. In addition, a graphical interface is described that affords intuitive selection of the appropriate weather product relative to the pilot s current flight situation.

Capturing information needs of care providers to support knowledge sharing and distributed decision making.

PubMed

Rogers, M; Zach, L; An, Y; Dalrymple, P

2012-01-01

This paper reports on work carried out to elicit information needs at a trans-disciplinary, nurse-managed health care clinic that serves a medically disadvantaged urban population. The trans-disciplinary model provides a "one-stop shop" for patients who can receive a wide range of services beyond traditional primary care. However, this model of health care presents knowledge sharing challenges because little is known about how data collected from the non-traditional services can be integrated into the traditional electronic medical record (EMR) and shared with other care providers. There is also little known about how health information technology (HIT) can be used to support the workflow in such a practice. The objective of this case study was to identify the information needs of care providers in order to inform the design of HIT to support knowledge sharing and distributed decision making. A participatory design approach is presented as a successful technique to specify requirements for HIT applications that can support a trans-disciplinary model of care. Using this design approach, the researchers identified the information needs of care providers working at the clinic and suggested HIT improvements to integrate non-traditional information into the EMR. These modifications allow knowledge sharing among care providers and support better health decisions. We have identified information needs of care providers as they are relevant to the design of health information systems. As new technology is designed and integrated into various workflows it is clear that understanding information needs is crucial to acceptance of that technology.

Decision support system for health care resources allocation

PubMed Central

Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

2017-01-01

Background A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. Aim The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. Methods To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. Results A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. Conclusion In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff. PMID:28848645

Decision support system for health care resources allocation.

PubMed

Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

2017-06-01

A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff.

FEMA's Earthquake Incident Journal: A Web-Based Data Integration and Decision Support Tool for Emergency Management

NASA Astrophysics Data System (ADS)

Jones, M.; Pitts, R.

2017-12-01

For emergency managers, government officials, and others who must respond to rapidly changing natural disasters, timely access to detailed information related to affected terrain, population and infrastructure is critical for planning, response and recovery operations. Accessing, analyzing and disseminating such disparate information in near real-time are critical decision support components. However, finding a way to handle a variety of informative yet complex datasets poses a challenge when preparing for and responding to disasters. Here, we discuss the implementation of a web-based data integration and decision support tool for earthquakes developed by the Federal Emergency Management Agency (FEMA) as a solution to some of these challenges. While earthquakes are among the most well- monitored and measured of natural hazards, the spatially broad impacts of shaking, ground deformation, landslides, liquefaction, and even tsunamis, are extremely difficult to quantify without accelerated access to data, modeling, and analytics. This web-based application, deemed the "Earthquake Incident Journal", provides real-time access to authoritative and event-specific data from external (e.g. US Geological Survey, NASA, state and local governments, etc.) and internal (FEMA) data sources. The journal includes a GIS-based model for exposure analytics, allowing FEMA to assess the severity of an event, estimate impacts to structures and population in near real-time, and then apply planning factors to exposure estimates to answer questions such as: What geographic areas are impacted? Will federal support be needed? What resources are needed to support survivors? And which infrastructure elements or essential facilities are threatened? This presentation reviews the development of the Earthquake Incident Journal, detailing the data integration solutions, the methodology behind the GIS-based automated exposure model, and the planning factors as well as other analytical advances that provide near real-time decision support to the federal government.

Free and open source enabling technologies for patient-centric, guideline-based clinical decision support: a survey.

PubMed

Leong, T Y; Kaiser, K; Miksch, S

2007-01-01

Guideline-based clinical decision support is an emerging paradigm to help reduce error, lower cost, and improve quality in evidence-based medicine. The free and open source (FOS) approach is a promising alternative for delivering cost-effective information technology (IT) solutions in health care. In this paper, we survey the current FOS enabling technologies for patient-centric, guideline-based care, and discuss the current trends and future directions of their role in clinical decision support. We searched PubMed, major biomedical informatics websites, and the web in general for papers and links related to FOS health care IT systems. We also relied on our background and knowledge for specific subtopics. We focused on the functionalities of guideline modeling tools, and briefly examined the supporting technologies for terminology, data exchange and electronic health record (EHR) standards. To effectively support patient-centric, guideline-based care, the computerized guidelines and protocols need to be integrated with existing clinical information systems or EHRs. Technologies that enable such integration should be accessible, interoperable, and scalable. A plethora of FOS tools and techniques for supporting different knowledge management and quality assurance tasks involved are available. Many challenges, however, remain in their implementation. There are active and growing trends of deploying FOS enabling technologies for integrating clinical guidelines, protocols, and pathways into the main care processes. The continuing development and maturation of such technologies are likely to make increasingly significant contributions to patient-centric, guideline-based clinical decision support.

An integrative model for in-silico clinical-genomics discovery science.

PubMed

Lussier, Yves A; Sarkar, Indra Nell; Cantor, Michael

2002-01-01

Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

Developing Flexible, Integrated Hydrologic Modeling Systems for Multiscale Analysis in the Midwest and Great Lakes Region

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Chiu, C. M.; Sharma, A.; Byun, K.; Hanson, Z.

2016-12-01

Physically based hydrologic modeling of surface and groundwater resources that can be flexibly and efficiently applied to support water resources policy/planning/management decisions at a wide range of spatial and temporal scales are greatly needed in the Midwest, where stakeholder access to such tools is currently a fundamental barrier to basic climate change assessment and adaptation efforts, and also the co-production of useful products to support detailed decision making. Based on earlier pilot studies in the Pacific Northwest Region, we are currently assembling a suite of end-to-end tools and resources to support various kinds of water resources planning and management applications across the region. One of the key aspects of these integrated tools is that the user community can access gridded products at any point along the end-to-end chain of models, looking backwards in time about 100 years (1915-2015), and forwards in time about 85 years using CMIP5 climate model projections. The integrated model is composed of historical and projected future meteorological data based on station observations and statistical and dynamically downscaled climate model output respectively. These gridded meteorological data sets serve as forcing data for the macro-scale VIC hydrologic model implemented over the Midwest at 1/16 degree resolution. High-resolution climate model (4km WRF) output provides inputs for the analyses of urban impacts, hydrologic extremes, agricultural impacts, and impacts to the Great Lakes. Groundwater recharge estimated by the surface water model provides input data for fine-scale and macro-scale groundwater models needed for specific applications. To highlight the multi-scale use of the integrated models in support of co-production of scientific information for decision making, we briefly describe three current case studies addressing different spatial scales of analysis: 1) Effects of climate change on the water balance of the Great Lakes, 2) Future hydropower resources in the St. Joseph River basin, 3) Effects of climate change on carbon cycling in small lakes in the Northern Highland Lakes District.

Socio-Hydrology Modelling for an Uncertain Future, with Examples from the USA and Canada (Invited)

NASA Astrophysics Data System (ADS)

White, D. D.; Gober, P.; Sampson, D. A.; Quay, R.; Kirkwood, C.

2013-12-01

Socio-hydrology brings an interest in human values, markets, social organizations and public policy to the traditional emphasis of water science on climate, hydrology, toxicology,and ecology. It also conveys a decision focus in the form of decision support tools, engagement, and new knowledge about the science-policy interface. This paper demonstrates how policy decisions and human behavior can be better integrated into climate and hydrological models to improve their usefulness for support in decision making. Examples from the Southwest USA and Western Canada highlight uncertainties, vulnerabilities, and critical tradeoffs facing water decision makers in the face of rapidly changing environmental and societal conditions. Irreducible uncertainties in downscaled climate and hydrological models limit the usefulness of climate-driven, predict-and-plan methods of water resource planning and management. Thus, it is argued that such methods should be replaced by approaches that use exploratory modelling, scenario planning, and risk assessment in which the emphasis is on managing uncertainty rather than on reducing it.

Technosocial Predictive Analytics in Support of Naturalistic Decision Making

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

Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.

2009-06-23

A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledgemore » management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.« less

Integrative sensing and prediction of urban water for sustainable cities (iSPUW)

NASA Astrophysics Data System (ADS)

Seo, D. J.; Fang, N. Z.; Yu, X.; Zink, M.; Gao, J.; Kerkez, B.

2014-12-01

We describe a newly launched project in the Dallas-Fort Worth Metroplex (DFW) area to develop a cyber-physical prototype system that integrates advanced sensing, modeling and prediction of urban water, to support its early adoption by a spectrum of users and stakeholders, and to educate a new generation of future sustainability scientists and engineers. The project utilizes the very high-resolution precipitation and other sensing capabilities uniquely available in DFW as well as crowdsourcing and cloud computing to advance understanding of the urban water cycle and to improve urban sustainability from transient shocks of heavy-to-extreme precipitation under climate change and urbanization. All available water information from observations and models will be fused objectively via advanced data assimilation to produce the best estimate of the state of the uncertain system. Modeling, prediction and decision support tools will be developed in the ensemble framework to increase the information content of the analysis and prediction and to support risk-based decision making.

A new framework for modeling decisions about changing information: The Piecewise Linear Ballistic Accumulator model

PubMed Central

Heathcote, Andrew

2016-01-01

In the real world, decision making processes must be able to integrate non-stationary information that changes systematically while the decision is in progress. Although theories of decision making have traditionally been applied to paradigms with stationary information, non-stationary stimuli are now of increasing theoretical interest. We use a random-dot motion paradigm along with cognitive modeling to investigate how the decision process is updated when a stimulus changes. Participants viewed a cloud of moving dots, where the motion switched directions midway through some trials, and were asked to determine the direction of motion. Behavioral results revealed a strong delay effect: after presentation of the initial motion direction there is a substantial time delay before the changed motion information is integrated into the decision process. To further investigate the underlying changes in the decision process, we developed a Piecewise Linear Ballistic Accumulator model (PLBA). The PLBA is efficient to simulate, enabling it to be fit to participant choice and response-time distribution data in a hierarchal modeling framework using a non-parametric approximate Bayesian algorithm. Consistent with behavioral results, PLBA fits confirmed the presence of a long delay between presentation and integration of new stimulus information, but did not support increased response caution in reaction to the change. We also found the decision process was not veridical, as symmetric stimulus change had an asymmetric effect on the rate of evidence accumulation. Thus, the perceptual decision process was slow to react to, and underestimated, new contrary motion information. PMID:26760448

Clinical, information and business process modeling to promote development of safe and flexible software.

PubMed

Liaw, Siaw-Teng; Deveny, Elizabeth; Morrison, Iain; Lewis, Bryn

2006-09-01

Using a factorial vignette survey and modeling methodology, we developed clinical and information models - incorporating evidence base, key concepts, relevant terms, decision-making and workflow needed to practice safely and effectively - to guide the development of an integrated rule-based knowledge module to support prescribing decisions in asthma. We identified workflows, decision-making factors, factor use, and clinician information requirements. The Unified Modeling Language (UML) and public domain software and knowledge engineering tools (e.g. Protégé) were used, with the Australian GP Data Model as the starting point for expressing information needs. A Web Services service-oriented architecture approach was adopted within which to express functional needs, and clinical processes and workflows were expressed in the Business Process Execution Language (BPEL). This formal analysis and modeling methodology to define and capture the process and logic of prescribing best practice in a reference implementation is fundamental to tackling deficiencies in prescribing decision support software.

Automating Guidelines for Clinical Decision Support: Knowledge Engineering and Implementation.

PubMed

Tso, Geoffrey J; Tu, Samson W; Oshiro, Connie; Martins, Susana; Ashcraft, Michael; Yuen, Kaeli W; Wang, Dan; Robinson, Amy; Heidenreich, Paul A; Goldstein, Mary K

2016-01-01

As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al. 5 identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology.

Coordinating complex decision support activities across distributed applications

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1994-01-01

Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

An Ecosystem Service Evaluation Tool to Support Ridge-to-Reef Management and Conservation in Hawaii

NASA Astrophysics Data System (ADS)

Oleson, K.; Callender, T.; Delevaux, J. M. S.; Falinski, K. A.; Htun, H.; Jin, G.

2014-12-01

Faced with increasing anthropogenic stressors and diverse stakeholders, local managers are adopting a ridge-to-reef and multi-objective management approach to restore declining coral reef health state. An ecosystem services framework, which integrates ecological indicators and stakeholder values, can foster more applied and integrated research, data collection, and modeling, and thus better inform the decision-making process and realize decision outcomes grounded in stakeholders' values. Here, we describe a research program that (i) leverages remotely sensed and empirical data to build an ecosystem services-based decision-support tool geared towards ridge-to-reef management; and (ii) applies it as part of a structured, value-based decision-making process to inform management in west Maui, a NOAA coral reef conservation priority site. The tool links terrestrial and marine biophysical models in a spatially explicit manner to quantify and map changes in ecosystem services delivery resulting from management actions, projected climate change impacts, and adaptive responses. We couple model outputs with localized valuation studies to translate ecosystem service outcomes into benefits and their associated socio-cultural and/or economic values. Managers can use this tool to run scenarios during their deliberations to evaluate trade-offs, cost-effectiveness, and equity implications of proposed policies. Ultimately, this research program aims at improving the effectiveness, efficiency, and equity outcomes of ecosystem-based management. This presentation will describe our approach, summarize initial results from the terrestrial modeling and economic valuations for west Maui, and highlight how this decision support tool benefits managers in west Maui.

Opportunities and Examples for Integration of Socio-environmental Approaches to Support Climate-informed Decisions

NASA Astrophysics Data System (ADS)

Kenney, M. A.

2014-12-01

Climate and environmental decisions require science that couples human and natural systems to quantify or articulate the observed physical, natural, and societal changes or likely consequences of different decision options. Despite the need for such policy-relevant research, multidisciplinary collaborations can be wrought with challenges of data integration, model interoperability, and communication across disciplinary divides. In this talk, I will present several examples where I have collaborated with colleagues from the physical, natural, and social sciences to develop novel, actionable science to inform decision-making. Specifically, I will discuss a cost analysis of water and sediment diversions to optimize land building in the Mississippi River delta (winner of American Geophysical Union Water Resources Research Editor's Choice Award 2014) and the development of a National Climate Indicator System that uses knowledge across the physical, natural, and social sciences to establish an end-to-end indicator system of climate changes, impacts, vulnerabilities, and responses. The latter project is in the process of moving from research to operations, an additional challenge and opportunity, as we work with the U.S. Global Change Research Program and their affiliated Federal agencies to establish it beyond the research prototype. Using these examples, I will provide some lessons learned that would have general applicability to socio-environmental research collaborations and integration of data, models, and information systems to support climate and environmental decision-making.

A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

NASA Astrophysics Data System (ADS)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

2017-08-01

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

Integrated Energy Solutions Research | Integrated Energy Solutions | NREL

Science.gov Websites

that spans the height and width of the wall they are facing. Decision Science and Informatics Enabling decision makers with rigorous, technology-neutral, data-backed decision support to maximize the impact of security in energy systems through analysis, decision support, advanced energy technology development, and

A dashboard-based system for supporting diabetes care.

PubMed

Dagliati, Arianna; Sacchi, Lucia; Tibollo, Valentina; Cogni, Giulia; Teliti, Marsida; Martinez-Millana, Antonio; Traver, Vicente; Segagni, Daniele; Posada, Jorge; Ottaviano, Manuel; Fico, Giuseppe; Arredondo, Maria Teresa; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo

2018-05-01

To describe the development, as part of the European Union MOSAIC (Models and Simulation Techniques for Discovering Diabetes Influence Factors) project, of a dashboard-based system for the management of type 2 diabetes and assess its impact on clinical practice. The MOSAIC dashboard system is based on predictive modeling, longitudinal data analytics, and the reuse and integration of data from hospitals and public health repositories. Data are merged into an i2b2 data warehouse, which feeds a set of advanced temporal analytic models, including temporal abstractions, care-flow mining, drug exposure pattern detection, and risk-prediction models for type 2 diabetes complications. The dashboard has 2 components, designed for (1) clinical decision support during follow-up consultations and (2) outcome assessment on populations of interest. To assess the impact of the clinical decision support component, a pre-post study was conducted considering visit duration, number of screening examinations, and lifestyle interventions. A pilot sample of 700 Italian patients was investigated. Judgments on the outcome assessment component were obtained via focus groups with clinicians and health care managers. The use of the decision support component in clinical activities produced a reduction in visit duration (P ≪ .01) and an increase in the number of screening exams for complications (P < .01). We also observed a relevant, although nonstatistically significant, increase in the proportion of patients receiving lifestyle interventions (from 69% to 77%). Regarding the outcome assessment component, focus groups highlighted the system's capability of identifying and understanding the characteristics of patient subgroups treated at the center. Our study demonstrates that decision support tools based on the integration of multiple-source data and visual and predictive analytics do improve the management of a chronic disease such as type 2 diabetes by enacting a successful implementation of the learning health care system cycle.

Use of microcomputers for planning and managing silviculture habitat relationships.

Treesearch

B.G. Marcot; R.S. McNay; R.E. Page

1988-01-01

Microcomputers aid in monitoring, modeling, and decision support for integrating objectives of silviculture and wildlife habitat management. Spreadsheets, data bases, statistics, and graphics programs are described for use in monitoring. Stand growth models, modeling languages, area and geobased information systems, and optimization models are discussed for use in...

Environmental impact assessment of transportation projects: An analysis using an integrated GIS, remote sensing, and spatial modeling approach

NASA Astrophysics Data System (ADS)

El-Gafy, Mohamed Anwar

Transportation projects will have impact on the environment. The general environmental pollution and damage caused by roads is closely associated with the level of economic activity. Although Environmental Impact Assessments (EIAs) are dependent on geo-spatial information in order to make an assessment, there are no rules per se how to conduct an environmental assessment. Also, the particular objective of each assessment is dictated case-by-case, based on what information and analyses are required. The conventional way of Environmental Impact Assessment (EIA) study is a time consuming process because it has large number of dependent and independent variables which have to be taken into account, which also have different consequences. With the emergence of satellite remote sensing technology and Geographic Information Systems (GIS), this research presents a new framework for the analysis phase of the Environmental Impact Assessment (EIA) for transportation projects based on the integration between remote sensing technology, geographic information systems, and spatial modeling. By integrating the merits of the map overlay method and the matrix method, the framework analyzes comprehensively the environmental vulnerability around the road and its impact on the environment. This framework is expected to: (1) improve the quality of the decision making process, (2) be applied both to urban and inter-urban projects, regardless of transport mode, and (3) present the data and make the appropriate analysis to support the decision of the decision-makers and allow them to present these data to the public hearings in a simple manner. Case studies, transportation projects in the State of Florida, were analyzed to illustrate the use of the decision support framework and demonstrate its capabilities. This cohesive and integrated system will facilitate rational decisions through cost effective coordination of environmental information and data management that can be tailored to specific projects. The framework would facilitate collecting, organizing, analyzing, archiving, and coordinating the information and data necessary to support technical and policy transportation decisions.

Deploying temporary networks for upscaling of sparse network stations

USDA-ARS?s Scientific Manuscript database

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, busin...

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

Streamlining the Discovery, Evaluation, and Integration of Data, Models, and Decision Support Systems: a Big Picture View

EPA Science Inventory

21st century environmental problems are wicked and require holistic systems thinking and solutions that integrate social and economic knowledge with knowledge of the environment. Computer-based technologies are fundamental to our ability to research and understand the relevant sy...

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

PubMed

McCullough, Laurence B

2013-02-01

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

Improvement of sand filter and constructed wetland design using an environmental decision support system.

PubMed

Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel

2008-01-01

With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.

Buffelgrass-Integrated modeling of an invasive plant

USGS Publications Warehouse

Holcombe, Tracy R.

2011-01-01

Buffelgrass (Pennisetum ciliare) poses a problem in the deserts of the United States, growing in dense stands and introducing a wildfire risk in an ecosystem not adapted to fire. The Invasive Species Science Branch of the Fort Collins Science Center has worked with many partners to develop a decision support model and a data management system to address the problem. The decision support model evaluates potential strategies for resource use and allocation. The data management system is a portal where users can submit, view, and download buffelgrass data. These tools provide a case study showcasing how the FORT is working to address the urgent issue of invasive species in the United States.

Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT

PubMed Central

Wimmer, Klaus; Compte, Albert; Roxin, Alex; Peixoto, Diogo; Renart, Alfonso; de la Rocha, Jaime

2015-01-01

Neuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these mechanisms during the decision-making process, we use a hierarchical network model composed of reciprocally connected sensory and integration circuits. Consistent with monkey behaviour in a fixed-duration motion discrimination task, the model integrates sensory evidence transiently, giving rise to a decaying bottom-up CP component. However, the dynamics of the hierarchical loop recruits a concurrently rising top-down component, resulting in sustained CP. We compute the CP time-course of neurons in the medial temporal area (MT) and find an early transient component and a separate late contribution reflecting decision build-up. The stability of individual CPs and the dynamics of noise correlations further support this decomposition. Our model provides a unified understanding of the circuit dynamics linking neural and behavioural variability. PMID:25649611

Integrating Hydrologic and Water Quality Models as a Decision Support Tool for Implementation of Low Impact Development in a Coastal Urban Watershed under Climate Variability and Sea Level Rise

NASA Astrophysics Data System (ADS)

Chang, N. B.

2016-12-01

Many countries concern about development and redevelopment efforts in urban regions to reduce the flood risk by considering hazards such as high-tide events, storm surge, flash floods, stormwater runoff, and impacts of sea level rise. Combining these present and future hazards with vulnerable characteristics found throughout coastal communities such as majority low-lying areas and increasing urban development, create scenarios for increasing exposure of flood hazard. As such, the most vulnerable areas require adaptation strategies and mitigation actions for flood hazard management. In addition, in the U.S., Numeric Nutrient Criteria (NNC) are a critical tool for protecting and restoring the designated uses of a waterbody with regard to nitrogen and phosphorus pollution. Strategies such as low impact development (LID) have been promoted in recent years as an alternative to traditional stormwater management and drainage to control both flooding and water quality impact. LID utilizes decentralized multifunctional site designs and incorporates on-site storm water management practices rather than conventional storm water management approaches that divert flow toward centralized facilities. How to integrate hydrologic and water quality models to achieve the decision support becomes a challenge. The Cross Bayou Watershed of Pinellas County in Tampa Bay, a highly urbanized coastal watershed, is utilized as a case study due to its sensitivity to flood hazards and water quality management within the watershed. This study will aid the County, as a decision maker, to implement its stormwater management policy and honor recent NNC state policy via demonstration of an integrated hydrologic and water quality model, including the Interconnected Channel and Pond Routing Model v.4 (ICPR4) and the BMPTRAIN model as a decision support tool. The ICPR4 can be further coupled with the ADCIRC/SWAN model to reflect the storm surge and seal level rise in coastal regions.

A public health decision support system model using reasoning methods.

PubMed

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

Decision support for the integrated restoration and protection strategy of the Forest Service, Northern Region

Treesearch

Keith Reynolds; Barry Bollenbacher; Chip Fisher; Melissa Hart; Mary Manning; Eric Henderson; Bruce Sims

2016-01-01

This report documents a decision-support process developed in the U.S. Department of Agriculture, Forest Service, Northern Region to assess management opportunities as part of an ecosystem-based approach to management that emphasizes ecological resilience. The decision-support system described in this work implements what is known as the Integrated Restoration and...

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...

Health decision making: lynchpin of evidence-based practice.

PubMed

Spring, Bonnie

2008-01-01

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

Health Decision Making: Lynchpin of Evidence-Based Practice

PubMed Central

Spring, Bonnie

2008-01-01

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

Enabling Real-time Water Decision Support Services Using Model as a Service

NASA Astrophysics Data System (ADS)

Zhao, T.; Minsker, B. S.; Lee, J. S.; Salas, F. R.; Maidment, D. R.; David, C. H.

2014-12-01

Through application of computational methods and an integrated information system, data and river modeling services can help researchers and decision makers more rapidly understand river conditions under alternative scenarios. To enable this capability, workflows (i.e., analysis and model steps) are created and published as Web services delivered through an internet browser, including model inputs, a published workflow service, and visualized outputs. The RAPID model, which is a river routing model developed at University of Texas Austin for parallel computation of river discharge, has been implemented as a workflow and published as a Web application. This allows non-technical users to remotely execute the model and visualize results as a service through a simple Web interface. The model service and Web application has been prototyped in the San Antonio and Guadalupe River Basin in Texas, with input from university and agency partners. In the future, optimization model workflows will be developed to link with the RAPID model workflow to provide real-time water allocation decision support services.

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.

Use of Knowledge Base Systems (EMDS) in Strategic and Tactical Forest Planning

NASA Astrophysics Data System (ADS)

Jensen, M. E.; Reynolds, K.; Stockmann, K.

2008-12-01

The USDA Forest Service 2008 Planning Rule requires Forest plans to provide a strategic vision for maintaining the sustainability of ecological, economic, and social systems across USFS lands through the identification of desired conditions and objectives. In this paper we show how knowledge-based systems can be efficiently used to evaluate disparate natural resource information to assess desired conditions and related objectives in Forest planning. We use the Ecosystem Management Decision Support (EMDS) system (http://www.institute.redlands.edu/emds/), which facilitates development of both logic-based models for evaluating ecosystem sustainability (desired conditions) and decision models to identify priority areas for integrated landscape restoration (objectives). The study area for our analysis spans 1,057 subwatersheds within western Montana and northern Idaho. Results of our study suggest that knowledge-based systems such as EMDS are well suited to both strategic and tactical planning and that the following points merit consideration in future National Forest (and other land management) planning efforts: 1) Logic models provide a consistent, transparent, and reproducible method for evaluating broad propositions about ecosystem sustainability such as: are watershed integrity, ecosystem and species diversity, social opportunities, and economic integrity in good shape across a planning area? The ability to evaluate such propositions in a formal logic framework also allows users the opportunity to evaluate statistical changes in outcomes over time, which could be very useful for regional and national reporting purposes and for addressing litigation; 2) The use of logic and decision models in strategic and tactical Forest planning provides a repository for expert knowledge (corporate memory) that is critical to the evaluation and management of ecosystem sustainability over time. This is especially true for the USFS and other federal resource agencies, which are likely to experience rapid turnover in tenured resource specialist positions within the next five years due to retirements; 3) Use of logic model output in decision models is an efficient method for synthesizing the typically large amounts of information needed to support integrated landscape restoration. Moreover, use of logic and decision models to design customized scenarios for integrated landscape restoration, as we have demonstrated with EMDS, offers substantial improvements to traditional GIS-based procedures such as suitability analysis. To our knowledge, this study represents the first attempt to link evaluations of desired conditions for ecosystem sustainability in strategic planning to tactical planning regarding the location of subwatersheds that best meet the objectives of integrated landscape restoration. The basic knowledge-based approach implemented in EMDS, with its logic (NetWeaver) and decision (Criterion Decision Plus) engines, is well suited both to multi-scale strategic planning and to multi-resource tactical planning.

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

DTIC Science & Technology

1984-09-01

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

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

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

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

Investigating the Heart Pump Implant Decision Process: Opportunities for Decision Support Tools to Help

PubMed Central

Yang, Qian; Zimmerman, John; Steinfeld, Aaron; Carey, Lisa; Antaki, James F.

2016-01-01

Clinical decision support tools (DSTs) are computational systems that aid healthcare decision-making. While effective in labs, almost all these systems failed when they moved into clinical practice. Healthcare researchers speculated it is most likely due to a lack of user-centered HCI considerations in the design of these systems. This paper describes a field study investigating how clinicians make a heart pump implant decision with a focus on how to best integrate an intelligent DST into their work process. Our findings reveal a lack of perceived need for and trust of machine intelligence, as well as many barriers to computer use at the point of clinical decision-making. These findings suggest an alternative perspective to the traditional use models, in which clinicians engage with DSTs at the point of making a decision. We identify situations across patients’ healthcare trajectories when decision supports would help, and we discuss new forms it might take in these situations. PMID:27833397

Improving World Agricultural Supply and Demand Estimates by Integrating NASA Remote Sensing Soil Moisture Data into USDA World Agricultural Outlook Board Decision Making Environment

NASA Astrophysics Data System (ADS)

Teng, W. L.; de Jeu, R. A.; Doraiswamy, P. C.; Kempler, S. J.; Shannon, H. D.

2009-12-01

A primary goal of the U.S. Department of Agriculture (USDA) is to expand markets for U.S. agricultural products and support global economic development. The USDA World Agricultural Outlook Board (WAOB) supports this goal by developing monthly World Agricultural Supply and Demand Estimates (WASDE) for the U.S. and major foreign producing countries. Because weather has a significant impact on crop progress, conditions, and production, WAOB prepares frequent agricultural weather assessments, in a GIS-based, Global Agricultural Decision Support Environment (GLADSE). The main objective of this project, thus, is to improve WAOB's estimates by integrating NASA remote sensing soil moisture observations and research results into GLADSE. Soil moisture is a primary data gap at WAOB. Soil moisture data, generated by the Land Parameter Retrieval Model (LPRM, developed by NASA GSFC and Vrije Universiteit Amsterdam) and customized to WAOB's requirements, will be directly integrated into GLADSE, as well as indirectly by first being integrated into USDA Agricultural Research Service (ARS)'s Environmental Policy Integrated Climate (EPIC) crop model. The LPRM-enhanced EPIC will be validated using three major agricultural regions important to WAOB and then integrated into GLADSE. Project benchmarking will be based on retrospective analyses of WAOB's analog year comparisons. The latter are between a given year and historical years with similar weather patterns. WAOB is the focal point for economic intelligence within the USDA. Thus, improving WAOB's agricultural estimates by integrating NASA satellite observations and model outputs will visibly demonstrate the value of NASA resources and maximize the societal benefits of NASA investments.

Energy Decision Science and Informatics | Integrated Energy Solutions |

Science.gov Websites

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

Toward patient-centered, personalized and personal decision support and knowledge management: a survey.

PubMed

Leong, T-Y

2012-01-01

This paper summarizes the recent trends and highlights the challenges and opportunities in decision support and knowledge management for patient-centered, personalized, and personal health care. The discussions are based on a broad survey of related references, focusing on the most recent publications. Major advances are examined in the areas of i) shared decision making paradigms, ii) continuity of care infrastructures and architectures, iii) human factors and system design approaches, iv) knowledge management innovations, and v) practical deployment and change considerations. Many important initiatives, projects, and plans with promising results have been identified. The common themes focus on supporting the individual patients who are playing an increasing central role in their own care decision processes. New collaborative decision making paradigms and information infrastructures are required to ensure effective continuity of care. Human factors and usability are crucial for the successful development and deployment of the relevant systems, tools, and aids. Advances in personalized medicine can be achieved through integrating genomic, phenotypic and other biological, individual, and population level information, and gaining useful insights from building and analyzing biological and other models at multiple levels of abstraction. Therefore, new Information and Communication Technologies and evaluation approaches are needed to effectively manage the scale and complexity of biomedical and health information, and adapt to the changing nature of clinical decision support. Recent research in decision support and knowledge management combines heterogeneous information and personal data to provide cost-effective, calibrated, personalized support in shared decision making at the point of care. Current and emerging efforts concentrate on developing or extending conventional paradigms, techniques, systems, and architectures for the new predictive, preemptive, and participatory health care model for patient-centered, personalized medicine. There is also an increasing emphasis on managing complexity with changing care models, processes, and settings.

Four principles for user interface design of computerised clinical decision support systems.

PubMed

Kanstrup, Anne Marie; Christiansen, Marion Berg; Nøhr, Christian

2011-01-01

The paper presents results from a design research project of a user interface (UI) for a Computerised Clinical Decision Support System (CDSS). The ambition has been to design Human-Computer Interaction (HCI) that can minimise medication errors. Through an iterative design process a digital prototype for prescription of medicine has been developed. This paper presents results from the formative evaluation of the prototype conducted in a simulation laboratory with ten participating physicians. Data from the simulation is analysed by use of theory on how users perceive information. The conclusion is a model, which sum up four principles of interaction for design of CDSS. The four principles for design of user interfaces for CDSS are summarised as four A's: All in one, At a glance, At hand and Attention. The model emphasises integration of all four interaction principles in the design of user interfaces for CDSS, i.e. the model is an integrated model which we suggest as a guide for interaction design when working with preventing medication errors.

Integrating modeling, monitoring, and management to reduce critical uncertainties in water resource decision making.

PubMed

Peterson, James T; Freeman, Mary C

2016-12-01

Stream ecosystems provide multiple, valued services to society, including water supply, waste assimilation, recreation, and habitat for diverse and productive biological communities. Managers striving to sustain these services in the face of changing climate, land uses, and water demands need tools to assess the potential effectiveness of alternative management actions, and often, the resulting tradeoffs between competing objectives. Integrating predictive modeling with monitoring data in an adaptive management framework provides a process by which managers can reduce model uncertainties and thus improve the scientific bases for subsequent decisions. We demonstrate an integration of monitoring data with a dynamic, metapopulation model developed to assess effects of streamflow alteration on fish occupancy in a southeastern US stream system. Although not extensive (collected over three years at nine sites), the monitoring data allowed us to assess and update support for alternative population dynamic models using model probabilities and Bayes rule. We then use the updated model weights to estimate the effects of water withdrawal on stream fish communities and demonstrate how feedback in the form of monitoring data can be used to improve water resource decision making. We conclude that investment in more strategic monitoring, guided by a priori model predictions under alternative hypotheses and an adaptive sampling design, could substantially improve the information available to guide decision-making and management for ecosystem services from lotic systems. Published by Elsevier Ltd.

Strengthening Resiliency in Coastal Watersheds: An Ecosystem Services and Ecological Integrity Decision Support System

EPA Science Inventory

This product provides an integrated assessment framework linked to a decision support system (DSS) that incorporates the ecological integrity (EI) principles and goals described in detail in the US EPA’s Office of Water’s Healthy Watersheds Program (HWP), with Ecosyst...

Building a Bridge into the Future: Dynamic Connectionist Modeling as an Integrative Tool for Research on Intertemporal Choice

PubMed Central

Scherbaum, Stefan; Dshemuchadse, Maja; Goschke, Thomas

2012-01-01

Temporal discounting denotes the fact that individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to a higher extent than suggested by normative economical theories. In this article, we identify three lines of research studying this phenomenon which aim (i) to describe temporal discounting mathematically, (ii) to explain observed choice behavior psychologically, and (iii) to predict the influence of specific factors on intertemporal decisions. We then opt for an approach integrating postulated mechanisms and empirical findings from these three lines of research. Our approach focuses on the dynamical properties of decision processes and is based on computational modeling. We present a dynamic connectionist model of intertemporal choice focusing on the role of self-control and time framing as two central factors determining choice behavior. Results of our simulations indicate that the two influences interact with each other, and we present experimental data supporting this prediction. We conclude that computational modeling of the decision process dynamics can advance the integration of different strands of research in intertemporal choice. PMID:23181048

Building a bridge into the future: dynamic connectionist modeling as an integrative tool for research on intertemporal choice.

PubMed

Scherbaum, Stefan; Dshemuchadse, Maja; Goschke, Thomas

2012-01-01

Temporal discounting denotes the fact that individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to a higher extent than suggested by normative economical theories. In this article, we identify three lines of research studying this phenomenon which aim (i) to describe temporal discounting mathematically, (ii) to explain observed choice behavior psychologically, and (iii) to predict the influence of specific factors on intertemporal decisions. We then opt for an approach integrating postulated mechanisms and empirical findings from these three lines of research. Our approach focuses on the dynamical properties of decision processes and is based on computational modeling. We present a dynamic connectionist model of intertemporal choice focusing on the role of self-control and time framing as two central factors determining choice behavior. Results of our simulations indicate that the two influences interact with each other, and we present experimental data supporting this prediction. We conclude that computational modeling of the decision process dynamics can advance the integration of different strands of research in intertemporal choice.

NASA Remote Sensing Observations for Water Resource and Infrastructure Management

NASA Astrophysics Data System (ADS)

Granger, S. L.; Armstrong, L.; Farr, T.; Geller, G.; Heath, E.; Hyon, J.; Lavoie, S.; McDonald, K.; Realmuto, V.; Stough, T.; Szana, K.

2008-12-01

Decision support tools employed by water resource and infrastructure managers often utilize data products obtained from local sources or national/regional databases of historic surveys and observations. Incorporation of data from these sources can be laborious and time consuming as new products must be identified, cleaned and archived for each new study site. Adding remote sensing observations to the list of sources holds promise for a timely, consistent, global product to aid decision support at regional and global scales by providing global observations of geophysical parameters including soil moisture, precipitation, atmospheric temperature, derived evapotranspiration, and snow extent needed for hydrologic models and decision support tools. However, issues such as spatial and temporal resolution arise when attempting to integrate remote sensing observations into existing decision support tools. We are working to overcome these and other challenges through partnerships with water resource managers, tool developers and other stakeholders. We are developing a new data processing framework, enabled by a core GIS server, to seamlessly pull together observations from disparate sources for synthesis into information products and visualizations useful to the water resources community. A case study approach is being taken to develop the system by working closely with water infrastructure and resource managers to integrate remote observations into infrastructure, hydrologic and water resource decision tools. We present the results of a case study utilizing observations from the PALS aircraft instrument as a proxy for NASA's upcoming Soil Moisture Active Passive (SMAP) mission and an existing commercial decision support tool.

Simulation-optimization model for production planning in the blood supply chain.

PubMed

Osorio, Andres F; Brailsford, Sally C; Smith, Honora K; Forero-Matiz, Sonia P; Camacho-Rodríguez, Bernardo A

2017-12-01

Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

Diverting the tourists: a spatial decision-support system for tourism planning on a developing island

NASA Astrophysics Data System (ADS)

Beedasy, Jaishree; Whyatt, Duncan

Mauritius is a small island (1865 km 2) in the Indian Ocean. Tourism is the third largest economic sector of the country, after manufacturing and agriculture. A limitation of space and the island's vulnerable ecosystem warrants a rational approach to tourism development. The main problems so far have been to manipulate and integrate all the factors affecting tourism planning and to match spatial data with their relevant attributes. A Spatial Decision Support System (SDSS) for sustainable tourism planning is therefore proposed. The proposed SDSS design would include a GIS as its core component. A first GIS model has already been constructed with available data. Supporting decision-making in a spatial context is implicit in the use of GIS. However the analytical capability of the GIS has to be enhanced to solve semi-structured problems, where subjective judgements come into play. The second part of the paper deals with the choice, implementation and customisation of a relevant model to develop a specialised SDSS. Different types of models and techniques are discussed, in particular a comparison of compensatory and non-compensatory approaches to multicriteria evaluation (MCE). It is concluded that compensatory multicriteria evaluation techniques increase the scope of the present GIS model as a decision-support tool. This approach gives the user or decision-maker the flexibility to change the importance of each criterion depending on relevant objectives.

Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

PubMed

Kalogeropoulos, Dimitris A; Carson, Ewart R; Collinson, Paul O

2003-09-01

Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

Don't panic--prepare: towards crisis-aware models of emergency department operations.

PubMed

Ceglowski, Red; Churilov, Leonid; Wasserheil, Jeff

2005-12-01

The existing models of Emergency Department (ED) operations that are based on the "flow-shop" management logic do not provide adequate decision support in dealing with the ED overcrowding crises. A conceptually different crisis-aware approach to ED modelling and operational decision support is introduced in this paper. It is based on Perrow's theory of "normal accidents" and calls for recognizing the inevitable nature of ED overcrowding crises within current health system setup. Managing the crisis before it happens--a standard approach in crisis management area--should become an integral part of ED operations management. The potential implications of adopting such a crisis-aware perspective for health services research and ED management are outlined.

GEOGRAPHICAL INFORMATION SYSTEM, DECISION SUPPORT SYSTEMS, AND URBAN STORMWATER MANAGEMENT

EPA Science Inventory

The full report reviews the application of Geographic Inforamtion System (GIS) technology to the field of urban stormwater modeling. The GIS literature is reviewed in the context of its use as a spatial database for urban stormwater modeling, integration of GIS and hydroloic time...

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.

Use of a Shared Mental Model by a Team Composed of Oncology, Palliative Care, and Supportive Care Clinicians to Facilitate Shared Decision Making in a Patient With Advanced Cancer.

PubMed

D'Ambruoso, Sarah F; Coscarelli, Anne; Hurvitz, Sara; Wenger, Neil; Coniglio, David; Donaldson, Dusty; Pietras, Christopher; Walling, Anne M

2016-11-01

Our case describes the efforts of team members drawn from oncology, palliative care, supportive care, and primary care to assist a woman with advanced cancer in accepting care for her psychosocial distress, integrating prognostic information so that she could share in decisions about treatment planning, involving family in her care, and ultimately transitioning to hospice. Team members in our setting included a medical oncologist, oncology nurse practitioner, palliative care nurse practitioner, oncology social worker, and primary care physician. The core members were the patient and her sister. Our team grew organically as a result of patient need and, in doing so, operationalized an explicitly shared understanding of care priorities. We refer to this shared understanding as a shared mental model for care delivery, which enabled our team to jointly set priorities for care through a series of warm handoffs enabled by the team's close proximity within the same clinic. When care providers outside our integrated team became involved in the case, significant communication gaps exposed the difficulty in extending our shared mental model outside the integrated team framework, leading to inefficiencies in care. Integration of this shared understanding for care and close proximity of team members proved to be key components in facilitating treatment of our patient's burdensome cancer-related distress so that she could more effectively participate in treatment decision making that reflected her goals of care.

Analysis of Advanced Respiratory Support Onboard ISS and CCV

NASA Technical Reports Server (NTRS)

Shah, Ronak V.; Kertsman, Eric L.; Alexander, David J.; Duchesne, Ted; Law, Jennifer; Roden, Sean K.

2014-01-01

NASA is collaborating with private entities for the development of commercial space vehicles. The Space and Clinical Operations Division was tasked to review the oxygen and respiratory support system and recommend what capabilities, if any, the vehicle should have to support the return of an ill or injured crewmember. The Integrated Medical Model (IMM) was utilized as a data source for the development of these recommendations. The Integrated Medical Model (IMM) was used to simulate a six month, six crew, International Space Station (ISS) mission. Three medical system scenarios were considered based on the availability of (1) oxygen only, (2) oxygen and a ventilator, or (3) neither oxygen nor ventilator. The IMM analysis provided probability estimates of medical events that would require either oxygen or ventilator support. It also provided estimates of crew health, the probability of evacuation, and the probability of loss of crew life secondary to medical events for each of the three medical system scenarios. These IMM outputs were used as objective data to enable evidence-based decisions regarding oxygen and respiratory support system requirements for commercial crew vehicles. The IMM provides data that may be utilized to support informed decisions regarding the development of medical systems for commercial crew vehicles.

Assessing the Problem Formulation in an Integrated Assessment Model: Implications for Climate Policy Decision-Support

NASA Astrophysics Data System (ADS)

Garner, G. G.; Reed, P. M.; Keller, K.

2014-12-01

Integrated assessment models (IAMs) are often used with the intent to aid in climate change decisionmaking. Numerous studies have analyzed the effects of parametric and/or structural uncertainties in IAMs, but uncertainties regarding the problem formulation are often overlooked. Here we use the Dynamic Integrated model of Climate and the Economy (DICE) to analyze the effects of uncertainty surrounding the problem formulation. The standard DICE model adopts a single objective to maximize a weighted sum of utilities of per-capita consumption. Decisionmakers, however, may be concerned with a broader range of values and preferences that are not captured by this a priori definition of utility. We reformulate the problem by introducing three additional objectives that represent values such as (i) reliably limiting global average warming to two degrees Celsius and minimizing both (ii) the costs of abatement and (iii) the damages due to climate change. We derive a set of Pareto-optimal solutions over which decisionmakers can trade-off and assess performance criteria a posteriori. We illustrate the potential for myopia in the traditional problem formulation and discuss the capability of this multiobjective formulation to provide decision support.

Cells, circuits, and choices: social influences on perceptual decision making.

PubMed

Mojzisch, Andreas; Krug, Kristine

2008-12-01

Making decisions is an integral part of everyday life. Social psychologists have demonstrated in many studies that humans' decisions are frequently and strongly influenced by the opinions of others--even in simple perceptual decisions, where, for example, participants have to judge what an image looks like. However, because the effect of other people's opinions on decision making has remained largely unaddressed by the neuroimaging and neurophysiology literature, we are only beginning to understand how social influence is integrated into the decision-making process. We put forward the thesis that by probing the neurophysiology of social influence with perceptual decision-making tasks similar to those used in the seminal work of Asch (1952, 1956), this gap could be remedied. Perceptual paradigms are already widely used to probe neuronal mechanisms of decision making in nonhuman primates. There is also increasing evidence about how nonhuman primates' behavior is influenced by observing conspecifics. The high spatial and temporal resolution of neurophysiological recordings in awake monkeys could provide insight into where and how social influence modulates decision making, and thus should enable us to develop detailed functional models of the neural mechanisms that support the integration of social influence into the decision-making process.

Integrating Water Quality and River Rehabilitation Management - A Decision-Analytical Perspective

NASA Astrophysics Data System (ADS)

Reichert, P.; Langhans, S.; Lienert, J.; Schuwirth, N.

2009-04-01

Integrative river management involves difficult decisions about alternative measures to improve their ecological state. For this reason, it seems useful to apply knowledge from the decision sciences to support river management. We discuss how decision-analytical elements can be employed for designing an integrated river management procedure. An important aspect of this procedure is to clearly separate scientific predictions of the consequences of alternatives from objectives to be achieved by river management. The key elements of the suggested procedure are (i) the quantitative elicitation of the objectives from different stakeholder groups, (ii) the compilation of the current scientific knowledge about the consequences of the effects resulting from suggested measures in the form of a probabilistic mathematical model, and (iii) the use of these predictions and valuations to prioritize alternatives, to uncover conflicting objectives, to support the design of better alternatives, and to improve the transparency of communication about the chosen management strategy. The development of this procedure led to insights regarding necessary steps to be taken for rational decision-making in river management, to guidelines about the use of decision-analytical techniques for performing these steps, but also to new insights about the application of decision-analytical techniques in general. In particular, the consideration of the spatial distribution of the effects of measures and the potential added value of connected rehabilitated river reaches leads to favoring measures that have a positive effect beyond a single river reach. As these effects only propagate within the river network, this results in a river basin oriented management concept as a consequence of a rational decision support procedure, rather than as an a priori management paradigm. There are also limitations to the support that can be expected from the decision-analytical perspective. It will not provide the societal values that are driving prioritization in river management, it will only support their elicitation and rational use. This is particularly important for the assessment of micro-pollutants because of severe limitations in scientific knowledge of their effects on river ecosystems. This makes the influence of pollution by micro-pollutants on prioritization of measures strongly dependent on the weight of the precautionary principle relative to other societal objectives of river management.

A Landscape Model (LEEMATH) to Evaluate Effects of Management Impacts on Timber and Wildlife Habitat

Treesearch

Harbin Li; David L. Gartner; Pu Mou; Carl C. Trettin

2000-01-01

Managing forest resources for sustainability requires the successful integration of economic and ecological goals. To attain such integration, land managers need decision support tools that incorporate science, land-use strategies, and policy options to assess resources sustainability at large scales. Landscape Evaluation of Effects of Management Activities on Timber...

HNS-MS : Improving Member States preparedness to face an HNS pollution of the Marine System

NASA Astrophysics Data System (ADS)

Legrand, Sebastien; Le Floch, Stéphane; Aprin, Laurent; Parthenay, Valérie; Donnay, Eric; Parmentier, Koen; Ovidio, Fabrice; Schallier, Ronny; Poncet, Florence; Chataing, Sophie; Poupon, Emmanuelle; Hellouvry, Yann-Hervé

2016-04-01

When dealing with a HNS pollution incident, one of the priority requirements is the identification of the hazard and an assessment of the risk posed to the public and responder safety, the environment and socioeconomic assets upon which a state or coastal community depend. The primary factors which determine the safety, environmental and socioeconomic impact of the released substance(s) relate to their physico-chemical properties and fate in the environment. Until now, preparedness actions at various levels have primarily aimed at classifying the general environmental or public health hazard of an HNS, or at performing a risk analysis of HNS transported in European marine regions. Operational datasheets have been (MIDSIS-TROCS) or are being (MAR-CIS) developed collating detailed, substance-specific information for responders and covering information needs at the first stage of an incident. However, contrary to oil pollution preparedness and response tools, only few decision-support tools used by Member State authorities (Coastguard agencies or other) integrate 3D models that are able to simulate the drift, fate and behaviour of HNS spills in the marine environment. When they do, they usually consider simplified or steady-state environmental conditions. Moreover, the above-mentioned available HNS information is currently not sufficiently detailed or not suitably classified to be used as an input for an advanced HNS support decision tool. HNS-MS aims at developing a 'one-stop shop' integrated HNS decision-support tool that is able to predict the drift, behaviour and Fate of HNS spills under realistic environmental conditions and at providing key product information - drawing upon and in complement to existing studies and databases - to improve the understanding and evaluation of a HNS spill situation in the field and the environmental and safety-related issues at stake. The 3D HNS drift and fate model and decision-support tool will also be useful at the preparedness stage. The expected results will be an operational HNS decision-support tool (prototype) for the Bonn Agreement area that can also be viewed as a demonstrator tool for other European marine regions. The developed tool will have a similar operational level as OSERIT, the Belgian oil spill drift model. The HNS decision-support tool will integrate the following features: 1. A database containing the physico-chemical parameters needed to compute the behaviour in the marine environment of 100+ relevant HNS; 2. A database of environmental and socioeconomic HNS-sensitive features; 3. A three dimensional HNS spill drift and fate model able to simulate HNS behaviour in the marine environment (including floaters, sinkers, evaporators and dissolvers). 4. A user-friendly web-based interface allowing Coastguard stations to launch a HNS drift simulation and visualize post-processed results in support of an incident evaluation and decision-making process. In this contribution, we will present the methodology followed to develop these four features.

Implementation of workflow engine technology to deliver basic clinical decision support functionality.

PubMed

Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

2011-04-10

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.

Further development and implementation of the DIWA distributed hydrological model-based integrated hydroinformatics system in the Danube River Basin for supporting decision making in water management

NASA Astrophysics Data System (ADS)

Szabó, J. A.; Réti, G. Z.; Tóth, T.

2012-04-01

Today, the most significant mission of the decision makers on integrated water management issues is to carry out sustainable management for sharing the resources between a variety of users and the environment under conditions of considerable uncertainty (such as climate/land use/population/etc. change) conditions. In light of this increasing water management complexity, we consider that the most pressing needs is to develop and implement up-to-date Spatial Decision Support Systems (SDSS) for aiding decision-making processes to improve water management. One of the most important parts of such an SDSS is a distributed hydrologic model-based integrated hydroinformatics system to analyze the different scenarios. The less successful statistical and/or empirical model-experiments of earlier decades have highlighted the importance of paradigm shift in hydrological modelling approach towards the physically based distributed models, to better describe the complex hydrological processes even on catchments of more ten thousands of square km. Answers to questions like what are the effects of human actions in the catchment area (e. g. forestation or deforestation) or the changing of climate/land use on the flood, drought, or water scarcity, or what is the optimal strategy for planning and/or operating reservoirs, have become increasingly important. Nowadays the answers to this kind of questions can be provided more easily than before. The progress of applied mathematical methods, the advanced state of computer technology as well as the development of remote sensing and meteorological radar technology have accelerated the research capable of answering these questions using well-designed integrated hydroinformatics systems. With most emphasis on the recent years of extensive scientific and computational development HYDROInform UnLtd developed a distributed hydrological model-based integrated hydroinformatics system for supporting the various decisions in water management. Our developed integrated model has two basic pillars: the DIWA (DIstributed WAtershed) hydrologic, and the well-known HEC-RAS hydraulic models. The DIWA is a dynamic water-balance model that distributed both in space and its parameters, and which was developed along combined principles but its mostly based on physical foundations. According to the philosophy of the distributed model approach the catchment is divided into basic elements, cells where the basin characteristics, parameters, physical properties, and the boundary conditions are applied in the centre of the cell, and the cell is supposed to be homogenous between the block boundaries. The neighbouring cells are connected to each other according to runoff hierarchy (local drain direction). Applying the hydrological mass balance and the adequate dynamic equations to these cells, the result is a distributed hydrological model on a continuous, 3D gridded domain. For calculating the water level as well the HEC-RASS hydraulic model has been embedded into DIWA model. In this integration the DIWA model provides the upper boundary conditions for HEC-RAS, and then HEC-RAS provides the water levels along the lowland parts of the river-network. In this presentation, our recently developed integrated hydroinformatics system and its implementation for the middle-upper part of the Danube River Basin will be reported. Following an outline of the backgrounds, an overview on the DIWA and the integrated model-system will be given. The implementation of this integrated hydroinformatics system in the Danube River Basin will also be presented, including a summary of the developed 1km resolution geo-dataset for the modelling. Then some demonstrative results of the use of the pre-calibrated system will be discussed. Finally, an outline of the future steps of the development will be discussed.

LUMINATE: Linking agricultural land use, local water quality and Gulf of Mexico hypoxia

USDA-ARS?s Scientific Manuscript database

In this paper, we discuss the importance of developing integrated assessment models to support the design and implementation of policies to address water quality problems associated with agricultural pollution. We describe a new modelling system, LUMINATE, which links land use decisions made at the...

Spatially targeted social interventions to improve BMP adoption in Maryland watersheds

USDA-ARS?s Scientific Manuscript database

The results of surveys of stakeholders knowledge and attitudes related to water resources, pollution and Best Management Practices (BMPs) are analyzed and used to develop a model of BMP adoption likelihood based on socio-economic factors. The model is integrated into a Diagnostic Decision Support Sy...

An Integrated Decision Support System with Hydrological Processes and Socio-economic Assessments

NASA Astrophysics Data System (ADS)

Yu, Yang; Disse, Markus; Yu, Ruide

2017-04-01

The debate over the effectiveness of Integrated Water Resources Management (IWRM) in practice has lasted for years. As the complexity and scope of IWRM increases, the difficulties of hydrological modeling is shifting from the model itself into the links with other cognate sciences, to understand the interactions among water, earth, ecosystem and humans. This work presents the design and development of a decision support system (DSS) that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use changes. Discharge and glacier geometry changes were simulated with hydrological model WASA. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were integrated as inputs into the DSS in three types of links: regression equations, stationary data inputs, or dynamic data inputs into DSS as the models running parallel in the simulation periods. Within DSS, three types of logics were established: equations, conditional statements and fuzzy logics. The programming was realized in C++. The implementation of DSS takes place in the Tarim River Basin. With the mainstream of 1,321km and located in an arid area in northwest China, the Tarim River is China's longest inland river. The Tarim basin on the northern edge of the Taklamakan desert is an extremely arid region. In this region, agricultural water consumption and allocation management are crucial to address the conflicts among irrigation water users from upstream to downstream. Since 2011, the German Ministry of Science and Education BMBF established the Sino-German SuMaRiO project, for the sustainable management of river oases along the Tarim River. Project SuMaRiO focus on realizable management strategies, considering social, economic and ecological criteria. This will have positive effects for nearly 10 million inhabitants of different ethnic groups. DSS is the main outcome of SuMaRiO. The overall goal of the DSS is to integrate all crucial research results of SuMaRiO, also including stakeholder perspectives, into a model based decision support system, which allows a Sustainability Impact Assessment (SIA) within regional planning. This SIA will take into account the perspectives of all relevant actors in the problem field of land and water management in the Tarim River Basin, to understand ecosystem services (ESS) and integrating them into land and water management. Under scenario assumptions, possible actions and their impacts are estimated in a semi-quantitative way with the help of sustainable indicators, which includes climate indicators, socio-economic Indicators, management Indicators, and ESS Indicators. A user-friendly graphical user interface (GUI) was developed to assist the decision-makers and common users, with Chinese and English versions available at the moment.

NOAA's National Water Model - Integration of National Water Model with Geospatial Data creating Water Intelligence

NASA Astrophysics Data System (ADS)

Clark, E. P.; Cosgrove, B.; Salas, F.

2016-12-01

As a significant step forward to transform NOAA's water prediction services, NOAA plans to implement a new National Water Model (NWM) Version 1.0 in August 2016. A continental scale water resources model, the NWM is an evolution of the WRF-Hydro architecture developed by the National Center for Atmospheric Research (NCAR). The NWM will provide analyses and forecasts of flow for the 2.7 million stream reaches nationwide in the National Hydrography Dataset Plus v2 (NHDPlusV2) jointly developed by the USGS and EPA. The NWM also produces high-resolution water budget variables of snow, soil moisture, and evapotranspiration on a 1-km grid. NOAA's stakeholders require additional decision support application to be built on these data. The Geo-intelligence division of the Office of Water Prediction is building new products and services that integrate output from the NWM with geospatial datasets such as infrastructure and demographics to better estimate the impacts dynamic water resource states on community resiliency. This presentation will detail the methods and underlying information to produce prototypes water resources intelligence that is timely, actionable and credible. Moreover, it will to explore the NWM capability to support sector-specific decision support services.

Dynamic Integration of Value Information into a Common Probability Currency as a Theory for Flexible Decision Making

PubMed Central

Christopoulos, Vassilios; Schrater, Paul R.

2015-01-01

Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation. PMID:26394299

Integrating geographically isolated wetlands into land management decisions

USGS Publications Warehouse

Golden, Heather E.; Creed, Irena F.; Ali, Genevieve; Basu, Nandita; Neff, Brian; Rains, Mark C.; McLaughlin, Daniel L.; Alexander, Laurie C.; Ameli, Ali A.; Christensen, Jay R.; Evenson, Grey R.; Jones, Charles N.; Lane, Charles R.; Lang, Megan

2017-01-01

Wetlands across the globe provide extensive ecosystem services. However, many wetlands – especially those surrounded by uplands, often referred to as geographically isolated wetlands (GIWs) – remain poorly protected. Protection and restoration of wetlands frequently requires information on their hydrologic connectivity to other surface waters, and their cumulative watershed‐scale effects. The integration of measurements and models can supply this information. However, the types of measurements and models that should be integrated are dependent on management questions and information compatibility. We summarize the importance of GIWs in watersheds and discuss what wetland connectivity means in both science and management contexts. We then describe the latest tools available to quantify GIW connectivity and explore crucial next steps to enhancing and integrating such tools. These advancements will ensure that appropriate tools are used in GIW decision making and maintaining the important ecosystem services that these wetlands support.

Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.

PubMed

Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M

2005-06-01

This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.

An Integrated Decision Support System for Water Quality Management of Songhua River Basin

NASA Astrophysics Data System (ADS)

Zhang, Haiping; Yin, Qiuxiao; Chen, Ling

2010-11-01

In the Songhua River Basin of China, many water resource and water environment conflicts interact. A Decision Support System (DSS) for the water quality management has been established for the Basin. The System is featured by the incorporation of a numerical water quality model system into a conventional water quality management system which usually consists of geographic information system (GIS), WebGIS technology, database system and network technology. The model system is built based on DHI MIKE software comprising of a basin rainfall-runoff module, a basin pollution load evaluation module, a river hydrodynamic module and a river water quality module. The DSS provides a friendly graphical user interface that enables the rapid and transparent calculation of various water quality management scenarios, and also enables the convenient access and interpretation of the modeling results to assist the decision-making.

Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

PubMed

Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu

2016-08-15

Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision. Copyright © 2016 Elsevier B.V. All rights reserved.

A decision support model for investment on P2P lending platform.

PubMed

Zeng, Xiangxiang; Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace-Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone.

A decision support model for investment on P2P lending platform

PubMed Central

Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace—Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone. PMID:28877234

Computerised decision support in physical activity interventions: A systematic literature review.

PubMed

Triantafyllidis, Andreas; Filos, Dimitris; Claes, Jomme; Buys, Roselien; Cornelissen, Véronique; Kouidi, Evangelia; Chouvarda, Ioanna; Maglaveras, Nicos

2018-03-01

The benefits of regular physical activity for health and quality of life are unarguable. New information, sensing and communication technologies have the potential to play a critical role in computerised decision support and coaching for physical activity. We provide a literature review of recent research in the development of physical activity interventions employing computerised decision support, their feasibility and effectiveness in healthy and diseased individuals, and map out challenges and future research directions. We searched the bibliographic databases of PubMed and Scopus to identify physical activity interventions with computerised decision support utilised in a real-life context. Studies were synthesized according to the target user group, the technological format (e.g., web-based or mobile-based) and decision-support features of the intervention, the theoretical model for decision support in health behaviour change, the study design, the primary outcome, the number of participants and their engagement with the intervention, as well as the total follow-up duration. From the 24 studies included in the review, the highest percentage (n = 7, 29%) targeted sedentary healthy individuals followed by patients with prediabetes/diabetes (n = 4, 17%) or overweight individuals (n = 4, 17%). Most randomized controlled trials reported significantly positive effects of the interventions, i.e., increase in physical activity (n = 7, 100%) for 7 studies assessing physical activity measures, weight loss (n = 3, 75%) for 4 studies assessing diet, and reductions in glycosylated hemoglobin (n = 2, 66%) for 3 studies assessing glycose concentration. Accelerometers/pedometers were used in almost half of the studies (n = 11, 46%). Most adopted decision support features included personalised goal-setting (n = 16, 67%) and motivational feedback sent to the users (n = 15, 63%). Fewer adopted features were integration with electronic health records (n = 3, 13%) and alerts sent to caregivers (n = 4, 17%). Theoretical models of decision support in health behaviour to drive the development of the intervention were not reported in most studies (n = 14, 58%). Interventions employing computerised decision support have the potential to promote physical activity and result in health benefits for both diseased and healthy individuals, and help healthcare providers to monitor patients more closely. Objectively measured activity through sensing devices, integration with clinical systems used by healthcare providers and theoretical frameworks for health behaviour change need to be employed in a larger scale in future studies in order to realise the development of evidence-based computerised systems for physical activity monitoring and coaching. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrated Modeling for Road Condition Prediction (IMRCP)

DOT National Transportation Integrated Search

2018-01-17

Intelligent transportation system deployments have enabled great advances in operational awareness and response based on the data they gather on the current state of the roadways. The next step in decision support is to forecast road conditions and b...

Development of a real-time clinical decision support system upon the web mvc-based architecture for prostate cancer treatment

PubMed Central

2011-01-01

Background A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. Methods We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. Results The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Conclusions Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases. PMID:21385459

Development of a real-time clinical decision support system upon the Web MVC-based architecture for prostate cancer treatment.

PubMed

Lin, Hsueh-Chun; Wu, Hsi-Chin; Chang, Chih-Hung; Li, Tsai-Chung; Liang, Wen-Miin; Wang, Jong-Yi Wang

2011-03-08

A real-time clinical decision support system (RTCDSS) with interactive diagrams enables clinicians to instantly and efficiently track patients' clinical records (PCRs) and improve their quality of clinical care. We propose a RTCDSS to process online clinical informatics from multiple databases for clinical decision making in the treatment of prostate cancer based on Web Model-View-Controller (MVC) architecture, by which the system can easily be adapted to different diseases and applications. We designed a framework upon the Web MVC-based architecture in which the reusable and extractable models can be conveniently adapted to other hospital information systems and which allows for efficient database integration. Then, we determined the clinical variables of the prostate cancer treatment based on participating clinicians' opinions and developed a computational model to determine the pretreatment parameters. Furthermore, the components of the RTCDSS integrated PCRs and decision factors for real-time analysis to provide evidence-based diagrams upon the clinician-oriented interface for visualization of treatment guidance and health risk assessment. The resulting system can improve quality of clinical treatment by allowing clinicians to concurrently analyze and evaluate the clinical markers of prostate cancer patients with instantaneous clinical data and evidence-based diagrams which can automatically identify pretreatment parameters. Moreover, the proposed RTCDSS can aid interactions between patients and clinicians. Our proposed framework supports online clinical informatics, evaluates treatment risks, offers interactive guidance, and provides real-time reference for decision making in the treatment of prostate cancer. The developed clinician-oriented interface can assist clinicians in conveniently presenting evidence-based information to patients and can be readily adapted to an existing hospital information system and be easily applied in other chronic diseases.

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

NASA Astrophysics Data System (ADS)

Pontius, J.; Duncan, J.

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Distributed software framework and continuous integration in hydroinformatics systems

NASA Astrophysics Data System (ADS)

Zhou, Jianzhong; Zhang, Wei; Xie, Mengfei; Lu, Chengwei; Chen, Xiao

2017-08-01

When encountering multiple and complicated models, multisource structured and unstructured data, complex requirements analysis, the platform design and integration of hydroinformatics systems become a challenge. To properly solve these problems, we describe a distributed software framework and it’s continuous integration process in hydroinformatics systems. This distributed framework mainly consists of server cluster for models, distributed database, GIS (Geographic Information System) servers, master node and clients. Based on it, a GIS - based decision support system for joint regulating of water quantity and water quality of group lakes in Wuhan China is established.

Integrated corridor management initiative : demonstration phase evaluation - Dallas decision support system analysis test plan.

DOT National Transportation Integrated Search

2012-08-01

This report presents the test plan for conducting the Decision Support System (DSS) Analysis for the United States Department of Transportation (U.S. DOT) evaluation of the Dallas U.S. 75 Integrated Corridor Management (ICM) Initiative Demonstration....

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The role of emotion in decision-making: a cognitive neuroeconomic approach towards understanding sexual risk behavior.

PubMed

Gutnik, Lily A; Hakimzada, A Forogh; Yoskowitz, Nicole A; Patel, Vimla L

2006-12-01

Models of decision-making usually focus on cognitive, situational, and socio-cultural variables in accounting for human performance. However, the emotional component is rarely addressed within these models. This paper reviews evidence for the emotional aspect of decision-making and its role within a new framework of investigation, called neuroeconomics. The new approach aims to build a comprehensive theory of decision-making, through the unification of theories and methods from economics, psychology, and neuroscience. In this paper, we review these integrative research methods and their applications to issues of public health, with illustrative examples from our research on young adults' safe sex practices. This approach promises to be valuable as a comprehensively descriptive and possibly, better predictive model for construction and customization of decision support tools for health professionals and consumers.

Development and Validation of a Primary Care-Based Family Health History and Decision Support Program (MeTree)

PubMed Central

Orlando, Lori A.; Buchanan, Adam H.; Hahn, Susan E.; Christianson, Carol A.; Powell, Karen P.; Skinner, Celette Sugg; Chesnut, Blair; Blach, Colette; Due, Barbara; Ginsburg, Geoffrey S.; Henrich, Vincent C.

2016-01-01

INTRODUCTION Family health history is a strong predictor of disease risk. To reduce the morbidity and mortality of many chronic diseases, risk-stratified evidence-based guidelines strongly encourage the collection and synthesis of family health history to guide selection of primary prevention strategies. However, the collection and synthesis of such information is not well integrated into clinical practice. To address barriers to collection and use of family health histories, the Genomedical Connection developed and validated MeTree, a Web-based, patient-facing family health history collection and clinical decision support tool. MeTree is designed for integration into primary care practices as part of the genomic medicine model for primary care. METHODS We describe the guiding principles, operational characteristics, algorithm development, and coding used to develop MeTree. Validation was performed through stakeholder cognitive interviewing, a genetic counseling pilot program, and clinical practice pilot programs in 2 community-based primary care clinics. RESULTS Stakeholder feedback resulted in changes to MeTree’s interface and changes to the phrasing of clinical decision support documents. The pilot studies resulted in the identification and correction of coding errors and the reformatting of clinical decision support documents. MeTree’s strengths in comparison with other tools are its seamless integration into clinical practice and its provision of action-oriented recommendations guided by providers’ needs. LIMITATIONS The tool was validated in a small cohort. CONCLUSION MeTree can be integrated into primary care practices to help providers collect and synthesize family health history information from patients with the goal of improving adherence to risk-stratified evidence-based guidelines. PMID:24044145

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

Corley, Courtney D.; Noonan, Christine F.; Bartholomew, Rachel A.

The U.S. Department of Homeland Security (DHS) National Biosurveillance Integration Center (NBIC) was established in 2008 with a primary mission to “(1) enhance the capability of the Federal Government to (A) rapidly identify, characterize, localize, and track a biological event of national concern by integrating and analyzing data relating to human health, animal, plant, food, and environmental monitoring systems (both national and international); and (B) disseminate alerts and other information to Member Agencies and, in coordination with (and where possible through) Member Agencies, to agencies of State, local, and tribal governments, as appropriate, to enhance the ability of such agenciesmore » to respond to a biological event of national concern; and (2) oversee development and operation of the National Biosurveillance Integration System (NBIS).” Inherent in its mission then and the broader NBIS, NBIC is concerned with the identification, understanding, and use of a variety of biosurveillance models and systems. The goal of this project is to characterize, evaluate, classify, and catalog existing disease forecast and prediction models that could provide operational decision support for recognizing a biological event having a potentially significant impact. Additionally, gaps should be identified and recommendations made on using disease models in an operational environment to support real-time decision making.« less

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.

Integrated decision support tools for Puget Sound salmon recovery planning

EPA Science Inventory

We developed a set of tools to provide decision support for community-based salmon recovery planning in Salish Sea watersheds. Here we describe how these tools are being integrated and applied in collaboration with Puget Sound tribes and community stakeholders to address restora...

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-level Winds For Space Launch

NASA Technical Reports Server (NTRS)

Bauman, William H., III; Flinn, Clay

2012-01-01

Launch directors need to know upper-level wind forecasts. We developed an Excel-based GUI to display upper-level winds: (1) Rawinsonde at CCAFS, (2) Wind profilers at KSC, (3) Model point data at CCAFS.

Clarity versus complexity: land-use modeling as a practical tool for decision-makers

USGS Publications Warehouse

Sohl, Terry L.; Claggett, Peter

2013-01-01

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

A Watershed-scale Design Optimization Model for Stormwater Best Management Practices

EPA Science Inventory

U.S. Environmental Protection Agency developed a decision-support system, System for Urban Stormwater Treatment and Analysis Integration (SUSTAIN), to evaluate alternative plans for stormwater quality management and flow abatement techniques in urban and developing areas. SUSTAI...

Salmon recovery planning using the VELMA model

EPA Science Inventory

We developed a set of tools to provide decision support for community-based salmon recovery planning in Pacific Northwest watersheds. This seminar describes how these tools are being integrated and applied in collaboration with Puget Sound tribes and community stakeholders to add...

Surface transportation weather decision support requirements : operational concept description : advanced-integrated decision support using weather information for surface transportation decisions makers : draft version 2.0

DOT National Transportation Integrated Search

2000-07-14

This is a draft document for the Surface Transportation Weather Decision Support Requirements (STWDSR) project. The STWDSR project is being conducted for the FHWAs Office of Transportation Operations (HOTO) Road Weather Management Program by Mitre...

The Enterprise Data Trust at Mayo Clinic: a semantically integrated warehouse of biomedical data

PubMed Central

Beck, Scott A; Fisk, Thomas B; Mohr, David N

2010-01-01

Mayo Clinic's Enterprise Data Trust is a collection of data from patient care, education, research, and administrative transactional systems, organized to support information retrieval, business intelligence, and high-level decision making. Structurally it is a top-down, subject-oriented, integrated, time-variant, and non-volatile collection of data in support of Mayo Clinic's analytic and decision-making processes. It is an interconnected piece of Mayo Clinic's Enterprise Information Management initiative, which also includes Data Governance, Enterprise Data Modeling, the Enterprise Vocabulary System, and Metadata Management. These resources enable unprecedented organization of enterprise information about patient, genomic, and research data. While facile access for cohort definition or aggregate retrieval is supported, a high level of security, retrieval audit, and user authentication ensures privacy, confidentiality, and respect for the trust imparted by our patients for the respectful use of information about their conditions. PMID:20190054

The Enterprise Data Trust at Mayo Clinic: a semantically integrated warehouse of biomedical data.

PubMed

Chute, Christopher G; Beck, Scott A; Fisk, Thomas B; Mohr, David N

2010-01-01

Mayo Clinic's Enterprise Data Trust is a collection of data from patient care, education, research, and administrative transactional systems, organized to support information retrieval, business intelligence, and high-level decision making. Structurally it is a top-down, subject-oriented, integrated, time-variant, and non-volatile collection of data in support of Mayo Clinic's analytic and decision-making processes. It is an interconnected piece of Mayo Clinic's Enterprise Information Management initiative, which also includes Data Governance, Enterprise Data Modeling, the Enterprise Vocabulary System, and Metadata Management. These resources enable unprecedented organization of enterprise information about patient, genomic, and research data. While facile access for cohort definition or aggregate retrieval is supported, a high level of security, retrieval audit, and user authentication ensures privacy, confidentiality, and respect for the trust imparted by our patients for the respectful use of information about their conditions.

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

PubMed

Li, Yan

2017-05-25

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

From Population Databases to Research and Informed Health Decisions and Policy.

PubMed

Machluf, Yossy; Tal, Orna; Navon, Amir; Chaiter, Yoram

2017-01-01

In the era of big data, the medical community is inspired to maximize the utilization and processing of the rapidly expanding medical datasets for clinical-related and policy-driven research. This requires a medical database that can be aggregated, interpreted, and integrated at both the individual and population levels. Policymakers seek data as a lever for wise, evidence-based decision-making and information-driven policy. Yet, bridging the gap between data collection, research, and policymaking, is a major challenge. To bridge this gap, we propose a four-step model: (A) creating a conjoined task force of all relevant parties to declare a national program to promote collaborations; (B) promoting a national digital records project, or at least a network of synchronized and integrated databases, in an accessible transparent manner; (C) creating an interoperative national research environment to enable the analysis of the organized and integrated data and to generate evidence; and (D) utilizing the evidence to improve decision-making, to support a wisely chosen national policy. For the latter purpose, we also developed a novel multidimensional set of criteria to illuminate insights and estimate the risk for future morbidity based on current medical conditions. Used by policymakers, providers of health plans, caregivers, and health organizations, we presume this model will assist transforming evidence generation to support the design of health policy and programs, as well as improved decision-making about health and health care, at all levels: individual, communal, organizational, and national.

Bridging the Gap between Human Judgment and Automated Reasoning in Predictive Analytics

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

Sanfilippo, Antonio P.; Riensche, Roderick M.; Unwin, Stephen D.

2010-06-07

Events occur daily that impact the health, security and sustainable growth of our society. If we are to address the challenges that emerge from these events, anticipatory reasoning has to become an everyday activity. Strong advances have been made in using integrated modeling for analysis and decision making. However, a wider impact of predictive analytics is currently hindered by the lack of systematic methods for integrating predictive inferences from computer models with human judgment. In this paper, we present a predictive analytics approach that supports anticipatory analysis and decision-making through a concerted reasoning effort that interleaves human judgment and automatedmore » inferences. We describe a systematic methodology for integrating modeling algorithms within a serious gaming environment in which role-playing by human agents provides updates to model nodes and the ensuing model outcomes in turn influence the behavior of the human players. The approach ensures a strong functional partnership between human players and computer models while maintaining a high degree of independence and greatly facilitating the connection between model and game structures.« less

Invasive Species Forecasting System: A Decision Support Tool for the U.S. Geological Survey: FY 2005 Benchmarking Report v.1.6

NASA Technical Reports Server (NTRS)

Stohlgren, Tom; Schnase, John; Morisette, Jeffrey; Most, Neal; Sheffner, Ed; Hutchinson, Charles; Drake, Sam; Van Leeuwen, Willem; Kaupp, Verne

2005-01-01

The National Institute of Invasive Species Science (NIISS), through collaboration with NASA's Goddard Space Flight Center (GSFC), recently began incorporating NASA observations and predictive modeling tools to fulfill its mission. These enhancements, labeled collectively as the Invasive Species Forecasting System (ISFS), are now in place in the NIISS in their initial state (V1.0). The ISFS is the primary decision support tool of the NIISS for the management and control of invasive species on Department of Interior and adjacent lands. The ISFS is the backbone for a unique information services line-of-business for the NIISS, and it provides the means for delivering advanced decision support capabilities to a wide range of management applications. This report describes the operational characteristics of the ISFS, a decision support tool of the United States Geological Survey (USGS). Recent enhancements to the performance of the ISFS, attained through the integration of observations, models, and systems engineering from the NASA are benchmarked; i.e., described quantitatively and evaluated in relation to the performance of the USGS system before incorporation of the NASA enhancements. This report benchmarks Version 1.0 of the ISFS.

Summary of hydrologic modeling for the Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER)

USGS Publications Warehouse

Williamson, Tanja N.; Lant, Jeremiah G.; Claggett, Peter; Nystrom, Elizabeth A.; Milly, Paul C.D.; Nelson, Hugh L.; Hoffman, Scott A.; Colarullo, Susan J.; Fischer, Jeffrey M.

2015-11-18

The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.

Decision Support For Digester Algae Integration For Improved Environmental And Economic Sustainability

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

Guillen, Donna P.; Panike, Katherine R.; Havlovick, Caryn M.

The Idaho National Laboratory (INL) has teamed with University of Idaho and Boise State University to make the use of ADs more attractive by implementing a two-stage AD and coupling additional processes to the system. The addition of a polyhydroxyalkanoate (PHA) reactor, algae cultivation system, and a biomass treatment system such as fast-pyrolysis or hydrothermal liquefaction (HTL) would further sequester carbon and nutrients, as well as add valuable products that can be sold or used on-site to mitigate costs. The Decision-support for Digester-Algae IntegRation for Improved Environmental and Economic Sustainability (DAIRIEES) technoeconomic model will play a key role in evaluatingmore » the effectiveness and viability of this system to achieve economic and environmental sustainability by the dairy industry.« less

Towards the ecotourism: a decision support model for the assessment of sustainability of mountain huts in the Alps.

PubMed

Stubelj Ars, Mojca; Bohanec, Marko

2010-12-01

This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts' surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists. Copyright © 2010 Elsevier Ltd. All rights reserved.

Evaluating critical uncertainty thresholds in a spatial model of forest pest invasion risk

Treesearch

Frank H. Koch; Denys Yemshanov; Daniel W. McKenney; William D. Smith

2009-01-01

Pest risk maps can provide useful decision support in invasive species management, but most do not adequately consider the uncertainty associated with predicted risk values. This study explores how increased uncertainty in a risk model’s numeric assumptions might affect the resultant risk map. We used a spatial stochastic model, integrating components for...

A Data Driven Framework for Integrating Regional Climate Models

NASA Astrophysics Data System (ADS)

Lansing, C.; Kleese van Dam, K.; Liu, Y.; Elsethagen, T.; Guillen, Z.; Stephan, E.; Critchlow, T.; Gorton, I.

2012-12-01

There are increasing needs for research addressing complex climate sensitive issues of concern to decision-makers and policy planners at a regional level. Decisions about allocating scarce water across competing municipal, agricultural, and ecosystem demands is just one of the challenges ahead, along with decisions regarding competing land use priorities such as biofuels, food, and species habitat. Being able to predict the extent of future climate change in the context of introducing alternative energy production strategies requires a new generation of modeling capabilities. We will also need more complete representations of human systems at regional scales, incorporating the influences of population centers, land use, agriculture and existing and planned electrical demand and generation infrastructure. At PNNL we are working towards creating a first-of-a-kind capability known as the Integrated Regional Earth System Model (iRESM). The fundamental goal of the iRESM initiative is the critical analyses of the tradeoffs and consequences of decision and policy making for integrated human and environmental systems. This necessarily combines different scientific processes, bridging different temporal and geographic scales and resolving the semantic differences between them. To achieve this goal, iRESM is developing a modeling framework and supporting infrastructure that enable the scientific team to evaluate different scenarios in light of specific stakeholder questions such as "How do regional changes in mean climate states and climate extremes affect water storage and energy consumption and how do such decisions influence possible mitigation and carbon management schemes?" The resulting capability will give analysts a toolset to gain insights into how regional economies can respond to climate change mitigation policies and accelerated deployment of alternative energy technologies. The iRESM framework consists of a collection of coupled models working with high resolution data that can represent the climate, geography, economy, energy supply, and demand of a region under study; an integrated data management framework that captures information about models, model couplings (workflows), observational and derived data sets, numerical experiments, and the provenance metadata connecting them; and a collaborative environment that enables scientific users to explore the datasets, register models and codes, launch workflows, retrieve provenance, and analyze results. In this presentation we address the challenges of coupling heterogeneous codes and handling large data sets. We describe our integration approach, which is based on a loosely coupled software architecture that supports experimentation and evolution of models on different datasets. We present our software prototype and show the scalability of our approach to handle a large number ( > 17,000) of model runs and a significant quantity of data in the order of terabytes. The resulting environment is now used by domain scientists and has proven useful to improve productivity in the evolving development of iRESM model coupling.

Implementation of workflow engine technology to deliver basic clinical decision support functionality

PubMed Central

2011-01-01

Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform. PMID:21477364

A framework for developing and integrating effective routing strategies within the emergency management decision-support system.

DOT National Transportation Integrated Search

2012-05-01

This report describes the modeling, calibration, and validation of a VISSIM traffic-flow simulation of the San Jos, California, downtown network and examines various evacuation scenarios and first-responder routings to assess strategies that would ...

A work-centered cognitively based architecture for decision support: the work-centered infomediary layer (WIL) model

NASA Astrophysics Data System (ADS)

Zachary, Wayne; Eggleston, Robert; Donmoyer, Jason; Schremmer, Serge

2003-09-01

Decision-making is strongly shaped and influenced by the work context in which decisions are embedded. This suggests that decision support needs to be anchored by a model (implicit or explicit) of the work process, in contrast to traditional approaches that anchor decision support to either context free decision models (e.g., utility theory) or to detailed models of the external (e.g., battlespace) environment. An architecture for cognitively-based, work centered decision support called the Work-centered Informediary Layer (WIL) is presented. WIL separates decision support into three overall processes that build and dynamically maintain an explicit context model, use the context model to identify opportunities for decision support and tailor generic decision-support strategies to the current context and offer them to the system-user/decision-maker. The generic decision support strategies include such things as activity/attention aiding, decision process structuring, work performance support (selective, contextual automation), explanation/ elaboration, infosphere data retrieval, and what if/action-projection and visualization. A WIL-based application is a work-centered decision support layer that provides active support without intent inferencing, and that is cognitively based without requiring classical cognitive task analyses. Example WIL applications are detailed and discussed.

Supported Decision Making: A Synthesis of the Literature across Intellectual Disability, Mental Health, and Aging

ERIC Educational Resources Information Center

Shogren, Karrie A.; Wehmeyer, Michael L.; Lassmann, Heather; Forber-Pratt, Anjali J.

2017-01-01

Supported decision making (SDM) has begun to receive significant attention as means to enable people to exercise autonomy and self-determination over decisions about their life. Practice frameworks that can be used to promote the provision of supports for decision making are needed. This paper integrates the literature across intellectual and…

Parallel constraint satisfaction in memory-based decisions.

PubMed

Glöckner, Andreas; Hodges, Sara D

2011-01-01

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

Enhancing the Impact of Family Justice Centers via Motivational Interviewing: An Integrated Review.

PubMed

Simmons, Catherine A; Howell, Kathryn H; Duke, Michael R; Beck, J Gayle

2016-12-01

The Family Justice Center (FJC) model is an approach to assisting survivors of intimate partner violence (IPV) that focuses on integration of services under one roof and co-location of staff members from a range of multidisciplinary agencies. Even though the FJC model is touted as a best practice strategy to help IPV survivors, empirical support for the effectiveness of this approach is scarce. The current article consolidates this small yet promising body of empirically based literature in a clinically focused review. Findings point to the importance of integrating additional resources into the FJC model to engage IPV survivors who have ambivalent feelings about whether to accept help, leave the abusive relationship, and/or participate in criminal justice processes to hold the offender accountable. One such resource, motivational interviewing (MI), holds promise in aiding IPV survivors with these decisions, but empirical investigation into how MI can be incorporated into the FJC model has yet to be published. This article, therefore, also integrates the body of literature supporting the FJC model with the body of literature supporting MI with IPV survivors. Implications for practice, policy, and research are incorporated throughout this review. © The Author(s) 2015.

An Integrated Web-based Decision Support System in Disaster Risk Management

NASA Astrophysics Data System (ADS)

Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

2012-04-01

Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact-probability matrix in terms of socio-economic dimension.

Collaboration and Synergy among Government, Industry and Academia in M&S Domain: Turkey’s Approach

DTIC Science & Technology

2009-10-01

Analysis, Decision Support System Design and Implementation, Simulation Output Analysis, Statistical Data Analysis, Virtual Reality , Artificial... virtual and constructive visual simulation systems as well as integrated advanced analytical models. Collaboration and Synergy among Government...simulation systems that are ready to use, credible, integrated with C4ISR systems.  Creating synthetic environments and/or virtual prototypes of concepts

How research funding agencies support science integration into policy and practice: An international overview

PubMed Central

2014-01-01

Background Funding agencies constitute one essential pillar for policy makers, researchers and health service delivery institutions. Such agencies are increasingly providing support for science implementation. In this paper, we investigate health research funding agencies and how they support the integration of science into policy, and of science into practice, and vice versa. Methods We selected six countries: Australia, The Netherlands, France, Canada, England and the United States. For 13 funding agencies, we compared their intentions to support, their actions related to science integration into policy and practice, and the reported benefits of this integration. We did a qualitative content analysis of the reports and information provided on the funding agencies’ websites. Results Most funding agencies emphasized the importance of science integration into policy and practice in their strategic orientation, and stated how this integration was structured. Their funding activities were embedded in the push, pull, or linkage/exchange knowledge transfer model. However, few program funding efforts were based on all three models. The agencies reported more often on the benefits of integration on practice, rather than on policy. External programs that were funded largely covered science integration into policy and practice at the end of grant stage, while overlooking the initial stages. Finally, external funding actions were more prominent than internally initiated bridging activities and training activities on such integration. Conclusions This paper contributes to research on science implementation because it goes beyond the two community model of researchers versus end users, to include funding agencies. Users of knowledge may be end users in health organizations like hospitals; civil servants assigned to decision making positions within funding agencies; civil servants outside of the Ministry of Health, such as the Ministry of the Environment; politicians deciding on health-related legislation; or even university researchers whose work builds on previous research. This heterogeneous sample of users may require different user-specific mechanisms for research initiation, development and dissemination. This paper builds the foundation for further discussion on science implementation from the perspective of funding agencies in the health field. In general, case studies can help in identifying best practices for evidence-informed decision making. PMID:24565209

How research funding agencies support science integration into policy and practice: an international overview.

PubMed

Smits, Pernelle A; Denis, Jean-Louis

2014-02-24

Funding agencies constitute one essential pillar for policy makers, researchers and health service delivery institutions. Such agencies are increasingly providing support for science implementation. In this paper, we investigate health research funding agencies and how they support the integration of science into policy, and of science into practice, and vice versa. We selected six countries: Australia, The Netherlands, France, Canada, England and the United States. For 13 funding agencies, we compared their intentions to support, their actions related to science integration into policy and practice, and the reported benefits of this integration. We did a qualitative content analysis of the reports and information provided on the funding agencies' websites. Most funding agencies emphasized the importance of science integration into policy and practice in their strategic orientation, and stated how this integration was structured. Their funding activities were embedded in the push, pull, or linkage/exchange knowledge transfer model. However, few program funding efforts were based on all three models. The agencies reported more often on the benefits of integration on practice, rather than on policy. External programs that were funded largely covered science integration into policy and practice at the end of grant stage, while overlooking the initial stages. Finally, external funding actions were more prominent than internally initiated bridging activities and training activities on such integration. This paper contributes to research on science implementation because it goes beyond the two community model of researchers versus end users, to include funding agencies. Users of knowledge may be end users in health organizations like hospitals; civil servants assigned to decision making positions within funding agencies; civil servants outside of the Ministry of Health, such as the Ministry of the Environment; politicians deciding on health-related legislation; or even university researchers whose work builds on previous research. This heterogeneous sample of users may require different user-specific mechanisms for research initiation, development and dissemination. This paper builds the foundation for further discussion on science implementation from the perspective of funding agencies in the health field. In general, case studies can help in identifying best practices for evidence-informed decision making.

An IT Architecture for Systems Medicine.

PubMed

Ganzinger, Matthias; Gietzelt, Matthias; Karmen, Christian; Firnkorn, Daniel; Knaup, Petra

2015-01-01

Systems medicine aims to support treatment of complex diseases like cancer by integrating all available data for the disease. To provide such a decision support in clinical practice, a suitable IT architecture is necessary. We suggest a generic architecture comprised of the following three layers: data representation, decision support, and user interface. For the systems medicine research project "Clinically-applicable, omics-based assessment of survival, side effects, and targets in multiple myeloma" (CLIOMMICS) we developed a concrete instance of the generic architecture. We use i2b2 for representing the harmonized data. Since no deterministic model exists for multiple myeloma we use case-based reasoning for decision support. For clinical practice, visualizations of the results must be intuitive and clear. At the same time, they must communicate the uncertainty immanent in stochastic processes. Thus, we develop a specific user interface for systems medicine based on the web portal software Liferay.

Interactive and Participatory Decision Support: Linking Cyberinfrastructure, Multi-Touch Interfaces, and Substantive Dialogue for Geothermal Systems

NASA Astrophysics Data System (ADS)

Malin, R.; Pierce, S. A.; Bass, B. J.

2012-12-01

Socio-technical approaches to complex, ill-structured decision problems are needed to identify adaptive responses for earth resource management. This research presents a hybrid approach to create decision tools and engender dialogue among stakeholders for geothermal development in Idaho, United States and El Tatio, Chile. Based on the scarcity of data, limited information availability, and tensions across stakeholder interests we designed and constructed a decision support model that allows stakeholders to rapidly collect, input, and visualize geoscientific data to assess geothermal system impacts and possible development strategies. We have integrated this decision support model into multi-touch interfaces that can be easily used by scientists and stakeholders alike. This toolkit is part of a larger cyberinfrastructure project designed to collect and present geoscientific information to support decision making processes. Consultation with stakeholders at the El Tatio geothermal complex of northern Chile—indigenous communities, local and national government agencies, developers, and geoscientists - informed the implementation of a sustained dialogue process. The El Tatio field case juxtaposes basic parameters such as pH, spring temperature, geochemical content, and FLIR imagery with stakeholder perceptions of risks due to mineral extraction and energy exploration efforts. The results of interviews and a participatory workshop are driving the creation of three initiatives within an indigenous community group; 1) microentrepreneurial efforts for science-based tourism, 2) design of a citizen-led environmental monitoring network in the Altiplano, and 3) business planning for an indigenous renewable energy cooperative. This toolkit is also being applied in the Snake River Plain of Idaho has as part of the DOE sponsored National Student Geothermal Competition. The Idaho case extends results from the Chilean case to implement a more streamlined system to analyze geothermal resource potential as well as integrate the decision support system with multi-touch interfaces which allow multiple stakeholders to view and interact with data. Beyond visual and tactile appeal, these interfaces also allow participants to dynamically update decision variables and decision preferences to create multiple scenarios and evaluate potential outcomes. Through this interactive scenario building, potential development sites can be targeted and stakeholders can interact with data to engage in substantive dialogue for related long-term planning or crisis response.

Operator decision support system for integrated wastewater management including wastewater treatment plants and receiving water bodies.

PubMed

Kim, Minsoo; Kim, Yejin; Kim, Hyosoo; Piao, Wenhua; Kim, Changwon

2016-06-01

An operator decision support system (ODSS) is proposed to support operators of wastewater treatment plants (WWTPs) in making appropriate decisions. This system accounts for water quality (WQ) variations in WWTP influent and effluent and in the receiving water body (RWB). The proposed system is comprised of two diagnosis modules, three prediction modules, and a scenario-based supporting module (SSM). In the diagnosis modules, the WQs of the influent and effluent WWTP and of the RWB are assessed via multivariate analysis. Three prediction modules based on the k-nearest neighbors (k-NN) method, activated sludge model no. 2d (ASM2d) model, and QUAL2E model are used to forecast WQs for 3 days in advance. To compare various operating alternatives, SSM is applied to test various predetermined operating conditions in terms of overall oxygen transfer coefficient (Kla), waste sludge flow rate (Qw), return sludge flow rate (Qr), and internal recycle flow rate (Qir). In the case of unacceptable total phosphorus (TP), SSM provides appropriate information for the chemical treatment. The constructed ODSS was tested using data collected from Geumho River, which was the RWB, and S WWTP in Daegu City, South Korea. The results demonstrate the capability of the proposed ODSS to provide WWTP operators with more objective qualitative and quantitative assessments of WWTP and RWB WQs. Moreover, the current study shows that ODSS, using data collected from the study area, can be used to identify operational alternatives through SSM at an integrated urban wastewater management level.

Land Use, climate change and BIOdiversity in cultural landscapes (LUBIO): Assessing feedbacks and promoting land-use strategies towards a viable future

NASA Astrophysics Data System (ADS)

Dullinger, Iwona; Bohner, Andreas; Dullinger, Stefan; Essl, Franz; Gaube, Veronika; Haberl, Helmut; Mayer, Andreas; Plutzar, Christoph; Remesch, Alexander

2016-04-01

Land-use and climate change are important, pervasive drivers of global environmental change and pose major threats to global biodiversity. Research to date has mostly focused either on land-use change or on climate change, but rarely on the interactions between both drivers, even though it is expected that systemic feedbacks between changes in climate and land use will have important effects on biodiversity. In particular, climate change will not only alter the pool of plant and animal species capable of thriving in a specific area, it will also force land owners to reconsider their land use decisions. Such changes in land-use practices may have major additional effects on local and regional species composition and abundance. In LUBIO, we will explore the anticipated systemic feedbacks between (1) climate change, (2) land owner's decisions on land use, (3) land-use change, and (4) changes in biodiversity patterns during the coming decades in a regional context which integrates a broad range of land use practices and intensity gradients. To achieve this goal, an integrated socioecological model will be designed and implemented, consisting of three principal components: (1) an agent based model (ABM) that simulates decisions of important actors, (2) a spatially explicit GIS model that translates these decisions into changes in land cover and land use patterns, and (3) a species distribution model (SDM) that calculates changes in biodiversity patterns following from both changes in climate and the land use decisions as simulated in the ABM. Upon integration of these three components, the coupled socioecological model will be used to generate scenarios of future land-use decisions of landowners under climate change and, eventually, the combined effects of climate and land use changes on biodiversity. Model development of the ABM will be supported by a participatory process intended to collect regional and expert knowledge through a series of expert interviews, a series of transdisciplinary participatory modelling workshops, and a questionnaire-based survey targeted at regional farmers. Beside the integrated socioecological model a catalogue of recommended actions will be developed in order to distribute the insights of the research to the most relevant regional stakeholder groups.

Systems analysis - a new paradigm and decision support tools for the water framework directive

NASA Astrophysics Data System (ADS)

Bruen, M.

2007-06-01

In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness. This is best done by trained sociologists fully integrated into the processes. The WINCOMS research project is an example applied to the implementation of the WFD in Ireland.

Integrating conflict analysis and consensus reaching in a decision support system for water resource management.

PubMed

Giordano, R; Passarella, G; Uricchio, V F; Vurro, M

2007-07-01

The importance of shared decision processes in water management derives from the awareness of the inadequacy of traditional--i.e. engineering--approaches in dealing with complex and ill-structured problems. It is becoming increasingly obvious that traditional problem solving and decision support techniques, based on optimisation and factual knowledge, have to be combined with stakeholder based policy design and implementation. The aim of our research is the definition of an integrated decision support system for consensus achievement (IDSS-C) able to support a participative decision-making process in all its phases: problem definition and structuring, identification of the possible alternatives, formulation of participants' judgments, and consensus achievement. Furthermore, the IDSS-C aims at structuring, i.e. systematising the knowledge which has emerged during the participative process in order to make it comprehensible for the decision-makers and functional for the decision process. Problem structuring methods (PSM) and multi-group evaluation methods (MEM) have been integrated in the IDSS-C. PSM are used to support the stakeholders in providing their perspective of the problem and to elicit their interests and preferences, while MEM are used to define not only the degree of consensus for each alternative, highlighting those where the agreement is high, but also the consensus label for each alternative and the behaviour of individuals during the participative decision-making. The IDSS-C is applied experimentally to a decision process regarding the use of treated wastewater for agricultural irrigation in the Apulia Region (southern Italy).

A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department.

PubMed

Wilk, S; Michalowski, W; O'Sullivan, D; Farion, K; Sayyad-Shirabad, J; Kuziemsky, C; Kukawka, B

2013-01-01

The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.

Collaborative agency to support integrated care for children, young people and families: an action research study.

PubMed

Stuart, Kaz

2014-04-01

Collaboration was legislated in the delivery of integrated care in the early 2000s in the UK. This research explored how the reality of practice met the rhetoric of collaboration. The paper is situated against a theoretical framework of structure, agency, identity and empowerment. Collectively and contextually these concepts inform the proposed model of 'collaborative agency' to sustain integrated care. The paper brings sociological theory on structure and agency to the dilemma of collaboration. Participative action research was carried out in collaborative teams that aspired to achieve integrated care for children, young people and families between 2009 and 2013. It was a part time, PhD study in collaborative practice. The research established that people needed to be able to be jointly aware of their context, to make joint decisions, and jointly act in order to deliver integrated services, and proposes a model of collaborative agency derived from practitioner's experiences and integrated action research and literature on agency. The model reflects the effects of a range of structures in shaping professional identity, empowerment, and agency in a dynamic. The author proposes that the collaborative agency model will support integrated care, although this is, as yet, an untested hypothesis.

Integrating uncertainty into public energy research and development decisions

NASA Astrophysics Data System (ADS)

Anadón, Laura Díaz; Baker, Erin; Bosetti, Valentina

2017-05-01

Public energy research and development (R&D) is recognized as a key policy tool for transforming the world's energy system in a cost-effective way. However, managing the uncertainty surrounding technological change is a critical challenge for designing robust and cost-effective energy policies. The design of such policies is particularly important if countries are going to both meet the ambitious greenhouse-gas emissions reductions goals set by the Paris Agreement and achieve the required harmonization with the broader set of objectives dictated by the Sustainable Development Goals. The complexity of informing energy technology policy requires, and is producing, a growing collaboration between different academic disciplines and practitioners. Three analytical components have emerged to support the integration of technological uncertainty into energy policy: expert elicitations, integrated assessment models, and decision frameworks. Here we review efforts to incorporate all three approaches to facilitate public energy R&D decision-making under uncertainty. We highlight emerging insights that are robust across elicitations, models, and frameworks, relating to the allocation of public R&D investments, and identify gaps and challenges that remain.

Modeling a Nursing Guideline with Standard Terminology and Unified Modeling Language for a Nursing Decision Support System: A Case Study.

PubMed

Choi, Jeeyae; Jansen, Kay; Coenen, Amy

In recent years, Decision Support Systems (DSSs) have been developed and used to achieve "meaningful use". One approach to developing DSSs is to translate clinical guidelines into a computer-interpretable format. However, there is no specific guideline modeling approach to translate nursing guidelines to computer-interpretable guidelines. This results in limited use of DSSs in nursing. Unified modeling language (UML) is a software writing language known to accurately represent the end-users' perspective, due to its expressive characteristics. Furthermore, standard terminology enabled DSSs have been shown to smoothly integrate into existing health information systems. In order to facilitate development of nursing DSSs, the UML was used to represent a guideline for medication management for older adults encode with the International Classification for Nursing Practice (ICNP®). The UML was found to be a useful and sufficient tool to model a nursing guideline for a DSS.

Modeling a Nursing Guideline with Standard Terminology and Unified Modeling Language for a Nursing Decision Support System: A Case Study

PubMed Central

Choi, Jeeyae; Jansen, Kay; Coenen, Amy

2015-01-01

In recent years, Decision Support Systems (DSSs) have been developed and used to achieve “meaningful use”. One approach to developing DSSs is to translate clinical guidelines into a computer-interpretable format. However, there is no specific guideline modeling approach to translate nursing guidelines to computer-interpretable guidelines. This results in limited use of DSSs in nursing. Unified modeling language (UML) is a software writing language known to accurately represent the end-users’ perspective, due to its expressive characteristics. Furthermore, standard terminology enabled DSSs have been shown to smoothly integrate into existing health information systems. In order to facilitate development of nursing DSSs, the UML was used to represent a guideline for medication management for older adults encode with the International Classification for Nursing Practice (ICNP®). The UML was found to be a useful and sufficient tool to model a nursing guideline for a DSS. PMID:26958174

DIDEM - An integrated model for comparative health damage costs calculation of air pollution

NASA Astrophysics Data System (ADS)

Ravina, Marco; Panepinto, Deborah; Zanetti, Maria Chiara

2018-01-01

Air pollution represents a continuous hazard to human health. Administration, companies and population need efficient indicators of the possible effects given by a change in decision, strategy or habit. The monetary quantification of health effects of air pollution through the definition of external costs is increasingly recognized as a useful indicator to support decision and information at all levels. The development of modelling tools for the calculation of external costs can provide support to analysts in the development of consistent and comparable assessments. In this paper, the DIATI Dispersion and Externalities Model (DIDEM) is presented. The DIDEM model calculates the delta-external costs of air pollution comparing two alternative emission scenarios. This tool integrates CALPUFF's advanced dispersion modelling with the latest WHO recommendations on concentration-response functions. The model is based on the impact pathway method. It was designed to work with a fine spatial resolution and a local or national geographic scope. The modular structure allows users to input their own data sets. The DIDEM model was tested on a real case study, represented by a comparative analysis of the district heating system in Turin, Italy. Additional advantages and drawbacks of the tool are discussed in the paper. A comparison with other existing models worldwide is reported.

Leadership of risk decision making in a complex, technology organization: The deliberative decision making model

NASA Astrophysics Data System (ADS)

Flaming, Susan C.

2007-12-01

The continuing saga of satellite technology development is as much a story of successful risk management as of innovative engineering. How do program leaders on complex, technology projects manage high stakes risks that threaten business success and satellite performance? This grounded theory study of risk decision making portrays decision leadership practices at one communication satellite company. Integrated product team (IPT) leaders of multi-million dollar programs were interviewed and observed to develop an extensive description of the leadership skills required to navigate organizational influences and drive challenging risk decisions to closure. Based on the study's findings the researcher proposes a new decision making model, Deliberative Decision Making, to describe the program leaders' cognitive and organizational leadership practices. This Deliberative Model extends the insights of prominent decision making models including the rational (or classical) and the naturalistic and qualifies claims made by bounded rationality theory. The Deliberative Model describes how leaders proactively engage resources to play a variety of decision leadership roles. The Model incorporates six distinct types of leadership decision activities, undertaken in varying sequence based on the challenges posed by specific risks. Novel features of the Deliberative Decision Model include: an inventory of leadership methods for managing task challenges, potential stakeholder bias and debates; four types of leadership meta-decisions that guide decision processes, and aligned organizational culture. Both supporting and constraining organizational influences were observed as leaders managed major risks, requiring active leadership on the most difficult decisions. Although the company's engineering culture emphasized the importance of data-based decisions, the uncertainties intrinsic to satellite risks required expert engineering judgment to be exercised throughout. An investigation into the co-variation of decision methods with uncertainty suggests that perceived risk severity may serve as a robust indicator for choices about decision practices. The Deliberative Decision processes incorporate multiple organizational and cultural controls as cross-checks to mitigate potential parochial bias of individuals, stakeholder groups, or leaders. Overall the Deliberative Decision framework describes how expert leadership practices, supportive organizational systems along with aligned cultural values and behavioral norms help leaders drive high stakes risk decisions to closure in this complex, advanced-technology setting.

Integrated Data & Analysis in Support of Informed and Transparent Decision Making

NASA Astrophysics Data System (ADS)

Guivetchi, K.

2012-12-01

The California Water Plan includes a framework for improving water reliability, environmental stewardship, and economic stability through two initiatives - integrated regional water management to make better use of local water sources by integrating multiple aspects of managing water and related resources; and maintaining and improving statewide water management systems. The Water Plan promotes ways to develop a common approach for data standards and for understanding, evaluating, and improving regional and statewide water management systems, and for common ways to evaluate and select from alternative management strategies and projects. The California Water Plan acknowledges that planning for the future is uncertain and that change will continue to occur. It is not possible to know for certain how population growth, land use decisions, water demand patterns, environmental conditions, the climate, and many other factors that affect water use and supply may change by 2050. To anticipate change, our approach to water management and planning for the future needs to consider and quantify uncertainty, risk, and sustainability. There is a critical need for information sharing and information management to support over-arching and long-term water policy decisions that cross-cut multiple programs across many organizations and provide a common and transparent understanding of water problems and solutions. Achieving integrated water management with multiple benefits requires a transparent description of dynamic linkages between water supply, flood management, water quality, land use, environmental water, and many other factors. Water Plan Update 2013 will include an analytical roadmap for improving data, analytical tools, and decision-support to advance integrated water management at statewide and regional scales. It will include recommendations for linking collaborative processes with technical enhancements, providing effective analytical tools, and improving and sharing data and information. Specifically, this includes achieving better integration and consistency with other planning activities; obtaining consensus on quantitative deliverables; building a common conceptual understanding of the water management system; developing common schematics of the water management system; establishing modeling protocols and standards; and improving transparency and exchange of Water Plan information.

The National Danish Water Resources Model - using an integrated groundwater - surface water model for decision support and WFD implementation in a changing climate

NASA Astrophysics Data System (ADS)

Lajer Hojberg, Anker; Hinsby, Klaus; Jørgen Henriksen, Hans; Troldborg, Lars

2014-05-01

Integrated and sustainable water resources management and development of river basin management plans according to the Water Framework Directive is getting increasingly complex especially when taking projected climate change into account. Furthermore, uncertainty in future developments and incomplete knowledge of the physical system introduces a high degree of uncertainty in the decision making process. Knowledge based decision making is therefore vital for formulation of robust management plans and to allow assessment of the inherent uncertainties. The Department of Hydrology at the Geological Survey of Denmark and Greenland started in 1996 to develop a mechanistically, transient and spatially distributed groundwater-surface water model - the DK-model - for the assessment of groundwater quantitative status accounting for interactions with surface water and anthropogenic changes, such as extraction strategies and land use, as well as climate change. The model has been subject to continuous update building on hydrogeological knowledge established by the regional water authorities and other national research institutes. With the on-going improvement of the DK-model it is now increasingly applied both by research projects and for decision support e.g. in implementation of the Water Framework Directive or to support other decisions related to protection of water resources (quantitative and chemical status), ecosystems and the built environment. At present, the DK-model constitutes the backbone of a strategic modelling project funded by the Danish Environmental Protection Agency, with the aim of developing a modelling complex that will provide the foundation of the implementation of the Water Framework Directive. Since 2003 the DK-model has been used in more than 25 scientific papers and even more public reports. In the poster and the related review paper we describe the most important applications in both science and policy, where the DK-model has been used either directly or as an important starting point for assessing the impact of climate change on the quantity and quality of groundwater and surface water e.g. in relation to changes in water tables, runoff, nutrient loadings, flooding risks (coastal and hinterland), irrigation demands, sea level rise and seawater intrusion or to assess where geology or climate change create the largest uncertainty for evaluation of the development of water resources quantity and quality.

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles; Saile, Lynn; deCarvalho, Mary Freire; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

2009-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

Overcoming roadblocks: current and emerging reimbursement strategies for integrated mental health services in primary care.

PubMed

O'Donnell, Allison N; Williams, Mark; Kilbourne, Amy M

2013-12-01

The Chronic Care Model (CCM) has been shown to improve medical and psychiatric outcomes for persons with mental disorders in primary care settings, and has been proposed as a model to integrate mental health care in the patient-centered medical home under healthcare reform. However, the CCM has not been widely implemented in primary care settings, primarily because of a lack of a comprehensive reimbursement strategy to compensate providers for day-to-day provision of its core components, including care management and provider decision support. Drawing upon the existing literature and regulatory guidelines, we provide a critical analysis of challenges and opportunities in reimbursing CCM components under the current fee-for-service system, and describe an emerging financial model involving bundled payments to support core CCM components to integrate mental health treatment into primary care settings. Ultimately, for the CCM to be used and sustained over time to integrate physical and mental health care, effective reimbursement models will need to be negotiated across payers and providers. Such payments should provide sufficient support for primary care providers to implement practice redesigns around core CCM components, including care management, measurement-based care, and mental health specialist consultation.

New Decision Support for Landslide and Other Disaster Events

NASA Astrophysics Data System (ADS)

Nair, U. S.; Keiser, K.; Wu, Y.; Kaulfus, A.; Srinivasan, K.; Anderson, E. R.; McEniry, M.

2013-12-01

An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of nodes required depending upon the nature of terrain and land cover. The performance of a water table model, to be utilized in the end-to-end system, is being evaluated by comparing against landslides that occurred during the 6th and 7th of May, 2003 and 20th and 21st of April, 2011. The model provides a deterministic assessment of slope stability by evaluating horizontal and vertical transport of underground water and associated weight bearing capacity. In the proposed end-to-end system, the model will be coupled to the WSN, and the in situ data collected will be used to drive the model. The output from the model could be communicated back to the WSN providing the capability of generating warning of possible events to the ED3 framework to trigger additional data retrieval or the processing of additional models based on decision maker's ED3 preparedness plans. NASA's Applied Science Program has funded a feasibility study of the ED3 technology and as a result the capability is on track be integrated into existing decision support systems, with an initial reference implementation hosted at the Global Hydrology Resource Center, a NASA distributed active archive center (DAAC).

Computer assisted surgery with 3D robot models and visualisation of the telesurgical action.

PubMed

Rovetta, A

2000-01-01

This paper deals with the support of virtual reality computer action in the procedures of surgical robotics. Computer support gives a direct representation of the surgical theatre. The modelization of the procedure in course and in development gives a psychological reaction towards safety and reliability. Robots similar to the ones used by the manufacturing industry can be used with little modification as very effective surgical tools. They have high precision, repeatability and are versatile in integrating with the medical instrumentation. Now integrated surgical rooms, with computer and robot-assisted intervention, are operating. The computer is the element for a decision taking aid, and the robot works as a very effective tool.

Anticoagulation therapy advisor: a decision-support system for heparin therapy during ECMO.

PubMed Central

Peverini, R. L.; Sale, M.; Rhine, W. D.; Fagan, L. M.; Lenert, L. A.

1992-01-01

We present a case study describing our development of a mathematical model to control a clinical parameter in a patient--in this case, the degree of anticoagulation during extracorporeal membrane oxygenation (ECMO) support. During ECMO therapy, an anticoagulant agent (heparin) is administered to prevent thrombosis. Under- or over-coagulation can have grave consequences. To improve control of anticoagulation, we developed a pharmacokinetic-pharmacodynamic (PK-PD) model that predicts activated clotting times (ACT) using the NONMEM program. We then integrated this model into a decision-support system, and validated it with an independent data set. The population model had a mean absolute error of prediction for ACT values of 33.5 seconds, with a mean bias in estimation of -14.3 seconds. Individualization of model-parameter estimates using nonlinear regression improved the absolute error prediction to 25.5 seconds, and lowered the mean bias to -3.1 seconds. The PK-PD model is coupled with software for heuristic interpretation of model results to provide a complete environment for the management of anticoagulation. PMID:1482937

EMDS users guide (version 2.0): knowledge-based decision support for ecological assessment.

Treesearch

Keith M. Reynolds

1999-01-01

The USDA Forest Service Pacific Northwest Research Station in Corvallis, Oregon, has developed the ecosystem management decision support (EMDS) system. The system integrates the logical formalism of knowledge-based reasoning into a geographic information system (GIS) environment to provide decision support for ecological landscape assessment and evaluation. The...

Developing an Interactive Data Visualization Tool to Assess the Impact of Decision Support on Clinical Operations.

PubMed

Huber, Timothy C; Krishnaraj, Arun; Monaghan, Dayna; Gaskin, Cree M

2018-05-18

Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.

A decision technology system for health care electronic commerce.

PubMed

Forgionne, G A; Gangopadhyay, A; Klein, J A; Eckhardt, R

1999-08-01

Mounting costs have escalated the pressure on health care providers and payers to improve decision making and control expenses. Transactions to form the needed decision data will routinely flow, often electronically, between the affected parties. Conventional health care information systems facilitate flow, process transactions, and generate useful decision information. Typically, such support is offered through a series of stand-alone systems that lose much useful decision knowledge and wisdom during health care electronic commerce (e-commerce). Integrating the stand-alone functions can enhance the quality and efficiency of the segmented support, create synergistic effects, and augment decision-making performance and value for both providers and payers. This article presents an information system that can provide complete and integrated support for e-commerce-based health care decision making. The article describes health care e-commerce, presents the system, examines the system's potential use and benefits, and draws implications for health care management and practice.

Institutional Transformation Model

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

2015-10-19

Reducing the energy consumption of large institutions with dozens to hundreds of existing buildings while maintaining and improving existing infrastructure is a critical economic and environmental challenge. SNL's Institutional Transformation (IX) work integrates facilities and infrastructure sustainability technology capabilities and collaborative decision support modeling approaches to help facilities managers at Sandia National Laboratories (SNL) simulate different future energy reduction strategies and meet long term energy conservation goals.

Improving the Slum Planning Through Geospatial Decision Support System

NASA Astrophysics Data System (ADS)

Shekhar, S.

2014-11-01

In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.

Perceptions of risk, risk aversion, and barriers to adoption of decision support systems and integrated pest management: an introduction.

PubMed

Gent, David H; De Wolf, Erick; Pethybridge, Sarah J

2011-06-01

Rational management of plant diseases, both economically and environmentally, involves assessing risks and the costs associated with both correct and incorrect tactical management decisions to determine when control measures are warranted. Decision support systems can help to inform users of plant disease risk and thus assist in accurately targeting events critical for management. However, in many instances adoption of these systems for use in routine disease management has been perceived as slow. The under-utilization of some decision support systems is likely due to both technical and perception constraints that have not been addressed adequately during development and implementation phases. Growers' perceptions of risk and their aversion to these perceived risks can be reasons for the "slow" uptake of decision support systems and, more broadly, integrated pest management (IPM). Decision theory provides some tools that may assist in quantifying and incorporating subjective and/or measured probabilities of disease occurrence or crop loss into decision support systems. Incorporation of subjective probabilities into IPM recommendations may be one means to reduce grower uncertainty and improve trust of these systems because management recommendations could be explicitly informed by growers' perceptions of risk and economic utility. Ultimately though, we suggest that an appropriate measure of the value and impact of decision support systems is grower education that enables more skillful and informed management decisions independent of consultation of the support tool outputs.

Surface transportation weather decision support requirements : user needs and appendices : advanced-integrated decision support using weather information for surface transportation decision makers

DOT National Transportation Integrated Search

2000-01-24

The Federal Highway Administration (FHWA) of the U.S. Department of Transportation (USDOT) : has a responsibility to coordinate and promote projects that will bring the best information on weather to decision makers, in order to improve performance o...

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

Treesearch

Morgan Pence; Tom Zimmerman

2011-01-01

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

An integrated decision support system for wastewater nutrient recovery and recycling to agriculture

NASA Astrophysics Data System (ADS)

Roy, E. D.; Bomeisl, L.; Cornbrooks, P.; Mo, W.

2017-12-01

Nutrient recovery and recycling has become a key research topic within the wastewater engineering and nutrient management communities. Several technologies now exist that can effectively capture nutrients from wastewater, and innovation in this area continues to be an important research pursuit. However, practical nutrient recycling solutions require more than capable nutrient capture technologies. We also need to understand the role that wastewater nutrient recovery and recycling can play within broader nutrient management schemes at the landscape level, including important interactions at the nexus of food, energy, and water. We are developing an integrated decision support system that combines wastewater treatment data, agricultural data, spatial nutrient balance modeling, life cycle assessment, stakeholder knowledge, and multi-criteria decision making. Our goals are to: (1) help guide design decisions related to the implementation of sustainable nutrient recovery technology, (2) support innovations in watershed nutrient management that operate at the interface of the built environment and agriculture, and (3) aid efforts to protect aquatic ecosystems while supporting human welfare in a circular nutrient economy. These goals will be realized partly through the assessment of plausible alternative scenarios for the future. In this presentation, we will describe the tool and focus on nutrient balance results for the New England region. These results illustrate that both centralized and decentralized wastewater nutrient recovery schemes have potential to transform nutrient flows in many New England watersheds, diverting wastewater N and P away from aquatic ecosystems and toward local or regional agricultural soils where they can offset a substantial percentage of imported fertilizer. We will also highlight feasibility criteria and next steps to integrate stakeholder knowledge, economics, and life cycle assessment into the tool.

Season-ahead Drought Forecast Models for the Lower Colorado River Authority in Texas

NASA Astrophysics Data System (ADS)

Block, P. J.; Zimmerman, B.; Grzegorzewski, M.; Watkins, D. W., Jr.; Anderson, R.

2014-12-01

The Lower Colorado River Authority (LCRA) in Austin, Texas, manages the Highland Lakes reservoir system in Central Texas, a series of six lakes on the Lower Colorado River. This system provides water to approximately 1.1 million people in Central Texas, supplies hydropower to a 55-county area, supports rice farming along the Texas Gulf Coast, and sustains in-stream flows in the Lower Colorado River and freshwater inflows to Matagorda Bay. The current, prolonged drought conditions are severely taxing the LCRA's system, making allocation and management decisions exceptionally challenging, and affecting the ability of constituents to conduct proper planning. In this work, we further develop and evaluate season-ahead statistical streamflow and precipitation forecast models for integration into LCRA decision support models. Optimal forecast lead time, predictive skill, form, and communication are all considered.

[Which research is needed to support clinical decision-making on integrative medicine? Can comparative effectiveness research close the gap?].

PubMed

Witt, Claudia M; Huang, Wen-jing; Lao, Lixing; Berman, Brian M

2013-08-01

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of best care options. This evidence, more generalizable than evidence generated by traditional randomized clinical trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on CER is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Which research is needed to support clinical decision-making on integrative medicine?- Can comparative effectiveness research close the gap?

PubMed

Witt, Claudia M; Huang, Wen-jing; Lao, Lixing; Bm, Berman

2012-10-01

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of the best care options. This evidence, more generalizable than the evidence generated by traditional randomized controlled trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on comparative effectiveness is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Flat-plate solar array project. Volume 8: Project analysis and integration

NASA Technical Reports Server (NTRS)

Mcguire, P.; Henry, P.

1986-01-01

Project Analysis and Integration (PA&I) performed planning and integration activities to support management of the various Flat-Plate Solar Array (FSA) Project R&D activities. Technical and economic goals were established by PA&I for each R&D task within the project to coordinate the thrust toward the National Photovoltaic Program goals. A sophisticated computer modeling capability was developed to assess technical progress toward meeting the economic goals. These models included a manufacturing facility simulation, a photovoltaic power station simulation and a decision aid model incorporating uncertainty. This family of analysis tools was used to track the progress of the technology and to explore the effects of alternative technical paths. Numerous studies conducted by PA&I signaled the achievement of milestones or were the foundation of major FSA project and national program decisions. The most important PA&I activities during the project history are summarized. The PA&I planning function is discussed and how it relates to project direction and important analytical models developed by PA&I for its analytical and assessment activities are reviewed.

Embracing uncertainty in applied ecology.

PubMed

Milner-Gulland, E J; Shea, K

2017-12-01

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

A Prototype Symbolic Model of Canonical Functional Neuroanatomy of the Motor System

PubMed Central

Rubin, Daniel L.; Halle, Michael; Musen, Mark; Kikinis, Ron

2008-01-01

Recent advances in bioinformatics have opened entire new avenues for organizing, integrating and retrieving neuroscientific data, in a digital, machine-processable format, which can be at the same time understood by humans, using ontological, symbolic data representations. Declarative information stored in ontological format can be perused and maintained by domain experts, interpreted by machines, and serve as basis for a multitude of decision-support, computerized simulation, data mining, and teaching applications. We have developed a prototype symbolic model of canonical neuroanatomy of the motor system. Our symbolic model is intended to support symbolic lookup, logical inference and mathematical modeling by integrating descriptive, qualitative and quantitative functional neuroanatomical knowledge. Furthermore, we show how our approach can be extended to modeling impaired brain connectivity in disease states, such as common movement disorders. In developing our ontology, we adopted a disciplined modeling approach, relying on a set of declared principles, a high-level schema, Aristotelian definitions, and a frame-based authoring system. These features, along with the use of the Unified Medical Language System (UMLS) vocabulary, enable the alignment of our functional ontology with an existing comprehensive ontology of human anatomy, and thus allow for combining the structural and functional views of neuroanatomy for clinical decision support and neuroanatomy teaching applications. Although the scope of our current prototype ontology is limited to a particular functional system in the brain, it may be possible to adapt this approach for modeling other brain functional systems as well. PMID:18164666

Development of integrated surveillance systems for the management of tuberculosis in New Zealand wildlife.

PubMed

Anderson, D P; Ramsey, D S L; de Lisle, G W; Bosson, M; Cross, M L; Nugent, G

2015-06-01

Disease surveillance for the management of bovine tuberculosis (TB) in New Zealand has focussed, to a large extent, on the development of tools specific for monitoring Mycobacterium bovis infection in wildlife. Diagnostic techniques have been modified progressively over 30 years of surveillance of TB in wildlife, from initial characterisation of gross TB lesions in a variety of wildlife, through development of sensitive culture techniques to identify viable mycobacteria, to molecular identification of individual M. bovis strains. Of key importance in disease surveillance has been the elucidation of the roles that different wildlife species play in the transmission of infection, specifically defining brushtail possums (Trichosurus vulpecula) as true maintenance hosts compared to those that are predominantly spillover hosts, but which may serve as useful sentinel species to indicate TB persistence. Epidemiological modelling has played a major role in TB surveillance, initially providing the theoretical support for large-scale possum population control and setting targets at which control effort should be deployed to ensure disease eradication. As TB prevalence in livestock and wildlife declined throughout the 2000s, more varied field tools were developed to gather surveillance data from the diminishing possum populations, and to provide information on changing TB prevalence. Accordingly, ever more precise (but disparate) surveillance information began to be integrated into multi-faceted decision-assist models to support TB management decisions, particularly to provide informed parameters at which control effort could be halted, culminating in the Proof of Freedom modelling framework that now allows an area to be declared TB-free within chosen confidence limits. As New Zealand moves from large-scale TB control to regional eradication of disease in the coming years, further integrative models will need to be developed to support management decisions, based on combined field data of possum and TB prevalence, sentinel information, risk assessment in relation to financial benefits, and changing political and environmental needs.

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

Integrated modelling for Sustainability Appraisal of urban river corridors: going beyond compartmentalised thinking.

PubMed

Kumar, Vikas; Rouquette, J R; Lerner, David N

2013-12-15

Sustainability Appraisal (SA) is a complex task that involves integration of social, environmental and economic considerations and often requires trade-offs between multiple stakeholders that may not easily be brought to consensus. Classical SA, often compartmentalised in the rigid boundary of disciplines, can facilitate discussion, but can only partially inform decision makers as many important aspects of sustainability remain abstract and not interlinked. A fully integrated model can overcome compartmentality in the assessment process and provides opportunity for a better integrative exploratory planning process. The objective of this paper is to explore the benefit of an integrated modelling approach to SA and how a structured integrated model can be used to provide a coherent, consistent and deliberative platform to assess policy or planning proposals. The paper discusses a participative and integrative modelling approach to urban river corridor development, incorporating the principal of sustainability. The paper uses a case study site in Sheffield, UK, with three alternative development scenarios, incorporating a number of possible riverside design features. An integrated SA model is used to develop better design by optimising different design elements and delivering a more sustainable (re)-development plan. We conclude that participatory integrated modelling has strong potential for supporting the SA processes. A high degree of integration provides the opportunity for more inclusive and informed decision-making regarding issues of urban development. It also provides the opportunity to reflect on their long-term dynamics, and to gain insights on the interrelationships underlying persistent sustainability problems. Thus the ability to address economic, social and environmental interdependencies within policies, plans, and legislations is enhanced. Copyright © 2013 Elsevier Ltd. All rights reserved.

Integrated modeling systems to assess exposure and toxicity of chemicals in support of aquatic ecological risk assessment of methodologically challenging chemicals

EPA Science Inventory

From an exposure assessment perspective, persistent, bioaccumulative and toxic chemicals (PBTs) are some of the most challenging chemicals facing environmental decision makers today. Due to their general physico-chemical properties [e.g., high octanol-water partition coefficien...

Measuring research progress in photovoltaics

NASA Technical Reports Server (NTRS)

Jackson, B.; Mcguire, P.

1986-01-01

The role and some results of the project analysis and integration function in the Flat-plate Solar Array (FSA) Project are presented. Activities included supporting the decision-making process, preparation of plans for project direction, setting goals for project activities, measuring progress within the project, and the development and maintenance of analytical models.

A Spatial Decision Support System to incorporate hydro-economic modeling results in the management of water resources under decentralized institutional arrangements in a semiarid reservoir region in Brazil

NASA Astrophysics Data System (ADS)

Moraes, M. G. A.; Souza da Silva, G.; Siegmund-Schultze, M.

2016-12-01

The integration of economic and hydrological components in models, aimed to support evaluating alternatives of water allocation policies, is promising, though, challenging. Worldwide, these models have been used primarily in academia, and so far seldom by water managers for practical purposes. Ideally, the models should be available through a Decision Support System. The São Francisco River Basin in Northeast of Brazil has around 48% of its area in a semi-arid region. Irrigation and public water supply are the primary water use sectors, along with hydropower utilization. The water for electricity generation is stored in two large reservoirs, built 30 to 50 years ago under the premise of regulating flows for hydropower and controlling floods. Since 20 years, however, the law stipulates the multiple uses paradigm in a participatory and decentralized way. So far, only few rules laid down. Studies revealed that most of the respective institutions still needed to update their routines to the new paradigm.A hydro-economic model was developed and applied in order to determine the economically optimal water allocation of main users in that semiarid reservoir region. In order to make this model available to the decision makers, a minimum required is some form of manipulating data entry and output as well as some graphical interfaces. We propose a Spatial Decision Support System (SDSS) with dedicated hydro-economic modules in a web-based Geographic Information System (GIS) environment for integrated water resource management. The open model platform will include geoprocessing tasks and water user related data management. The hydro-economic geoprocessing will link to generic optimization modeling systems, such as EXCEL Solver, GAMS and MATLAB. The institutions that are deliberating or deciding over water allocation at different scales could use the generated information on potential economic benefits as a transparent basis for discussion. In addition, they can use the SDSS to include constraints into the model in order to account for further objectives, such as preference given to specific uses or timing of uses. This information, and corresponding policies, can foster enhanced economic welfare and sustainable water use, as well as help to solve water use conflicts.

A Spatial Decision Support System to incorporate hydro-economic modeling results in the management of water resources under decentralized institutional arrangements in a semiarid reservoir region in Brazil

NASA Astrophysics Data System (ADS)

Alcoforado de Moraes, Márcia; Silva, Gerald; Siegmund-Schultze, Marianna

2017-04-01

The integration of economic and hydrological components in models, aimed to support evaluating alternatives of water allocation policies, is promising, though, challenging. Worldwide, these models have been used primarily in academia, and so far seldom by water managers for practical purposes. Ideally, the models should be available through a Decision Support System. The São Francisco River Basin in Northeast of Brazil has around 48% of its area in a semi-arid region. Irrigation and public water supply are the primary water use sectors, along with hydropower utilization. The water for electricity generation is stored in two large reservoirs, built 30 to 50 years ago under the premise of regulating flows for hydropower and controlling floods. Since 20 years, however, the law stipulates the multiple uses paradigm in a participatory and decentralized way. So far, only few rules laid down. Studies revealed that most of the respective institutions still needed to update their routines to the new paradigm. A hydro-economic model was developed and applied in order to determine the economically optimal water allocation of main users in that semiarid reservoir region. In order to make this model available to the decision makers, a minimum required is some form of manipulating data entry and output as well as some graphical interfaces. We propose and present the first features of a Spatial Decision Support System (SDSS) with dedicated hydro-economic modules in a web-based Geographic Information System (GIS) environment for integrated water resource management. The open model platform should include geoprocessing tasks and water user related data management. The hydro-economic geoprocessing will link to generic optimization modeling systems, such as EXCEL Solver, GAMS and MATLAB. The institutions are deliberating or deciding over water allocation at different scales could use the generated information on potential economic benefits as a transparent basis for discussion. In addition, they can use the SDSS to include constraints into the model in order to account for further objectives, such as preference given to specific uses or timing of uses. This information, and corresponding policies, can foster enhanced economic welfare and sustainable water use, as well as help to solve water use conflicts.

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

PubMed

Hilbig, Benjamin E; Pohl, Rüdiger F

2009-09-01

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

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

PubMed

Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-26

Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness.

Implementing interactive decision support: A case for combining cyberinfrastructure, data fusion, and social process to mobilize scientific knowledge in sustainability problems

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2014-12-01

Geosciences are becoming increasingly data intensive, particularly in relation to sustainability problems, which are multi-dimensional, weakly structured and characterized by high levels of uncertainty. In the case of complex resource management problems, the challenge is to extract meaningful information from data and make sense of it. Simultaneously, scientific knowledge alone is insufficient to change practice. Creating tools, and group decision support processes for end users to interact with data are key challenges to transforming science-based information into actionable knowledge. The ENCOMPASS project began as a multi-year case study in the Atacama Desert of Chile to design and implement a knowledge transfer model for energy-water-mining conflicts in the region. ENCOMPASS combines the use of cyberinfrastructure (CI), automated data collection, interactive interfaces for dynamic decision support, and participatory modelling to support social learning. A pilot version of the ENCOMPASS CI uses open source systems and serves as a structure to integrate and store multiple forms of data and knowledge, such as DEM, meteorological, water quality, geomicrobiological, energy demand, and groundwater models. In the case study, informatics and data fusion needs related to scientific uncertainty around deep groundwater flowpaths and energy-water connections. Users may upload data from field sites with handheld devices or desktops. Once uploaded, data assets are accessible for a variety of uses. To address multi-attributed decision problems in the Atacama region a standalone application with touch-enabled interfaces was created to improve real-time interactions with datasets by groups. The tool was used to merge datasets from the ENCOMPASS CI to support exploration among alternatives and build shared understanding among stakeholders. To date, the project has increased technical capacity among stakeholders, resulted in the creation of both for-profit and non-profit entities, enabled cross-sector collaboration with mining-indigenous stakeholders, and produced an interactive application for group decision support. ENCOMPASS leverages advances in computational tools to deliver data and models for group decision support applied to sustainability science problems.

Water quality modeling in the systems impact assessment model for the Klamath River basin - Keno, Oregon to Seiad Valley, California

USGS Publications Warehouse

Hanna, R. Blair; Campbell, Sharon G.

2000-01-01

This report describes the water quality model developed for the Klamath River System Impact Assessment Model (SIAM). The Klamath River SIAM is a decision support system developed by the authors and other US Geological Survey (USGS), Midcontinent Ecological Science Center staff to study the effects of basin-wide water management decisions on anadromous fish in the Klamath River. The Army Corps of Engineersa?? HEC5Q water quality modeling software was used to simulate water temperature, dissolved oxygen and conductivity in 100 miles of the Klamath River Basin in Oregon and California. The water quality model simulated three reservoirs and the mainstem Klamath River influenced by the Shasta and Scott River tributaries. Model development, calibration and two validation exercises are described as well as the integration of the water quality model into the SIAM decision support system software. Within SIAM, data are exchanged between the water quantity model (MODSIM), the water quality model (HEC5Q), the salmon population model (SALMOD) and methods for evaluating ecosystem health. The overall predictive ability of the water quality model is described in the context of calibration and validation error statistics. Applications of SIAM and the water quality model are described.

Mental Health Collaborative Care and Its Role in Primary Care Settings

PubMed Central

Goodrich, David E.; Kilbourne, Amy M.; Nord, Kristina M.; Bauer, Mark S.

2013-01-01

Collaborative care models (CCMs) provide a pragmatic strategy to deliver integrated mental health and medical care for persons with mental health conditions served in primary care settings. CCMs are team-based intervention to enact system-level redesign by improving patient care through organizational leadership support, provider decision support, and clinical information systems as well as engaging patients in their care through self-management support and linkages to community resources. The model is also a cost-efficient strategy for primary care practices to improve outcomes for a range of mental health conditions across populations and settings. CCMs can help achieve integrated care aims under healthcare reform yet organizational and financial issues may affect adoption into routine primary care. Notably, successful implementation of CCMs in routine care will require alignment of financial incentives to support systems redesign investments, reimbursements for mental health providers, and adaptation across different practice settings and infrastructure to offer all CCM components. PMID:23881714

Mental health collaborative care and its role in primary care settings.

PubMed

Goodrich, David E; Kilbourne, Amy M; Nord, Kristina M; Bauer, Mark S

2013-08-01

Collaborative care models (CCMs) provide a pragmatic strategy to deliver integrated mental health and medical care for persons with mental health conditions served in primary care settings. CCMs are team-based intervention to enact system-level redesign by improving patient care through organizational leadership support, provider decision support, and clinical information systems, as well as engaging patients in their care through self-management support and linkages to community resources. The model is also a cost-efficient strategy for primary care practices to improve outcomes for a range of mental health conditions across populations and settings. CCMs can help achieve integrated care aims underhealth care reform yet organizational and financial issues may affect adoption into routine primary care. Notably, successful implementation of CCMs in routine care will require alignment of financial incentives to support systems redesign investments, reimbursements for mental health providers, and adaptation across different practice settings and infrastructure to offer all CCM components.

Water-Energy-Food Nexus: Compelling Issues for Geophysical Research

NASA Astrophysics Data System (ADS)

Akhbari, M.; Grigg, N. S.; Waskom, R.

2014-12-01

The joint security of water, food, and energy systems is an urgent issue everywhere, and strong drivers of development and land use change, exacerbated by climate change, require new knowledge to achieve integrated solution using a nexus-based approach to assess inter-dependencies. Effective research-based decision support tools are essential to identify the major issues and interconnections to help in implementation of the nexus approach. The major needs are models and data to clearly and unambiguously present decision scenarios to local cooperative groups of farmers, electric energy generators and water officials for joint decisions. These can be developed by integrated models to link hydrology, land use, energy use, cropping simulation, and optimization with economic objectives and socio-physical constraints. The first step in modeling is to have a good conceptual model and then to get data. As the linking of models increases uncertainties, each one should be supplied with adequate data at suitable spatial and temporal resolutions. Most models are supplied with data by geophysical scientists, such as hydrologists, geologists, atmospheric scientists, soil scientists, and climatologists, among others. Outcomes of a recently-completed project to study the water-energy-food nexus will be explained to illuminate the model and data needs to inform future management actions across the nexus. The project included a workshop of experts from government, business, academia, and the non-profit sector who met to define and explain nexus interactions and needs. An example of the findings is that data inconsistencies among sectors create barriers to integrated planning. A nexus-based systems model is needed to outline sectoral inter-dependencies and identify data demands and gaps. Geophysical scientists can help to create this model and take leadership on designing data systems to facilitate sharing and enable integrated management.

SERVIR-Africa: Developing an Integrated Platform for Floods Disaster Management in Africa

NASA Technical Reports Server (NTRS)

Macharia, Daniel; Korme, Tesfaye; Policelli, Fritz; Irwin, Dan; Adler, Bob; Hong, Yang

2010-01-01

SERVIR-Africa is an ambitious regional visualization and monitoring system that integrates remotely sensed data with predictive models and field-based data to monitor ecological processes and respond to natural disasters. It aims addressing societal benefits including floods and turning data into actionable information for decision-makers. Floods are exogenous disasters that affect many parts of Africa, probably second only to drought in terms of social-economic losses. This paper looks at SERVIR-Africa's approach to floods disaster management through establishment of an integrated platform, floods prediction models, post-event flood mapping and monitoring as well as flood maps dissemination in support of flood disaster management.

Decision Support for Resilient Communities: EPA’s Watershed Management Optimization Support Tool

EPA Science Inventory

The U.S. EPA Atlantic Ecology Division is releasing version 3 of the Watershed Management Optimization Support Tool (WMOST v3) in February 2018. WMOST is a decision-support tool that facilitates integrated water resources management (IWRM) by communities and watershed organizati...

A new parameterization for integrated population models to document amphibian reintroductions

USGS Publications Warehouse

Duarte, Adam; Pearl, Christopher; Adams, Michael J.; Peterson, James T.

2017-01-01

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog (Rana pretiosa) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010–2011 to 0.86 in 2012–2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but related, data sets has an advantage of being able to estimate complex ecological relationships across multiple life stages, offering a modeling framework that accommodates uncertainty, enforces parsimony, and ensures all model parameters can be confronted with monitoring data.

A new parameterization for integrated population models to document amphibian reintroductions.

PubMed

Duarte, Adam; Pearl, Christopher A; Adams, Michael J; Peterson, James T

2017-09-01

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog (Rana pretiosa) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010-2011 to 0.86 in 2012-2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but related, data sets has an advantage of being able to estimate complex ecological relationships across multiple life stages, offering a modeling framework that accommodates uncertainty, enforces parsimony, and ensures all model parameters can be confronted with monitoring data. © 2017 by the Ecological Society of America.

Fluor Hanford, Inc. Groundwater and Technical Integration Support (Master Project) Quality Assurance Management Plan

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

Fix, N. J.

The scope of the Fluor Hanford, Inc. Groundwater and Technical Integration Support (Master Project) is to provide technical and integration support to Fluor Hanford, Inc., including operable unit investigations at 300-FF-5 and other groundwater operable units, strategic integration, technical integration and assessments, remediation decision support, and science and technology. This Quality Assurance Management Plan provides the quality assurance requirements and processes that will be followed by the Fluor Hanford, Inc. Groundwater and Technical Integration Support (Master Project).

Modeling aesthetics to support an ecosystem services approach for natural resource management decision making.

PubMed

Booth, Pieter N; Law, Sheryl A; Ma, Jane; Buonagurio, John; Boyd, James; Turnley, Jessica

2017-09-01

This paper reviews literature on aesthetics and describes the development of vista and landscape aesthetics models. Spatially explicit variables were chosen to represent physical characteristics of natural landscapes that are important to aesthetic preferences. A vista aesthetics model evaluates the aesthetics of natural landscapes viewed from distances of more than 1000 m, and a landscape aesthetics model evaluates the aesthetic value of wetlands and forests within 1000 m from the viewer. Each of the model variables is quantified using spatially explicit metrics on a pixel-specific basis within EcoAIM™, a geographic information system (GIS)-based ecosystem services (ES) decision analysis support tool. Pixel values are "binned" into ranked categories, and weights are assigned to select variables to represent stakeholder preferences. The final aesthetic score is the weighted sum of all variables and is assigned ranked values from 1 to 10. Ranked aesthetic values are displayed on maps by patch type and integrated within EcoAIM. The response of the aesthetic scoring in the models was tested by comparing current conditions in a discrete area of the facility with a Development scenario in the same area. The Development scenario consisted of two 6-story buildings and a trail replacing natural areas. The results of the vista aesthetic model indicate that the viewshed area variable had the greatest effect on the aesthetics overall score. Results from the landscape aesthetics model indicate a 10% increase in overall aesthetics value, attributed to the increase in landscape diversity. The models are sensitive to the weights assigned to certain variables by the user, and these weights should be set to reflect regional landscape characteristics as well as stakeholder preferences. This demonstration project shows that natural landscape aesthetics can be evaluated as part of a nonmonetary assessment of ES, and a scenario-building exercise provides end users with a tradeoff analysis in support of natural resource management decisions. Integr Environ Assess Manag 2017;13:926-938. © 2017 SETAC. © 2017 SETAC.

Clinical errors that can occur in the treatment decision-making process in psychotherapy.

PubMed

Park, Jake; Goode, Jonathan; Tompkins, Kelley A; Swift, Joshua K

2016-09-01

Clinical errors occur in the psychotherapy decision-making process whenever a less-than-optimal treatment or approach is chosen when working with clients. A less-than-optimal approach may be one that a client is unwilling to try or fully invest in based on his/her expectations and preferences, or one that may have little chance of success based on contraindications and/or limited research support. The doctor knows best and the independent choice models are two decision-making models that are frequently used within psychology, but both are associated with an increased likelihood of errors in the treatment decision-making process. In particular, these models fail to integrate all three components of the definition of evidence-based practice in psychology (American Psychological Association, 2006). In this article we describe both models and provide examples of clinical errors that can occur in each. We then introduce the shared decision-making model as an alternative that is less prone to clinical errors. PsycINFO Database Record (c) 2016 APA, all rights reserved

Integrated analysis for population estimation, management impact evaluation, and decision-making for a declining species

USGS Publications Warehouse

Crawford, Brian A.; Moore, Clinton; Norton, Terry M.; Maerz, John C.

2018-01-01

A challenge for making conservation decisions is predicting how wildlife populations respond to multiple, concurrent threats and potential management strategies, usually under substantial uncertainty. Integrated modeling approaches can improve estimation of demographic rates necessary for making predictions, even for rare or cryptic species with sparse data, but their use in management applications is limited. We developed integrated models for a population of diamondback terrapins (Malaclemys terrapin) impacted by road-associated threats to (i) jointly estimate demographic rates from two mark-recapture datasets, while directly estimating road mortality and the impact of management actions deployed during the study; and (ii) project the population using population viability analysis under simulated management strategies to inform decision-making. Without management, population extirpation was nearly certain due to demographic impacts of road mortality, predators, and vegetation. Installation of novel flashing signage increased survival of terrapins that crossed roads by 30%. Signage, along with small roadside barriers installed during the study, increased population persistence probability, but the population was still predicted to decline. Management strategies that included actions targeting multiple threats and demographic rates resulted in the highest persistence probability, and roadside barriers, which increased adult survival, were predicted to increase persistence more than other actions. Our results support earlier findings showing mitigation of multiple threats is likely required to increase the viability of declining populations. Our approach illustrates how integrated models may be adapted to use limited data efficiently, represent system complexity, evaluate impacts of threats and management actions, and provide decision-relevant information for conservation of at-risk populations.

Enabling Integrated Decision Making for Electronic-Commerce by Modelling an Enterprise's Sharable Knowledge.

ERIC Educational Resources Information Center

Kim, Henry M.

2000-01-01

An enterprise model, a computational model of knowledge about an enterprise, is a useful tool for integrated decision-making by e-commerce suppliers and customers. Sharable knowledge, once represented in an enterprise model, can be integrated by the modeled enterprise's e-commerce partners. Presents background on enterprise modeling, followed by…

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...

Secondary students' use of social and natural world information in a land use decision context

NASA Astrophysics Data System (ADS)

Kumler, Laura M.

Many societal problems, including land use issues, are complex integrated human-ecological challenges that require an understanding of social and natural world connections. This dissertation investigates how secondary students perceive the social and natural world dimensions of land use, how they might act to support sustainable land use, and how Kaplan and Kaplan's (2008) Reasonable Person Model can inform teaching approaches to prepare students for such complex decisions and action-taking. The dissertation argues that subject compartmentalization in high schools adversely impacts students' abilities to use and to integrate information from various subjects to make a land use decision. Nine secondary science and social studies teachers and their students (n=500) participated in a quasi-experiment using pre- and posttests with treatment and comparison groups to gauge students' requests for social versus natural world information to make land use decisions. Students' self-reported actions and knowledge of actions to support sustainable land use were also measured. Additional data included classroom observations, teacher logs and interviews, and 52 student interviews. Results indicated that students requested social world over natural world information and preferred to consult with social scientists and stakeholders over natural scientists. Results also suggested that experiencing an integrated curriculum increased students' requests for natural world information relevant to the land use decision. Interestingly, this effect occurred even among social studies students whose teachers reported putting scant emphasis on the natural world curriculum content. Moreover, the type of course in which students experienced the curriculum predicted student information use. Finally, students were found to have a limited repertoire of land use actions and knowledge of actions and generally reported undertaking and thinking of individual actions such as recycling or trash pick-up rather than collective actions or political, consumer, or information-sharing actions. The curriculum had only a limited impact on students' actions and knowledge of actions, possibly because teachers did not engage students in actions. The concluding chapter discusses these results in the context of the Reasonable Person Model. The model suggests that cognitive needs, including mental model building, exploration, and meaningful participation, are mutually reinforcing and when provided for can enhance student learning outcomes.

A development of logistics management models for the Space Transportation System

NASA Technical Reports Server (NTRS)

Carrillo, M. J.; Jacobsen, S. E.; Abell, J. B.; Lippiatt, T. F.

1983-01-01

A new analytic queueing approach was described which relates stockage levels, repair level decisions, and the project network schedule of prelaunch operations directly to the probability distribution of the space transportation system launch delay. Finite source population and limited repair capability were additional factors included in this logistics management model developed specifically for STS maintenance requirements. Data presently available to support logistics decisions were based on a comparability study of heavy aircraft components. A two-phase program is recommended by which NASA would implement an integrated data collection system, assemble logistics data from previous STS flights, revise extant logistics planning and resource requirement parameters using Bayes-Lin techniques, and adjust for uncertainty surrounding logistics systems performance parameters. The implementation of these recommendations can be expected to deliver more cost-effective logistics support.

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

Pattern Analysis and Decision Support for Cancer through Clinico-Genomic Profiles

NASA Astrophysics Data System (ADS)

Exarchos, Themis P.; Giannakeas, Nikolaos; Goletsis, Yorgos; Papaloukas, Costas; Fotiadis, Dimitrios I.

Advances in genome technology are playing a growing role in medicine and healthcare. With the development of new technologies and opportunities for large-scale analysis of the genome, genomic data have a clear impact on medicine. Cancer prognostics and therapeutics are among the first major test cases for genomic medicine, given that all types of cancer are related with genomic instability. In this paper we present a novel system for pattern analysis and decision support in cancer. The system integrates clinical data from electronic health records and genomic data. Pattern analysis and data mining methods are applied to these integrated data and the discovered knowledge is used for cancer decision support. Through this integration, conclusions can be drawn for early diagnosis, staging and cancer treatment.

An Assessment of Behavioral Dynamic Information Processing Measures in Audiovisual Speech Perception

PubMed Central

Altieri, Nicholas; Townsend, James T.

2011-01-01

Research has shown that visual speech perception can assist accuracy in identification of spoken words. However, little is known about the dynamics of the processing mechanisms involved in audiovisual integration. In particular, architecture and capacity, measured using response time methodologies, have not been investigated. An issue related to architecture concerns whether the auditory and visual sources of the speech signal are integrated “early” or “late.” We propose that “early” integration most naturally corresponds to coactive processing whereas “late” integration corresponds to separate decisions parallel processing. We implemented the double factorial paradigm in two studies. First, we carried out a pilot study using a two-alternative forced-choice discrimination task to assess architecture, decision rule, and provide a preliminary assessment of capacity (integration efficiency). Next, Experiment 1 was designed to specifically assess audiovisual integration efficiency in an ecologically valid way by including lower auditory S/N ratios and a larger response set size. Results from the pilot study support a separate decisions parallel, late integration model. Results from both studies showed that capacity was severely limited for high auditory signal-to-noise ratios. However, Experiment 1 demonstrated that capacity improved as the auditory signal became more degraded. This evidence strongly suggests that integration efficiency is vitally affected by the S/N ratio. PMID:21980314

Brazilian LTER: ecosystem and biodiversity information in support of decision-making.

PubMed

Barbosa, F A R; Scarano, F R; Sabará, M G; Esteves, F A

2004-01-01

Brazil officially joined the International Long Term Ecological Research (ILTER) network in January 2000, when nine research sites were created and funded by the Brazilian Council for Science and Technology (CNPq). Two-years later some positive signs already emerge of the scientific, social and political achievements of the Brazilian LTER program. We discuss examples of how ecosystem and biodiversity information gathered within a long-term research approach are currently subsidizing decision-making as regards biodiversity conservation and watershed management at local and regional scales. Success in this respect has often been related to satisfactory communication between scientists, private companies, government and local citizens. Environmental education programs in the LTER sites are playing an important role in social and political integration. Most examples of integration of ecological research to decision-making in Brazil derive from case studies at local or regional scale. Despite the predominance of a bottom-up integrative pathway (from case studies to models; from local to national scale), some top-down initiatives are also in order, such as the construction of a model to estimate the inpact of different macroeconomic policies and growth trajectories on land use. We believe science and society in Brazil will benefit of the coexistence of bottom-up and top-down integrative approaches.

Web-Based Tools for Data Visualization and Decision Support for South Asia

NASA Astrophysics Data System (ADS)

Jones, N.; Nelson, J.; Pulla, S. T.; Ames, D. P.; Souffront, M.; David, C. H.; Zaitchik, B. F.; Gatlin, P. N.; Matin, M. A.

2017-12-01

The objective of the NASA SERVIR project is to assist developing countries in using information provided by Earth observing satellites to assess and manage climate risks, land use, and water resources. We present a collection of web apps that integrate earth observations and in situ data to facilitate deployment of data and water resources models as decision-making tools in support of this effort. The interactive nature of web apps makes this an excellent medium for creating decision support tools that harness cutting edge modeling techniques. Thin client apps hosted in a cloud portal eliminates the need for the decision makers to procure and maintain the high performance hardware required by the models, deal with issues related to software installation and platform incompatibilities, or monitor and install software updates, a problem that is exacerbated for many of the regional SERVIR hubs where both financial and technical capacity may be limited. All that is needed to use the system is an Internet connection and a web browser. We take advantage of these technologies to develop tools which can be centrally maintained but openly accessible. Advanced mapping and visualization make results intuitive and information derived actionable. We also take advantage of the emerging standards for sharing water information across the web using the OGC and WMO approved WaterML standards. This makes our tools interoperable and extensible via application programming interfaces (APIs) so that tools and data from other projects can both consume and share the tools developed in our project. Our approach enables the integration of multiple types of data and models, thus facilitating collaboration between science teams in SERVIR. The apps developed thus far by our team process time-varying netCDF files from Earth observations and large-scale computer simulations and allow visualization and exploration via raster animation and extraction of time series at selected points and/or regions.

A Decision Support System for Planning, Control and Auditing of DoD Software Cost Estimation.

DTIC Science & Technology

1986-03-01

is frequently used in U. S. Air Force software cost estimates. Barry Boehm’s Constructive Cost Estimation Model (COCOMO) was recently selected for use...are considered basic to the proper development of software. Pressman , [Ref. 11], addresses these basic elements in a manner which attempts to integrate...H., Jr., and Carlson, Eric D., Building E fective Decision SUDDOrt Systems, Prentice-Hal, EnglewoodNJ, 1982 11. Pressman , Roger S., o A Practioner’s A

Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: a sociotechnical analysis.

PubMed

Sheehan, Barbara; Nigrovic, Lise E; Dayan, Peter S; Kuppermann, Nathan; Ballard, Dustin W; Alessandrini, Evaline; Bajaj, Lalit; Goldberg, Howard; Hoffman, Jeffrey; Offerman, Steven R; Mark, Dustin G; Swietlik, Marguerite; Tham, Eric; Tzimenatos, Leah; Vinson, David R; Jones, Grant S; Bakken, Suzanne

2013-10-01

Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making. Copyright © 2013 Elsevier Inc. All rights reserved.

Collaborative agency to support integrated care for children, young people and families: an action research study

PubMed Central

Stuart, Kaz

2014-01-01

Abstract Introduction Collaboration was legislated in the delivery of integrated care in the early 2000s in the UK. This research explored how the reality of practice met the rhetoric of collaboration. Theory The paper is situated against a theoretical framework of structure, agency, identity and empowerment. Collectively and contextually these concepts inform the proposed model of ‘collaborative agency’ to sustain integrated care. The paper brings sociological theory on structure and agency to the dilemma of collaboration. Methods Participative action research was carried out in collaborative teams that aspired to achieve integrated care for children, young people and families between 2009 and 2013. It was a part time, PhD study in collaborative practice. Results The research established that people needed to be able to be jointly aware of their context, to make joint decisions, and jointly act in order to deliver integrated services, and proposes a model of collaborative agency derived from practitioner’s experiences and integrated action research and literature on agency. The model reflects the effects of a range of structures in shaping professional identity, empowerment, and agency in a dynamic. The author proposes that the collaborative agency model will support integrated care, although this is, as yet, an untested hypothesis. PMID:24868192

Progress in and prospects for fluvial flood modelling.

PubMed

Wheater, H S

2002-07-15

Recent floods in the UK have raised public and political awareness of flood risk. There is an increasing recognition that flood management and land-use planning are linked, and that decision-support modelling tools are required to address issues of climate and land-use change for integrated catchment management. In this paper, the scientific context for fluvial flood modelling is discussed, current modelling capability is considered and research challenges are identified. Priorities include (i) appropriate representation of spatial precipitation, including scenarios of climate change; (ii) development of a national capability for continuous hydrological simulation of ungauged catchments; (iii) improved scientific understanding of impacts of agricultural land-use and land-management change, and the development of new modelling approaches to represent those impacts; (iv) improved representation of urban flooding, at both local and catchment scale; (v) appropriate parametrizations for hydraulic simulation of in-channel and flood-plain flows, assimilating available ground observations and remotely sensed data; and (vi) a flexible decision-support modelling framework, incorporating developments in computing, data availability, data assimilation and uncertainty analysis.

Prescriptive models to support decision making in genetics.

PubMed

Pauker, S G; Pauker, S P

1987-01-01

Formal prescriptive models can help patients and clinicians better understand the risks and uncertainties they face and better formulate well-reasoned decisions. Using Bayes rule, the clinician can interpret pedigrees, historical data, physical findings and laboratory data, providing individualized probabilities of various diagnoses and outcomes of pregnancy. With the advent of screening programs for genetic disease, it becomes increasingly important to consider the prior probabilities of disease when interpreting an abnormal screening test result. Decision trees provide a convenient formalism for structuring diagnostic, therapeutic and reproductive decisions; such trees can also enhance communication between clinicians and patients. Utility theory provides a mechanism for patients to understand the choices they face and to communicate their attitudes about potential reproductive outcomes in a manner which encourages the integration of those attitudes into appropriate decisions. Using a decision tree, the relevant probabilities and the patients' utilities, physicians can estimate the relative worth of various medical and reproductive options by calculating the expected utility of each. By performing relevant sensitivity analyses, clinicians and patients can understand the impact of various soft data, including the patients' attitudes toward various health outcomes, on the decision making process. Formal clinical decision analytic models can provide deeper understanding and improved decision making in clinical genetics.

Autonomous, In-Flight Crew Health Risk Management for Exploration-Class Missions: Leveraging the Integrated Medical Model for the Exploration Medical System Demonstration Project

NASA Technical Reports Server (NTRS)

Butler, D. J.; Kerstman, E.; Saile, L.; Myers, J.; Walton, M.; Lopez, V.; McGrath, T.

2011-01-01

The Integrated Medical Model (IMM) captures organizational knowledge across the space medicine, training, operations, engineering, and research domains. IMM uses this knowledge in the context of a mission and crew profile to forecast risks to crew health and mission success. The IMM establishes a quantified, statistical relationship among medical conditions, risk factors, available medical resources, and crew health and mission outcomes. These relationships may provide an appropriate foundation for developing an in-flight medical decision support tool that helps optimize the use of medical resources and assists in overall crew health management by an autonomous crew with extremely limited interactions with ground support personnel and no chance of resupply.

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations.

PubMed

Mohammed, Ibrahim Nourein; Bolten, John D; Srinivasan, Raghavan; Lakshmi, Venkat

2018-06-01

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region's hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling.

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations

PubMed Central

Mohammed, Ibrahim Nourein; Bolten, John D.; Srinivasan, Raghavan; Lakshmi, Venkat

2018-01-01

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region’s hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling. PMID:29938116

Linking MODFLOW with an agent-based land-use model to support decision making

USGS Publications Warehouse

Reeves, H.W.; Zellner, M.L.

2010-01-01

The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent-based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time. Copyright ?? 2010 The Author(s). Journal compilation ?? 2010 National Ground Water Association.

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

PubMed

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

Hybridization of Architectural Styles for Integrated Enterprise Information Systems

NASA Astrophysics Data System (ADS)

Bagusyte, Lina; Lupeikiene, Audrone

Current enterprise systems engineering theory does not provide adequate support for the development of information systems on demand. To say more precisely, it is forming. This chapter proposes the main architectural decisions that underlie the design of integrated enterprise information systems. This chapter argues for the extending service-oriented architecture - for merging it with component-based paradigm at the design stage and using connectors of different architectural styles. The suitability of general-purpose language SysML for the modeling of integrated enterprise information systems architectures is described and arguments pros are presented.

Integrated Workforce Planning Model: A Proof of Concept

NASA Technical Reports Server (NTRS)

Guruvadoo, Eranna K.

2001-01-01

Recently, the Workforce and Diversity Management Office at KSC have launched a major initiative to develop and implement a competency/skill approach to Human Resource management. As the competency/skill dictionary is being elaborated, the need for a competency-based workforce-planning model is recognized. A proof of concept for such a model is presented using a multidimensional data model that can provide the data infrastructure necessary to drive intelligent decision support systems for workforce planing. The components of competency-driven workforce planning model are explained. The data model is presented and several schemes that would support the workforce-planning model are presented. Some directions and recommendations for future work are given.

Decision support models for economically efficient integrated forest management

Treesearch

Hans R. Zuuring; Judy M. Troutwine; Greg J. Jones; Janet Sullivan

2005-01-01

Forest managers are challenged to fulfill conflicting social, biological, and commodity production objectives. To wisely use available, scarce resources for management activities, it is not enough to consider short term costs and effects of management (fuel reduction, planting, or other forest treatments). Long term tactical, spatial and temporal planning is needed to...

A framework for simulating map error in ecosystem models

Treesearch

Sean P. Healey; Shawn P. Urbanski; Paul L. Patterson; Chris Garrard

2014-01-01

The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader...

Multi-sensory integration in a small brain

NASA Astrophysics Data System (ADS)

Gepner, Ruben; Wolk, Jason; Gershow, Marc

Understanding how fluctuating multi-sensory stimuli are integrated and transformed in neural circuits has proved a difficult task. To address this question, we study the sensori-motor transformations happening in the brain of the Drosophila larva, a tractable model system with about 10,000 neurons. Using genetic tools that allow us to manipulate the activity of individual brain cells through their transparent body, we observe the stochastic decisions made by freely-behaving animals as their visual and olfactory environments fluctuate independently. We then use simple linear-nonlinear models to correlate outputs with relevant features in the inputs, and adaptive filtering processes to track changes in these relevant parameters used by the larva's brain to make decisions. We show how these techniques allow us to probe how statistics of stimuli from different sensory modalities combine to affect behavior, and can potentially guide our understanding of how neural circuits are anatomically and functionally integrated. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture

NASA Astrophysics Data System (ADS)

Ines, A. V. M.; Han, E.; Baethgen, W.

2017-12-01

Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate "what-if" scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions. The CAMDT has a functionality to disaggregate a probabilistic SCF into daily weather realizations (either a parametric or non-parametric disaggregation method) and to run DSSAT-CSM-Rice with the disaggregated weather realizations. The convenient graphical user-interface allows easy implementation of several "what-if" scenarios for non-technical users and visualize the results of the scenario runs. In addition, the CAMDT also translates crop model outputs to economic terms once the user provides expected crop price and cost. The CAMDT is a practical tool for real-world applications, specifically for agricultural climate risk management in the Bicol region, Philippines, having a great flexibility for being adapted to other crops or regions in the world. CAMDT GitHub: https://github.com/Agro-Climate/CAMDT

Bringing the "social" into sociohydrology: Conservation policy support in the Central Great Plains of Kansas, USA

NASA Astrophysics Data System (ADS)

Sanderson, Matthew R.; Bergtold, Jason S.; Heier Stamm, Jessica L.; Caldas, Marcellus M.; Ramsey, Steven M.

2017-08-01

Identifying means of empirically modeling the human component of a coupled, human-water system becomes critically important to further advances in sociohydrology. We develop a social-psychological model of environmental decision making that addresses four key challenges of incorporating social science into integrated models. We use the model to explain preferences for three conservation policies designed to conserve and protect water resources and aquatic ecosystems in the Smoky Hill River Basin, a semiarid agricultural region in the Central U.S. Great Plains. Further, we compare the model's capacity to explain policy preferences among members of two groups in the River Basin: agricultural producers and members of nonfarming communities. We find that financial obligation is the strongest and most consistent explanation of support for conservation policies among members of both groups. We also find that policy support is grounded in cultural values—deeply held ideas about right and wrong. Environmental values are particularly important explanations of policy support. The constellations of values invoked to make decisions about policies, and the social-psychological pathways linking values to policy support, can vary across policies and types of agents (farmers and nonfarmers). We discuss the implications of the results for future research in sociohydrology.

An integrated modelling framework to aid smallholder farming system management in the Olifants River Basin, South Africa

NASA Astrophysics Data System (ADS)

Magombeyi, M. S.; Taigbenu, A. E.

Computerised integrated models from science contribute to better informed and holistic assessments of multifaceted policies and technologies than individual models. This view has led to considerable effort being devoted to developing integrated models to support decision-making under integrated water resources management (IWRM). Nevertheless, an appraisal of previous and ongoing efforts to develop such decision support systems shows considerable deficiencies in attempts to address the hydro-socio-economic effects on livelihoods. To date, no universal standard integration method or framework is in use. For the existing integrated models, their application failures have pointed to the lack of stakeholder participation. In an endeavour to close this gap, development and application of a seasonal time-step integrated model with prediction capability is presented in this paper. This model couples existing hydrology, agronomy and socio-economic models with feedbacks to link livelihoods of resource-constrained smallholder farmers to water resources at catchment level in the semi-arid Olifants subbasin in South Africa. These three models, prior to coupling, were calibrated and validated using observed data and participation of local stakeholders. All the models gave good representation of the study conditions, as indicated by the statistical indicators. The integrated model is of general applicability, hence can be extended to other catchments. The impacts of untied ridges, planting basins and supplemental irrigation were compared to conventional rainfed tillage under maize crop production and for different farm typologies. Over the 20 years of simulation, the predicted benefit of untied ridges and planting basins versus conventional rainfed tillage on surface runoff (Mm 3/year) reduction was 14.3% and 19.8%, respectively, and about 41-46% sediment yield (t/year) reduction in the catchment. Under supplemental irrigation, maize yield improved by up to 500% from the long-term average yield of 0.5 t/ha. At 90% confidence interval, family savings improved from between US 4 and US 270 under conventional rainfed to between US 233 and US 1140 under supplemental irrigation. These results highlight the economic and environmental benefits that could be achieved by adopting these improved crop management practices. However, the application of various crop management practices is site-specific and depends on both physical and socio-economic characteristics of the farmers.

A knowledge-based decision support system for payload scheduling

NASA Technical Reports Server (NTRS)

Floyd, Stephen; Ford, Donnie

1988-01-01

The role that artificial intelligence/expert systems technologies play in the development and implementation of effective decision support systems is illustrated. A recently developed prototype system for supporting the scheduling of subsystems and payloads/experiments for NASA's Space Station program is presented and serves to highlight various concepts. The potential integration of knowledge based systems and decision support systems which has been proposed in several recent articles and presentations is illustrated.

Agricultural Model for the Nile Basin Decision Support System

NASA Astrophysics Data System (ADS)

van der Bolt, Frank; Seid, Abdulkarim

2014-05-01

To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses

PubMed Central

Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-01

Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. Conclusions Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness. PMID:26813512

The Invasive Species Forecasting System

NASA Technical Reports Server (NTRS)

Schnase, John; Most, Neal; Gill, Roger; Ma, Peter

2011-01-01

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

A model of caregiver paediatric HIV disclosure decision-making

PubMed Central

Evangeli, Michael; Kagee, Ashraf

2016-01-01

Many of the over 3 million HIV-positive children will only be told of their status as adolescents. Knowing one’s status may increase treatment adherence, reduce onward HIV transmission, increase trust in caregivers, and maximise available support. Yet deciding whether, what, how, and when to tell HIV-positive children about their condition, is challenging for caregivers. We systematically review HIV disclosure theories before presenting a process model of caregiver paediatric HIV disclosure decision-making. The model, consisting of both a pre-intention and a post-intention stage, integrates individual and contextual determinants. It aims to be situationally-specific, broadly applicable, and consistent with the empirical literature. Research and practice implications are discussed. PMID:26119063

Dual Rationality and Deliberative Agents

NASA Astrophysics Data System (ADS)

Debenham, John; Sierra, Carles

Human agents deliberate using models based on reason for only a minute proportion of the decisions that they make. In stark contrast, the deliberation of artificial agents is heavily dominated by formal models based on reason such as game theory, decision theory and logic—despite that fact that formal reasoning will not necessarily lead to superior real-world decisions. Further the Nobel Laureate Friedrich Hayek warns us of the ‘fatal conceit’ in controlling deliberative systems using models based on reason as the particular model chosen will then shape the system’s future and either impede, or eventually destroy, the subtle evolutionary processes that are an integral part of human systems and institutions, and are crucial to their evolution and long-term survival. We describe an architecture for artificial agents that is founded on Hayek’s two rationalities and supports the two forms of deliberation used by mankind.

An Overview of NASA's Program of Future M&S VV&A Outreach and Training Activities

NASA Technical Reports Server (NTRS)

Caine, Lisa; Hale, Joseph P.

2006-01-01

NASA's Exploration Systems Mission Directorate (ESMD) is implementing a management approach for modeling and simulation (M&S) that will provide decision-makers information on the model s fidelity, credibility, and quality. The Integrated Modeling & Simulation Verification, Validation and Accreditation (IM&S W&A) process will allow the decision-maker to understand the risks involved in using a model s results for mission-critical decisions. The W&A Technical Working Group (W&A TWG) has been identified to communicate this process throughout the agency. As the W&A experts, the W&A NVG will be the central resource for support of W&A policy, procedures, training and templates for documentation. This presentation will discuss the W&A Technical Working Group s outreach approach aimed at educating M&S program managers, developers, users and proponents on the W&A process, beginning at MSFC with the CLV program.

Clinical Decision Support to Implement CYP2D6 Drug-Gene Interaction.

PubMed

Caraballo, Pedro J; Parkulo, Mark; Blair, David; Elliott, Michelle; Schultz, Cloann; Sutton, Joseph; Rao, Padma; Bruflat, Jamie; Bleimeyer, Robert; Crooks, John; Gabrielson, Donald; Nicholson, Wayne; Rohrer Vitek, Carolyn; Wix, Kelly; Bielinski, Suzette J; Pathak, Jyotishman; Kullo, Iftikhar

2015-01-01

The level of CYP2D6 metabolic activity can be predicted by pharmacogenomic testing, and concomitant use of clinical decision support has the potential to prevent adverse effects from those drugs metabolized by this enzyme. Our initial findings after implementation of clinical decision support alerts integrated in the electronic health records suggest high feasibility, but also identify important challenges.

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.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods.

PubMed

Skjerdal, Taran; Gefferth, Andras; Spajic, Miroslav; Estanga, Edurne Gaston; de Cecare, Alessandra; Vitali, Silvia; Pasquali, Frederique; Bovo, Federica; Manfreda, Gerardo; Mancusi, Rocco; Trevisiani, Marcello; Tessema, Girum Tadesse; Fagereng, Tone; Moen, Lena Haugland; Lyshaug, Lars; Koidis, Anastasios; Delgado-Pando, Gonzalo; Stratakos, Alexandros Ch; Boeri, Marco; From, Cecilie; Syed, Hyat; Muccioli, Mirko; Mulazzani, Roberto; Halbert, Catherine

2017-01-01

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes , quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as "good"; "sufficient"; or "corrective action needed" based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods

PubMed Central

Gefferth, Andras; Spajic, Miroslav; Estanga, Edurne Gaston; Vitali, Silvia; Pasquali, Frederique; Bovo, Federica; Manfreda, Gerardo; Mancusi, Rocco; Tessema, Girum Tadesse; Fagereng, Tone; Moen, Lena Haugland; Lyshaug, Lars; Koidis, Anastasios; Delgado-Pando, Gonzalo; Stratakos, Alexandros Ch.; Boeri, Marco; From, Cecilie; Syed, Hyat; Muccioli, Mirko; Mulazzani, Roberto; Halbert, Catherine

2017-01-01

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as “good”; “sufficient”; or “corrective action needed” based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users. PMID:29457031

ISTIMES Integrated System for Transport Infrastructures Surveillance and Monitoring by Electromagnetic Sensing

NASA Astrophysics Data System (ADS)

Argenti, M.; Giannini, V.; Averty, R.; Bigagli, L.; Dumoulin, J.

2012-04-01

The EC FP7 ISTIMES project has the goal of realizing an ICT-based system exploiting distributed and local sensors for non destructive electromagnetic monitoring in order to make critical transport infrastructures more reliable and safe. Higher situation awareness thanks to real time and detailed information and images of the controlled infrastructure status allows improving decision capabilities for emergency management stakeholders. Web-enabled sensors and a service-oriented approach are used as core of the architecture providing a sys-tem that adopts open standards (e.g. OGC SWE, OGC CSW etc.) and makes efforts to achieve full interoperability with other GMES and European Spatial Data Infrastructure initiatives as well as compliance with INSPIRE. The system exploits an open easily scalable network architecture to accommodate a wide range of sensors integrated with a set of tools for handling, analyzing and processing large data volumes from different organizations with different data models. Situation Awareness tools are also integrated in the system. Definition of sensor observations and services follows a metadata model based on the ISO 19115 Core set of metadata elements and the O&M model of OGC SWE. The ISTIMES infrastructure is based on an e-Infrastructure for geospatial data sharing, with a Data Cata-log that implements the discovery services for sensor data retrieval, acting as a broker through static connections based on standard SOS and WNS interfaces; a Decision Support component which helps decision makers providing support for data fusion and inference and generation of situation indexes; a Presentation component which implements system-users interaction services for information publication and rendering, by means of a WEB Portal using SOA design principles; A security framework using Shibboleth open source middleware based on the Security Assertion Markup Language supporting Single Sign On (SSO). ACKNOWLEDGEMENT - The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement n° 225663

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.

Perceptions of risk, risk aversion, and barriers to adoption of decision support systems and integrated pest management: An introduction

USDA-ARS?s Scientific Manuscript database

Rational management of plant diseases, both economically and environmentally, involves assessing risks and the costs associated with both correct and incorrect management decisions to determine when control measures are warranted. Decision support systems can help to inform users of plant disease r...

TethysCluster: A comprehensive approach for harnessing cloud resources for hydrologic modeling

NASA Astrophysics Data System (ADS)

Nelson, J.; Jones, N.; Ames, D. P.

2015-12-01

Advances in water resources modeling are improving the information that can be supplied to support decisions affecting the safety and sustainability of society. However, as water resources models become more sophisticated and data-intensive they require more computational power to run. Purchasing and maintaining the computing facilities needed to support certain modeling tasks has been cost-prohibitive for many organizations. With the advent of the cloud, the computing resources needed to address this challenge are now available and cost-effective, yet there still remains a significant technical barrier to leverage these resources. This barrier inhibits many decision makers and even trained engineers from taking advantage of the best science and tools available. Here we present the Python tools TethysCluster and CondorPy, that have been developed to lower the barrier to model computation in the cloud by providing (1) programmatic access to dynamically scalable computing resources, (2) a batch scheduling system to queue and dispatch the jobs to the computing resources, (3) data management for job inputs and outputs, and (4) the ability to dynamically create, submit, and monitor computing jobs. These Python tools leverage the open source, computing-resource management, and job management software, HTCondor, to offer a flexible and scalable distributed-computing environment. While TethysCluster and CondorPy can be used independently to provision computing resources and perform large modeling tasks, they have also been integrated into Tethys Platform, a development platform for water resources web apps, to enable computing support for modeling workflows and decision-support systems deployed as web apps.

Integrating research tools to support the management of social-ecological systems under climate change

USGS Publications Warehouse

Miller, Brian W.; Morisette, Jeffrey T.

2014-01-01

Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide data-driven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.

Integrated models to support multiobjective ecological restoration decisions.

PubMed

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

2017-12-01

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

Towards integration of clinical decision support in commercial hospital information systems using distributed, reusable software and knowledge components.

PubMed

Müller, M L; Ganslandt, T; Eich, H P; Lang, K; Ohmann, C; Prokosch, H U

2001-12-01

Clinicians' acceptance of clinical decision support depends on its workflow-oriented, context-sensitive accessibility and availability at the point of care, integrated into the Electronic Patient Record (EPR). Commercially available Hospital Information Systems (HIS) often focus on administrative tasks and mostly do not provide additional knowledge based functionality. Their traditionally monolithic and closed software architecture encumbers integration of and interaction with external software modules. Our aim was to develop methods and interfaces to integrate knowledge sources into two different commercial hospital information systems to provide the best decision support possible within the context of available patient data. An existing, proven standalone scoring system for acute abdominal pain was supplemented by a communication interface. In both HIS we defined data entry forms and developed individual and reusable mechanisms for data exchange with external software modules. We designed an additional knowledge support frontend which controls data exchange between HIS and the knowledge modules. Finally, we added guidelines and algorithms to the knowledge library. Despite some major drawbacks which resulted mainly from the HIS' closed software architectures we showed exemplary, how external knowledge support can be integrated almost seamlessly into different commercial HIS. This paper describes the prototypical design and current implementation and discusses our experiences.

Use of Decision Models in the Development of Evidence-Based Clinical Preventive Services Recommendations: Methods of the U.S. Preventive Services Task Force.

PubMed

Owens, Douglas K; Whitlock, Evelyn P; Henderson, Jillian; Pignone, Michael P; Krist, Alex H; Bibbins-Domingo, Kirsten; Curry, Susan J; Davidson, Karina W; Ebell, Mark; Gillman, Matthew W; Grossman, David C; Kemper, Alex R; Kurth, Ann E; Maciosek, Michael; Siu, Albert L; LeFevre, Michael L

2016-10-04

The U.S. Preventive Services Task Force (USPSTF) develops evidence-based recommendations about preventive care based on comprehensive systematic reviews of the best available evidence. Decision models provide a complementary, quantitative approach to support the USPSTF as it deliberates about the evidence and develops recommendations for clinical and policy use. This article describes the rationale for using modeling, an approach to selecting topics for modeling, and how modeling may inform recommendations about clinical preventive services. Decision modeling is useful when clinical questions remain about how to target an empirically established clinical preventive service at the individual or program level or when complex determinations of magnitude of net benefit, overall or among important subpopulations, are required. Before deciding whether to use decision modeling, the USPSTF assesses whether the benefits and harms of the preventive service have been established empirically, assesses whether there are key issues about applicability or implementation that modeling could address, and then defines the decision problem and key questions to address through modeling. Decision analyses conducted for the USPSTF are expected to follow best practices for modeling. For chosen topics, the USPSTF assesses the strengths and limitations of the systematically reviewed evidence and the modeling analyses and integrates the results of each to make preventive service recommendations.

Technosocial Modeling of IED Threat Scenarios and Attacks

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

Whitney, Paul D.; Brothers, Alan J.; Coles, Garill A.

2009-03-23

This paper describes an approach for integrating sociological and technical models to develop more complete threat assessment. Current approaches to analyzing and addressing threats tend to focus on the technical factors. This paper addresses development of predictive models that encompass behavioral as well as these technical factors. Using improvised explosive device (IED) attacks as motivation, this model supports identification of intervention activities 'left of boom' as well as prioritizing attack modalities. We show how Bayes nets integrate social factors associated with IED attacks into general threat model containing technical and organizational steps from planning through obtaining the IED to initiationmore » of the attack. The social models are computationally-based representations of relevant social science literature that describes human decision making and physical factors. When combined with technical models, the resulting model provides improved knowledge integration into threat assessment for monitoring. This paper discusses the construction of IED threat scenarios, integration of diverse factors into an analytical framework for threat assessment, indicator identification for future threats, and future research directions.« less

Rationality versus reality: the challenges of evidence-based decision making for health policy makers

PubMed Central

2010-01-01

Background Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved. PMID:20504357

Rationality versus reality: the challenges of evidence-based decision making for health policy makers.

PubMed

McCaughey, Deirdre; Bruning, Nealia S

2010-05-26

Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be improved.

Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness.

PubMed

Herasevich, Vitaly; Pickering, Brian W; Dong, Yue; Peters, Steve G; Gajic, Ognjen

2010-03-01

To develop and validate an informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Using open-schema data feeds imported from electronic medical records (EMRs), we developed a near-real-time relational database (Multidisciplinary Epidemiology and Translational Research in Intensive Care Data Mart). Imported data domains included physiologic monitoring, medication orders, laboratory and radiologic investigations, and physician and nursing notes. Open database connectivity supported the use of Boolean combinations of data that allowed authorized users to develop syndrome surveillance, decision support, and reporting (data "sniffers") routines. Random samples of database entries in each category were validated against corresponding independent manual reviews. The Multidisciplinary Epidemiology and Translational Research in Intensive Care Data Mart accommodates, on average, 15,000 admissions to the intensive care unit (ICU) per year and 200,000 vital records per day. Agreement between database entries and manual EMR audits was high for sex, mortality, and use of mechanical ventilation (kappa, 1.0 for all) and for age and laboratory and monitored data (Bland-Altman mean difference +/- SD, 1(0) for all). Agreement was lower for interpreted or calculated variables, such as specific syndrome diagnoses (kappa, 0.5 for acute lung injury), duration of ICU stay (mean difference +/- SD, 0.43+/-0.2), or duration of mechanical ventilation (mean difference +/- SD, 0.2+/-0.9). Extraction of essential ICU data from a hospital EMR into an open, integrative database facilitates process control, reporting, syndrome surveillance, decision support, and outcome research in the ICU.

Evaluation of new farming technologies in Ethiopia using the Integrated Decision Support System (IDSS).

PubMed

Clarke, Neville; Bizimana, Jean-Claude; Dile, Yihun; Worqlul, Abeyou; Osorio, Javier; Herbst, Brian; Richardson, James W; Srinivasan, Raghavan; Gerik, Thomas J; Williams, Jimmy; Jones, Charles A; Jeong, Jaehak

2017-01-31

This study investigates multi-dimensional impacts of adopting new technology in agriculture at the farm/village and watershed scale in sub-Saharan Africa using the Integrated Decision Support System (IDSS). Application of IDSS as an integrated modeling tool helps solve complex issues in agricultural systems by simultaneously assessing production, environmental, economic, and nutritional consequences of adopting agricultural technologies for sustainable increases in food production and use of scarce natural resources. The IDSS approach was applied to the Amhara region of Ethiopia, where the scarcity of resources and agro-environmental consequences are critical to agricultural productivity of small farm, to analyze the impacts of alternative agricultural technology interventions. Results show significant improvements in family income and nutrition, achieved through the adoption of irrigation technologies, proper use of fertilizer, and improved seed varieties while preserving environmental indicators in terms of soil erosion and sediment loadings. These pilot studies demonstrate the usefulness of the IDSS approach as a tool that can be used to predict and evaluate the economic and environmental consequences of adopting new agricultural technologies that aim to improve the livelihoods of subsistence farmers.

GeoProMT: A Collaborative Platform Supporting Natural Hazards Project Management From Assessment to Resilience

NASA Astrophysics Data System (ADS)

Renschler, C.; Sheridan, M. F.; Patra, A. K.

2008-05-01

The impact and consequences of extreme geophysical events (hurricanes, floods, wildfires, volcanic flows, mudflows, etc.) on properties and processes should be continuously assessed by a well-coordinated interdisciplinary research and outreach approach addressing risk assessment and resilience. Communication between various involved disciplines and stakeholders is the key to a successful implementation of an integrated risk management plan. These issues become apparent at the level of decision support tools for extreme events/disaster management in natural and managed environments. The Geospatial Project Management Tool (GeoProMT) is a collaborative platform for research and training to document and communicate the fundamental steps in transforming information for extreme events at various scales for analysis and management. GeoProMT is an internet-based interface for the management of shared geo-spatial and multi-temporal information such as measurements, remotely sensed images, and other GIS data. This tool enhances collaborative research activities and the ability to assimilate data from diverse sources by integrating information management. This facilitates a better understanding of natural processes and enhances the integrated assessment of resilience against both the slow and fast onset of hazard risks. Fundamental to understanding and communicating complex natural processes are: (a) representation of spatiotemporal variability, extremes, and uncertainty of environmental properties and processes in the digital domain, (b) transformation of their spatiotemporal representation across scales (e.g. interpolation, aggregation, disaggregation.) during data processing and modeling in the digital domain, and designing and developing tools for (c) geo-spatial data management, and (d) geo-spatial process modeling and effective implementation, and (e) supporting decision- and policy-making in natural resources and hazard management at various spatial and temporal scales of interest. GeoProMT is useful for researchers, practitioners, and decision-makers, because it provides an integrated environmental system assessment and data management approach that considers the spatial and temporal scales and variability in natural processes. Particularly in the occurrence or onset of extreme events it can utilize the latest data sources that are available at variable scales, combine them with existing information, and update assessment products such as risk and vulnerability assessment maps. Because integrated geo-spatial assessment requires careful consideration of all the steps in utilizing data, modeling and decision-making formats, each step in the sequence must be assessed in terms of how information is being scaled. At the process scale various geophysical models (e.g. TITAN, LAHARZ, or many other examples) are appropriate for incorporation in the tool. Some examples that illustrate our approach include: 1) coastal parishes impacted by Hurricane Rita (Southwestern Louisiana), 2) a watershed affected by extreme rainfall induced debris-flows (Madison County, Virginia; Panabaj, Guatemala; Casita, Nicaragua), and 3) the potential for pyroclastic flows to threaten a city (Tungurahua, Ecuador). This research was supported by the National Science Foundation.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

PubMed

Freebairn, Louise; Rychetnik, Lucie; Atkinson, Jo-An; Kelly, Paul; McDonnell, Geoff; Roberts, Nick; Whittall, Christine; Redman, Sally

2017-10-02

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Hybrid supply chain model for material requirement planning under financial constraints: A case study

NASA Astrophysics Data System (ADS)

Curci, Vita; Dassisti, Michele; Josefa, Mula Bru; Manuel, Díaz Madroñero

2014-10-01

Supply chain model (SCM) are potentially capable to integrate different aspects in supporting decision making for enterprise management tasks. The aim of the paper is to propose an hybrid mathematical programming model for optimization of production requirements resources planning. The preliminary model was conceived bottom-up from a real industrial case analysed oriented to maximize cash flow. Despite the intense computational effort required to converge to a solution, optimisation done brought good result in solving the objective function.

Spiking Phineas Gage: a neurocomputational theory of cognitive-affective integration in decision making.

PubMed

Wagar, Brandon M; Thagard, Paul

2004-01-01

The authors present a neurological theory of how cognitive information and emotional information are integrated in the nucleus accumbens during effective decision making. They describe how the nucleus accumbens acts as a gateway to integrate cognitive information from the ventromedial prefrontal cortex and the hippocampus with emotional information from the amygdala. The authors have modeled this integration by a network of spiking artificial neurons organized into separate areas and used this computational model to simulate 2 kinds of cognitive-affective integration. The model simulates successful performance by people with normal cognitive-affective integration. The model also simulates the historical case of Phineas Gage as well as subsequent patients whose ability to make decisions became impeded by damage to the ventromedial prefrontal cortex.

A decision support system for delivering optimal quality peach and tomato

NASA Technical Reports Server (NTRS)

Thai, C. N.; Pease, J. N.; Shewfelt, R. L.

1990-01-01

Several studies have indicated that color and firmness are the two quality attributes most important to consumers in making purchasing decisions of fresh peaches and tomatoes. However, at present, retail produce managers do not have the proper information for handling fresh produce so it has the most appealing color and firmness when it reaches the consumer. This information should help them predict the consumer color and firmness perception and preference for produce from various storage conditions. Since 1987, for 'Redglobe' peach and 'Sunny' tomato, we have been generating information about their physical quality attributes (firmness and color) and their corresponding consumer sensory scores. This article reports on our current progress toward the goal of integrating such information into a model-based decision support system for retail level managers in handling fresh peaches and tomatoes.

Effects of Individual Differences and Job Characteristics on the Psychological Health of Italian Nurses

PubMed Central

Zurlo, Maria Clelia; Vallone, Federica; Smith, Andrew P.

2018-01-01

The Demand Resources and Individual Effects Model (DRIVE Model) is a transactional model that integrates Demands- Control-Support and Effort-Reward Imbalance models emphasising the role of individual (Coping Strategies; Overcommitment) and job characteristics (Job Demands, Social Support, Decision Latitude, Skill Discretion, Effort, Rewards) in the work-related stress process. The present study aimed to test the DRIVE Model in a sample of 450 Italian nurses and to compare findings with those of a study conducted in a sample of UK nurses. A questionnaire composed of Ways of Coping Checklist-Revised (WCCL-R); Job Content Questionnaire (JCQ); ERI Test; Hospital Anxiety and Depression Scale (HADS) was used. Data supported the application of the DRIVE Model to the Italian context, showing significant associations of the individual characteristics of Problem-focused, Seek Advice and Wishful Thinking coping strategies and the job characteristics of Job Demands, Skill Discretion, Decision Latitude, and Effort with perceived levels of Anxiety and Depression. Effort represented the best predictor for psychological health conditions among Italian nurses, and Social Support significantly moderated the effects of Job Demands on perceived levels of Anxiety. The comparison study showed significant differences in the risk profiles of Italian and UK nurses. Findings were discussed in order to define focused interventions to promote nurses’ wellbeing.

Equilibrium approach towards water resource management and pollution control in coal chemical industrial park.

PubMed

Xu, Jiuping; Hou, Shuhua; Xie, Heping; Lv, Chengwei; Yao, Liming

2018-08-01

In this study, an integrated water and waste load allocation model is proposed to assist decision makers in better understanding the trade-offs between economic growth, resource utilization, and environmental protection of coal chemical industries which characteristically have high water consumption and pollution. In the decision framework, decision makers in a same park, each of whom have different goals and preferences, work together to seek a collective benefit. Similar to a Stackelberg-Nash game, the proposed approach illuminates the decision making interrelationships and involves in the conflict coordination between the park authority and the individual coal chemical company stockholders. In the proposed method, to response to climate change and other uncertainties, a risk assessment tool, Conditional Value-at-Risk (CVaR) and uncertainties through reflecting parameters and coefficients using probability and fuzzy set theory are integrated in the modeling process. Then a case study from Yuheng coal chemical park is presented to demonstrate the practicality and efficiency of the optimization model. To reasonable search the potential consequences of different responses to water and waste load allocation strategies, a number of scenario results considering environmental uncertainty and decision maker' attitudes are examined to explore the tradeoffs between economic development and environmental protection and decision makers' objectives. The results are helpful for decision/police makers to adjust current strategies adapting for current changes. Based on the scenario analyses and discussion, some propositions and operational policies are given and sensitive adaptation strategies are presented to support the efficient, balanced and sustainable development of coal chemical industrial parks. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Exploring Challenges and Opportunities of Coproduction: USDA Climate Hub Efforts to Integrate Coproduction with Applied Research and Decision Support Tool Development in the Northwest

NASA Astrophysics Data System (ADS)

Roesch-McNally, G.; Prendeville, H. R.

2017-12-01

A lack of coproduction, the joint production of new technologies or knowledge among technical experts and other groups, is arguably one of the reasons why much scientific information and resulting decision support systems are not very usable. Increasingly, public agencies and academic institutions are emphasizing the importance of coproduction of scientific knowledge and decision support systems in order to facilitate greater engagement between the scientific community and key stakeholder groups. Coproduction has been embraced as a way for the scientific community to develop actionable scientific information that will assist end users in solving real-world problems. Increasing the level of engagement and stakeholder buy-in to the scientific process is increasingly necessary, particularly in the context of growing politicization of science and the scientific process. Coproduction can be an effective way to build trust and can build-on and integrate local and traditional knowledge. Employing coproduction strategies may enable the development of more relevant and useful information and decision support tools that address stakeholder challenges at relevant scales. The USDA Northwest Climate Hub has increasingly sought ways to integrate coproduction in the development of both applied research projects and the development of decision support systems. Integrating coproduction, however, within existing institutions is not always simple, given that coproduction is often more focused on process than products and products are, for better or worse, often the primary focus of applied research and tool development projects. The USDA Northwest Climate Hub sought to integrate coproduction into our FY2017 call for proposal process. As a result we have a set of proposals and fledgling projects that fall along the engagement continuum (see Figure 1- attached). We will share the challenges and opportunities that emerged from this purposeful integration of coproduction into the work that we prioritized for funding. This effort highlights strategies for how federal agencies might consider how and whether to codify coproduction tenets into their collaborations and agenda setting.

Mindful judgment and decision making.

PubMed

Weber, Elke U; Johnson, Eric J

2009-01-01

A full range of psychological processes has been put into play to explain judgment and choice phenomena. Complementing work on attention, information integration, and learning, decision research over the past 10 years has also examined the effects of goals, mental representation, and memory processes. In addition to deliberative processes, automatic processes have gotten closer attention, and the emotions revolution has put affective processes on a footing equal to cognitive ones. Psychological process models provide natural predictions about individual differences and lifespan changes and integrate across judgment and decision making (JDM) phenomena. "Mindful" JDM research leverages our knowledge about psychological processes into causal explanations for important judgment and choice regularities, emphasizing the adaptive use of an abundance of processing alternatives. Such explanations supplement and support existing mathematical descriptions of phenomena such as loss aversion or hyperbolic discounting. Unlike such descriptions, they also provide entry points for interventions designed to help people overcome judgments or choices considered undesirable.

Integrating knowledge representation and quantitative modelling in physiology.

PubMed

de Bono, Bernard; Hunter, Peter

2012-08-01

A wealth of potentially shareable resources, such as data and models, is being generated through the study of physiology by computational means. Although in principle the resources generated are reusable, in practice, few can currently be shared. A key reason for this disparity stems from the lack of consistent cataloguing and annotation of these resources in a standardised manner. Here, we outline our vision for applying community-based modelling standards in support of an automated integration of models across physiological systems and scales. Two key initiatives, the Physiome Project and the European contribution - the Virtual Phsysiological Human Project, have emerged to support this multiscale model integration, and we focus on the role played by two key components of these frameworks, model encoding and semantic metadata annotation. We present examples of biomedical modelling scenarios (the endocrine effect of atrial natriuretic peptide, and the implications of alcohol and glucose toxicity) to illustrate the role that encoding standards and knowledge representation approaches, such as ontologies, could play in the management, searching and visualisation of physiology models, and thus in providing a rational basis for healthcare decisions and contributing towards realising the goal of of personalized medicine. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systems Analysis - a new paradigm and decision support tools for the water framework directive

NASA Astrophysics Data System (ADS)

Bruen, M.

2008-05-01

In the early days of Systems Analysis the focus was on providing tools for optimisation, modelling and simulation for use by experts. Now there is a recognition of the need to develop and disseminate tools to assist in making decisions, negotiating compromises and communicating preferences that can easily be used by stakeholders without the need for specialist training. The Water Framework Directive (WFD) requires public participation and thus provides a strong incentive for progress in this direction. This paper places the new paradigm in the context of the classical one and discusses some of the new approaches which can be used in the implementation of the WFD. These include multi-criteria decision support methods suitable for environmental problems, adaptive management, cognitive mapping, social learning and cooperative design and group decision-making. Concordance methods (such as ELECTRE) and the Analytical Hierarchy Process (AHP) are identified as multi-criteria methods that can be readily integrated into Decision Support Systems (DSS) that deal with complex environmental issues with very many criteria, some of which are qualitative. The expanding use of the new paradigm provides an opportunity to observe and learn from the interaction of stakeholders with the new technology and to assess its effectiveness.

Optimal multisensory decision-making in a reaction-time task.

PubMed

Drugowitsch, Jan; DeAngelis, Gregory C; Klier, Eliana M; Angelaki, Dora E; Pouget, Alexandre

2014-06-14

Humans and animals can integrate sensory evidence from various sources to make decisions in a statistically near-optimal manner, provided that the stimulus presentation time is fixed across trials. Little is known about whether optimality is preserved when subjects can choose when to make a decision (reaction-time task), nor when sensory inputs have time-varying reliability. Using a reaction-time version of a visual/vestibular heading discrimination task, we show that behavior is clearly sub-optimal when quantified with traditional optimality metrics that ignore reaction times. We created a computational model that accumulates evidence optimally across both cues and time, and trades off accuracy with decision speed. This model quantitatively explains subjects's choices and reaction times, supporting the hypothesis that subjects do, in fact, accumulate evidence optimally over time and across sensory modalities, even when the reaction time is under the subject's control.

United States Air Force Graduate Student Summer Support Program (1987). Program Management Report.

DTIC Science & Technology

1987-12-01

were briefed on the benefits and research opportunities of the SFRP. The targeted groups within the University community were faculty of the...Effects on Fine Mary C. Robinson Motor Skill and Decoding Tasks 78 Design of a Mechanism to Control Wind Filiberto Santiago Tunnel Turbulence 79 Low...Systems 81 The Integration of Decision Support Jon A. Shupe Problems into Feature Modeling Based Design 89 r 0 82 Optimal Control of the Wing

ISERV Pathfinder. The ISS SERVIR Environmental Research and Visualization System

NASA Technical Reports Server (NTRS)

Howell, Burgess

2011-01-01

SERVIR integrates Earth observations (e.g., space imagery), predictive models, and in situ data to provide timely information products to support environmental decision makers. ISERV propoesed development -- ISERV-W: Internal Visible/Near-Infrared (VNIR), attached to ISS via Window Observational Research Facility (WORF), ISERV-E: External Visible/Broad-Infrared (V/IR) and ISERV-PM: External Passive Microwave.

Integrating Data Mining in Program Evaluation of K-12 Online Education

ERIC Educational Resources Information Center

Hung, Jui-Long; Hsu, Yu-Chang; Rice, Kerry

2012-01-01

This study investigated an innovative approach of program evaluation through analyses of student learning logs, demographic data, and end-of-course evaluation surveys in an online K-12 supplemental program. The results support the development of a program evaluation model for decision making on teaching and learning at the K-12 level. A case study…

Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: methods of a decision-maker-researcher partnership systematic review.

PubMed

Haynes, R Brian; Wilczynski, Nancy L

2010-02-05

Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit. The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system. Data will be summarized using descriptive summary measures, including proportions for categorical variables and means for continuous variables. Univariable and multivariable logistic regression models will be used to investigate associations between outcomes of interest and study specific covariates. When reporting results from individual studies, we will cite the measures of association and p-values reported in the studies. If appropriate for groups of studies with similar features, we will conduct meta-analyses. A decision-maker-researcher partnership provides a model for systematic reviews that may foster knowledge translation and uptake.

Utilization of Live Localized Weather Information for Sustainable Agriculture

NASA Astrophysics Data System (ADS)

Anderson, J.; Usher, J.

2010-09-01

Authors: Jim Anderson VP, Global Network and Business Development WeatherBug® Professional Jeremy Usher Managing Director, Europe WeatherBug® Professional Localized, real-time weather information is vital for day-to-day agronomic management of all crops. The challenge for agriculture is twofold in that local and timely weather data is not often available for producers and farmers, and it is not integrated into decision-support tools they require. Many of the traditional sources of weather information are not sufficient for agricultural applications because of the long distances between weather stations, meaning the data is not always applicable for on-farm decision making processes. The second constraint with traditional weather information is the timeliness of the data. Most delivery systems are designed on a one-hour time step, whereas many decisions in agriculture are based on minute-by-minute weather conditions. This is especially true for decisions surrounding chemical and fertilizer application and frost events. This presentation will outline how the creation of an agricultural mesonet (weather network) can enable producers and farmers with live, local weather information from weather stations installed in farm/field locations. The live weather information collected from each weather station is integrated into a web-enabled decision support tool, supporting numerous on-farm agronomic activities such as pest management, or dealing with heavy rainfall and frost events. Agronomic models can be used to assess the potential of disease pressure, enhance the farmer's abilities to time pesticide applications, or assess conditions contributing to yield and quality fluctuations. Farmers and industry stakeholders may also view quality-assured historical weather variables at any location. This serves as a record-management tool for viewing previously uncharted agronomic weather events in graph or table form. This set of weather tools is unique and provides a significant enhancement to the agronomic decision-support process. Direct benefits to growers can take the form of increased yield and grade potential, as well as savings in money and time. Pest management strategies become more efficient due to timely and localized disease and pest modelling, and increased efficacy of pest and weed control. Examples from the Canadian Wheat Board (CWB) WeatherFarm weather network will be utilized to illustrate the processes, decision tools and benefits to producers and farmers.

Integrated Watershed Management using the Watershed Management Optimization Support Tool (WMOST)

EPA Science Inventory

Integrated watershed management is an effective planning strategy to balance tradeoffs between competing water uses within a watershed. WMOST is an Excel-based decision tool to aid planners in making cost effective decisions that meet water quantity and quality regulations. WMOST...

User's Guide for SeedCalc: A Decision-Support System for Integrated Pest Management in Slash Pine Seed Orchards

Treesearch

Carl W. Fatzinger; Wayne N. Dixon

1996-01-01

SeedCalc, a decision-support system designed for use on personal computers, evaluates the consequences of different pest management strategies in slash pine (Pinus ellliottii Engelm. var. elliottii) seed orchards.

Integrated Hydrographical Basin Management. Study Case - Crasna River Basin

NASA Astrophysics Data System (ADS)

Visescu, Mircea; Beilicci, Erika; Beilicci, Robert

2017-10-01

Hydrographical basins are important from hydrological, economic and ecological points of view. They receive and channel the runoff from rainfall and snowmelt which, when adequate managed, can provide fresh water necessary for water supply, irrigation, food industry, animal husbandry, hydrotechnical arrangements and recreation. Hydrographical basin planning and management follows the efficient use of available water resources in order to satisfy environmental, economic and social necessities and constraints. This can be facilitated by a decision support system that links hydrological, meteorological, engineering, water quality, agriculture, environmental, and other information in an integrated framework. In the last few decades different modelling tools for resolving problems regarding water quantity and quality were developed, respectively water resources management. Watershed models have been developed to the understanding of water cycle and pollution dynamics, and used to evaluate the impacts of hydrotechnical arrangements and land use management options on water quantity, quality, mitigation measures and possible global changes. Models have been used for planning monitoring network and to develop plans for intervention in case of hydrological disasters: floods, flash floods, drought and pollution. MIKE HYDRO Basin is a multi-purpose, map-centric decision support tool for integrated hydrographical basin analysis, planning and management. MIKE HYDRO Basin is designed for analyzing water sharing issues at international, national and local hydrographical basin level. MIKE HYDRO Basin uses a simplified mathematical representation of the hydrographical basin including the configuration of river and reservoir systems, catchment hydrology and existing and potential water user schemes with their various demands including a rigorous irrigation scheme module. This paper analyzes the importance and principles of integrated hydrographical basin management and develop a case study for Crasna river basin, with the use of MIKE HYDRO Basin advanced hydroinformatic tool for integrated hydrographical basin analysis, planning and management.

Medical Device Integrated Vital Signs Monitoring Application with Real-Time Clinical Decision Support.

PubMed

Moqeem, Aasia; Baig, Mirza; Gholamhosseini, Hamid; Mirza, Farhaan; Lindén, Maria

2018-01-01

This research involves the design and development of a novel Android smartphone application for real-time vital signs monitoring and decision support. The proposed application integrates market available, wireless and Bluetooth connected medical devices for collecting vital signs. The medical device data collected by the app includes heart rate, oxygen saturation and electrocardiograph (ECG). The collated data is streamed/displayed on the smartphone in real-time. This application was designed by adopting six screens approach (6S) mobile development framework and focused on user-centered approach and considered clinicians-as-a-user. The clinical engagement, consultations, feedback and usability of the application in the everyday practices were considered critical from the initial phase of the design and development. Furthermore, the proposed application is capable to deliver rich clinical decision support in real-time using the integrated medical device data.

A systematic approach to embedded biomedical decision making.

PubMed

Song, Zhe; Ji, Zhongkai; Ma, Jian-Guo; Sputh, Bernhard; Acharya, U Rajendra; Faust, Oliver

2012-11-01

An embedded decision making is a key feature for many biomedical systems. In most cases human life directly depends on correct decisions made by these systems, therefore they have to work reliably. This paper describes how we applied systems engineering principles to design a high performance embedded classification system in a systematic and well structured way. We introduce the structured design approach by discussing requirements capturing, specifications refinement, implementation and testing. Thereby, we follow systems engineering principles and execute each of these processes as formal as possible. The requirements, which motivate the system design, describe an automated decision making system for diagnostic support. These requirements are refined into the implementation of a support vector machine (SVM) algorithm which enables us to integrate automated decision making in embedded systems. With a formal model we establish functionality, stability and reliability of the system. Furthermore, we investigated different parallel processing configurations of this computationally complex algorithm. We found that, by adding SVM processes, an almost linear speedup is possible. Once we established these system properties, we translated the formal model into an implementation. The resulting implementation was tested using XMOS processors with both normal and failure cases, to build up trust in the implementation. Finally, we demonstrated that our parallel implementation achieves the speedup, predicted by the formal model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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

Anderson, Katherine H.; Cutler, Dylan S.; Olis, Daniel R.

REopt is a techno-economic decision support model used to optimize energy systems for buildings, campuses, communities, and microgrids. The primary application of the model is for optimizing the integration and operation of behind-the-meter energy assets. This report provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible, and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

Continuous track paths reveal additive evidence integration in multistep decision making.

PubMed

Buc Calderon, Cristian; Dewulf, Myrtille; Gevers, Wim; Verguts, Tom

2017-10-03

Multistep decision making pervades daily life, but its underlying mechanisms remain obscure. We distinguish four prominent models of multistep decision making, namely serial stage, hierarchical evidence integration, hierarchical leaky competing accumulation (HLCA), and probabilistic evidence integration (PEI). To empirically disentangle these models, we design a two-step reward-based decision paradigm and implement it in a reaching task experiment. In a first step, participants choose between two potential upcoming choices, each associated with two rewards. In a second step, participants choose between the two rewards selected in the first step. Strikingly, as predicted by the HLCA and PEI models, the first-step decision dynamics were initially biased toward the choice representing the highest sum/mean before being redirected toward the choice representing the maximal reward (i.e., initial dip). Only HLCA and PEI predicted this initial dip, suggesting that first-step decision dynamics depend on additive integration of competing second-step choices. Our data suggest that potential future outcomes are progressively unraveled during multistep decision making.

Clinical Use of an Enterprise Data Warehouse

PubMed Central

Evans, R. Scott; Lloyd, James F.; Pierce, Lee A.

2012-01-01

The enormous amount of data being collected by electronic medical records (EMR) has found additional value when integrated and stored in data warehouses. The enterprise data warehouse (EDW) allows all data from an organization with numerous inpatient and outpatient facilities to be integrated and analyzed. We have found the EDW at Intermountain Healthcare to not only be an essential tool for management and strategic decision making, but also for patient specific clinical decision support. This paper presents the structure and two case studies of a framework that has provided us the ability to create a number of decision support applications that are dependent on the integration of previous enterprise-wide data in addition to a patient’s current information in the EMR. PMID:23304288

Supportive care for older people with frailty in hospital: An integrative review.

PubMed

Nicholson, Caroline; Morrow, Elizabeth M; Hicks, Allan; Fitzpatrick, Joanne

2017-01-01

Growing numbers of older people living with frailty and chronic health conditions are being referred to hospitals with acute care needs. Supportive care is a potentially highly relevant and clinically important approach which could bridge the practice gap between curative models of care and palliative care. However, future interventions need to be informed and underpinned by existing knowledge of supportive care. To identify and build upon existing theories and evidence about supportive care, specifically in relation to the hospital care of older people with frailty, to inform future interventions and their evaluation. An integrative review was used to identify and integrate theory and evidence. Electronic databases (Cochrane Medline, EMBASE and CIHAHL) were searched using the key term 'supportive care'. Screening identified studies employing qualitative and/or quantitative methods published between January 1990 and December 2015. Citation searches, reference checking and searches of the grey literature were also undertaken. Literature searches identified 2733 articles. After screening, and applying eligibility criteria based on relevance to the research question, studies were subject to methodological quality appraisal. Findings from included articles (n=52) were integrated using synthesis of themes. Relevant evidence was identified across different research literatures, on clinical conditions and contexts. Seven distinct themes of the synthesis were identified, these were: Ensuring fundamental aspects of care are met, Communicating and connecting with the patient, Carer and family engagement, Building up a picture of the person and their circumstances, Decisions and advice about best care for the person, Enabling self-help and connection to wider support, and Supporting patients through transitions in care. A tentative integrative model of supportive care for frail older people is developed from the findings. The findings and model developed here will inform future interventions and can help staff and hospital managers to develop appropriate strategies, staff training and resource allocation models to improve the quality of health care for older people. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Qualitative Readiness-Requirements Assessment Model for Enterprise Big-Data Infrastructure Investment

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

Olama, Mohammed M; McNair, Wade; Sukumar, Sreenivas R

2014-01-01

In the last three decades, there has been an exponential growth in the area of information technology providing the information processing needs of data-driven businesses in government, science, and private industry in the form of capturing, staging, integrating, conveying, analyzing, and transferring data that will help knowledge workers and decision makers make sound business decisions. Data integration across enterprise warehouses is one of the most challenging steps in the big data analytics strategy. Several levels of data integration have been identified across enterprise warehouses: data accessibility, common data platform, and consolidated data model. Each level of integration has its ownmore » set of complexities that requires a certain amount of time, budget, and resources to implement. Such levels of integration are designed to address the technical challenges inherent in consolidating the disparate data sources. In this paper, we present a methodology based on industry best practices to measure the readiness of an organization and its data sets against the different levels of data integration. We introduce a new Integration Level Model (ILM) tool, which is used for quantifying an organization and data system s readiness to share data at a certain level of data integration. It is based largely on the established and accepted framework provided in the Data Management Association (DAMA-DMBOK). It comprises several key data management functions and supporting activities, together with several environmental elements that describe and apply to each function. The proposed model scores the maturity of a system s data governance processes and provides a pragmatic methodology for evaluating integration risks. The higher the computed scores, the better managed the source data system and the greater the likelihood that the data system can be brought in at a higher level of integration.« less

A qualitative readiness-requirements assessment model for enterprise big-data infrastructure investment

NASA Astrophysics Data System (ADS)

Olama, Mohammed M.; McNair, Allen W.; Sukumar, Sreenivas R.; Nutaro, James J.

2014-05-01

In the last three decades, there has been an exponential growth in the area of information technology providing the information processing needs of data-driven businesses in government, science, and private industry in the form of capturing, staging, integrating, conveying, analyzing, and transferring data that will help knowledge workers and decision makers make sound business decisions. Data integration across enterprise warehouses is one of the most challenging steps in the big data analytics strategy. Several levels of data integration have been identified across enterprise warehouses: data accessibility, common data platform, and consolidated data model. Each level of integration has its own set of complexities that requires a certain amount of time, budget, and resources to implement. Such levels of integration are designed to address the technical challenges inherent in consolidating the disparate data sources. In this paper, we present a methodology based on industry best practices to measure the readiness of an organization and its data sets against the different levels of data integration. We introduce a new Integration Level Model (ILM) tool, which is used for quantifying an organization and data system's readiness to share data at a certain level of data integration. It is based largely on the established and accepted framework provided in the Data Management Association (DAMADMBOK). It comprises several key data management functions and supporting activities, together with several environmental elements that describe and apply to each function. The proposed model scores the maturity of a system's data governance processes and provides a pragmatic methodology for evaluating integration risks. The higher the computed scores, the better managed the source data system and the greater the likelihood that the data system can be brought in at a higher level of integration.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

Efficacy of an evidence-based clinical decision support in primary care practices: a randomized clinical trial.

PubMed

McGinn, Thomas G; McCullagh, Lauren; Kannry, Joseph; Knaus, Megan; Sofianou, Anastasia; Wisnivesky, Juan P; Mann, Devin M

2013-09-23

There is consensus that incorporating clinical decision support into electronic health records will improve quality of care, contain costs, and reduce overtreatment, but this potential has yet to be demonstrated in clinical trials. To assess the influence of a customized evidence-based clinical decision support tool on the management of respiratory tract infections and on the effectiveness of integrating evidence at the point of care. In a randomized clinical trial, we implemented 2 well-validated integrated clinical prediction rules, namely, the Walsh rule for streptococcal pharyngitis and the Heckerling rule for pneumonia. INTERVENTIONS AND MAIN OUTCOMES AND MEASURES: The intervention group had access to the integrated clinical prediction rule tool and chose whether to complete risk score calculators, order medications, and generate progress notes to assist with complex decision making at the point of care. The intervention group completed the integrated clinical prediction rule tool in 57.5% of visits. Providers in the intervention group were significantly less likely to order antibiotics than the control group (age-adjusted relative risk, 0.74; 95% CI, 0.60-0.92). The absolute risk of the intervention was 9.2%, and the number needed to treat was 10.8. The intervention group was significantly less likely to order rapid streptococcal tests compared with the control group (relative risk, 0.75; 95% CI, 0.58-0.97; P= .03). The integrated clinical prediction rule process for integrating complex evidence-based clinical decision report tools is of relevant importance for national initiatives, such as Meaningful Use. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01386047.

A Practical Review of Integrated Urban Water Models: Applications as Decision Support Tools and Beyond

NASA Astrophysics Data System (ADS)

Mosleh, L.; Negahban-Azar, M.

2017-12-01

The integrated urban water management has become a necessity due to the high rate of urbanization, water scarcity, and climate variability. Climate and demographic changes, shifting the social attitude toward the water usage, and insufficiencies in system resilience increase the pressure on the water resources. Alongside with the water management, modeling urban water systems have progressed from traditional view to comprise alternatives such as decentralized water and wastewater systems, fit-for-purpose practice, graywater/rainwater reuse, and green infrastructure. While there are review papers available focusing on the technical part of the models, they seem to be more beneficial for model developers. Some of the models analyze a number of scenarios considering factors such as climate change and demography and their future impacts. However, others only focus on quality and quantity of water in a supply/demand approach. For example, optimizing the size of water or waste water store, characterizing the supply and quantity of urban stormwater and waste water, and link source of water to demand. A detailed and practical comparison of such models has become a necessity for the practitioner and policy makers. This research compares more than 7 most commonly used integrated urban water cycle models and critically reviews their capabilities, input requirements, output and their applications. The output of such detailed comparison will help the policy makers for the decision process in the built environment to compare and choose the best models that meet their goals. The results of this research show that we need a transition from developing/using integrated water cycle models to integrated system models which incorporate urban water infrastructures and ecological and economic factors. Such models can help decision makers to reflect other important criteria but with the focus on urban water management. The research also showed that there is a need in exploring sustainability, comprising water energy-nexus, and considering ecosystem services in the models. In addition, socio-economic factors such as public acceptance can be added to such models. Finally, the reliability and resilience of urban water management scenarios should be addressed under different uncertainties such as climate variability.

Decision making by relatives about brain death organ donation: an integrative review.

PubMed

de Groot, Jack; Vernooij-Dassen, Myrra; Hoedemaekers, Cornelia; Hoitsma, Andries; Smeets, Wim; van Leeuwen, Evert

2012-06-27

Deciding about the organ donation of one's brain-dead beloved often occurs in an unexpected and delicate situation. We explored the decision making of the relatives of potential brain-dead donors, its evaluation, and the factors influencing decision making. We used the integrative review method. Our search included 10 databases. Inclusion criteria were presence of the donation request or the subsequent decision process. Three authors independently assessed the eligibility of identified articles. Content analysis of 70 included articles led to three themes: decision, evaluation, and support. We extracted results and recommendations concerning these three themes. The timing of the request and understandable information influence the decision. The relatives evaluate their decision differently: in case of refusal, approximately one third regret their decision, and in case of consent, approximately one tenth mention regret. The relatives are often ambivalent about their values (protection, altruism, and respect) and the deceased's wishes, not wanting additional suffering either for their beloved or for themselves. Support is mainly focused on increasing consent rates and less on satisfaction with the decision. Evaluation of decision making by the relatives of potential brain-dead donors reveals possibilities for improving the decision process. Special skills of the requester, attention to the circumstances, and unconditional support for the relatives might prevent the relatives' regret about refusal and unnecessary loss of organs. We hypothesize that support in exploring the relatives' values and the deceased's wishes can lead to stable decisions. This hypothesis deserves further investigation.

A GIS-based decision support system for regional eco-security assessment and its application on the Tibetan Plateau.

PubMed

Xiaodan, Wang; Xianghao, Zhong; Pan, Gao

2010-10-01

Regional eco-security assessment is an intricate, challenging task. In previous studies, the integration of eco-environmental models and geographical information systems (GIS) usually takes two approaches: loose coupling and tight coupling. However, the present study used a full coupling approach to develop a GIS-based regional eco-security assessment decision support system (ESDSS). This was achieved by merging the pressure-state-response (PSR) model and the analytic hierarchy process (AHP) into ArcGIS 9 as a dynamic link library (DLL) using ArcObjects in ArcGIS and Visual Basic for Applications. Such an approach makes it easy to capitalize on the GIS visualization and spatial analysis functions, thereby significantly supporting the dynamic estimation of regional eco-security. A case study is presented for the Tibetan Plateau, known as the world's "third pole" after the Arctic and Antarctic. Results verified the usefulness and feasibility of the developed method. As a useful tool, the ESDSS can also help local managers to make scientifically-based and effective decisions about Tibetan eco-environmental protection and land use. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

An integrated decision support system for TRAC: A proposal

NASA Technical Reports Server (NTRS)

Mukkamala, Ravi

1991-01-01

Optimal allocation and usage of resources is a key to effective management. Resources of concern to TRAC are: Manpower (PSY), Money (Travel, contracts), Computing, Data, Models, etc. Management activities of TRAC include: Planning, Programming, Tasking, Monitoring, Updating, and Coordinating. Existing systems are insufficient, not completely automated, manpower intensive, and has the potential for data inconsistency exists. A system is proposed which suggests a means to integrate all project management activities of TRAC through the development of a sophisticated software and by utilizing the existing computing systems and network resources. The systems integration proposal is examined in detail.

Personalization and Patient Involvement in Decision Support Systems: Current Trends

PubMed Central

Sacchi, L.; Lanzola, G.; Viani, N.

2015-01-01

Summary Objectives This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care. Methods We considered papers published on scientific journals, by querying PubMed and Web of Science™. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. Results We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness. Conclusions Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large. PMID:26293857

Iterative integral parameter identification of a respiratory mechanics model.

PubMed

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

Management System Design for a Learner Centered School.

ERIC Educational Resources Information Center

Wagner, Kathleen

2000-01-01

Examines how a learner-centered Montessori school in Toronto, Ontario, defines, specifies, and implements its management decision-support system. Findings indicate a tightly integrated management system comprised of a few student-focused decision-support elements. Identifies relationships, resources, and particular organizational arrangements as…

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

ERIC Educational Resources Information Center

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

2016-01-01

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

SimBasin: serious gaming for integrated decision-making in the Magdalena-Cauca basin

NASA Astrophysics Data System (ADS)

Craven, Joanne; Angarita, Hector; Corzo, Gerald

2016-04-01

The Magdalena-Cauca macrobasin covers 24% of the land area of Colombia, and provides more than half of the country's economic potential. The basin is also home a large proportion of Colombia's biodiversity. These conflicting demands have led to problems in the basin, including a dramatic fall in fish populations, additional flooding (such as the severe nationwide floods caused by the La Niña phenomenon in 2011), and habitat loss. It is generally believed that the solution to these conflicts is to manage the basin in a more integrated way, and bridge the gaps between decision-makers in different sectors and scientists. To this end, inter-ministerial agreements are being formulated and a decision support system is being developed by The Nature Conservancy Colombia. To engage stakeholders in this process SimBasin, a "serious game", has been developed. It is intended to act as a catalyst for bringing stakeholders together, an illustration of the uncertainties, relationships and feedbacks in the basin, and an accessible introduction to modelling and decision support for non-experts. During the game, groups of participants are led through a 30 year future development of the basin, during which they take decisions about the development of the basin and see the impacts on four different sectors: agriculture, hydropower, flood risk, and environment. These impacts are displayed through seven indicators, which players should try to maintain above critical thresholds. To communicate the effects of uncertainty and climate variability, players see the actual value of the indicator and also a band of possible values, so they can see if their decisions have actually reduced risk or if they just "got lucky". The game works as a layer on top of a WEAP water resources model of the basin, adapted from a basin-wide model already created, so the fictional game basin is conceptually similar to the Magdalena-Cauca basin. The game is freely available online, and new applications are being discussed, such as using the game in planning processes and to engage local communities. The game has been beta tested at a modelling workshop in Bangkok and was then used as the basis of a national basin management forum in Bogotá. 42 high-level stakeholders attended and the session generated a great deal of interest in the decision support system, and served as a nucleus for different stakeholders to discuss ideas. The study discusses the development of the game and observations from these sessions. More information: http://simbasin.hilab.nl

SymptomCare@Home: Developing an Integrated Symptom Monitoring and Management System for Outpatients Receiving Chemotherapy.

PubMed

Beck, Susan L; Eaton, Linda H; Echeverria, Christina; Mooney, Kathi H

2017-10-01

SymptomCare@Home, an integrated symptom monitoring and management system, was designed as part of randomized clinical trials to help patients with cancer who receive chemotherapy in ambulatory clinics and often experience significant symptoms at home. An iterative design process was informed by chronic disease management theory and features of assessment and clinical decision support systems used in other diseases. Key stakeholders participated in the design process: nurse scientists, clinical experts, bioinformatics experts, and computer programmers. Especially important was input from end users, patients, and nurse practitioners participating in a series of studies testing the system. The system includes both a patient and clinician interface and fully integrates two electronic subsystems: a telephone computer-linked interactive voice response system and a Web-based Decision Support-Symptom Management System. Key features include (1) daily symptom monitoring, (2) self-management coaching, (3) alerting, and (4) nurse practitioner follow-up. The nurse practitioner is distinctively positioned to provide assessment, education, support, and pharmacologic and nonpharmacologic interventions to intensify management of poorly controlled symptoms at home. SymptomCare@Home is a model for providing telehealth. The system facilitates using evidence-based guidelines as part of a comprehensive symptom management approach. The design process and system features can be applied to other diseases and conditions.

Knowledge Integration to Make Decisions About Complex Systems: Sustainability of Energy Production from Agriculture

ScienceCinema

Danuso, Francesco

2017-12-22

A major bottleneck for improving the governance of complex systems, rely on our ability to integrate different forms of knowledge into a decision support system (DSS). Preliminary aspects are the classification of different types of knowledge (a priori or general, a posteriori or specific, with uncertainty, numerical, textual, algorithmic, complete/incomplete, etc.), the definition of ontologies for knowledge management and the availability of proper tools like continuous simulation models, event driven models, statistical approaches, computational methods (neural networks, evolutionary optimization, rule based systems etc.) and procedure for textual documentation. Following these views at University of Udine, a computer language (SEMoLa, Simple, Easy Modelling Language) for knowledge integration has been developed.  SEMoLa can handle models, data, metadata and textual knowledge; it implements and extends the system dynamics ontology (Forrester, 1968; Jørgensen, 1994) in which systems are modelled by the concepts of material, group, state, rate, parameter, internal and external events and driving variables. As an example, a SEMoLa model to improve management and sustainability (economical, energetic, environmental) of the agricultural farms is presented. The model (X-Farm) simulates a farm in which cereal and forage yield, oil seeds, milk, calves and wastes can be sold or reused. X-Farm is composed by integrated modules describing fields (crop and soil), feeds and materials storage, machinery management, manpower  management, animal husbandry, economic and energetic balances, seed oil extraction, manure and wastes management, biogas production from animal wastes and biomasses.

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

The dynamics of decision making in risky choice: an eye-tracking analysis.

PubMed

Fiedler, Susann; Glöckner, Andreas

2012-01-01

In the last years, research on risky choice has moved beyond analyzing choices only. Models have been suggested that aim to describe the underlying cognitive processes and some studies have tested process predictions of these models. Prominent approaches are evidence accumulation models such as decision field theory (DFT), simple serial heuristic models such as the adaptive toolbox, and connectionist approaches such as the parallel constraint satisfaction (PCS) model. In two studies involving measures of attention and pupil dilation, we investigate hypotheses derived from these models in choices between two gambles with two outcomes each. We show that attention to an outcome of a gamble increases with its probability and its value and that attention shifts toward the subsequently favored gamble after about two thirds of the decision process, indicating a gaze-cascade effect. Information search occurs mostly within-gambles, and the direction of search does not change over the course of decision making. Pupil dilation, which reflects both cognitive effort and arousal, increases during the decision process and increases with mean expected value. Overall, the results support aspects of automatic integration models for risky choice such as DFT and PCS, but in their current specification none of them can account for the full pattern of results.

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

USGS Publications Warehouse

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

2014-01-01

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

Integrating Social Media and Mobile Sensor Data for Clinical Decision Support: Concept and Requirements.

PubMed

Denecke, Kerstin

2016-01-01

Social media are increasingly used by individuals for the purpose of collecting data and reporting on the personal health status, on health issues, symptoms and experiences with treatments. Beyond, fitness trackers are more used by individuals to monitor their fitness and health. The health data that is becoming available due to these developments could provide a valuable source for continuous health monitoring, prevention of unexpected health events and clinical decision making since it gives insights into behavior and life habits. However, an integration of the data is challenging. This paper aims triggering the discussion about this current topic. We present a concept for integrating social media data with mobile sensor data and clinical data using digital patient modelling. Further, we collect requirements and challenges for a possible realization of the concept. Challenges include the data volume, reliability and semantic interoperability.

Building place-based collaborations to develop high school students' groundwater systems knowledge and decision-making capacity

NASA Astrophysics Data System (ADS)

Podrasky, A.; Covitt, B. A.; Woessner, W.

2017-12-01

The availability of clean water to support human uses and ecological integrity has become an urgent interest for many scientists, decision makers and citizens. Likewise, as computational capabilities increasingly revolutionize and become integral to the practice of science, technology, engineering and math (STEM) disciplines, the STEM+ Computing (STEM+C) Partnerships program seeks to integrate the use of computational approaches in K-12 STEM teaching and learning. The Comp Hydro project, funded by a STEM+C grant from the National Science Foundation, brings together a diverse team of scientists, educators, professionals and citizens at sites in Arizona, Colorado, Maryland and Montana to foster water literacy, as well as computational science literacy, by integrating authentic, place- and data- based learning using physical, mathematical, computational and conceptual models. This multi-state project is currently engaging four teams of six teachers who work during two academic years with educators and scientists at each site. Teams work to develop instructional units specific to their region that integrate hydrologic science and computational modeling. The units, currently being piloted in high school earth and environmental science classes, provide a classroom context to investigate student understanding of how computation is used in Earth systems science. To develop effective science instruction that is rich in place- and data- based learning, effective collaborations between researchers, educators, scientists, professionals and citizens are crucial. In this poster, we focus on project implementation in Montana, where an instructional unit has been developed and is being tested through collaboration among University scientists, researchers and educators, high school teachers and agency and industry scientists and engineers. In particular, we discuss three characteristics of effective collaborative science education design for developing and implementing place- and data- based science education to support students in developing socio-scientific and computational literacy sufficient for making decisions about real world issues such as groundwater contamination. These characteristics include that science education experiences are real, responsive/accessible and rigorous.

Integrated Water Resources Planning and Management in Arid/Semi-arid Regions: Data, Modeling, and Assessment

NASA Astrophysics Data System (ADS)

Gupta, H.; Liu, Y.; Wagener, T.; Durcik, M.; Duffy, C.; Springer, E.

2005-12-01

Water resources in arid and semi-arid regions are highly sensitive to climate variability and change. As the demand for water continues to increase due to economic and population growth, planning and management of available water resources under climate uncertainties becomes increasingly critical in order to achieve basin-scale water sustainability (i.e., to ensure a long-term balance between supply and demand of water).The tremendous complexity of the interactions between the natural hydrologic system and the human environment means that modeling is the only available mechanism for properly integrating new knowledge into the decision-making process. Basin-scale integrated models have the potential to allow us to study the feedback processes between the physical and human systems (including institutional, engineering, and behavioral components); and an integrated assessment of the potential second- and higher-order effects of political and management decisions can aid in the selection of a rational water-resources policy. Data and information, especially hydrological and water-use data, are critical to the integrated modeling and assessment for water resources management of any region. To this end we are in the process of developing a multi-resolution integrated modeling and assessment framework for the south-western USA, which can be used to generate simulations of the probable effects of human actions while taking into account the uncertainties brought about by future climatic variability and change. Data are being collected (including the development of a hydro-geospatial database) and used in support of the modeling and assessment activities. This paper will present a blueprint of the modeling framework, describe achievements so far and discuss the science questions which still require answers with a particular emphasis on issues related to dry regions.

Testing Multi-Alternative Decision Models with Non-Stationary Evidence

PubMed Central

Tsetsos, Konstantinos; Usher, Marius; McClelland, James L.

2011-01-01

Recent research has investigated the process of integrating perceptual evidence toward a decision, converging on a number of sequential sampling choice models, such as variants of race and diffusion models and the non-linear leaky competing accumulator (LCA) model. Here we study extensions of these models to multi-alternative choice, considering how well they can account for data from a psychophysical experiment in which the evidence supporting each of the alternatives changes dynamically during the trial, in a way that creates temporal correlations. We find that participants exhibit a tendency to choose an alternative whose evidence profile is temporally anti-correlated with (or dissimilar from) that of other alternatives. This advantage of the anti-correlated alternative is well accounted for in the LCA, and provides constraints that challenge several other models of multi-alternative choice. PMID:21603227

Testing multi-alternative decision models with non-stationary evidence.

PubMed

Tsetsos, Konstantinos; Usher, Marius; McClelland, James L

2011-01-01

Recent research has investigated the process of integrating perceptual evidence toward a decision, converging on a number of sequential sampling choice models, such as variants of race and diffusion models and the non-linear leaky competing accumulator (LCA) model. Here we study extensions of these models to multi-alternative choice, considering how well they can account for data from a psychophysical experiment in which the evidence supporting each of the alternatives changes dynamically during the trial, in a way that creates temporal correlations. We find that participants exhibit a tendency to choose an alternative whose evidence profile is temporally anti-correlated with (or dissimilar from) that of other alternatives. This advantage of the anti-correlated alternative is well accounted for in the LCA, and provides constraints that challenge several other models of multi-alternative choice.

Content-specific evidence accumulation in inferior temporal cortex during perceptual decision-making

PubMed Central

Tremel, Joshua J.; Wheeler, Mark E.

2015-01-01

During a perceptual decision, neuronal activity can change as a function of time-integrated evidence. Such neurons may serve as decision variables, signaling a choice when activity reaches a boundary. Because the signals occur on a millisecond timescale, translating to human decision-making using functional neuroimaging has been challenging. Previous neuroimaging work in humans has identified patterns of neural activity consistent with an accumulation account. However, the degree to which the accumulating neuroimaging signals reflect specific sources of perceptual evidence is unknown. Using an extended face/house discrimination task in conjunction with cognitive modeling, we tested whether accumulation signals, as measured using functional magnetic resonance imaging (fMRI), are stimulus-specific. Accumulation signals were defined as a change in the slope of the rising edge of activation corresponding with response time (RT), with higher slopes associated with faster RTs. Consistent with an accumulation account, fMRI activity in face- and house-selective regions in the inferior temporal cortex increased at a rate proportional to decision time in favor of the preferred stimulus. This finding indicates that stimulus-specific regions perform an evidence integrative function during goal-directed behavior and that different sources of evidence accumulate separately. We also assessed the decision-related function of other regions throughout the brain and found that several regions were consistent with classifications from prior work, suggesting a degree of domain generality in decision processing. Taken together, these results provide support for an integration-to-boundary decision mechanism and highlight possible roles of both domain-specific and domain-general regions in decision evidence evaluation. PMID:25562821

Comprehensive process model of clinical information interaction in primary care: results of a "best-fit" framework synthesis.

PubMed

Veinot, Tiffany C; Senteio, Charles R; Hanauer, David; Lowery, Julie C

2018-06-01

To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research. We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research. The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process. The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations. The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.

Success matters: Recasting the relationship among geophysical, biological, and behavioral scientists to support decision making on major environmental challenges

NASA Astrophysics Data System (ADS)

Knopman, Debra S.

2006-03-01

Coping with global change, providing clean water for growing populations, and disposing of nuclear waste are some of the most difficult public policy challenges of our time. Unknowns in the physical sciences are one source of the difficulty. Real difficulties in meeting these challenges also arise in the behavioral sciences. A potentially rich vein of transdisciplinary research is to integrate the psychology of decision making, known as "judgment and decision making," or JDM, with the development of technical information and decision support tools for complex, long-term environmental problems. Practitioners of JDM conduct research on how individuals and groups respond to uncertainty and ambiguity, hedge against risks, anchor decisions to the status quo, compare relative risks and rewards of alternative strategies, and cope with other classes of decisions. Practitioners use a variety of stimuli, chance devices, hypothetical and real choices involving small stakes, scenarios, and questionnaires to measure (directly and indirectly) preferences under varying conditions. These kinds of experiments can help guide choices about the level of complexity required for different types of decision-making processes, the value of new data collection efforts, and the ways in which uncertainty in model outcomes can be cast to minimize decision-making paralysis. They can also provide a scientific basis for interacting with decision makers throughout the model development process, designing better ways of eliciting and combining opinions and of communicating information relevant to public policy issues with the goal of improving the value of the scientific contribution to the social decision.

Integrated Drought Monitoring and Forecasts for Decision Making in Water and Agricultural Sectors over the Southeastern US under Changing Climate

NASA Astrophysics Data System (ADS)

Arumugam, S.; Mazrooei, A.; Ward, R.

2017-12-01

Changing climate arising from structured oscillations such as ENSO and rising temperature poses challenging issues in meeting the increasing water demand (due to population growth) for public supply and agriculture over the Southeast US. This together with infrastructural (e.g., most reservoirs being within-year systems) and operational (e.g., static rule curves) constraints requires an integrated approach that seamlessly monitors and forecasts water and soil moisture conditions to support adaptive decision making in water and agricultural sectors. In this talk, we discuss the utility of an integrated drought management portal that both monitors and forecasts streamflow and soil moisture over the southeast US. The forecasts are continuously developed and updated by forcing monthly-to-seasonal climate forecasts with a land surface model for various target basins. The portal also houses a reservoir allocation model that allows water managers to explore different release policies in meeting the system constraints and target storages conditioned on the forecasts. The talk will also demonstrate how past events (e.g., 2007-2008 drought) could be proactively monitored and managed to improve decision making in water and agricultural sectors over the Southeast US. Challenges in utilizing the portal information from institutional and operational perspectives will also be presented.

Integration of the Response Surface Methodology with the Compromise Decision Support Problem in Developing a General Robust Design Procedure

NASA Technical Reports Server (NTRS)

Chen, Wei; Tsui, Kwok-Leung; Allen, Janet K.; Mistree, Farrokh

1994-01-01

In this paper we introduce a comprehensive and rigorous robust design procedure to overcome some limitations of the current approaches. A comprehensive approach is general enough to model the two major types of robust design applications, namely, robust design associated with the minimization of the deviation of performance caused by the deviation of noise factors (uncontrollable parameters), and robust design due to the minimization of the deviation of performance caused by the deviation of control factors (design variables). We achieve mathematical rigor by using, as a foundation, principles from the design of experiments and optimization. Specifically, we integrate the Response Surface Method (RSM) with the compromise Decision Support Problem (DSP). Our approach is especially useful for design problems where there are no closed-form solutions and system performance is computationally expensive to evaluate. The design of a solar powered irrigation system is used as an example. Our focus in this paper is on illustrating our approach rather than on the results per se.

Preparing for a decision support system.

PubMed

Callan, K

2000-08-01

The increasing pressure to reduce costs and improve outcomes is driving the health care industry to view information as a competitive advantage. Timely information is required to help reduce inefficiencies and improve patient care. Numerous disparate operational or transactional information systems with inconsistent and often conflicting data are no longer adequate to meet the information needs of integrated care delivery systems and networks in competitive managed care environments. This article reviews decision support system characteristics and describes a process to assess the preparedness of an organization to implement and use decision support systems to achieve a more effective, information-based decision process. Decision support tools included in this article range from reports to data mining.

Automation and decision support in interactive consumer products.

PubMed

Sauer, J; Rüttinger, B

2007-06-01

This article presents two empirical studies (n = 30, n = 48) that are concerned with different forms of automation in interactive consumer products. The goal of the studies was to evaluate the effectiveness of two types of automation: perceptual augmentation (i.e. supporting users' information acquisition and analysis); and control integration (i.e. supporting users' action selection and implementation). Furthermore, the effectiveness of on-product information (i.e. labels attached to product) in supporting automation design was evaluated. The findings suggested greater benefits for automation in control integration than in perceptual augmentation alone, which may be partly due to the specific requirements of consumer product usage. If employed appropriately, on-product information can be a helpful means of information conveyance. The article discusses the implications of automation design in interactive consumer products while drawing on automation models from the work environment.

Integrating environmental monitoring with cumulative effects management and decision making.

PubMed

Cronmiller, Joshua G; Noble, Bram F

2018-05-01

Cumulative effects (CE) monitoring is foundational to emerging regional and watershed CE management frameworks, yet monitoring is often poorly integrated with CE management and decision-making processes. The challenges are largely institutional and organizational, more so than scientific or technical. Calls for improved integration of monitoring with CE management and decision making are not new, but there has been limited research on how best to integrate environmental monitoring programs to ensure credible CE science and to deliver results that respond to the more immediate questions and needs of regulatory decision makers. This paper examines options for the integration of environmental monitoring with CE frameworks. Based on semistructured interviews with practitioners, regulators, and other experts in the Lower Athabasca, Alberta, Canada, 3 approaches to monitoring system design are presented. First, a distributed monitoring system, reflecting the current approach in the Lower Athabasca, where monitoring is delegated to different external programs and organizations; second, a 1-window system in which monitoring is undertaken by a single, in-house agency for the purpose of informing management and regulatory decision making; third, an independent system driven primarily by CE science and understanding causal relationships, with knowledge adopted for decision support where relevant to specific management questions. The strengths and limitations of each approach are presented. A hybrid approach may be optimal-an independent, nongovernment, 1-window model for CE science, monitoring, and information delivery-capitalizing on the strengths of distributed, 1-window, and independent monitoring systems while mitigating their weaknesses. If governments are committed to solving CE problems, they must invest in the long-term science needed to do so; at the same time, if science-based monitoring programs are to be sustainable over the long term, they must be responsive to the more immediate, often shorter term needs and CE information requirements of decision makers. Integr Environ Assess Manag 2018;14:407-417. © 2018 SETAC. © 2018 SETAC.

Information Product Development: Data product life cycle links engineering, science, and applications

NASA Astrophysics Data System (ADS)

Stavros, E. N.; Owen, S. E.

2016-12-01

Information products are assimilated and used to: a) conduct scientific research and b) provide decision support for management and policy. For example, aboveground biomass (i.e. an information product) can be integrated into Earth system models to test hypotheses about the changing world, or used to inform decision-making with respect to natural resource management and policy. Production and dissemination of an information product is referred to as the data product life cycle, which includes: 1) identifying needed information from decision-makers and researchers, 2) engineering an instrument and collecting the raw physical measurements (e.g, number of photons returned), 3) the scientific algorithm(s) for processing the data into an observable (e.g., number of dying trees), and 4) the integration and utilization of that observables by researchers and decision-makers. In this talk, I will discuss the data product life cycle in detail and provide examples from the pre-Hyperspectral Infrared Imager (HyspIRI) airborne campaign and the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR) mission. Examples will focus on information products related to terrestrial ecosystems and natural resource management and will demonstrate that the key to providing information products for advancing scientific understanding and informing decision-makers, is the interdisciplinary integration of science, engineering and applied science - noting that applied science defines the wider impact and adoption of scientific principles by a wider community. As pre-HyspIRI airborne data is for research and development and NISAR is not yet launched, examples will include current plans for developing exemplar data products (from pre-HyspIRI) and the mission Applications Plan (for NISAR). Copyright 2016 California Institute of Technology. All Rights Reserved. We acknowledge support of the US Government, NASA, the Earth Science Division and Terrestrial Ecology program.

DATA COLLECTION MANAGER MODULE OF REGION III'S MULTI-CRITERIA INTEGRATED RESOURCE ASSESSMENT (MIRA) ENVIRONMENTAL DECISION MAKING APPROACH

EPA Science Inventory

This proposal pertains to the on-going development of the Data Collection Manager (DCM) module, which is one of three modules that compose MIRA, Multi-criteria Integrated Resource Assessment. MIRA is Region III's newly conceived and continually developing decision support approac...

Overcoming Indecision by Changing the Decision Boundary

PubMed Central

2017-01-01

The dominant theoretical framework for decision making asserts that people make decisions by integrating noisy evidence to a threshold. It has recently been shown that in many ecologically realistic situations, decreasing the decision boundary maximizes the reward available from decisions. However, empirical support for decreasing boundaries in humans is scant. To investigate this problem, we used an ideal observer model to identify the conditions under which participants should change their decision boundaries with time to maximize reward rate. We conducted 6 expanded-judgment experiments that precisely matched the assumptions of this theoretical model. In this paradigm, participants could sample noisy, binary evidence presented sequentially. Blocks of trials were fixed in duration, and each trial was an independent reward opportunity. Participants therefore had to trade off speed (getting as many rewards as possible) against accuracy (sampling more evidence). Having access to the actual evidence samples experienced by participants enabled us to infer the slope of the decision boundary. We found that participants indeed modulated the slope of the decision boundary in the direction predicted by the ideal observer model, although we also observed systematic deviations from optimality. Participants using suboptimal boundaries do so in a robust manner, so that any error in their boundary setting is relatively inexpensive. The use of a normative model provides insight into what variable(s) human decision makers are trying to optimize. Furthermore, this normative model allowed us to choose diagnostic experiments and in doing so we present clear evidence for time-varying boundaries. PMID:28406682

Advancing Alternative Analysis: Integration of Decision Science.

PubMed

Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina M; Blake, Ann; Carroll, William F; Corbett, Charles J; Hansen, Steffen Foss; Lempert, Robert J; Linkov, Igor; McFadden, Roger; Moran, Kelly D; Olivetti, Elsa; Ostrom, Nancy K; Romero, Michelle; Schoenung, Julie M; Seager, Thomas P; Sinsheimer, Peter; Thayer, Kristina A

2017-06-13

Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings. We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. We advance four recommendations: a ) engaging the systematic development and evaluation of decision approaches and tools; b ) using case studies to advance the integration of decision analysis into alternatives analysis; c ) supporting transdisciplinary research; and d ) supporting education and outreach efforts. https://doi.org/10.1289/EHP483.

Advancing Alternative Analysis: Integration of Decision Science

PubMed Central

Zaunbrecher, Virginia M.; Batteate, Christina M.; Blake, Ann; Carroll, William F.; Corbett, Charles J.; Hansen, Steffen Foss; Lempert, Robert J.; Linkov, Igor; McFadden, Roger; Moran, Kelly D.; Olivetti, Elsa; Ostrom, Nancy K.; Romero, Michelle; Schoenung, Julie M.; Seager, Thomas P.; Sinsheimer, Peter; Thayer, Kristina A.

2017-01-01

Background: Decision analysis—a systematic approach to solving complex problems—offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. Objectives: We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. Methods: A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups’ findings. Results: We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. Conclusions: We advance four recommendations: a) engaging the systematic development and evaluation of decision approaches and tools; b) using case studies to advance the integration of decision analysis into alternatives analysis; c) supporting transdisciplinary research; and d) supporting education and outreach efforts. https://doi.org/10.1289/EHP483 PMID:28669940

REMOTE SENSING, VISUALIZATION AND DECISION SUPPORT FOR WATERSHED MANAGEMENT AND SUSTAINABLE AGRICULTURE

EPA Science Inventory

The integration of satellite and airborne remote sensing, scientific visualization and decision support tools is discussed within the context of management techniques for minimizing the non-point source pollution load of inland waterways and the sustainability of food crop produc...

“Smart Forms” in an Electronic Medical Record: Documentation-based Clinical Decision Support to Improve Disease Management

PubMed Central

Schnipper, Jeffrey L.; Linder, Jeffrey A.; Palchuk, Matvey B.; Einbinder, Jonathan S.; Li, Qi; Postilnik, Anatoly; Middleton, Blackford

2008-01-01

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing “Smart Forms” to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions. PMID:18436911

"Smart Forms" in an Electronic Medical Record: documentation-based clinical decision support to improve disease management.

PubMed

Schnipper, Jeffrey L; Linder, Jeffrey A; Palchuk, Matvey B; Einbinder, Jonathan S; Li, Qi; Postilnik, Anatoly; Middleton, Blackford

2008-01-01

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing "Smart Forms" to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions.

Development of a case tool to support decision based software development

NASA Technical Reports Server (NTRS)

Wild, Christian J.

1993-01-01

A summary of the accomplishments of the research over the past year are presented. Achievements include: made demonstrations with DHC, a prototype supporting decision based software development (DBSD) methodology, for Paramax personnel at ODU; met with Paramax personnel to discuss DBSD issues, the process of integrating DBSD and Refinery and the porting process model; completed and submitted a paper describing DBSD paradigm to IFIP '92; completed and presented a paper describing the approach for software reuse at the Software Reuse Workshop in April 1993; continued to extend DHC with a project agenda, facility necessary for a better project management; completed a primary draft of the re-engineering process model for porting; created a logging form to trace all the activities involved in the process of solving the reengineering problem, and developed a primary chart with the problems involved by the reengineering process.

Integrating complex business processes for knowledge-driven clinical decision support systems.

PubMed

Kamaleswaran, Rishikesan; McGregor, Carolyn

2012-01-01

This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

Integrated Decision Support, Sensor Networks and Adaptive Control for Wireless Site-specific Sprinkler Irrigation

USDA-ARS?s Scientific Manuscript database

The development of site-specific sprinkler irrigation water management systems will be a major factor in future efforts to improve the various efficiencies of water-use and to support a sustainable irrigated environment. The challenge is to develop fully integrated management systems with supporting...

Integrated decision support, sensor networks and adaptive control for wireless site-specific sprinkler irrigation

USDA-ARS?s Scientific Manuscript database

The development of site-specific sprinkler irrigation water management systems will be a major factor in future efforts to improve the various efficiencies of water-use and to support a sustainable irrigated environment. The challenge is to develop fully integrated management systems with supporting...

From guideline modeling to guideline execution: defining guideline-based decision-support services.

PubMed Central

Tu, S. W.; Musen, M. A.

2000-01-01

We describe our task-based approach to defining the guideline-based decision-support services that the EON system provides. We categorize uses of guidelines in patient-specific decision support into a set of generic tasks--making of decisions, specification of work to be performed, interpretation of data, setting of goals, and issuance of alert and reminders--that can be solved using various techniques. Our model includes constructs required for representing the knowledge used by these techniques. These constructs form a toolkit from which developers can select modeling solutions for guideline task. Based on the tasks and the guideline model, we define a guideline-execution architecture and a model of interactions between a decision-support server and clients that invoke services provided by the server. These services use generic interfaces derived from guideline tasks and their associated modeling constructs. We describe two implementations of these decision-support services and discuss how this work can be generalized. We argue that a well-defined specification of guideline-based decision-support services will facilitate sharing of tools that implement computable clinical guidelines. PMID:11080007

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

PubMed

Wolf, Lisa

2013-02-01

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

Integrated Forecast-Decision Systems For River Basin Planning and Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.

2005-12-01

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

Modifications and integration of the electronic tracking board in a pediatric emergency department.

PubMed

Dexheimer, Judith W; Kennebeck, Stephanie

2013-07-01

Electronic health records (EHRs) are used for data storage; provider, laboratory, and patient communication; clinical decision support; procedure and medication orders; and decision support alerts. Clinical decision support is part of any EHR and is designed to help providers make better decisions. The emergency department (ED) poses a unique environment to the use of EHRs and clinical decision support. Used effectively, computerized tracking boards can help improve flow, communication, and the dissemination of pertinent visit information between providers and other departments in a busy ED. We discuss the unique modifications and decisions made in the implementation of an EHR and computerized tracking board in a pediatric ED. We discuss the changing views based on provider roles, customization to the user interface including the layout and colors, decision support, tracking board best practices collected from other institutions and colleagues, and a case study of using reminders on the electronic tracking board to drive pain reassessments.

A cyber-enabled spatial decision support system to inventory Mangroves in Mozambique: coupling scientific workflows and cloud computing

Treesearch

Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Christina E. Stringer; Carl C. Trettin

2017-01-01

Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for...

Dynamics and resilience in interdependent systems at the energy-water-land nexus

NASA Astrophysics Data System (ADS)

Moss, R. H.

2017-12-01

Water resources management is already complex enough, given fragmented landscapes and institutions and uncertain climate and environmental conditions. But given the interdependence of water, energy, and land systems (the "energy-water-land nexus"), integrated approaches to cross-sectoral modeling and decision making that account for the interdependencies are increasingly important. This presentation will describe the context of the broader institutional and policy dimensions (e.g., cross-Federal research agencies) and scientific challenges of bringing the water, energy, and land research communities together (e.g., different epistemologies, data, modeling, and decision support methods). The speaker will describe efforts to develop a shared community of practice to improve research collaboration and provide insights on coupled system resilience.

An integrated Riverine Environmental Flow Decision Support System (REFDSS) to evaluate the ecological effects of alternative flow scenarios on river ecosystems

USGS Publications Warehouse

Maloney, Kelly O.; Talbert, Colin B.; Cole, Jeffrey C.; Galbraith, Heather S.; Blakeslee, Carrie J.; Hanson, Leanne; Holmquist-Johnson, Christopher L.

2015-01-01

In regulated rivers, managers must evaluate competing flow release scenarios that attempt to balance both human and natural needs. Meeting these natural flow needs is complex due to the myriad of interacting physical and hydrological factors that affect ecosystems. Tools that synthesize the voluminous scientific data and models on these factors will facilitate management of these systems. Here, we present the Riverine Environmental Flow Decision Support System (REFDSS), a tool that enables evaluation of competing flow scenarios and other variables on instream habitat. We developed a REFDSS for the Upper Delaware River, USA, a system that is regulated by three headwater reservoirs. This version of the REFDSS has the ability to integrate any set of spatially explicit data and synthesizes modeled discharge for three competing management scenarios, flow-specific 2-D hydrodynamic modeled estimates of local hydrologic conditions (e.g., depth, velocity, shear stress, etc.) at a fine pixel-scale (1 m2), and habitat suitability criteria (HSC) for a variety of taxa. It contains all individual model outputs, computationally integrates these data, and outputs the amount of potentially available habitat for a suite of species of interest under each flow release scenario. Users have the flexibility to change the time period of interest and vary the HSC. The REFDSS was developed to enable side-by-side evaluation of different flow management scenarios and their effects on potential habitat availability, allowing managers to make informed decisions on the best flow scenarios. An exercise comparing two alternative flow scenarios to a baseline scenario for several key species is presented. The Upper Delaware REFDSS was robust to minor changes in HSC (± 10 %). The general REFDSS platform was developed as a user-friendly Windows desktop application that was designed to include other potential parameters of interest (e.g., temperature) and for transferability to other riverine systems.

Integrating Personalized and Community Services for Mobile Travel Planning and Management

NASA Astrophysics Data System (ADS)

Yu, Chien-Chih

Personalized and community services have been noted as keys to enhance and facilitate e-tourism as well as mobile applications. This paper aims at proposing an integrated service framework for combining personalized and community functions to support mobile travel planning and management. Major mobile tourism related planning and decision support functions specified include personalized profile management, information search and notification, evaluation and recommendation, do-it-yourself planning and design, community and collaboration management, auction and negotiation, transaction and payment, as well as trip tracking and quality control. A system implementation process with an example prototype is also presented for illustrating the feasibility and effectiveness of the proposed system framework, process model, and development methodology.

A model of interval timing by neural integration.

PubMed

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

Analysis of the process of representing clinical statements for decision-support applications: a comparison of openEHR archetypes and HL7 virtual medical record.

PubMed

González-Ferrer, A; Peleg, M; Marcos, M; Maldonado, J A

2016-07-01

Delivering patient-specific decision-support based on computer-interpretable guidelines (CIGs) requires mapping CIG clinical statements (data items, clinical recommendations) into patients' data. This is most effectively done via intermediate data schemas, which enable querying the data according to the semantics of a shared standard intermediate schema. This study aims to evaluate the use of HL7 virtual medical record (vMR) and openEHR archetypes as intermediate schemas for capturing clinical statements from CIGs that are mappable to electronic health records (EHRs) containing patient data and patient-specific recommendations. Using qualitative research methods, we analyzed the encoding of ten representative clinical statements taken from two CIGs used in real decision-support systems into two health information models (openEHR archetypes and HL7 vMR instances) by four experienced informaticians. Discussion among the modelers about each case study example greatly increased our understanding of the capabilities of these standards, which we share in this educational paper. Differing in content and structure, the openEHR archetypes were found to contain a greater level of representational detail and structure while the vMR representations took fewer steps to complete. The use of openEHR in the encoding of CIG clinical statements could potentially facilitate applications other than decision-support, including intelligent data analysis and integration of additional properties of data items from existing EHRs. On the other hand, due to their smaller size and fewer details, the use of vMR potentially supports quicker mapping of EHR data into clinical statements.

Neural dynamics of social tie formation in economic decision-making.

PubMed

Bault, Nadège; Pelloux, Benjamin; Fahrenfort, Johannes J; Ridderinkhof, K Richard; van Winden, Frans

2015-06-01

The disposition for prosocial conduct, which contributes to cooperation as arising during social interaction, requires cortical network dynamics responsive to the development of social ties, or care about the interests of specific interaction partners. Here, we formulate a dynamic computational model that accurately predicted how tie formation, driven by the interaction history, influences decisions to contribute in a public good game. We used model-driven functional MRI to test the hypothesis that brain regions key to social interactions keep track of dynamics in tie strength. Activation in the medial prefrontal cortex (mPFC) and posterior cingulate cortex tracked the individual's public good contributions. Activation in the bilateral posterior superior temporal sulcus (pSTS), and temporo-parietal junction was modulated parametrically by the dynamically developing social tie-as estimated by our model-supporting a role of these regions in social tie formation. Activity in these two regions further reflected inter-individual differences in tie persistence and sensitivity to behavior of the interaction partner. Functional connectivity between pSTS and mPFC activations indicated that the representation of social ties is integrated in the decision process. These data reveal the brain mechanisms underlying the integration of interaction dynamics into a social tie representation which in turn influenced the individual's prosocial decisions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

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

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE PAGES

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith; ...

2017-11-06

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

ProVac Global Initiative: a vision shaped by ten years of supporting evidence-based policy decisions.

PubMed

Jauregui, Barbara; Janusz, Cara Bess; Clark, Andrew D; Sinha, Anushua; Garcia, Ana Gabriela Felix; Resch, Stephen; Toscano, Cristiana M; Sanderson, Colin; Andrus, Jon Kim

2015-05-07

The Pan American Health Organization (PAHO) created the ProVac Initiative in 2004 with the goal of strengthening national technical capacity to make evidence-based decisions on new vaccine introduction, focusing on economic evaluations. In view of the 10th anniversary of the ProVac Initiative, this article describes its progress and reflects on lessons learned to guide the next phase. We quantified the output of the Initiative's capacity-building efforts and critically assess its progress toward achieving the milestones originally proposed in 2004. Additionally, we reviewed how country studies supported by ProVac have directly informed and strengthened the deliberations around new vaccine introduction. Since 2004, ProVac has conducted four regional workshops and supported 24 health economic analyses in 15 Latin American and Caribbean countries. Five Regional Centers of Excellence were funded, resulting in six operational research projects and nine publications. Twenty four decisions on new vaccine introductions were supported with ProVac studies. Enduring products include the TRIVAC and CERVIVAC cost-effectiveness models, the COSTVAC program costing model, methodological guides, workshop training materials and the OLIVES on-line data repository. Ten NITAGs were strengthened through ProVac activities. The evidence accumulated suggests that initiatives with emphasis on sustainable training and direct support for countries to generate evidence themselves, can help accelerate the introduction of the most valuable new vaccines. International and Regional Networks of Collaborators are necessary to provide technical support and tools to national teams conducting analyses. Timeliness, integration, quality and country ownership of the process are four necessary guiding principles for national economic evaluations to have an impact on policymaking. It would be an asset to have a model that offers different levels of complexity to choose from depending on the vaccine being evaluated, the availability of data, and the time frame of the decision. Decision support for new vaccine introduction in low- and middle-income countries is critical to maximizing the efficiency and impact of vaccination programs. Global technical cooperation will be required. In the future, PAHO and WHO have an opportunity to expand the reach of the ProVac philosophy, models, and methods to additional regions and countries requiring real-time support. The ProVac Global Initiative is proposed as an effective mechanism to do so. Copyright © 2015. Published by Elsevier Ltd.

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

PubMed

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

2015-06-01

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

Bringing ecosystem services into integrated water resources management.

PubMed

Liu, Shuang; Crossman, Neville D; Nolan, Martin; Ghirmay, Hiyoba

2013-11-15

In this paper we propose an ecosystem service framework to support integrated water resource management and apply it to the Murray-Darling Basin in Australia. Water resources in the Murray-Darling Basin have been over-allocated for irrigation use with the consequent degradation of freshwater ecosystems. In line with integrated water resource management principles, Australian Government reforms are reducing the amount of water diverted for irrigation to improve ecosystem health. However, limited understanding of the broader benefits and trade-offs associated with reducing irrigation diversions has hampered the planning process supporting this reform. Ecosystem services offer an integrative framework to identify the broader benefits associated with integrated water resource management in the Murray-Darling Basin, thereby providing support for the Government to reform decision-making. We conducted a multi-criteria decision analysis for ranking regional potentials to provide ecosystem services at river basin scale. We surveyed the wider public about their understanding of, and priorities for, managing ecosystem services and then integrated the results with spatially explicit indicators of ecosystem service provision. The preliminary results of this work identified the sub-catchments with the greatest potential synergies and trade-offs of ecosystem service provision under the integrated water resources management reform process. With future development, our framework could be used as a decision support tool by those grappling with the challenge of the sustainable allocation of water between irrigation and the environment. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Decision Making in Rangelands: An Integrated Modeling Approach to Resilience and Change

NASA Astrophysics Data System (ADS)

Galvin, K. A.; Ojima, D. S.; Boone, R. B.

2007-12-01

Rangelands comprise approximately 25% of the earth's surface and these landscapes support more than 20 million people and most of the world's charismatic megafauna. Most of the people who live in these regions of the world herd domestic livestock and some do limited cultivation so they are dependent directly on the environment for their livelihoods. But change is rapidly changing the environments upon which these people depend through such factors as population pressures, land use and land tenure changes, climate variability, and policy changes which fragment their resources and thus their ability to earn a living. How can we understand change in this linked human-environment system? The study of complex biophysical and human systems can be greatly assisted by appropriate simulation models that integrate what is known about ecological and human decision-making processes. We have developed an integrated modeling system for Kajiado, Kenya where land use management decisions have implications for economics and the ecosystem. In this paper we look at how land use decisions, that is, livestock movement patterns have implications for societal economics and ecosystem services. Research that focuses on local behavior is important because it is at that level where fundamental decisions are made regarding events like extreme climate and changes such as land tenure policy and it is here where resilience is manifested. The notion that broad recommendation domains can be identified for a broad set of people and large regions coping with change is becoming increasingly hard to trust given the spatial and temporal heterogeneity of the systems we are looking at, and the complexity of the world we now live in. Why is this important? The only way the research community is going to make great progress in attaining objectives that do confer resilience (on social and ecological systems) is through much better targeting ability, a large part of which seem to be intimately entwined with understanding how make decisions are made at the local level.

Integrated Decision Strategies for Skin Sensitization Hazard

PubMed Central

Strickland, Judy; Zang, Qingda; Kleinstreuer, Nicole; Paris, Michael; Lehmann, David M.; Choksi, Neepa; Matheson, Joanna; Jacobs, Abigail; Lowit, Anna; Allen, David; Casey, Warren

2016-01-01

One of the top priorities of ICCVAM is the identification and evaluation of non-animal alternatives for skin sensitization testing. Although skin sensitization is a complex process, the key biological events of the process have been well characterized in an adverse outcome pathway (AOP) proposed by OECD. Accordingly, ICCVAM is working to develop integrated decision strategies based on the AOP using in vitro, in chemico, and in silico information. Data were compiled for 120 substances tested in the murine local lymph node assay (LLNA), direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT), and KeratinoSens assay. Data for six physicochemical properties that may affect skin penetration were also collected, and skin sensitization read-across predictions were performed using OECD QSAR Toolbox. All data were combined into a variety of potential integrated decision strategies to predict LLNA outcomes using a training set of 94 substances and an external test set of 26 substances. Fifty-four models were built using multiple combinations of machine learning approaches and predictor variables. The seven models with the highest accuracy (89–96% for the test set and 96–99% for the training set) for predicting LLNA outcomes used a support vector machine (SVM) approach with different combinations of predictor variables. The performance statistics of the SVM models were higher than any of the non-animal tests alone and higher than simple test battery approaches using these methods. These data suggest that computational approaches are promising tools to effectively integrate data sources to identify potential skin sensitizers without animal testing. PMID:26851134

Integration of Airborne Aerosol Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Sprigg, William A.; Huete, Alfredo; Pejanovic, Goran; Nickovic,Slobodan; Ponce-Campos, Guillermo; Krapfl, Heide; Budge, Amy; Zelicoff, Alan; VandeWater, Peter K.;

Intelligent support of e-management for consumer-focused virtual enterprises

NASA Astrophysics Data System (ADS)

Chandra, Charu; Smirnov, Alexander V.

2000-10-01

The interest in consumer-focused virtual enterprises (VE) decision-making problem is growing fast. The purpose of this type of enterprise is to transform incomplete information about customer orders and available resources into-co-ordinated plans for production and replenishment of goods and services in the temporal network formed by collaborating units. This implies that information in the consumer-focused VE can be shared via Internet, Intranet, and Extranet for business-to-consumer (B2C), business-to-business service (B2B-S), and business-to-business goods (B2B-G) transactions. One of the goals of Internet-Based Management (e-management) is to facilitate transfer and sharing of data and knowledge in the context of enterprise collaboration. This paper discusses a generic framework of e-management that integrates intelligent information support group-decision making, and agreement modeling for a VE network. It offers the platform for design and modeling of diverse implementation strategies related to the type of agreement, optimization policies, decision-making strategies, organization structures, and information sharing strategies and mechanisms, and business policies for the VE.

Maximizing Social Model Principles in Residential Recovery Settings

PubMed Central

Polcin, Douglas; Mericle, Amy; Howell, Jason; Sheridan, Dave; Christensen, Jeff

2014-01-01

Abstract Peer support is integral to a variety of approaches to alcohol and drug problems. However, there is limited information about the best ways to facilitate it. The “social model” approach developed in California offers useful suggestions for facilitating peer support in residential recovery settings. Key principles include using 12-step or other mutual-help group strategies to create and facilitate a recovery environment, involving program participants in decision making and facility governance, using personal recovery experience as a way to help others, and emphasizing recovery as an interaction between the individual and their environment. Although limited in number, studies have shown favorable outcomes for social model programs. Knowledge about social model recovery and how to use it to facilitate peer support in residential recovery homes varies among providers. This article presents specific, practical suggestions for enhancing social model principles in ways that facilitate peer support in a range of recovery residences. PMID:25364996

Effective Team Support: From Modeling to Software Agents

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie; Sycara, Katia

2003-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and engineers and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in modeling infrastructure and task infrastructure. Work is continuing under a different contract to complete empirical data collection, cognitive modeling, and the building of software agents to support the teams task.

Advanced Satellite Workstation - An integrated workstation environment for operational support of satellite system planning and analysis

NASA Astrophysics Data System (ADS)

Hamilton, Marvin J.; Sutton, Stewart A.

A prototype integrated environment, the Advanced Satellite Workstation (ASW), which was developed and delivered for evaluation and operator feedback in an operational satellite control center, is described. The current ASW hardware consists of a Sun Workstation and Macintosh II Workstation connected via an ethernet Network Hardware and Software, Laser Disk System, Optical Storage System, and Telemetry Data File Interface. The central objective of ASW is to provide an intelligent decision support and training environment for operator/analysis of complex systems such as satellites. Compared to the many recent workstation implementations that incorporate graphical telemetry displays and expert systems, ASW provides a considerably broader look at intelligent, integrated environments for decision support, based on the premise that the central features of such an environment are intelligent data access and integrated toolsets.

Development of a Decision Support System for Monitoring, Reporting, Forecasting Ecological Conditions of the Appalachian Trail

Treesearch

Y. Wang; R. Nemani; F. Dieffenbach; K. Stolte; G. Holcomb

2010-01-01

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decision-making on management of the A.T. by providing a coherent framework for data integration,...

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

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

USGS Publications Warehouse

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

2017-11-22

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

Valuing investments in sustainable land management using an integrated modelling framework to support a watershed conservation scheme in the Upper Tana River, Kenya

NASA Astrophysics Data System (ADS)

Hunink, Johannes E.; Bryant, Benjamin P.; Vogl, Adrian; Droogers, Peter

2015-04-01

We analyse the multiple impacts of investments in sustainable land use practices on ecosystem services in the Upper Tana basin (Kenya) to support a watershed conservation scheme (a "water fund"). We apply an integrated modelling framework, building on previous field-based and modelling studies in the basin, and link biophysical outputs to economic benefits for the main actors in the basin. The first step in the modelling workflow is the use of a high-resolution spatial prioritization tool (Resource Investment Optimization System -- RIOS) to allocate the type and location of conservation investments in the different subbasins, subject to budget constraints and stakeholder concerns. We then run the Soil and Water Assessment Tool (SWAT) using the RIOS-identified investment scenarios to produce spatially explicit scenarios that simulate changes in water yield and suspended sediment. Finally, in close collaboration with downstream water users (urban water supply and hydropower) we link those biophysical outputs to monetary metrics, including: reduced water treatment costs, increased hydropower production, and crop yield benefits for upstream farmers in the conservation area. We explore how different budgets and different spatial targeting scenarios influence the return of the investments and the effectiveness of the water fund scheme. This study is novel in that it presents an integrated analysis targeting interventions in a decision context that takes into account local environmental and socio-economic conditions, and then relies on detailed, process-based, biophysical models to demonstrate the economic return on those investments. We conclude that the approach allows for an analysis on different spatial and temporal scales, providing conclusive evidence to stakeholders and decision makers on the contribution and benefits of the land-based investments in this basin. This is serving as foundational work to support the implementation of the Upper Tana-Nairobi Water Fund, a public-private partnership to safeguard ecosystem service provision and food security.

Geospatial Data Fusion and Multigroup Decision Support for Surface Water Quality Management

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Osidele, O.; Green, R. T.; Xie, H.

2010-12-01

Social networking and social media have gained significant popularity and brought fundamental changes to many facets of our everyday life. With the ever-increasing adoption of GPS-enabled gadgets and technology, location-based content is likely to play a central role in social networking sites. While location-based content is not new to the geoscience community, where geographic information systems (GIS) are extensively used, the delivery of useful geospatial data to targeted user groups for decision support is new. Decision makers and modelers ought to make more effective use of the new web-based tools to expand the scope of environmental awareness education, public outreach, and stakeholder interaction. Environmental decision processes are often rife with uncertainty and controversy, requiring integration of multiple sources of information and compromises between diverse interests. Fusing of multisource, multiscale environmental data for multigroup decision support is a challenging task. Toward this goal, a multigroup decision support platform should strive to achieve transparency, impartiality, and timely synthesis of information. The latter criterion often constitutes a major technical bottleneck to traditional GIS-based media, featuring large file or image sizes and requiring special processing before web deployment. Many tools and design patterns have appeared in recent years to ease the situation somewhat. In this project, we explore the use of Web 2.0 technologies for “pushing” location-based content to multigroups involved in surface water quality management and decision making. In particular, our granular bottom-up approach facilitates effective delivery of information to most relevant user groups. Our location-based content includes in-situ and remotely sensed data disseminated by NASA and other national and local agencies. Our project is demonstrated for managing the total maximum daily load (TMDL) program in the Arroyo Colorado coastal river basin in Texas. The overall design focuses on assigning spatial information to decision support elements and on efficiently using Web 2.0 technologies to relay scientific information to the nonscientific community. We conclude that (i) social networking, if appropriately used, has great potential for mitigating difficulty associated with multigroup decision making; (ii) all potential stakeholder groups should be involved in creating a useful decision support system; and (iii) environmental decision support systems should be considered a must-have, instead of an optional component of TMDL decision support projects. Acknowledgment: This project was supported by NASA grant NNX09AR63G.

Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility.

PubMed

Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat

2013-08-01

Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support patient recruitment in the framework of a clinical trial for colorectal cancer screening. The utilisation of archetypes not only has proved satisfactory to achieve interoperability between CDSSs and EHRs but also offers various advantages, in particular from a data model perspective. First, the VHR/data models we work with are of a high level of abstraction and can incorporate semantic descriptions. Second, archetypes can potentially deal with different EHR architectures, due to their deliberate independence of the reference model. Third, the archetype instances we obtain are valid instances of the underlying reference model, which would enable e.g. feeding back the EHR with data derived by abstraction mechanisms. Lastly, the medical and technical validity of archetype models would be assured, since in principle clinicians should be the main actors in their development. Copyright © 2013 Elsevier Inc. All rights reserved.

Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

NASA Astrophysics Data System (ADS)

Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

2016-04-01

Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

Dynamic aspects of voluntary turnover: an integrated approach to curvilinearity in the performance-turnover relationship.

PubMed

Becker, William J; Cropanzano, Russell

2011-03-01

Previous research pertaining to job performance and voluntary turnover has been guided by 2 distinct theoretical perspectives. First, the push-pull model proposes that there is a quadratic or curvilinear relationship existing between these 2 variables. Second, the unfolding model of turnover posits that turnover is a dynamic process and that a downward performance change may increase the likelihood of organizational separation. Drawing on decision theory, we propose and test an integrative framework. This approach incorporates both of these earlier models. Specifically, we argue that individuals are most likely to voluntarily exit when they are below-average performers who are also experiencing a downward performance change. Furthermore, the interaction between this downward change and performance partially accounts for the curvilinear relationship proposed by the push-pull model. Findings from a longitudinal field study supported this integrative theory. PsycINFO Database Record (c) 2011 APA, all rights reserved.

Wildfire Decision Making Under Uncertainty

NASA Astrophysics Data System (ADS)

Thompson, M.

2013-12-01

Decisions relating to wildfire management are subject to multiple sources of uncertainty, and are made by a broad range of individuals, across a multitude of environmental and socioeconomic contexts. In this presentation I will review progress towards identification and characterization of uncertainties and how this information can support wildfire decision-making. First, I will review a typology of uncertainties common to wildfire management, highlighting some of the more salient sources of uncertainty and how they present challenges to assessing wildfire risk. This discussion will cover the expanding role of burn probability modeling, approaches for characterizing fire effects, and the role of multi-criteria decision analysis, and will provide illustrative examples of integrated wildfire risk assessment across a variety of planning scales. Second, I will describe a related uncertainty typology that focuses on the human dimensions of wildfire management, specifically addressing how social, psychological, and institutional factors may impair cost-effective risk mitigation. This discussion will encompass decision processes before, during, and after fire events, with a specific focus on active management of complex wildfire incidents. An improved ability to characterize uncertainties faced in wildfire management could lead to improved delivery of decision support, targeted communication strategies, and ultimately to improved wildfire management outcomes.

NED-2: A decision support system for integrated forest ecosystem management

Treesearch

Mark J. Twery; Peter D. Knopp; Scott A. Thomasma; H. Michael Rauscher; Donald E. Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mayukh Dass; Hajime Uchiyama; Astrid Glende; Robin E. Hoffman

2005-01-01

NED-2 is a Windows-based system designed to improve project-level planning and decision making by providing useful and scientifically sound information to natural resource managers. Resources currently addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-2 expands on previous versions of NED applications by integrating treatment...

NED-2: a decision support system for integrated forest ecosystem management

Treesearch

Mark J. Twery; Peter D. Knopp; Scott A. Thomasma; H. Michael Rauscher; Donald E. Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mayukh Dass; Hajime Uchiyama; Astrid Glende; Robin E. Hoffman

2005-01-01

NED-2 is a Windows-based system designed to improve project-level planning and decision making by providing useful and scientifically sound information to natural resource managers. Resources currently addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-2 expands on previous versions of NED applications by integrating treatment...

Integration of RAMS in LCC analysis for linear transport infrastructures. A case study for railways.

NASA Astrophysics Data System (ADS)

Calle-Cordón, Álvaro; Jiménez-Redondo, Noemi; Morales-Gámiz, F. J.; García-Villena, F. A.; Garmabaki, Amir H. S.; Odelius, Johan

2017-09-01

Life-cycle cost (LCC) analysis is an economic technique used to assess the total costs associated with the lifetime of a system in order to support decision making in long term strategic planning. For complex systems, such as railway and road infrastructures, the cost of maintenance plays an important role in the LCC analysis. Costs associated with maintenance interventions can be more reliably estimated by integrating the probabilistic nature of the failures associated to these interventions in the LCC models. Reliability, Maintainability, Availability and Safety (RAMS) parameters describe the maintenance needs of an asset in a quantitative way by using probabilistic information extracted from registered maintenance activities. Therefore, the integration of RAMS in the LCC analysis allows obtaining reliable predictions of system maintenance costs and the dependencies of these costs with specific cost drivers through sensitivity analyses. This paper presents an innovative approach for a combined RAMS & LCC methodology for railway and road transport infrastructures being developed under the on-going H2020 project INFRALERT. Such RAMS & LCC analysis provides relevant probabilistic information to be used for condition and risk-based planning of maintenance activities as well as for decision support in long term strategic investment planning.

End of Asset Life Reinvestment Decision Support Tool (INFR2R11AT)

EPA Science Inventory

This “End of Asset Life” Reinvestment Decision-Support Tool is intended as a step by step guide for the asset management practitioner who faces the challenge of developing an investment strategy that represents the best integration of maintenance, operations, and capital investme...

A decision support tool for vehicle infrastructure integration : understanding information effects and advancing data fusion algorithms for traffic management applications.

DOT National Transportation Integrated Search

2009-10-15

This research seeks to explore vehicle-to-vehicle information networks to understand the interplay : between the information communicated and traffic conditions on the network. A longer-term goal is to : develop a decision support tool for processing...

Using Decision Support to Address Racial Disparities in Mental Health Service Utilization

ERIC Educational Resources Information Center

Rawal, Purva H.; Anderson, Tanya R.; Romansky, Jill R.; Lyons, John S.

2008-01-01

Unfortunately, racial disparities are well documented in the delivery of behavioral health services. This study examines the effects of implementing a decision support process, integrating clinical information into the administration of mental health services, on racial disparities in psychiatric hospital admissions for children in state custody.…

HNS-MS : Improving Member States preparedness to face an HNS pollution of the Marine System

NASA Astrophysics Data System (ADS)

Legrand, Sébastien; Le Floch, Stéphane; Aprin, Laurent; Partenay, Valérie; Donnay, Eric; Parmentier, Koen; Ovidio, Fabrice; Schallier, Ronny; Poncet, Florence; Chataing, Sophie; Poupon, Emmanuelle; Hellouvry, Yann-Hervé

2017-04-01

When dealing with a HNS pollution incident, one of the priority requirements is the identification of the hazard and an assessment of the risk posed to the public and responder safety, the environment and socioeconomic assets upon which a state or coastal community depend. The primary factors which determine the safety, environmental and socioeconomic impact of the released substance(s) relate to their physico-chemical properties and fate in the environment. Until now, preparedness actions at various levels have primarily aimed at classifying the general environmental or public health hazard of an HNS, or at performing a risk analysis of HNS transported in European marine regions. Operational datasheets have been (MIDSIS-TROCS) or are being (MAR-CIS) developed collating detailed, substance-specific information for responders and covering information needs at the first stage of an incident. However, contrary to oil pollution preparedness and response tools, only few decision-support tools used by Member State authorities (Coastguard agencies or other) integrate 3D models that are able to simulate the drift, fate and behaviour of HNS spills in the marine environment. When they do, they usually consider simplified or steady-state environmental conditions. As a significant step forward, a 'one-stop shop' integrated HNS decision-support system has been developed in the framework of the HNS-MS project. Focussing on the Bonn Agreement area, the system integrates 1. A database containing the physico-chemical parameters needed to compute the behaviour in the marine environment of 120 relevant HNS; 2. A digital atlas of the HNS environmental and socioeconomic vulnerability maps ; 3. A three dimensional HNS spill drift and fate model able to simulate HNS behaviour in the marine environment (including floaters, sinkers, evaporators and dissolvers). 4. A user-friendly web-based interface allowing Coastguard stations to launch a HNS drift simulation and visualize post-processed results in support of an incident evaluation and decision-making process. All these results will be further presented.

Integrating DXplain into a clinical information system using the World Wide Web.

PubMed

Elhanan, G; Socratous, S A; Cimino, J J

1996-01-01

The World Wide Web(WWW) offers a cross-platform environment and standard protocols that enable integration of various applications available on the Internet. The authors use the Web to facilitate interaction between their Web-based Clinical Information System and a decision-support system-DXplain, at the Massachusetts General Hospital-using local architecture and Common Gateway Interface programs. The current application translates patients laboratory test results into DXplain's terms to generate diagnostic hypotheses. Two different access methods are utilized for this model; Hypertext Transfer Protocol (HTTP) and TCP/IP function calls. While clinical aspects cannot be evaluated as yet, the model demonstrates the potential of Web-based applications for interaction and integration and how local architecture, with a controlled vocabulary server, can further facilitate such integration. This model serves to demonstrate some of the limitations of the current WWW technology and identifies issues such as control over Web resources and their utilization and liability issues as possible obstacles for further integration.

The OncoSim model: development and use for better decision-making in Canadian cancer control.

PubMed

Gauvreau, C L; Fitzgerald, N R; Memon, S; Flanagan, W M; Nadeau, C; Asakawa, K; Garner, R; Miller, A B; Evans, W K; Popadiuk, C M; Wolfson, M; Coldman, A J

2017-12-01

The Canadian Partnership Against Cancer was created in 2007 by the federal government to accelerate cancer control across Canada. Its OncoSim microsimulation model platform, which consists of a suite of specific cancer models, was conceived as a tool to augment conventional resources for population-level policy- and decision-making. The Canadian Partnership Against Cancer manages the OncoSim program, with funding from Health Canada and model development by Statistics Canada. Microsimulation modelling allows for the detailed capture of population heterogeneity and health and demographic history over time. Extensive data from multiple Canadian sources were used as inputs or to validate the model. OncoSim has been validated through expert consultation; assessments of face validity, internal validity, and external validity; and model fit against observed data. The platform comprises three in-depth cancer models (lung, colorectal, cervical), with another in-depth model (breast) and a generalized model (25 cancers) being in development. Unique among models of its class, OncoSim is available online for public sector use free of charge. Users can customize input values and output display, and extensive user support is provided. OncoSim has been used to support decision-making at the national and jurisdictional levels. Although simulation studies are generally not included in hierarchies of evidence, they are integral to informing cancer control policy when clinical studies are not feasible. OncoSim can evaluate complex intervention scenarios for multiple cancers. Canadian decision-makers thus have a powerful tool to assess the costs, benefits, cost-effectiveness, and budgetary effects of cancer control interventions when faced with difficult choices for improvements in population health and resource allocation.

Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0)

NASA Technical Reports Server (NTRS)

Talabac, Stephen; Ames, Troy; Blank, Karin; Hostetter, Carl; Brandt, Matthew

2013-01-01

ILIADS 3.0 provides the data management capabilities to access CxP-vetted lunar data sets from the LMMP-provided Data Portal and the LMMP-provided On-Moon lunar data product server. (LMMP stands for Lunar Mapping and Modeling Project.) It also provides specific quantitative analysis functions to meet the stated LMMP Level 3 functional and performance requirements specifications that were approved by the CxP. The purpose of ILIADS 3.0 is to provide an integrated, rich client lunar GIS software application

Water Planning in Phoenix: Managing Risk in the Face of Climatic Uncertainty

NASA Astrophysics Data System (ADS)

Gober, P.

2009-12-01

The Decision Center for a Desert City (DCDC) was founded in 2004 to develop scientifically-credible support tools to improve water management decisions in the face of growing climatic uncertainty and rapid urbanization in metropolitan Phoenix. At the center of DCDC's effort is WaterSim, a model that integrates information about water supply from groundwater, the Colorado River, and upstream watersheds and water demand from land use change and population growth. Decision levers enable users to manipulate model outcomes in response to climate change scenarios, drought conditions, population growth rates, technology innovations, lifestyle changes, and policy decisions. WaterSim allows users to examine the risks of water shortage from global climate change, the tradeoffs between groundwater sustainability and lifestyle choices, the effects of various policy decisions, and the consequences of delaying policy for the exposure to risk. WaterSim is an important point of contact for DCDC’s relationships with local decision makers. Knowledge, tools, and visualizations are co-produced—by scientists and policy makers, and the Center’s social scientists mine this co-production process for new insights about model development and application. WaterSim is less a static scientific product and more a dynamic process of engagement between decision makers and scientists.

The Lenfest Ocean Program's experience in building institutional support for connecting science and decision-making in marine systems

NASA Astrophysics Data System (ADS)

Bednarek, A.; Close, S.; Curran, K.; Hudson, C.

2017-12-01

Addressing contemporary sustainability challenges requires attention to the integration of scientific knowledge into decision-making and deliberation. However, this remains a challenge in practice. We contend that careful stewardship of this process of integration can result in positive, durable outcomes by reconciling the production and use of scientific knowledge, and improve its relevance and utility to decision-makers. We will share lessons learned from a grantmaking program that has addressed this challenge through programmatic innovations, including by supporting staff devoted to an intermediary role. Over the past 13 years, the Lenfest Ocean Program served in a boundary spanning role by integrating decision-makers into the scoping and outreach of program supported scientific research grants. Program staff engage with decision-makers and influencers to identify policy-relevant research questions and approaches, ensuring that the research direction addresses users' needs. As research progresses, the staff monitor the grant's progress to improve the match between the research and user needs. The process is resource-intensive, however, and raises interesting questions about the role and development of this kind of specialist within different kinds of institutions, including funding agencies. We suggest that nurturing this role as a practice and profession could ultimately help the scientific community more efficiently respond to sustainability challenges.

Strategies and Decision Support Systems for Integrating Variable Energy Resources in Control Centers for Reliable Grid Operations

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

Jones, Lawrence E.

This report provides findings from the field regarding the best ways in which to guide operational strategies, business processes and control room tools to support the integration of renewable energy into electrical grids.

Integrating cost information with health management support system: an enhanced methodology to assess health care quality drivers.

PubMed

Kohli, R; Tan, J K; Piontek, F A; Ziege, D E; Groot, H

1999-08-01

Changes in health care delivery, reimbursement schemes, and organizational structure have required health organizations to manage the costs of providing patient care while maintaining high levels of clinical and patient satisfaction outcomes. Today, cost information, clinical outcomes, and patient satisfaction results must become more fully integrated if strategic competitiveness and benefits are to be realized in health management decision making, especially in multi-entity organizational settings. Unfortunately, traditional administrative and financial systems are not well equipped to cater to such information needs. This article presents a framework for the acquisition, generation, analysis, and reporting of cost information with clinical outcomes and patient satisfaction in the context of evolving health management and decision-support system technology. More specifically, the article focuses on an enhanced costing methodology for determining and producing improved, integrated cost-outcomes information. Implementation issues and areas for future research in cost-information management and decision-support domains are also discussed.

SFINX-a drug-drug interaction database designed for clinical decision support systems.

PubMed

Böttiger, Ylva; Laine, Kari; Andersson, Marine L; Korhonen, Tuomas; Molin, Björn; Ovesjö, Marie-Louise; Tirkkonen, Tuire; Rane, Anders; Gustafsson, Lars L; Eiermann, Birgit

2009-06-01

The aim was to develop a drug-drug interaction database (SFINX) to be integrated into decision support systems or to be used in website solutions for clinical evaluation of interactions. Key elements such as substance properties and names, drug formulations, text structures and references were defined before development of the database. Standard operating procedures for literature searches, text writing rules and a classification system for clinical relevance and documentation level were determined. ATC codes, CAS numbers and country-specific codes for substances were identified and quality assured to ensure safe integration of SFINX into other data systems. Much effort was put into giving short and practical advice regarding clinically relevant drug-drug interactions. SFINX includes over 8,000 interaction pairs and is integrated into Swedish and Finnish computerised decision support systems. Over 31,000 physicians and pharmacists are receiving interaction alerts through SFINX. User feedback is collected for continuous improvement of the content. SFINX is a potentially valuable tool delivering instant information on drug interactions during prescribing and dispensing.

Supporting shared decision-making for older people with multiple health and social care needs: a protocol for a realist synthesis to inform integrated care models

PubMed Central

Bunn, Frances; Goodman, Claire; Manthorpe, Jill; Durand, Marie-Anne; Hodkinson, Isabel; Rait, Greta; Millac, Paul; Davies, Sue L; Russell, Bridget; Wilson, Patricia

2017-01-01

Introduction Including the patient or user perspective is a central organising principle of integrated care. Moreover, there is increasing recognition of the importance of strengthening relationships among patients, carers and practitioners, particularly for individuals receiving substantial health and care support, such as those with long-term or multiple conditions. The overall aims of this synthesis are to provide a context-relevant understanding of how models to facilitate shared decision-making (SDM) might work for older people with multiple health and care needs, and how they might be applied to integrated care models. Methods and analysis The synthesis draws on the principles of realist inquiry, to explain how, in what contexts and for whom, interventions that aim to strengthen SDM among older patients, carers and practitioners are effective. We will use an iterative, stakeholder-driven, three-phase approach. Phase 1: development of programme theory/theories that will be tested through a first scoping of the literature and consultation with key stakeholder groups; phase 2: systematic searches of the evidence to test and develop the theories identified in phase 1; phase 3: validation of programme theory/theories with a purposive sample of participants from phase 1. The synthesis will draw on prevailing theories such as candidacy, self-efficacy, personalisation and coproduction. Ethics and dissemination Ethics approval for the stakeholder interviews was obtained from the University of Hertfordshire ECDA (Ethics Committee with Delegated Authority), reference number HSK/SF/UH/02387. The propositions arising from this review will be used to develop recommendations about how to tailor SDM interventions to older people with complex health and social care needs in an integrated care setting. PMID:28174225

Eradicating the grey squirrel Sciurus carolinensis from urban areas: an innovative decision-making approach based on lessons learnt in Italy.

PubMed

La Morgia, Valentina; Paoloni, Daniele; Genovesi, Piero

2017-02-01

Eradication of invasive alien species supports the recovery of native biodiversity. A new European Union Regulation introduces obligations to eradicate the most harmful invasive species. However, eradications of charismatic mammals may encounter strong opposition. Considering the case study of the eastern grey squirrel (Sciurus carolinensis Gmelin, 1788) in central Italy, we developed a structured decision-making technique based on a Bayesian decision network model and explicitly considering the plurality of environmental values of invasive species management to reduce potential social conflicts. The model identified priority areas for management activities. These areas corresponded to the core of the grey squirrel range, but they also included peripheral zones, where rapid eradication is fundamental to prevent the spread of squirrels. However, when the model was expanded to integrate the attitude of citizens towards the project, the intervention strategy slightly changed. In some areas, the citizens' support was limited, and this resulted in a reduced overall utility of intervention. The suggested approach extends the scientific basis for management decisions, evaluated in terms of technical efficiency, feasibility and social impact. Here, the Bayesian decision network model analysed the potential technical and social consequences of management actions, and it responded to the need for transparency in the decision-making process, but it can easily be extended to consider further issues that are common in many mammal eradication programmes. Owing to its flexibility and comprehensiveness, it provides an innovative example of how to plan rapid eradication or control activities, as required by the new EU Regulation. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Satellite Observations for Detecting and Tracking Changes in Atmospheric Composition

NASA Technical Reports Server (NTRS)

Neil, Doreen O.; Kondragunbta, Shobha; Osterman, Gregory; Pickering, Kenneth; Pinder, Robert W.; Prados, Ana I.; Szykman, James

2009-01-01

The satellite observations provide constraints on detailed atmospheric modeling, including emissions inventories, indications of transport, harmonized data over vast areas suitable for trends analysis, and a link between spatial scales ranging from local to global, and temporal scales from diurnal to interannual. 1 The National Oceanic and Atmospheric Administration's (NOAA) long-term commitments help provide these observations in cooperation with international meteorological organizations. NASA s long-term commitments will advance scientifically important observations as part of its Earth Science Program, and will assist the transition of the science measurements to applied analyses through the Applied Science Program. Both NASA and NOAA have begun to provide near realtime data and tools to visualize and analyze satellite data,2 while maintaining data quality, validation, and standards. Consequently, decision-makers can expect satellite data services to support air quality decision making now and in the future. The international scientific community's Integrated Global Atmosphere Chemistry Observation System Report3 outlined a plan for ground-based, airborne and satellite measurements and models to integrate the observations into a four-dimensional representation of the atmosphere (space and time) to support assessment and policy information needs. This plan is being carried out under the Global Earth Observation System of Systems (GEOSS). Demonstrations of such an integrated capability4 provide new understanding of the changing atmosphere and link policy decisions to benefits for society. In this article, we highlight the use of satellite data to constrain biomass burning emissions, to assess oxides of nitrogen (NO(x)) emission reductions, and to contribute to state implementation plans, as examples of the use of satellite observations for detecting and tracking changes in atmospheric composition.

A climate robust integrated modelling framework for regional impact assessment of climate change

NASA Astrophysics Data System (ADS)

Janssen, Gijs; Bakker, Alexander; van Ek, Remco; Groot, Annemarie; Kroes, Joop; Kuiper, Marijn; Schipper, Peter; van Walsum, Paul; Wamelink, Wieger; Mol, Janet

2013-04-01

Decision making towards climate proofing the water management of regional catchments can benefit greatly from the availability of a climate robust integrated modelling framework, capable of a consistent assessment of climate change impacts on the various interests present in the catchments. In the Netherlands, much effort has been devoted to developing state-of-the-art regional dynamic groundwater models with a very high spatial resolution (25x25 m2). Still, these models are not completely satisfactory to decision makers because the modelling concepts do not take into account feedbacks between meteorology, vegetation/crop growth, and hydrology. This introduces uncertainties in forecasting the effects of climate change on groundwater, surface water, agricultural yields, and development of groundwater dependent terrestrial ecosystems. These uncertainties add to the uncertainties about the predictions on climate change itself. In order to create an integrated, climate robust modelling framework, we coupled existing model codes on hydrology, agriculture and nature that are currently in use at the different research institutes in the Netherlands. The modelling framework consists of the model codes MODFLOW (groundwater flow), MetaSWAP (vadose zone), WOFOST (crop growth), SMART2-SUMO2 (soil-vegetation) and NTM3 (nature valuation). MODFLOW, MetaSWAP and WOFOST are coupled online (i.e. exchange information on time step basis). Thus, changes in meteorology and CO2-concentrations affect crop growth and feedbacks between crop growth, vadose zone water movement and groundwater recharge are accounted for. The model chain WOFOST-MetaSWAP-MODFLOW generates hydrological input for the ecological prediction model combination SMART2-SUMO2-NTM3. The modelling framework was used to support the regional water management decision making process in the 267 km2 Baakse Beek-Veengoot catchment in the east of the Netherlands. Computations were performed for regionalized 30-year climate change scenarios developed by KNMI for precipitation and reference evapotranspiration according to Penman-Monteith. Special focus in the project was on the role of uncertainty. How valid is the information that is generated by this modelling framework? What are the most important uncertainties of the input data, how do they affect the results of the model chain and how can the uncertainties of the data, results, and model concepts be quantified and communicated? Besides these technical issues, an important part of the study was devoted to the perception of stakeholders. Stakeholder analysis and additional working sessions yielded insight into how the models, their results and the uncertainties are perceived, how the modelling framework and results connect to the stakeholders' information demands and what kind of additional information is needed for adequate support on decision making.

When four principles are too many: bloodgate, integrity and an action-guiding model of ethical decision making in clinical practice.

PubMed

Muirhead, William

2012-04-01

Medical ethical analysis remains dominated by the principlist account first proposed by Beauchamp and Childress. This paper argues that the principlist model is unreflective of how ethical decisions are taken in clinical practice. Two kinds of medical ethical decisions are distinguished: biosocial ethics and clinical ethics. It is argued that principlism is an inappropriate model for clinical ethics as it is neither sufficiently action-guiding nor does it emphasise the professional integrity of the clinician. An alternative model is proposed for decision making in the realm of clinical ethics.

Collaborative deliberation: a model for patient care.

PubMed

Elwyn, Glyn; Lloyd, Amy; May, Carl; van der Weijden, Trudy; Stiggelbout, Anne; Edwards, Adrian; Frosch, Dominick L; Rapley, Tim; Barr, Paul; Walsh, Thom; Grande, Stuart W; Montori, Victor; Epstein, Ronald

2014-11-01

Existing theoretical work in decision making and behavior change has focused on how individuals arrive at decisions or form intentions. Less attention has been given to theorizing the requirements that might be necessary for individuals to work collaboratively to address difficult decisions, consider new alternatives, or change behaviors. The goal of this work was to develop, as a forerunner to a middle range theory, a conceptual model that considers the process of supporting patients to consider alternative health care options, in collaboration with clinicians, and others. Theory building among researchers with experience and expertise in clinician-patient communication, using an iterative cycle of discussions. We developed a model composed of five inter-related propositions that serve as a foundation for clinical communication processes that honor the ethical principles of respecting individual agency, autonomy, and an empathic approach to practice. We named the model 'collaborative deliberation.' The propositions describe: (1) constructive interpersonal engagement, (2) recognition of alternative actions, (3) comparative learning, (4) preference construction and elicitation, and (5) preference integration. We believe the model underpins multiple suggested approaches to clinical practice that take the form of patient centered care, motivational interviewing, goal setting, action planning, and shared decision making. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Multi-criteria Integrated Resource Assessment (MIRA)

EPA Pesticide Factsheets

MIRA is an approach that facilitates stakeholder engagement for collaborative multi-objective decision making. MIRA is designed to facilitate and support an inclusive, explicit, transparent, iterative learning-based decision process.

Integrating disease management into the outpatient delivery system during and after managed care.

PubMed

Villagra, Victor G

2004-01-01

Managed care introduced disease management as a replacement strategy to utilization management. The focus changed from influencing treatment decisions to supporting self-care and compliance. Disease management rendered operational many elements of the chronic care model, but it did so outside the delivery system, thus escaping the financial limitations, cultural barriers, and inertia inherent in effecting radical change from within. Medical management "after managed care" should include the functional and structural integration of disease management with primary care clinics. Such integration would supply the infrastructure that primary care physicians need to coordinate the care of chronically ill patients more effectively.

Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: An example from a vertigo phase III study with longitudinal count data as primary endpoint

PubMed Central

2012-01-01

Background A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. Methods We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). Results The instruments under study provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. Conclusions The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint. PMID:22962944

Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: an example from a vertigo phase III study with longitudinal count data as primary endpoint.

PubMed

Adrion, Christine; Mansmann, Ulrich

2012-09-10

A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). The instruments under study provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint.

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.

An innovative approach to addressing childhood obesity: a knowledge-based infrastructure for supporting multi-stakeholder partnership decision-making in Quebec, Canada.

PubMed

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L; Dubé, Laurette

2015-01-23

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a "portrait", which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity.

An Innovative Approach to Addressing Childhood Obesity: A Knowledge-Based Infrastructure for Supporting Multi-Stakeholder Partnership Decision-Making in Quebec, Canada

PubMed Central

Addy, Nii Antiaye; Shaban-Nejad, Arash; Buckeridge, David L.; Dubé, Laurette

2015-01-01

Multi-stakeholder partnerships (MSPs) have become a widespread means for deploying policies in a whole of society strategy to address the complex problem of childhood obesity. However, decision-making in MSPs is fraught with challenges, as decision-makers are faced with complexity, and have to reconcile disparate conceptualizations of knowledge across multiple sectors with diverse sets of indicators and data. These challenges can be addressed by supporting MSPs with innovative tools for obtaining, organizing and using data to inform decision-making. The purpose of this paper is to describe and analyze the development of a knowledge-based infrastructure to support MSP decision-making processes. The paper emerged from a study to define specifications for a knowledge-based infrastructure to provide decision support for community-level MSPs in the Canadian province of Quebec. As part of the study, a process assessment was conducted to understand the needs of communities as they collect, organize, and analyze data to make decisions about their priorities. The result of this process is a “portrait”, which is an epidemiological profile of health and nutrition in their community. Portraits inform strategic planning and development of interventions, and are used to assess the impact of interventions. Our key findings indicate ambiguities and disagreement among MSP decision-makers regarding causal relationships between actions and outcomes, and the relevant data needed for making decisions. MSP decision-makers expressed a desire for easy-to-use tools that facilitate the collection, organization, synthesis, and analysis of data, to enable decision-making in a timely manner. Findings inform conceptual modeling and ontological analysis to capture the domain knowledge and specify relationships between actions and outcomes. This modeling and analysis provide the foundation for an ontology, encoded using OWL 2 Web Ontology Language. The ontology is developed to provide semantic support for the MSP process, defining objectives, strategies, actions, indicators, and data sources. In the future, software interacting with the ontology can facilitate interactive browsing by decision-makers in the MSP in the form of concepts, instances, relationships, and axioms. Our ontology also facilitates the integration and interpretation of community data, and can help in managing semantic interoperability between different knowledge sources. Future work will focus on defining specifications for the development of a database of indicators and an information system to help decision-makers to view, analyze and organize indicators for their community. This work should improve MSP decision-making in the development of interventions to address childhood obesity. PMID:25625409

Integrated Modeling and Decision-Support System for Water Management in the Puget Sound Basin: Snow Caps to White Caps

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

Copping, Andrea E.; Yang, Zhaoqing; Voisin, Nathalie

2013-12-01

Final Report for the EPA-sponsored project Snow Caps to White Caps that provides data products and insight for water resource managers to support their predictions and management actions to address future changes in water resources (fresh and marine) in the Puget Sound basin. This report details the efforts of a team of scientists and engineers from Pacific Northwest National Laboratory (PNNL) and the University of Washington (UW) to examine the movement of water in the Snohomish Basin, within the watershed and the estuary, under present and future conditions, using a set of linked numerical models.

A Successful Implementation Strategy to Support Adoption of Decision Making in Mental Health Services.

PubMed

MacDonald-Wilson, Kim L; Hutchison, Shari L; Karpov, Irina; Wittman, Paul; Deegan, Patricia E

2017-04-01

Individual involvement in treatment decisions with providers, often through the use of decision support aids, improves quality of care. This study investigates an implementation strategy to bring decision support to community mental health centers (CMHC). Fifty-two CMHCs implemented a decision support toolkit supported by a 12-month learning collaborative using the Breakthrough Series model. Participation in learning collaborative activities was high, indicating feasibility of the implementation model. Progress by staff in meeting process aims around utilization of components of the toolkit improved significantly over time (p < .0001). Survey responses by individuals in service corroborate successful implementation. Community-based providers were able to successfully implement decision support in mental health services as evidenced by improved process outcomes and sustained practices over 1 year through the structure of the learning collaborative model.

USGS River Ecosystem Modeling: Where Are We, How Did We Get Here, and Where Are We Going?

USGS Publications Warehouse

Hanson, Leanne; Schrock, Robin; Waddle, Terry; Duda, Jeffrey J.; Lellis, Bill

2009-01-01

This report developed as an outcome of the USGS River Ecosystem Modeling Work Group, convened on February 11, 2008 as a preconference session to the second USGS Modeling Conference in Orange Beach, Ala. Work Group participants gained an understanding of the types of models currently being applied to river ecosystem studies within the USGS, learned how model outputs are being used by a Federal land management agency, and developed recommendations for advancing the state of the art in river ecosystem modeling within the USGS. During a break-out session, participants restated many of the recommendations developed at the first USGS Modeling Conference in 2006 and in previous USGS needs assessments. All Work Group recommendations require organization and coordination across USGS disciplines and regions, and include (1) enhancing communications, (2) increasing efficiency through better use of current human and technologic resources, and (3) providing a national infrastructure for river ecosystem modeling resources, making it easier to integrate modeling efforts. By implementing these recommendations, the USGS will benefit from enhanced multi-disciplinary, integrated models for river ecosystems that provide valuable risk assessment and decision support tools for adaptive management of natural and managed riverine ecosystems. These tools generate key information that resource managers need and can use in making decisions about river ecosystem resources.

Modeling forest planning trade-offs on the Colorado Front Range using MAGIS, an optimization, spatial decision support system

Treesearch

Edward B. Butler

2005-01-01

The fires of 2000 and 2002 catalyzed a national mandate for fuel treatment programs to facilitate wildfire mitigation, yet the issues that need to be considered when planning large landscape projects are daunting, often ending in gridlock due to planning conflicts. Hazardous fuels maps help little when planning for integrated, system-wide ecological objectives and fail...

Personal resilience, cognitive appraisals, and coping: an integrative model of adjustment to abortion.

PubMed

Major, B; Richards, C; Cooper, M L; Cozzarelli, C; Zubek, J

1998-03-01

We hypothesized that the effects of personality (self-esteem, control, and optimism) on postabortion adaptation (distress, well-being, and decision satisfaction) would be fully mediated by preabortion cognitive appraisals (stress appraisals and self-efficacy appraisals) and postabortion coping. We further proposed that the effects of preabortion appraisals on adaptation would be fully mediated by postabortion coping. Results of a longitudinal study of 527 women who had first-trimester abortions supported our hypotheses. Women with more resilient personalities appraised their abortion as less stressful and had higher self-efficacy for coping with the abortion. More positive appraisals predicted greater acceptance/reframing coping and lesser avoidance/denial, venting, support seeking, and religious coping. Acceptance-reframing predicted better adjustment on all measures, whereas avoidance-denial and venting related to poorer adjustment on all measures. Greater support seeking was associated with reduced distress, and greater religious coping was associated with less decision satisfaction.

Using a Pareto-optimal solution set to characterize trade-offs between a broad range of values and preferences in climate risk management

NASA Astrophysics Data System (ADS)

Garner, Gregory; Reed, Patrick; Keller, Klaus

2015-04-01

Integrated assessment models (IAMs) are often used to inform the design of climate risk management strategies. Previous IAM studies have broken important new ground on analyzing the effects of parametric uncertainties, but they are often silent on the implications of uncertainties regarding the problem formulation. Here we use the Dynamic Integrated model of Climate and the Economy (DICE) to analyze the effects of uncertainty surrounding the definition of the objective(s). The standard DICE model adopts a single objective to maximize a weighted sum of utilities of per-capita consumption. Decision makers, however, are often concerned with a broader range of values and preferences that may be poorly captured by this a priori definition of utility. We reformulate the problem by introducing three additional objectives that represent values such as (i) reliably limiting global average warming to two degrees Celsius and minimizing (ii) the costs of abatement and (iii) the climate change damages. We use advanced multi-objective optimization methods to derive a set of Pareto-optimal solutions over which decision makers can trade-off and assess performance criteria a posteriori. We illustrate the potential for myopia in the traditional problem formulation and discuss the capability of this multiobjective formulation to provide decision support.

Integrating human and ecological risk assessment: application to the cyanobacterial harmful algal bloom problem.

PubMed

Orme-Zavaleta, Jennifer; Munns, Wayne R

2008-01-01

Environmental and public health policy continues to evolve in response to new and complex social, economic and environmental drivers. Globalization and centralization of commerce, evolving patterns of land use (e.g., urbanization, deforestation), and technological advances in such areas as manufacturing and development of genetically modified foods have created new and complex classes of stressors and risks (e.g., climate change, emergent and opportunist disease, sprawl, genomic change). In recognition of these changes, environmental risk assessment and its use are changing from stressor-endpoint specific assessments used in command and control types of decisions to an integrated approach for application in community-based decisions. As a result, the process of risk assessment and supporting risk analyses are evolving to characterize the human-environment relationship. Integrating risk paradigms combine the process of risk estimation for humans, biota, and natural resources into one assessment to improve the information used in environmental decisions (Suter et al. 2003b). A benefit to this approach includes a broader, system-wide evaluation that considers the interacting effects of stressors on humans and the environment, as well the interactions between these entities. To improve our understanding of the linkages within complex systems, risk assessors will need to rely on a suite of techniques for conducting rigorous analyses characterizing the exposure and effects relationships between stressors and biological receptors. Many of the analytical techniques routinely employed are narrowly focused and unable to address the complexities of an integrated assessment. In this paper, we describe an approach to integrated risk assessment, and discuss qualitative community modeling and Probabilistic Relational Modeling techniques that address these limitations and evaluate their potential for use in an integrated risk assessment of cyanobacteria.

Use of agents to implement an integrated computing environment

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.

1995-01-01

Integrated Product and Process Development (IPPD) embodies the simultaneous application to both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. Agents are used to implement the overall infrastructure on the computer. Successful agent utilization requires that they be made of three components: the resource, the model, and the wrap. Current work is focused on the development of generalized agent schemes and associated demonstration projects. When in place, the technology independent computing infrastructure will aid the designer in systematically generating knowledge used to facilitate decision-making.

The tale of hearts and reason: the influence of mood on decision making.

PubMed

Laborde, Sylvain; Raab, Markus

2013-08-01

In decision-making research, one important aspect of real-life decisions has so far been neglected: the mood of the decision maker when generating options. The authors tested the use of the take-the-first (TTF) heuristic and extended the TTF model to understand how mood influences the option-generation process of individuals in two studies, the first using a between-subjects design (30 nonexperts, 30 near-experts, and 30 experts) and the second conceptually replicating the first using a within-subject design (30 nonexperts). Participants took part in an experimental option-generation task, with 31 three-dimensional videos of choices in team handball. Three moods were elicited: positive, neutral, and negative. The findings (a) replicate previous results concerning TTF and (b) show that the option-generation process was associated with the physiological component of mood, supporting the neurovisceral integration model. The extension of TTF to processing emotional factors is an important step forward in explaining fast choices in real-life situations.

Overview of EPA tools for supporting local-, state- and regional-level decision makers addressing energy and environmental issues: NYC MARKAL Energy Systems Model and Municipal Solid Waste Decision Support Tool

EPA Science Inventory

A workshop will be conducted to demonstrate and focus on two decision support tools developed at EPA/ORD: 1. Community-scale MARKAL model: an energy-water technology evaluation tool and 2. Municipal Solid Waste Decision Support Tool (MSW DST). The Workshop will be part of Southea...

Multiple methods for multiple futures: Integrating qualitative scenario planning and quantitative simulation modeling for natural resource decision making

USGS Publications Warehouse

Symstad, Amy J.; Fisichelli, Nicholas A.; Miller, Brian W.; Rowland, Erika; Schuurman, Gregor W.

2017-01-01

Scenario planning helps managers incorporate climate change into their natural resource decision making through a structured “what-if” process of identifying key uncertainties and potential impacts and responses. Although qualitative scenarios, in which ecosystem responses to climate change are derived via expert opinion, often suffice for managers to begin addressing climate change in their planning, this approach may face limits in resolving the responses of complex systems to altered climate conditions. In addition, this approach may fall short of the scientific credibility managers often require to take actions that differ from current practice. Quantitative simulation modeling of ecosystem response to climate conditions and management actions can provide this credibility, but its utility is limited unless the modeling addresses the most impactful and management-relevant uncertainties and incorporates realistic management actions. We use a case study to compare and contrast management implications derived from qualitative scenario narratives and from scenarios supported by quantitative simulations. We then describe an analytical framework that refines the case study’s integrated approach in order to improve applicability of results to management decisions. The case study illustrates the value of an integrated approach for identifying counterintuitive system dynamics, refining understanding of complex relationships, clarifying the magnitude and timing of changes, identifying and checking the validity of assumptions about resource responses to climate, and refining management directions. Our proposed analytical framework retains qualitative scenario planning as a core element because its participatory approach builds understanding for both managers and scientists, lays the groundwork to focus quantitative simulations on key system dynamics, and clarifies the challenges that subsequent decision making must address.

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

PubMed

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

2017-04-01

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

Design and usability of heuristic-based deliberation tools for women facing amniocentesis.

PubMed

Durand, Marie-Anne; Wegwarth, Odette; Boivin, Jacky; Elwyn, Glyn

2012-03-01

Evidence suggests that in decision contexts characterized by uncertainty and time constraints (e.g. health-care decisions), fast and frugal decision-making strategies (heuristics) may perform better than complex rules of reasoning. To examine whether it is possible to design deliberation components in decision support interventions using simple models (fast and frugal heuristics). The 'Take The Best' heuristic (i.e. selection of a 'most important reason') and 'The Tallying' integration algorithm (i.e. unitary weighing of pros and cons) were used to develop two deliberation components embedded in a Web-based decision support intervention for women facing amniocentesis testing. Ten researchers (recruited from 15), nine health-care providers (recruited from 28) and ten pregnant women (recruited from 14) who had recently been offered amniocentesis testing appraised evolving versions of 'your most important reason' (Take The Best) and 'weighing it up' (Tallying). Most researchers found the tools useful in facilitating decision making although emphasized the need for simple instructions and clear layouts. Health-care providers however expressed concerns regarding the usability and clarity of the tools. By contrast, 7 out of 10 pregnant women found the tools useful in weighing up the pros and cons of each option, helpful in structuring and clarifying their thoughts and visualizing their decision efforts. Several pregnant women felt that 'weighing it up' and 'your most important reason' were not appropriate when facing such a difficult and emotional decision. Theoretical approaches based on fast and frugal heuristics can be used to develop deliberation tools that provide helpful support to patients facing real-world decisions about amniocentesis. © 2011 Blackwell Publishing Ltd.

Leveraging Web Services in Providing Efficient Discovery, Retrieval, and Integration of NASA-Sponsored Observations and Predictions

NASA Astrophysics Data System (ADS)

Bambacus, M.; Alameh, N.; Cole, M.

2006-12-01

The Applied Sciences Program at NASA focuses on extending the results of NASA's Earth-Sun system science research beyond the science and research communities to contribute to national priority applications with societal benefits. By employing a systems engineering approach, supporting interoperable data discovery and access, and developing partnerships with federal agencies and national organizations, the Applied Sciences Program facilitates the transition from research to operations in national applications. In particular, the Applied Sciences Program identifies twelve national applications, listed at http://science.hq.nasa.gov/earth-sun/applications/, which can be best served by the results of NASA aerospace research and development of science and technologies. The ability to use and integrate NASA data and science results into these national applications results in enhanced decision support and significant socio-economic benefits for each of the applications. This paper focuses on leveraging the power of interoperability and specifically open standard interfaces in providing efficient discovery, retrieval, and integration of NASA's science research results. Interoperability (the ability to access multiple, heterogeneous geoprocessing environments, either local or remote by means of open and standard software interfaces) can significantly increase the value of NASA-related data by increasing the opportunities to discover, access and integrate that data in the twelve identified national applications (particularly in non-traditional settings). Furthermore, access to data, observations, and analytical models from diverse sources can facilitate interdisciplinary and exploratory research and analysis. To streamline this process, the NASA GeoSciences Interoperability Office (GIO) is developing the NASA Earth-Sun System Gateway (ESG) to enable access to remote geospatial data, imagery, models, and visualizations through open, standard web protocols. The gateway (online at http://esg.gsfc.nasa.gov) acts as a flexible and searchable registry of NASA-related resources (files, services, models, etc) and allows scientists, decision makers and others to discover and retrieve a wide variety of observations and predictions of natural and human phenomena related to Earth Science from NASA and other sources. To support the goals of the Applied Sciences national applications, GIO staff is also working with the national applications communities to identify opportunities where open standards-based discovery and access to NASA data can enhance the decision support process of the national applications. This paper describes the work performed to-date on that front, and summarizes key findings in terms of identified data sources and benefiting national applications. The paper also highlights the challenges encountered in making NASA-related data accessible in a cross-cutting fashion and identifies areas where interoperable approaches can be leveraged.

Invited review: Helping dairy farmers to improve economic performance utilizing data-driving decision support tools.

PubMed

Cabrera, V E

2018-01-01

The objective of this review paper is to describe the development and application of a suite of more than 40 computerized dairy farm decision support tools contained at the University of Wisconsin-Madison (UW) Dairy Management website http://DairyMGT.info. These data-driven decision support tools are aimed to help dairy farmers improve their decision-making, environmental stewardship and economic performance. Dairy farm systems are highly dynamic in which changing market conditions and prices, evolving policies and environmental restrictions together with every time more variable climate conditions determine performance. Dairy farm systems are also highly integrated with heavily interrelated components such as the dairy herd, soils, crops, weather and management. Under these premises, it is critical to evaluate a dairy farm following a dynamic integrated system approach. For this approach, it is crucial to use meaningful data records, which are every time more available. These data records should be used within decision support tools for optimal decision-making and economic performance. Decision support tools in the UW-Dairy Management website (http://DairyMGT.info) had been developed using combination and adaptation of multiple methods together with empirical techniques always with the primary goal for these tools to be: (1) highly user-friendly, (2) using the latest software and computer technologies, (3) farm and user specific, (4) grounded on the best scientific information available, (5) remaining relevant throughout time and (6) providing fast, concrete and simple answers to complex farmers' questions. DairyMGT.info is a translational innovative research website in various areas of dairy farm management that include nutrition, reproduction, calf and heifer management, replacement, price risk and environment. This paper discusses the development and application of 20 selected (http://DairyMGT.info) decision support tools.

Using Visualization in Cockpit Decision Support Systems

NASA Technical Reports Server (NTRS)

Aragon, Cecilia R.

2005-01-01

In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.

Decision Support System for an efficient irrigation water management in semi arid environment

NASA Astrophysics Data System (ADS)

Khan, M. A.; Islam, M.; Hafeez, M. M.; Flugel, W. A.

2009-12-01

A significant increase in agricultural productivity over the last few decades has protected the world from episodes of hunger and food shortages. Water management in irrigated agriculture was instrumental in achieving those gains. Water resources are under high pressure due to rapid population growth and increased competition among various sectors. Access to reliable data on water availability, quantity and quality can provide the necessary foundation for sound management of water resources. There are many traditional methods for matching water demand and supply, however imbalances between demand and supply remain inevitable. It is possible to reduce the imbalances considerably through development of appropriate irrigation water management tool that take into account various factors such as soil type, irrigation water supply, and crop water demand. All components of water balance need to be understood and quantified for efficient and sustainable management of water resources. Application of an intelligent Decision Support System (DSS) is becoming significant. A DSS incorporates knowledge and expertise within the decision support framework. It is an integrated set of data, functions, models and other relevant information that efficiently processes input data, simulates models and displays the results in a user friendly format. It helps in decision-making process, to analyse the problem and explore various scenarios to make the most appropriate decision for water management. This paper deals with the Coleambally Irrigation Area (CIA) located in Murrumbidgee catchment, NSW, Australia. An Integrated River Information System called Coleambally IRIS has been developed to improve the irrigation water management ranging from farm to sub-system and system level. It is a web-based information management system with a focus on time series and geospatial hydrological, climatic and remote sensing data including land cover class, surface temperature, soil moisture, Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI) and Evapotranspiration (ET). Coleambally IRIS provides user friendly environment for data input and output, and an adaptable set of functions for data analysis, management and decision making to develops strategies for sustainable irrigation water management. Coleambally IRIS is used to assist the managers of irrigation service provider and the farmers in their decision making by providing relevant information over the web. The developed DSS has been practically used in managing irrigation water under the current drought conditions. The DSS will be further extended for forecasting irrigation water demand in the future.

The design and implementation of urban earthquake disaster loss evaluation and emergency response decision support systems based on GIS

NASA Astrophysics Data System (ADS)

Yang, Kun; Xu, Quan-li; Peng, Shuang-yun; Cao, Yan-bo

2008-10-01

Based on the necessity analysis of GIS applications in earthquake disaster prevention, this paper has deeply discussed the spatial integration scheme of urban earthquake disaster loss evaluation models and visualization technologies by using the network development methods such as COM/DCOM, ActiveX and ASP, as well as the spatial database development methods such as OO4O and ArcSDE based on ArcGIS software packages. Meanwhile, according to Software Engineering principles, a solution of Urban Earthquake Emergency Response Decision Support Systems based on GIS technologies have also been proposed, which include the systems logical structures, the technical routes,the system realization methods and function structures etc. Finally, the testing systems user interfaces have also been offered in the paper.

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.

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

NASA Technical Reports Server (NTRS)

Breininger, David; Duncan, Brean; Eaton, Mitchell; Johnson, Fred; Nichols, James

2014-01-01

Land cover modeling is used to inform land management, but most often via a two-step process where science informs how management alternatives can influence resources and then decision makers can use this to make decisions. A more efficient process is to directly integrate science and decision making, where science allows us to learn to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuels monitoring with decision making focused on dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy, but habitat trajectories suggest tradeoffs. Knowledge about system responses to actions can be informed by applying competing management actions to different land units in the same system state and by ideas about fire behavior. Monitoring and management integration is important to optimize state-specific management decisions and increase knowledge about system responses. We believe this approach has broad utility for and cover modeling programs intended to inform decision making.

Integrated environmental monitoring and simulation system for use as a management decision support tool in urban areas.

PubMed

Fatta, D; Naoum, D; Loizidou, M

2002-04-01

Leachates are generated as a result of water or other liquid passing through waste at a landfill site. These contaminated liquids originate from a number of sources, including the water produced during the decomposition of the waste as well as rain-fall which penetrates the waste and dissolves the material with which it comes into contact. The penetration of the rain-water depends on the nature of the landfill (e.g. surface characteristics, type and quantity of vegetation, gradient of layers, etc). The uncontrolled infiltration of leachate into the vadose (unsaturated) zone and finally into the saturated zone (groundwater) is considered to be the most serious environmental impact of a landfill. In the present paper the water flow and the pollutant transport characteristics of the Ano Liosia Landfill site in Athens (Greece) were simulated by creating a model of groundwater flows and contaminant transport. A methodology for the model is presented. The model was then integrated into the Ecosim system which is a prototype funded by the EU, (Directorate General XIII: Telematics and Environment). This is an integrated environmental monitoring and modeling system, which supports the management of environmental planning in urban areas.

Methodology and application of combined watershed and ground-water models in Kansas

USGS Publications Warehouse

Sophocleous, M.; Perkins, S.P.

2000-01-01

Increased irrigation in Kansas and other regions during the last several decades has caused serious water depletion, making the development of comprehensive strategies and tools to resolve such problems increasingly important. This paper makes the case for an intermediate complexity, quasi-distributed, comprehensive, large-watershed model, which falls between the fully distributed, physically based hydrological modeling system of the type of the SHE model and the lumped, conceptual rainfall-runoff modeling system of the type of the Stanford watershed model. This is achieved by integrating the quasi-distributed watershed model SWAT with the fully-distributed ground-water model MODFLOW. The advantage of this approach is the appreciably smaller input data requirements and the use of readily available data (compared to the fully distributed, physically based models), the statistical handling of watershed heterogeneities by employing the hydrologic-response-unit concept, and the significantly increased flexibility in handling stream-aquifer interactions, distributed well withdrawals, and multiple land uses. The mechanics of integrating the component watershed and ground-water models are outlined, and three real-world management applications of the integrated model from Kansas are briefly presented. Three different aspects of the integrated model are emphasized: (1) management applications of a Decision Support System for the integrated model (Rattlesnake Creek subbasin); (2) alternative conceptual models of spatial heterogeneity related to the presence or absence of an underlying aquifer with shallow or deep water table (Lower Republican River basin); and (3) the general nature of the integrated model linkage by employing a watershed simulator other than SWAT (Wet Walnut Creek basin). These applications demonstrate the practicality and versatility of this relatively simple and conceptually clear approach, making public acceptance of the integrated watershed modeling system much easier. This approach also enhances model calibration and thus the reliability of model results. (C) 2000 Elsevier Science B.V.Increased irrigation in Kansas and other regions during the last several decades has caused serious water depletion, making the development of comprehensive strategies and tools to resolve such problems increasingly important. This paper makes the case for an intermediate complexity, quasi-distributed, comprehensive, large-watershed model, which falls between the fully distributed, physically based hydrological modeling system of the type of the SHE model and the lumped, conceptual rainfall-runoff modeling system of the type of the Stanford watershed model. This is achieved by integrating the quasi-distributed watershed model SWAT with the fully-distributed ground-water model MODFLOW. The advantage of this approach is the appreciably smaller input data requirements and the use of readily available data (compared to the fully distributed, physically based models), the statistical handling of watershed heterogeneities by employing the hydrologic-response-unit concept, and the significantly increased flexibility in handling stream-aquifer interactions, distributed well withdrawals, and multiple land uses. The mechanics of integrating the component watershed and ground-water models are outlined, and three real-world management applications of the integrated model from Kansas are briefly presented. Three different aspects of the integrated model are emphasized: (1) management applications of a Decision Support System for the integrated model (Rattlesnake Creek subbasin); (2) alternative conceptual models of spatial heterogeneity related to the presence or absence of an underlying aquifer with shallow or deep water table (Lower Republican River basin); and (3) the general nature of the integrated model linkage by employing a watershed simulator other than SWAT (Wet Walnut Creek basin). These applications demonstrate the practicality and ve

Executive Decision Making: Using Microcomputers in Budget Planning.

ERIC Educational Resources Information Center

Hoffman, Roslyn; Robinson, Lucinda

The successful integration of microcomputer support to help prepare for an anticipated budget crisis at the University of Illinois at Chicago is described. The IBM Personal Computer and VisiCalc software were key tools in the decision support system. When campus executives were instructed to cut budgets and reallocate funds to produce a…

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-02-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning, supporting ecosystem-based management.

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-12-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning, supporting ecosystem-based management.

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

NASA Astrophysics Data System (ADS)

Dietrich, Jörg; Funke, Markus

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

An Integrated Gate Turnaround Management Concept Leveraging Big Data/Analytics for NAS Performance Improvements

NASA Technical Reports Server (NTRS)

Chung, William; Chachad, Girish; Hochstetler, Ronald

2016-01-01

The Integrated Gate Turnaround Management (IGTM) concept was developed to improve the gate turnaround performance at the airport by leveraging relevant historical data to support optimization of airport gate operations, which include: taxi to the gate, gate services, push back, taxi to the runway, and takeoff, based on available resources, constraints, and uncertainties. By analyzing events of gate operations, primary performance dependent attributes of these events were identified for the historical data analysis such that performance models can be developed based on uncertainties to support descriptive, predictive, and prescriptive functions. A system architecture was developed to examine system requirements in support of such a concept. An IGTM prototype was developed to demonstrate the concept using a distributed network and collaborative decision tools for stakeholders to meet on time pushback performance under uncertainties.

A Developmental Approach to the Teaching of Ethical Decision Making.

ERIC Educational Resources Information Center

Neukrug, Edward S.

1996-01-01

Examines the newly adopted code of ethics, reviews some ethical decision-making models, and hypothesizes how the maturity of a student might mediate the effective use of codes and of decision-making models. Provides a model for human service educators that integrates ethical guidelines and ethical decision-making models. (RJM)

Inexact Socio-Dynamic Modeling of Groundwater Contamination Management

NASA Astrophysics Data System (ADS)

Vesselinov, V. V.; Zhang, X.

2015-12-01

Groundwater contamination may alter the behaviors of the public such as adaptation to such a contamination event. On the other hand, social behaviors may affect groundwater contamination and associated risk levels such as through changing ingestion amount of groundwater due to the contamination. Decisions should consider not only the contamination itself, but also social attitudes on such contamination events. Such decisions are inherently associated with uncertainty, such as subjective judgement from decision makers and their implicit knowledge on selection of whether to supply water or reduce the amount of supplied water under the scenario of the contamination. A socio-dynamic model based on the theories of information-gap and fuzzy sets is being developed to address the social behaviors facing the groundwater contamination and applied to a synthetic problem designed based on typical groundwater remediation sites where the effects of social behaviors on decisions are investigated and analyzed. Different uncertainties including deep uncertainty and vague/ambiguous uncertainty are effectively and integrally addressed. The results can provide scientifically-defensible decision supports for groundwater management in face of the contamination.

A multiobjective decision support/numerical modeling approach for design and evaluation of shallow landfill burial systems

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

Ascough, II, James Clifford

1992-05-01

The capability to objectively evaluate design performance of shallow landfill burial (SLB) systems is of great interest to diverse scientific disciplines, including hydrologists, engineers, environmental scientists, and SLB regulators. The goal of this work was to develop and validate a procedure for the nonsubjective evaluation of SLB designs under actual or simulated environmental conditions. A multiobjective decision module (MDM) based on scoring functions (Wymore, 1988) was implemented to evaluate SLB design performance. Input values to the MDM are provided by hydrologic models. The MDM assigns a total score to each SLB design alternative, thereby allowing for rapid and repeatable designmore » performance evaluation. The MDM was validated for a wide range of SLB designs under different climatic conditions. Rigorous assessment of SLB performance also requires incorporation of hydrologic probabilistic analysis and hydrologic risk into the overall design. This was accomplished through the development of a frequency analysis module. The frequency analysis module allows SLB design event magnitudes to be calculated based on the hydrologic return period. The multiobjective decision and freqeuncy anslysis modules were integrated in a decision support system (DSS) framework, SLEUTH (Shallow Landfill Evaluation Using Transport and Hydrology). SLEUTH is a Microsoft Windows {trademark} application, and is written in the Knowledge Pro Windows (Knowledge Garden, Inc., 1991) development language.« less

Decision support systems in water and wastewater treatment process selection and design: a review.

PubMed

Hamouda, M A; Anderson, W B; Huck, P M

2009-01-01

The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.

Effective Team Support: From Task and Cognitive Modeling to Software Agents for Time-Critical Complex Work Environments

NASA Technical Reports Server (NTRS)

Remington, Roger W. (Technical Monitor); John, Bonnie E.; Sycara, Katia

2005-01-01

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in completing a system for empirical data collection, cognitive modeling, and the building of software agents to support a team's tasks, and in running experiments for the collection of baseline data.

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

USGS Publications Warehouse

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

2002-01-01

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

Clinical-decision support based on medical literature: A complex network approach

NASA Astrophysics Data System (ADS)

Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin

2016-10-01

In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.