Decision-support systems for natural-hazards and land-management issues

USGS Publications Warehouse

Dinitz, Laura; Forney, William; Byrd, Kristin

2012-01-01

Scientists at the USGS Western Geographic Science Center are developing decision-support systems (DSSs) for natural-hazards and land-management issues. DSSs are interactive computer-based tools that use data and models to help identify and solve problems. These systems can provide crucial support to policymakers, planners, and communities for making better decisions about long-term natural hazards mitigation and land-use planning.

Design and realization of tourism spatial decision support system based on GIS

NASA Astrophysics Data System (ADS)

Ma, Zhangbao; Qi, Qingwen; Xu, Li

2008-10-01

In this paper, the existing problems of current tourism management information system are analyzed. GIS, tourism as well as spatial decision support system are introduced, and the application of geographic information system technology and spatial decision support system to tourism management and the establishment of tourism spatial decision support system based on GIS are proposed. System total structure, system hardware and software environment, database design and structure module design of this system are introduced. Finally, realization methods of this systemic core functions are elaborated.

Decision support methods for the environmental assessment of contamination at mining sites.

PubMed

Jordan, Gyozo; Abdaal, Ahmed

2013-09-01

Polluting mine accidents and widespread environmental contamination associated with historic mining in Europe and elsewhere has triggered the improvement of related environmental legislation and of the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background pollution associated with natural mineral deposits, industrial activities and contamination located in the three-dimensional sub-surface space, the problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites and abandoned mines in historic regions like Europe. These mining-specific problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to review and evaluate some of the decision support methods that have been developed and applied to mining contamination. In this paper, only those methods that are both efficient decision support tools and provide a 'holistic' approach to the complex problem as well are considered. These tools are (1) landscape ecology, (2) industrial ecology, (3) landscape geochemistry, (4) geo-environmental models, (5) environmental impact assessment, (6) environmental risk assessment, (7) material flow analysis and (8) life cycle assessment. This unique inter-disciplinary study should enable both the researcher and the practitioner to obtain broad view on the state-of-the-art of decision support methods for the environmental assessment of contamination at mine sites. Documented examples and abundant references are also provided.

Do clients' problem-solving appraisals predict career counseling outcomes or vice versa? A reanalysis of Heppner, et al.

PubMed

Lee, Dong-Gwi; Park, Hyun-Joo; Heppner, Mary J

2009-12-01

Using Heppner, et al.'s data from 2004, this study tested career counseling clients in the United States on problem-solving appraisal scores and career-related variables. A cross-lagged panel design with structural equation modeling was used. Results supported the link between clients' precounseling problem-solving appraisal scores and career outcome. This finding held for career decision-making, but not for vocational identity. The study provided further support for Heppner, et al.'s findings, highlighting the influential role of clients' problem-solving appraisals in advancing their career decision-making processes.

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 ...

Toward the Modularization of Decision Support Systems

NASA Astrophysics Data System (ADS)

Raskin, R. G.

2009-12-01

Decision support systems are typically developed entirely from scratch without the use of modular components. This “stovepiped” approach is inefficient and costly because it prevents a developer from leveraging the data, models, tools, and services of other developers. Even when a decision support component is made available, it is difficult to know what problem it solves, how it relates to other components, or even that the component exists, The Spatial Decision Support (SDS) Consortium was formed in 2008 to organize the body of knowledge in SDS within a common portal. The portal identifies the canonical steps in the decision process and enables decision support components to be registered, categorized, and searched. This presentation describes how a decision support system can be assembled from modular models, data, tools and services, based on the needs of the Earth science application.

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.

Prioritization of information using decision support systems for seismic risk in Bucharest city

NASA Astrophysics Data System (ADS)

Armas, Iuliana; Gheorghe, Diana

2014-05-01

Nowadays, because of the ever increasing volume of information, policymakers are faced with decision making problems. Achieving an objective and suitable decision making may become a challenge. In such situations decision support systems (DSS) have been developed. DSS can assist in the decision making process, offering support on how a decision should be made, rather than what decision should be made (Simon, 1979). This in turn potentially involves a huge number of stakeholders and criteria. Regarding seismic risk, Bucharest City is highly vulnerable (Mandrescu et al., 2007). The aim of this study is to implement a spatial decision support system in order to secure a suitable shelter in case of an earthquake occurrence in the historical centre of Bucharest City. In case of a seismic risk, a shelter is essential for sheltering people who lost their homes or whose homes are in danger of collapsing while people at risk receive first aid in the post-disaster phase. For the present study, the SMCE Module for ILWIS 3.4 was used. The methodology included structuring the problem by creating a decision tree, standardizing and weighting of the criteria. The results showed that the most suitable buildings are Tania Hotel, Hanul lui Manuc, The National Bank of Romania, The Romanian Commercial Bank and The National History Museum.

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

Supporting Valid Decision Making: Uses and Misuses of Assessment Data within the Context of RtI

ERIC Educational Resources Information Center

Ball, Carrie R.; Christ, Theodore J.

2012-01-01

Within an RtI problem-solving context, assessment and decision making generally center around the tasks of problem identification, problem analysis, progress monitoring, and program evaluation. We use this framework to discuss the current state of the literature regarding curriculum based measurement, its technical properties, and its utility for…

Supporting multi-stakeholder environmental decisions.

PubMed

Hajkowicz, Stefan A

2008-09-01

This paper examines how multiple criteria analysis (MCA) can be used to support multi-stakeholder environmental management decisions. It presents a study through which 48 stakeholders from environmental, primary production and community interest groups used MCA to prioritise 30 environmental management problems in the Mackay-Whitsunday region of Queensland, Australia. The MCA model, with procedures for aggregating multi-stakeholder output, was used to inform a final decision on the priority of the region's environmental management problems. The result was used in the region's environmental management plan as required under Australia's Natural Heritage Trust programme. The study shows how relatively simple MCA methods can help stakeholders make group decisions, even when they hold strongly conflicting preferences.

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.

Decision making and problem solving with computer assistance

NASA Technical Reports Server (NTRS)

Kraiss, F.

1980-01-01

In modern guidance and control systems, the human as manager, supervisor, decision maker, problem solver and trouble shooter, often has to cope with a marginal mental workload. To improve this situation, computers should be used to reduce the operator from mental stress. This should not solely be done by increased automation, but by a reasonable sharing of tasks in a human-computer team, where the computer supports the human intelligence. Recent developments in this area are summarized. It is shown that interactive support of operator by intelligent computer is feasible during information evaluation, decision making and problem solving. The applied artificial intelligence algorithms comprehend pattern recognition and classification, adaptation and machine learning as well as dynamic and heuristic programming. Elementary examples are presented to explain basic principles.

Emergency physicians' attitudes and preferences regarding computed tomography, radiation exposure, and imaging decision support.

PubMed

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

2014-07-01

Although computerized decision support for imaging is often recommended for optimizing computed tomography (CT) use, no studies have evaluated emergency physicians' (EPs') preferences regarding computerized decision support in the emergency department (ED). In this needs assessment, the authors sought to determine if EPs view overutilization as a problem, if they want decision support, and if so, the kinds of support they prefer. A 42-item, Web-based survey of EPs was developed and used to measure EPs' attitudes, preferences, and knowledge. Key contacts at local EDs sent letters describing the study to their physicians. Exploratory principal components analysis (PCA) was used to determine the underlying factor structure of multi-item scales, Cronbach's alpha was used to measure internal consistency of items on a scale, Spearman correlations were used to describe bivariate associations, and multivariable linear regression analysis was used to identify variables independently associated with physician interest in decision support. Of 235 surveys sent, 155 (66%) EPs responded. Five factors emerged from the PCA. EPs felt that: 1) CT overutilization is a problem in the ED (α = 0.75); 2) a patient's cumulative CT study count affects decisions of whether and what type of imaging study to order only some of the time (α = 0.75); 3) knowledge that a patient has had prior CT imaging for the same indication makes EPs less likely to order a CT (α = 0.42); 4) concerns about malpractice, patient satisfaction, or insistence on CTs affect CT ordering decisions (α = 0.62); and 5) EPs want decision support before ordering CTs (α = 0.85). Performance on knowledge questions was poor, with only 18% to 39% correctly responding to each of the three multiple-choice items about effective radiation doses of chest radiograph and single-pass abdominopelvic CT, as well as estimated increased risk of cancer from a 10-mSv exposure. Although EPs wanted information on patients' cumulative exposures, they feel inadequately familiar with this information to make use of it clinically. If provided with patients' cumulative radiation exposures from CT, 87% of EPs said that they would use this information to discuss imaging options with their patients. In the multiple regression model, which included all variables associated with interest in decision support at p < 0.10 in bivariate tests, items independently associated with EPs' greater interest in all types of decision support proposed included lower total knowledge scores, greater frequency that cumulative CT study count affects EP's decision to order CTs, and greater agreement that overutilization of CT is a problem and that awareness of multiple prior CTs for a given indication affects CT ordering decisions. Emergency physicians view overutilization of CT scans as a problem with potential for improvement in the ED and would like to have more information to discuss risks with their patients. EPs are interested in all types of imaging decision support proposed to help optimize imaging ordering in the ED and to reduce radiation to their patients. Findings reveal several opportunities that could potentially affect CT utilization. © 2014 by the Society for Academic Emergency Medicine.

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

PubMed Central

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

2014-01-01

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

A decision-based perspective for the design of methods for systems design

NASA Technical Reports Server (NTRS)

Mistree, Farrokh; Muster, Douglas; Shupe, Jon A.; Allen, Janet K.

1989-01-01

Organization of material, a definition of decision based design, a hierarchy of decision based design, the decision support problem technique, a conceptual model design that can be manufactured and maintained, meta-design, computer-based design, action learning, and the characteristics of decisions are among the topics covered.

Decision analysis framing study; in-valley drainage management strategies for the western San Joaquin Valley, California

USGS Publications Warehouse

Presser, Theresa S.; Jenni, Karen E.; Nieman, Timothy; Coleman, James

2010-01-01

Constraints on drainage management in the western San Joaquin Valley and implications of proposed approaches to management were recently evaluated by the U.S. Geological Survey (USGS). The USGS found that a significant amount of data for relevant technical issues was available and that a structured, analytical decision support tool could help optimize combinations of specific in-valley drainage management strategies, address uncertainties, and document underlying data analysis for future use. To follow-up on USGS's technical analysis and to help define a scientific basis for decisionmaking in implementing in-valley drainage management strategies, this report describes the first step (that is, a framing study) in a Decision Analysis process. In general, a Decision Analysis process includes four steps: (1) problem framing to establish the scope of the decision problem(s) and a set of fundamental objectives to evaluate potential solutions, (2) generation of strategies to address identified decision problem(s), (3) identification of uncertainties and their relationships, and (4) construction of a decision support model. Participation in such a systematic approach can help to promote consensus and to build a record of qualified supporting data for planning and implementation. In December 2008, a Decision Analysis framing study was initiated with a series of meetings designed to obtain preliminary input from key stakeholder groups on the scope of decisions relevant to drainage management that were of interest to them, and on the fundamental objectives each group considered relevant to those decisions. Two key findings of this framing study are: (1) participating stakeholders have many drainage management objectives in common; and (2) understanding the links between drainage management and water management is necessary both for sound science-based decisionmaking and for resolving stakeholder differences about the value of proposed drainage management solutions. Citing ongoing legal processes associated with drainage management in the western San Joaquin Valley, the U.S. Bureau of Reclamation (USBR) withdrew from the Decision Analysis process early in the proceedings. Without the involvement of the USBR, the USGS discontinued further development of this study.

Involving Students in Natural Resource Decision-Making Groups.

ERIC Educational Resources Information Center

Ellsworth, Peter; Ellsworth, Judith

2001-01-01

Describes the Coordinated Resource Management (CRM) in the Classroom project, in which Wyoming high school students work on an authentic natural resource problem, using a decision-making process based on consensus to reach agreement on solutions to the problem. Notes implementation issues of professional development and support, and considers…

Legal and Constitutional Problems of Public Support for Nonpublic Schools.

ERIC Educational Resources Information Center

Whelan, Charles M.; Freund, Paul A.

Two authors analyze the problems facing aid to nonpublic school education and review relevant court decisions, emphasizing the latest Supreme Court decisions on the subject. Charles M. Whelan provides an analytical framework for determining the constitutionality of various assistance forms. He suggests that each program should be submitted to…

Triple Value System Dynamics Modeling to Help Stakeholders Engage with Food-Energy-Water Problems

EPA Science Inventory

Triple Value (3V) Community scoping projects and Triple Value Simulation (3VS) models help decision makers and stakeholders apply systems-analysis methodology to complex problems related to food production, water quality, and energy use. 3VS models are decision support tools that...

Linking guidelines to Electronic Health Record design for improved chronic disease management.

PubMed

Barretto, Sistine A; Warren, Jim; Goodchild, Andrew; Bird, Linda; Heard, Sam; Stumptner, Markus

2003-01-01

The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and workflow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR.

Linking Guidelines to Electronic Health Record Design for Improved Chronic Disease Management

PubMed Central

Barretto, Sistine A.; Warren, Jim; Goodchild, Andrew; Bird, Linda; Heard, Sam; Stumptner, Markus

2003-01-01

The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and work-flow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR. PMID:14728135

Human Cognitive Limitations. Broad, Consistent, Clinical Application of Physiological Principles Will Require Decision Support.

PubMed

Morris, Alan H

2018-02-01

Our education system seems to fail to enable clinicians to broadly understand core physiological principles. The emphasis on reductionist science, including "omics" branches of research, has likely contributed to this decrease in understanding. Consequently, clinicians cannot be expected to consistently make clinical decisions linked to best physiological evidence. This is a large-scale problem with multiple determinants, within an even larger clinical decision problem: the failure of clinicians to consistently link their decisions to best evidence. Clinicians, like all human decision-makers, suffer from significant cognitive limitations. Detailed context-sensitive computer protocols can generate personalized medicine instructions that are well matched to individual patient needs over time and can partially resolve this problem.

Decision-Making under Criteria Uncertainty

NASA Astrophysics Data System (ADS)

Kureychik, V. M.; Safronenkova, I. B.

2018-05-01

Uncertainty is an essential part of a decision-making procedure. The paper deals with the problem of decision-making under criteria uncertainty. In this context, decision-making under uncertainty, types and conditions of uncertainty were examined. The decision-making problem under uncertainty was formalized. A modification of the mathematical decision support method under uncertainty via ontologies was proposed. A critical distinction of the developed method is ontology usage as its base elements. The goal of this work is a development of a decision-making method under criteria uncertainty with the use of ontologies in the area of multilayer board designing. This method is oriented to improvement of technical-economic values of the examined domain.

Managing Decisions on Changes in the Virtual Enterprise Evolution

NASA Astrophysics Data System (ADS)

Drissen-Silva, Marcus Vinicius; Rabelo, Ricardo José

VE evolution deals with problems that happen during the VE operation and that put on risk planned results. This requires the application of problem-solving mechanisms to guarantee the construction of a new but feasible VE plan. Grounded on Project Management and Decision Support Systems foundations, this paper proposes a distributed collaborative decision support system to manage the VE evolution. Its main rationale is that VE’s members are autonomous and hence that all the affected partners should discuss about the necessary changes on the current VE’s plan. In the proposed approach, this discussion is guided by a decision protocol, and the impact of decisions can be evaluated. Results of a first prototype implementation are presented and discussed, with a special focus on the part which regulates the argumentation, voting and comparison of possible solutions.

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

PubMed

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

PubMed Central

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

OPTIMIZING USABILITY OF AN ECONOMIC DECISION SUPPORT TOOL: PROTOTYPE OF THE EQUIPT TOOL.

PubMed

Cheung, Kei Long; Hiligsmann, Mickaël; Präger, Maximilian; Jones, Teresa; Józwiak-Hagymásy, Judit; Muñoz, Celia; Lester-George, Adam; Pokhrel, Subhash; López-Nicolás, Ángel; Trapero-Bertran, Marta; Evers, Silvia M A A; de Vries, Hein

2018-01-01

Economic decision-support tools can provide valuable information for tobacco control stakeholders, but their usability may impact the adoption of such tools. This study aims to illustrate a mixed-method usability evaluation of an economic decision-support tool for tobacco control, using the EQUIPT ROI tool prototype as a case study. A cross-sectional mixed methods design was used, including a heuristic evaluation, a thinking aloud approach, and a questionnaire testing and exploring the usability of the Return of Investment tool. A total of sixty-six users evaluated the tool (thinking aloud) and completed the questionnaire. For the heuristic evaluation, four experts evaluated the interface. In total twenty-one percent of the respondents perceived good usability. A total of 118 usability problems were identified, from which twenty-six problems were categorized as most severe, indicating high priority to fix them before implementation. Combining user-based and expert-based evaluation methods is recommended as these were shown to identify unique usability problems. The evaluation provides input to optimize usability of a decision-support tool, and may serve as a vantage point for other developers to conduct usability evaluations to refine similar tools before wide-scale implementation. Such studies could reduce implementation gaps by optimizing usability, enhancing in turn the research impact of such interventions.

Group Decision Support System to Aid the Process of Design and Maintenance of Large Scale Systems

DTIC Science & Technology

1992-03-23

from a fuzzy set of user requirements. The overall objective of the project is to develop a system combining the characteristics of a compact computer... AHP ) for hierarchical prioritization. 4) Individual Evaluation and Selection of Alternatives - Allows the decision maker to individually evaluate...its concept of outranking relations. The AHP method supports complex decision problems by successively decomposing and synthesizing various elements

Relational Algebra in Spatial Decision Support Systems Ontologies.

PubMed

Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos

2017-01-01

Decision Support Systems (DSS) is a powerful tool, for facilitates researchers to choose the correct decision based on their final results. Especially in medical cases where doctors could use these systems, to overcome the problem with the clinical misunderstanding. Based on these systems, queries must be constructed based on the particular questions that doctors must answer. In this work, combination between questions and queries would be presented via relational algebra.

Decision support system for nursing management control

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

Ernst, C.J.

A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.

A Decision Support System for Concrete Bridge Maintenance

NASA Astrophysics Data System (ADS)

Rashidi, Maria; Lemass, Brett; Gibson, Peter

2010-05-01

The maintenance of bridges as a key element in transportation infrastructure has become a major concern for asset managers and society due to increasing traffic volumes, deterioration of existing bridges and well-publicised bridge failures. A pivotal responsibility for asset managers in charge of bridge remediation is to identify the risks and assess the consequences of remediation programs to ensure that the decisions are transparent and lead to the lowest predicted losses in recognized constraint areas. The ranking of bridge remediation treatments can be quantitatively assessed using a weighted constraint approach to structure the otherwise ill-structured phases of problem definition, conceptualization and embodiment [1]. This Decision Support System helps asset managers in making the best decision with regards to financial limitations and other dominant constraints imposed upon the problem at hand. The risk management framework in this paper deals with the development of a quantitative intelligent decision support system for bridge maintenance which has the ability to provide a source for consistent decisions through selecting appropriate remediation treatments based upon cost, service life, product durability/sustainability, client preferences, legal and environmental constraints. Model verification and validation through industry case studies is ongoing.

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Agent-Centric Approach for Cybersecurity Decision-Support with Partial Observability

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

Tipireddy, Ramakrishna; Chatterjee, Samrat; Paulson, Patrick R.

Generating automated cyber resilience policies for real-world settings is a challenging research problem that must account for uncertainties in system state over time and dynamics between attackers and defenders. In addition to understanding attacker and defender motives and tools, and identifying “relevant” system and attack data, it is also critical to develop rigorous mathematical formulations representing the defender’s decision-support problem under uncertainty. Game-theoretic approaches involving cyber resource allocation optimization with Markov decision processes (MDP) have been previously proposed in the literature. Moreover, advancements in reinforcement learning approaches have motivated the development of partially observable stochastic games (POSGs) in various multi-agentmore » problem domains with partial information. Recent advances in cyber-system state space modeling have also generated interest in potential applicability of POSGs for cybersecurity. However, as is the case in strategic card games such as poker, research challenges using game-theoretic approaches for practical cyber defense applications include: 1) solving for equilibrium and designing efficient algorithms for large-scale, general problems; 2) establishing mathematical guarantees that equilibrium exists; 3) handling possible existence of multiple equilibria; and 4) exploitation of opponent weaknesses. Inspired by advances in solving strategic card games while acknowledging practical challenges associated with the use of game-theoretic approaches in cyber settings, this paper proposes an agent-centric approach for cybersecurity decision-support with partial system state observability.« less

Using ILOG OPL-CPLEX and ILOG Optimization Decision Manager (ODM) to Develop Better Models

NASA Astrophysics Data System (ADS)

2008-10-01

This session will provide an in-depth overview on building state-of-the-art decision support applications and models. You will learn how to harness the full power of the ILOG OPL-CPLEX-ODM Development System (ODMS) to develop optimization models and decision support applications that solve complex problems ranging from near real-time scheduling to long-term strategic planning. We will demonstrate how to use ILOG's Open Programming Language (OPL) to quickly model problems solved by ILOG CPLEX, and how to use ILOG ODM to gain further insight about the model. By the end of the session, attendees will understand how to take advantage of the powerful combination of ILOG OPL (to describe an optimization model) and ILOG ODM (to understand the relationships between data, decision variables and constraints).

Water flow algorithm decision support tool for travelling salesman problem

NASA Astrophysics Data System (ADS)

Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd

2016-08-01

This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.

An Internationally Consented Standard for Nursing Process-Clinical Decision Support Systems in Electronic Health Records.

PubMed

Müller-Staub, Maria; de Graaf-Waar, Helen; Paans, Wolter

2016-11-01

Nurses are accountable to apply the nursing process, which is key for patient care: It is a problem-solving process providing the structure for care plans and documentation. The state-of-the art nursing process is based on classifications that contain standardized concepts, and therefore, it is named Advanced Nursing Process. It contains valid assessments, nursing diagnoses, interventions, and nursing-sensitive patient outcomes. Electronic decision support systems can assist nurses to apply the Advanced Nursing Process. However, nursing decision support systems are missing, and no "gold standard" is available. The study aim is to develop a valid Nursing Process-Clinical Decision Support System Standard to guide future developments of clinical decision support systems. In a multistep approach, a Nursing Process-Clinical Decision Support System Standard with 28 criteria was developed. After pilot testing (N = 29 nurses), the criteria were reduced to 25. The Nursing Process-Clinical Decision Support System Standard was then presented to eight internationally known experts, who performed qualitative interviews according to Mayring. Fourteen categories demonstrate expert consensus on the Nursing Process-Clinical Decision Support System Standard and its content validity. All experts agreed the Advanced Nursing Process should be the centerpiece for the Nursing Process-Clinical Decision Support System and should suggest research-based, predefined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions, and patient outcomes.

Multi-objective optimization of solid waste flows: environmentally sustainable strategies for municipalities.

PubMed

Minciardi, Riccardo; Paolucci, Massimo; Robba, Michela; Sacile, Roberto

2008-11-01

An approach to sustainable municipal solid waste (MSW) management is presented, with the aim of supporting the decision on the optimal flows of solid waste sent to landfill, recycling and different types of treatment plants, whose sizes are also decision variables. This problem is modeled with a non-linear, multi-objective formulation. Specifically, four objectives to be minimized have been taken into account, which are related to economic costs, unrecycled waste, sanitary landfill disposal and environmental impact (incinerator emissions). An interactive reference point procedure has been developed to support decision making; these methods are considered appropriate for multi-objective decision problems in environmental applications. In addition, interactive methods are generally preferred by decision makers as they can be directly involved in the various steps of the decision process. Some results deriving from the application of the proposed procedure are presented. The application of the procedure is exemplified by considering the interaction with two different decision makers who are assumed to be in charge of planning the MSW system in the municipality of Genova (Italy).

Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

USGS Publications Warehouse

Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

2006-01-01

There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

Decision Making: New Paradigm for Education.

ERIC Educational Resources Information Center

Wales, Charles E.; And Others

1986-01-01

Defines education's new paradigm as schooling based on decision making, the critical thinking skills serving it, and the knowledge base supporting it. Outlines a model decision-making process using a hypothetical breakfast problem; a late riser chooses goals, generates ideas, develops an action plan, and implements and evaluates it. (4 references)…

Goals, dilemmas and assumptions in infant feeding education and support. Applying theory of constraints thinking tools to develop new priorities for action.

PubMed

Trickey, Heather; Newburn, Mary

2014-01-01

Three important infant feeding support problems are addressed: (1) mothers who use formula milk can feel undersupported and judged; (2) mothers can feel underprepared for problems with breastfeeding; and (3) many mothers who might benefit from breastfeeding support do not access help. Theory of constraints (TOC) is used to examine these problems in relation to ante-natal education and post-natal support. TOC suggests that long-standing unresolved problems or 'undesirable effects' in any system (in this case a system to provide education and support) are caused by conflicts, or dilemmas, within the system, which might not be explicitly acknowledged. Potential solutions are missed by failure to question assumptions which, when interrogated, often turn out to be invalid. Three core dilemmas relating to the three problems are identified, articulated and explored using TOC methodology. These are whether to: (1) promote feeding choice or to promote breastfeeding; (2) present breastfeeding positively, as straightforward and rewarding, or focus on preparing mothers for problems; and (3) offer support proactively or ensure that mothers themselves initiate requests for support. Assumptions are identified and interrogated, leading to clarified priorities for action relating to each problem. These are (1) shift the focus from initial decision-making towards support for mothers throughout their feeding journeys, enabling and protecting decisions to breastfeed as one aspect of ongoing support; (2) to promote the concept of an early-weeks investment and adjustment period during which breastfeeding is established; and (3) to develop more proactive mother-centred models of support for all forms of infant feeding. © 2012 John Wiley & Sons Ltd.

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.

A robust optimisation approach to the problem of supplier selection and allocation in outsourcing

NASA Astrophysics Data System (ADS)

Fu, Yelin; Keung Lai, Kin; Liang, Liang

2016-03-01

We formulate the supplier selection and allocation problem in outsourcing under an uncertain environment as a stochastic programming problem. Both the decision-maker's attitude towards risk and the penalty parameters for demand deviation are considered in the objective function. A service level agreement, upper bound for each selected supplier's allocation and the number of selected suppliers are considered as constraints. A novel robust optimisation approach is employed to solve this problem under different economic situations. Illustrative examples are presented with managerial implications highlighted to support decision-making.

Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTEGE-II to protocol-based decision support.

PubMed

Tu, S W; Eriksson, H; Gennari, J H; Shahar, Y; Musen, M A

1995-06-01

PROTEGE-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTEGE-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTEGE-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTEGE-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.

When to Renew Software Licences at HPC Centres? A Mathematical Analysis

NASA Astrophysics Data System (ADS)

Baolai, Ge; MacIsaac, Allan B.

2010-11-01

In this paper we study a common problem faced by many high performance computing (HPC) centres: When and how to renew commercial software licences. Software vendors often sell perpetual licences along with forward update and support contracts at an additional, annual cost. Every year or so, software support personnel and the budget units of HPC centres are required to make the decision of whether or not to renew such support, and usually such decisions are made intuitively. The total cost for a continuing support contract can, however, be costly. One might therefore want a rational answer to the question of whether the option for a renewal should be exercised and when. In an attempt to study this problem within a market framework, we present the mathematical problem derived for the day to day operation of a hypothetical HPC centre that charges for the use of software packages. In the mathematical model, we assume that the uncertainty comes from the demand, number of users using the packages, as well as the price. Further we assume the availability of up to date software versions may also affect the demand. We develop a renewal strategy that aims to maximize the expected profit from the use the software under consideration. The derived problem involves a decision tree, which constitutes a numerical procedure that can be processed in parallel.

Design, implementation, use, and preliminary evaluation of SEBASTIAN, a standards-based Web service for clinical decision support.

PubMed

Kawamoto, Kensaku; Lobach, David F

2005-01-01

Despite their demonstrated ability to improve care quality, clinical decision support systems are not widely used. In part, this limited use is due to the difficulty of sharing medical knowledge in a machine-executable format. To address this problem, we developed a decision support Web service known as SEBASTIAN. In SEBASTIAN, individual knowledge modules define the data requirements for assessing a patient, the conclusions that can be drawn using that data, and instructions on how to generate those conclusions. Using standards-based XML messages transmitted over HTTP, client decision support applications provide patient data to SEBASTIAN and receive patient-specific assessments and recommendations. SEBASTIAN has been used to implement four distinct decision support systems; an architectural overview is provided for one of these systems. Preliminary assessments indicate that SEBASTIAN fulfills all original design objectives, including the re-use of executable medical knowledge across diverse applications and care settings, the straightforward authoring of knowledge modules, and use of the framework to implement decision support applications with significant clinical utility.

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

PubMed

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

2017-01-01

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

Use of case-based reasoning to enhance intensive management of patients on insulin pump therapy.

PubMed

Schwartz, Frank L; Shubrook, Jay H; Marling, Cynthia R

2008-07-01

This study was conducted to develop case-based decision support software to improve glucose control in patients with type 1 diabetes mellitus (T1DM) on insulin pump therapy. While the benefits of good glucose control are well known, achieving and maintaining good glucose control remains a difficult task. Case-based decision support software may assist by recalling past problems in glucose control and their associated therapeutic adjustments. Twenty patients with T1DM on insulin pumps were enrolled in a 6-week study. Subjects performed self-glucose monitoring and provided daily logs via the Internet, tracking insulin dosages, work, sleep, exercise, meals, stress, illness, menstrual cycles, infusion set changes, pump problems, hypoglycemic episodes, and other events. Subjects wore a continuous glucose monitoring system at weeks 1, 3, and 6. Clinical data were interpreted by physicians, who explained the relationship between life events and observed glucose patterns as well as treatment rationales to knowledge engineers. Knowledge engineers built a prototypical system that contained cases of problems in glucose control together with their associated solutions. Twelve patients completed the study. Fifty cases of clinical problems and solutions were developed and stored in a case base. The prototypical system detected 12 distinct types of clinical problems. It displayed the stored problems that are most similar to the problems detected, and offered learned solutions as decision support to the physician. This software can screen large volumes of clinical data and glucose levels from patients with T1DM, identify clinical problems, and offer solutions. It has potential application in managing all forms of diabetes.

Adaptation by Stealth: Understanding climate information use across scales and decision spaces in water management in the United States

NASA Astrophysics Data System (ADS)

Kirchhoff, C.; Vang Rasmussen, L.; Lemos, M. C.

2016-12-01

While there has been considerable focus on understanding how factors related to the creation of climate knowledge affect its uptake and use, less attention has been paid to the actors, decisions, and processes through which climate information supports, or fails to support, action. This is particularly the case concerning how different scales of decision-making influence information uptake. In this study, we seek to understand how water and resource managers' decision space influences climate information use in two Great Lakes watersheds. We find that despite the availability of tailored climate information, actual use of information in decision making remains low. Reasons include: a) lack of willingness to place climate on agendas because local managers perceive climate change as politically risky and a difficult and intangible problem; b) lack of formal mandate or authority at the city and county scale to translate climate information into on-the-ground action, c) problems with the information itself, and d) perceived lack of demand for climate information by those managers who have the mandate and authority (e.g. at the state level) to use (or help others use) climate information. Our findings suggest that 1) climate scientists and information brokers should produce information that meets a range of decision needs and reserve intensive tailoring efforts for decision makers who have authority and willingness to employ climate information, 2) without support from higher levels of decision-making (e.g. state) it is unlikely that climate information use for adaptation decisions will accelerate significantly in the next few years, and 3) the trend towards adopting more sustainability and resilience practices over climate-specific actions should be supported as an important component of the climate adaptation repertoire.

The role of decision-making in cannabis-related problems among young adults

PubMed Central

Gonzalez, Raul; Schuster, Randi M.; Mermelstein, Robin M.; Diviak, Kathleen R.

2015-01-01

Background Deficits in decision-making and episodic memory are often reported among heavy cannabis users, yet little is known on how they influence negative consequences from cannabis use. Individual differences in decision-making may explain, in part, why some individuals experience significant problems from their cannabis use whereas others do not. We hypothesized that poor decision-making would moderate relationships between amount of cannabis use and problems from cannabis use whereas episodic memory performance would not. Method Young adult cannabis users (n = 52) with cannabis as their drug of choice and with minimal comorbidities completed semi-structured interviews, self-report questionnaires, and measures of neurocognitive functioning, with decision-making accessed via the Iowa Gambling Task (IGT), episodic memory via the Hopkins Verbal Learning Test – Revised (HVLT) and problems from cannabis use with the Marijuana Problems Scale. Results Strong relationships were observed between amount of cannabis use (lifetime, 12-month, and 30-day) and problems reported from use, but only among participants with Low (impaired) decision-making (R2 = .39 to .51; p < .01). No significant relationships were observed among those with better (low average to high average) decision-making performance (p > .05). In contrast, episodic memory performance was not a significant moderator of the relationship between amount of cannabis use and cannabis problems (p > .05). Conclusions Cannabis users with poor decision-making may be at greater risk for experiencing significant negative consequences from their cannabis use. Our results lend further support to emerging evidence of decision-making as a risk factor for addiction and extend these findings to cannabis users. PMID:26199058

Developing Digital Dashboard Management for Learning System Dynamic Cooperative Simulation Behavior of Indonesia. (Study on Cooperative Information Organization in the Ministry of Cooperatives and SME)

NASA Astrophysics Data System (ADS)

Eni, Yuli; Aryanto, Rudy

2014-03-01

There are problems being experienced by the Ministry of cooperatives and SME (Small and Medium Enterprise) including the length of time in the decision by the Government to establish a policy that should be taken for local cooperatives across the province of Indonesia. The decision-making process is still analyzed manually, so that sometimes the decisions taken are also less appropriate, effective and efficient. The second problem is the lack of monitoring data cooperative process province that is too much, making it difficult for the analysis of dynamic information to be useful. Therefore the authors want to fix the system that runs by using digital dashboard management system supported by the modeling of system dynamics. In addition, the author also did the design of a system that can support the system. Design of this system is aimed to ease the experts, head, and the government to decide (DSS - Decision Support System) accurately effectively and efficiently, because in the system are raised alternative simulation in a description of the decision to be taken and the result from the decision. The system is expected to be designed dan simulated can ease and expedite the decision making. The design of dynamic digital dashboard management conducted by method of OOAD (Objects Oriented Analysis and Design) complete with UML notation.

Taking risks and taking advice: The role of experience in airline pilot diversions

NASA Technical Reports Server (NTRS)

Cohen, Marvin S.

1993-01-01

The research asks how pilots make diversion decisions, what factors determine whether they are make well or poorly, and how they may be improved. The results support the view that experienced decision makers may solve problems in a way that is qualitatively different from the approaches of less experienced decision makers. The results also support a concept of expertise that goes beyond a stock of specialized recognitional templates, to include domain-specific methods for processing information. Such metacognitive skills evolve through long experience. They may enhance both the accuracy and the efficiency of decision processes.

An Environmental Decision Support System for Spatial Assessment and Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates environmental assessment tools for effective problem-solving. The software integrates modules for GIS, visualization, geospatial analysis, statistical analysis, human health and ecolog...

Decision Support System for Coastal Protection Layout Design (DSS4CPD) Using Genetic Algorithm (ga) and Multicriteria Analysis (mca)

NASA Astrophysics Data System (ADS)

Jinchai, Phinai; Chittaladakorn, Suwatana

This research has its objective to develop the decision support system on GIS to be used in the coastal erosion protection management. The developed model in this research is called Decision Support System for Coastal Protection Layout Design (DSS4CPD). It has created both for systematic protection and solution measures to the problem by using Genetic Algorithm (GA) and Multicriteria Analysis (MCA) for finding the coastal structure layout optimal solution. In this research, three types of coastal structures were used as structure alternatives for the layout, which are seawall, breakwater, and groin. The coastal area in Nakornsrithammaraj, Thailand was used as the case study. The studied result has found the appropriate position of coastal structures considering the suitable rock size relied on the wave energy, and the appropriate coastal structure position based on the wave breaking line. Using GA and MCA in DSS4CPD, it found the best layout in this project. This DSS4CPD will be used by the authorized decision makers to find the most suitable erosion problem solution.

Development of Decision Support Intervention for Black Women with Breast Cancer

PubMed Central

Williams, Karen Patricia; Harrison, Toni Michelle; Jennings, Yvonne; Lucas, Wanda; Stephen, Juleen; Robinson, Dana; Mandelblatt, Jeanne S.; Taylor, Kathryn L.

2011-01-01

Adjuvant therapy improves breast cancer survival but is underutilized by Black women. Few interventions have addressed this problem. This preliminary report describes the process we used to develop a decision support intervention for Black women eligible for adjuvant therapy. Aims were to use qualitative methods to describe factors that influence Black women’s adjuvant therapy decisions, use these formative data to develop messages for a treatment decision-support intervention, and pilot test the acceptability and utility of the intervention with community members and newly diagnosed women. Thirty-four in-depth interviews were conducted with breast cancer patients in active treatment, survivors and cancer providers to gather qualitative data. Participant ages ranged from 38 to 69 years. A cultural framework was used to analyze the data and to inform intervention messages. Most women relied on their providers for treatment recommendations. Several women reported problems communicating with providers and felt unprepared to ask questions and discuss adjuvant treatment options. Other factors related to treatment experiences were: spiritual coping, collectivism, and sharing breast cancer experiences with other Black survivors. Using these formative data, we developed an intervention that is survivor-based and includes an in-person session which incorporates sharing personal stories, communication skills training and decision support. Intervention materials were reviewed by community members, researchers/clinicians and patients newly diagnosed with breast cancer. Patients reported satisfaction with the intervention and felt better prepared to talk with providers. The intervention will be tested in a randomized trial to enhance decision support and increase use of indicated adjuvant treatment. PMID:19267384

IONIO Project: Computer-mediated Decision Support System and Communication in Ocean Science

NASA Astrophysics Data System (ADS)

Oddo, Paolo; Acierno, Arianna; Cuna, Daniela; Federico, Ivan; Galati, Maria Barbara; Awad, Esam; Korres, Gerasimos; Lecci, Rita; Manzella, Giuseppe M. R.; Merico, Walter; Perivoliotis, Leonidas; Pinardi, Nadia; Shchekinova, Elena; Mannarini, Gianandrea; Vamvakaki, Chrysa; Pecci, Leda; Reseghetti, Franco

2013-04-01

A decision Support System is composed by four main steps. The first one is the definition of the problem, the issue to be covered, decisions to be taken. Different causes can provoke different problems, for each of the causes or its effects it is necessary to define a list of information and/or data that are required in order to take the better decision. The second step is the determination of sources from where information/data needed for decision-making can be obtained and who has that information. Furthermore it must be possible to evaluate the quality of the sources to see which of them can provide the best information, and identify the mode and format in which the information is presented. The third step is relying on the processing of knowledge, i.e. if the information/data are fitting for purposes. It has to be decided which parts of the information/data need to be used, what additional data or information is necessary to access, how can information be best presented to be able to understand the situation and take decisions. Finally, the decision making process is an interactive and inclusive process involving all concerned parties, whose different views must be taken into consideration. A knowledge based discussion forum is necessary to reach a consensus. A decision making process need to be examined closely and refined, and modified to meet differing needs over time. The report is presenting legal framework and knowledge base for a scientific based decision support system and a brief exploration of some of the skills that enhances the quality of decisions taken.

Decision Support System for Determining Scholarship Selection using an Analytical Hierarchy Process

NASA Astrophysics Data System (ADS)

Puspitasari, T. D.; Sari, E. O.; Destarianto, P.; Riskiawan, H. Y.

2018-01-01

Decision Support System is a computer program application that analyzes data and presents it so that users can make decision more easily. Determining Scholarship Selection study case in Senior High School in east Java wasn’t easy. It needed application to solve the problem, to improve the accuracy of targets for prospective beneficiaries of poor students and to speed up the screening process. This research will build system uses the method of Analytical Hierarchy Process (AHP) is a method that solves a complex and unstructured problem into its group, organizes the groups into a hierarchical order, inputs numerical values instead of human perception in comparing relative and ultimately with a synthesis determined elements that have the highest priority. The accuracy system for this research is 90%.

Shared Decision Making and Motivational Interviewing: Achieving Patient-Centered Care Across the Spectrum of Health Care Problems

PubMed Central

Elwyn, Glyn; Dehlendorf, Christine; Epstein, Ronald M.; Marrin, Katy; White, James; Frosch, Dominick L.

2014-01-01

Patient-centered care requires different approaches depending on the clinical situation. Motivational interviewing and shared decision making provide practical and well-described methods to accomplish patient-centered care in the context of situations where medical evidence supports specific behavior changes and the most appropriate action is dependent on the patient’s preferences. Many clinical consultations may require elements of both approaches, however. This article describes these 2 approaches—one to address ambivalence to medically indicated behavior change and the other to support patients in making health care decisions in cases where there is more than one reasonable option—and discusses how clinicians can draw on these approaches alone and in combination to achieve patient-centered care across the range of health care problems. PMID:24821899

Set-up of a decision support system to support sustainable development of the Laguna de Bay, Philippines.

PubMed

Nauta, Tjitte A; Bongco, Alicia E; Santos-Borja, Adelina C

2003-01-01

Over recent decades, population expansion, deforestation, land conversion, urbanisation, intense fisheries and industrialisation have produced massive changes in the Laguna de Bay catchment, Philippines. The resulting problems include rapid siltation of the lake, eutrophication, inputs of toxics, flooding problems and loss of biodiversity. Rational and systematic resolution of conflicting water use and water allocation interests is now urgently needed in order to ensure sustainable use of the water resources. With respect to the competing and conflicting pressures on the water resources, the Laguna Lake Development Authority (LLDA) needs to achieve comprehensive management and development of the area. In view of these problems and needs, the Government of the Netherlands was funding a two-year project entitled 'Sustainable Development of the Laguna de Bay Environment'.A comprehensive tool has been developed to support decision-making at catchment level. This consists of an ArcView GIS-database linked to a state-of-the-art modelling suite, including hydrological and waste load models for the catchment area and a three-dimensional hydrodynamic and water quality model (Delft3D) linked to a habitat evaluation module for the lake. In addition, MS Office based tools to support a stakeholder analysis and financial and economic assessments have been developed. The project also focused on technical studies relating to dredging, drinking water supply and infrastructure works. These aimed to produce technically and economically feasible solutions to water quantity and quality problems. The paper also presents the findings of a study on the development of polder islands in the Laguna de Bay, addressing the water quantity and quality problems and focusing on the application of the decision support system.

Comparison of risk-based decision-support systems for brownfield site rehabilitation: DESYRE and SADA applied to a Romanian case study.

PubMed

Stezar, I C; Pizzol, L; Critto, A; Ozunu, A; Marcomini, A

2013-12-15

Brownfield rehabilitation is an essential step for sustainable land-use planning and management in the European Union. In brownfield regeneration processes, the legacy contamination plays a significant role, firstly because of the persistent contaminants in soil or groundwater which extends the existing hazards and risks well into the future; and secondly, problems from historical contamination are often more difficult to manage than contamination caused by new activities. Due to the complexity associated with the management of brownfield site rehabilitation, Decision Support Systems (DSSs) have been developed to support problem holders and stakeholders in the decision-making process encompassing all phases of the rehabilitation. This paper presents a comparative study between two DSSs, namely SADA (Spatial Analysis and Decision Assistance) and DESYRE (Decision Support System for the Requalification of Contaminated Sites), with the main objective of showing the benefits of using DSSs to introduce and process data and then to disseminate results to different stakeholders involved in the decision-making process. For this purpose, a former car manufacturing plant located in the Brasov area, Central Romania, contaminated chiefly by heavy metals and total petroleum hydrocarbons, has been selected as a case study to apply the two examined DSSs. Major results presented here concern the analysis of the functionalities of the two DSSs in order to identify similarities, differences and complementarities and, thus, to provide an indication of the most suitable integration options. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improving performance with clinical decision support.

PubMed

Brailer, D J; Goldfarb, S; Horgan, M; Katz, F; Paulus, R A; Zakrewski, K

1996-07-01

CADU/CIS (Clinical and Administrative Decision-support Utility and Clinical Information System) is a clinical decision-support workstation that allows large volumes of clinical information systems data to be analyzed in a timely and user-friendly fashion. CARE PROCESS MEASUREMENT: For any given disease, subgroups of patients are identified, and automated, customized "clinical pathways" are generated. For each subgroup, the best practice norms for use of test and therapies are identified. Practice style variations are then compared to outcomes to focus inquiry on decisions that significantly affect outcomes. INTESTINAL OBSTRUCTION: Graduate Health Systems, a multisite integrated provider in the Philadelphia area, has used CADU/CIS to improve quality problems, reduce treatment-intensity variations, and improve clinical participation in care process evaluation and decision making. A task force selected intestinal obstruction without hernia as its first study because of the related high-volume and high-morbidity complications. Use of a ten-step method for clinical performance improvement showed that the intravenous administration of unnecessary fluids to 104 patients with intestinal obstruction induced congestive heart failure (CHF) in 5 patients. Task force members and other practicing physicians are now developing guidelines and other interventions aimed at fluid use. Indeed, the task force used CADU/CIS to identify an additional 250 patients in one year whose conditions were complicated by CHF. A clinical decision support tool can be instrumental in detecting problems with important clinical and economic implications, identifying their important underlying causes, tracking the associated tests and therapies, and monitoring interventions.

A Requirements Analysis Model for Selection of Personal Computer (PC) software in Air Force Organizations

DTIC Science & Technology

1988-09-01

Institute of Technology Air University In Partial Fulfillment of the Requirements for the Degree of Master of Science in Systems Management Dexter R... management system software Diag/Prob Diagnosis and problem solving or problem finding GR Graphics software Int/Transp Interoperability and...language software Plan/D.S. Planning and decision support or decision making PM Program management software SC Systems for Command, Control, Communications

A Fuzzy-Based Decision Support Model for Selecting the Best Dialyser Flux in Haemodialysis.

PubMed

Oztürk, Necla; Tozan, Hakan

2015-01-01

Decision making is an important procedure for every organization. The procedure is particularly challenging for complicated multi-criteria problems. Selection of dialyser flux is one of the decisions routinely made for haemodialysis treatment provided for chronic kidney failure patients. This study provides a decision support model for selecting the best dialyser flux between high-flux and low-flux dialyser alternatives. The preferences of decision makers were collected via a questionnaire. A total of 45 questionnaires filled by dialysis physicians and nephrologists were assessed. A hybrid fuzzy-based decision support software that enables the use of Analytic Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), Analytic Network Process (ANP), and Fuzzy Analytic Network Process (FANP) was used to evaluate the flux selection model. In conclusion, the results showed that a high-flux dialyser is the best. option for haemodialysis treatment.

Decision strategies for handling the uncertainty of future extreme rainfall under the influence of climate change.

PubMed

Gregersen, I B; Arnbjerg-Nielsen, K

2012-01-01

Several extraordinary rainfall events have occurred in Denmark within the last few years. For each event, problems in urban areas occurred as the capacity of the existing drainage systems were exceeded. Adaptation to climate change is necessary but also very challenging as urban drainage systems are characterized by long technical lifetimes and high, unrecoverable construction costs. One of the most important barriers for the initiation and implementation of the adaptation strategies is therefore the uncertainty when predicting the magnitude of the extreme rainfall in the future. This challenge is explored through the application and discussion of three different theoretical decision support strategies: the precautionary principle, the minimax strategy and Bayesian decision support. The reviewed decision support strategies all proved valuable for addressing the identified uncertainties, at best applied together as they all yield information that improved decision making and thus enabled more robust decisions.

A Mechanized Decision Support System for Academic Scheduling.

DTIC Science & Technology

1986-03-01

an operational system called software. The first step in the development phase is Design . Designers destribute software control by factoring the Data...SUBJECT TERMS (Continue on reverse if necessary and identify by block number) ELD GROUP SUB-GROUP Scheduling, Decision Support System , Software Design ...scheduling system . It will also examine software - design techniques to identify the most appropriate method- ology for this problem. " - Chapter 3 will

Foster care assessment: A study of the placement decision process in Flanders.

PubMed

Vanderfaeillie, Johan; Pijnenburg, Huub; Damen, Harm; Van Holen, Frank

2015-11-01

Family foster care placement decision-making has a weak scientific underpinning. Mostly a 'variable-oriented approach' is taken, which requires a lot of information that is not always available. The identification of clusters of foster children with similar characteristics may be a more viable decision strategy. In this study we investigated if foster children could indeed be clustered, which problems were identified at the time of placement, and the influence of placement history. It proved possible to group foster children into two clusters: (1) young children with familial problems and few behavioral problems, and (2) older children with prominent child problems and behavioral problems. For foster children with and without placement history, problems associated with placement proved identical. Considering that a foster care placement did not result in fundamental change in the problems present at time of placement, the importance is stressed of approaching foster care assessment as part of a decision making process which looks back as well as forward. Placement decisions should be based on an appraisal of the appropriateness of foster placement as a solution for the child. In conjunction with this appraisal a decision is required on how parents can be supported toward reunification. Or--if this is not an option--whether long term foster care is the best option for the child and if so, what conditions need to be met. Copyright © 2015 Elsevier Ltd. All rights reserved.

Study protocol: a mixed methods study to assess mental health recovery, shared decision-making and quality of life (Plan4Recovery).

PubMed

Coffey, Michael; Hannigan, Ben; Meudell, Alan; Hunt, Julian; Fitzsimmons, Deb

2016-08-17

Recovery in mental health care is complex, highly individual and can be facilitated by a range of professional and non-professional support. In this study we will examine how recovery from mental health problems is promoted in non-medical settings. We hypothesise a relationship between involvement in decisions about care, social support and recovery and quality of life outcomes. We will use standardised validated instruments of involvement in decision-making, social contacts, recovery and quality of life with a random sample of people accessing non-statutory mental health social care services in Wales. We will add to this important information with detailed one to one case study interviews with people, their family members and their support workers. We will use a series of these interviews to examine how people build recovery over time to help us understand more about their involvement in decisions and the social links they build. We want to see how being involved in decisions about care and the social links people have are related to recovery and quality of life for people with experience of using mental health support services. We want to understand the different perspectives of the people involved in making recovery possible. We will use this information to guide further studies of particular types of social interventions and their use in helping recovery from mental health problems.

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.

Data access and decision tools for coastal water resources management

EPA Science Inventory

US EPA has supported the development of numerous models and tools to support implementation of environmental regulations. However, transfer of knowledge and methods from detailed technical models to support practical problem solving by local communities and watershed or coastal ...

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A decision support system for map projections of small scale data

USGS Publications Warehouse

Finn, Michael P.; Usery, E. Lynn; Posch, Stephan T.; Seong, Jeong Chang

2004-01-01

The use of commercial geographic information system software to process large raster datasets of terrain elevation, population, land cover, vegetation, soils, temperature, and rainfall requires both projection from spherical coordinates to plane coordinate systems and transformation from one plane system to another. Decision support systems deliver information resulting in knowledge that assists in policies, priorities, or processes. This paper presents an approach to handling the problems of raster dataset projection and transformation through the development of a Web-enabled decision support system to aid users of transformation processes with the selection of appropriate map projections based on data type, areal extent, location, and preservation properties.

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.

A shared computer-based problem-oriented patient record for the primary care team.

PubMed

Linnarsson, R; Nordgren, K

1995-01-01

1. INTRODUCTION. A computer-based patient record (CPR) system, Swedestar, has been developed for use in primary health care. The principal aim of the system is to support continuous quality improvement through improved information handling, improved decision-making, and improved procedures for quality assurance. The Swedestar system has evolved during a ten-year period beginning in 1984. 2. SYSTEM DESIGN. The design philosophy is based on the following key factors: a shared, problem-oriented patient record; structured data entry based on an extensive controlled vocabulary; advanced search and query functions, where the query language has the most important role; integrated decision support for drug prescribing and care protocols and guidelines; integrated procedures for quality assurance. 3. A SHARED PROBLEM-ORIENTED PATIENT RECORD. The core of the CPR system is the problem-oriented patient record. All problems of one patient, recorded by different members of the care team, are displayed on the problem list. Starting from this list, a problem follow-up can be made, one problem at a time or for several problems simultaneously. Thus, it is possible to get an integrated view, across provider categories, of those problems of one patient that belong together. This shared problem-oriented patient record provides an important basis for the primary care team work. 4. INTEGRATED DECISION SUPPORT. The decision support of the system includes a drug prescribing module and a care protocol module. The drug prescribing module is integrated with the patient records and includes an on-line check of the patient's medication list for potential interactions and data-driven reminders concerning major drug problems. Care protocols have been developed for the most common chronic diseases, such as asthma, diabetes, and hypertension. The patient records can be automatically checked according to the care protocols. 5. PRACTICAL EXPERIENCE. The Swedestar system has been implemented in a primary care area with 30,000 inhabitants. It is being used by all the primary care team members: 15 general practitioners, 25 district nurses, and 10 physiotherapists. Several years of practical experience of the CPR system shows that it has a positive impact on quality of care on four levels: 1) improved clinical follow-up of individual patients; 2) facilitated follow-up of aggregated data such as practice activity analysis, annual reports, and clinical indicators; 3) automated medical audit; and 4) concurrent audit. Within that primary care area, quality of care has improved substantially in several aspects due to the use of the CPR system [1].

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 ...

Application of GIS in foreign direct investment decision support system

NASA Astrophysics Data System (ADS)

Zhou, Jianlan; Sun, Koumei

2007-06-01

It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.

Advanced Economic Analysis

NASA Technical Reports Server (NTRS)

Greenberg, Marc W.; Laing, William

2013-01-01

An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.

PubMed

Wright, Adam; Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W

2011-01-01

Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100,000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100,000 records to assess its accuracy. Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100,000 randomly selected patients showed high sensitivity (range: 62.8-100.0%) and positive predictive value (range: 79.8-99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts.

Simulation and Modeling Efforts to Support Decision Making in Healthcare Supply Chain Management

PubMed Central

Lazarova-Molnar, Sanja

2014-01-01

Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes' efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges. PMID:24683333

[Clinical everyday ethics-support in handling moral distress? : Evaluation of an ethical decision-making model for interprofessional clinical teams].

PubMed

Tanner, S; Albisser Schleger, H; Meyer-Zehnder, B; Schnurrer, V; Reiter-Theil, S; Pargger, H

2014-06-01

High-tech medicine and cost rationing provoke moral distress up to burnout syndromes. The consequences are severe, not only for those directly involved but also for the quality of patient care and the institutions. The multimodal model METAP (Modular, Ethical, Treatment, Allocation, Process) was developed as clinical everyday ethics to support the interprofessional ethical decision-making process. The distinctive feature of the model lays in education concerning ethics competence in dealing with difficult treatment decisions. METAP has been evaluated for quality testing. The research question of interest was whether METAP supports the handling of moral distress. The evaluation included 3 intensive care units and 3 geriatric units. In all, 33 single and 9 group interviews were held with 24 physicians, 44 nurses, and 9 persons from other disciplines. An additional questionnaire was completed by 122 persons (return rate 57%). Two-thirds of the interview answers and 55% of the questionnaire findings show that clinical everyday ethics supports the handling of moral distress, especially for interdisciplinary communication and collaboration and for the explanation and evaluation of treatment goals. METAP does not provide support for persons who are rarely confronted with ethical problems or have not applied the model long enough yet. To a certain degree, moral distress is unavoidable and must be addressed as an interprofessional problem. Herein, clinical everyday ethics may provide targeted support for ethical decision-making competence.

Models, Measurements, and Local Decisions: Assessing and ...

EPA Pesticide Factsheets

This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include either exposure or emissions reduction, and a host of stakeholders, including residents, academics, NGOs, local and federal agencies. This presentation includes results from the C-PORT modeling system, and from a citizen science project from the local area. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention

PubMed Central

Fisher, Brian; Smith, Jennifer; Pike, Ian

2017-01-01

Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods: Inspired by the Delphi method, we introduced a novel methodology—group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders’ observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results: The GA methodology triggered the emergence of ‘common ground’ among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders’ verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusions: Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ‘common ground’ among diverse stakeholders about health data and their implications. PMID:28895928

Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention.

PubMed

Al-Hajj, Samar; Fisher, Brian; Smith, Jennifer; Pike, Ian

2017-09-12

Background : Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods : Inspired by the Delphi method, we introduced a novel methodology-group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders' observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results : The GA methodology triggered the emergence of ' common g round ' among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders' verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusion s : Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ' common ground' among diverse stakeholders about health data and their implications.

Decision problems in management of construction projects

NASA Astrophysics Data System (ADS)

Szafranko, E.

2017-10-01

In a construction business, one must oftentimes make decisions during all stages of a building process, from planning a new construction project through its execution to the stage of using a ready structure. As a rule, the decision making process is made more complicated due to certain conditions specific for civil engineering. With such diverse decision situations, it is recommended to apply various decision making support methods. Both, literature and hands-on experience suggest several methods based on analytical and computational procedures, some less and some more complex. This article presents the methods which can be helpful in supporting decision making processes in the management of civil engineering projects. These are multi-criteria methods, such as MCE, AHP or indicator methods. Because the methods have different advantages and disadvantages, whereas decision situations have their own specific nature, a brief summary of the methods alongside some recommendations regarding their practical applications has been given at the end of the paper. The main aim of this article is to review the methods of decision support and their analysis for possible use in the construction industry.

Multicriteria decision model for retrofitting existing buildings

NASA Astrophysics Data System (ADS)

Bostenaru Dan, B.

2003-04-01

In this paper a model to decide which buildings from an urban area should be retrofitted is presented. The model has been cast into existing ones by choosing the decision rule, criterion weighting and decision support system types most suitable for the spatial problem of reducing earthquake risk in urban areas, considering existing spatial multiatributive and multiobjective decision methods and especially collaborative issues. Due to the participative character of the group decision problem "retrofitting existing buildings" the decision making model is based on interactivity. Buildings have been modeled following the criteria of spatial decision support systems. This includes identifying the corresponding spatial elements of buildings according to the information needs of actors from different sphaeres like architects, construction engineers and economists. The decision model aims to facilitate collaboration between this actors. The way of setting priorities interactivelly will be shown, by detailing the two phases: judgemental and computational, in this case site analysis, collection and evaluation of the unmodified data and converting survey data to information with computational methods using additional expert support. Buildings have been divided into spatial elements which are characteristic for the survey, present typical damages in case of an earthquake and are decisive for a better seismic behaviour in case of retrofitting. The paper describes the architectural and engineering characteristics as well as the structural damage for constuctions of different building ages on the example of building types in Bucharest, Romania in compressible and interdependent charts, based on field observation, reports from the 1977 earthquake and detailed studies made by the author together with a local engineer for the EERI Web Housing Encyclopedia. On this base criteria for setting priorities flow into the expert information contained in the system.

Selecting essential information for biosurveillance--a multi-criteria decision analysis.

PubMed

Generous, Nicholas; Margevicius, Kristen J; Taylor-McCabe, Kirsten J; Brown, Mac; Daniel, W Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.

Building University Capacity to Visualize Solutions to Complex Problems in the Arctic

NASA Astrophysics Data System (ADS)

Broderson, D.; Veazey, P.; Raymond, V. L.; Kowalski, K.; Prakash, A.; Signor, B.

2016-12-01

Rapidly changing environments are creating complex problems across the globe, which are particular magnified in the Arctic. These worldwide challenges can best be addressed through diverse and interdisciplinary research teams. It is incumbent on such teams to promote co-production of knowledge and data-driven decision-making by identifying effective methods to communicate their findings and to engage with the public. Decision Theater North (DTN) is a new semi-immersive visualization system that provides a space for teams to collaborate and develop solutions to complex problems, relying on diverse sets of skills and knowledge. It provides a venue to synthesize the talents of scientists, who gather information (data); modelers, who create models of complex systems; artists, who develop visualizations; communicators, who connect and bridge populations; and policymakers, who can use the visualizations to develop sustainable solutions to pressing problems. The mission of Decision Theater North is to provide a cutting-edge visual environment to facilitate dialogue and decision-making by stakeholders including government, industry, communities and academia. We achieve this mission by adopting a multi-faceted approach reflected in the theater's design, technology, networking capabilities, user support, community relationship building, and strategic partnerships. DTN is a joint project of Alaska's National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) and the University of Alaska Fairbanks (UAF), who have brought the facility up to full operational status and are now expanding its development space to support larger team science efforts. Based in Fairbanks, Alaska, DTN is uniquely poised to address changes taking place in the Arctic and subarctic, and is connected with a larger network of decision theaters that include the Arizona State University Decision Theater Network and the McCain Institute in Washington, DC.

Predicting species distributions for conservation decisions

PubMed Central

Guisan, Antoine; Tingley, Reid; Baumgartner, John B; Naujokaitis-Lewis, Ilona; Sutcliffe, Patricia R; Tulloch, Ayesha I T; Regan, Tracey J; Brotons, Lluis; McDonald-Madden, Eve; Mantyka-Pringle, Chrystal; Martin, Tara G; Rhodes, Jonathan R; Maggini, Ramona; Setterfield, Samantha A; Elith, Jane; Schwartz, Mark W; Wintle, Brendan A; Broennimann, Olivier; Austin, Mike; Ferrier, Simon; Kearney, Michael R; Possingham, Hugh P; Buckley, Yvonne M

2013-01-01

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. PMID:24134332

Deciding Where to Turn: A Qualitative Investigation of College Students' Helpseeking Decisions After Sexual Assault.

PubMed

DeLoveh, Heidi L M; Cattaneo, Lauren Bennett

2017-03-01

Sexual assault is a widespread problem on college campuses that has been the subject of substantial attention in recent years (Ali, 2011; Krebs, Lindquist, Berzofsky, Shook-Sa, & Peterson, 2016). Resources designed to address the problem exist, but there is evidence that they are underutilized by survivors (Campbell, 2008). The current study used grounded theory to explore how sexual assault survivors make decisions about helpseeking. In-depth interviews were conducted with 14 college sexual assault survivors to develop a theoretical model for their decision-making process. The resulting model, Deciding Where to Turn, suggests that survivors engage in three key decision points: determining if there is a problem related to the sexual assault (Do I Need Help), considering options (What Can I Do), and weighing the consequences of these options (What Will I Do). This process results in one of four behavioral choices: cope on one's own, seek support from friends/family, seek support from formal resources, or covert helpseeking, where needs are met without disclosure. Deciding Where to Turn contributes to the literature by providing a framework for understanding helpseeking decisions after sexual assault, highlighting the need to match reactions to survivor perceptions. The concept of covert helpseeking in particular adds to the way researchers and practitioners think about helpseeking. Research and practice implications are discussed. © Society for Community Research and Action 2017.

Applying evidence to support ethical decisions: is the placebo really powerless?.

PubMed

Porzsolt, Franz; Schlotz-Gorton, Nicole; Biller-Andorno, Nikola; Thim, Anke; Meissner, Karin; Roeckl-Wiedmann, Irmgard; Herzberger, Barbara; Ziegler, Renatus; Gaus, Wilhelm; Pöppe, Ernst

2004-01-01

Using placebos in day-to-day practice is an ethical problem. This paper summarises the available epidemiological evidence to support this difficult decision. Based on these data we propose to differentiate between placebo and "knowledge framing". While the use of placebo should be confined to experimental settings in clinical trials, knowledge framing--which is only conceptually different from placebo--is a desired, expected and necessary component of any doctor-patient encounter. Examples from daily practice demonstrate both, the need to investigate the effects of knowledge framing and its impact on ethical, medical, economical and legal decisions.

Decision support for patient care: implementing cybernetics.

PubMed

Ozbolt, Judy; Ozdas, Asli; Waitman, Lemuel R; Smith, Janis B; Brennan, Grace V; Miller, Randolph A

2004-01-01

The application of principles and methods of cybernetics permits clinicians and managers to use feedback about care effectiveness and resource expenditure to improve quality and to control costs. Keys to the process are the specification of therapeutic goals and the creation of an organizational culture that supports the use of feedback to improve care. Daily feedback on the achievement of each patient's therapeutic goals provides tactical decision support, enabling clinicians to adjust care as needed. Monthly or quarterly feedback on aggregated goal achievement for all patients on a clinical pathway provides strategic decision support, enabling clinicians and managers to identify problems with supposed "best practices" and to test hypotheses about solutions. Work is underway at Vanderbilt University Medical Center to implement feedback loops in care and management processes and to evaluate the effects.

IBM's Health Analytics and Clinical Decision Support.

PubMed

Kohn, M S; Sun, J; Knoop, S; Shabo, A; Carmeli, B; Sow, D; Syed-Mahmood, T; Rapp, W

2014-08-15

This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation.

Group Participation and Satisfaction: Results from a PBL Computer-Supported Module

ERIC Educational Resources Information Center

Ochoa, Theresa A.; Gottschall, Holly; Stuart, Shannon K.

2004-01-01

Special education policy requires schools to make disciplinary decisions concerning students with disabilities within a multidisciplinary team. In order to respond to this mandate, teacher educators must ensure that teachers have group collaboration and decision making skills. This article describes a multimedia problem-based learning module…

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...

Overview of USEPA's ORD Technical Outreach and Support Activities on Vapor Intrusion Impacts - 03/2008

EPA Science Inventory

The science of determining, characterizing and managing vapor intrusion risks is constantly evolving. Much remains to be done in assisting regulators, consultants and other decision-makers to make informed decisions in mitigating the problem and reducing these risks. ORD has been...

Strategic control in decision-making under uncertainty.

PubMed

Venkatraman, Vinod; Huettel, Scott A

2012-04-01

Complex economic decisions - whether investing money for retirement or purchasing some new electronic gadget - often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, evaluate outcomes against a variety of contexts, and flexibly match behavior to changes in the environment. In recent years, substantial research has implicated the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision-making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision-making. This region contains a functional topography such that the posterior dmPFC supports response-related control, whereas the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue for both generalized contributions of the dmPFC to cognitive control, and specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are likely to be critical for decision-making in other domains, including interpersonal interactions in social settings. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Strategic Control in Decision Making under Uncertainty

PubMed Central

Venkatraman, Vinod; Huettel, Scott

2012-01-01

Complex economic decisions – whether investing money for retirement or purchasing some new electronic gadget – often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, to evaluate outcomes against a variety of contexts, and to flexibly match behavior to changes in the environment. In recent years, substantial research implicates the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision making. This region contains a functional topography such that the posterior dmPFC supports response-related control while the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue both for generalized contributions of the dmPFC to cognitive control, and for specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are also likely to be critical for decision making in other domains, including interpersonal interactions in social settings. PMID:22487037

A spatial decision support system (SDSS) for sustainable tourism planning in Cameron Highlands, Malaysia

NASA Astrophysics Data System (ADS)

Aminu, M.; Matori, A. N.; Yusof, K. W.

2014-02-01

The study describes a methodological approach based on an integrated use of Geographic Information System (GIS) and Analytic Network Process (ANP) of Multi Criteria Evaluation (MCE) to determine nature conservation and tourism development priorities among the highland areas. A set of criteria and indicators were defined to evaluate the highlands biodiversity conservation and tourism development. Pair wise comparison technique was used in order to support solution of a decision problem by evaluating possible alternatives from different perspectives. After the weights have been derived from the pairwise comparison technique, the next step was to compute the unweighted supermatrix, weighted supermatrix and the limit matrix. The limit matrix was normalized to obtain the priorities and the results transferred into GIS environment. Elements evaluated and ranked were represented by criterion maps. Map layers reflecting the opinion of different experts involved were summed using the weighted overlay approach of GIS. Subsequently sustainable tourism development scenarios were generated. The generation of scenarios highlighted the critical issues of the decision problem because it allows one to gradually narrow down a problem.

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

PubMed

Yu, Peter Paul

2015-03-01

One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.

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.

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

To stand back or step in? Exploring the responses of employees who observe workplace bullying.

PubMed

MacCurtain, Sarah; Murphy, Caroline; O'Sullivan, Michelle; MacMahon, Juliet; Turner, Tom

2018-01-01

Bullying remains a pervasive problem in healthcare, and evidence suggests systems in place are not utilised due to perceptions of ineffectiveness and inequity. This study examines bystander responses to bullying and factors that influence decisions to intervene. We explore relationships between bystanders' perceptions of psychological safety across three levels (organisation, supervisor and colleague) and reactions to witnessing bullying. We suggest psychological safety would be positively associated with the decision to intervene. Findings indicate the most pervasive reaction to witnessing incidents of bullying is to discuss with colleagues, a low-involvement reaction. We find perceptions of supervisory and organisational safety/support are positively related to high-involvement decisions such as formal reporting of the incidents, highlighting the importance of support from those in power. However, perceptions of collegial support may lead to low-involvement responses, which risk reinforcing and underpinning dysfunctional organisational dynamics by providing informal social and emotional responses that may substitute more formal organisational responses to this persistent problem. This study highlights the importance of support from individuals in power if bystanders are to feel comfortable making high-involvement interventions. © 2017 John Wiley & Sons Ltd.

Healthcare provider attitudes towards the problem list in an electronic health record: a mixed-methods qualitative study

PubMed Central

2012-01-01

Background The problem list is a key part of the electronic health record (EHR) that allows practitioners to see a patient’s diagnoses and health issues. Yet, as the content of the problem list largely represents the subjective decisions of those who edit it, patients’ problem lists are often unreliable when shared across practitioners. The lack of standards for how the problem list is compiled in the EHR limits its effectiveness in improving patient care, particularly as a resource for clinical decision support and population management tools. The purpose of this study is to discover practitioner opinions towards the problem list and the logic behind their decisions during clinical situations. Materials and methods An observational cross-sectional study was conducted at two major Boston teaching hospitals. Practitioners’ opinions about the problem list were collected through both in-person interviews and an online questionnaire. Questions were framed using vignettes of clinical scenarios asking practitioners about their preferred actions towards the problem list. Results These data confirmed prior research that practitioners differ in their opinions over managing the problem list, but in most responses to a questionnaire, there was a common approach among the relative majority of respondents. Further, basic demographic characteristics of providers (age, medical experience, etc.) did not appear to strongly affect attitudes towards the problem list. Conclusion The results supported the premise that policies and EHR tools are needed to bring about a common approach. Further, the findings helped identify what issues might benefit the most from a defined policy and the level of restriction a problem list policy should place on the addition of different types of information. PMID:23140312

A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record

PubMed Central

Pang, Justine; Feblowitz, Joshua C; Maloney, Francine L; Wilcox, Allison R; Ramelson, Harley Z; Schneider, Louise I; Bates, David W

2011-01-01

Background Accurate knowledge of a patient's medical problems is critical for clinical decision making, quality measurement, research, billing and clinical decision support. Common structured sources of problem information include the patient problem list and billing data; however, these sources are often inaccurate or incomplete. Objective To develop and validate methods of automatically inferring patient problems from clinical and billing data, and to provide a knowledge base for inferring problems. Study design and methods We identified 17 target conditions and designed and validated a set of rules for identifying patient problems based on medications, laboratory results, billing codes, and vital signs. A panel of physicians provided input on a preliminary set of rules. Based on this input, we tested candidate rules on a sample of 100 000 patient records to assess their performance compared to gold standard manual chart review. The physician panel selected a final rule for each condition, which was validated on an independent sample of 100 000 records to assess its accuracy. Results Seventeen rules were developed for inferring patient problems. Analysis using a validation set of 100 000 randomly selected patients showed high sensitivity (range: 62.8–100.0%) and positive predictive value (range: 79.8–99.6%) for most rules. Overall, the inference rules performed better than using either the problem list or billing data alone. Conclusion We developed and validated a set of rules for inferring patient problems. These rules have a variety of applications, including clinical decision support, care improvement, augmentation of the problem list, and identification of patients for research cohorts. PMID:21613643

Translational Cognition for Decision Support in Critical Care Environments: A Review

PubMed Central

Patel, Vimla L.; Zhang, Jiajie; Yoskowitz, Nicole A.; Green, Robert; Sayan, Osman R.

2008-01-01

The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers. PMID:18343731

Translational cognition for decision support in critical care environments: a review.

PubMed

Patel, Vimla L; Zhang, Jiajie; Yoskowitz, Nicole A; Green, Robert; Sayan, Osman R

2008-06-01

The dynamic and distributed work environment in critical care requires a high level of collaboration among clinical team members and a sophisticated task coordination system to deliver safe, timely and effective care. A complex cognitive system underlies the decision-making process in such cooperative workplaces. This methodological review paper addresses the issues of translating cognitive research to clinical practice with a specific focus on decision-making in critical care, and the role of information and communication technology to aid in such decisions. Examples are drawn from studies of critical care in our own research laboratories. Critical care, in this paper, includes both intensive (inpatient) and emergency (outpatient) care. We define translational cognition as the research on basic and applied cognitive issues that contribute to our understanding of how information is stored, retrieved and used for problem-solving and decision-making. The methods and findings are discussed in the context of constraints on decision-making in real-world complex environments and implications for supporting the design and evaluation of decision support tools for critical care health providers.

How can we make progress with decision support systems in landscape and river basin management? Lessons learned from a comparative analysis of four different decision support systems.

PubMed

Volk, Martin; Lautenbach, Sven; van Delden, Hedwig; Newham, Lachlan T H; Seppelt, Ralf

2010-12-01

This article analyses the benefits and shortcomings of the recently developed decision support systems (DSS) FLUMAGIS, Elbe-DSS, CatchMODS, and MedAction. The analysis elaborates on the following aspects: (i) application area/decision problem, (ii) stakeholder interaction/users involved, (iii) structure of DSS/model structure, (iv) usage of the DSS, and finally (v) most important shortcomings. On the basis of this analysis, we formulate four criteria that we consider essential for the successful use of DSS in landscape and river basin management. The criteria relate to (i) system quality, (ii) user support and user training, (iii) perceived usefulness and (iv) user satisfaction. We can show that the availability of tools and technologies for DSS in landscape and river basin management is good to excellent. However, our investigations indicate that several problems have to be tackled. First of all, data availability and homogenisation, uncertainty analysis and uncertainty propagation and problems with model integration require further attention. Furthermore, the appropriate and methodological stakeholder interaction and the definition of 'what end-users really need and want' have been documented as general shortcomings of all four examples of DSS. Thus, we propose an iterative development process that enables social learning of the different groups involved in the development process, because it is easier to design a DSS for a group of stakeholders who actively participate in an iterative process. We also identify two important lines of further development in DSS: the use of interactive visualization tools and the methodology of optimization to inform scenario elaboration and evaluate trade-offs among environmental measures and management alternatives.

How Can We Make Progress with Decision Support Systems in Landscape and River Basin Management? Lessons Learned from a Comparative Analysis of Four Different Decision Support Systems

NASA Astrophysics Data System (ADS)

Volk, Martin; Lautenbach, Sven; van Delden, Hedwig; Newham, Lachlan T. H.; Seppelt, Ralf

2010-12-01

This article analyses the benefits and shortcomings of the recently developed decision support systems (DSS) FLUMAGIS, Elbe-DSS, CatchMODS, and MedAction. The analysis elaborates on the following aspects: (i) application area/decision problem, (ii) stakeholder interaction/users involved, (iii) structure of DSS/model structure, (iv) usage of the DSS, and finally (v) most important shortcomings. On the basis of this analysis, we formulate four criteria that we consider essential for the successful use of DSS in landscape and river basin management. The criteria relate to (i) system quality, (ii) user support and user training, (iii) perceived usefulness and (iv) user satisfaction. We can show that the availability of tools and technologies for DSS in landscape and river basin management is good to excellent. However, our investigations indicate that several problems have to be tackled. First of all, data availability and homogenisation, uncertainty analysis and uncertainty propagation and problems with model integration require further attention. Furthermore, the appropriate and methodological stakeholder interaction and the definition of `what end-users really need and want' have been documented as general shortcomings of all four examples of DSS. Thus, we propose an iterative development process that enables social learning of the different groups involved in the development process, because it is easier to design a DSS for a group of stakeholders who actively participate in an iterative process. We also identify two important lines of further development in DSS: the use of interactive visualization tools and the methodology of optimization to inform scenario elaboration and evaluate trade-offs among environmental measures and management alternatives.

Vulnerability assessment of urban ecosystems driven by water resources, human health and atmospheric environment

NASA Astrophysics Data System (ADS)

Shen, Jing; Lu, Hongwei; Zhang, Yang; Song, Xinshuang; He, Li

2016-05-01

As ecosystem management is a hotspot and urgent topic with increasing population growth and resource depletion. This paper develops an urban ecosystem vulnerability assessment method representing a new vulnerability paradigm for decision makers and environmental managers, as it's an early warning system to identify and prioritize the undesirable environmental changes in terms of natural, human, economic and social elements. The whole idea is to decompose a complex problem into sub-problem, and analyze each sub-problem, and then aggregate all sub-problems to solve this problem. This method integrates spatial context of Geographic Information System (GIS) tool, multi-criteria decision analysis (MCDA) method, ordered weighted averaging (OWA) operators, and socio-economic elements. Decision makers can find out relevant urban ecosystem vulnerability assessment results with different vulnerable attitude. To test the potential of the vulnerability methodology, it has been applied to a case study area in Beijing, China, where it proved to be reliable and consistent with the Beijing City Master Plan. The results of urban ecosystem vulnerability assessment can support decision makers in evaluating the necessary of taking specific measures to preserve the quality of human health and environmental stressors for a city or multiple cities, with identifying the implications and consequences of their decisions.

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

PubMed

Dhukaram, Anandhi Vivekanandan; Baber, Chris

2015-06-01

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

On Developing a Taxonomy for Multidisciplinary Design Optimization: A Decision-Based Perspective

NASA Technical Reports Server (NTRS)

Lewis, Kemper; Mistree, Farrokh

1995-01-01

In this paper, we approach MDO from a Decision-Based Design (DBD) perspective and explore classification schemes for designing complex systems and processes. Specifically, we focus on decisions, which are only a small portion of the Decision Support Problem (DSP) Technique, our implementation of DBD. We map coupled nonhierarchical and hierarchical representations from the DSP Technique into the Balling-Sobieski (B-S) framework (Balling and Sobieszczanski-Sobieski, 1994), and integrate domain-independent linguistic terms to complete our taxonomy. Application of DSPs to the design of complex, multidisciplinary systems include passenger aircraft, ships, damage tolerant structural and mechanical systems, and thermal energy systems. In this paper we show that Balling-Sobieski framework is consistent with that of the Decision Support Problem Technique through the use of linguistic entities to describe the same type of formulations. We show that the underlying linguistics of the solution approaches are the same and can be coalesced into a homogeneous framework with which to base the research, application, and technology MDO upon. We introduce, in the Balling-Sobieski framework, examples of multidisciplinary design, namely, aircraft, damage tolerant structural and mechanical systems, and thermal energy systems.

History matching through dynamic decision-making

PubMed Central

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

2017-01-01

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

The potential for meta-analysis to support decision analysis in ecology.

PubMed

Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

2015-06-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.

Neighborhood graph and learning discriminative distance functions for clinical decision support.

PubMed

Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

2009-01-01

There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.

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.

GODDESS: A Goal-Directed Decision Structuring System.

DTIC Science & Technology

1980-06-01

differ- ent support techniques. From a practical viewpoint, though, the major drawback of manual interviews is their length and cost. Since real - time ...conducting his future inquiries. A direct man-machine interface could provide three distinct advantages. First, it offers the capability of real - time ...knowledge in tree form. In many real -world applications, the decision maker may not perceive a problem in the form of a time sequence of decision

The Involvement of Parents in Healthcare Decisions Where Adult Children Are at Risk of Lacking Decision-Making Capacity: A Qualitative Study of Treatment Decisions in Epilepsy

ERIC Educational Resources Information Center

Redley, M.; Prince, E.; Bateman, N.; Pennington, M.; Wood, N.; Croudace, T.; Ring, H.

2013-01-01

Background: Patients with intellectual disabilities (ID) receive health care by proxy. It is family members and/or paid support staff who must recognise health problems, communicate with clinicians, and report the benefits, if any, of a particular treatment. At the same time international and national statutes protect and promote the right of…

The Effects of Successful versus Failure-Based Cases on Argumentation while Solving Decision-Making Problems

ERIC Educational Resources Information Center

Tawfik, Andrew; Jonassen, David

2013-01-01

Solving complex, ill-structured problems may be effectively supported by case-based reasoning through case libraries that provide just-in-time domain-specific principles in the form of stories. The cases not only articulate previous experiences of practitioners, but also serve as problem-solving narratives from which learners can acquire meaning.…

Human-computer interface for the study of information fusion concepts in situation analysis and command decision support systems

NASA Astrophysics Data System (ADS)

Roy, Jean; Breton, Richard; Paradis, Stephane

2001-08-01

Situation Awareness (SAW) is essential for commanders to conduct decision-making (DM) activities. Situation Analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision maker. Operational trends in warfare put the situation analysis process under pressure. This emphasizes the need for a real-time computer-based Situation analysis Support System (SASS) to aid commanders in achieving the appropriate situation awareness, thereby supporting their response to actual or anticipated threats. Data fusion is clearly a key enabler for SA and a SASS. Since data fusion is used for SA in support of dynamic human decision-making, the exploration of the SA concepts and the design of data fusion techniques must take into account human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight integration of the human element with the SA technology is essential. Regarding these issues, this paper provides a description of CODSI (Command Decision Support Interface), and operational- like human machine interface prototype for investigations in computer-based SA and command decision support. With CODSI, one objective was to apply recent developments in SA theory and information display technology to the problem of enhancing SAW quality. It thus provides a capability to adequately convey tactical information to command decision makers. It also supports the study of human-computer interactions for SA, and methodologies for SAW measurement.

Cogenerating a Competency-based HRM Degree: A Model and Some Lessons from Experience.

ERIC Educational Resources Information Center

Wooten, Kevin C.; Elden, Max

2001-01-01

A competency-based degree program in human resource management was co-generated by six groups of stakeholders who synthesized competency models using group decision support software. The program focuses on core human resource processes, general business management, strategic decision making and problem solving, change management, and personal…

Evaluation of Communication about Groups: The Hydra Phenomenon.

ERIC Educational Resources Information Center

Desmond, Roger Jon; Bezzini, John

A study investigated how the attribution of a problem solution to an individual or group affects the consumer's perception of the solution's quality. Based on the tendency to support group decision-making (Hydra phenomenon) it was predicted that decisions attributed to groups would be perceived as higher in quality than those made by individuals,…

Improving Water Management Decision Support Tools Using NASA Satellite and Modeling Data

NASA Astrophysics Data System (ADS)

Toll, D. L.; Arsenault, K.; Nigro, J.; Pinheiro, A.; Engman, E. T.; Triggs, J.; Cosgrove, B.; Alonge, C.; Boyle, D.; Allen, R.; Townsend, P.; Ni-Meister, W.

2006-05-01

One of twelve Applications of National priority within NASA's Applied Science Program, the Water Management Program Element addresses concerns and decision making related to water availability, water forecast and water quality. The goal of the Water Management Program Element is to encourage water management organizations to use NASA Earth science data, models products, technology and other capabilities in their decision support tools for problem solving. The Water Management Program Element partners with Federal agencies, academia, private firms, and may include international organizations. This paper further describes the Water Management Program with the objective of informing the applications community of the potential opportunities for using NASA science products for problem solving. We will illustrate some ongoing and application Water Management projects evaluating and benchmarking NASA data with partnering federal agencies and their decision support tools: 1) Environmental Protection Agency for water quality; 2) Bureau of Reclamation for water supply, demand and forecast; and 3) NOAA National Weather Service for improved weather prediction. Examples of the types of NASA contributions to the these agency decision support tools include: 1) satellite observations within models assist to estimate water storage, i.e., snow water equivalent, soil moisture, aquifer volumes, or reservoir storages; 2) model derived products, i.e., evapotranspiration, precipitation, runoff, ground water recharge, and other 4-dimensional data assimilation products; 3) improve water quality, assessments by using improved inputs from NASA models (precipitation, evaporation) and satellite observations (e.g., temperature, turbidity, land cover) to nonpoint source models; and 4) water (i.e., precipitation) and temperature predictions from days to decades over local, regional and global scales.

Sustainable aggregate production planning in the chemical process industry - A benchmark problem and dataset.

PubMed

Brandenburg, Marcus; Hahn, Gerd J

2018-06-01

Process industries typically involve complex manufacturing operations and thus require adequate decision support for aggregate production planning (APP). The need for powerful and efficient approaches to solve complex APP problems persists. Problem-specific solution approaches are advantageous compared to standardized approaches that are designed to provide basic decision support for a broad range of planning problems but inadequate to optimize under consideration of specific settings. This in turn calls for methods to compare different approaches regarding their computational performance and solution quality. In this paper, we present a benchmarking problem for APP in the chemical process industry. The presented problem focuses on (i) sustainable operations planning involving multiple alternative production modes/routings with specific production-related carbon emission and the social dimension of varying operating rates and (ii) integrated campaign planning with production mix/volume on the operational level. The mutual trade-offs between economic, environmental and social factors can be considered as externalized factors (production-related carbon emission and overtime working hours) as well as internalized ones (resulting costs). We provide data for all problem parameters in addition to a detailed verbal problem statement. We refer to Hahn and Brandenburg [1] for a first numerical analysis based on and for future research perspectives arising from this benchmarking problem.

Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis

PubMed Central

Generous, Nicholas; Margevicius, Kristen J.; Taylor-McCabe, Kirsten J.; Brown, Mac; Daniel, W. Brent; Castro, Lauren; Hengartner, Andrea; Deshpande, Alina

2014-01-01

The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system. PMID:24489748

Health care workers and their needs: the forgotten shadow of AIM research.

PubMed

Lillehaug, S I; Lajoie, S

1998-01-01

The field of AI in Medicine (AIM) seems to have accepted that decision support is, and will be, needed within most medical domains. As society calls for cost-effectiveness, and human expertise or expert guidance are not always available, decision support systems (DSSs) are proposed as the solutions. These solutions, however, do not necessarily correspond with the basic needs of their targeted users. We will show this through a review of the literature related to health care workers and the various factors that have an influence on their performances. Furthermore, we will use these empirical findings to argue that the AIM community must go beyond its decision support philosophy, whereby the gaps in human expertise are filled in by the computer. In the future, joint emphasis must be placed on decision support and the promotion towards independent and self-sufficient problem solving. In order to implement this paradigm change, the AIM community will have to incorporate findings from the research discipline of AI in Education.

“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.

The application of decision analysis to life support research and technology development

NASA Technical Reports Server (NTRS)

Ballin, Mark G.

1994-01-01

Applied research and technology development is often characterized by uncertainty, risk, and significant delays before tangible returns are obtained. Decision making regarding which technologies to advance and what resources to devote to them is a challenging but essential task. In the application of life support technology to future manned space flight, new technology concepts typically are characterized by nonexistent data and rough approximations of technology performance, uncertain future flight program needs, and a complex, time-intensive process to develop technology to a flight-ready status. Decision analysis is a quantitative, logic-based discipline that imposes formalism and structure to complex problems. It also accounts for the limits of knowledge that may be available at the time a decision is needed. The utility of decision analysis to life support technology R & D was evaluated by applying it to two case studies. The methodology was found to provide insight that is not possible from more traditional analysis approaches.

Development of a decision support system for tsunami evacuation: application to the Jiyang District of Sanya city in China

NASA Astrophysics Data System (ADS)

Hou, Jingming; Yuan, Ye; Wang, Peitao; Ren, Zhiyuan; Li, Xiaojuan

2017-03-01

Major tsunami disasters often cause great damage in the first few hours following an earthquake. The possible severity of such events requires preparations to prevent tsunami disasters or mitigate them. This paper is an attempt to develop a decision support system for rapid tsunami evacuation for local decision makers. Based on the numerical results database of tsunami disasters, this system can quickly obtain the tsunami inundation and travel time. Because numerical models are calculated in advance, this system can reduce decision-making time. Population distribution, as a vulnerability factor, was analyzed to identify areas of high risk for tsunami disasters. Combined with spatial data, this system can comprehensively analyze the dynamic and static evacuation process and identify problems that negatively impact evacuation, thus supporting the decision-making for tsunami evacuation in high-risk areas. When an earthquake and tsunami occur, this system can rapidly obtain the tsunami inundation and travel time and provide information to assist with tsunami evacuation operations.

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.

The EVOTION Decision Support System: Utilizing It for Public Health Policy-Making in Hearing Loss.

PubMed

Katrakazas, Panagiotis; Trenkova, Lyubov; Milas, Josip; Brdaric, Dario; Koutsouris, Dimitris

2017-01-01

As Decision Support Systems start to play a significant role in decision making, especially in the field of public-health policy making, we present an initial attempt to formulate such a system in the concept of public health policy making for hearing loss related problems. Justification for the system's conceptual architecture and its key functionalities are presented. The introduction of the EVOTION DSS sets a key innovation and a basis for paradigm shift in policymaking, by incorporating relevant models, big data analytics and generic demographic data. Expected outcomes for this joint effort are discussed from a public-health point of view.

A simulation study to quantify the impacts of exposure ...

EPA Pesticide Factsheets

A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Sensemaking Strategies for Ethical Decision-making.

PubMed

Caughron, Jay J; Antes, Alison L; Stenmark, Cheryl K; Thiel, Chaise E; Wang, Xiaoqian; Mumford, Michael D

2011-01-01

The current study uses a sensemaking model and thinking strategies identified in earlier research to examine ethical decision-making. Using a sample of 163 undergraduates, a low fidelity simulation approach is used to study the effects personal involvement (in causing the problem and personal involvement in experiencing the outcomes of the problem) could have on the use of cognitive reasoning strategies that have been shown to promote ethical decision-making. A mediated model is presented which suggests that environmental factors influence reasoning strategies, reasoning strategies influence sensemaking, and sensemaking in turn influences ethical decision-making. Findings were mixed but generally supported the hypothesized model. Interestingly, framing the outcomes of ethically charged situations in terms of more global organizational outcomes rather than personal outcomes was found to promote the use of pro-ethical cognitive reasoning strategies.

Sensemaking Strategies for Ethical Decision-making

PubMed Central

Caughron, Jay J.; Antes, Alison L.; Stenmark, Cheryl K.; Thiel, Chaise E.; Wang, Xiaoqian; Mumford, Michael D.

2015-01-01

The current study uses a sensemaking model and thinking strategies identified in earlier research to examine ethical decision-making. Using a sample of 163 undergraduates, a low fidelity simulation approach is used to study the effects personal involvement (in causing the problem and personal involvement in experiencing the outcomes of the problem) could have on the use of cognitive reasoning strategies that have been shown to promote ethical decision-making. A mediated model is presented which suggests that environmental factors influence reasoning strategies, reasoning strategies influence sensemaking, and sensemaking in turn influences ethical decision-making. Findings were mixed but generally supported the hypothesized model. Interestingly, framing the outcomes of ethically charged situations in terms of more global organizational outcomes rather than personal outcomes was found to promote the use of pro-ethical cognitive reasoning strategies. PMID:26257505

SUPPORT Tools for evidence-informed health Policymaking (STP)

PubMed Central

2009-01-01

This article is the Introduction to a series written for people responsible for making decisions about health policies and programmes and for those who support these decision makers. Knowing how to find and use research evidence can help policymakers and those who support them to do their jobs better and more efficiently. Each article in this series presents a proposed tool that can be used by those involved in finding and using research evidence to support evidence-informed health policymaking. The series addresses four broad areas: 1. Supporting evidence-informed policymaking 2. Identifying needs for research evidence in relation to three steps in policymaking processes, namely problem clarification, options framing, and implementation planning 3. Finding and assessing both systematic reviews and other types of evidence to inform these steps, and 4. Going from research evidence to decisions. Each article begins with between one and three typical scenarios relating to the topic. These scenarios are designed to help readers decide on the level of detail relevant to them when applying the tools described. Most articles in this series are structured using a set of questions that guide readers through the proposed tools and show how to undertake activities to support evidence-informed policymaking efficiently and effectively. These activities include, for example, using research evidence to clarify problems, assessing the applicability of the findings of a systematic review about the effects of options selected to address problems, organising and using policy dialogues to support evidence-informed policymaking, and planning policy monitoring and evaluation. In several articles, the set of questions presented offers more general guidance on how to support evidence-informed policymaking. Additional information resources are listed and described in every article. The evaluation of ways to support evidence-informed health policymaking is a developing field and feedback about how to improve the series is welcome. PMID:20018098

IBM’s Health Analytics and Clinical Decision Support

PubMed Central

Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

2014-01-01

Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron.

DTIC Science & Technology

1987-06-01

Security Classification) Design of an Aircrew Scheduling Decision Aid for the 6916th Electronic Security Squadron 12. PERSONAL AUTHOR(S) Thomas J. Kopf...Because of the great number of possible scheduling alternatives, it is difficult to find an optimal solution to-the scheduling problem. Additionally...changes to the original schedule make it even more difficult to find an optimal solution. The emergence of capable microcompu- ters, decision support

Incorporating uncertainty in watershed management decision-making: A mercury TMDL case study

USGS Publications Warehouse

Labiosa, W.; Leckie, J.; Shachter, R.; Freyberg, D.; Rytuba, J.; ,

2005-01-01

Water quality impairment due to high mercury fish tissue concentrations and high mercury aqueous concentrations is a widespread problem in several sub-watersheds that are major sources of mercury to the San Francisco Bay. Several mercury Total Maximum Daily Load regulations are currently being developed to address this problem. Decisions about control strategies are being made despite very large uncertainties about current mercury loading behavior, relationships between total mercury loading and methyl mercury formation, and relationships between potential controls and mercury fish tissue levels. To deal with the issues of very large uncertainties, data limitations, knowledge gaps, and very limited State agency resources, this work proposes a decision analytical alternative for mercury TMDL decision support. The proposed probabilistic decision model is Bayesian in nature and is fully compatible with a "learning while doing" adaptive management approach. Strategy evaluation, sensitivity analysis, and information collection prioritization are examples of analyses that can be performed using this approach.

Surrogate Motherhood and Abortion for Fetal Abnormality.

PubMed

Walker, Ruth; van Zyl, Liezl

2015-10-01

A diagnosis of fetal abnormality presents parents with a difficult - even tragic - moral dilemma. Where this diagnosis is made in the context of surrogate motherhood there is an added difficulty, namely that it is not obvious who should be involved in making decisions about abortion, for the person who would normally have the right to decide - the pregnant woman - does not intend to raise the child. This raises the question: To what extent, if at all, should the intended parents be involved in decision-making? In commercial surrogacy it is thought that as part of the contractual agreement the intended parents acquire the right to make this decision. By contrast, in altruistic surrogacy the pregnant woman retains the right to make these decisions, but the intended parents are free to decide not to adopt the child. We argue that both these strategies are morally unsound, and that the problems encountered serve to highlight more fundamental defects within the commercial and altruistic models, as well as in the legal and institutional frameworks that support them. We argue in favour of the professional model, which acknowledges the rights and responsibilities of both parties and provides a legal and institutional framework that supports good decision-making. In particular, the professional model acknowledges the surrogate's right to decide whether to undergo an abortion, and the intended parents' obligation to accept legal custody of the child. While not solving all the problems that arise in surrogacy, the model provides a framework that supports good decision-making. © 2015 John Wiley & Sons Ltd.

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.

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

PubMed

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

2015-01-01

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

Consensus oriented fuzzified decision support for oil spill contingency management.

PubMed

Liu, Xin; Wirtz, Kai W

2006-06-30

Studies on multi-group multi-criteria decision-making problems for oil spill contingency management are in their infancy. This paper presents a second-order fuzzy comprehensive evaluation (FCE) model to resolve decision-making problems in the area of contingency management after environmental disasters such as oil spills. To assess the performance of different oil combat strategies, second-order FCE allows for the utilization of lexical information, the consideration of ecological and socio-economic criteria and the involvement of a variety of stakeholders. On the other hand, the new approach can be validated by using internal and external checks, which refer to sensitivity tests regarding its internal setups and comparisons with other methods, respectively. Through a case study, the Pallas oil spill in the German Bight in 1998, it is demonstrated that this approach can help decision makers who search for an optimal strategy in multi-thread contingency problems and has a wider application potential in the field of integrated coastal zone management.

Optimal assignment of workers to supporting services in a hospital

NASA Astrophysics Data System (ADS)

Sawik, Bartosz; Mikulik, Jerzy

2008-01-01

Supporting services play an important role in health care institutions such as hospitals. This paper presents an application of operations research model for optimal allocation of workers among supporting services in a public hospital. The services include logistics, inventory management, financial management, operations management, medical analysis, etc. The optimality criterion of the problem is to minimize operations costs of supporting services subject to some specific constraints. The constraints represent specific conditions for resource allocation in a hospital. The overall problem is formulated as an integer program in the literature known as the assignment problem, where the decision variables represent the assignment of people to various jobs. The results of some computational experiments modeled on a real data from a selected Polish hospital are reported.

From Data to Improved Decisions: Operations Research in Healthcare Delivery.

PubMed

Capan, Muge; Khojandi, Anahita; Denton, Brian T; Williams, Kimberly D; Ayer, Turgay; Chhatwal, Jagpreet; Kurt, Murat; Lobo, Jennifer Mason; Roberts, Mark S; Zaric, Greg; Zhang, Shengfan; Schwartz, J Sanford

2017-11-01

The Operations Research Interest Group (ORIG) within the Society of Medical Decision Making (SMDM) is a multidisciplinary interest group of professionals that specializes in taking an analytical approach to medical decision making and healthcare delivery. ORIG is interested in leveraging mathematical methods associated with the field of Operations Research (OR) to obtain data-driven solutions to complex healthcare problems and encourage collaborations across disciplines. This paper introduces OR for the non-expert and draws attention to opportunities where OR can be utilized to facilitate solutions to healthcare problems. Decision making is the process of choosing between possible solutions to a problem with respect to certain metrics. OR concepts can help systematically improve decision making through efficient modeling techniques while accounting for relevant constraints. Depending on the problem, methods that are part of OR (e.g., linear programming, Markov Decision Processes) or methods that are derived from related fields (e.g., regression from statistics) can be incorporated into the solution approach. This paper highlights the characteristics of different OR methods that have been applied to healthcare decision making and provides examples of emerging research opportunities. We illustrate OR applications in healthcare using previous studies, including diagnosis and treatment of diseases, organ transplants, and patient flow decisions. Further, we provide a selection of emerging areas for utilizing OR. There is a timely need to inform practitioners and policy makers of the benefits of using OR techniques in solving healthcare problems. OR methods can support the development of sustainable long-term solutions across disease management, service delivery, and health policies by optimizing the performance of system elements and analyzing their interaction while considering relevant constraints.

The Potential for Meta-Analysis to Support Decision Analysis in Ecology

ERIC Educational Resources Information Center

Mengersen, Kerrie; MacNeil, M. Aaron; Caley, M. Julian

2015-01-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable…

Envisioning the Impact of Decisions Made about Early Childhood Professional Development Systems by Different Constituent Groups

ERIC Educational Resources Information Center

Apple, Peggy; McMullen, Mary Benson

2007-01-01

In this article the authors explore the need for early childhood practitioners and scholars to engage in joint problem solving to create and support early childhood education and care (ECEC) professional development systems in which all constituents benefit. Primary constituent groups and principal decision-making bodies are defined and analyzed,…

Psychosocial working conditions: an analysis of emotional symptoms and conduct problems amongst adolescent students.

PubMed

Plenty, Stephanie; Ostberg, Viveca; Almquist, Ylva B; Augustine, Lilly; Modin, Bitte

2014-06-01

This study explored how psychosocial features of the schoolwork environment are associated with students' mental health. Data was drawn from 3699 ninth grade (15 year-old) Swedish students participating in the Health Behaviour in School-Aged Children survey. Using Structural Equation Modelling, perceived school demands, decision control and social support from teachers, classmates and parents were examined in relation to students' emotional and conduct problems. Higher demands were associated with greater emotional symptoms and conduct problems. Although weaker social support predicted emotional symptoms and conduct problems, the relative influence of teachers, classmates and parents differed. Teacher support was more closely associated with conduct problems, particularly for girls, while classmate support was more strongly related to emotional symptoms. The findings indicate that while excessive school pressure is associated with poorer mental health, social support can assist in optimising adolescents' emotional health and adaptive behaviour, as well as shaping perceptions of demands. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

GIS-based spatial decision support system for grain logistics management

NASA Astrophysics Data System (ADS)

Zhen, Tong; Ge, Hongyi; Jiang, Yuying; Che, Yi

2010-07-01

Grain logistics is the important component of the social logistics, which can be attributed to frequent circulation and the great quantity. At present time, there is no modern grain logistics distribution management system, and the logistics cost is the high. Geographic Information Systems (GIS) have been widely used for spatial data manipulation and model operations and provide effective decision support through its spatial database management capabilities and cartographic visualization. In the present paper, a spatial decision support system (SDSS) is proposed to support policy makers and to reduce the cost of grain logistics. The system is composed of two major components: grain logistics goods tracking model and vehicle routing problem optimization model and also allows incorporation of data coming from external sources. The proposed system is an effective tool to manage grain logistics in order to increase the speed of grain logistics and reduce the grain circulation cost.

Decision support system for the operating room rescheduling problem.

PubMed

van Essen, J Theresia; Hurink, Johann L; Hartholt, Woutske; van den Akker, Bernd J

2012-12-01

Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

Canonical Duality Theory and Algorithms for Solving Some Challenging Problems in Global Optimization and Decision Science

DTIC Science & Technology

2015-09-24

algorithms for solving real- world problems. Within the past five years, 2 books, 5 journal special issues, and about 60 papers have been published...Four international conferences have been organized, including the 3rd World Congress of Global Optimization. A unified methodology and algorithm have...been developed with real- world applications. This grant has been used to support and co-support three post-doctors, three PhD students, one part

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

EPA Pesticide Factsheets

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

Cynefin as Reference Framework to Facilitate Insight and Decision-Making in Complex Contexts of Biomedical Research.

PubMed

Kempermann, Gerd

2017-01-01

The Cynefin scheme is a concept of knowledge management, originally devised to support decision making in management, but more generally applicable to situations, in which complexity challenges the quality of insight, prediction, and decision. Despite the fact that life itself, and especially the brain and its diseases, are complex to the extent that complexity could be considered their cardinal feature, complex problems in biomedicine are often treated as if they were actually not more than the complicated sum of solvable sub-problems. Because of the emergent properties of complex contexts this is not correct. With a set of clear criteria Cynefin helps to set apart complex problems from "simple/obvious," "complicated," "chaotic," and "disordered" contexts in order to avoid misinterpreting the relevant causality structures. The distinction comes with the insight, which specific kind of knowledge is possible in each of these categories and what are the consequences for resulting decisions and actions. From student's theses over the publication and grant writing process to research politics, misinterpretation of complexity can have problematic or even dangerous consequences, especially in clinical contexts. Conceptualization of problems within a straightforward reference language like Cynefin improves clarity and stringency within projects and facilitates communication and decision-making about them.

A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions.

PubMed

Turrini, Enrico; Carnevale, Claudio; Finzi, Giovanna; Volta, Marialuisa

2018-04-15

This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO 2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessment and Treatment of Personality Disorders: A Behavioral Perspective

ERIC Educational Resources Information Center

Nelson-Gray, Rosemery O.; Lootens, Christopher M.; Mitchell, John T.; Robertson, Christopher D.; Hundt, Natalie E.; Kimbrel, Nathan A.

2009-01-01

Personality disorders are complex and highly challenging to treatment providers; yet, for clients with these problems, there exist very few treatment options that have been supported by research. Given the lack of empirically-supported therapies for personality disorders, it can be difficult to make treatment decisions for this population. The…

Developing Intuitive Reasoning with Graphs to Support Science Arguments

ERIC Educational Resources Information Center

Grueber, David

2011-01-01

Graphs are important for supporting critical thinking and scientific argumentation because students can use them to reason, make judgments and decisions, and solve problems like a scientist (Connery 2007). Yet teaching students how to use math to actually think critically continues to be difficult for teachers. This article describes two…

Editorial Commentary: Got Evidence? What We Really Need Is an Algorithm for Treating Symptomatic Bipartite Patella.

PubMed

Fithian, Donald C

2018-05-01

Bipartite patella is an uncommon but potentially troublesome problem for young athletes. Numerous uncontrolled retrospective studies have reported good results after various treatments. What is needed are studies that will guide workup and support treatment decisions based on the condition of the cartilage surfaces of the fragment, presence of pseudoarthrosis, and size and location of the fragment. To support decisions, we need prospective comparative studies, either randomized or, at least, prospective cohort studies that identify patients at the time of presentation, document key decision points, and follow patients to successful resolution of symptoms. Copyright © 2018 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Data warehousing: toward knowledge management.

PubMed

Shams, K; Farishta, M

2001-02-01

With rapid changes taking place in the practice and delivery of health care, decision support systems have assumed an increasingly important role. More and more health care institutions are deploying data warehouse applications as decision support tools for strategic decision making. By making the right information available at the right time to the right decision makers in the right manner, data warehouses empower employees to become knowledge workers with the ability to make the right decisions and solve problems, creating strategic leverage for the organization. Health care management must plan and implement data warehousing strategy using a best practice approach. Through the power of data warehousing, health care management can negotiate bettermanaged care contracts based on the ability to provide accurate data on case mix and resource utilization. Management can also save millions of dollars through the implementation of clinical pathways in better resource utilization and changing physician behavior to best practices based on evidence-based medicine.

Designing Computerized Decision Support That Works for Clinicians and Families

PubMed Central

Fiks, Alexander G.

2011-01-01

Evidence-based decision-making is central to the practice of pediatrics. Clinical trials and other biomedical research provide a foundation for this process, and practice guidelines, drawing from their results, inform the optimal management of an increasing number of childhood health problems. However, many clinicians fail to adhere to guidelines. Clinical decision support delivered using health information technology, often in the form of electronic health records, provides a tool to deliver evidence-based information to the point of care and has the potential to overcome barriers to evidence-based practice. An increasing literature now informs how these systems should be designed and implemented to most effectively improve outcomes in pediatrics. Through the examples of computerized physician order entry, as well as the impact of alerts at the point of care on immunization rates, the delivery of evidence-based asthma care, and the follow-up of children with attention deficit hyperactivity disorder, the following review addresses strategies for success in using these tools. The following review argues that, as decision support evolves, the clinician should no longer be the sole target of information and alerts. Through the Internet and other technologies, families are increasingly seeking health information and gathering input to guide health decisions. By enlisting clinical decision support systems to deliver evidence-based information to both clinicians and families, help families express their preferences and goals, and connect families to the medical home, clinical decision support may ultimately be most effective in improving outcomes. PMID:21315295

Implementing shared decision making in routine mental health care

PubMed Central

Slade, Mike

2017-01-01

Shared decision making (SDM) in mental health care involves clinicians and patients working together to make decisions. The key elements of SDM have been identified, decision support tools have been developed, and SDM has been recommended in mental health at policy level. Yet implementation remains limited. Two justifications are typically advanced in support of SDM. The clinical justification is that SDM leads to improved outcome, yet the available empirical evidence base is inconclusive. The ethical justification is that SDM is a right, but clinicians need to balance the biomedical ethical principles of autonomy and justice with beneficence and non‐maleficence. It is argued that SDM is “polyvalent”, a sociological concept which describes an idea commanding superficial but not deep agreement between disparate stakeholders. Implementing SDM in routine mental health services is as much a cultural as a technical problem. Three challenges are identified: creating widespread access to high‐quality decision support tools; integrating SDM with other recovery‐supporting interventions; and responding to cultural changes as patients develop the normal expectations of citizenship. Two approaches which may inform responses in the mental health system to these cultural changes – social marketing and the hospitality industry – are identified. PMID:28498575

An intelligent, knowledge-based multiple criteria decision making advisor for systems design

NASA Astrophysics Data System (ADS)

Li, Yongchang

In systems engineering, design and operation of systems are two main problems which always attract researcher's attentions. The accomplishment of activities in these problems often requires proper decisions to be made so that the desired goal can be achieved, thus, decision making needs to be carefully fulfilled in the design and operation of systems. Design is a decision making process which permeates through out the design process, and is at the core of all design activities. In modern aircraft design, more and more attention is paid to the conceptual and preliminary design phases so as to increase the odds of choosing a design that will ultimately be successful at the completion of the design process, therefore, decisions made during these early design stages play a critical role in determining the success of a design. Since aerospace systems are complex systems with interacting disciplines and technologies, the Decision Makers (DMs) dealing with such design problems are involved in balancing the multiple, potentially conflicting attributes/criteria, transforming a large amount of customer supplied guidelines into a solidly defined set of requirement definitions. Thus, one could state with confidence that modern aerospace system design is a Multiple Criteria Decision Making (MCDM) process. A variety of existing decision making methods are available to deal with this type of decision problems. The selection of the most appropriate decision making method is of particular importance since inappropriate decision methods are likely causes of misleading engineering design decisions. With no sufficient knowledge about each of the methods, it is usually difficult for the DMs to find an appropriate analytical model capable of solving their problems. In addition, with the complexity of the decision problem and the demand for more capable methods increasing, new decision making methods are emerging with time. These various methods exacerbate the difficulty of the selection of an appropriate decision making method. Furthermore, some DMs may be exclusively using one or two specific methods which they are familiar with or trust and not realizing that they may be inappropriate to handle certain classes of the problems, thus yielding erroneous results. These issues reveal that in order to ensure a good decision a suitable decision method should be chosen before the decision making process proceeds. The first part of this dissertation proposes an MCDM process supported by an intelligent, knowledge-based advisor system referred to as Multi-Criteria Interactive Decision-Making Advisor and Synthesis process (MIDAS), which is able to facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. The second part of this dissertation presents an autonomous decision making advisor which is capable of dealing with ever-evolving real time information and making autonomous decisions under uncertain conditions. The advisor encompasses a Markov Decision Process (MDP) formulation which takes uncertainty into account when determines the best action for each system state. (Abstract shortened by UMI.)

Clinical decision support systems in child and adolescent psychiatry: a systematic review.

PubMed

Koposov, Roman; Fossum, Sturla; Frodl, Thomas; Nytrø, Øystein; Leventhal, Bennett; Sourander, Andre; Quaglini, Silvana; Molteni, Massimo; de la Iglesia Vayá, María; Prokosch, Hans-Ulrich; Barbarini, Nicola; Milham, Michael Peter; Castellanos, Francisco Xavier; Skokauskas, Norbert

2017-11-01

Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13:395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.

Knowledge-based geographic information systems on the Macintosh computer: a component of the GypsES project

Treesearch

Gregory Elmes; Thomas Millette; Charles B. Yuill

1991-01-01

GypsES, a decision-support and expert system for the management of Gypsy Moth addresses five related research problems in a modular, computer-based project. The modules are hazard rating, monitoring, prediction, treatment decision and treatment implementation. One common component is a geographic information system designed to function intelligently. We refer to this...

NURSE-LED INTERVENTION TO IMPROVE SURROGATE DECISION MAKING FOR PATIENTS WITH ADVANCED CRITICAL ILLNESS

PubMed Central

White, Douglas B.; Cua, Sarah Martin; Walk, Roberta; Pollice, Laura; Weissfeld, Lisa; Hong, Seoyeon; Landefeld, C. Seth; Arnold, Robert M.

2013-01-01

Background Problems persist with surrogate decision making in intensive care units, leading to distress for surrogates and treatment that may not reflect patients’ values. Objectives To assess the feasibility, acceptability, and perceived effectiveness of a multifaceted, nurse-led intervention to improve surrogate decision making in intensive care units. Study Design A single-center, single-arm, interventional study in which 35 surrogates and 15 physicians received the Four Supports Intervention, which involved incorporating a family support specialist into the intensive care team. That specialist maintained a longitudinal relationship with surrogates and provided emotional support, communication support, decision support, and anticipatory grief support. A mixed-methods approach was used to evaluate the intervention. Results The intervention was implemented successfully in all 15 patients, with a high level of completion of each component of the intervention. The family support specialist devoted a mean of 48 (SD 36) minutes per day to each clinician-patient-family triad. All participants reported that they would recommend the intervention to others. At least 90% of physicians and surrogates reported that the intervention (1) improved the quality and timeliness of communication, (2) facilitated discussion of the patient’s values and treatment preferences, and (3) improved the patient-centeredness of care. Conclusions The Four Supports Intervention is feasible, acceptable, and was perceived by physicians and surrogates to improve the quality of decision making and the patient-centeredness of care. A randomized trial is warranted to determine whether the intervention improves patient, family, and health system outcomes. PMID:23117903

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.

Web-based GIS for collaborative planning and public participation: an application to the strategic planning of wind farm sites.

PubMed

Simão, Ana; Densham, Paul J; Haklay, Mordechai Muki

2009-05-01

Spatial planning typically involves multiple stakeholders. To any specific planning problem, stakeholders often bring different levels of knowledge about the components of the problem and make assumptions, reflecting their individual experiences, that yield conflicting views about desirable planning outcomes. Consequently, stakeholders need to learn about the likely outcomes that result from their stated preferences; this learning can be supported through enhanced access to information, increased public participation in spatial decision-making and support for distributed collaboration amongst planners, stakeholders and the public. This paper presents a conceptual system framework for web-based GIS that supports public participation in collaborative planning. The framework combines an information area, a Multi-Criteria Spatial Decision Support System (MC-SDSS) and an argumentation map to support distributed and asynchronous collaboration in spatial planning. After analysing the novel aspects of this framework, the paper describes its implementation, as a proof of concept, in a system for Web-based Participatory Wind Energy Planning (WePWEP). Details are provided on the specific implementation of each of WePWEP's four tiers, including technical and structural aspects. Throughout the paper, particular emphasis is placed on the need to support user learning throughout the planning process.

A prototype knowledge-based decision support system for industrial waste management. Part 1: The decision support system

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

Boyle, C.A.; Baetz, B.W.

1998-12-31

Although there are a number of expert systems available which are designed to assist in resolving environmental problems, there is still a need for a system which would assist managers in determining waste management options for all types of wastes from one or more industrial plants, giving priority to sustainable use of resources, reuse and recycling. A prototype model was developed to determine the potentials for reuse and recycling of waste materials, to select the treatments needed to recycle waste materials or for treatment before disposal, and to determine potentials for co-treatment of wastes. A knowledge-based decision support system wasmore » then designed using this model. This paper describes the prototype model, the developed knowledge-based decision support system, the input and storage of data within the system and the inference engine developed for the system to determine the treatment options for the wastes. Options for sorting and selecting treatment trains are described, along with a discussion of the limitations of the approach and future developments needed for the system.« less

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.

Nurse Managers' Decisions: Fast and Favoring Remediation

PubMed Central

Effken, Judith A.; Verran, Joyce A.; Logue, Melanie D.; Hsu, Ya-Chuan

2010-01-01

How do nurse managers make decisions about quality issues on their units? We asked 10 nurse managers in 3 Arizona hospitals to describe how they resolved a recent quality issue. The managers tended to use a linear, but cognitively expensive strategy, often jumping from problem to solution without a clear goal and selecting solutions biased toward remedial education. Decision support tools should help managers think more systemically, systematically and efficiently, while encouraging consideration of more alternatives to reach targeted goals. PMID:20305465

Reviewing model application to support animal health decision making.

PubMed

Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann

2011-04-01

Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated. Copyright © 2011 Elsevier B.V. All rights reserved.

Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

NASA Astrophysics Data System (ADS)

da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

2018-02-01

In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

Health literacy, numeracy, and other characteristics associated with hospitalized patients' preferences for involvement in decision making.

PubMed

Goggins, Kathryn M; Wallston, Kenneth A; Nwosu, Samuel; Schildcrout, Jonathan S; Castel, Liana; Kripalani, Sunil

2014-01-01

Little research has examined the association of health literacy and numeracy with patients' preferred involvement in the problem-solving and decision-making process in the hospital. Using a sample of 1,249 patients hospitalized with cardiovascular disease from the Vanderbilt Inpatient Cohort Study (VICS), we assessed patients' preferred level of involvement using responses to two scenarios of differing symptom severity from the Problem-Solving Decision-Making Scale. Using multivariable modeling, we determined the relationship of health literacy, subjective numeracy, and other patient characteristics with preferences for involvement in decisions, and how this differed by scenario. The authors found that patients with higher levels of health literacy desired more participation in the problem-solving and decision-making process, as did patients with higher subjective numeracy skills, greater educational attainment, female gender, less perceived social support, or greater health care system distrust (p<.05 for each predictor in multivariable models). Patients also preferred to participate more in the decision-making process when the hypothetical symptom they were experiencing was less severe (i.e., they deferred more to their physician when the hypothetical symptom was more severe). These findings underscore the role that patient characteristics, especially health literacy and numeracy, play in decisional preferences among hospitalized patients.

Reasoned Decision Making Without Math? Adaptability and Robustness in Response to Surprise.

PubMed

Smithson, Michael; Ben-Haim, Yakov

2015-10-01

Many real-world planning and decision problems are far too uncertain, too variable, and too complicated to support realistic mathematical models. Nonetheless, we explain the usefulness, in these situations, of qualitative insights from mathematical decision theory. We demonstrate the integration of info-gap robustness in decision problems in which surprise and ignorance are predominant and where personal and collective psychological factors are critical. We present practical guidelines for employing adaptable-choice strategies as a proxy for robustness against uncertainty. These guidelines include being prepared for more surprises than we intuitively expect, retaining sufficiently many options to avoid premature closure and conflicts among preferences, and prioritizing outcomes that are steerable, whose consequences are observable, and that do not entail sunk costs, resource depletion, or high transition costs. We illustrate these concepts and guidelines with the example of the medical management of the 2003 SARS outbreak in Vietnam. © 2015 Society for Risk Analysis.

Approach of Decision Making Based on the Analytic Hierarchy Process for Urban Landscape Management

NASA Astrophysics Data System (ADS)

Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan

2013-03-01

This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.

Approach of decision making based on the analytic hierarchy process for urban landscape management.

PubMed

Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan

2013-03-01

This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.

A study of fuzzy logic ensemble system performance on face recognition problem

NASA Astrophysics Data System (ADS)

Polyakova, A.; Lipinskiy, L.

2017-02-01

Some problems are difficult to solve by using a single intelligent information technology (IIT). The ensemble of the various data mining (DM) techniques is a set of models which are able to solve the problem by itself, but the combination of which allows increasing the efficiency of the system as a whole. Using the IIT ensembles can improve the reliability and efficiency of the final decision, since it emphasizes on the diversity of its components. The new method of the intellectual informational technology ensemble design is considered in this paper. It is based on the fuzzy logic and is designed to solve the classification and regression problems. The ensemble consists of several data mining algorithms: artificial neural network, support vector machine and decision trees. These algorithms and their ensemble have been tested by solving the face recognition problems. Principal components analysis (PCA) is used for feature selection.

MAUD: An Interactive Computer Program for the Structuring, Decomposition, and Recomposition of Preferences between Multiattributed Alternatives. Final Report. Technical Report 543.

ERIC Educational Resources Information Center

Humphreys, Patrick; Wisudha, Ayleen

As a demonstration of the application of heuristic devices to decision-theoretical techniques, an interactive computer program known as MAUD (Multiattribute Utility Decomposition) has been designed to support decision or choice problems that can be decomposed into component factors, or to act as a tool for investigating the microstructure of a…

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

Representing Human Expertise by the OWL Web Ontology Language to Support Knowledge Engineering in Decision Support Systems.

PubMed

Ramzan, Asia; Wang, Hai; Buckingham, Christopher

2014-01-01

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Effective chronic disease management: patients' perspectives on medication-related problems.

PubMed

Gordon, Karen; Smith, Felicity; Dhillon, Soraya

2007-03-01

To examine medication-related problems from the perspective of patients with a chronic condition and to identify how they may be supported in managing their medication. Patients prescribed medication for cardiovascular disease were recruited through five general medical surgeries and four community pharmacies in south London. Data were collected in 98 face-to-face interviews in participants' own homes. Interviews were designed to enable a detailed and holistic exploration of medication-related problems from participants' perspectives. Data were audio-recorded and transcribed verbatim to allow qualitative analysis. Five broad categories of medication-related problem emerged which were examined in the context of patients' perspectives on, and experiences of, the use of medicines and health services. These were concerns about and management of side effects; differing views regarding the use of medicines; cognitive, practical and sensory problems; lack of information or understanding; and problems with access to, and organisation of, services. All categories of problem had potential implications for the success of therapy in that they created barriers to adherence, access to medication or informed decision-making. The study demonstrated how patients actively engage in decision-making about their medicines in the home, if not in the consultation. The five categories of problem provide a focus for interventions by health professionals to support patients in achieving optimal theory outcomes. They demonstrate the need for a comprehensive approach, spanning patient education to the systems of delivery of care. Within the NHS in Britain, policy and practice initiatives are being designed to achieve this end. Further research should focus on the evaluation of professional practices and service developments in supporting patients in the self-management of their medicines.

Common decisions made and actions taken during small-animal consultations at eight first-opinion practices in the United Kingdom.

PubMed

Robinson, N J; Brennan, M L; Cobb, M; Dean, R S

2017-04-01

In order for veterinary surgeons to undertake an evidence-based approach to making decisions about their patients, it is important that new evidence is generated to support the clinical decision-making process. Many of the decisions are likely to be around the actions taken to treat or manage health problems discussed during the consultation, and little is currently known about the factors which affect the type of action taken. The aim of this study was to determine the decisions made and actions taken for health problems discussed during first-opinion small-animal consultations, as well as identifying factors which may affect the decision-making process. Data were gathered during direct observation of small-animal consultations conducted by 62 veterinary surgeons in eight first-opinion practices in the United Kingdom. For each patient presented, data were gathered on all health problems discussed during the consultation. The decision made (whether an action was taken or not) and the action taken where applicable (e.g. therapeutic treatment with antibiotics) was also recorded. A three-level multivariable logistic-regression model was developed, with problem (Level 1) nested within patient (Level 2) nested within consulting veterinary surgeon (Level 3), and a binary outcome variable of action versus no action. At least one action was taken for 69% (n=2203/3192) of all problems discussed. Therapeutic treatment was the most common action taken (n=1286/3192 problems; 40.3%), followed by management advice (n=1040/3192; 32.6%) and diagnostic work-up (n=323/3192; 10.1%). The most common therapeutic treatment was antibiotics (n=386/1286; 30%), while the most common management advice given was dietary advice (n=509/1040; 48.9%). The three explanatory variables remaining in the final model were whether the problem was a presenting or non-presenting problem, the type of diagnosis made, and the body system affected. Explanatory variables which did not remain in the final model were patient signalment, problem history, consultation type, clinical examination type, and who raised the problem (veterinary surgeon or owner). For over two-thirds of problems discussed, an action was taken which suggests these problems may be seen as important by the veterinary surgeon and/or pet owner. No action was taken for almost a third of cases which could represent 'watchful waiting', which has been highlighted as important in human healthcare. Future research should focus on the common actions taken, further exploring the complex decision-making process, and examining the effect of the decisions made on long-term patient outcomes. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Using mobile health technology to deliver decision support for self-monitoring after lung transplantation.

PubMed

Jiang, Yun; Sereika, Susan M; DeVito Dabbs, Annette; Handler, Steven M; Schlenk, Elizabeth A

2016-10-01

Lung transplant recipients (LTR) experience problems recognizing and reporting critical condition changes during their daily health self-monitoring. Pocket PATH(®), a mobile health application, was designed to provide automatic feedback messages to LTR to guide decisions for detecting and reporting critical values of health indicators. To examine the degree to which LTR followed decision support messages to report recorded critical values, and to explore predictors of appropriately following technology decision support by reporting critical values during the first year after transplantation. A cross-sectional correlational study was conducted to analyze existing data from 96 LTR who used the Pocket PATH for daily health self-monitoring. When a critical value is entered, the device automatically generated a feedback message to guide LTR about when and what to report to their transplant coordinators. Their socio-demographics and clinical characteristics were obtained before discharge. Their use of Pocket PATH for health self-monitoring during 12 months was categorized as low (≤25% of days), moderate (>25% to ≤75% of days), and high (>75% of days) use. Following technology decision support was defined by the total number of critical feedback messages appropriately handled divided by the total number of critical feedback messages generated. This variable was dichotomized by whether or not all (100%) feedback messages were appropriately followed. Binary logistic regression was used to explore predictors of appropriately following decision support. Of the 96 participants, 53 had at least 1 critical feedback message generated during 12 months. Of these 53 participants, the average message response rate was 90% and 33 (62%) followed 100% decision support. LTR who moderately used Pocket PATH (n=23) were less likely to follow technology decision support than the high (odds ratio [OR]=0.11, p=0.02) and low (OR=0.04, p=0.02) use groups. The odds of following decision support were reduced in LTR whose income met basic needs (OR=0.01, p=0.01) or who had longer hospital stays (OR=0.94, p=0.004). A significant interaction was found between gender and past technology experience (OR=0.21, p=0.03), suggesting that with increased past technology experience, the odds of following decision support to report all critical values decreased in men but increased in women. The majority of LTR responded appropriately to mobile technology-based decision support for reporting recorded critical values. Appropriately following technology decision support was associated with gender, income, experience with technology, length of hospital stay, and frequency of use of technology for self-monitoring. Clinicians should monitor LTR, who are at risk for poor reporting of recorded critical values, more vigilantly even when LTR are provided with mobile technology decision support. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process

PubMed Central

Masías, Víctor H.; Krause, Mariane; Valdés, Nelson; Pérez, J. C.; Laengle, Sigifredo

2015-01-01

Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice. PMID:25914657

Using decision trees to characterize verbal communication during change and stuck episodes in the therapeutic process.

PubMed

Masías, Víctor H; Krause, Mariane; Valdés, Nelson; Pérez, J C; Laengle, Sigifredo

2015-01-01

Methods are needed for creating models to characterize verbal communication between therapists and their patients that are suitable for teaching purposes without losing analytical potential. A technique meeting these twin requirements is proposed that uses decision trees to identify both change and stuck episodes in therapist-patient communication. Three decision tree algorithms (C4.5, NBTree, and REPTree) are applied to the problem of characterizing verbal responses into change and stuck episodes in the therapeutic process. The data for the problem is derived from a corpus of 8 successful individual therapy sessions with 1760 speaking turns in a psychodynamic context. The decision tree model that performed best was generated by the C4.5 algorithm. It delivered 15 rules characterizing the verbal communication in the two types of episodes. Decision trees are a promising technique for analyzing verbal communication during significant therapy events and have much potential for use in teaching practice on changes in therapeutic communication. The development of pedagogical methods using decision trees can support the transmission of academic knowledge to therapeutic practice.

Economic evaluation of health promotion for older people-methodological problems and challenges.

PubMed

Huter, Kai; Kocot, Ewa; Kissimova-Skarbek, Katarzyna; Dubas-Jakóbczyk, Katarzyna; Rothgang, Heinz

2016-09-05

The support of health promotion activities for older people gains societal relevance in terms of enhancing the health and well-being of older people with a view to the efficient use of financial resources in the healthcare sector. Health economic evaluations have become an important instrument to support decision-making processes in many countries. Sound evidence on the cost-effectiveness of health promotion activities would encourage support for the implementation of health promotion activities for older people. This debate article discusses to what extent economic evaluation techniques are appropriate to support decision makers in the allocation of resources regarding health promotion activities for older people. We address the problem that the economic evaluation of these interventions is hampered by methodological obstacles that limit comparability, e.g. with economic evaluations of curative measures. Our central objective is to describe and discuss the specific problems and challenges entailed in the economic evaluation of health promotion activities especially for older people with regard to their usefulness for informing decision making processes. Beyond general problems concerning the economic evaluation of health promotion, our discussion focusses on problems that pertain to the analysis of cost and outcomes of health promotion interventions for older people. With regard to costs these are general problems of economic evaluations, namely the actual implementation of a societal perspective, the appropriate measurement and valuation of informal caregiver time, the measurement and valuation of productivity costs and costs incurred in added years of life. The main problems concerning the identification and measurement of outcomes are related to the identification of outcome parameters that, firstly, adequately reflect the broad effects of health promotion interventions, especially social benefits that gain importance for older people, and secondly, ensure a comparability of effects across different age groups. In particular, the limitations of the widely used QALY for older people are discussed and recently developed alternatives are presented. The key conclusion of the article is that a comparison of the effects of different health promotion initiatives between different age groups by means of economic evaluation is not recommendable. Taking into account the complex outcomes of health promotion interventions it has to be accepted that the outcomes of these interventions will often not be comparable with clinical interventions and have to be assessed differently.

The ambiguity of patient-centred practices: the case of a Dutch fertility clinic.

PubMed

Gerrits, Trudie

2014-01-01

When in-vitro fertilization (IVF) was introduced in the 1970s, doctors were criticized for not properly informing prospective users about its possible risks and limited success rates as well as for medicalizing fertility problems. Nowadays, many fertility clinics are seeking to improve their accountability to stakeholders through patient-centred practices. Based on an ethnographic study of a Dutch fertility clinic, outspoken in its aims to provide patient-centred medicine and to empower clients, this paper addresses how patient-centred medicine affects couples' decision-making to use IVF and related reproductive technologies. The author contends that while patient-centred practices facilitate informed decision-making and support couples emotionally, they may also have unintended disciplining and normalizing effects. The information and support provided, the trust couples have in clinic staff, the ongoing visualization of conception mediated by medical technology--all can be seen as practices that strengthen lay people's 'medical gaze' in how they come to view their bodies, fertility problems and possible solutions. These unintended effects are labelled 'the ambiguity of patient-centeredness' as they (may) interfere with processes of autonomous decision-making.

Concept of information technology of monitoring and decision-making support

NASA Astrophysics Data System (ADS)

Kovalenko, Aleksandr S.; Tymchyk, Sergey V.; Kostyshyn, Sergey V.; Zlepko, Sergey M.; Wójcik, Waldemar; Kalizhanova, Aliya; Burlibay, Aron; Kozbekova, Ainur

2017-08-01

Presented concept of information technology monitoring and decision support to determine the health of students. The preconditions of a concept formulated its goal and purpose. Subject area concepts proposed to consider a set of problems, grouped into 8 categories, which in turn necessitates the application when creating technology basic principles from the principles of "first head" and "systems approach" to the principles of "interoperability" and "system integration ". The content of the information providing IT, its position in the segment of single information space, stages of creation. To evaluate the efficiency of the IT system developed proposed criteria.

Non-Cooperative Group Decision Support Systems: Problems and Some Solutions.

DTIC Science & Technology

1986-09-01

appears that in these situations the 46 content of the problem and the structure of the problem is " fuzzy ." It requires an active cooperation between the...some unstructured parts will remain. This partial ’unstructurability’ is due to uncertainty, fuzziness , ignorance, and an inability to...according to the Analytic Hierarchy Process ( AHP ) technique (Gui, 1985). The AHP algorithm consists of the following steps; (i) Perform a pairwise comparison

Stochastic search, optimization and regression with energy applications

NASA Astrophysics Data System (ADS)

Hannah, Lauren A.

Designing clean energy systems will be an important task over the next few decades. One of the major roadblocks is a lack of mathematical tools to economically evaluate those energy systems. However, solutions to these mathematical problems are also of interest to the operations research and statistical communities in general. This thesis studies three problems that are of interest to the energy community itself or provide support for solution methods: R&D portfolio optimization, nonparametric regression and stochastic search with an observable state variable. First, we consider the one stage R&D portfolio optimization problem to avoid the sequential decision process associated with the multi-stage. The one stage problem is still difficult because of a non-convex, combinatorial decision space and a non-convex objective function. We propose a heuristic solution method that uses marginal project values---which depend on the selected portfolio---to create a linear objective function. In conjunction with the 0-1 decision space, this new problem can be solved as a knapsack linear program. This method scales well to large decision spaces. We also propose an alternate, provably convergent algorithm that does not exploit problem structure. These methods are compared on a solid oxide fuel cell R&D portfolio problem. Next, we propose Dirichlet Process mixtures of Generalized Linear Models (DPGLM), a new method of nonparametric regression that accommodates continuous and categorical inputs, and responses that can be modeled by a generalized linear model. We prove conditions for the asymptotic unbiasedness of the DP-GLM regression mean function estimate. We also give examples for when those conditions hold, including models for compactly supported continuous distributions and a model with continuous covariates and categorical response. We empirically analyze the properties of the DP-GLM and why it provides better results than existing Dirichlet process mixture regression models. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression like CART, Bayesian trees and Gaussian processes. Compared to existing techniques, the DP-GLM provides a single model (and corresponding inference algorithms) that performs well in many regression settings. Finally, we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whose behavior depends on an exogenous state variable which affects the shape of the objective function. Currently, there is no general purpose algorithm to solve this class of problems. We use nonparametric density estimation to take observations from the joint state-outcome distribution and use them to infer the optimal decision for a given query state. We propose two solution methods that depend on the problem characteristics: function-based and gradient-based optimization. We examine two weighting schemes, kernel-based weights and Dirichlet process-based weights, for use with the solution methods. The weights and solution methods are tested on a synthetic multi-product newsvendor problem and the hour-ahead wind commitment problem. Our results show that in some cases Dirichlet process weights offer substantial benefits over kernel based weights and more generally that nonparametric estimation methods provide good solutions to otherwise intractable problems.

The emergency patient's participation in medical decision-making.

PubMed

Wang, Li-Hsiang; Goopy, Suzanne; Lin, Chun-Chih; Barnard, Alan; Han, Chin-Yen; Liu, Hsueh-Erh

2016-09-01

The purpose of this research was to explore the medical decision-making processes of patients in emergency departments. Studies indicate that patients should be given enough time to acquire relevant information and receive adequate support when they need to make medical decisions. It is difficult to satisfy these requirements in emergency situations. Limited research has addressed the topic of decision-making among emergency patients. This qualitative study used a broadly defined grounded theory approach to explore decision-making in an emergency department in Taiwan. Thirty emergency patients were recruited between June and December 2011 for semi-structured interviews that were audio-taped and transcribed verbatim. The study identified three stages in medical decision-making by emergency patients: predecision (interpreting the problem); decision (a balancing act) and postdecision (reclaiming the self). Transference was identified as the core category and pattern of behaviour through which patients resolved their main concerns. This transference around decision-making represents a type of bricolage. The findings fill a gap in knowledge about the decision-making process among emergency patients. The results inform emergency professionals seeking to support patients faced with complex medical decision-making and suggest an emphasis on informed patient decision-making, advocacy, patient-centred care and in-service education of health staff. © 2016 John Wiley & Sons Ltd.

Theory of the decision/problem state

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

A theory of the decision-problem state was introduced and elaborated. Starting with the basic model of a decision-problem condition, an attempt was made to explain how a major decision-problem may consist of subsets of decision-problem conditions composing different condition sequences. In addition, the basic classical decision-tree model was modified to allow for the introduction of a series of characteristics that may be encountered in an analysis of a decision-problem state. The resulting hierarchical model reflects the unique attributes of the decision-problem state. The basic model of a decision-problem condition was used as a base to evolve a more complex model that is more representative of the decision-problem state and may be used to initiate research on decision-problem states.

Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2017-04-01

Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

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.

Evaluation of the Seniors Offering Support Program of Hoover City Schools.

ERIC Educational Resources Information Center

Petri, Cynthia J.; Geiger, Brian F.; Boling, Whitney; Hartline, Anne; Powers, Catherine

Efforts of one school system in Alabama to respond to students' self-reports of participation in at-risk behaviors are examined. The Seniors Offering Support (SOS) program was designed to deal with these problems. The program aimed towards fostering student resiliency in an attempt to create healthy decision making. The program attempted to…

Using M and S to Improve Human Decision Making and Achieve Effective Problem Solving in an International Environment

NASA Technical Reports Server (NTRS)

Christie, Vanessa L.; Landess, David J.

2012-01-01

In the international arena, decision makers are often swayed away from fact-based analysis by their own individual cultural and political bias. Modeling and Simulation-based training can raise awareness of individual predisposition and improve the quality of decision making by focusing solely on fact vice perception. This improved decision making methodology will support the multinational collaborative efforts of military and civilian leaders to solve challenges more effectively. The intent of this experimental research is to create a framework that allows decision makers to "come to the table" with the latest and most significant facts necessary to determine an appropriate solution for any given contingency.

Use of multicriteria decision analysis to address conservation conflicts.

PubMed

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

2013-10-01

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

Decision support system of e-book provider selection for library using Simple Additive Weighting

NASA Astrophysics Data System (ADS)

Ciptayani, P. I.; Dewi, K. C.

2018-01-01

Each library has its own criteria and differences in the importance of each criterion in choosing an e-book provider for them. The large number of providers and the different importance levels of each criterion make the problem of determining the e-book provider to be complex and take a considerable time in decision making. The aim of this study was to implement Decision support system (DSS) to assist the library in selecting the best e-book provider based on their preferences. The way of DSS works is by comparing the importance of each criterion and the condition of each alternative decision. SAW is one of DSS method that is quite simple, fast and widely used. This study used 9 criteria and 18 provider to demonstrate how SAW work in this study. With the DSS, then the decision-making time can be shortened and the calculation results can be more accurate than manual calculations.

Modeling the Problem-Based Learning Preferences of McMaster University Undergraduate Medical Students Using a Discrete Choice Conjoint Experiment

ERIC Educational Resources Information Center

Cunningham, Charles E.; Deal, Ken; Neville, Alan; Rimas, Heather; Lohfeld, Lynne

2006-01-01

Objectives: To use methods from the field of marketing research to involve students in the redesign of McMaster University's small group, problem-based undergraduate medical education program. Methods: We used themes from a focus group conducted in an electronic decision support lab to compose 14 four-level educational attributes. Undergraduate…

Problem Areas in Data Warehousing and Data Mining in a Surgical Clinic

PubMed Central

Tusch, Guenter; Mueller, Margarete; Rohwer-Mensching, Katrin; Heiringhoff, Karlheinz; Klempnauer, Juergen

2001-01-01

Hospitals and clinics have taken advantage of information systems to streamline many clinical and administrative processes. However, the potential of health care information technology as a source of data for clinical and administrative decision support has not been fully explored. In response to pressure for timely information, many hospitals are developing clinical data warehouses. This paper attempts to identify problem areas in the process of developing a data warehouse to support data mining in surgery. Based on the experience from a data warehouse in surgery several solutions are discussed.

Implementation plan and cost analysis for Oregon's online crash reporting system.

DOT National Transportation Integrated Search

2011-07-01

Federal, state and local transportation agencies, law enforcement, the legislature, consulting firms, safety advocates and the : public use crash data to quantify emerging traffic safety issues and problems, determine priorities, support decision-mak...

The 2014 Sandia Verification and Validation Challenge: Problem statement

DOE PAGES

Hu, Kenneth; Orient, George

2016-01-18

This paper presents a case study in utilizing information from experiments, models, and verification and validation (V&V) to support a decision. It consists of a simple system with data and models provided, plus a safety requirement to assess. The goal is to pose a problem that is flexible enough to allow challengers to demonstrate a variety of approaches, but constrained enough to focus attention on a theme. This was accomplished by providing a good deal of background information in addition to the data, models, and code, but directing the participants' activities with specific deliverables. In this challenge, the theme ismore » how to gather and present evidence about the quality of model predictions, in order to support a decision. This case study formed the basis of the 2014 Sandia V&V Challenge Workshop and this resulting special edition of the ASME Journal of Verification, Validation, and Uncertainty Quantification.« less

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.

A Decision Model for Supporting Task Allocation Processes in Global Software Development

NASA Astrophysics Data System (ADS)

Lamersdorf, Ansgar; Münch, Jürgen; Rombach, Dieter

Today, software-intensive systems are increasingly being developed in a globally distributed way. However, besides its benefit, global development also bears a set of risks and problems. One critical factor for successful project management of distributed software development is the allocation of tasks to sites, as this is assumed to have a major influence on the benefits and risks. We introduce a model that aims at improving management processes in globally distributed projects by giving decision support for task allocation that systematically regards multiple criteria. The criteria and causal relationships were identified in a literature study and refined in a qualitative interview study. The model uses existing approaches from distributed systems and statistical modeling. The article gives an overview of the problem and related work, introduces the empirical and theoretical foundations of the model, and shows the use of the model in an example scenario.

An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

NASA Astrophysics Data System (ADS)

Song, M.; Li, W.; Zhou, X.

2014-12-01

In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

SynopSIS: integrating physician sign-out with the electronic medical record.

PubMed

Sarkar, Urmimala; Carter, Jonathan T; Omachi, Theodore A; Vidyarthi, Arpana R; Cucina, Russell; Bokser, Seth; van Eaton, Erik; Blum, Michael

2007-09-01

Safe delivery of care depends on effective communication among all health care providers, especially during transfers of care. The traditional medical chart does not adequately support such communication. We designed a patient-tracking tool that enhances provider communication and supports clinical decision making. To develop a problem-based patient-tracking tool, called Sign-out, Information Retrieval, and Summary (SynopSIS), in order to support patient tracking, transfers of care (ie, sign-outs), and daily rounds. Tertiary-care, university-based teaching hospital. SynopSIS compiles and organizes information from the electronic medical record to support hospital discharge and disposition decisions, daily provider decisions, and overnight or cross-coverage decisions. It reflects the provider's patient-care and daily work-flow needs. We plan to use Web-based surveys, audits of daily use, and interdisciplinary focus groups to evaluate SynopSIS's impact on communication between providers, quality of sign-out, patient continuity of care, and rounding efficiency. We expect SynopSIS to improve care by facilitating communication between care teams, standardizing sign-out, and automating daily review of clinical and laboratory trends. SynopSIS redesigns the clinical chart to better serve provider and patient needs. (c) 2007 Society of Hospital Medicine.

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.

Interorganizational transfer of technology - A study of adoption of NASA innovations

NASA Technical Reports Server (NTRS)

Chakrabarti, A. K.; Rubenstein, A. H.

1976-01-01

The paper describes a study on the effects of top management support, various techno-economic factors, organizational climate, and decision-making modes on the adoption of NASA innovations. Field research consisted of interviews and questionnaires directed to sixty-five organizations. Forty-five test cases where different decisions for adoption of ideas for new products or processes were made on NASA Tech Briefs were studied in relation to the effects of various factors on the degree of success of adoption, including: (1) the degree of general connection of the technology to the firm's existing operation, (2) the specificity of the relationship between the technology and some existing and recognized problem, (3) the degree of urgency of the problem to which the technology was related, (4) maturity of technology available to implement the technology, (5) availability of personnel and financial resources to implement the technology, (6) degree of top management interest, (7) the use of confrontation in joint-decision, (8) the use of smoothing in decision-making, and (9) the use of forcing in decision-making. It was found that top managements interest was important in the product cases only, and that the success of process innovations was dependent on the quality of information and the specificity of the relationship between the technology and some recognized existing problem.

Seeing the NICE side of cost-effectiveness analysis: a qualitative investigation of the use of CEA in NICE technology appraisals.

PubMed

Bryan, Stirling; Williams, Iestyn; McIver, Shirley

2007-02-01

Resource scarcity is the raison d'être for the discipline of economics. Thus, the primary purpose of economic analysis is to help decision-makers when addressing problems arising due to the scarcity problem. The research reported here was concerned with how cost-effectiveness information is used by the National Institute for Health & Clinical Excellence (NICE) in national technology coverage decisions in the UK, and how its impact might be increased. The research followed a qualitative case study methodology with semi-structured interviews, supported by observation and analysis of secondary sources. Our research highlights that the technology appraisal function of NICE represents an important progression for the UK health economics community: new cost-effectiveness work is commissioned for each technology and that work directly informs national health policy. However, accountability in policy decisions necessitates that the information upon which decisions are based (including cost-effectiveness analysis, CEA) is accessible. This was found to be a serious problem and represents one of the main ongoing challenges. Other issues highlighted include perceived weaknesses in analysis methods and the poor alignment between the health maximisation objectives assumed in economic analyses and the range of other objectives facing decision-makers in reality. Copyright (c) 2006 John Wiley & Sons, Ltd.

WHAT DOESNT GET MEASURED - DOESNT GET DONE: IMPLEMENTING CONTINUOUS PROCESS IMPROVEMENT IN THE AIR FORCE RESERVE

DTIC Science & Technology

2016-04-01

Practical Problem Solving Method RMD Resource Management Decision ROI Return on Investment SECAF Secretary of the Air Force SECNAV Secretary of...AFSO21 and now AF CPI, this program seeks to train and certify an organic cadre of CPI practitioners to support the use of its standard problem solving ...process known as the AF Practical Problem Solving Method (PPSM) to solve mission critical process deficiencies. The PPSM leverages several industry

Decision support system for drinking water management

NASA Astrophysics Data System (ADS)

Janža, M.

2012-04-01

The problems in drinking water management are complex and often solutions must be reached under strict time constrains. This is especially distinct in case of environmental accidents in the catchment areas of the wells that are used for drinking water supply. The beneficial tools that can help decision makers and make program of activities more efficient are decision support systems (DSS). In general they are defined as computer-based support systems that help decision makers utilize data and models to solve unstructured problems. The presented DSS was developed in the frame of INCOME project which is focused on the long-term stable and safe drinking water supply in Ljubljana. The two main water resources Ljubljana polje and Barje alluvial aquifers are characterized by a strong interconnection of surface and groundwater, high vulnerability, high velocities of groundwater flow and pollutant transport. In case of sudden pollution, reactions should be very fast to avoid serious impact to the water supply. In the area high pressures arising from urbanization, industry, traffic, agriculture and old environmental burdens. The aim of the developed DSS is to optimize the activities in cases of emergency water management and to optimize the administrative work regarding the activities that can improve groundwater quality status. The DSS is an interactive computer system that utilizes data base, hydrological modelling, and experts' and stakeholders' knowledge. It consists of three components, tackling the different abovementioned issues in water management. The first one utilizes the work on identification, cleaning up and restoration of illegal dumpsites that are a serious threat to the qualitative status of groundwater. The other two components utilize the predictive capability of the hydrological model and scenario analysis. The user interacts with the system by a graphical interface that guides the user step-by-step to the recommended remedial measures. Consequently, the acquisition of information to support the water management's decisions is simplified and faster, thus contributing to more efficient water management and a safer supply of drinking water.

Empirical evaluation of decision support systems: Needs, definitions, potential methods, and an example pertaining to waterfowl management

USGS Publications Warehouse

Sojda, R.S.

2007-01-01

Decision support systems are often not empirically evaluated, especially the underlying modelling components. This can be attributed to such systems necessarily being designed to handle complex and poorly structured problems and decision making. Nonetheless, evaluation is critical and should be focused on empirical testing whenever possible. Verification and validation, in combination, comprise such evaluation. Verification is ensuring that the system is internally complete, coherent, and logical from a modelling and programming perspective. Validation is examining whether the system is realistic and useful to the user or decision maker, and should answer the question: “Was the system successful at addressing its intended purpose?” A rich literature exists on verification and validation of expert systems and other artificial intelligence methods; however, no single evaluation methodology has emerged as preeminent. At least five approaches to validation are feasible. First, under some conditions, decision support system performance can be tested against a preselected gold standard. Second, real-time and historic data sets can be used for comparison with simulated output. Third, panels of experts can be judiciously used, but often are not an option in some ecological domains. Fourth, sensitivity analysis of system outputs in relation to inputs can be informative. Fifth, when validation of a complete system is impossible, examining major components can be substituted, recognizing the potential pitfalls. I provide an example of evaluation of a decision support system for trumpeter swan (Cygnus buccinator) management that I developed using interacting intelligent agents, expert systems, and a queuing system. Predicted swan distributions over a 13-year period were assessed against observed numbers. Population survey numbers and banding (ringing) studies may provide long term data useful in empirical evaluation of decision support.

Developing infrastructure for interconnecting transportation network and electric grid.

DOT National Transportation Integrated Search

2011-09-01

This report is primarily focused on the development of mathematical models that can be used to : support decisions regarding a charging station location and installation problem. The major parts : of developing the models included identification of t...

Computer Models Used to Support Cleanup Decision Making at Hazardous and Radioactive Waste Sites

EPA Pesticide Factsheets

This report is a product of the Interagency Environmental Pathway Modeling Workgroup. This report will help bring a uniform approach to solving environmental modeling problems common to site remediation and restoration efforts.

Developing a model-based decision support system for call-a-ride paratransit service problems.

DOT National Transportation Integrated Search

2011-02-01

Paratransit is the transportation service that supplements larger public transportation : systems by providing individualized rides without fixed routes or timetables. In 1990, : the Americans with Disabilities Act (ADA) was passed which allows passe...

Pieces of the Puzzle: Tracking the Chemical Component of the ...

EPA Pesticide Factsheets

This presentation provides an overview of the risk assessment conducted at the U.S. EPA, as well as some research examples related to the exposome concept. This presentation also provides the recommendation of using two organizational and predictive frameworks for tracking chemical components in the exposome. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

The Air Quality Model Evaluation International Initiative ...

EPA Pesticide Factsheets

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

A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology

NASA Astrophysics Data System (ADS)

Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli

2007-06-01

Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.

Fuzzy cognitive maps for issue identification in a water resources conflict resolution system

NASA Astrophysics Data System (ADS)

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

In water management, conflicts of interests are inevitable due to the variety in quality demands and the number of stakeholders, which are affected in different ways by decisions concerning the use of the resources. Ignoring the differences among interests involved in water resources management and not resolving the emerging conflicts could lead to controversial strategies. In such cases, proposed solutions could generate strong opposition, making these solutions unfeasible. In our contribution, a Community Decision Support System is proposed. Such a system is able to support discussion and collaboration. The system helps participants to structure their problem, to help them learn about possible alternatives, their constraints and implications and to support the participants in the specification of their own preferences. More in detail, the proposed system helps each user in representing and communicating problem perspectives. To reach this aim, cognitive maps are used to capture parts of the stakeholders’ point of view and to enhance negotiation among individuals and organizations. The aim of the negotiation process is to define a shared cognitive map with regard to water management problems. Such a map can be called a water community cognitive map. The system performance has been tested by simulating a real conflict on water resources management that occurred some years ago in a river basin in the south of Italy.

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

PubMed

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

2016-01-01

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

SUPPORT Tools for evidence-informed health Policymaking (STP) 4: Using research evidence to clarify a problem

PubMed Central

2009-01-01

This article is part of a series written for people responsible for making decisions about health policies and programmes and for those who support these decision makers. Policymakers and those supporting them often find themselves in situations that spur them on to work out how best to define a problem. These situations may range from being asked an awkward or challenging question in the legislature, through to finding a problem highlighted on the front page of a newspaper. The motivations for policymakers wanting to clarify a problem are diverse. These may range from deciding whether to pay serious attention to a particular problem that others claim is important, through to wondering how to convince others to agree that a problem is important. Debates and struggles over how to define a problem are a critically important part of the policymaking process. The outcome of these debates and struggles will influence whether and, in part, how policymakers take action to address a problem. Efforts at problem clarification that are informed by an appreciation of concurrent developments are more likely to generate actions. These concurrent developments can relate to policy and programme options (e.g. the publication of a report demonstrating the effectiveness of a particular option) or to political events (e.g. the appointment of a new Minister of Health with a personal interest in a particular issue). In this article, we suggest questions that can be used to guide those involved in identifying a problem and characterising its features. These are: 1. What is the problem? 2. How did the problem come to attention and has this process influenced the prospect of it being addressed? 3. What indicators can be used, or collected, to establish the magnitude of the problem and to measure progress in addressing it? 4. What comparisons can be made to establish the magnitude of the problem and to measure progress in addressing it? 5. How can the problem be framed (or described) in a way that will motivate different groups? PMID:20018111

A Framework for Multi-Stakeholder Decision-Making and ...

EPA Pesticide Factsheets

This contribution describes the implementation of the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. It is observed that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as random variables. We thus shape the dissatisfaction distribution and find an optimal compromise solution by solving a CVaR minimization problem parameterized in the probability level. This enables us to generalize multi-stakeholder settings previously proposed in the literature that minimizes average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework. We demonstrate the framework in a bio-waste processing facility location case study, where we seek compromise solutions (facility locations) that balance stakeholder priorities on transportation, safety, water quality, and capital costs. This conference presentation abstract explains a new decision-making framework that computes compromise solution alternatives (reach consensus) by mitigating dissatisfactions among stakeholders as needed for SHC Decision Science and Support Tools project.

Managing the Risks of Climate Change and Terrorism

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

Rosa, Eugene; Dietz, Tom; Moss, Richard H.

2012-04-07

Society has difficult decisions to make about how best to allocate its resources to ensure future sustainability. Risk assessment can be a valuable tool: it has long been used to support decisions to address environmental problems. But in a time when the risks to sustainability range from climate change to terrorism, applying risk assessment to sustainability will require careful rethinking. For new threats, we will need a new approach to risk assessment.

The Warfighter Associate: Decision-Support and Metrics for Mission Command

DTIC Science & Technology

2013-01-01

complex situations can be captured it makes sense to use software to provide this important adjunct to complex human cognitive problems. As a software...tasks that could distract the user from the important events occurring. An Associate System also observes the actions undertaken by a human operator...the Commander’s Critical Information Requirements. ‡It is important to note that the Warfighter Associate maintains a human -in-the-loop for decision

A decision support framework for characterizing and managing dermal exposures to chemicals during Emergency Management and Operations.

PubMed

Dotson, G Scott; Hudson, Naomi L; Maier, Andrew

2015-01-01

Emergency Management and Operations (EMO) personnel are in need of resources and tools to assist in understanding the health risks associated with dermal exposures during chemical incidents. This article reviews available resources and presents a conceptual framework for a decision support system (DSS) that assists in characterizing and managing risk during chemical emergencies involving dermal exposures. The framework merges principles of three decision-making techniques: 1) scenario planning, 2) risk analysis, and 3) multicriteria decision analysis (MCDA). This DSS facilitates dynamic decision making during each of the distinct life cycle phases of an emergency incident (ie, preparedness, response, or recovery) and identifies EMO needs. A checklist tool provides key questions intended to guide users through the complexities of conducting a dermal risk assessment. The questions define the scope of the framework for resource identification and application to support decision-making needs. The framework consists of three primary modules: 1) resource compilation, 2) prioritization, and 3) decision. The modules systematically identify, organize, and rank relevant information resources relating to the hazards of dermal exposures to chemicals and risk management strategies. Each module is subdivided into critical elements designed to further delineate the resources based on relevant incident phase and type of information. The DSS framework provides a much needed structure based on contemporary decision analysis principles for 1) documenting key questions for EMO problem formulation and 2) a method for systematically organizing, screening, and prioritizing information resources on dermal hazards, exposures, risk characterization, and management.

A decision support framework for characterizing and managing dermal exposures to chemicals during Emergency Management and Operations

PubMed Central

Dotson, G. Scott; Hudson, Naomi L.; Maier, Andrew

2016-01-01

Emergency Management and Operations (EMO) personnel are in need of resources and tools to assist in understanding the health risks associated with dermal exposures during chemical incidents. This article reviews available resources and presents a conceptual framework for a decision support system (DSS) that assists in characterizing and managing risk during chemical emergencies involving dermal exposures. The framework merges principles of three decision-making techniques: 1) scenario planning, 2) risk analysis, and 3) multicriteria decision analysis (MCDA). This DSS facilitates dynamic decision making during each of the distinct life cycle phases of an emergency incident (ie, preparedness, response, or recovery) and identifies EMO needs. A checklist tool provides key questions intended to guide users through the complexities of conducting a dermal risk assessment. The questions define the scope of the framework for resource identification and application to support decision-making needs. The framework consists of three primary modules: 1) resource compilation, 2) prioritization, and 3) decision. The modules systematically identify, organize, and rank relevant information resources relating to the hazards of dermal exposures to chemicals and risk management strategies. Each module is subdivided into critical elements designed to further delineate the resources based on relevant incident phase and type of information. The DSS framework provides a much needed structure based on contemporary decision analysis principles for 1) documenting key questions for EMO problem formulation and 2) a method for systematically organizing, screening, and prioritizing information resources on dermal hazards, exposures, risk characterization, and management. PMID:26312660

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 Development and Validation of the Rational and Intuitive Decision Styles Scale.

PubMed

Hamilton, Katherine; Shih, Shin-I; Mohammed, Susan

2016-01-01

Decision styles reflect the typical manner by which individuals make decisions. The purpose of this research was to develop and validate a decision style scale that addresses conceptual and psychometric problems with current measures. The resulting 10-item scale captures a broad range of the rational and intuitive styles construct domain. Results from 5 independent samples provide initial support for the dimensionality and reliability of the new scale, as demonstrated by a clear factor structure and high internal consistency. In addition, our results show evidence of convergent and discriminant validity through expected patterns of correlations across decision-making individual differences and the International Personality Item Pool (IPIP) Big Five traits. Research domains that would benefit from incorporating the concept of decision styles are discussed.

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

PubMed

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

2014-02-01

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

An older worker's decision to "push or protect self" following a work-related injury.

PubMed

Stikeleather, Jill

2004-01-01

This study highlights the return-to-work experience of older workers on worker's compensation as there is a dearth of research in this area. Qualitative research methods delineated the experience of four older workers who had sustained work-related musculoskeletal injuries. "Push or Protect Self" emerged as the core category with three themes, including the level of employer support and degree of flexibility in work; continued health problems; and financial distress. These themes influenced each worker's decision to either "push self" to meet their pre-injury work demands, or "protect self" and accept a job post-injury that was less physically demanding, but was at a lower pay level. The four workers sustained financial difficulties subsequent to being off work, and reported continued health problems related to their injuries after being discharged from the worker's compensation system. Degree of employer support in providing flexibility in work demands varied, where low support and inflexibility in job tasks contributed to difficulty in returning to work or in sustaining the work demands of the job.

Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2017-12-01

Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case studies to highlight how Cloud CI streamlines the process for setting up an interactive decision support system. Moreover, advances in artificial intelligence offer new techniques for old problems from integrating data to adaptive sensing or from interactive dashboards to optimizing multi-attribute problems. The combination of scientific expertise, flexible cloud computing solutions, and intelligent systems opens new research horizons.

The relationship between three-dimensional imaging and group decision making: an exploratory study.

PubMed

Litynski, D M; Grabowski, M; Wallace, W A

1997-07-01

This paper describes an empirical investigation of the effect of three dimensional (3-D) imaging on group performance in a tactical planning task. The objective of the study is to examine the role that stereoscopic imaging can play in supporting face-to-face group problem solving and decision making-in particular, the alternative generation and evaluation processes in teams. It was hypothesized that with the stereoscopic display, group members would better visualize the information concerning the task environment, producing open communication and information exchanges. The experimental setting was a tactical command and control task, and the quality of the decisions and nature of the group decision process were investigated with three treatments: 1) noncomputerized, i.e., topographic maps with depth cues; 2) two-dimensional (2-D) imaging; and 3) stereoscopic imaging. The results were mixed on group performance. However, those groups with the stereoscopic displays generated more alternatives and spent less time on evaluation. In addition, the stereoscopic decision aid did not interfere with the group problem solving and decision-making processes. The paper concludes with a discussion of potential benefits, and the need to resolve demonstrated weaknesses of the technology.

An Overview Of The Ecosystem Services Research Program Decision Support Framework

EPA Science Inventory

There is an increasing understanding that top-down regulatory and technology driven responses are not sufficient to address current and emerging environmental challenges such as climate change, sustainable communities, and environmental justice. Such problems require ways to dee...

Design of Tactical Support Strategies in Military Logistics: Trade-offs Between Efficiency and Effectiveness. A Column and Cut Generation Modeling Methods

DTIC Science & Technology

2011-12-01

problems need to be addressed in the design of military logis- tics networks. The design problem includes strategic decisions, such as the location of...military strategic logistics [11–13]. In this study, we focus on the design of tactical logistics strategies, which achieve different optimal balances...is clear that our problem is N P−Hard 1 since it generalizes the CVPR and the BPP . Different solutions to handle the loading and routing of

Dynamic simulation modelling of policy responses to reduce alcohol-related harms: rationale and procedure for a participatory approach.

PubMed

Atkinson, Jo-An; O'Donnell, Eloise; Wiggers, John; McDonnell, Geoff; Mitchell, Jo; Freebairn, Louise; Indig, Devon; Rychetnik, Lucie

2017-02-15

Development of effective policy responses to address complex public health problems can be challenged by a lack of clarity about the interaction of risk factors driving the problem, differing views of stakeholders on the most appropriate and effective intervention approaches, a lack of evidence to support commonly implemented and acceptable intervention approaches, and a lack of acceptance of effective interventions. Consequently, political considerations, community advocacy and industry lobbying can contribute to a hotly contested debate about the most appropriate course of action; this can hinder consensus and give rise to policy resistance. The problem of alcohol misuse and its associated harms in New South Wales (NSW), Australia, provides a relevant example of such challenges. Dynamic simulation modelling is increasingly being valued by the health sector as a robust tool to support decision making to address complex problems. It allows policy makers to ask 'what-if' questions and test the potential impacts of different policy scenarios over time, before solutions are implemented in the real world. Participatory approaches to modelling enable researchers, policy makers, program planners, practitioners and consumer representatives to collaborate with expert modellers to ensure that models are transparent, incorporate diverse evidence and perspectives, are better aligned to the decision-support needs of policy makers, and can facilitate consensus building for action. This paper outlines a procedure for embedding stakeholder engagement and consensus building in the development of dynamic simulation models that can guide the development of effective, coordinated and acceptable policy responses to complex public health problems, such as alcohol-related harms in NSW.

Ethically problematic treatment decisions: a physician survey.

PubMed

Saarni, Samuli I; Parmanne, Piitu; Halila, Ritva

2008-02-01

Experiencing ethical problems requires both ethically problematic situations and ethical sensitivity. Ethically problematic treatment decisions are distressing and might reflect health care quality problems. Whether all physicians actually experience ethical problems, what these problems are and how they vary according to physician age, gender and work sector are largely unknown. A mail survey of all non-retired physicians licensed in Finland (n = 17,172, response rate 75.6%). The proportion of physicians reporting having made ethically problematic treatment decisions decreased in linear fashion from 60% at ages below 30 years to 21% at ages over 63 years. The only problem that did not decrease in frequency with age was having withdrawn necessary treatments. Women and primary care physicians reported problematic decisions most often, although gender differences were small. Primary care physicians most often reported having performed too many investigations or having pressured patients, whereas hospital physicians emphasized having withdrawn necessary treatments. Performing unnecessary treatments or investigations was explained by pressure from patients or relatives, and performing too few treatments or investigations was explained by inadequate resources. In general, young physicians felt pressured to do too much, whereas older physicians felt they could not do enough due to inadequate resources. Older physicians might be less exposed to ethically problematic situations, be more able to handle them or have lower ethical sensitivity. Young physicians could benefit from support in resisting pressure to perform unnecessary treatments, whereas older physicians might benefit from training in recognizing ethical issues.

Challenges in building intelligent systems for space mission operations

NASA Technical Reports Server (NTRS)

Hartman, Wayne

1991-01-01

The purpose here is to provide a top-level look at the stewardship functions performed in space operations, and to identify the major issues and challenges that must be addressed to build intelligent systems that can realistically support operations functions. The focus is on decision support activities involving monitoring, state assessment, goal generation, plan generation, and plan execution. The bottom line is that problem solving in the space operations domain is a very complex process. A variety of knowledge constructs, representations, and reasoning processes are necessary to support effective human problem solving. Emulating these kinds of capabilities in intelligent systems offers major technical challenges that the artificial intelligence community is only beginning to address.

The ambiguity of patient-centred practices: the case of a Dutch fertility clinic

PubMed Central

Gerrits, Trudie

2014-01-01

When in-vitro fertilization (IVF) was introduced in the 1970s, doctors were criticized for not properly informing prospective users about its possible risks and limited success rates as well as for medicalizing fertility problems. Nowadays, many fertility clinics are seeking to improve their accountability to stakeholders through patient-centred practices. Based on an ethnographic study of a Dutch fertility clinic, outspoken in its aims to provide patient-centred medicine and to empower clients, this paper addresses how patient-centred medicine affects couples’ decision-making to use IVF and related reproductive technologies. The author contends that while patient-centred practices facilitate informed decision-making and support couples emotionally, they may also have unintended disciplining and normalizing effects. The information and support provided, the trust couples have in clinic staff, the ongoing visualization of conception mediated by medical technology – all can be seen as practices that strengthen lay people's ‘medical gaze’ in how they come to view their bodies, fertility problems and possible solutions. These unintended effects are labelled ‘the ambiguity of patient-centeredness’ as they (may) interfere with processes of autonomous decision-making. PMID:24827743

A business man views commercial ventures in space.

NASA Technical Reports Server (NTRS)

Scarff, D. D.; Bloom, H. L.

1973-01-01

Paper reviews technical, resource planning and marketing steps an industrial organization must perform in arriving at a decision to undertake space development and production of commercial products or services for Users on the ground. Technical elements are supported by particular examples. Analysis of required resources emphasizes facility and financial inter-relationships between commercial organizations and NASA. Marketing planning covers elements of profitability. Paper addresses questions related to protection of corporate stockholders and public interest, investment decision timing, budget variations. Paper concludes with observations on timeliness of planning shuttle-based commercial ventures and on key industry/NASA problems and decisions.

Solving fuzzy shortest path problem by genetic algorithm

NASA Astrophysics Data System (ADS)

Syarif, A.; Muludi, K.; Adrian, R.; Gen, M.

2018-03-01

Shortest Path Problem (SPP) is known as one of well-studied fields in the area Operations Research and Mathematical Optimization. It has been applied for many engineering and management designs. The objective is usually to determine path(s) in the network with minimum total cost or traveling time. In the past, the cost value for each arc was usually assigned or estimated as a deteministic value. For some specific real world applications, however, it is often difficult to determine the cost value properly. One way of handling such uncertainty in decision making is by introducing fuzzy approach. With this situation, it will become difficult to solve the problem optimally. This paper presents the investigations on the application of Genetic Algorithm (GA) to a new SPP model in which the cost values are represented as Triangular Fuzzy Number (TFN). We adopts the concept of ranking fuzzy numbers to determine how good the solutions. Here, by giving his/her degree value, the decision maker can determine the range of objective value. This would be very valuable for decision support system in the real world applications.Simulation experiments were carried out by modifying several test problems with 10-25 nodes. It is noted that the proposed approach is capable attaining a good solution with different degree of optimism for the tested problems.

Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks

NASA Astrophysics Data System (ADS)

Horita, Flávio E. A.; Albuquerque, João Porto de; Degrossi, Lívia C.; Mendiondo, Eduardo M.; Ueyama, Jó

2015-07-01

Effective flood risk management requires updated information to ensure that the correct decisions can be made. This can be provided by Wireless Sensor Networks (WSN) which are a low-cost means of collecting updated information about rivers. Another valuable resource is Volunteered Geographic Information (VGI) which is a comparatively new means of improving the coverage of monitored areas because it is able to supply supplementary information to the WSN and thus support decision-making in flood risk management. However, there still remains the problem of how to combine WSN data with VGI. In this paper, an attempt is made to investigate AGORA-DS, which is a Spatial Decision Support System (SDSS) that is able to make flood risk management more effective by combining these data sources, i.e. WSN with VGI. This approach is built over a conceptual model that complies with the interoperable standards laid down by the Open Geospatial Consortium (OGC) - e.g. Sensor Observation Service (SOS) and Web Feature Service (WFS) - and seeks to combine and present unified information in a web-based decision support tool. This work was deployed in a real scenario of flood risk management in the town of São Carlos in Brazil. The evidence obtained from this deployment confirmed that interoperable standards can support the integration of data from distinct data sources. In addition, they also show that VGI is able to provide information about areas of the river basin which lack data since there is no appropriate station in the area. Hence it provides a valuable support for the WSN data. It can thus be concluded that AGORA-DS is able to combine information provided by WSN and VGI, and provide useful information for supporting flood risk management.

The window of opportunity: decision theory and the timing of prognostic tests for newborn infants.

PubMed

Wilkinson, Dominic

2009-11-01

In many forms of severe acute brain injury there is an early phase when prognosis is uncertain, followed later by physiological recovery and the possibility of more certain predictions of future impairment. There may be a window of opportunity for withdrawal of life support early, but if decisions are delayed there is the risk that the patient will survive with severe impairment. In this paper I focus on the example of neonatal encephalopathy and the question of the timing of prognostic tests and decisions to continue or to withdraw life-sustaining treatment. Should testing be performed early or later; and how should parents decide what to do given the conflicting values at stake? I apply decision theory to the problem, using sensitivity analysis to assess how different features of the tests or different values would affect a decision to perform early or late prognostic testing. I draw some general conclusions from this model for decisions about the timing of testing in neonatal encephalopathy. Finally I consider possible solutions to the problem posed by the window of opportunity. Decision theory highlights the costs of uncertainty. This may prompt further research into improving prognostic tests. But it may also prompt us to reconsider our current attitudes towards the palliative care of newborn infants predicted to be severely impaired.

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.

Design Requirements for a Decision Support System for the Dynamic Retasking of Electronic Combat Assets.

DTIC Science & Technology

1988-03-01

primary mission was not pursued. The question of the *t employment and retasking of EC assets is basically a question of command and control, though...The] primary function of command is deploying and maneuvering forces or other sources of potential power to be in the best possible position to...unstructured, and multivariable problem. Research Objective The primary objective of this research is to develop an initial set requirements for a decision

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

NASA Astrophysics Data System (ADS)

Jiang, Wen; Wei, Boya

2018-02-01

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

STATISTICS-BASED APPROACH TO WASTEWATER TREATMENT PLANT OPERATIONS

EPA Science Inventory

This paper describes work toward development of a convenient decision support system to improve everyday operation and control of the wastewater treatment process. The goal is to help the operator detect problems in the process and select appropriate control actions. The system...

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

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

Soltani, Atousa; Hewage, Kasun; Reza, Bahareh

2015-01-15

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

Evidence-based Sensor Tasking for Space Domain Awareness

NASA Astrophysics Data System (ADS)

Jaunzemis, A.; Holzinger, M.; Jah, M.

2016-09-01

Space Domain Awareness (SDA) is the actionable knowledge required to predict, avoid, deter, operate through, recover from, and/or attribute cause to the loss and/or degradation of space capabilities and services. A main purpose for SDA is to provide decision-making processes with a quantifiable and timely body of evidence of behavior(s) attributable to specific space threats and/or hazards. To fulfill the promise of SDA, it is necessary for decision makers and analysts to pose specific hypotheses that may be supported or refuted by evidence, some of which may only be collected using sensor networks. While Bayesian inference may support some of these decision making needs, it does not adequately capture ambiguity in supporting evidence; i.e., it struggles to rigorously quantify 'known unknowns' for decision makers. Over the past 40 years, evidential reasoning approaches such as Dempster Shafer theory have been developed to address problems with ambiguous bodies of evidence. This paper applies mathematical theories of evidence using Dempster Shafer expert systems to address the following critical issues: 1) How decision makers can pose critical decision criteria as rigorous, testable hypotheses, 2) How to interrogate these hypotheses to reduce ambiguity, and 3) How to task a network of sensors to gather evidence for multiple competing hypotheses. This theory is tested using a simulated sensor tasking scenario balancing search versus track responsibilities.

A Conceptual Framework for Decision-making Support in Uncertainty- and Risk-based Diagnosis of Rare Clinical Cases by Specialist Physicians.

PubMed

Santos, Adriano A; Moura, J Antão B; de Araújo, Joseana Macêdo Fechine Régis

2015-01-01

Mitigating uncertainty and risks faced by specialist physicians in analysis of rare clinical cases is something desired by anyone who needs health services. The number of clinical cases never seen by these experts, with little documentation, may introduce errors in decision-making. Such errors negatively affect well-being of patients, increase procedure costs, rework, health insurance premiums, and impair the reputation of specialists and medical systems involved. In this context, IT and Clinical Decision Support Systems (CDSS) play a fundamental role, supporting decision-making process, making it more efficient and effective, reducing a number of avoidable medical errors and enhancing quality of treatment given to patients. An investigation has been initiated to look into characteristics and solution requirements of this problem, model it, propose a general solution in terms of a conceptual risk-based, automated framework to support rare-case medical diagnostics and validate it by means of case studies. A preliminary validation study of the proposed framework has been carried out by interviews conducted with experts who are practicing professionals, academics, and researchers in health care. This paper summarizes the investigation and its positive results. These results motivate continuation of research towards development of the conceptual framework and of a software tool that implements the proposed model.

Automatic system testing of a decision support system for insulin dosing using Google Android.

PubMed

Spat, Stephan; Höll, Bernhard; Petritsch, Georg; Schaupp, Lukas; Beck, Peter; Pieber, Thomas R

2013-01-01

Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. A framework for high-volume, reproducible and automated system testing of the GlucoTab system was set up applying several Open Source tools for test automation and system time handling. The REACTION insulin titration protocol was investigated in a paper-based clinical trial (PBCT). In order to validate the GlucoTab system, data from this trial was used for simulation and system tests. In total, 1190 decision support action points were identified and simulated. Four data points (0.3%) resulted in a GlucoTab system error caused by a defective implementation. In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards.

Impacts of Lateral Boundary Conditions on US Ozone ...

EPA Pesticide Factsheets

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, we perform annual simulations over North America with chemical boundary conditions prepared from two global models (GEOS-CHEM and Hemispheric CMAQ). Results indicate that the impacts of different boundary conditions on ozone can be significant throughout the year. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

A new intuitionism: Meaning, memory, and development in Fuzzy-Trace Theory

PubMed Central

Reyna, Valerie F.

2014-01-01

Combining meaning, memory, and development, the perennially popular topic of intuition can be approached in a new way. Fuzzy-trace theory integrates these topics by distinguishing between meaning-based gist representations, which support fuzzy (yet advanced) intuition, and superficial verbatim representations of information, which support precise analysis. Here, I review the counterintuitive findings that led to the development of the theory and its most recent extensions to the neuroscience of risky decision making. These findings include memory interference (worse verbatim memory is associated with better reasoning); nonnumerical framing (framing effects increase when numbers are deleted from decision problems); developmental decreases in gray matter and increases in brain connectivity; developmental reversals in memory, judgment, and decision making (heuristics and biases based on gist increase from childhood to adulthood, challenging conceptions of rationality); and selective attention effects that provide critical tests comparing fuzzy-trace theory, expected utility theory, and its variants (e.g., prospect theory). Surprising implications for judgment and decision making in real life are also discussed, notably, that adaptive decision making relies mainly on gist-based intuition in law, medicine, and public health. PMID:25530822

TIUPAM: A Framework for Trustworthiness-Centric Information Sharing

NASA Astrophysics Data System (ADS)

Xu, Shouhuai; Sandhu, Ravi; Bertino, Elisa

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

Human-Computer Interaction with Medical Decisions Support Systems

NASA Technical Reports Server (NTRS)

Adolf, Jurine A.; Holden, Kritina L.

1994-01-01

Decision Support Systems (DSSs) have been available to medical diagnosticians for some time, yet their acceptance and use have not increased with advances in technology and availability of DSS tools. Medical DSSs will be necessary on future long duration space missions, because access to medical resources and personnel will be limited. Human-Computer Interaction (HCI) experts at NASA's Human Factors and Ergonomics Laboratory (HFEL) have been working toward understanding how humans use DSSs, with the goal of being able to identify and solve the problems associated with these systems. Work to date consists of identification of HCI research areas, development of a decision making model, and completion of two experiments dealing with 'anchoring'. Anchoring is a phenomenon in which the decision maker latches on to a starting point and does not make sufficient adjustments when new data are presented. HFEL personnel have replicated a well-known anchoring experiment and have investigated the effects of user level of knowledge. Future work includes further experimentation on level of knowledge, confidence in the source of information and sequential decision making.

A new intuitionism: Meaning, memory, and development in Fuzzy-Trace Theory.

PubMed

Reyna, Valerie F

2012-05-01

Combining meaning, memory, and development, the perennially popular topic of intuition can be approached in a new way. Fuzzy-trace theory integrates these topics by distinguishing between meaning-based gist representations, which support fuzzy (yet advanced) intuition, and superficial verbatim representations of information, which support precise analysis. Here, I review the counterintuitive findings that led to the development of the theory and its most recent extensions to the neuroscience of risky decision making. These findings include memory interference (worse verbatim memory is associated with better reasoning); nonnumerical framing (framing effects increase when numbers are deleted from decision problems); developmental decreases in gray matter and increases in brain connectivity; developmental reversals in memory, judgment, and decision making (heuristics and biases based on gist increase from childhood to adulthood, challenging conceptions of rationality); and selective attention effects that provide critical tests comparing fuzzy-trace theory, expected utility theory, and its variants (e.g., prospect theory). Surprising implications for judgment and decision making in real life are also discussed, notably, that adaptive decision making relies mainly on gist-based intuition in law, medicine, and public health.

The experience of foot problems and decisions to access foot care in patients with rheumatoid arthritis: a qualitative study.

PubMed

Wilson, Oonagh; Kirwan, John; Dures, Emma; Quest, Enid; Hewlett, Sarah

2017-01-01

Although foot problems are common in rheumatoid arthritis (RA), the consequences of foot problems from the patient perspective have not been fully explored. The aims of this study were to explore the experience of foot problems and decisions to access foot care services or not in patients with RA. Semi structured, one-to-one interviews with patients recruited from 2 UK rheumatology units, purposively sampled for self-reported foot problems and a range of personal/disease characteristics. Inductive thematic analysis was used, with rigour provided by multiple independent analysers. Emerging themes were discussed and agreed by all authors. Twelve patients participated: 7 female; mean age 56 years (29-72); mean disease duration 12 years (2-27), 5 had accessed foot care services. The 'Impact' of foot problems was substantial and formed the underpinning theme, comprising three organising themes: 'Foot symptoms'; 'Consequences'; and 'Cost'. Foot symptoms such as pain and numbness required self-management, and affected daily life (walking, working) leading to social and emotional costs. The global theme, 'Decision to access foot care or not', also comprised three organising themes: 'Access perceived unnecessary' (no problem, can cope); 'Access hindered by patients' perception'; and 'Access supported by patient and clinician'. Decisions to access foot care or not were complex and influenced by patient beliefs regarding possible treatments and how to access these, and hindered by patient perceptions that their feet were ignored by rheumatology clinicians. Positive experience of foot care encouraged continued utilisation but negative experiences contributed to patients' decisions to discontinue foot care services. Foot problems are important issues for patients and impact on many aspects of their physical, social and emotional lives. Patients who had accessed foot care services prioritised their foot problems as an important health care need. However, for others who would like foot care services, personal knowledge and values, and perceived barriers in clinical practice, appear to interact to inhibit foot care access. The extent which these interactions affect overall access to foot care in RA patients in general now needs to be quantified to help to inform and improve the effectiveness of the organisation and delivery of foot care.

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

A Virtual Information-Action Workspace for Command and Control

NASA Astrophysics Data System (ADS)

Lintern, Gavan; Naikar, Neelam

2002-10-01

Information overload has become a critical challenge within military Command and Control. However, the problem is not so much one of too much information but of abundant information that is poorly organized and poorly represented. In addition, the capabilities to test the effects of decisions before they are implemented and to monitor the progress of events after a decision is implemented are primitive. A virtual information-action workspace could be designed to resolve these issues. The design of such a space would require a detailed understanding of the specific information needed to support decision making in Command and Control. That information can be obtained with the use of knowledge acquisition and knowledge representation tools from the field of applied cognitive psychology. In addition, it will be necessary to integrate forms for perception and action into a virtual space that will support access to the information and that will provide means for testing and implementing decisions. This paper presents a rationale for a virtual information-action workspace and outlines an approach to its design.

Decision Support Model for Mosque Renovation and Rehabilitation (Case Study: Ten Mosques in Jakarta Barat, Indonesia)

NASA Astrophysics Data System (ADS)

Utama, D. N.; Triana, Y. S.; Iqbal, M. M.; Iksal, M.; Fikri, I.; Dharmawan, T.

2018-03-01

Mosque, for Muslim, is not only a place for daily worshipping, however as a center of culture as well. It is an important and valuable building to be well managed. For a responsible department or institution (such as Religion or Plan Department in Indonesia), to practically manage a lot of mosques is not simple task to handle. The challenge is in relation to data number and characteristic problems tackled. Specifically for renovating and rehabilitating the damaged mosques, a decision to determine the first damaged mosque priority to be renovated and rehabilitated is problematic. Through two types of optimization method, simulated-annealing and hill-climbing, a decision support model for mosque renovation and rehabilitation was systematically constructed. The method fuzzy-logic was also operated to establish the priority of eleven selected parameters. The constructed model is able to simulate an efficiency comparison between two optimization methods used and suggest the most objective decision coming from 196 generated alternatives.

Towards a web-based decision support tool for selecting appropriate statistical test in medical and biological sciences.

PubMed

Suner, Aslı; Karakülah, Gökhan; Dicle, Oğuz

2014-01-01

Statistical hypothesis testing is an essential component of biological and medical studies for making inferences and estimations from the collected data in the study; however, the misuse of statistical tests is widely common. In order to prevent possible errors in convenient statistical test selection, it is currently possible to consult available test selection algorithms developed for various purposes. However, the lack of an algorithm presenting the most common statistical tests used in biomedical research in a single flowchart causes several problems such as shifting users among the algorithms, poor decision support in test selection and lack of satisfaction of potential users. Herein, we demonstrated a unified flowchart; covers mostly used statistical tests in biomedical domain, to provide decision aid to non-statistician users while choosing the appropriate statistical test for testing their hypothesis. We also discuss some of the findings while we are integrating the flowcharts into each other to develop a single but more comprehensive decision algorithm.

Groundwater Remediation using Bayesian Information-Gap Decision Theory

NASA Astrophysics Data System (ADS)

O'Malley, D.; Vesselinov, V. V.

2016-12-01

Probabilistic analyses of groundwater remediation scenarios frequently fail because the probability of an adverse, unanticipated event occurring is often high. In general, models of flow and transport in contaminated aquifers are always simpler than reality. Further, when a probabilistic analysis is performed, probability distributions are usually chosen more for convenience than correctness. The Bayesian Information-Gap Decision Theory (BIGDT) was designed to mitigate the shortcomings of the models and probabilistic decision analyses by leveraging a non-probabilistic decision theory - information-gap decision theory. BIGDT considers possible models that have not been explicitly enumerated and does not require us to commit to a particular probability distribution for model and remediation-design parameters. Both the set of possible models and the set of possible probability distributions grow as the degree of uncertainty increases. The fundamental question that BIGDT asks is "How large can these sets be before a particular decision results in an undesirable outcome?". The decision that allows these sets to be the largest is considered to be the best option. In this way, BIGDT enables robust decision-support for groundwater remediation problems. Here we apply BIGDT to in a representative groundwater remediation scenario where different options for hydraulic containment and pump & treat are being considered. BIGDT requires many model runs and for complex models high-performance computing resources are needed. These analyses are carried out on synthetic problems, but are applicable to real-world problems such as LANL site contaminations. BIGDT is implemented in Julia (a high-level, high-performance dynamic programming language for technical computing) and is part of the MADS framework (http://mads.lanl.gov/ and https://github.com/madsjulia/Mads.jl).

[Medical expert systems and clinical needs].

PubMed

Buscher, H P

1991-10-18

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

Identifying Opportunities for Decision Support Systems in Support of Regional Resource Use Planning: An Approach Through Soft Systems Methodology.

PubMed

Zhu; Dale

2000-10-01

/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.

Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts.

PubMed

Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam; Zurek, Tomasz

2015-01-01

Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains.

Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts

PubMed Central

Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam

2015-01-01

Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains. PMID:26495435

An intelligent decision support system for work zone traffic management and planning : executive summary report.

DOT National Transportation Integrated Search

2004-01-01

Problem: Periodic resurfacing, rehabilitation, restoration, and reconstruction work is needed on the aging highway system in the state of Ohio to maintain a desired level of service for the traveling public. However, temporary work zones on highways ...

Robust parameter extraction for decision support using multimodal intensive care data

PubMed Central

Clifford, G.D.; Long, W.J.; Moody, G.B.; Szolovits, P.

2008-01-01

Digital information flow within the intensive care unit (ICU) continues to grow, with advances in technology and computational biology. Recent developments in the integration and archiving of these data have resulted in new opportunities for data analysis and clinical feedback. New problems associated with ICU databases have also arisen. ICU data are high-dimensional, often sparse, asynchronous and irregularly sampled, as well as being non-stationary, noisy and subject to frequent exogenous perturbations by clinical staff. Relationships between different physiological parameters are usually nonlinear (except within restricted ranges), and the equipment used to measure the observables is often inherently error-prone and biased. The prior probabilities associated with an individual's genetics, pre-existing conditions, lifestyle and ongoing medical treatment all affect prediction and classification accuracy. In this paper, we describe some of the key problems and associated methods that hold promise for robust parameter extraction and data fusion for use in clinical decision support in the ICU. PMID:18936019

A usability study of CPOE's medication administration functions: impact on physician-nurse cooperation.

PubMed

Beuscart-Zéphir, Marie Catherine; Pelayo, Sylvia; Degoulet, Patrice; Anceaux, Françoise; Guerlinger, Sandra; Meaux, Jean-Jacques

2004-01-01

Implementation of CPOE systems in Healthcare Institutions has proven efficient in reducing medication errors but it also induces hidden side-effects on Doctor-Nurse cooperation. We propose a usability engineering approach to this problem. An extensive activity analysis of the medication ordering and administration process was performed in several departments of 3 different hospitals. Two of these hospitals are still using paper-based orders, while the 3rd one is in the roll-out phase of medication functions of its CPOE system. We performed a usability assessment of this CPOE system. The usability assessment uncovered usability problems for the entry of medication administration time scheduling by the physician and revealed that the information can be ambiguous for the nurse. The comparison of cooperation models in both situation shows that users tend to adopt a distributed decision making paradigm in the paper-based situation, while the CPOE system supports a centralized decision making process. This analysis can support recommendation for the re-engineering of the Human-Computer Interface.

Decision Support Model for Optimal Management of Coastal Gate

NASA Astrophysics Data System (ADS)

Ditthakit, Pakorn; Chittaladakorn, Suwatana

2010-05-01

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

Use of an Online Clinical Process Support System as an Aid to Identification and Management of Developmental and Mental Health Problems.

PubMed

Howard, Barbara J; Sturner, Raymond

2017-12-01

To describe benefits and problems with screening and addressing developmental and behavioral problems in primary care and using an online clinical process support system as a solution. Screening has been found to have various implementation barriers including time costs, accuracy, workflow and knowledge of tools. In addition, training of clinicians in dealing with identified issues is lacking. Patients disclose more to and prefer computerized screening. An online clinical process support system (CHADIS) shows promise in addressing these issues. Use of a comprehensive panel of online pre-visit screens; linked decision support to provide moment-of-care training; and post-visit activities and resources for patient-specific education, monitoring and care coordination is an efficient way to make the entire process of screening and follow up care feasible in primary care. CHADIS fulfills these requirements and provides Maintenance of Certification credit to physicians as well as added income for screening efforts.

The contingency of patient preferences for involvement in health decision making.

PubMed

Ryan, John; Sysko, James

2007-01-01

Studies indicate that better patient compliance and higher patient satisfaction result when agreement exists between the physician and the patient regarding the medical problem and its treatment. This study will extend previous work by investigating (1) under what conditions patients prefer to be actively involved in their treatment decisions, (2) the underlying theoretical reasons that may account for patient decision-making preferences, and (3) what medical decision-making model can guide physicians and medical policy makers when adapting their medical decision-making styles. A total of 2,765 individuals were surveyed by the National Opinion Research Center as part of the 2002 General Social Survey (GSS). This survey included a one-time topical module on "Doctors and Patients," which incorporated questions on patient preferences concerning the physician-patient relationship. Demographic information (e.g., age, education, and sex) was analyzed against patient preferences for medical decision making. Results support patient preferences for participatory medical decision making, and this is especially true for younger, more educated, and female patients. Common prudence would suggest that the best way to determine a patient's preference for participating in medical decision making is to simply ask them. However, the very asking of this straightforward question is based on the assumption that patients do wish to be actively involved. Results of this study support such an assumption. In the absence of all other knowledge, the results of this national survey support the health care practitioner's belief that U.S. patients, in general, have a preference for being actively involved in medical decision making and that this preference is truer for younger, female, and more educated patients.

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.

Democratic input into the nuclear waste disposal problem: The influence of geographical data on decision making examined through a Web-based GIS

NASA Astrophysics Data System (ADS)

Evans, Andrew J.; Kingston, Richard; Carver, Steve

This paper elucidates the manner in which users of an online decision support system respond to spatially distributed data when assessing the solution to environmental risks, specifically, nuclear waste disposal. It presents tests for revealing whether users are responding to geographical data and whether they are influenced by their home location (Not in My Back Yard - style behavior). The tests specifically cope with problems associated with testing home-to-risk distances where both locations are constrained by the shape of the landmass available. In addition, we detail the users' wider feelings towards such a system, and reflect upon the possibilities such systems offer for participatory democracy initiatives.

Can Limiting Choice Increase Social Welfare? The Elderly and Health Insurance

PubMed Central

Hanoch, Yaniv; Rice, Thomas

2006-01-01

Herbert Simon's work on bounded rationality has had little impact on health policy discourse, despite numerous supportive findings. This is particularly surprising in regard to the elderly, a group marked by a decline in higher cognitive functions. Elders' cognitive capacity to make decisions will be challenged even further with the introduction of the new Medicare prescription drug benefit program, mainly because of the many options available. At the same time, a growing body of evidence points to the perils of having too many choices. By combining research from decision science, economics, and psychology, we highlight the potential problems with the expanding health insurance choices facing the elderly and conclude with some policy suggestions to alleviate the problem. PMID:16529568

Life insurance risk assessment using a fuzzy logic expert system

NASA Technical Reports Server (NTRS)

Carreno, Luis A.; Steel, Roy A.

1992-01-01

In this paper, we present a knowledge based system that combines fuzzy processing with rule-based processing to form an improved decision aid for evaluating risk for life insurance. This application illustrates the use of FuzzyCLIPS to build a knowledge based decision support system possessing fuzzy components to improve user interactions and KBS performance. The results employing FuzzyCLIPS are compared with the results obtained from the solution of the problem using traditional numerical equations. The design of the fuzzy solution consists of a CLIPS rule-based system for some factors combined with fuzzy logic rules for others. This paper describes the problem, proposes a solution, presents the results, and provides a sample output of the software product.

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

Sanfilippo, Antonio P.; Riensche, Roderick M.; Haack, Jereme N.

“Gamification”, the application of gameplay to real-world problems, enables the development of human computation systems that support decision-making through the integration of social and machine intelligence. One of gamification’s major benefits includes the creation of a problem solving environment where the influence of cognitive and cultural biases on human judgment can be curtailed through collaborative and competitive reasoning. By reducing biases on human judgment, gamification allows human computation systems to exploit human creativity relatively unhindered by human error. Operationally, gamification uses simulation to harvest human behavioral data that provide valuable insights for the solution of real-world problems.

Mental Health and Head Start: Teaching Adaptive Skills.

ERIC Educational Resources Information Center

Forness, Steven R.; Serna, Loretta A.; Kavale, Kenneth A.; Nielsen, Elizabeth

1998-01-01

Describes the use of a self-determination curriculum for mental-health intervention and primary prevention for Head Start children. The curriculum addresses critical adaptive-skills domains, including social skills, self-evaluation, self-direction, networking or friendship, collaboration or support seeking, problem solving and decision making, and…

Counseling the Young Adult Lesbian.

ERIC Educational Resources Information Center

Miller, Rhoda

1980-01-01

Focuses on problems faced by young adult lesbians. Suggests counselors should: (1) encourage the counselee to "dump"; (2) guide her in a decision on coming out; (3) explain the legal rights and restrictions; (4) provide ongoing support for those who socialize openly; and (5) publicly promote gay rights. (Author)

A miniature ultrasonic actuator-control system for plant stem diameter micro-variation measurements

USDA-ARS?s Scientific Manuscript database

Measurements of micro-variations in plant stem diameter are potentially useful to optimize irrigation decision support systems that are based on plant physiological responses. However, for this technology to be suitable for field applications, problems associated with stem softness and micro variati...

Student Achievement Effects of Technology-Supported Remediation of Understanding of Fractions

ERIC Educational Resources Information Center

Ross, John A.; Bruce, Catherine D.

2009-01-01

Students have difficulty learning fractions, and problems in understanding fractions persist into adulthood, with moderate to severe consequences for everyday and occupational decision-making. Remediation of student misconceptions is hampered by deficiencies in teachers' knowledge of the discipline and pedagogical content knowledge. We theorized…

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Using Decision Structures for Policy Analysis in Software Product-line Evolution - A Case Study

NASA Astrophysics Data System (ADS)

Sarang, Nita; Sanglikar, Mukund A.

Project management decisions are the primary basis for project success (or failure). Mostly, such decisions are based on an intuitive understanding of the underlying software engineering and management process and have a likelihood of being misjudged. Our problem domain is product-line evolution. We model the dynamics of the process by incorporating feedback loops appropriate to two decision structures: staffing policy, and the forces of growth associated with long-term software evolution. The model is executable and supports project managers to assess the long-term effects of possible actions. Our work also corroborates results from earlier studies of E-type systems, in particular the FEAST project and the rules for software evolution, planning and management.

Constructor theory of probability

PubMed Central

2016-01-01

Unitary quantum theory, having no Born Rule, is non-probabilistic. Hence the notorious problem of reconciling it with the unpredictability and appearance of stochasticity in quantum measurements. Generalizing and improving upon the so-called ‘decision-theoretic approach’, I shall recast that problem in the recently proposed constructor theory of information—where quantum theory is represented as one of a class of superinformation theories, which are local, non-probabilistic theories conforming to certain constructor-theoretic conditions. I prove that the unpredictability of measurement outcomes (to which constructor theory gives an exact meaning) necessarily arises in superinformation theories. Then I explain how the appearance of stochasticity in (finitely many) repeated measurements can arise under superinformation theories. And I establish sufficient conditions for a superinformation theory to inform decisions (made under it) as if it were probabilistic, via a Deutsch–Wallace-type argument—thus defining a class of decision-supporting superinformation theories. This broadens the domain of applicability of that argument to cover constructor-theory compliant theories. In addition, in this version some of the argument's assumptions, previously construed as merely decision-theoretic, follow from physical properties expressed by constructor-theoretic principles. PMID:27616914

A modelling tool for policy analysis to support the design of efficient and effective policy responses for complex public health problems.

PubMed

Atkinson, Jo-An; Page, Andrew; Wells, Robert; Milat, Andrew; Wilson, Andrew

2015-03-03

In the design of public health policy, a broader understanding of risk factors for disease across the life course, and an increasing awareness of the social determinants of health, has led to the development of more comprehensive, cross-sectoral strategies to tackle complex problems. However, comprehensive strategies may not represent the most efficient or effective approach to reducing disease burden at the population level. Rather, they may act to spread finite resources less intensively over a greater number of programs and initiatives, diluting the potential impact of the investment. While analytic tools are available that use research evidence to help identify and prioritise disease risk factors for public health action, they are inadequate to support more targeted and effective policy responses for complex public health problems. This paper discusses the limitations of analytic tools that are commonly used to support evidence-informed policy decisions for complex problems. It proposes an alternative policy analysis tool which can integrate diverse evidence sources and provide a platform for virtual testing of policy alternatives in order to design solutions that are efficient, effective, and equitable. The case of suicide prevention in Australia is presented to demonstrate the limitations of current tools to adequately inform prevention policy and discusses the utility of the new policy analysis tool. In contrast to popular belief, a systems approach takes a step beyond comprehensive thinking and seeks to identify where best to target public health action and resources for optimal impact. It is concerned primarily with what can be reasonably left out of strategies for prevention and can be used to explore where disinvestment may occur without adversely affecting population health (or equity). Simulation modelling used for policy analysis offers promise in being able to better operationalise research evidence to support decision making for complex problems, improve targeting of public health policy, and offers a foundation for strengthening relationships between policy makers, stakeholders, and researchers.

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.

Development and application of air quality models at the US ...

EPA Pesticide Factsheets

Overview of the development and application of air quality models at the U.S. EPA, particularly focused on the development and application of the Community Multiscale Air Quality (CMAQ) model developed within the Computation Exposure Division (CED) of the National Exposure Research Laboratory (NERL). This presentation will provide a simple overview of air quality model development and application geared toward a non-technical student audience. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Decision making: rational or hedonic?

PubMed Central

Cabanac, Michel; Bonniot-Cabanac, Marie-Claude

2007-01-01

Three experiments studied the hedonicity of decision making. Participants rated their pleasure/displeasure while reading item-sentences describing political and social problems followed by different decisions (Questionnaire 1). Questionnaire 2 was multiple-choice, grouping the items from Questionnaire 1. In Experiment 1, participants answered Questionnaire 2 rapidly or slowly. Both groups selected what they had rated as pleasant, but the 'leisurely' group maximized pleasure less. In Experiment 2, participants selected the most rational responses. The selected behaviors were pleasant but less than spontaneous behaviors. In Experiment 3, Questionnaire 2 was presented once with items grouped by theme, and once with items shuffled. Participants maximized the pleasure of their decisions, but the items selected on Questionnaires 2 were different when presented in different order. All groups maximized pleasure equally in their decisions. These results support that decisions are made predominantly in the hedonic dimension of consciousness. PMID:17848195

Shared Decision-Making and Patient Empowerment in Preventive Cardiology.

PubMed

Kambhampati, Swetha; Ashvetiya, Tamara; Stone, Neil J; Blumenthal, Roger S; Martin, Seth S

2016-05-01

Shared decision-making, central to evidence-based medicine and good patient care, begins and ends with the patient. It is the process by which a clinician and a patient jointly make a health decision after discussing options, potential benefits and harms, and considering the patient's values and preferences. Patient empowerment is crucial to shared decision-making and occurs when a patient accepts responsibility for his or her health. They can then learn to solve their own problems with information and support from professionals. Patient empowerment begins with the provider acknowledging that patients are ultimately in control of their care and aims to increase a patient's capacity to think critically and make autonomous, informed decisions about their health. This article explores the various components of shared decision-making in scenarios such as hypertension and hyperlipidemia, heart failure, and diabetes. It explores barriers and the potential for improving medication adherence, disease awareness, and self-management of chronic disease.

Producing More Actionable Science Isn't the Problem; It's Providing Decision-Makers with Access to Right Actionable Knowledge

NASA Astrophysics Data System (ADS)

Trexler, M.

2017-12-01

Policy-makers today have almost infinite climate-relevant scientific and other information available to them. The problem for climate change decision-making isn't missing science or inadequate knowledge of climate risks; the problem is that the "right" climate change actionable knowledge isn't getting to the right decision-maker, or is getting there too early or too late to effectively influence her decision-making. Actionable knowledge is not one-size-fit-all, and for a given decision-maker might involve scientific, economic, or risk-based information. Simply producing more and more information as we are today is not the solution, and actually makes it harder for individual decision-makers to access "their" actionable knowledge. The Climatographers began building the Climate Web five years ago to test the hypothesis that a knowledge management system could help navigate the gap between infinite information and individual actionable knowledge. Today the Climate Web's more than 1,500 index terms allow instant access to almost any climate change topic. It is a curated public-access knowledgebase of more than 1,000 books, 2,000 videos, 15,000 reports and articles, 25,000 news stories, and 3,000 websites. But it is also much more, linking together tens of thousands of individually extracted ideas and graphics, and providing Deep Dives into more than 100 key topics from changing probability distributions of extreme events to climate communications best practices to cognitive dissonance in climate change decision-making. The public-access Climate Web is uniquely able to support cross-silo learning, collaboration, and actionable knowledge dissemination. The presentation will use the Climate Web to demonstrate why knowledge management should be seen as a critical component of science and policy-making collaborations.

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

NASA Astrophysics Data System (ADS)

Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

Problem formulation, metrics, open government, and on-line collaboration

NASA Astrophysics Data System (ADS)

Ziegler, C. R.; Schofield, K.; Young, S.; Shaw, D.

2010-12-01

Problem formulation leading to effective environmental management, including synthesis and application of science by government agencies, may benefit from collaborative on-line environments. This is illustrated by two interconnected projects: 1) literature-based evidence tools that support causal assessment and problem formulation, and 2) development of output, outcome, and sustainability metrics for tracking environmental conditions. Specifically, peer-production mechanisms allow for global contribution to science-based causal evidence databases, and subsequent crowd-sourced development of causal networks supported by that evidence. In turn, science-based causal networks may inform problem formulation and selection of metrics or indicators to track environmental condition (or problem status). Selecting and developing metrics in a collaborative on-line environment may improve stakeholder buy-in, the explicit relevance of metrics to planning, and the ability to approach problem apportionment or accountability, and to define success or sustainability. Challenges include contribution governance, data-sharing incentives, linking on-line interfaces to data service providers, and the intersection of environmental science and social science. Degree of framework access and confidentiality may vary by group and/or individual, but may ultimately be geared at demonstrating connections between science and decision making and supporting a culture of open government, by fostering transparency, public engagement, and collaboration.

Comparison AHP and SAW to promotion of head major department SMK Muhammadiyah 04 Medan

NASA Astrophysics Data System (ADS)

Saputra, M.; Sitompul, O. S.; Sihombing, P.

2018-04-01

Decision Support System (DSS) is a system that can help a person to make informed decisions about various types of choices that are performed accurately and in accordance with the desired goals. Many problems can be solved by using decision support systems. In this journal the decision support system is used to assist the Chief of Muhammadiyah Medan branch in the selection of the department chief. The criteria used for the election of department chiefs are: Loyalty, Job Performance, Responsibility, Obedience, Honesty, Cooperation, Education, and Leadership. The selection promotion process consists of Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The data were obtained through teacher assessment questionnaires by principals and colleagues. The results of this study used a comparison with two decision methods namely SAW method and AHP method so that the decision maker (principal) is more appropriate in the determination of candidates who will be elected head of department at school. The final result of this research is the first rank obtained by muhammad musa with weight value on AHP method (0.274) and weight value on SAW method (0.993), alvin syahrin with weight value on AHP method (0.241) and weight value on SAW method (0.883), noviyanti with weight value on AHP method (0.193) and weight value on SAW method (0.707). So the conclusion on the research that is by using SAW method the value of weight produced more accurate.

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

Analysis And Assistant Planning System Ofregional Agricultural Economic Inform

NASA Astrophysics Data System (ADS)

Han, Jie; Zhang, Junfeng

For the common problems existed in regional development and planning, we try to design a decision support system for assisting regional agricultural development and alignment as a decision-making tool for local government and decision maker. The analysis methods of forecast, comparative advantage, liner programming and statistical analysis are adopted. According to comparative advantage theory, the regional advantage can be determined by calculating and comparing yield advantage index (YAI), Scale advantage index (SAI), Complicated advantage index (CAI). Combining with GIS, agricultural data are presented as a form of graph such as area, bar and pie to uncover the principle and trend for decision-making which can't be found in data table. This system provides assistant decisions for agricultural structure adjustment, agro-forestry development and planning, and can be integrated to information technologies such as RS, AI and so on.

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...

Building a model-based decision support system for solving vehicle routing and driver scheduling problems under hours of service regulations.

DOT National Transportation Integrated Search

2011-08-27

"In principle, hours-of-service (HOS) regulations are intended to help truck drivers ensure get adequate rest and perform safe operations. The new HOS regulations, however, may lead to substantial cost increases for regional common carriers which hav...

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...

The Public School: Assaults on a Great Idea

ERIC Educational Resources Information Center

Butts, R. Freeman

1973-01-01

This article is a statement of support for free American public education. The development of the public education system is described. Note is taken of the struggles for control, financing problems, court decisions which provide for free access, and the divisive cultural conflicts which have spurred movements toward alternative systems. (SM)

A Low-Subsidy Problem in Public Higher Education

ERIC Educational Resources Information Center

Fethke, Gary

2011-01-01

With an exogenous public subsidy and a break-even restriction on university net revenue, tuition discrimination supports a quasi-efficient departure from marginal-cost pricing. In contrast, when the legislature and university interact in their subsidy and tuition decisions, the public subsidy becomes endogenous. With an endogenous public subsidy,…

A Decision Support Tool to Evaluate Sources and Sinks of Nitrogen within a Watershed Framework

EPA Science Inventory

Human transformation of the nitrogen (N) cycle is causing a number of environmental and human health problems. Federal, state and local authorities focusing on management of N loadings face both technical and non-technical challenges. One technical issue is that we need a bette...

Developing Materials for Deliberative Forums

ERIC Educational Resources Information Center

Rourke, Brad

2014-01-01

When citizens deliberate together about important issues, they can reach decisions and take action together on problems that confront them. Deliberation does not require a certain kind of guide, or framework, or language, or facilitator, but, because it can be difficult to face such choices, supporting materials can make it easier. In Developing…

Fixing the Net Tuition Revenue Dilemma: The Dickinson College Story

ERIC Educational Resources Information Center

Massa, Robert J.; Parker, Annette S.

2007-01-01

This chapter describes how Dickinson College, guided by a strategic plan, addressed its net tuition revenue problem through effective decision support, marketing and branding approaches, and pricing and financial aid strategies. The college's strategic plan guides allocation of resources toward fulfilling the college's purpose of providing an…

The Costs of Reneging: Reputation and Alliance Formation

ERIC Educational Resources Information Center

Gibler, Douglas M.

2008-01-01

Reputations are supposed to matter. Decision makers consistently refer to reputations for resolve, and international relations theories confirm the value of being able to credibly signal intentions during times of crisis. However, empirical support for the effects of reputation has been lacking. Problems of strategic selection have hampered…

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.

Can Religious Beliefs be a Protective Factor for Suicidal Behavior? A Decision Tree Analysis in a Mid-Sized City in Iran, 2013.

PubMed

Baneshi, Mohammad Reza; Haghdoost, Ali Akbar; Zolala, Farzaneh; Nakhaee, Nouzar; Jalali, Maryam; Tabrizi, Reza; Akbari, Maryam

2017-04-01

This study aimed to assess using tree-based models the impact of different dimensions of religion and other risk factors on suicide attempts in the Islamic Republic of Iran. Three hundred patients who attempted suicide and 300 age- and sex-matched patient attendants with other types of disease who referred to Kerman Afzalipour Hospital were recruited for this study following a convenience sampling. Religiosity was assessed by the Duke University Religion Index. A tree-based model was constructed using the Gini Index as the homogeneity criterion. A complementary discrimination analysis was also applied. Variables contributing to the construction of the tree were stressful life events, mental disorder, family support, and religious belief. Strong religious belief was a protective factor for those with a low number of stressful life events and those with a high mental disorder score; 72 % of those who formed these two groups had not attempted suicide. Moreover, 63 % of those with a high number of stressful life events, strong family support, strong problem-solving skills, and a low mental disorder score were less likely to attempt suicide. The significance of four other variables, GHQ, problem-coping skills, friend support, and neuroticism, was revealed in the discrimination analysis. Religious beliefs seem to be an independent factor that can predict risk for suicidal behavior. Based on the decision tree, religious beliefs among people with a high number of stressful life events might not be a dissuading factor. Such subjects need more family support and problem-solving skills.

Artificial intelligence based decision support for trumpeter swan management

USGS Publications Warehouse

Sojda, Richard S.

2002-01-01

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.

A water management decision support system contributing to sustainability

NASA Astrophysics Data System (ADS)

Horváth, Klaudia; van Esch, Bart; Baayen, Jorn; Pothof, Ivo; Talsma, Jan; van Heeringen, Klaas-Jan

2017-04-01

Deltares and Eindhoven University of Technology are developing a new decision support system (DSS) for regional water authorities. In order to maintain water levels in the Dutch polder system, water should be drained and pumped out from the polders to the sea. The time and amount of pumping depends on the current sea level, the water level in the polder, the weather forecast and the electricity price forecast and possibly local renewable power production. This is a multivariable optimisation problem, where the goal is to keep the water level in the polder within certain bounds. By optimizing the operation of the pumps the energy usage and costs can be reduced, hence the operation of the regional water authorities can be more sustainable, while also anticipating on increasing share of renewables in the energy mix in a cost-effective way. The decision support system, based on Delft-FEWS as operational data-integration platform, is running an optimization model built in RTC-Tools 2, which is performing real-time optimization in order to calculate the pumping strategy. It is taking into account the present and future circumstances. As being the core of the real time decision support system, RTC-Tools 2 fulfils the key requirements to a DSS: it is fast, robust and always finds the optimal solution. These properties are associated with convex optimization. In such problems the global optimum can always be found. The challenge in the development is to maintain the convex formulation of all the non-linear components in the system, i.e. open channels, hydraulic structures, and pumps. The system is introduced through 4 pilot projects, one of which is a pilot of the Dutch Water Authority Rivierenland. This is a typical Dutch polder system: several polders are drained to the main water system, the Linge. The water from the Linge can be released to the main rivers that are subject to tidal fluctuations. In case of low tide, water can be released via the gates. In case of high tide, water should be pumped. The goal of the pilot is to make the operation of the regional water authority more sustainable and cost-efficient. Sustainability can be achieved by minimizing the CO2 production trough minimizing the energy used for pumping. This work is showing the functionalities of the new decision support system, using RTC-Tools 2, through the example of a pilot project.

Using Concept Mapping to Define Problems and Identify Key Kernels during the Development of a Decision Support System

DTIC Science & Technology

1987-06-01

The problem chosen was an intriguing look at the question; ’When should a theater level commander request authorization for the use of tactical nuclear ...years experience in strategic nuclear missile systems, established ourselves as the best experts available. The literature search revealed the existence...CONTROL DSS Introduction This paper contains the storyboards of the DSS for the command and control of theater nuclear weapons. The storyboards are

EmoBurnout: An Approach for Supporting Burnout Syndrome Diagnosis.

PubMed

Martinez, Esteban; Mera, Giovanni; González, Carolina; López, Diego M; Blobel, Bernd

2015-01-01

Burnout is scientifically a work related syndrome which consists of three dimensions: emotional exhaustion, depersonalization and reduced professional efficacy. Different instruments for the diagnosis of burnout exist, accompanied by many associated problems, however. This paper describes a proposal aiming at supporting the diagnosis of burnout using measures complementary to the Maslach Burnout Inventory (MBI). It specifically focuses on emotions detection to provide useful information that contributes to the decision making process about the syndrome.

Human perspectives and conservation of grizzly bears in Banff National Park, Canada.

PubMed

Chamberlain, Emily C; Rutherford, Murray B; Gibeau, Michael L

2012-06-01

Some conservation initiatives provoke intense conflict among stakeholders. The need for action, the nature of the conservation measures, and the effects of these measures on human interests may be disputed. Tools are needed to depolarize such situations, foster understanding of the perspectives of people involved, and find common ground. We used Q methodology to explore stakeholders' perspectives on conservation and management of grizzly bears (Ursus arctos horribilis) in Banff National Park and the Bow River watershed of Alberta, Canada. Twenty-nine stakeholders participated in the study, including local residents, scientists, agency employees, and representatives of nongovernmental conservation organizations and other interest groups. Participants rank ordered a set of statements to express their opinions on the problems of grizzly bear management (I-IV) and a second set of statements on possible solutions to the problems (A-C). Factor analysis revealed that participants held 4 distinct views of the problems: individuals associated with factor I emphasized deficiencies in goals and plans; those associated with factor II believed that problems had been exaggerated; those associated with factor III blamed institutional flaws such as disjointed management and inadequate resources; and individuals associated with factor IV blamed politicized decision making. There were 3 distinct views about the best solutions to the problems: individuals associated with factor A called for increased conservation efforts; those associated with factor B wanted reforms in decision-making processes; and individuals associated with factor C supported active landscape management. We connected people's definitions of the problem with their preferred solutions to form 5 overall problem narratives espoused by groups in the study: the problem is deficient goals and plans, the solution is to prioritize conservation efforts (planning-oriented conservation advocates); the problem is flawed institutions, the solution is to prioritize conservation efforts (institutionally-oriented conservation advocates); the problems have been exaggerated, but there is a need to improve decision-making processes (optimistic decision-process reformers); the problems have been exaggerated, but managers should more actively manage the landscape (optimistic landscape managers); and the problem is politicized decision making, solutions vary (democratizers). Although these 5 groups differed on many issues, they agreed that the population of grizzly bears is vulnerable to extirpation, human use of the area should be designed around ecological constraints, and more inclusive decision-making processes are needed. We used our results to inform a series of workshops in which stakeholders developed and agreed on new management strategies that were implemented by Parks Canada. Our research demonstrates the usefulness of Q method to illuminate people's perspectives and identify common ground in settings where conservation is contested. ©2012 Society for Conservation Biology.

The Voice of the Patient Methodology: A Novel Mixed-Methods Approach to Identifying Treatment Goals for Men with Prostate Cancer.

PubMed

Saigal, Christopher S; Lambrechts, Sylvia I; Seenu Srinivasan, V; Dahan, Ely

2017-06-01

Many guidelines advocate the use of shared decision making for men with newly diagnosed prostate cancer. Decision aids can facilitate the process of shared decision making. Implicit in this approach is the idea that physicians understand which elements of treatment matter to patients. Little formal work exists to guide physicians or developers of decision aids in identifying these attributes. We use a mixed-methods technique adapted from marketing science, the 'Voice of the Patient', to describe and identify treatment elements of value for men with localized prostate cancer. We conducted semi-structured interviews with 30 men treated for prostate cancer in the urology clinic of the West Los Angeles Veteran Affairs Medical Center. We used a qualitative analysis to generate themes in patient narratives, and a quantitative approach, agglomerative hierarchical clustering, to identify attributes of treatment that were most relevant to patients making decisions about prostate cancer. We identified five 'traditional' prostate cancer treatment attributes: sexual dysfunction, bowel problems, urinary problems, lifespan, and others' opinions. We further identified two novel treatment attributes: a treatment's ability to validate a sense of proactivity and the need for an incision (separate from risks of surgery). Application of a successful marketing technique, the 'Voice of the Customer', in a clinical setting elicits non-obvious attributes that highlight unique patient decision-making concerns. Use of this method in the development of decision aids may result in more effective decision support.

Spatially explicit decision support for selecting translocation areas for Mojave desert tortoises

USGS Publications Warehouse

Heaton, Jill S.; Nussear, Kenneth E.; Esque, Todd C.; Inman, Richard D.; Davenport, Frank; Leuteritz, Thomas E.; Medica, Philip A.; Strout, Nathan W.; Burgess, Paul A.; Benvenuti, Lisa

2008-01-01

Spatially explicit decision support systems are assuming an increasing role in natural resource and conservation management. In order for these systems to be successful, however, they must address real-world management problems with input from both the scientific and management communities. The National Training Center at Fort Irwin, California, has expanded its training area, encroaching U.S. Fish and Wildlife Service critical habitat set aside for the Mojave desert tortoise (Gopherus agassizii), a federally threatened species. Of all the mitigation measures proposed to offset expansion, the most challenging to implement was the selection of areas most feasible for tortoise translocation. We developed an objective, open, scientifically defensible spatially explicit decision support system to evaluate translocation potential within the Western Mojave Recovery Unit for tortoise populations under imminent threat from military expansion. Using up to a total of 10 biological, anthropogenic, and/or logistical criteria, seven alternative translocation scenarios were developed. The final translocation model was a consensus model between the seven scenarios. Within the final model, six potential translocation areas were identified.

Decision tools in health care: focus on the problem, not the solution.

PubMed

Liu, Joseph; Wyatt, Jeremy C; Altman, Douglas G

2006-01-20

Systematic reviews or randomised-controlled trials usually help to establish the effectiveness of drugs and other health technologies, but are rarely sufficient by themselves to ensure actual clinical use of the technology. The process from innovation to routine clinical use is complex. Numerous computerised decision support systems (DSS) have been developed, but many fail to be taken up into actual use. Some developers construct technologically advanced systems with little relevance to the real world. Others did not determine whether a clinical need exists. With NHS investing 5 billion pounds sterling in computer systems, also occurring in other countries, there is an urgent need to shift from a technology-driven approach to one that identifies and employs the most cost-effective method to manage knowledge, regardless of the technology. The generic term, 'decision tool' (DT), is therefore suggested to demonstrate that these aids, which seem different technically, are conceptually the same from a clinical viewpoint. Many computerised DSSs failed for various reasons, for example, they were not based on best available knowledge; there was insufficient emphasis on their need for high quality clinical data; their development was technology-led; or evaluation methods were misapplied. We argue that DSSs and other computer-based, paper-based and even mechanical decision aids are members of a wider family of decision tools. A DT is an active knowledge resource that uses patient data to generate case specific advice, which supports decision making about individual patients by health professionals, the patients themselves or others concerned about them. The identification of DTs as a consistent and important category of health technology should encourage the sharing of lessons between DT developers and users and reduce the frequency of decision tool projects focusing only on technology. The focus of evaluation should become more clinical, with the impact of computer-based DTs being evaluated against other computer, paper- or mechanical tools, to identify the most cost effective tool for each clinical problem. We suggested the generic term 'decision tool' to demonstrate that decision-making aids, such as computerised DSSs, paper algorithms, and reminders are conceptually the same, so the methods to evaluate them should be the same.

Improving Multi-Objective Management of Water Quality Tipping Points: Revisiting the Classical Shallow Lake Problem

NASA Astrophysics Data System (ADS)

Quinn, J. D.; Reed, P. M.; Keller, K.

2015-12-01

Recent multi-objective extensions of the classical shallow lake problem are useful for exploring the conceptual and computational challenges that emerge when managing irreversible water quality tipping points. Building on this work, we explore a four objective version of the lake problem where a hypothetical town derives economic benefits from polluting a nearby lake, but at the risk of irreversibly tipping the lake into a permanently polluted state. The trophic state of the lake exhibits non-linear threshold dynamics; below some critical phosphorus (P) threshold it is healthy and oligotrophic, but above this threshold it is irreversibly eutrophic. The town must decide how much P to discharge each year, a decision complicated by uncertainty in the natural P inflow to the lake. The shallow lake problem provides a conceptually rich set of dynamics, low computational demands, and a high level of mathematical difficulty. These properties maximize its value for benchmarking the relative merits and limitations of emerging decision support frameworks, such as Direct Policy Search (DPS). Here, we explore the use of DPS as a formal means of developing robust environmental pollution control rules that effectively account for deeply uncertain system states and conflicting objectives. The DPS reformulation of the shallow lake problem shows promise in formalizing pollution control triggers and signposts, while dramatically reducing the computational complexity of the multi-objective pollution control problem. More broadly, the insights from the DPS variant of the shallow lake problem formulated in this study bridge emerging work related to socio-ecological systems management, tipping points, robust decision making, and robust control.

Developing quality indicators and auditing protocols from formal guideline models: knowledge representation and transformations.

PubMed

Advani, Aneel; Goldstein, Mary; Shahar, Yuval; Musen, Mark A

2003-01-01

Automated quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe a model representation and algorithm for deriving structured quality indicators and auditing protocols from formalized specifications of guidelines used in decision support systems. We apply the model and algorithm to the assessment of physician concordance with a guideline knowledge model for hypertension used in a decision-support system. The properties of our solution include the ability to derive automatically context-specific and case-mix-adjusted quality indicators that can model global or local levels of detail about the guideline parameterized by defining the reliability of each indicator or element of the guideline.

Applications of decision analysis and related techniques to industrial engineering problems at KSC

NASA Technical Reports Server (NTRS)

Evans, Gerald W.

1995-01-01

This report provides: (1) a discussion of the origination of decision analysis problems (well-structured problems) from ill-structured problems; (2) a review of the various methodologies and software packages for decision analysis and related problem areas; (3) a discussion of how the characteristics of a decision analysis problem affect the choice of modeling methodologies, thus providing a guide as to when to choose a particular methodology; and (4) examples of applications of decision analysis to particular problems encountered by the IE Group at KSC. With respect to the specific applications at KSC, particular emphasis is placed on the use of the Demos software package (Lumina Decision Systems, 1993).

What can paper-based clinical information systems tell us about the design of computerized clinical information systems (CIS) in the ICU?

PubMed

Miller, A; Pilcher, D; Mercaldo, N; Leong, T; Scheinkestel, C; Schildcrout, J

2010-08-01

Screen designs in computerized clinical information systems (CIS) have been modeled on their paper predecessors. However, limited understanding about how paper forms support clinical work means that we risk repeating old mistakes and creating new opportunities for error and inefficiency as illustrated by problems associated with computerized provider order entry systems. This study was designed to elucidate principles underlying a successful ICU paper-based CIS. The research was guided by two exploratory hypotheses: (1) paper-based artefacts (charts, notes, equipment, order forms) are used differently by nurses, doctors and other healthcare professionals in different (formal and informal) conversation contexts and (2) different artefacts support different decision processes that are distributed across role-based conversations. All conversations undertaken at the bedsides of five patients were recorded with any supporting artefacts for five days per patient. Data was coded according to conversational role-holders, clinical decision process, conversational context and artefacts. 2133 data points were analyzed using Poisson logistic regression analyses. Results show significant interactions between artefacts used during different professional conversations in different contexts (chi(2)((df=16))=55.8, p<0.0001). The interaction between artefacts used during different professional conversations for different clinical decision processes was not statistically significant although all two-way interactions were statistically significant. Paper-based CIS have evolved to support complex interdisciplinary decision processes. The translation of two design principles - support interdisciplinary perspectives and integrate decision processes - from paper to computerized CIS may minimize the risks associated with computerization. 2010 Australian College of Critical Care Nurses Ltd. Published by Elsevier Ltd. All rights reserved.

Ideology and Palliative Care: Moral Hazards at the Bedside.

PubMed

Rhodes, Rosamond; Strain, James J

2018-01-01

Palliative care has had a long-standing commitment to teaching medical students and other medical professionals about pain management, communication, supporting patients in their decisions, and providing compassionate end-of-life care. Palliative care programs also have a critical role in helping patients understand medical conditions, and in supporting them in dealing with pain, fear of dying, and the experiences of the terminal phase of their lives. We applaud their efforts to provide that critical training and fully support their continued important work in meeting the needs of patients and families. Although we appreciate the contributions of palliative care services, we have noted a problem involving some palliative care professionals' attitudes, methods of decisionmaking, and use of language. In this article we explain these problems by discussing two cases that we encountered.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Rhetorical Use of Inscriptions in Students' Written Arguments About Socioscientific Issues

NASA Astrophysics Data System (ADS)

Xiao, Sihan

2018-05-01

Educators expect that students be able to make informed decisions about science-related problems in their everyday lives. Engaging science in such problems often entails evaluating available evidence for given arguments. This study explores how students use inscriptions as evidence to argue about socioscientific issues. Fifth- and sixth-grade students (N = 102) in two intact classrooms completed written argument tasks in which they were asked to cite given inscriptions to support their decisions about energy use or genetically modified organisms. Qualitative content analyses of these written arguments, which focused on the coordination between inscriptions and claims, show three patterns of rhetorical use of inscriptions: seeing is believing, believing is seeing, and asserting is inferring. What counts as evidence was not the inscriptions per se, but the rhetorical functions they performed in particular arguments. These findings suggest that justifying socioscientific decisions is functionally different from explaining scientific phenomena. Linking these two activities in school may help students more productively engage with science in their everyday lives.

Multicriteria Decision-Making Approach with Hesitant Interval-Valued Intuitionistic Fuzzy Sets

PubMed Central

Peng, Juan-juan; Wang, Jian-qiang; Wang, Jing; Chen, Xiao-hong

2014-01-01

The definition of hesitant interval-valued intuitionistic fuzzy sets (HIVIFSs) is developed based on interval-valued intuitionistic fuzzy sets (IVIFSs) and hesitant fuzzy sets (HFSs). Then, some operations on HIVIFSs are introduced in detail, and their properties are further discussed. In addition, some hesitant interval-valued intuitionistic fuzzy number aggregation operators based on t-conorms and t-norms are proposed, which can be used to aggregate decision-makers' information in multicriteria decision-making (MCDM) problems. Some valuable proposals of these operators are studied. In particular, based on algebraic and Einstein t-conorms and t-norms, some hesitant interval-valued intuitionistic fuzzy algebraic aggregation operators and Einstein aggregation operators can be obtained, respectively. Furthermore, an approach of MCDM problems based on the proposed aggregation operators is given using hesitant interval-valued intuitionistic fuzzy information. Finally, an illustrative example is provided to demonstrate the applicability and effectiveness of the developed approach, and the study is supported by a sensitivity analysis and a comparison analysis. PMID:24983009

Use of multicriteria analysis (MCA) for sustainable hydropower planning and management.

PubMed

Vassoney, Erica; Mammoliti Mochet, Andrea; Comoglio, Claudio

2017-07-01

Multicriteria analysis (MCA) is a decision-making tool applied to a wide range of environmental management problems, including renewable energy planning and management. An interesting field of application of MCA is the evaluation and analysis of the conflicting aspects of hydropower (HP) exploitation, affecting the three pillars of sustainability and involving several different stakeholders. The present study was aimed at reviewing the state of the art of MCA applications to sustainable hydropower production and related decision-making problems, based on a detailed analysis of the scientific papers published over the last 15 years on this topic. The papers were analysed and compared, focusing on the specific features of the MCA methods applied in the described case studies, highlighting the general aspects of the MCA application (purpose, spatial scale, software used, stakeholders, etc.) and the specific operational/technical features of the selected MCA technique (methodology, criteria, evaluation, approach, sensitivity, etc.). Some specific limitations of the analysed case studies were identified and a set of "quality indexes" of an exhaustive MCA application were suggested as potential improvements for more effectively support decision-making processes in sustainable HP planning and management problems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Option generation in decision making: ideation beyond memory retrieval

PubMed Central

Del Missier, Fabio; Visentini, Mimì; Mäntylä, Timo

2015-01-01

According to prescriptive decision theories, the generation of options for choice is a central aspect of decision making. A too narrow representation of the problem may indeed limit the opportunity to evaluate promising options. However, despite the theoretical and applied significance of this topic, the cognitive processes underlying option generation are still unclear. In particular, while a cued recall account of option generation emphasizes the role of memory and executive control, other theoretical proposals stress the importance of ideation processes based on various search and thinking processes. Unfortunately, relevant behavioral evidence on the cognitive processes underlying option generation is scattered and inconclusive. In order to reach a better understanding, we carried out an individual-differences study employing a wide array of cognitive predictors, including measures of episodic memory, semantic memory, cognitive control, and ideation fluency. The criterion tasks consisted of three different poorly-structured decision-making scenarios, and the participants were asked to generate options to solve these problems. The main criterion variable of the study was the number of valid options generated, but also the diversity and the quality of generated options were examined. The results showed that option generation fluency and diversity in the context of ill-structured decision making are supported by ideation ability even after taking into account the effects of individual differences in several other aspects of cognitive functioning. Thus, ideation processes, possibly supported by search and thinking processes, seem to contribute to option generation beyond basic associative memory retrieval. The findings of the study also indicate that generating more options may have multifaceted consequences for choice, increasing the quality of the best option generated but decreasing the mean quality of the options in the generated set. PMID:25657628

Option generation in decision making: ideation beyond memory retrieval.

PubMed

Del Missier, Fabio; Visentini, Mimì; Mäntylä, Timo

2014-01-01

According to prescriptive decision theories, the generation of options for choice is a central aspect of decision making. A too narrow representation of the problem may indeed limit the opportunity to evaluate promising options. However, despite the theoretical and applied significance of this topic, the cognitive processes underlying option generation are still unclear. In particular, while a cued recall account of option generation emphasizes the role of memory and executive control, other theoretical proposals stress the importance of ideation processes based on various search and thinking processes. Unfortunately, relevant behavioral evidence on the cognitive processes underlying option generation is scattered and inconclusive. In order to reach a better understanding, we carried out an individual-differences study employing a wide array of cognitive predictors, including measures of episodic memory, semantic memory, cognitive control, and ideation fluency. The criterion tasks consisted of three different poorly-structured decision-making scenarios, and the participants were asked to generate options to solve these problems. The main criterion variable of the study was the number of valid options generated, but also the diversity and the quality of generated options were examined. The results showed that option generation fluency and diversity in the context of ill-structured decision making are supported by ideation ability even after taking into account the effects of individual differences in several other aspects of cognitive functioning. Thus, ideation processes, possibly supported by search and thinking processes, seem to contribute to option generation beyond basic associative memory retrieval. The findings of the study also indicate that generating more options may have multifaceted consequences for choice, increasing the quality of the best option generated but decreasing the mean quality of the options in the generated set.

Problem Management Module: An Innovative System to Improve Problem List Workflow

PubMed Central

Hodge, Chad M.; Kuttler, Kathryn G.; Bowes, Watson A.; Narus, Scott P.

2014-01-01

Electronic problem lists are essential to modern health record systems, with a primary goal to serve as the repository of a patient’s current health issues. Additionally, coded problems can be used to drive downstream activities such as decision support, evidence-based medicine, billing, and cohort generation for research. Meaningful Use also requires use of a coded problem list. Over the course of three years, Intermountain Healthcare developed a problem management module (PMM) that provided innovative functionality to improve clinical workflow and boost problem list adoption, e.g. smart search, user customizable views, problem evolution, and problem timelines. In 23 months of clinical use, clinicians entered over 70,000 health issues, the percentage of free-text items dropped to 1.2%, completeness of problem list items increased by 14%, and more collaborative habits were initiated. PMID:25954372

Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

PubMed

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

NASA Astrophysics Data System (ADS)

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Does Prevention Pay? Costs and Potential Cost-savings of School Interventions Targeting Children with Mental Health Problems.

PubMed

Wellander, Lisa; Wells, Michael B; Feldman, Inna

2016-06-01

In Sweden, the local government is responsible for funding schools in their district. One funding initiative is for schools to provide students with mental health problems with additional support via extra teachers, personal assistants, and special education classes. There are evidence-based preventive interventions delivered in schools, which have been shown to decrease the levels of students' mental health problems. However, little is known about how much the local government currently spends on students' mental health support and if evidence-based interventions could be financially beneficial. The aim of this study was to estimate the costs of providing additional support for students' mental health problems and the potential cost-offsets, defined as reduced school-based additional support, if two evidence-based school interventions targeting children's mental health problems were implemented in routine practice. This study uses data on the additional support students with mental health problems received in schools. Data was collected from one school district for students aged 6 to 16 years. We modeled two Swedish school interventions, Comet for Teachers and Social and Emotional Training (SET), which both had evidence of reducing mental health problems. We used a cost-offset analysis framework, assuming both interventions were fully implemented throughout the whole school district. Based on the published studies, the expected effects and the costs of the interventions were calculated. We defined the cost-offsets as the amount of predicted averted additional support for students with ongoing mental health problems who might no longer require receiving services such as one-on-one time with an extra teacher, a personal assistant, or to be placed in a special education classroom. A cost-offset analysis, from a payer's perspective (the local government responsible for school financing), was conducted comparing the costs of both interventions with the potential cost-savings due to a reduction in the prevalence of mental health problems and averted additional support required. The school district was comprised of 6,256 students, with 310 students receiving additional support for their mental health problems. Of these, 143 received support in their original school due to either having ADHD (n = 111), psychosocial problems (n = 26), or anxiety/depression (n = 6). The payers' total cost of additional support was 2,637,850 Euro per school year (18,447 Euro per student). The cost of running both interventions for the school district was 953,643 Euro for one year, while the potential savings for these interventions were estimated to be 627,150 Euro. The estimated effects showed that there would be a reduction of students needing additional support (25 for ADHD, eight for psychosocial problems, and one for anxiety/depression), and the payer would receive a return on their invested resources in less than two years (1.5 years) after implementation. Preventive school interventions can both improve some children's mental health problems and be financially beneficial for the payer. However, they are still limited in their scope of reducing all students' mental health statuses to below clinical cut-offs; therefore, the preventive school interventions should be used as a supplement, but not a replacement, to current practices. The findings have political and societal implications, in that payers can reallocate their funds toward preventive measures targeting students' mental health problems, while reducing the costs. When evaluating public health actions, it is necessary to consider their economic impact. The resources are scarce and the decision makers need knowledge on how to allocate their resources in an efficient way. Cost-offset analysis is seen as one way for decision makers to comprehend research findings; however, such analyses tend to not include the full benefits of the interventions, and actual impacts need to be fully evaluated in routine implementation.

REACT Real-Time Emergency Action Coordination Tool

NASA Technical Reports Server (NTRS)

2004-01-01

Recently the Emergency Management Operations Center (EMOC) of St. Tammany Parish turned to the Technology Development and Transfer Office (TDTO) of NASA's Stennis Space Center (SSC) for help in combating the problems associated with water inundation. Working through a Dual-Use Development Agreement the Technology Development and Transfer Office, EMOC and a small geospatial applications company named Nvision provided the parish with a new front-line defense. REACT, Real-time Emergency Action coordination Tool is a decision support system that integrates disparate information to enable more efficient decision making by emergency management personnel.

Value of DNA tests: a decision perspective.

PubMed

Taroni, Franco; Bozza, Silvia; Bernard, Magali; Champod, Christophe

2007-01-01

Before a Court of Law testifying in DNA-evidence cases, scientists are often challenged with the idea that the more markers (loci) the better, i.e., why does the scientist not use 16 or more markers? This paper introduces a new perspective, decision analysis, to deal with the problem of the number of markers to type in a criminal context. The decision-making process, which plays a key role in the routine work of a forensic scientist, consists of the rational choice, given personal objectives, between two or more possible outcomes when the consequences of the choice are uncertain. Simulated results support the hypothesis that analytical added value does not increase with the number of markers.

WRF/CMAQ AQMEII3 Simulations of US Regional-Scale ...

EPA Pesticide Factsheets

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary conditions prepared from four different global models. Results indicate that the impacts of different boundary conditions are significant for ozone throughout the year and most pronounced outside the summer season. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

The menu-setting problem and subsidized prices: drug formulary illustration.

PubMed

Olmstead, T; Zeckhauser, R

1999-10-01

The menu-setting problem (MSP) determines the goods and services an institution offers and the prices charged. It appears widely in health care, from choosing the services an insurance arrangement offers, to selecting the health plans an employer proffers. The challenge arises because purchases are subsidized, and consumers (or their physician agents) may make cost-ineffective choices. The intuitively comprehensible MSP model--readily solved by computer using actual data--helps structure thinking and support decision making about such problems. The analysis uses drug formularies--lists of approved drugs in a plan or institution--to illustrate the framework.

Portable parallel portfolio optimization in the Aurora Financial Management System

NASA Astrophysics Data System (ADS)

Laure, Erwin; Moritsch, Hans

2001-07-01

Financial planning problems are formulated as large scale, stochastic, multiperiod, tree structured optimization problems. An efficient technique for solving this kind of problems is the nested Benders decomposition method. In this paper we present a parallel, portable, asynchronous implementation of this technique. To achieve our portability goals we elected the programming language Java for our implementation and used a high level Java based framework, called OpusJava, for expressing the parallelism potential as well as synchronization constraints. Our implementation is embedded within a modular decision support tool for portfolio and asset liability management, the Aurora Financial Management System.

Research and application of genetic algorithm in path planning of logistics distribution vehicle

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

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.

Advanced Technology Multiple Criteria Decision Model.

DTIC Science & Technology

1981-11-01

ratings of the sys- tem parameters; and (3), HEADER which contains information on the structure of the problem and titles. Two supporting programs develop...in these files are given in Section V.2. 2. DATA STRUCTURE TABLES This section describes the data files used in the system selection model program ...the supporting program PPP and an input file to UPPP and SSMP. Figure 13 shows the structure of this file. b. User’s preference package (UPP) UPP is

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

Does the cost function matter in Bayes decision rule?

PubMed

Schlü ter, Ralf; Nussbaum-Thom, Markus; Ney, Hermann

2012-02-01

In many tasks in pattern recognition, such as automatic speech recognition (ASR), optical character recognition (OCR), part-of-speech (POS) tagging, and other string recognition tasks, we are faced with a well-known inconsistency: The Bayes decision rule is usually used to minimize string (symbol sequence) error, whereas, in practice, we want to minimize symbol (word, character, tag, etc.) error. When comparing different recognition systems, we do indeed use symbol error rate as an evaluation measure. The topic of this work is to analyze the relation between string (i.e., 0-1) and symbol error (i.e., metric, integer valued) cost functions in the Bayes decision rule, for which fundamental analytic results are derived. Simple conditions are derived for which the Bayes decision rule with integer-valued metric cost function and with 0-1 cost gives the same decisions or leads to classes with limited cost. The corresponding conditions can be tested with complexity linear in the number of classes. The results obtained do not make any assumption w.r.t. the structure of the underlying distributions or the classification problem. Nevertheless, the general analytic results are analyzed via simulations of string recognition problems with Levenshtein (edit) distance cost function. The results support earlier findings that considerable improvements are to be expected when initial error rates are high.

Toward Epistemologically Authentic Engineering Design Activities in the Science Classroom

ERIC Educational Resources Information Center

Leonard, Mary J.

2004-01-01

In recent years educators and educational researchers in the U.S. have begun to introduce engineering design activities in secondary science classrooms for the purpose of scaffolding science learning as well as supporting such general problem-solving skills as decision making and working in teams. However, such curricula risk perpetuating a…

Technology for the Struggling Reader: Free and Easily Accessible Resources

ERIC Educational Resources Information Center

Berkeley, Sheri; Lindstrom, Jennifer H.

2011-01-01

A fundamental problem for many struggling readers, their parents, and their teachers is that there are few benchmarks to guide decision making about assistive technological supports when the nature of a disability is cognitive (e.g., specific learning disability, SLD) rather than physical. However, resources such as the National Center on…

Information and knowledge management in support of sustainable forestry: a review

Treesearch

H. Michael Rauscher; Daniel L. Schmoldt; Harald Vacik

2007-01-01

For individuals, organizations and nations, success and even survival depend upon making good decisions. Doing so can be extremely difficult when problems are not well structured and situations are complex, as they are for natural resource management. Recent advances in computer technology coupled with the increase in accessibility brought about by the...

Computer Simulation of a Hardwood Processing Plant

Treesearch

D. Earl Kline; Philip A. Araman

1990-01-01

The overall purpose of this paper is to introduce computer simulation as a decision support tool that can be used to provide managers with timely information. A simulation/animation modeling procedure is demonstrated for wood products manufacuring systems. Simulation modeling techniques are used to assist in identifying and solving problems. Animation is used for...

Natural Language Techniques for Decision Support Based on Patient Complaints

ERIC Educational Resources Information Center

ElMessiry, Adel Magdi

2016-01-01

Complaining is a fundamental human characteristic that has prevailed throughout the ages. We normally complain about something that went wrong. Patient complaints are no exception; they focus on problems that occurred during the episode of care. The Institute of Medicine estimated that each year thousands of patients die due to medical errors. The…

Reporting Data with "Over-the-Counter" Data Analysis Supports Increases Educators' Analysis Accuracy

ERIC Educational Resources Information Center

Rankin, Jenny Grant

2013-01-01

There is extensive research on the benefits of making data-informed decisions to improve learning, but these benefits rely on the data being effectively interpreted. Despite educators' above-average intellect and education levels, there is evidence many educators routinely misinterpret student data. Data analysis problems persist even at districts…

A hybrid approach to select features and classify diseases based on medical data

NASA Astrophysics Data System (ADS)

AbdelLatif, Hisham; Luo, Jiawei

2018-03-01

Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

Decision-Making, Cognitive Distortions and Alcohol Use in Adolescent Problem and Non-problem Gamblers: An Experimental Study.

PubMed

Ciccarelli, Maria; Griffiths, Mark D; Nigro, Giovanna; Cosenza, Marina

2016-12-01

In the psychological literature, many studies have investigated the neuropsychological and behavioral changes that occur developmentally during adolescence. These studies have consistently observed a deficit in the decision-making ability of children and adolescents. This deficit has been ascribed to incomplete brain development. The same deficit has also been observed in adult problem and pathological gamblers. However, to date, no study has examined decision-making in adolescents with and without gambling problems. Furthermore, no study has ever examined associations between problem gambling, decision-making, cognitive distortions and alcohol use in youth. To address these issues, 104 male adolescents participated in this study. They were equally divided in two groups, problem gamblers and non-problem gamblers, based on South Oaks Gambling Screen Revised for Adolescents scores. All participants performed the Iowa gambling task and completed the Gambling Related Cognitions Scale and the alcohol use disorders identification test. Adolescent problem gamblers displayed impaired decision-making, reported high cognitive distortions, and had more problematic alcohol use compared to non-problem gamblers. Strong correlations between problem gambling, alcohol use, and cognitive distortions were observed. Decision-making correlated with interpretative bias. This study demonstrated that adolescent problem gamblers appear to have the same psychological profile as adult problem gamblers and that gambling involvement can negatively impact on decision-making ability that, in adolescence, is still developing. The correlations between interpretative bias and decision-making suggested that the beliefs in the ability to influence gambling outcomes may facilitate decision-making impairment.

Helping the decision maker effectively promote various experts' views into various optimal solutions to China's institutional problem of health care provider selection through the organization of a pilot health care provider research system.

PubMed

Tang, Liyang

2013-04-04

The main aim of China's Health Care System Reform was to help the decision maker find the optimal solution to China's institutional problem of health care provider selection. A pilot health care provider research system was recently organized in China's health care system, and it could efficiently collect the data for determining the optimal solution to China's institutional problem of health care provider selection from various experts, then the purpose of this study was to apply the optimal implementation methodology to help the decision maker effectively promote various experts' views into various optimal solutions to this problem under the support of this pilot system. After the general framework of China's institutional problem of health care provider selection was established, this study collaborated with the National Bureau of Statistics of China to commission a large-scale 2009 to 2010 national expert survey (n = 3,914) through the organization of a pilot health care provider research system for the first time in China, and the analytic network process (ANP) implementation methodology was adopted to analyze the dataset from this survey. The market-oriented health care provider approach was the optimal solution to China's institutional problem of health care provider selection from the doctors' point of view; the traditional government's regulation-oriented health care provider approach was the optimal solution to China's institutional problem of health care provider selection from the pharmacists' point of view, the hospital administrators' point of view, and the point of view of health officials in health administration departments; the public private partnership (PPP) approach was the optimal solution to China's institutional problem of health care provider selection from the nurses' point of view, the point of view of officials in medical insurance agencies, and the health care researchers' point of view. The data collected through a pilot health care provider research system in the 2009 to 2010 national expert survey could help the decision maker effectively promote various experts' views into various optimal solutions to China's institutional problem of health care provider selection.

A Decision Support System for effective use of probability forecasts

NASA Astrophysics Data System (ADS)

De Kleermaeker, Simone; Verkade, Jan

2013-04-01

Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.

Using Elearning techniques to support problem based learning within a clinical simulation laboratory.

PubMed

Docherty, Charles; Hoy, Derek; Topp, Helena; Trinder, Kathryn

2004-01-01

This paper details the results of the first phase of a project that used eLearning to support students' learning within a simulated environment. The locus was a purpose built Clinical Simulation Laboratory (CSL) where the School's newly adopted philosophy of Problem Based Learning (PBL) was challenged through lecturers reverting to traditional teaching methods. The solution, a student-centred, problem-based approach to the acquisition of clinical skills was developed using learning objects embedded within web pages that substituted for lecturers providing instruction and demonstration. This allowed lecturers to retain their facilitator role, and encouraged students to explore, analyse and make decisions within the safety of a clinical simulation. Learning was enhanced through network communications and reflection on video performances of self and others. Evaluations were positive, students demonstrating increased satisfaction with PBL, improved performance in exams, and increased self-efficacy in the performance of nursing activities. These results indicate that an elearning approach can support PBL in delivering a student centred learning experience.

A pathway to personalization of integrated treatment: informatics and decision science in psychiatric rehabilitation.

PubMed

Spaulding, William; Deogun, Jitender

2011-09-01

Personalization of treatment is a current strategic goal for improving health care. Integrated treatment approaches such as psychiatric rehabilitation benefit from personalization because they involve matching diverse arrays of treatment options to individually unique profiles of need. The need for personalization is evident in the heterogeneity of people with severe mental illness and in the findings of experimental psychopathology. One pathway to personalization lies in analysis of the judgments and decision making of human experts and other participants as they respond to complex circumstances in pursuit of treatment and rehabilitation goals. Such analysis is aided by computer simulation of human decision making, which in turn informs development of computerized clinical decision support systems. This inspires a research program involving concurrent development of databases, domain ontology, and problem-solving algorithms, toward the goal of personalizing psychiatric rehabilitation through human collaboration with intelligent cyber systems. The immediate hurdle is to demonstrate that clinical decisions beyond diagnosis really do affect outcome. This can be done by supporting the hypothesis that a human treatment team with access to a reasonably comprehensive clinical database that tracks patient status and treatment response over time achieves better outcome than a treatment team without such access, in a controlled experimental trial. Provided the hypothesis can be supported, the near future will see prototype systems that can construct an integrated assessment, formulation, and rehabilitation plan from clinical assessment data and contextual information. This will lead to advanced systems that collaborate with human decision makers to personalize psychiatric rehabilitation and optimize outcome.

The design and implementation of an Interactive Computerised Decision Support Framework (ICDSF) as a strategy to improve nursing students' clinical reasoning skills.

PubMed

Hoffman, Kerry; Dempsey, Jennifer; Levett-Jones, Tracy; Noble, Danielle; Hickey, Noelene; Jeong, Sarah; Hunter, Sharyn; Norton, Carol

2011-08-01

This paper describes the conceptual design and testing of an Interactive Computerised Decision Support Framework (ICDSF) which was constructed to enable student nurses to "think like a nurse." The ICDSF was based on a model of clinical reasoning. Teaching student nurses to reason clinically is important as poor clinical reasoning skills can lead to "failure-to rescue" of deteriorating patients. The framework of the ICDSF was based on nursing concepts to encourage deep learning and transferability of knowledge. The principles of active student participation, situated cognition to solve problems, authenticity, and cognitive rehearsal were used to develop the ICDSF. The ICDSF was designed in such a way that students moved through it in a step-wise fashion and were required to achieve competency at each step before proceeding to the next. The quality of the ICDSF was evaluated using a questionairre survey, students' written comments and student assessment measures on a pilot and the ICDSF. Overall students were highly satisfied with the clinical scenarios of the ICDSF and believed they were an interesting and useful way to engage in authentic clinical learning. They also believed the ICDSF was useful in developing cognitive skills such as clinical reasoning, problem-solving and decision-making. Some reported issues were the need for good technical support and the lack of face to face contact when using e-learning. Some students also believed the ICDSF was less useful than actual clinical placements. Copyright © 2010 Elsevier Ltd. All rights reserved.

[Spinal muscular atrophy and respiratory failure. How do primary care pediatricians act in a simulated scenario?].

PubMed

Agra Tuñas, M C; Sánchez Santos, L; Busto Cuiñas, M; Rodríguez Núñez, A

2015-11-01

Spinal muscular atrophy type 1 (SMA-1) tends to be fatal in the first year of life if there is no ventilatory support. The decision whether to start such support is an ethical conflict for healthcare professionals. A scenario of acute respiratory failure in an infant with SMA-1 has been included in a training program using advanced simulation for Primary Care pediatricians (PCP). The performances of 34 groups of 4 pediatricians, who participated in 17 courses, were systematically analyzed. Clinical, ethical and communication aspects with parents were evaluated. The initial technical assistance (Administration of oxygen and immediate ventilatory support) was correctly performed by 94% of the teams. However, the PCP had problems in dealing with the ethical aspects of the case. Of the 85% of the teams that raised the ethical conflict with parents, 29% did so on their own initiative, 23% actively excluded them, and only 6% involved them and took their opinion into account in making decisions. Only 11.7% asked about the quality of life of children and 12% for their knowledge of the prognosis of the disease. None explained treatment alternatives, nor tried to contact the pediatrician responsible for the child. When faced with a simulated SMA-1 infant with respiratory failure, PCP have difficulties in interacting with the family, and to involve it in the decision making process. Practical training of all pediatricians should include case scenarios with an ethical clinical problem. Copyright © 2014 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

Cross-lagged relationships between workplace demands, control, support, and sleep problems.

PubMed

Hanson, Linda L Magnusson; Åkerstedt, Torbjörn; Näswall, Katharina; Leineweber, Constanze; Theorell, Töres; Westerlund, Hugo

2011-10-01

Sleep problems are experienced by a large part of the population. Work characteristics are potential determinants, but limited longitudinal evidence is available to date, and reverse causation is a plausible alternative. This study examines longitudinal, bidirectional relationships between work characteristics and sleep problems. Prospective cohort/two-wave panel. Sweden. 3065 working men and women approximately representative of the Swedish workforce who responded to the 2006 and 2008 waves of the Swedish Longitudinal Occupational Survey of Health (SLOSH). N/A. Bidirectional relationships between, on the one hand, workplace demands, decision authority, and support, and, on the other hand, sleep disturbances (reflecting lack of sleep continuity) and awakening problems (reflecting feelings of being insufficiently restored), were investigated by structural equation modeling. All factors were modeled as latent variables and adjusted for gender, age, marital status, education, alcohol consumption, and job change. Concerning sleep disturbances, the best fitting models were the "forward" causal model for demands and the "reverse" causal model for support. Regarding awakening problems, reciprocal models fitted the data best. Cross-lagged analyses indicates a weak relationship between demands at Time 1 and sleep disturbances at Time 2, a "reverse" relationship from support T1 to sleep disturbances T2, and bidirectional associations between work characteristics and awakening problems. In contrast to an earlier study on demands, control, sleep quality, and fatigue, this study suggests reverse and reciprocal in addition to the commonly hypothesized causal relationships between work characteristics and sleep problems based on a 2-year time lag.

Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management

PubMed Central

Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason

2016-01-01

With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM3 ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs. PMID:27983713

Problem Formulation in Knowledge Discovery via Data Analytics (KDDA) for Environmental Risk Management.

PubMed

Li, Yan; Thomas, Manoj; Osei-Bryson, Kweku-Muata; Levy, Jason

2016-12-15

With the growing popularity of data analytics and data science in the field of environmental risk management, a formalized Knowledge Discovery via Data Analytics (KDDA) process that incorporates all applicable analytical techniques for a specific environmental risk management problem is essential. In this emerging field, there is limited research dealing with the use of decision support to elicit environmental risk management (ERM) objectives and identify analytical goals from ERM decision makers. In this paper, we address problem formulation in the ERM understanding phase of the KDDA process. We build a DM³ ontology to capture ERM objectives and to inference analytical goals and associated analytical techniques. A framework to assist decision making in the problem formulation process is developed. It is shown how the ontology-based knowledge system can provide structured guidance to retrieve relevant knowledge during problem formulation. The importance of not only operationalizing the KDDA approach in a real-world environment but also evaluating the effectiveness of the proposed procedure is emphasized. We demonstrate how ontology inferencing may be used to discover analytical goals and techniques by conceptualizing Hazardous Air Pollutants (HAPs) exposure shifts based on a multilevel analysis of the level of urbanization (and related economic activity) and the degree of Socio-Economic Deprivation (SED) at the local neighborhood level. The HAPs case highlights not only the role of complexity in problem formulation but also the need for integrating data from multiple sources and the importance of employing appropriate KDDA modeling techniques. Challenges and opportunities for KDDA are summarized with an emphasis on environmental risk management and HAPs.

Using the Reliability Theory for Assessing the Decision Confidence Probability for Comparative Life Cycle Assessments.

PubMed

Wei, Wei; Larrey-Lassalle, Pyrène; Faure, Thierry; Dumoulin, Nicolas; Roux, Philippe; Mathias, Jean-Denis

2016-03-01

Comparative decision making process is widely used to identify which option (system, product, service, etc.) has smaller environmental footprints and for providing recommendations that help stakeholders take future decisions. However, the uncertainty problem complicates the comparison and the decision making. Probability-based decision support in LCA is a way to help stakeholders in their decision-making process. It calculates the decision confidence probability which expresses the probability of a option to have a smaller environmental impact than the one of another option. Here we apply the reliability theory to approximate the decision confidence probability. We compare the traditional Monte Carlo method with a reliability method called FORM method. The Monte Carlo method needs high computational time to calculate the decision confidence probability. The FORM method enables us to approximate the decision confidence probability with fewer simulations than the Monte Carlo method by approximating the response surface. Moreover, the FORM method calculates the associated importance factors that correspond to a sensitivity analysis in relation to the probability. The importance factors allow stakeholders to determine which factors influence their decision. Our results clearly show that the reliability method provides additional useful information to stakeholders as well as it reduces the computational time.

Applying multi-criteria decision-making to improve the waste reduction policy in Taiwan.

PubMed

Su, Jun-Pin; Hung, Ming-Lung; Chao, Chia-Wei; Ma, Hwong-wen

2010-01-01

Over the past two decades, the waste reduction problem has been a major issue in environmental protection. Both recycling and waste reduction policies have become increasingly important. As the complexity of decision-making has increased, it has become evident that more factors must be considered in the development and implementation of policies aimed at resource recycling and waste reduction. There are many studies focused on waste management excluding waste reduction. This study paid more attention to waste reduction. Social, economic, and management aspects of waste treatment policies were considered in this study. Further, a life-cycle assessment model was applied as an evaluation system for the environmental aspect. Results of both quantitative and qualitative analyses on the social, economic, and management aspects were integrated via the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method into the comprehensive decision-making support system of multi-criteria decision-making (MCDM). A case study evaluating the waste reduction policy in Taoyuan County is presented to demonstrate the feasibility of this model. In the case study, reinforcement of MSW sorting was shown to be the best practice. The model in this study can be applied to other cities faced with the waste reduction problems.

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions.

PubMed

Stewart, G B; Mengersen, K; Meader, N

2014-03-01

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to 'empty' reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence. Copyright © 2013 John Wiley & Sons, Ltd.

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.

Cognitive issues in autonomous spacecraft-control operations: An investigation of software-mediated decision making in a scaled environment

NASA Astrophysics Data System (ADS)

Murphy, Elizabeth Drummond

As advances in technology are applied in complex, semi-automated domains, human controllers are distanced from the controlled process. This physical and psychological distance may both facilitate and degrade human performance. To investigate cognitive issues in spacecraft ground-control operations, the present experimental research was undertaken. The primary issue concerned the ability of operations analysts who do not monitor operations to make timely, accurate decisions when autonomous software calls for human help. Another key issue involved the potential effects of spatial-visualization ability (SVA) in environments that present data in graphical formats. Hypotheses were derived largely from previous findings and predictions in the literature. Undergraduate psychology students were assigned at random to a monitoring condition or an on-call condition in a scaled environment. The experimental task required subjects to decide on the veracity of a problem diagnosis delivered by a software process on-board a simulated spacecraft. To support decision-making, tabular and graphical data displays presented information on system status. A level of software confidence in the problem diagnosis was displayed, and subjects reported their own level of confidence in their decisions. Contrary to expectations, the performance of on-call subjects did not differ significantly from that of continuous monitors. Analysis yielded a significant interaction of sex and condition: Females in the on-call condition had the lowest mean accuracy. Results included a preference for bar charts over line graphs and faster performance with tables than with line graphs. A significant correlation was found between subjective confidence and decision accuracy. SVA was found to be predictive of accuracy but not speed; and SVA was found to be a stronger predictor of performance for males than for females. Low-SVA subjects reported that they relied more on software confidence than did medium- or high-SVA subjects. These and other findings have implications for the design of user interfaces to support human decision-making in on-call situations and to accommodate low-SVA users.

Sell in May and Go Away? Learning and Risk Taking in Nonmonotonic Decision Problems

ERIC Educational Resources Information Center

Frey, Renato; Rieskamp, Jörg; Hertwig, Ralph

2015-01-01

In nonmonotonic decision problems, the magnitude of outcomes can both increase and decrease over time depending on the state of the decision problem. These increases and decreases may occur repeatedly and result in a variety of possible outcome distributions. In many previously investigated sequential decision problems, in contrast, outcomes (or…

Image-guided decision support system for pulmonary nodule classification in 3D thoracic CT images

NASA Astrophysics Data System (ADS)

Kawata, Yoshiki; Niki, Noboru; Ohmatsu, Hironobu; Kusumoto, Masahiro; Kakinuma, Ryutaro; Mori, Kiyoshi; Yamada, Kozo; Nishiyama, Hiroyuki; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki

2004-05-01

The purpose of this study is to develop an image-guided decision support system that assists decision-making in clinical differential diagnosis of pulmonary nodules. This approach retrieves and displays nodules that exhibit morphological and internal profiles consistent to the nodule in question. It uses a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. In order to build the system, there are following issues that should be solved: 1) to categorize the nodule database with respect to morphological and internal features, 2) to quickly search nodule images similar to an indeterminate nodule from a large database, and 3) to reveal malignancy likelihood computed by using similar nodule images. Especially, the first problem influences the design of other issues. The successful categorization of nodule pattern might lead physicians to find important cues that characterize benign and malignant nodules. This paper focuses on an approach to categorize the nodule database with respect to nodule shape and CT density patterns inside nodule.

Team Meetings within Clinical Domains - Exploring the Use of Routines and Technical Support for Communication

NASA Astrophysics Data System (ADS)

Groth, Kristina; Lantz, Ann; Sallnäs, Eva-Lotta; Frykholm, Oscar; Green, Anders

Today, it is common that a team of clinicians, from different disciplines, instead of one single doctor, care for a patient. This is especially true when it concerns more complicated diseases in highly specialised health care. Going from one doctor to a team of doctors raises new dimensions/problems/issues when deciding about the diagnosis and how to treat the patient. Instead of one person deciding, based on the information given from others, a group of people need to agree on a decision. How do the participants during such decision meetings argue for their experience and skill? What kind of technologies are available and how do they support the communication in the meeting? Måseide (2006), for example, focuses on how different forms of evidence influence and regulate the judgements and decisions of medical practitioners during such meetings. Groth et al. (2008), for example, focuses on the technology used during such meetings, with a focus on audio, video, and images.

Description and status update on GELLO: a proposed standardized object-oriented expression language for clinical decision support.

PubMed

Sordo, Margarita; Boxwala, Aziz A; Ogunyemi, Omolola; Greenes, Robert A

2004-01-01

A major obstacle to sharing computable clinical knowledge is the lack of a common language for specifying expressions and criteria. Such a language could be used to specify decision criteria, formulae, and constraints on data and action. Al-though the Arden Syntax addresses this problem for clinical rules, its generalization to HL7's object-oriented data model is limited. The GELLO Expression language is an object-oriented language used for expressing logical conditions and computations in the GLIF3 (GuideLine Interchange Format, v. 3) guideline modeling language. It has been further developed under the auspices of the HL7 Clinical Decision Support Technical Committee, as a proposed HL7 standard., GELLO is based on the Object Constraint Language (OCL), because it is vendor-independent, object-oriented, and side-effect-free. GELLO expects an object-oriented data model. Although choice of model is arbitrary, standardization is facilitated by ensuring that the data model is compatible with the HL7 Reference Information Model (RIM).

System for decision analysis support on complex waste management issues

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

Shropshire, D.E.

1997-10-01

A software system called the Waste Flow Analysis has been developed and applied to complex environmental management processes for the United States Department of Energy (US DOE). The system can evaluate proposed methods of waste retrieval, treatment, storage, transportation, and disposal. Analysts can evaluate various scenarios to see the impacts to waste slows and schedules, costs, and health and safety risks. Decision analysis capabilities have been integrated into the system to help identify preferred alternatives based on a specific objectives may be to maximize the waste moved to final disposition during a given time period, minimize health risks, minimize costs,more » or combinations of objectives. The decision analysis capabilities can support evaluation of large and complex problems rapidly, and under conditions of variable uncertainty. The system is being used to evaluate environmental management strategies to safely disposition wastes in the next ten years and reduce the environmental legacy resulting from nuclear material production over the past forty years.« less

Volatile decision dynamics: experiments, stochastic description, intermittency control and traffic optimization

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Schönhof, Martin; Kern, Daniel

2002-06-01

The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.

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

PubMed Central

2014-01-01

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

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

PubMed

Youngstrom, Eric A

2014-03-01

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

Induced abortion and psychological sequelae.

PubMed

Cameron, Sharon

2010-10-01

The decision to seek an abortion is never easy. Women have different reasons for choosing an abortion and their social, economic and religious background may influence how they cope. Furthermore, once pregnant, the alternatives of childbirth and adoption or keeping the baby may not be psychologically neutral. Research studies in this area have been hampered by methodological problems, but most of the better-quality studies have shown no increased risk of mental health problems in women having an abortion. A consistent finding has been that of pre-existing mental illness and subsequent mental health problems after either abortion or childbirth. Furthermore, studies have shown that only a minority of women experience any lasting sadness or regret. Risk factors for this include ambivalence about the decision, level of social support and whether or not the pregnancy was originally intended. More robust, definitive research studies are required on mental health after abortion and alternative outcomes such as childbirth. Copyright 2010 Elsevier Ltd. All rights reserved.

Adaptive Peircean decision aid project summary assessments.

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

Senglaub, Michael E.

2007-01-01

This efforts objective was to identify and hybridize a suite of technologies enabling the development of predictive decision aids for use principally in combat environments but also in any complex information terrain. The technologies required included formal concept analysis for knowledge representation and information operations, Peircean reasoning to support hypothesis generation, Mill's's canons to begin defining information operators that support the first two technologies and co-evolutionary game theory to provide the environment/domain to assess predictions from the reasoning engines. The intended application domain is the IED problem because of its inherent evolutionary nature. While a fully functioning integrated algorithm wasmore » not achieved the hybridization and demonstration of the technologies was accomplished and demonstration of utility provided for a number of ancillary queries.« less

Developing Quality Indicators and Auditing Protocols from Formal Guideline Models: Knowledge Representation and Transformations

PubMed Central

Advani, Aneel; Goldstein, Mary; Shahar, Yuval; Musen, Mark A.

2003-01-01

Automated quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe a model representation and algorithm for deriving structured quality indicators and auditing protocols from formalized specifications of guidelines used in decision support systems. We apply the model and algorithm to the assessment of physician concordance with a guideline knowledge model for hypertension used in a decision-support system. The properties of our solution include the ability to derive automatically (1) context-specific and (2) case-mix-adjusted quality indicators that (3) can model global or local levels of detail about the guideline (4) parameterized by defining the reliability of each indicator or element of the guideline. PMID:14728124

A collaborative framework for contributing DICOM RT PHI (Protected Health Information) to augment data mining in clinical decision support

NASA Astrophysics Data System (ADS)

Deshpande, Ruchi; Thuptimdang, Wanwara; DeMarco, John; Liu, Brent J.

2014-03-01

We have built a decision support system that provides recommendations for customizing radiation therapy treatment plans, based on patient models generated from a database of retrospective planning data. This database consists of relevant metadata and information derived from the following DICOM objects - CT images, RT Structure Set, RT Dose and RT Plan. The usefulness and accuracy of such patient models partly depends on the sample size of the learning data set. Our current goal is to increase this sample size by expanding our decision support system into a collaborative framework to include contributions from multiple collaborators. Potential collaborators are often reluctant to upload even anonymized patient files to repositories outside their local organizational network in order to avoid any conflicts with HIPAA Privacy and Security Rules. We have circumvented this problem by developing a tool that can parse DICOM files on the client's side and extract de-identified numeric and text data from DICOM RT headers for uploading to a centralized system. As a result, the DICOM files containing PHI remain local to the client side. This is a novel workflow that results in adding only relevant yet valuable data from DICOM files to the centralized decision support knowledge base in such a way that the DICOM files never leave the contributor's local workstation in a cloud-based environment. Such a workflow serves to encourage clinicians to contribute data for research endeavors by ensuring protection of electronic patient data.

Deepening the quality of clinical reasoning and decision-making in rural hospital nursing practice.

PubMed

Sedgwick, M G; Grigg, L; Dersch, S

2014-01-01

Rural acute care nursing requires an extensive breadth and depth of knowledge as well as the ability to quickly reason through problems in order to make sound clinical decisions. This reasoning often occurs within an environment that has minimal medical or ancillary support. Registered nurses (RN) new to rural nursing, and employers, have raised concerns about patient safety while new nurses make the transition into rural practice. In addition, feeling unprepared for the rigors of rural hospital nursing practice is a central issue influencing RN recruitment and retention. Understanding how rural RNs reason is a key element for identifying professional development needs and may support recruitment and retention of skilled rural nurses. The purpose of this study was to explore how rural RNs reason through clinical problems as well as to assess the quality of such reasoning. This study used a non-traditional approach for data collection. Fifteen rural acute care nurses with varying years of experience working in southern Alberta, Canada, were observed while they provided care to patients of varying acuity within a simulated rural setting. Following the simulation, semi-structured interviews were conducted using a substantive approach to critical thinking. Findings revealed that the ability to engage in deep clinical reasoning varied considerably among participants despite being given the same information under the same circumstances. Furthermore, the number of years of experience did not seem to be directly linked to the ability to engage in sound clinical reasoning. Novice nurses, however, did rely heavily on others in their decision making in order to ensure they were making the right decision. Hence, their relationships with other staff members influenced their ability to engage in clinical reasoning and decision making. In situations where the patient's condition was deteriorating quickly, regardless of years of experience, all of the participants depended on their colleagues when making decisions and reasoning throughout the simulation. Deep clinical reasoning and decision making is a function of reflection and self-correction that requires a critical self-awareness and is more about how nurses think than what they think. The degree of sophistication in reasoning of experts and novices is at times equivalent in that the reasoning of experts and novices can be somewhat limited and focused primarily on human physicality and less on conceptual knowledge. To become proficient in clinical reasoning, practice is necessary. The study supports the accumulating evidence that using clinical simulation and reflective interviewing that emphasize how clinical decisions are made enhances reasoning skills and confidence.

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

NASA Astrophysics Data System (ADS)

Lee, Seung Yup

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

Education in the workplace for the physician: clinical management states as an organizing framework.

PubMed

Greenes, R A

2000-01-01

Medical educators are interested in approaches to making selected relevant knowledge available in the context of problem-based care. This is of value both during the process of care and as a means of organizing information for offline self-study. Four trends in health information technology are relevant to achieving the goal and can be expected to play a growing role in the future. First, health care enterprises are developing approaches for access to information resources related to the care of a patient, including clinical data and images but also communication tools, referral and other logistic tools, decision support, and educational materials. Second, information for patients and methods for patient-doctor interaction and decision making are becoming available. Third, computer-based methods for representation of practice guidelines are being developed to support applications that can incorporate their logic. Finally, considering patients as being in particular "clinical management states" (or CMSs) for specific problems, approaches are being developed to use guidelines as a kind of "predictive" framework to enable development of interfaces for problem-based clinical encounters. The guidelines for a CMS can be used to identify the kinds of resources specifically needed for clinical encounters of that type. As the above trends converge to produce problem-specific environments, professional specialty organizations and continuing medical education course designers will need to focus energies on organizing and updating medical knowledge to make it available in CMS-specific contexts.

Learning Reverse Engineering and Simulation with Design Visualization

NASA Technical Reports Server (NTRS)

Hemsworth, Paul J.

2018-01-01

The Design Visualization (DV) group supports work at the Kennedy Space Center by utilizing metrology data with Computer-Aided Design (CAD) models and simulations to provide accurate visual representations that aid in decision-making. The capability to measure and simulate objects in real time helps to predict and avoid potential problems before they become expensive in addition to facilitating the planning of operations. I had the opportunity to work on existing and new models and simulations in support of DV and NASA’s Exploration Ground Systems (EGS).

Extension of a Computer Assisted Decision Support (CADS) Study to Improve Outcomes in Patients with Type 2 DM Treated by Primary Care Providers (short title, CADS-X). Addendum

DTIC Science & Technology

2014-12-01

Hypertension is one of the most common co-morbidities associated with DM and substantially contributes to the macrovascular disease that occurs in...After Numera terminated the contract to provide glucometer download support Estenda activated the patient portal , Diabetes Mellitus Everywhere...several patients. Problem areas include having to download JAVA with first upload and accessing the DME portal . d. PO has downloaded glucose

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.

Creative Design of Digital Cognitive Games: Application of Cognitive Toys and Isomorphism

ERIC Educational Resources Information Center

Sedig, Kamran; Haworth, Robert

2012-01-01

Digital cognitive games (DCGs) are games whose primary purpose is to mediate (i.e., support, develop, and enhance) cognitive activities such as problem solving, decision making, planning, and critical reasoning. As these games increase in popularity and usage, more attention should be paid to their design. Currently, there is a lack of design…

Probabilistic Ontology Architecture for a Terrorist Identification Decision Support System

DTIC Science & Technology

2014-06-01

in real-world problems requires probabilistic ontologies, which integrate the inferential reasoning power of probabilistic representations with the... inferential reasoning power of probabilistic representations with the first-order expressivity of ontologies. The Reference Architecture for...ontology, terrorism, inferential reasoning, architecture I. INTRODUCTION A. Background Whether by nature or design, the personas of terrorists are

Testing the Usability of Interactive Visualizations for Complex Problem-Solving: Findings Related to Improving Interfaces and Help.

ERIC Educational Resources Information Center

Mirel, Barbara

2001-01-01

Conducts a scenario-based usability test with 10 data analysts using visual querying (visually analyzing data with interactive graphics). Details a range of difficulties found in visual selection that, at times, gave rise to inaccurate selections, invalid conclusions, and misguided decisions. Argues that support for visual selection must be built…

Doing All the Right Things: Teacher Retention Issues

ERIC Educational Resources Information Center

Brown, Kathleen M.; Schainker, Stanley A.

2008-01-01

Teacher retention has become a national crisis. This case study describes one principal's efforts to support new teachers and reduce the turnover rate at her school. Recognizing the problem a few years ago, the principal took what she thought were a number of proactive, decisive steps to resolve the issue--she is doing all the right things.…

Benefits a Community College Can Realize by Providing Older Adult Programs: A Trustee's Viewpoint.

ERIC Educational Resources Information Center

Hartstein, Ray

Board members of community colleges need to carefully consider and actively support feasible programs for older people with a firm commitment to fiscal and programmatic decisions assuring lifelong learning opportunities and public service activities. Trustees must be aware of and understand problems and issues of older adults, secure data for…

A watershed decision support tool for managing invasive species on Hawai‘i Island, USA

Treesearch

Nicholas A. Povak; Paul F. Hessburg; Christian P. Giardina; Keith M. Reynolds; Chris Heider; Ed Salminen; R. Brion Salter; Richard A. MacKenzie

2017-01-01

Non-native species invasions, growing human populations, and climate change are central ecological concerns in tropical island communities. The combination of these threats have led to losses of native biota, altered hydrological and ecosystem processes, and reduced ecosystem services. These threats pose complex problems to often underfunded management entities. We...

Making the Grade: The Quest for Validity in Admissions Decisions.

ERIC Educational Resources Information Center

Pelech, William; Stalker, Carol A.; Regehr, Cheryl; Jacobs, Marilyn

1999-01-01

A study found that students having problems in a graduate social-work program are more likely to be older, be male, have lower undergraduate grades, have more experience in social service-related work, and be rated lower in emotional maturity based on personal statements. Implications for provision of support for such students are discussed.…

A Crime Analysis Decision Support System for Crime Report Classification and Visualization

ERIC Educational Resources Information Center

Ku, Chih-Hao

2012-01-01

Today's Internet-based crime reporting systems make timely and anonymous crime reporting possible. However, these reports also result in a rapidly growing set of unstructured text files. Complicating the problem is that the information has not been filtered or guided in a detective-led interview resulting in much irrelevant information. To…

Resources for Clergy in Human Genetic Problems. A Selected Bibliography. Second Edition.

ERIC Educational Resources Information Center

National Center for Education in Maternal and Child Health, Washington, DC.

Genetic disease and birth defects pose a unique set of concerns for affected individuals and their families. The need of these individuals for pastoral care--guidance for difficult decisions, bereavement counseling, and support--has opened a new area of ministry for pastors and pastoral counselors of all faiths. This ministry occupies the…

Applying the Brakes: How Practical Classroom Decisions Affect the Adoption of Inquiry Instruction

ERIC Educational Resources Information Center

Yarnall, Louise; Fusco, Judi

2014-01-01

If college science instructors are to use inquiry practices more in the classroom, they need both professional support to foster comfort with the pedagogy and practical ways to engage students in inquiry. Over a semester, we studied 13 community college biology instructors as they adopted bioinformatics problem-based learning (PBL) modules in…

Coping strategies and immune neglect in affective forecasting: Direct evidence and key moderators

PubMed Central

Hoerger, Michael

2012-01-01

Affective forecasting skills have important implications for decision making. However, recent research suggests that immune neglect – the tendency to overlook coping strategies that reduce future distress – may lead to affective forecasting problems. Prior evidence for immune neglect has been indirect. More direct evidence and a deeper understanding of immune neglect are vital to informing the design of future decision-support interventions. In the current study, young adults (N = 325) supplied predicted, actual, and recollected reactions to an emotionally-evocative interpersonal event, Valentine’s Day. Based on participants’ qualitative descriptions of the holiday, a team of raters reliably coded the effectiveness of their coping strategies. Supporting the immune neglect hypothesis, participants overlooked the powerful role of coping strategies when predicting their emotional reactions. Immune neglect was present not only for those experiencing the holiday negatively (non-daters) but also for those experiencing it positively (daters), suggesting that the bias may be more robust than originally theorized. Immune neglect was greater for immediate emotional reactions than more enduring reactions. Further, immune neglect was conspicuously absent from recollected emotional reactions. Implications for decision-support interventions are discussed. PMID:22375161

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex and Dynamic Conditions

DTIC Science & Technology

2015-07-14

AFRL-OSR-VA-TR-2015-0202 Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex...Computational Modeling of Team Problem Solving for Decision Making Under Complex and Dynamic Conditions 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1...functioning as they solve complex problems, and propose the means to improve the performance of teams, under changing or adversarial conditions. By

“The problem often is that we do not have a family spokesperson but a spokesgroup”: Family Member Informal Roles in End-of-Life Decision-Making in Adult ICUs

PubMed Central

Quinn, Jill R.; Schmitt, Madeline; Baggs, Judith Gedney; Norton, Sally A.; Dombeck, Mary T.; Sellers, Craig R.

2013-01-01

Background To support the process of effective family decision-making, it is important to recognize and understand informal roles various family members may play in the end-of-life decision-making process. Objective The purpose of this study was to describe some informal roles consistently enacted by family members involved in the process of end-of-life decision-making in intensive care units (ICUs). Methods Ethnographic study. Data were collected via participant observation with field notes and semi-structured interviews on four ICUs in an academic health center in the mid-Atlantic United States from 2001 to 2004. The units studied were a medical ICU, a surgical ICU, a burn and trauma ICU, and a cardiovascular ICU. Participants Participants included health care clinicians, patients, and family members. Results Informal roles for family members consistently observed were:, Primary Caregiver, Primary Decision Maker, Family Spokesperson, Out-of-Towner, Patient Wishes Expert, Protector, Vulnerable Member, and Health Care Expert. The identified informal roles were part of family decision making processes, and each role was part of a potentially complicated family dynamic for end-of-life decision-making within the family system, and between the family and health care domains. Conclusions These informal roles reflect the diverse responses to demands for family decision making in what is usually a novel and stressful situation. Identification and description of these family member informal roles can assist clinicians to recognize and understand the functions of these roles in family decision making at the end-of-life, and guide development of strategies to support and facilitate increased effectiveness of family discussions and decision-making processes. PMID:22210699

eLearning techniques supporting problem based learning in clinical simulation.

PubMed

Docherty, Charles; Hoy, Derek; Topp, Helena; Trinder, Kathryn

2005-08-01

This paper details the results of the first phase of a project using eLearning to support students' learning within a simulated environment. The locus was a purpose built clinical simulation laboratory (CSL) where the School's philosophy of problem based learning (PBL) was challenged through lecturers using traditional teaching methods. a student-centred, problem based approach to the acquisition of clinical skills that used high quality learning objects embedded within web pages, substituting for lecturers providing instruction and demonstration. This encouraged student nurses to explore, analyse and make decisions within the safety of a clinical simulation. Learning was facilitated through network communications and reflection on video performances of self and others. Evaluations were positive, students demonstrating increased satisfaction with PBL, improved performance in exams, and increased self-efficacy in the performance of nursing activities. These results indicate that eLearning techniques can help students acquire clinical skills in the safety of a simulated environment within the context of a problem based learning curriculum.

Psychosocial Working Conditions and Cognitive Complaints among Swedish Employees

PubMed Central

Stenfors, Cecilia U. D.; Magnusson Hanson, Linda; Oxenstierna, Gabriel; Theorell, Töres; Nilsson, Lars-Göran

2013-01-01

Background Cognitive complaints involving problems with concentration, memory, decision-making and thinking are relatively common in the work force. The sensitivity of both subjective and objective cognitive functioning to common psychiatric conditions, stress levels and to cognitive load makes it plausible that psychosocial working conditions play a role in cognitive complaints. Thus, this study aimed to test the associations between psychosocial work factors and cognitive complaints in nationally representative samples of the Swedish work force. Cross-sectional (n = 9751) and prospective (n = 3644; two time points two years apart) sequential multiple regression analyses were run, adjusting for general confounders, depressive- and sleeping problems. Additional prospective analyses were run adjusting for baseline cognitive complaints. Cross-sectional results High quantitative demands, information and communication technology (ICT) demands, underqualification and conflicts were positively associated with cognitive complaints, while social support, good resources at work and overqualification were negatively associated with cognitive complaints in all models. Skill discretion and decision authority were weakly associated with cognitive complaints. Conflicts were more strongly associated with cognitive complaints in women than in men, after adjustment for general confounders. Prospective results Quantitative job demands, ICT demands and underqualification were positively associated with future cognitive complaints in all models, including when adjusted for baseline cognitive complaints. Decision authority was weakly positively associated with future cognitive complaints, only after adjustment for depressive- and sleeping problems respectively. Social support was negatively associated with future cognitive complaints after adjustment for general confounders and baseline cognitive complaints. Skill discretion and resources were negatively associated with future cognitive complaints after adjustment for general confounders. The associations between quantitative demands and future cognitive complaints were stronger in women. Discussion/Conclusions The findings indicate that psychosocial working conditions should be taken into account when considering cognitive complaints among employees. PMID:23560101

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

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

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

Estimating the potential water reuse based on fuzzy reasoning.

PubMed

Almeida, Giovana; Vieira, José; Marques, Alfeu Sá; Kiperstok, Asher; Cardoso, Alberto

2013-10-15

Studies worldwide suggest that the risk of water shortage in regions affected by climate change is growing. Decision support tools can help governments to identify future water supply problems in order to plan mitigation measures. Treated wastewater is considered a suitable alternative water resource and it is used for non-potable applications in many dry regions around the world. This work describes a decision support system (DSS) that was developed to identify current water reuse potential and the variables that determine the reclamation level. The DSS uses fuzzy inference system (FIS) as a tool and multi-criteria decision making is the conceptual approach behind the DSS. It was observed that water reuse level seems to be related to environmental factors such as drought, water exploitation index, water use, population density and the wastewater treatment rate, among others. A dataset was built to analyze these features through water reuse potential with a FIS that considered 155 regions and 183 cities. Despite some inexact fit between the classification and simulation data for agricultural and urban water reuse potential it was found that the FIS was suitable to identify the water reuse trend. Information on the water reuse potential is important because it issues a warning about future water supply needs based on climate change scenarios, which helps to support decision making with a view to tackling water shortage. Copyright © 2013 Elsevier Ltd. All rights reserved.

a Novel Approach to Support Majority Voting in Spatial Group Mcdm Using Density Induced Owa Operator for Seismic Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Moradi, M.; Delavar, M. R.; Moshiri, B.; Khamespanah, F.

2014-10-01

Being one of the most frightening disasters, earthquakes frequently cause huge damages to buildings, facilities and human beings. Although the prediction of characteristics of an earthquake seems to be impossible, its loss and damage is predictable in advance. Seismic loss estimation models tend to evaluate the extent to which the urban areas are vulnerable to earthquakes. Many factors contribute to the vulnerability of urban areas against earthquakes including age and height of buildings, the quality of the materials, the density of population and the location of flammable facilities. Therefore, seismic vulnerability assessment is a multi-criteria problem. A number of multi criteria decision making models have been proposed based on a single expert. The main objective of this paper is to propose a model which facilitates group multi criteria decision making based on the concept of majority voting. The main idea of majority voting is providing a computational tool to measure the degree to which different experts support each other's opinions and make a decision regarding this measure. The applicability of this model is examined in Tehran metropolitan area which is located in a seismically active region. The results indicate that neglecting the experts which get lower degrees of support from others enables the decision makers to avoid the extreme strategies. Moreover, a computational method is proposed to calculate the degree of optimism in the experts' opinions.

Optimization of Operations Resources via Discrete Event Simulation Modeling

NASA Technical Reports Server (NTRS)

Joshi, B.; Morris, D.; White, N.; Unal, R.

1996-01-01

The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.

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.

Economics of Obesity — Learning from the Past to Contribute to a Better Future

PubMed Central

Ananthapavan, Jaithri; Sacks, Gary; Moodie, Marj; Carter, Rob

2014-01-01

The discipline of economics plays a varied role in informing the understanding of the problem of obesity and the impact of different interventions aimed at addressing it. This paper discusses the causes of the obesity epidemic from an economics perspective, and outlines various justifications for government intervention in this area. The paper then focuses on the potential contribution of health economics in supporting resource allocation decision making for obesity prevention/treatment. Although economic evaluations of single interventions provide useful information, evaluations undertaken as part of a priority setting exercise provide the greatest scope for influencing decision making. A review of several priority setting examples in obesity prevention/treatment indicates that policy (as compared with program-based) interventions, targeted at prevention (as compared with treatment) and focused “upstream” on the food environment, are likely to be the most cost-effective options for change. However, in order to further support decision makers, several methodological advances are required. These include the incorporation of intervention costs/benefits outside the health sector, the addressing of equity impacts, and the increased engagement of decision makers in the priority setting process. PMID:24736685

Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

NASA Astrophysics Data System (ADS)

Subagadis, Y. H.; Schütze, N.; Grundmann, J.

2014-09-01

The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Evidence Based Medicine and Shared Decision Making: the challenge of getting both evidence and preferences into health care.

PubMed

Barratt, Alexandra

2008-12-01

Evidence Based Medicine (EBM) and Shared Medical Decision Making (SDM) are changing the nature of health care decisions. It is broadly accepted that health care decisions require the integration of research evidence and individual preferences. These approaches are justified on both efficacy grounds (that evidence based practice and Shared Decision Making should lead to better health outcomes and may lead to a more cost-effective use of health care resources) and ethical grounds (patients' autonomy should be respected in health care). However, despite endorsement by physicians and consumers of these approaches, implementation remains limited in practice, particularly outside academic and tertiary health care centres. There are practical problems of implementation, which include training, access to research, and development of and access to tools to display evidence and support decision making. There may also be philosophical difficulties, and some have even suggested that the two approaches (evidence based practice and Shared Decision Making) are fundamentally incompatible. This paper look at the achievements of EBM and SDM so far, the potential tensions between them, and how things might progress in the future.

Strategies in Forecasting Outcomes in Ethical Decision-making: Identifying and Analyzing the Causes of the Problem

PubMed Central

Beeler, Cheryl K.; Antes, Alison L.; Wang, Xiaoqian; Caughron, Jared J.; Thiel, Chase E.; Mumford, Michael D.

2010-01-01

This study examined the role of key causal analysis strategies in forecasting and ethical decision-making. Undergraduate participants took on the role of the key actor in several ethical problems and were asked to identify and analyze the causes, forecast potential outcomes, and make a decision about each problem. Time pressure and analytic mindset were manipulated while participants worked through these problems. The results indicated that forecast quality was associated with decision ethicality, and the identification of the critical causes of the problem was associated with both higher quality forecasts and higher ethicality of decisions. Neither time pressure nor analytic mindset impacted forecasts or ethicality of decisions. Theoretical and practical implications of these findings are discussed. PMID:20352056

A proposal for the development of national certification standards for patient decision aids in the US.

PubMed

Elwyn, Glyn; Burstin, Helen; Barry, Michael J; Corry, Maureen P; Durand, Marie Anne; Lessler, Daniel; Saigal, Christopher

2018-04-27

Efforts to implement the use of patient decision aids to stimulate shared decision making are gaining prominence. Patient decision aids have been designed to help patients participate in making specific choices among health care options. Because these tools clearly influence decisions, poor quality, inaccurate or unbalanced presentations or misleading tools are a risk to patients. As payer interest in these tools increases, so does the risk that patients are harmed by the use of tools that are described as patient decision aids yet fail to meet established standards. To address this problem, the National Quality Forum (NQF) in the USA convened a multi-stakeholder expert panel in 2016 to propose national standards for a patient decision aid certification process. In 2017, NQF established an Action Team to foster shared decision making, and to call for a national certification process as one recommendation among others to stimulate improvement. A persistent barrier to the setup of a national patient decision aids certification process is the lack of a sustainable financial model to support the work. Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.

Strategic and non-strategic problem gamblers differ on decision-making under risk and ambiguity.

PubMed

Lorains, Felicity K; Dowling, Nicki A; Enticott, Peter G; Bradshaw, John L; Trueblood, Jennifer S; Stout, Julie C

2014-07-01

To analyse problem gamblers' decision-making under conditions of risk and ambiguity, investigate underlying psychological factors associated with their choice behaviour and examine whether decision-making differed in strategic (e.g., sports betting) and non-strategic (e.g., electronic gaming machine) problem gamblers. Cross-sectional study. Out-patient treatment centres and university testing facilities in Victoria, Australia. Thirty-nine problem gamblers and 41 age, gender and estimated IQ-matched controls. Decision-making tasks included the Iowa Gambling Task (IGT) and a loss aversion task. The Prospect Valence Learning (PVL) model was used to provide an explanation of cognitive, motivational and response style factors involved in IGT performance. Overall, problem gamblers performed more poorly than controls on both the IGT (P = 0.04) and the loss aversion task (P = 0.01), and their IGT decisions were associated with heightened attention to gains (P = 0.003) and less consistency (P = 0.002). Strategic problem gamblers did not differ from matched controls on either decision-making task, but non-strategic problem gamblers performed worse on both the IGT (P = 0.006) and the loss aversion task (P = 0.02). Furthermore, we found differences in the PVL model parameters underlying strategic and non-strategic problem gamblers' choices on the IGT. Problem gamblers demonstrated poor decision-making under conditions of risk and ambiguity. Strategic (e.g. sports betting, poker) and non-strategic (e.g. electronic gaming machines) problem gamblers differed in decision-making and the underlying psychological processes associated with their decisions. © 2014 Society for the Study of Addiction.

Negotiation and Decision Making with Collaborative Software: How MarineMap 'Changed the Game' in California's Marine Life Protected Act Initiative.

PubMed

Cravens, Amanda E

2016-02-01

Environmental managers and planners have become increasingly enthusiastic about the potential of decision support tools (DSTs) to improve environmental decision-making processes as information technology transforms many aspects of daily life. Discussions about DSTs, however, rarely recognize the range of ways software can influence users' negotiation, problem-solving, or decision-making strategies and incentives, in part because there are few empirical studies of completed processes that used technology. This mixed-methods study-which draws on data from approximately 60 semi-structured interviews and an online survey--examines how one geospatial DST influenced participants' experiences during a multi-year marine planning process in California. Results suggest that DSTs can facilitate communication by creating a common language, help users understand the geography and scientific criteria in play during the process, aid stakeholders in identifying shared or diverging interests, and facilitate joint problem solving. The same design features that enabled the tool to aid in decision making, however, also presented surprising challenges in certain circumstances by, for example, making it difficult for participants to discuss information that was not spatially represented on the map-based interface. The study also highlights the importance of the social context in which software is developed and implemented, suggesting that the relationship between the software development team and other participants may be as important as technical software design in shaping how DSTs add value. The paper concludes with considerations to inform the future use of DSTs in environmental decision-making processes.

Negotiation and Decision Making with Collaborative Software: How MarineMap `Changed the Game' in California's Marine Life Protected Act Initiative

NASA Astrophysics Data System (ADS)

Cravens, Amanda E.

2016-02-01

Environmental managers and planners have become increasingly enthusiastic about the potential of decision support tools (DSTs) to improve environmental decision-making processes as information technology transforms many aspects of daily life. Discussions about DSTs, however, rarely recognize the range of ways software can influence users' negotiation, problem-solving, or decision-making strategies and incentives, in part because there are few empirical studies of completed processes that used technology. This mixed-methods study—which draws on data from approximately 60 semi-structured interviews and an online survey—examines how one geospatial DST influenced participants' experiences during a multi-year marine planning process in California. Results suggest that DSTs can facilitate communication by creating a common language, help users understand the geography and scientific criteria in play during the process, aid stakeholders in identifying shared or diverging interests, and facilitate joint problem solving. The same design features that enabled the tool to aid in decision making, however, also presented surprising challenges in certain circumstances by, for example, making it difficult for participants to discuss information that was not spatially represented on the map-based interface. The study also highlights the importance of the social context in which software is developed and implemented, suggesting that the relationship between the software development team and other participants may be as important as technical software design in shaping how DSTs add value. The paper concludes with considerations to inform the future use of DSTs in environmental decision-making processes.

Designing for Decision Making

ERIC Educational Resources Information Center

Jonassen, David H.

2012-01-01

Decision making is the most common kind of problem solving. It is also an important component skill in other more ill-structured and complex kinds of problem solving, including policy problems and design problems. There are different kinds of decisions, including choices, acceptances, evaluations, and constructions. After describing the centrality…

A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Lund, Jay R.

2011-05-01

Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

Study on the key technology of grain logistics tracking system

NASA Astrophysics Data System (ADS)

Zhen, Tong; Ge, Hongyi; Jiang, Yuying; Che, Yi

2010-07-01

In recent year, with the rapid development of GIS technology, more and more programming problems depend on the GIS technology and professional model system. The solution of auxiliary programming problem by using GIS technology, which has become very popular. GIS is an important tool and technology, that captures, stores, analyzes, manages, and presents data that are linked to location. A grain logistics distribution system based on GIS is established, which provides a visualization scheme during the process of grain circulation and supports users making decision and analyzing for grain logistics enterprise.

A comparison of students who chose a traditional or a problem-based learning curriculum after failing year 2 in the traditional curriculum: a unique case study at the Nelson R. Mandela School of Medicine.

PubMed

McLean, Michelle

2004-01-01

To canvas perceptions and experiences of students who had failed Year 2 of a traditional medical program and who chose to remain in the conventional program (n = 6) or had swapped to Curriculum 2001 (C2001), a problem-based learning (PBL) curriculum (n = 14). A year after their decision regarding curriculum choice, students were canvassed (largely open-ended survey) about this decision and about their perceptions of their curricular experiences. C2001 students were positive about their PBL experiences. Overwhelmingly, their decision to swap streams had been a good one. They identified PBL features as supporting their learning. Repeating traditional curriculum students were, however, more circumspect in their opinions. C2001 students had clearly embraced PBL. They were now medical students, largely because of PBL activities underpinned by a sound educational philosophy. This unique case study has provided additional evidence that PBL students are generally more content with their studies than their conventional curriculum counterparts.

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.

Are insurance companies liable under the Americans with Disabilities Act?

PubMed

Manning, J S

2000-03-01

Federal courts have split on the question of the applicability of the Americans with Disabilities Act to insurance coverage decisions that insurance companies make on the basis of disability; they have similarly split on other issues pertaining to the scope of that Act's application. In deciding whether to read the Act as prohibiting discrimination in insurance decisions that are often crucial in the lives of people with disabilities, courts have faced two problems. First, where it prohibits discrimination in the equal enjoyment of the goods and services of places of public accommodation, the Act's area of concern may be limited to the ability of people with disabilities to gain physical access to facilities; or that area may extend to all forms of disability-based discrimination in the provision of goods and services. This Comment argues that the language and legislative history of the Act are consistent only with the latter view. Second, the provision limiting the Act's applicability to insurance may create an exemption for all insurance decisions; or it may protect only the ability of an insurance company to make an insurance decision to the disadvantage of an insured with a disability where actuarial data support the decision. This comment argues that the ambiguous language of the limiting provision should be resolved in favor of the latter view. Legislative history and the broader background of the history of insurance discrimination law support this resolution. Consequently, the Act should be interpreted as prohibiting disability-based discrimination by insurance companies in selling insurance policies and as defining discrimination as making disability-based insurance decisions without the support of actuarial data. By accepting this interpretation, courts can help stop the pattern of judicial narrowing of the Act's application through inappropriately restrictive statutory construction.

The Role of Ethics Committees and Ethics Consultation in Allocation Decisions

PubMed Central

Strech, Daniel; Hurst, Samia; Danis, Marion

2013-01-01

Background Decisions about the allocation and rationing of medical interventions likely occur in all health care systems worldwide. So far very little attention has been given to the question of what role ethics consultation and ethics committees could or should play in questions of allocation at the hospital level. Objectives and Methods This article argues for the need for ethics consultation in rationing decisions using empirical data about the status quo and the inherent nature of bedside rationing. Subsequently, it introduces a 4-stage process for establishing and conducting ethics consultation in rationing questions with systematic reference to core elements of procedural justice. Results Qualitative and quantitative findings show a significant demand for ethics consultation expressed directly by doctors, as well as additional indirect evidence of such a need as indicated by ethically challenging circumstances of inconsistent and structurally disadvantaging rationing decisions. To address this need, we suggest 4 stages for establishing and conducting ethics consultation in rationing questions we recommend: (1) training, (2) identifying actual scarcity-related problems at clinics, (3) supporting decision-making, and (4) evaluation. Conclusion This process of ethics consultation regarding rationing decisions would facilitate the achievement of several practical goals: (i) encouragement of an awareness and understanding of ethical problems in bedside rationing, (ii) encouragement of achieving efficiency along with rationing, (iii) reinforcement of consistency in inter- and intraindvidual decision-making, (iv) encouragement of explicit reflection and justification of the prioritization criteria taken into consideration, (v) improvement in internal (in-house) and external transparency, and (vi) prevention of the misuse of the corresponding consulting structures. PMID:20706163

Overcoming barriers to cancer-helpline professionals providing decision support for callers: an implementation study.

PubMed

Stacey, Dawn; Chambers, Suzanne K; Jacobsen, Mary Jane; Dunn, Jeff

2008-11-01

To evaluate the effect of an intervention on healthcare professionals' perceptions of barriers influencing their provision of decision support for callers facing cancer-related decisions. A pre- and post-test study guided by the Ottawa Model of Research Use. Australian statewide cancer call center that provides public access to information and supportive cancer services. 34 nurses, psychologists, and other allied healthcare professionals at the cancer call center. Participants completed baseline measures and, subsequently, were exposed to an intervention that included a decision support tutorial, coaching protocol, and skill-building workshop. Strategies were implemented to address organizational barriers. Perceived barriers and facilitators influencing provision of decision support, decision support knowledge, quality of decision support provided to standardized callers, and call length. Postintervention participants felt more prepared, confident in providing decision support, and aware of decision support resources. They had a stronger belief that providing decision support was within their role. Participants significantly improved their knowledge and provided higher-quality decision support to standardized callers without changing call length. The implementation intervention overcame several identified barriers that influenced call center professionals when providing decision support. Nurses and other helpline professionals have the potential to provide decision support designed to help callers understand cancer information, clarify their values associated with their options, and reduce decisional conflict. However, they require targeted education and organizational interventions to reduce their perceived barriers to providing decision support.

A Tentative Organizational Schema for Decision-Making Problems.

ERIC Educational Resources Information Center

Osborn, William C.; Goodman, Barbara Ettinger

This report presents the results of research that examined widely diverse decision problems and attempted to specify their common behavior elements. To take into account the psychological complexity of most real-life decision problems, and to develop a tentative organization of decision behavior that will embrace the many, highly diverse types of…

Generation of Look-Up Tables for Dynamic Job Shop Scheduling Decision Support Tool

NASA Astrophysics Data System (ADS)

Oktaviandri, Muchamad; Hassan, Adnan; Mohd Shaharoun, Awaluddin

2016-02-01

Majority of existing scheduling techniques are based on static demand and deterministic processing time, while most job shop scheduling problem are concerned with dynamic demand and stochastic processing time. As a consequence, the solutions obtained from the traditional scheduling technique are ineffective wherever changes occur to the system. Therefore, this research intends to develop a decision support tool (DST) based on promising artificial intelligent that is able to accommodate the dynamics that regularly occur in job shop scheduling problem. The DST was designed through three phases, i.e. (i) the look-up table generation, (ii) inverse model development and (iii) integration of DST components. This paper reports the generation of look-up tables for various scenarios as a part in development of the DST. A discrete event simulation model was used to compare the performance among SPT, EDD, FCFS, S/OPN and Slack rules; the best performances measures (mean flow time, mean tardiness and mean lateness) and the job order requirement (inter-arrival time, due dates tightness and setup time ratio) which were compiled into look-up tables. The well-known 6/6/J/Cmax Problem from Muth and Thompson (1963) was used as a case study. In the future, the performance measure of various scheduling scenarios and the job order requirement will be mapped using ANN inverse model.

Information System Engineering Supporting Observation, Orientation, Decision, and Compliant Action

NASA Astrophysics Data System (ADS)

Georgakopoulos, Dimitrios

The majority of today's software systems and organizational/business structures have been built on the foundation of solving problems via long-term data collection, analysis, and solution design. This traditional approach of solving problems and building corresponding software systems and business processes, falls short in providing the necessary solutions needed to deal with many problems that require agility as the main ingredient of their solution. For example, such agility is needed in responding to an emergency, in military command control, physical security, price-based competition in business, investing in the stock market, video gaming, network monitoring and self-healing, diagnosis in emergency health care, and many other areas that are too numerous to list here. The concept of Observe, Orient, Decide, and Act (OODA) loops is a guiding principal that captures the fundamental issues and approach for engineering information systems that deal with many of these problem areas. However, there are currently few software systems that are capable of supporting OODA. In this talk, we provide a tour of the research issues and state of the art solutions for supporting OODA. In addition, we provide specific examples of OODA solutions we have developed for the video surveillance and emergency response domains.

Selection criteria and facilitation training for the study of groupware

NASA Technical Reports Server (NTRS)

Robichaux, Barry P.

1993-01-01

Computer support for planning and decision making groups is a growing trend in the 90s. Groupware is a name often applied to group software and has been defined as 'computer-based systems that support groups engaged in a common task (or goal) and that provide an interface to a shared environment'. Unlike most single-user software, groupware assists user groups in their collaboration, coordination, and communication efforts. This paper focuses on groupware to support the meeting process. These systems are often called group decision support systems (GDSS), electronic meeting systems (EMS), or group support systems (GSS). The term 'meeting support groupware' is used here to include any computer-based system to support meetings. In order to understand this technology, one must first understand groups, what they do and the problems they face, and groupware, a wide range of technology to support group work. Guidelines for selecting groups for study as part of an overall research plan are provided in this document. These were taken from the literature and from persons for whom the information in this paper was targeted. Also, guidelines for facilitation training are discussed. Familiarity with known and accepted techniques are the principle duties of the facilitator and any form of training must include practice in using these techniques.

Training conservation practitioners to be better decision makers

USGS Publications Warehouse

Johnson, Fred A.; Eaton, Mitchell J.; Williams, James H.; Jensen, Gitte H.; Madsen, Jesper

2015-01-01

Traditional conservation curricula and training typically emphasizes only one part of systematic decision making (i.e., the science), at the expense of preparing conservation practitioners with critical skills in values-setting, working with decision makers and stakeholders, and effective problem framing. In this article we describe how the application of decision science is relevant to conservation problems and suggest how current and future conservation practitioners can be trained to be better decision makers. Though decision-analytic approaches vary considerably, they all involve: (1) properly formulating the decision problem; (2) specifying feasible alternative actions; and (3) selecting criteria for evaluating potential outcomes. Two approaches are available for providing training in decision science, with each serving different needs. Formal education is useful for providing simple, well-defined problems that allow demonstrations of the structure, axioms and general characteristics of a decision-analytic approach. In contrast, practical training can offer complex, realistic decision problems requiring more careful structuring and analysis than those used for formal training purposes. Ultimately, the kinds and degree of training necessary depend on the role conservation practitioners play in a decision-making process. Those attempting to facilitate decision-making processes will need advanced training in both technical aspects of decision science and in facilitation techniques, as well as opportunities to apprentice under decision analysts/consultants. Our primary goal should be an attempt to ingrain a discipline for applying clarity of thought to all decisions.

A web based spatial decision supporting system for land management and soil conservation

NASA Astrophysics Data System (ADS)

Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.

2015-02-01

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) but also many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a Spatial Decision Support System based on geospatial cyber-infrastructure (GCI) can embody all of the above, so producing a smart system for supporting decision making for agriculture, forestry and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on soil and land conservation (SOILCONSWEB-LIFE+ project). The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry and urban planning issues through the web. The system has been applied to and tested in an area of about 20 000 ha in the South of Italy, within the framework of a European LIFE+ project. The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart web based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (http://www.landconsultingweb.eu). This may help bridge the last much important divide between scientists working on the landscape and end users.

A Web-based spatial decision supporting system for land management and soil conservation

NASA Astrophysics Data System (ADS)

Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.

2015-07-01

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) as well as many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a spatial decision support system based on geospatial cyberinfrastructure (GCI) can address all of the above, so producing a smart system for supporting decision making for agriculture, forestry, and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on land management and soil conservation. The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry, and urban planning issues through the Web. The system has been applied to and tested in an area of about 20 000 ha in the south of Italy, within the framework of a European LIFE+ project (SOILCONSWEB). The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart Web-based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (www.landconsultingweb.eu). This may help bridge the last very important divide between scientists working on the landscape and end users.

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.

Cost-effectiveness analysis and formulary decision making in England: findings from research.

PubMed

Williams, Iestyn P; Bryan, Stirling

2007-11-01

In a context of rapid technological advances in health care and increasing demand for expensive treatments, local formulary committees are key players in the management of scarce resources. However, little is known about the information and processes used when making decisions on the inclusion of new treatments. This paper reports research on the use of economic evaluations in technology coverage decisions in England, although the findings have a relevance to other health care systems with devolved responsibility for resource allocation. It reports a study of four local formulary committees in which both qualitative and quantitative data were collected. Our main research finding is that it is an exception for cost-effectiveness analysis to inform technology coverage decisions. Barriers to use include access and expertise levels, concerns relating to the independence of analyses and problems with implementation of study recommendations. Further barriers derive from the constraints on decision makers, a lack of clarity over functions and aims of local committees, and the challenge of disinvestment in medical technologies. The relative weakness of the research-practice dynamics in this context suggests the need for a rethinking of the role of both analysts and decision makers. Our research supports the view that in order to be useful, analysis needs to better reflect the constraints of the local decision-making environment. We also recommend that local decision-making committees and bodies in the National Health Service more clearly identify the 'problems' which they are charged with solving and how their outputs contribute to broader finance and commissioning functions. This would help to establish the ways in which the routine use of cost-effectiveness analysis might become a reality.

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.

[A study on participation in clinical decision making by home healthcare nurses].

PubMed

Kim, Se Young

2010-12-01

This study was done to identify participation by home healthcare nurses in clinical decision making and factors influencing clinical decision making. A descriptive survey was used to collect data from 68 home healthcare nurses in 22 hospital-based home healthcare services in Korea. To investigate participation, the researcher developed 3 scenarios through interviews with 5 home healthcare nurses. A self-report questionnaire composed of tools for characteristics, factors of clinical decision making, and participation was used. Participation was relatively high, but significantly lower in the design phase (F=3.51, p=.032). Competency in clinical decision making (r=.45, p<.001), perception of the decision maker role (r=.47, p<.001), and perception of the utility of clinical practice guidelines (r=.25, p=.043) were significantly correlated with participation. Competency in clinical decision making (Odds ratio [OR]=41.79, p=.007) and perception of the decision maker role (OR=15.09, p=.007) were significant factors predicting participation in clinical decision making by home healthcare nurses. In order to encourage participation in clinical decision making, education programs should be provided to home healthcare nurses. Official clinical practice guidelines should be used to support home healthcare nurses' participation in clinical decision making in cases where they can identify and solve the patient health problems.

Enhancing User Customization through Novel Software Architecture for Utility Scale Solar Siting Software

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

Brant Peery; Sam Alessi; Randy Lee

2014-06-01

There is a need for a spatial decision support application that allows users to create customized metrics for comparing proposed locations of a new solar installation. This document discusses how PVMapper was designed to overcome the customization problem through the development of loosely coupled spatial and decision components in a JavaScript plugin architecture. This allows the user to easily add functionality and data to the system. The paper also explains how PVMapper provides the user with a dynamic and customizable decision tool that enables them to visually modify the formulas that are used in the decision algorithms that convert datamore » to comparable metrics. The technologies that make up the presentation and calculation software stack are outlined. This document also explains the architecture that allows the tool to grow through custom plugins created by the software users. Some discussion is given on the difficulties encountered while designing the system.« less

Goal-oriented Site Characterization in Hydrogeological Applications: An Overview

NASA Astrophysics Data System (ADS)

Nowak, W.; de Barros, F.; Rubin, Y.

2011-12-01

In this study, we address the importance of goal-oriented site characterization. Given the multiple sources of uncertainty in hydrogeological applications, information needs of modeling, prediction and decision support should be satisfied with efficient and rational field campaigns. In this work, we provide an overview of an optimal sampling design framework based on Bayesian decision theory, statistical parameter inference and Bayesian model averaging. It optimizes the field sampling campaign around decisions on environmental performance metrics (e.g., risk, arrival times, etc.) while accounting for parametric and model uncertainty in the geostatistical characterization, in forcing terms, and measurement error. The appealing aspects of the framework lie on its goal-oriented character and that it is directly linked to the confidence in a specified decision. We illustrate how these concepts could be applied in a human health risk problem where uncertainty from both hydrogeological and health parameters are accounted.

Thinking Fast Increases Framing Effects in Risky Decision Making.

PubMed

Guo, Lisa; Trueblood, Jennifer S; Diederich, Adele

2017-04-01

Every day, people face snap decisions when time is a limiting factor. In addition, the way a problem is presented can influence people's choices, which creates what are known as framing effects. In this research, we explored how time pressure interacts with framing effects in risky decision making. Specifically, does time pressure strengthen or weaken framing effects? On one hand, research has suggested that framing effects evolve through the deliberation process, growing larger with time. On the other hand, dual-process theory attributes framing effects to an intuitive, emotional system that responds automatically to stimuli. In our experiments, participants made decisions about gambles framed in terms of either gains or losses, and time pressure was manipulated across blocks. Results showed increased framing effects under time pressure in both hypothetical and incentivized choices, which supports the dual-process hypothesis that these effects arise from a fast, intuitive system.

The Case for Using Personally Relevant and Emotionally Stimulating Gambling Messages as a Gambling Harm-Minimisation Strategy.

PubMed

Harris, Andrew; Parke, Adrian; Griffiths, Mark D

2018-01-01

Emotions typically exert powerful, enduring, and often predictable influences over decision-making. However, emotion-based decision-making is seen as a mediator of impulsive and reckless gambling behaviour, where emotion may be seen as the antithesis of controlled and rational decision-making, a proposition supported by recent neuroimaging evidence. The present paper argues that the same emotional mechanisms can be used to influence a gambler to cease gambling, by focusing their emotional decision-making on positive external and personally relevant factors, such as familial impact or longer term financial factors. Emotionally stimulating messages may also have the advantage of capturing attention above and beyond traditionally responsible gambling messaging. This is important given the highly emotionally aroused states often experienced by both gamblers and problem gamblers, where attentional activation thresholds for external stimuli such as messages may be increased.

Clarification process: Resolution of decision-problem conditions

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

A model of a general process which occurs in both decisionmaking and problem-solving tasks is presented. It is called the clarification model and is highly dependent on information flow. The model addresses the possible constraints of individual indifferences and experience in achieving success in resolving decision-problem conditions. As indicated, the application of the clarification process model is only necessary for certain classes of the basic decision-problem condition. With less complex decision problem conditions, certain phases of the model may be omitted. The model may be applied across a wide range of decision problem conditions. The model consists of two major components: (1) the five-phase prescriptive sequence (based on previous approaches to both concepts) and (2) the information manipulation function (which draws upon current ideas in the areas of information processing, computer programming, memory, and thinking). The two components are linked together to provide a structure that assists in understanding the process of resolving problems and making decisions.

Decisions to Attend and Drink at Party Events: The Effects of Incentives and Disincentives and Lifetime Alcohol and Antisocial Problems.

PubMed

Finn, Peter R; Gerst, Kyle; Lake, Allison; Bogg, Tim

2017-09-01

Alcohol use disorders are associated with patterns of impulsive/risky decision making on behavioral economic decision tasks, but little is known about the factors affecting drinking-related decisions. The effects of incentives and disincentives to attend and drink at hypothetical alcohol-related party events as a function of lifetime (LT) alcohol and antisocial problems were examined in a sample of 434 young adults who varied widely in LT alcohol and antisocial problems. Moderate and high disincentives substantially discouraged decisions to attend the party events and were associated with decisions to drink less at the party events. High versus low party incentives were associated with more attendance decisions. LT antisocial problems were associated with being less deterred from attending by moderate and high disincentives. LT alcohol problems were associated with greater attendance at high party incentive contexts. LT alcohol problems were associated with drinking more at the majority of events; however, the results indicate that young adults with high levels of alcohol problems moderate their drinking in response to moderate and high disincentives. Finally, attendance and drinking decisions on this hypothetical task were significantly related to actual drinking practices. The results suggest that antisocial symptoms are associated with a reduced sensitivity to the potential negative consequences of drinking, while alcohol problems are associated with a greater sensitivity to the rewarding aspects of partying. The results also underline the value of directly assessing drinking-related decisions in different hypothetical contexts as well as assessing decisions about attendance at risky drinking events in addition to drinking amount decisions. Copyright © 2017 by the Research Society on Alcoholism.

Managing risk during care transitions when approaching end of life: A qualitative study of patients' and health care professionals' decision making.

PubMed

Coombs, Maureen A; Parker, Roses; de Vries, Kay

2017-07-01

Increasing importance is being placed on the coordination of services at the end of life. To describe decision-making processes that influence transitions in care when approaching the end of life. Qualitative study using field observations and longitudinal semi-structured interviews. Field observations were undertaken in three sites: a residential care home, a medical assessment unit and a general medical unit in New Zealand. The Supportive and Palliative Care Indicators Tool was used to identify participants with advanced and progressive illness. Patients and family members were interviewed on recruitment and 3-4 months later. Four weeks of fieldwork were conducted in each site. A total of 40 interviews were conducted: 29 initial interviews and 11 follow-up interviews. Thematic analysis was undertaken. Managing risk was an important factor that influenced transitions in care. Patients and health care staff held different perspectives on how such risks were managed. At home, patients tolerated increasing risk and used specific support measures to manage often escalating health and social problems. In contrast, decisions about discharge in hospital were driven by hospital staff who were risk-adverse. Availability of community and carer services supported risk management while a perceived need for early discharge decision making in hospital and making 'safe' discharge options informed hospital discharge decisions. While managing risk is an important factor during care transitions, patients should be able to make choices on how to live with risk at the end of life. This requires reconsideration of transitional care and current discharge planning processes at the end of life.

On decentralized design: Rationale, dynamics, and effects on decision-making

NASA Astrophysics Data System (ADS)

Chanron, Vincent

The focus of this dissertation is the design of complex systems, including engineering systems such as cars, airplanes, and satellites. Companies who design these systems are under constant pressure to design better products that meet customer expectations, and competition forces them to develop them faster. One of the responses of the industry to these conflicting challenges has been the decentralization of the design responsibilities. The current lack of understanding of the dynamics of decentralized design processes is the main motivation for this research, and places value on the descriptive base. It identifies the main reasons and the true benefits for companies to decentralize the design of their products. It also demonstrates the limitations of this approach by listing the relevant issues and problems created by the decentralization of decisions. Based on these observations, a game-theoretic approach to decentralized design is proposed to model the decisions made during the design process. The dynamics are modeled using mathematical formulations inspired from control theory. Building upon this formalism, the issue of convergence in decentralized design is analyzed: the equilibrium points of the design space are identified and convergent and divergent patterns are recognized. This rigorous investigation of the design process provides motivation and support for proposing new approaches to decentralized design problems. Two methods are developed, which aim at improving the design process in two ways: decreasing the product development time, and increasing the optimality of the final design. The frame of these methods are inspired by eigenstructure decomposition and set-based design, respectively. The value of the research detailed within this dissertation is in the proposed methods which are built upon the sound mathematical formalism developed. The contribution of this work is two fold: rigorous investigation of the design process, and practical support to decision-making in decentralized environments.

Integrated system dynamics toolbox for water resources planning.

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

Reno, Marissa Devan; Passell, Howard David; Malczynski, Leonard A.

2006-12-01

Public mediated resource planning is quickly becoming the norm rather than the exception. Unfortunately, supporting tools are lacking that interactively engage the public in the decision-making process and integrate over the myriad values that influence water policy. In the pages of this report we document the first steps toward developing a specialized decision framework to meet this need; specifically, a modular and generic resource-planning ''toolbox''. The technical challenge lies in the integration of the disparate systems of hydrology, ecology, climate, demographics, economics, policy and law, each of which influence the supply and demand for water. Specifically, these systems, their associatedmore » processes, and most importantly the constitutive relations that link them must be identified, abstracted, and quantified. For this reason, the toolbox forms a collection of process modules and constitutive relations that the analyst can ''swap'' in and out to model the physical and social systems unique to their problem. This toolbox with all of its modules is developed within the common computational platform of system dynamics linked to a Geographical Information System (GIS). Development of this resource-planning toolbox represents an important foundational element of the proposed interagency center for Computer Aided Dispute Resolution (CADRe). The Center's mission is to manage water conflict through the application of computer-aided collaborative decision-making methods. The Center will promote the use of decision-support technologies within collaborative stakeholder processes to help stakeholders find common ground and create mutually beneficial water management solutions. The Center will also serve to develop new methods and technologies to help federal, state and local water managers find innovative and balanced solutions to the nation's most vexing water problems. The toolbox is an important step toward achieving the technology development goals of this center.« less

Object-oriented design and programming in medical decision support.

PubMed

Heathfield, H; Armstrong, J; Kirkham, N

1991-12-01

The concept of object-oriented design and programming has recently received a great deal of attention from the software engineering community. This paper highlights the realisable benefits of using the object-oriented approach in the design and development of clinical decision support systems. These systems seek to build a computational model of some problem domain and therefore tend to be exploratory in nature. Conventional procedural design techniques do not support either the process of model building or rapid prototyping. The central concepts of the object-oriented paradigm are introduced, namely encapsulation, inheritance and polymorphism, and their use illustrated in a case study, taken from the domain of breast histopathology. In particular, the dual roles of inheritance in object-oriented programming are examined, i.e., inheritance as a conceptual modelling tool and inheritance as a code reuse mechanism. It is argued that the use of the former is not entirely intuitive and may be difficult to incorporate into the design process. However, inheritance as a means of optimising code reuse offers substantial technical benefits.

A System of Deception and Fraud Detection Using Reliable Linguistic Cues Including Hedging, Disfluencies, and Repeated Phrases

ERIC Educational Resources Information Center

Humpherys, Sean LaMarc

2010-01-01

Given the increasing problem of fraud, crime, and national security threats, assessing credibility is a recurring research topic in Information Systems and in other disciplines. Decision support systems can help. But the success of the system depends on reliable cues that can distinguish deceptive/truthful behavior and on a proven classification…

A Method for Increasing the Training Effectiveness of Marine Corps Tactical Exercises: A Pilot Study.

ERIC Educational Resources Information Center

Rocklyn, Eugene H.; And Others

Methods for better utilizing simulated combat systems for training officers are required by the Marine Corps to ensure efficient acquisition of combat decision-making skills. In support of this requirement, a review and analysis of several combat training systems helped to identify a set of major training problems. These included the small number…

M.E.T.R.O.-Apex Gaming Simulation, Volume 28 (OS/360 Version).

ERIC Educational Resources Information Center

Michigan Univ., Ann Arbor. Environmental Simulation Lab.

Operator's instructions and technical support materials needed for processing the M.E.T.R.O.-APEX (Air Pollution Exercise) game decisions on an IBM 360 computer are compiled in this volume. M.E.T.R.O.-APEX is a computerized college and professional level "real world" simulation of a community with urban and rural problems, industrial activities,…

Steps to Success: Helping Women with Alcohol and Drug Problems Move from Welfare to Work.

ERIC Educational Resources Information Center

Rubinstein, Gwen

This report helps state and local decision makers understand the range of services ordinarily needed and provided in alcohol and drug treatment programs serving women and families receiving welfare and how those services support the goals of welfare reform. The model programs profiled here tend to the needs of women on welfare and their families…

Using Simulation in a Vocational Programme: Does the Method Support the Theory?

ERIC Educational Resources Information Center

Rush, Sue; Acton, Lesley; Tolley, Kim; Marks-Maran, Di; Burke, Linda

2010-01-01

Use of simulation is well established as a way of learning and assessing skills in vocational disciplines. In many institutions the use of simulation with student nurses is being tested as a way of helping them learn clinical skills, problem-solving, clinical assessment and decision-making. This paper explores the value of simulation as a learning…

Optimal tactics for close support operations. III - Degraded intelligence and communications

NASA Astrophysics Data System (ADS)

Hess, J.; Kalaba, R.; Kagiwada, H.; Spingarn, K.; Tsokos, C.

1980-04-01

A new generation of C3 (command, control, and communication) models for military cybernetics is developed. Recursive equations for the solution of the C3 problem are derived for an amphibious campaign with linear time-varying dynamics. Air and ground commanders are assumed to have no intelligence and no communications. Numerical results are given for the optimal decision rules.

"Should We Kill the Grey Squirrels?" A Study Exploring Students' Justifications and Decision-Making

ERIC Educational Resources Information Center

Evagorou, Maria; Jimenez-Aleixandre, Maria Pilar; Osborne, Jonathan

2012-01-01

A problem that is still unexplored in the field of socioscientific issues (SSI) and that was explored in this study is how different students decide upon a SSI they are discussing, how their justifications change during the instruction and how they use (or not) the evidence from the learning environment to support their justifications. For the…

AMDIS Case Conference

PubMed Central

Graham, J.; Levick, D.; Schreiber, R.

2010-01-01

Clinical decision support that provides enhanced patient safety at the point of care frequently encounters significant pushback from clinicians who find the process intrusive or time-consuming. We present a hypothetical medical center’s dilemma about its allergy alerting system and discuss similar problems faced by real hospitals. We then share some lessons learned and best practices for institutions who wish to implement these tools themselves. PMID:23616828

The Use of Linear Models for Determining School Workload and Activity Level.

ERIC Educational Resources Information Center

Vicino, Frank L.

This paper outlines the design and use of two linear models as decision-making tools in a school district. The problem to be solved was the allocation of resources for both clerical and custodial personnel. A solution was desired that could be quantified and documented and objectively serve the needs of the district. A clerical support model was…

GWM-a ground-water management process for the U.S. Geological Survey modular ground-water model (MODFLOW-2000)

USGS Publications Warehouse

Ahlfeld, David P.; Barlow, Paul M.; Mulligan, Anne E.

2005-01-01

GWM is a Ground?Water Management Process for the U.S. Geological Survey modular three?dimensional ground?water model, MODFLOW?2000. GWM uses a response?matrix approach to solve several types of linear, nonlinear, and mixed?binary linear ground?water management formulations. Each management formulation consists of a set of decision variables, an objective function, and a set of constraints. Three types of decision variables are supported by GWM: flow?rate decision variables, which are withdrawal or injection rates at well sites; external decision variables, which are sources or sinks of water that are external to the flow model and do not directly affect the state variables of the simulated ground?water system (heads, streamflows, and so forth); and binary variables, which have values of 0 or 1 and are used to define the status of flow?rate or external decision variables. Flow?rate decision variables can represent wells that extend over one or more model cells and be active during one or more model stress periods; external variables also can be active during one or more stress periods. A single objective function is supported by GWM, which can be specified to either minimize or maximize the weighted sum of the three types of decision variables. Four types of constraints can be specified in a GWM formulation: upper and lower bounds on the flow?rate and external decision variables; linear summations of the three types of decision variables; hydraulic?head based constraints, including drawdowns, head differences, and head gradients; and streamflow and streamflow?depletion constraints. The Response Matrix Solution (RMS) Package of GWM uses the Ground?Water Flow Process of MODFLOW to calculate the change in head at each constraint location that results from a perturbation of a flow?rate variable; these changes are used to calculate the response coefficients. For linear management formulations, the resulting matrix of response coefficients is then combined with other components of the linear management formulation to form a complete linear formulation; the formulation is then solved by use of the simplex algorithm, which is incorporated into the RMS Package. Nonlinear formulations arise for simulated conditions that include water?table (unconfined) aquifers or head?dependent boundary conditions (such as streams, drains, or evapotranspiration from the water table). Nonlinear formulations are solved by sequential linear programming; that is, repeated linearization of the nonlinear features of the management problem. In this approach, response coefficients are recalculated for each iteration of the solution process. Mixed?binary linear (or mildly nonlinear) formulations are solved by use of the branch and bound algorithm, which is also incorporated into the RMS Package. Three sample problems are provided to demonstrate the use of GWM for typical ground?water flow management problems. These sample problems provide examples of how GWM input files are constructed to specify the decision variables, objective function, constraints, and solution process for a GWM run. The GWM Process runs with the MODFLOW?2000 Global and Ground?Water Flow Processes, but in its current form GWM cannot be used with the Observation, Sensitivity, Parameter?Estimation, or Ground?Water Transport Processes. The GWM Process is written with a modular structure so that new objective functions, constraint types, and solution algorithms can be added.

Acceptance and barriers pertaining to a general practice decision support system for multiple clinical conditions: A mixed methods evaluation.

PubMed

Arts, Derk L; Medlock, Stephanie K; van Weert, Henk C P M; Wyatt, Jeremy C; Abu-Hanna, Ameen

2018-01-01

Many studies have investigated the use of clinical decision support systems as a means to improve care, but have thus far failed to show significant effects on patient-related outcomes. We developed a clinical decision support system that attempted to address issues that were identified in these studies. The system was implemented in Dutch general practice and was designed to be both unobtrusive and to respond in real time. Despite our efforts, usage of the system was low. In the current study we perform a mixed methods evaluation to identify remediable barriers which led to disappointing usage rates for our system. A mixed methods evaluation employing an online questionnaire and focus group. The focus group was organized to clarify free text comments and receive more detailed feedback from general practitioners. Topics consisted of items based on results from the survey and additional open questions. The response rate for the questionnaire was 94%. Results from the questionnaire and focus group can be summarized as follows: The system was perceived as interruptive, despite its design. Participants felt that there were too many recommendations and that the relevance of the recommendations varied. Demographic based recommendations (e.g. age) were often irrelevant, while specific risk-based recommendations (e.g. diagnosis) were more relevant. The other main barrier to use was lack of time during the patient visit. These results are likely to be useful to other researchers who are attempting to address the problems of interruption and alert fatigue in decision support.

Clinic-Based Mobile Health Decision Support to Enhance Adult Epilepsy Self-Management: An Intervention Mapping Approach.

PubMed

Shegog, Ross; Begley, Charles E

2017-01-01

Epilepsy is a neurological disorder involving recurrent seizures. It affects approximately 5 million people in the U.S. To optimize their quality of life people with epilepsy are encouraged to engage in self-management (S-M) behaviors. These include managing their treatment (e.g., adhering to anti-seizure medication and clinical visit schedules), managing their seizures (e.g., responding to seizure episodes), managing their safety (e.g., monitoring and avoiding environmental seizure triggers), and managing their co-morbid conditions (e.g., anxiety, depression). The clinic-based Management Information Decision Support Epilepsy Tool (MINDSET) is a decision-support system founded on theory and empirical evidence. It is designed to increase awareness by adult patients (≥18 years) and their health-care provider regarding the patient's epilepsy S-M behaviors, facilitate communication during the clinic visit to prioritize S-M goals and strategies commensurate with the patient's needs, and increase the patient's self-efficacy to achieve those goals. The purpose of this paper is to describe the application of intervention mapping (IM) to develop, implement, and formatively evaluate the clinic-based MINDSET prototype and in developing implementation and evaluation plans. Deliverables comprised a logic model of the problem (IM Step 1); matrices of program objectives (IM Step 2); a program planning document comprising scope, sequence, theory-based methods, and practical strategies (IM Step 3); a functional MINDSET program prototype (IM Step 4); plans for implementation (IM Step 5); and evaluation (IM Step 6). IM provided a logical and systematic approach to developing and evaluating clinic-based decision support toward epilepsy S-M.

Information technology and social sciences: how can health IT be used to support the health professional?

PubMed

Wagner-Menghin, Michaela; Pokieser, Peter

2016-10-01

Keeping up to date with the increasing amount of health-related knowledge and managing the increasing numbers of patients with more complex clinical problems is a challenge for healthcare professionals and healthcare systems. Health IT applications, such as electronic health records or decision-support systems, are meant to support both professionals and their support systems. However, for physicians using these applications, the applications often cause new problems, such as the impracticality of their use in clinical practice. This review adopts a social sciences perspective to understand these problems and derive suggestions for further development. Indeed, humans use tools to remediate the brain's weaknesses and enhance thinking. Available health IT tools have been shaped to fit administrative needs rather than physicians' needs. To increase the beneficial effect of health IT applications in health care, clinicians' style of thinking and their learning needs must be considered when designing and implementing such systems. New health IT tools must be shaped to fit health professionals' needs. To further ease the integration of new health IT tools into clinical practice, we must also consider the effects of implementing new tools on the wider social framework. © 2016 New York Academy of Sciences.

Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

NASA Astrophysics Data System (ADS)

Jegadeeshwaran, R.; Sugumaran, V.

2015-02-01

Hydraulic brakes in automobiles are important components for the safety of passengers; therefore, the brakes are a good subject for condition monitoring. The condition of the brake components can be monitored by using the vibration characteristics. On-line condition monitoring by using machine learning approach is proposed in this paper as a possible solution to such problems. The vibration signals for both good as well as faulty conditions of brakes were acquired from a hydraulic brake test setup with the help of a piezoelectric transducer and a data acquisition system. Descriptive statistical features were extracted from the acquired vibration signals and the feature selection was carried out using the C4.5 decision tree algorithm. There is no specific method to find the right number of features required for classification for a given problem. Hence an extensive study is needed to find the optimum number of features. The effect of the number of features was also studied, by using the decision tree as well as Support Vector Machines (SVM). The selected features were classified using the C-SVM and Nu-SVM with different kernel functions. The results are discussed and the conclusion of the study is presented.

A duality theorem-based algorithm for inexact quadratic programming problems: Application to waste management under uncertainty

NASA Astrophysics Data System (ADS)

Kong, X. M.; Huang, G. H.; Fan, Y. R.; Li, Y. P.

2016-04-01

In this study, a duality theorem-based algorithm (DTA) for inexact quadratic programming (IQP) is developed for municipal solid waste (MSW) management under uncertainty. It improves upon the existing numerical solution method for IQP problems. The comparison between DTA and derivative algorithm (DAM) shows that the DTA method provides better solutions than DAM with lower computational complexity. It is not necessary to identify the uncertain relationship between the objective function and decision variables, which is required for the solution process of DAM. The developed method is applied to a case study of MSW management and planning. The results indicate that reasonable solutions have been generated for supporting long-term MSW management and planning. They could provide more information as well as enable managers to make better decisions to identify desired MSW management policies in association with minimized cost under uncertainty.

The complications of controlling agency time discretion: FDA review deadlines and postmarket drug safety.

PubMed

Carpenter, Daniel; Chattopadhyay, Jacqueline; Moffitt, Susan; Nall, Clayton

2012-01-01

Public agencies have discretion on the time domain, and politicians deploy numerous policy instruments to constrain it. Yet little is known about how administrative procedures that affect timing also affect the quality of agency decisions. We examine whether administrative deadlines shape decision timing and the observed quality of decisions. Using a unique and rich dataset of FDA drug approvals that allows us to examine decision timing and quality, we find that this administrative tool induces a piling of decisions before deadlines, and that these “just-before-deadline” approvals are linked with higher rates of postmarket safety problems (market withdrawals, severe safety warnings, safety alerts). Examination of data from FDA advisory committees suggests that the deadlines may impede quality by impairing late-stage deliberation and agency risk communication. Our results both support and challenge reigning theories about administrative procedures, suggesting they embody expected control-expertise trade-offs, but may also create unanticipated constituency losses.

Public health policy decisions on medical innovations: what role can early economic evaluation play?

PubMed

Hartz, Susanne; John, Jürgen

2009-02-01

Our contribution aims to explore the different ways in which early economic data can inform public health policy decisions on new medical technologies. A literature research was conducted to detect methodological contributions covering the health policy perspective. Early economic data on new technologies can support public health policy decisions in several ways. Embedded in horizon scanning and HTA activities, it adds to monitoring and assessment of innovations. It can play a role in the control of technology diffusion by informing coverage and reimbursement decisions as well as the direct public promotion of healthcare technologies, leading to increased efficiency. Major problems include the uncertainty related to economic data at early stages as well as the timing of the evaluation of an innovation. Decision-makers can benefit from the information supplied by early economic data, but the actual use in practice is difficult to determine. Further empirical evidence should be gathered, while the use could be promoted by further standardization.

Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers.

PubMed

Yu, Hualong; Hong, Shufang; Yang, Xibei; Ni, Jun; Dan, Yuanyuan; Qin, Bin

2013-01-01

DNA microarray technology can measure the activities of tens of thousands of genes simultaneously, which provides an efficient way to diagnose cancer at the molecular level. Although this strategy has attracted significant research attention, most studies neglect an important problem, namely, that most DNA microarray datasets are skewed, which causes traditional learning algorithms to produce inaccurate results. Some studies have considered this problem, yet they merely focus on binary-class problem. In this paper, we dealt with multiclass imbalanced classification problem, as encountered in cancer DNA microarray, by using ensemble learning. We utilized one-against-all coding strategy to transform multiclass to multiple binary classes, each of them carrying out feature subspace, which is an evolving version of random subspace that generates multiple diverse training subsets. Next, we introduced one of two different correction technologies, namely, decision threshold adjustment or random undersampling, into each training subset to alleviate the damage of class imbalance. Specifically, support vector machine was used as base classifier, and a novel voting rule called counter voting was presented for making a final decision. Experimental results on eight skewed multiclass cancer microarray datasets indicate that unlike many traditional classification approaches, our methods are insensitive to class imbalance.

Multicriteria analysis of ontologically represented information

NASA Astrophysics Data System (ADS)

Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

2014-11-01

Our current work concerns the development of a decision support system for the software selection problem. The main idea is to utilize expert knowledge to help the user in selecting the best software / method / computational resource to solve a computational problem. Obviously, this involves multicriterial decision making and the key open question is: which method to choose. The context of the work is provided by the Agents in Grid (AiG) project, where the software selection (and thus multicriterial analysis) is to be realized when all information concerning the problem, the hardware and the software is ontologically represented. Initially, we have considered the Analytical Hierarchy Process (AHP), which is well suited for the hierarchical data structures (e.g., such that have been formulated in terms of ontologies). However, due to its well-known shortcomings, we have decided to extend our search for the multicriterial analysis method best suited for the problem in question. In this paper we report results of our search, which involved: (i) TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), (ii) PROMETHEE, and (iii) GRIP (Generalized Regression with Intensities of Preference). We also briefly argue why other methods have not been considered as valuable candidates.

Development, deployment and usability of a point-of-care decision support system for chronic disease management using the recently-approved HL7 decision support service standard.

PubMed

Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight

2007-01-01

Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.

Analysis of the policymaking process in Burkina Faso's health sector: case studies of the creation of two health system support units.

PubMed

Zida, Andre; Lavis, John N; Sewankambo, Nelson K; Kouyate, Bocar; Moat, Kaelan; Shearer, Jessica

2017-02-13

Burkina Faso has made a number of health system policy decisions to improve performance on health indicators and strengthen responsiveness to health-related challenges. These included the creation of a General Directorate of Health Information and Statistics (DGISS) and a technical unit to coordinate performance-based financing (CT-FBR). We analysed the policymaking processes associated with the establishment of these units, and documented the factors that influenced this process. We used a multiple-case study design based on Kingdon's agenda-setting model to investigate the DGISS and CT-FBR policymaking processes. Data were collected from interviews with key informants (n = 28), published literature, policy documents (including two strategic and 230 action plans), and 55 legal/regulatory texts. Interviews were analysed using thematic qualitative analysis. Data from the documentary analysis were triangulated with the qualitative interview data. Key factors influencing the policymaking processes associated with the two units involved the 'problem' (problem identification), 'policy' (formation of policy proposals), and 'politics' (political climate/change) streams, which came together in a way that resulted in proposals being placed on the decision agenda. A number of problems with Burkina Faso's health information and financing systems were identified. Policy proposals for the DGISS and CT-FBR units were developed in response to these problems, emerging from several sources including development partners. Changes in political and public service administrations (specifically the 2008 appointment of a new Minister of Health and the establishment of a new budget allocation system), with corresponding changes in the actors and interests involved, appeared key in elevating the proposals to the decision agenda. Efforts to improve performance on health indicators and strengthen responsiveness to health-related challenges need focus on the need for a compelling problem, a viable policy, and conducive politics in order to make it to the decision agenda.

Helping the decision maker effectively promote various experts’ views into various optimal solutions to China’s institutional problem of health care provider selection through the organization of a pilot health care provider research system

PubMed Central

2013-01-01

Background The main aim of China’s Health Care System Reform was to help the decision maker find the optimal solution to China’s institutional problem of health care provider selection. A pilot health care provider research system was recently organized in China’s health care system, and it could efficiently collect the data for determining the optimal solution to China’s institutional problem of health care provider selection from various experts, then the purpose of this study was to apply the optimal implementation methodology to help the decision maker effectively promote various experts’ views into various optimal solutions to this problem under the support of this pilot system. Methods After the general framework of China’s institutional problem of health care provider selection was established, this study collaborated with the National Bureau of Statistics of China to commission a large-scale 2009 to 2010 national expert survey (n = 3,914) through the organization of a pilot health care provider research system for the first time in China, and the analytic network process (ANP) implementation methodology was adopted to analyze the dataset from this survey. Results The market-oriented health care provider approach was the optimal solution to China’s institutional problem of health care provider selection from the doctors’ point of view; the traditional government’s regulation-oriented health care provider approach was the optimal solution to China’s institutional problem of health care provider selection from the pharmacists’ point of view, the hospital administrators’ point of view, and the point of view of health officials in health administration departments; the public private partnership (PPP) approach was the optimal solution to China’s institutional problem of health care provider selection from the nurses’ point of view, the point of view of officials in medical insurance agencies, and the health care researchers’ point of view. Conclusions The data collected through a pilot health care provider research system in the 2009 to 2010 national expert survey could help the decision maker effectively promote various experts’ views into various optimal solutions to China’s institutional problem of health care provider selection. PMID:23557082

Decision-Making Styles and Problem-Solving Appraisal.

ERIC Educational Resources Information Center

Phillips, Susan D.; And Others

1984-01-01

Compared decision-making style and problem-solving appraisal in 243 undergraduates. Results suggested that individuals who employ rational decision-making strategies approach problematic situations, while individuals who endorse dependent decisional strategies approach problematic situations without confidence in their problem-solving abilities.…

Robust optimization modelling with applications to industry and environmental problems

NASA Astrophysics Data System (ADS)

Chaerani, Diah; Dewanto, Stanley P.; Lesmana, Eman

2017-10-01

Robust Optimization (RO) modeling is one of the existing methodology for handling data uncertainty in optimization problem. The main challenge in this RO methodology is how and when we can reformulate the robust counterpart of uncertain problems as a computationally tractable optimization problem or at least approximate the robust counterpart by a tractable problem. Due to its definition the robust counterpart highly depends on how we choose the uncertainty set. As a consequence we can meet this challenge only if this set is chosen in a suitable way. The development on RO grows fast, since 2004, a new approach of RO called Adjustable Robust Optimization (ARO) is introduced to handle uncertain problems when the decision variables must be decided as a ”wait and see” decision variables. Different than the classic Robust Optimization (RO) that models decision variables as ”here and now”. In ARO, the uncertain problems can be considered as a multistage decision problem, thus decision variables involved are now become the wait and see decision variables. In this paper we present the applications of both RO and ARO. We present briefly all results to strengthen the importance of RO and ARO in many real life problems.

The Decision Support Matrix (DSM) Approach to Reducing Risk of Flooding and Water Pollution in Farmed Landscapes

NASA Astrophysics Data System (ADS)

Hewett, Caspar J. M.; Quinn, Paul; Wilkinson, Mark

2014-05-01

Intense farming plays a key role in contributing to problems such as increased flood risk, soil erosion and poor water quality. This means that there is great potential for agricultural practitioners to play a major part in reducing multiple risks through better land-use management. Greater understanding by farmers, land managers, practitioners and policy-makers of the ways in which farmed landscapes contribute to risks and the ways in which those risks might be mitigated can be an essential component in improving practice. The Decision Support Matrix (DSM) approach involves the development of a range of visualization and communication tools to help compare the risks associated with different farming practices and explore options to manage runoff. DSMs are simple decision support systems intended for use by the non-expert which combine expert hydrological evidence with local knowledge of runoff patterns. They are developed through direct engagement with stakeholders, ensuring that the examples and language used makes sense to end-users. A key element of the tools is that they show the current conditions of the land and describe extremes of land-use management within a hydrological and agricultural land-management context. The tools include conceptual models of a series of pre-determined runoff scenarios, providing the end-user with a variety of potential land management practices and runoff management options. Visual examples of different farming practices are used to illustrate the impact of good and bad practice on specific problems such as nutrient export or risk of flooding. These show both how current conditions cause problems downstream and how systems are vulnerable to changes in climate and land-use intensification. The level of risk associated with a particular land management option is represented by a mapping on a two- or three-dimensional matrix. Interactive spreadsheet-based tools are developed in which multiple questions allow the user to explore different management options and see the impact of decisions plotted as a risk level on the DSM. They employ a ranking methodology combined with a simple mapping of information onto a visual matrix. A nominal scoring system is used to rank higher or lower runoff risk. The end-user can then assess numerous land use and runoff management options to lower risk. The objective is to encourage policy makers, catchment managers and farmers to produce resilient local landscapes at minimal cost. A number of DSMs have been developed successfully over a number of years working with a variety of stakeholders in the UK, including the Phosphorus Export Risk Matrix (PERM), The Nitrate Export Risk Matrix (NO3RM) and arable and livestock versions of the Floods and Agriculture Risk Matrix (FARM) (available from http://research.ncl.ac.uk/thefarm). Despite uncertainty, the tools do contribute to stakeholders having greater confidence in making decisions to make landscapes more resilient. DSMs have been taken up widely in the UK by bodies such as the Environment Agency and Defra, and have been successfully employed within wider decision support frameworks alongside modelling at multiple scales. Such tools could be used in similar farmed landscapes internationally.

Empirically supported religious and spiritual therapies.

PubMed

Hook, Joshua N; Worthington, Everett L; Davis, Don E; Jennings, David J; Gartner, Aubrey L; Hook, Jan P

2010-01-01

This article evaluated the efficacy status of religious and spiritual (R/S) therapies for mental health problems, including treatments for depression, anxiety, unforgiveness, eating disorders, schizophrenia, alcoholism, anger, and marital issues. Religions represented included Christianity, Islam, Taoism, and Buddhism. Some studies incorporated a generic spirituality. Several R/S therapies were found to be helpful for clients, supporting the further use and research on these therapies. There was limited evidence that R/S therapies outperformed established secular therapies, thus the decision to use an R/S therapy may be an issue of client preference and therapist comfort.

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.

Decision-problem state analysis methodology

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

A methodology for analyzing a decision-problem state is presented. The methodology is based on the analysis of an incident in terms of the set of decision-problem conditions encountered. By decomposing the events that preceded an unwanted outcome, such as an accident, into the set of decision-problem conditions that were resolved, a more comprehensive understanding is possible. All human-error accidents are not caused by faulty decision-problem resolutions, but it appears to be one of the major areas of accidents cited in the literature. A three-phase methodology is presented which accommodates a wide spectrum of events. It allows for a systems content analysis of the available data to establish: (1) the resolutions made, (2) alternatives not considered, (3) resolutions missed, and (4) possible conditions not considered. The product is a map of the decision-problem conditions that were encountered as well as a projected, assumed set of conditions that should have been considered. The application of this methodology introduces a systematic approach to decomposing the events that transpired prior to the accident. The initial emphasis is on decision and problem resolution. The technique allows for a standardized method of accident into a scenario which may used for review or the development of a training simulation.

Exploring the future with anticipatory networks

NASA Astrophysics Data System (ADS)

Skulimowski, A. M. J.

2013-01-01

This paper presents a theory of anticipatory networks that originates from anticipatory models of consequences in multicriteria decision problems. When making a decision, the decision maker takes into account the anticipated outcomes of each future decision problem linked by the causal relations with the present one. In a network of linked decision problems, the causal relations are defined between time-ordered nodes. The scenarios of future consequences of each decision are modeled by multiple vertices starting from an appropriate node. The network is supplemented by one or more relations of anticipation, or future feedback, which describe a situation where decision makers take into account the anticipated results of some future optimization problems while making their choice. So arises a multigraph of decision problems linked causally and by one or more anticipation relation, termed here the anticipatory network. We will present the properties of anticipatory networks and propose a method of reducing, transforming and using them to solve current decision problems. Furthermore, it will be shown that most anticipatory networks can be regarded as superanticipatory systems, i.e. systems that are anticipatory in the Rosen sense and contain a future model of at least one other anticipatory system. The anticipatory networks can also be applied to filter the set of future scenarios in a foresight exercise.

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

PubMed Central

2018-01-01

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

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

PubMed

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

2018-01-01

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

Online image classification under monotonic decision boundary constraint

NASA Astrophysics Data System (ADS)

Lu, Cheng; Allebach, Jan; Wagner, Jerry; Pitta, Brandi; Larson, David; Guo, Yandong

2015-01-01

Image classification is a prerequisite for copy quality enhancement in all-in-one (AIO) device that comprises a printer and scanner, and which can be used to scan, copy and print. Different processing pipelines are provided in an AIO printer. Each of the processing pipelines is designed specifically for one type of input image to achieve the optimal output image quality. A typical approach to this problem is to apply Support Vector Machine to classify the input image and feed it to its corresponding processing pipeline. The online training SVM can help users to improve the performance of classification as input images accumulate. At the same time, we want to make quick decision on the input image to speed up the classification which means sometimes the AIO device does not need to scan the entire image to make a final decision. These two constraints, online SVM and quick decision, raise questions regarding: 1) what features are suitable for classification; 2) how we should control the decision boundary in online SVM training. This paper will discuss the compatibility of online SVM and quick decision capability.

Multicriteria Selection of Optimal Location of TCSC in a Competitive Energy Market

NASA Astrophysics Data System (ADS)

Alomoush, Muwaffaq I.

2010-05-01

The paper investigates selection of the best location of thyristor-controlled series compensator (TCSC) in a transmission system from many candidate locations in a competitive energy market such that the TCSC causes a net valuable impact on congestion management outcome, transmission utilization, transmission losses, voltage stability, degree of fulfillment of spot market contracts, and system security. The problem is treated as a multicriteria decision-making process such that the candidate locations of TCSC are the alternatives and the conflicting objectives are the outcomes of the dispatch process, which may have different importance weights. The paper proposes some performance indices that the dispatch decision-making entity can use to measure market dispatch outcomes of each alternative. Based on agreed-upon preferences, the measures presented may help the decision maker compare and rank dispatch scenarios to ultimately decide which location is the optimal one. To solve the multicriteria decision, we use the preference ranking organization method for enrichment evaluations (PROMETHEE), which is a multicriteria decision support method that can handle complex conflicting-objective decision-making processes.

The Role of Medication in Supporting Emotional Wellbeing in Young People with Long-Term Needs

PubMed Central

Gray, Nicola J.; Wood, Damian M.

2017-01-01

Young people frequently use and access prescribed medications for a range of health problems. Medications aimed at treating both common health problems and long-term physical and mental health needs in adolescence can have a significant effect on a young person’s emotional well-being. We use a series of case studies to illustrate the challenges for healthcare professionals supporting young people with medication use. The studies illustrate the efficacy and limitations of medication on improving emotional well-being by alleviating illness and distress, and how this efficacy must be balanced against both the adverse effects and the burden of treatment. There are specific challenges for medication management during adolescence including issues of adherence/concordance, facilitating autonomy and participation in decision making, and promoting independence. PMID:29099742

A comparative study of machine learning models for ethnicity classification

NASA Astrophysics Data System (ADS)

Trivedi, Advait; Bessie Amali, D. Geraldine

2017-11-01

This paper endeavours to adopt a machine learning approach to solve the problem of ethnicity recognition. Ethnicity identification is an important vision problem with its use cases being extended to various domains. Despite the multitude of complexity involved, ethnicity identification comes naturally to humans. This meta information can be leveraged to make several decisions, be it in target marketing or security. With the recent development of intelligent systems a sub module to efficiently capture ethnicity would be useful in several use cases. Several attempts to identify an ideal learning model to represent a multi-ethnic dataset have been recorded. A comparative study of classifiers such as support vector machines, logistic regression has been documented. Experimental results indicate that the logical classifier provides a much accurate classification than the support vector machine.

Economic analyses to support decisions about HPV vaccination in low- and middle-income countries: a consensus report and guide for analysts.

PubMed

Jit, Mark; Levin, Carol; Brisson, Marc; Levin, Ann; Resch, Stephen; Berkhof, Johannes; Kim, Jane; Hutubessy, Raymond

2013-01-30

Low- and middle-income countries need to consider economic issues such as cost-effectiveness, affordability and sustainability before introducing a program for human papillomavirus (HPV) vaccination. However, many such countries lack the technical capacity and data to conduct their own analyses. Analysts informing policy decisions should address the following questions: 1) Is an economic analysis needed? 2) Should analyses address costs, epidemiological outcomes, or both? 3) If costs are considered, what sort of analysis is needed? 4) If outcomes are considered, what sort of model should be used? 5) How complex should the analysis be? 6) How should uncertainty be captured? 7) How should model results be communicated? Selecting the appropriate analysis is essential to ensure that all the important features of the decision problem are correctly represented, but that the analyses are not more complex than necessary. This report describes the consensus of an expert group convened by the World Health Organization, prioritizing key issues to be addressed when considering economic analyses to support HPV vaccine introduction in these countries.

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

Wu, Qishi; Zhu, Mengxia; Rao, Nageswara S

We propose an intelligent decision support system based on sensor and computer networks that incorporates various component techniques for sensor deployment, data routing, distributed computing, and information fusion. The integrated system is deployed in a distributed environment composed of both wireless sensor networks for data collection and wired computer networks for data processing in support of homeland security defense. We present the system framework and formulate the analytical problems and develop approximate or exact solutions for the subtasks: (i) sensor deployment strategy based on a two-dimensional genetic algorithm to achieve maximum coverage with cost constraints; (ii) data routing scheme tomore » achieve maximum signal strength with minimum path loss, high energy efficiency, and effective fault tolerance; (iii) network mapping method to assign computing modules to network nodes for high-performance distributed data processing; and (iv) binary decision fusion rule that derive threshold bounds to improve system hit rate and false alarm rate. These component solutions are implemented and evaluated through either experiments or simulations in various application scenarios. The extensive results demonstrate that these component solutions imbue the integrated system with the desirable and useful quality of intelligence in decision making.« less

Developing an Environmental Decision Support System for Stream Management: the STREAMES Experience

NASA Astrophysics Data System (ADS)

Riera, J.; Argerich, A.; Comas, J.; Llorens, E.; Martí, E.; Godé, L.; Pargament, D.; Puig, M.; Sabater, F.

2005-05-01

Transferring research knowledge to stream managers is crucial for scientifically sound management. Environmental decision support systems are advocated as an effective means to accomplish this. STREAMES (STream REAach Management: an Expert System) is a decision tree based EDSS prototype developed within the context of an European project as a tool to assist water managers in the diagnosis of problems, detection of causes, and selection of management strategies for coping with stream degradation issues related mostly to excess nutrient availability. STREAMES was developed by a team of scientists, water managers, and experts in knowledge engineering. Although the tool focuses on management at the stream reach scale, it also incorporates a mass-balance catchment nutrient emission model and a simple GIS module. We will briefly present the prototype and share our experience in its development. Emphasis will be placed on the process of knowledge acquisition, the design process, the pitfalls and benefits of the communication between scientists and managers, and the potential for future development of STREAMES, particularly in the context of the EU Water Framework Directive.

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.

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.

Decision Support | Solar Research | NREL

Science.gov Websites

informed solar decision making with credible, objective, accessible, and timely resources. Solar Energy Decision Support Decision Support NREL provides technical and analytical support to support provide unbiased information on solar policies and issues for state and local government decision makers

The Students Decision Making in Solving Discount Problem

ERIC Educational Resources Information Center

Abdillah; Nusantara, Toto; Subanji; Susanto, Hery; Abadyo

2016-01-01

This research is reviewing students' process of decision making intuitively, analytically, and interactively. The research done by using discount problem which specially created to explore student's intuition, analytically, and interactively. In solving discount problems, researcher exploring student's decision in determining their attitude which…

European laws on compulsory commitment to care of persons suffering from substance use disorders or misuse problems- a comparative review from a human and civil rights perspective.

PubMed

Israelsson, Magnus; Nordlöf, Kerstin; Gerdner, Arne

2015-08-28

Laws on compulsory commitment to care (CCC) in mental health, social and criminal legislation for adult persons with alcohol and/or drug dependence or misuse problems are constructed to address different scenarios related to substance use disorders. This study examines how such CCC laws in European states vary in terms of legal rights, formal orders of decision and criteria for involuntary admission, and assesses whether three legal frameworks (criminal, mental and social law) equally well ensure human and civil rights. Thirty-nine laws, from 38 countries, were analysed. Respondents replied in web-based questionnaires concerning a) legal rights afforded the persons with substance use problems during commitment proceedings, b) sources of formal application, c) instances for decision on admission, and d) whether or not 36 different criteria could function as grounds for decisions on CCC according to the law in question. Analysis of a-c were conducted in bivariate cross-tabulations. The 36 criteria for admission were sorted in criteria groups based on principal component analysis (PCA). To investigate whether legal rights, decision-making authorities or legal criteria may discriminate between types of law on CCC, discriminant analyses (DA) were conducted. There are few differences between the three types of law on CCC concerning legal rights afforded the individual. However, proper safeguards of the rights against unlawful detention seem still to be lacking in some CCC laws, regardless type of law. Courts are the decision-making body in 80 % of the laws, but this varies clearly between law types. Criteria for CCC also differ between types of law, i.e. concerning who should be treated: dependent offenders, persons with substance use problems with acting out or aggressive behaviors, or other vulnerable persons with alcohol or drug problems. The study raises questions concerning whether various European CCC laws in relation to substance use disorder or misuse problems comply with international ratified conventions concerning human and civil rights. This, however, applies to all three types of law, i.e. social, mental health and criminal legislation. The main differences between law types concern legal criteria, reflecting different national priorities on implicit ambitions of CCC - for correction, for prevention, or for support to those in greatest need of care.