Science.gov

Sample records for computer decision support

  1. Computer Based Decision Support in Dentistry.

    ERIC Educational Resources Information Center

    Wagner, Ina-Veronika; Schneider, Werner

    1991-01-01

    The paper discusses computer-based decision support in the following areas: the dental patient record system; diagnosis and treatment of diseases of the oral mucosa; treatment strategy in complex clinical situations; diagnosis and treatment of functional disturbances of the masticatory system; and patient recall. (DB)

  2. Computational Support for Technology- Investment Decisions

    NASA Technical Reports Server (NTRS)

    Adumitroaie, Virgil; Hua, Hook; Lincoln, William; Block, Gary; Mrozinski, Joseph; Shelton, Kacie; Weisbin, Charles; Elfes, Alberto; Smith, Jeffrey

    2007-01-01

    Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.

  3. 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.

  4. Reducing Diagnostic Error with Computer-Based Clinical Decision Support

    ERIC Educational Resources Information Center

    Greenes, Robert A.

    2009-01-01

    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

  5. Effectiveness of an Electronic Performance Support System on Computer Ethics and Ethical Decision-Making Education

    ERIC Educational Resources Information Center

    Kert, Serhat Bahadir; Uz, Cigdem; Gecu, Zeynep

    2014-01-01

    This study examined the effectiveness of an electronic performance support system (EPSS) on computer ethics education and the ethical decision-making processes. There were five different phases to this ten month study: (1) Writing computer ethics scenarios, (2) Designing a decision-making framework (3) Developing EPSS software (4) Using EPSS in a…

  6. EWall - Electronic Card Wall: Computational Support for Decision-Making in Collaborative Environments

    DTIC Science & Technology

    2007-12-17

    Support for Decision-Making in Collaborative Environments Final Report Grant Number: N000140410569 December 2007 Submitted to...4.2.1. Decision-Making Constructs in Distributed Environments ............................ 15 4.2.2. Collaborative Knowledge in Asynchronous...work environments . We developed an experimental computational environment referred to as the EWall system. The EWall system is designed to be used for

  7. Computer decision support system for the stomach cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Polyakov, E. V.; Sukhova, O. G.; Korenevskaya, P. Y.; Ovcharova, V. S.; Kudryavtseva, I. O.; Vlasova, S. V.; Grebennikova, O. P.; Burov, D. A.; Yemelyanova, G. S.; Selchuk, V. Y.

    2017-01-01

    The paper considers the creation of the computer knowledge base containing the data of histological, cytologic, and clinical researches. The system is focused on improvement of diagnostics quality of stomach cancer - one of the most frequent death causes among oncologic patients.

  8. Computer-assisted diagnostic decision support: history, challenges, and possible paths forward.

    PubMed

    Miller, Randolph A

    2009-09-01

    This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References indicate the original sources of many of these ideas.

  9. Computer-Assisted Diagnostic Decision Support: History, Challenges, and Possible Paths Forward

    ERIC Educational Resources Information Center

    Miller, Randolph A.

    2009-01-01

    This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References…

  10. Computer-based tools for decision support at the Hanford Site

    SciTech Connect

    Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

    1992-11-01

    To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high` level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the ``glue`` or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

  11. Computer-based tools for decision support at the Hanford Site

    SciTech Connect

    Doctor, P.G.; Mahaffey, J.A.; Cowley, P.J.; Freshley, M.D.; Hassig, N.L.; Brothers, J.W.; Glantz, C.S.; Strachan, D.M.

    1992-11-01

    To help integrate activities in the environmental restoration and waste management mission of the Hanford Site, the Hanford Integrated Planning Project (HIPP) was established and funded by the US Department of Energy. The project is divided into three key program elements, the first focusing on an explicit, defensible and comprehensive method for evaluating technical options. Based on the premise that computer technology can be used to support the decision-making process and facilitate integration among programs and activities, the Decision Support Tools Task was charged with assessing the status of computer technology for those purposes at the Site. The task addressed two types of tools: tools need to provide technical information and management support tools. Technical tools include performance and risk assessment models, information management systems, data and the computer infrastructure to supports models, data, and information management systems. Management decision support tools are used to synthesize information at a high' level to assist with making decisions. The major conclusions resulting from the assessment are that there is much technical information available, but it is not reaching the decision-makers in a form to be used. Many existing tools provide components that are needed to integrate site activities; however, some components are missing and, more importantly, the glue'' or connections to tie the components together to answer decision-makers questions is largely absent. Top priority should be given to decision support tools that support activities given in the TPA. Other decision tools are needed to facilitate and support the environmental restoration and waste management mission.

  12. Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review.

    PubMed

    Liedlgruber, Michael; Uhl, Andreas

    2011-01-01

    Today, medical endoscopy is a widely used procedure to inspect the inner cavities of the human body. The advent of endoscopic imaging techniques-allowing the acquisition of images or videos-created the possibility for the development of the whole new branch of computer-aided decision support systems. Such systems aim at helping physicians to identify possibly malignant abnormalities more accurately. At the beginning of this paper, we give a brief introduction to the history of endoscopy, followed by introducing the main types of endoscopes which emerged so far (flexible endoscope, wireless capsule endoscope, and confocal laser endomicroscope). We then give a brief introduction to computer-aided decision support systems specifically targeted at endoscopy in the gastrointestinal tract. Then we present general facts and figures concerning computer-aided decision support systems and summarize work specifically targeted at computer-aided decision support in the gastrointestinal tract. This summary is followed by a discussion of some common issues concerning the approaches reviewed and suggestions of possible ways to resolve them.

  13. Computer Decision Support to Improve Autism Screening and Care in Community Pediatric Clinics

    ERIC Educational Resources Information Center

    Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.

    2013-01-01

    An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…

  14. Biomedical informatics for computer-aided decision support systems: a survey.

    PubMed

    Belle, Ashwin; Kon, Mark A; Najarian, Kayvan

    2013-01-01

    The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest.

  15. Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey

    PubMed Central

    Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan

    2013-01-01

    The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259

  16. Enabling Water Quality Management Decision Support and Public Outreach Using Cloud-Computing Services

    NASA Astrophysics Data System (ADS)

    Sun, A. Y.; Scanlon, B. R.; Uhlman, K.

    2013-12-01

    Watershed management is a participatory process that requires collaboration among multiple groups of people. Environmental decision support systems (EDSS) have long been used to support such co-management and co-learning processes in watershed management. However, implementing and maintaining EDSS in-house can be a significant burden to many water agencies because of budget, technical, and policy constraints. Basing on experiences from several web-GIS environmental management projects in Texas, we showcase how cloud-computing services can help shift the design and hosting of EDSS from the traditional client-server-based platforms to be simple clients of cloud-computing services.

  17. Integration of sensing and computing in an intelligent decision support system for homeland security defense

    SciTech Connect

    Wu, Qishi; Zhu, Mengxia; Rao, Nageswara S

    2009-04-01

    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 to 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.

  18. The Use of Computer-Aided Decision Support Systems for Complex Source Selection Decisions

    DTIC Science & Technology

    1989-09-01

    making processes under which virtually all decisions can be categorized. Optimizing. To optimize is to make the best possible decision under the... community ; 45 AFIT students may not be a representative sample. A subjective case may be made, however, that these subjects were relatively typical...career paths of the population studied, compared with that which apparently exists in the acquisition community . Discussion of Variables Major Constructs

  19. Modern data-driven decision support systems: the role of computing with words and computational linguistics

    NASA Astrophysics Data System (ADS)

    Kacprzyk, Janusz; Zadrożny, Sławomir

    2010-05-01

    We present how the conceptually and numerically simple concept of a fuzzy linguistic database summary can be a very powerful tool for gaining much insight into the very essence of data. The use of linguistic summaries provides tools for the verbalisation of data analysis (mining) results which, in addition to the more commonly used visualisation, e.g. via a graphical user interface, can contribute to an increased human consistency and ease of use, notably for supporting decision makers via the data-driven decision support system paradigm. Two new relevant aspects of the analysis are also outlined which were first initiated by the authors. First, following Kacprzyk and Zadrożny, it is further considered how linguistic data summarisation is closely related to some types of solutions used in natural language generation (NLG). This can make it possible to use more and more effective and efficient tools and techniques developed in NLG. Second, similar remarks are given on relations to systemic functional linguistics. Moreover, following Kacprzyk and Zadrożny, comments are given on an extremely relevant aspect of scalability of linguistic summarisation of data, using a new concept of a conceptual scalability.

  20. Using old technology to implement modern computer-aided decision support for primary diabetes care.

    PubMed Central

    Hunt, D. L.; Haynes, R. B.; Morgan, D.

    2001-01-01

    BACKGROUND: Implementation rates of interventions known to be beneficial for people with diabetes mellitus are often suboptimal. Computer-aided decision support systems (CDSSs) can improve these rates. The complexity of establishing a fully integrated electronic medical record that provides decision support, however, often prevents their use. OBJECTIVE: To develop a CDSS for diabetes care that can be easily introduced into primary care settings and diabetes clinics. THE SYSTEM: The CDSS uses fax-machine-based optical character recognition software for acquiring patient information. Simple, 1-page paper forms, completed by patients or health practitioners, are faxed to a central location. The information is interpreted and recorded in a database. This initiates a routine that matches the information against a knowledge base so that patient-specific recommendations can be generated. These are formatted and faxed back within 4-5 minutes. IMPLEMENTATION: The system is being introduced into 2 diabetes clinics. We are collecting information on frequency of use of the system, as well as satisfaction with the information provided. CONCLUSION: Computer-aided decision support can be provided in any setting with a fax machine, without the need for integrated electronic medical records or computerized data-collection devices. PMID:11825194

  1. Clinical decision support foundations.

    PubMed

    Pradhan, Malcolm; Liaw, Siaw Teng

    2010-01-01

    This chapter gives an educational overview of: * The elements of a clinical decision; * The elements of decision making: prior probability, evidence (likelihood), posterior probability, actions, utility (value); * A framework for decision making, and support, encompassing validity, utility, importance and certainty; and * The required elements of a clinical decision support system. * The role of knowledge management in the construction and maintenance of clinical decision support.

  2. From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported guideline refinement.

    PubMed

    Hsueh, Pei-Yun; Lan, Ci-Wei; Deng, Vincent; Zhu, Xinxin

    2012-01-01

    Personalized wellness decision support has gained significant attention, owing to the shift to a patient-centric paradigm in healthcare domains, and the consequent availability of a wealth of patient-related data. Despite the success of data-driven analytics in improving practice outcome, there is a gap towards their deployment in guideline-based practice. In this paper we report on findings related to computer-supported guideline refinement, which maps a patient's guideline requirements to personalized recommendations that suit the patient's current context. In particular, we present a novel data-driven personalization framework, casting the mapping task as a statistical decision problem in search of a solution to maximize expected utility. The proposed framework is well suited to produce personalized recommendations based on not only clinical factors but contextual factors that reflect individual differences in non-clinical settings. We then describe its implementation within the guideline-based clinical decision support system and discuss opportunities and challenges looking forward.

  3. Computer models used to support cleanup decision-making at hazardous and radioactive waste sites

    SciTech Connect

    Moskowitz, P.D.; Pardi, R.; DePhillips, M.P.; Meinhold, A.F.

    1992-07-01

    Massive efforts are underway to cleanup hazardous and radioactive waste sites located throughout the US To help determine cleanup priorities, computer models are being used to characterize the source, transport, fate and effects of hazardous chemicals and radioactive materials found at these sites. Although, the US Environmental Protection Agency (EPA), the US Department of Energy (DOE), and the US Nuclear Regulatory Commission (NRC) have provided preliminary guidance to promote the use of computer models for remediation purposes, no Agency has produced directed guidance on models that must be used in these efforts. To identify what models are actually being used to support decision-making at hazardous and radioactive waste sites, a project jointly funded by EPA, DOE and NRC was initiated. The purpose of this project was to: (1) Identify models being used for hazardous and radioactive waste site assessment purposes; and (2) describe and classify these models. This report presents the results of this study.

  4. Improving Computational Efficiency of Model Predictive Control Genetic Algorithms for Real-Time Decision Support

    NASA Astrophysics Data System (ADS)

    Minsker, B. S.; Zimmer, A. L.; Ostfeld, A.; Schmidt, A.

    2014-12-01

    Enabling real-time decision support, particularly under conditions of uncertainty, requires computationally efficient algorithms that can rapidly generate recommendations. In this paper, a suite of model predictive control (MPC) genetic algorithms are developed and tested offline to explore their value for reducing CSOs during real-time use in a deep-tunnel sewer system. MPC approaches include the micro-GA, the probability-based compact GA, and domain-specific GA methods that reduce the number of decision variable values analyzed within the sewer hydraulic model, thus reducing algorithm search space. Minimum fitness and constraint values achieved by all GA approaches, as well as computational times required to reach the minimum values, are compared to large population sizes with long convergence times. Optimization results for a subset of the Chicago combined sewer system indicate that genetic algorithm variations with coarse decision variable representation, eventually transitioning to the entire range of decision variable values, are most efficient at addressing the CSO control problem. Although diversity-enhancing micro-GAs evaluate a larger search space and exhibit shorter convergence times, these representations do not reach minimum fitness and constraint values. The domain-specific GAs prove to be the most efficient and are used to test CSO sensitivity to energy costs, CSO penalties, and pressurization constraint values. The results show that CSO volumes are highly dependent on the tunnel pressurization constraint, with reductions of 13% to 77% possible with less conservative operational strategies. Because current management practices may not account for varying costs at CSO locations and electricity rate changes in the summer and winter, the sensitivity of the results is evaluated for variable seasonal and diurnal CSO penalty costs and electricity-related system maintenance costs, as well as different sluice gate constraint levels. These findings indicate

  5. Recurrent neural networks in computer-based clinical decision support for laryngopathies: an experimental study.

    PubMed

    Szkoła, Jarosław; Pancerz, Krzysztof; Warchoł, Jan

    2011-01-01

    The main goal of this paper is to give the basis for creating a computer-based clinical decision support (CDS) system for laryngopathies. One of approaches which can be used in the proposed CDS is based on the speech signal analysis using recurrent neural networks (RNNs). RNNs can be used for pattern recognition in time series data due to their ability of memorizing some information from the past. The Elman networks (ENs) are a classical representative of RNNs. To improve learning ability of ENs, we may modify and combine them with another kind of RNNs, namely, with the Jordan networks. The modified Elman-Jordan networks (EJNs) manifest a faster and more exact achievement of the target pattern. Validation experiments were carried out on speech signals of patients from the control group and with two kinds of laryngopathies.

  6. A Computer Based Decision Support System for Tailoring Logistics Support Analysis Record (LSAR) Requirements

    DTIC Science & Technology

    1989-09-01

    physical teardown logistics demonstration ( PTLD ) both to record data as a result of the PTLD , and to review the results of the PTLD against the LSAR...manually insert and describe those support items not identified in the LSAR but found to be required during the PTLD review. ENDTEXT @22,1 WAIT CLEAR

  7. Survey on computer aided decision support for diagnosis of celiac disease

    PubMed Central

    Hegenbart, Sebastian; Uhl, Andreas; Vécsei, Andreas

    2015-01-01

    Celiac disease (CD) is a complex autoimmune disorder in genetically predisposed individuals of all age groups triggered by the ingestion of food containing gluten. A reliable diagnosis is of high interest in view of embarking on a strict gluten-free diet, which is the CD treatment modality of first choice. The gold standard for diagnosis of CD is currently based on a histological confirmation of serology, using biopsies performed during upper endoscopy. Computer aided decision support is an emerging option in medicine and endoscopy in particular. Such systems could potentially save costs and manpower while simultaneously increasing the safety of the procedure. Research focused on computer-assisted systems in the context of automated diagnosis of CD has started in 2008. Since then, over 40 publications on the topic have appeared. In this context, data from classical flexible endoscopy as well as wireless capsule endoscopy (WCE) and confocal laser endomicrosopy (CLE) has been used. In this survey paper, we try to give a comprehensive overview of the research focused on computer-assisted diagnosis of CD. PMID:25770906

  8. Clinical experience with a decision support computer program using Bayes' theorem to diagnose chest pain patients.

    PubMed

    Aase, O

    1999-01-01

    A decision support computer program (DSP) was used by the emergency room physician as a diagnostic tool on patients admitted with acute chest pain to guide the referral of these patients either to the Coronary Care Unit (CCU) or general ward. The DSP used Bayes' theorem on 38 anamnestic and clinical variables to classify patients into one of nine diagnoses. During a six months trial period 32 physicians used the DSP to diagnose 493 patients admitted with acute chest pain. The physicians referred the patients to CCU or general ward based on their clinical judgements, the ECG findings and the diagnostic estimates given by the DSP. The program correctly diagnosed 150 (84%) of 178 patients with acute myocardial infarction and 63 of 112 patients with unstable angina. However, acute ischemic heart disease (acute myocardial infarction or unstable angina) was correctly classified by the DSP for 259 (89%) of 290 patients. By using the DSP, the number of patients unnecessarily referred to CCU was reduced from 35% to 19% and the number of patients in need of CCU observation misallocated to general ward was reduced from 13% to 10%. Thus, use of the DSP in the emergency room on easily available anamnestic and clinical variables may improve referrals to the CCU, optimize therapy and resource use.

  9. 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.

  10. Computer Decision Support Changes Physician Practice But Not Knowledge Regarding Autism Spectrum Disorders

    PubMed Central

    Carroll, A.E.; Saha, C.; Downs, S.M.

    2015-01-01

    Summary Objective To examine whether adding an autism module promoting adherence to clinical guidelines to an existing computer decision support system (CDSS) changed physician knowledge and self-reported clinical practice. Methods The CHICA (Child Health Improvement through Computer Automation) system, a CDSS, was enhanced with a module to improve management of autism in 2 of the 4 community pediatric clinics using the system. We examined the knowledge and beliefs of pediatric users using cross-sectional surveys administered at 3 time points (baseline, 12 months and 24 months post-implementation) between November 2010 and January 2013. Surveys measured knowledge, beliefs and self-reported practice patterns related to autism. Results A total of 45, 39, and 42 pediatricians responded at each time point, respectively, a 95-100% response rate. Respondents’ knowledge of autism and perception of role for diagnosis did not vary between control and intervention groups either at baseline or any of the two post-intervention time points. At baseline, there was no difference between these groups in rates in the routine use of parent-rated screening instruments for autism. However, by 12 and 24 months post-implementation there was a significant difference between intervention and control clinics in terms of the intervention clinics consistently screening eligible patients with a validated autism tool. Physicians at all clinics reported ongoing challenges to community resources for further work-up and treatment related to autism. Conclusions A CDSS module to improve primary care management of ASD in pediatric practice led to significant improvements in physician-reported use of validated screening tools to screen for ASDs. However it did not lead to corresponding changes in physician knowledge or attitudes. PMID:26448791

  11. Decision Support for Medical Treatment: A TPN Prescription System on a Central Hospital Computer

    PubMed Central

    Moliver, Nina; Coates, Allan L.

    1987-01-01

    An interactive decision-support system for the prescription of total or partial parenteral nutrition (TPN) is described. The system is applicable to all sizes and ages of patients, from premature infants to adults. Both the physician and the pharmacist are users of the system, with the physician using rule-based safety checks and branching algorithms to make decisions in the prescription process, and the pharmacist receiving the prescription totals electronically in order to complete further calculations needed. Since its introduction, the system appears to have increased the safety of the TPN prescription, saved time, and improved the quality and appropriateness of TPN prescriptions.

  12. A Decision Support System for Cost-Effectiveness Analysis for Control and Security of Computer Systems.

    DTIC Science & Technology

    1985-09-01

    Support System for Cost- Master’s Thesis Effectiveness Analysis for Control and September 1985 Security of Computer Systems 6. PERFORMING ORG . REPORT...F )3010 >~T .0 0 Find directory U Figulre 8. i reaFlw iara fies.obe ->~Ne8 DrbelExoue Controls Inc z W &Z ,~L. UJ. LiL La CA CC 449 -*LA- D. P Erase

  13. Decision Support Systems: Theory.

    DTIC Science & Technology

    1976-01-01

    comprehensive bibli- ography search was initiated . This activity continued throughout the contract period. It included a library search, and contact with...bibliography appears at the end of this report. While the bibliographical search con- tinued, a corpanion activity was initiated . This consisted of...number, support decisions which occur infrequently or are not usually anticipated. 2.3 Some Definitions of a DSS Much of the initial focus and direction

  14. The Effect of Interactivity on Decision Confidence and Outcome Expectations in Computer Supported Task Environment

    ERIC Educational Resources Information Center

    Lee, Kiljae

    2013-01-01

    While interactivity is regarded as a distinguishing characteristic of computer technology, the explanation on its impact remains in its infancy. The present research investigates what it means to provide a more (or less) interactive computer interface design by attempting to uncover its cognitive influences on the user's expectation of outcome and…

  15. An Integrated Approach to Computer-Based Decision Support at the Point of Care

    PubMed Central

    Cimino, James J.

    2007-01-01

    Information needs that arise when clinicians use clinical information systems often go unresolved, forcing clinicians to defer decisions or make them with incomplete knowledge. My research characterizes these needs in order to build information systems that can help clinicians get timely answers to their questions. My colleagues and I have developed “Infobuttons”, which are links between clinical information systems and on-line knowledge resources, and have developed an “Infobutton Manager” (IM) that attempts to determine the information need based on the context of what the user is doing. The IM presents users with a set of questions, each of which is a link to an online information resource that will answer the question. The Infobutton Manager has been successfully deployed in five systems at four institutions and provides users with over 1,000 accesses to on-line health information each month, with a positive impact on patient care. PMID:18528510

  16. Personal computer based decision support system for routing nuclear spent fuel

    SciTech Connect

    Chin, Shih-Miao; Joy, D.S.; Johnson, P.E. ); Bobic, S.M.; Miaou, Shaw-Pin . Transportation Center)

    1989-11-14

    An approach has been formulated to route nuclear spent fuel over the US Interstate highway network. This approach involves the generation of alternative routes so that any potential adverse impacts will not only concentrate on regions along the shortest path between the nuclear power plant and repository. Extensive literature research on the shortest path finding algorithms has been carried out. Consequently, an extremely efficient shortest path algorithm has been implemented and significantly increases the overall system performance. State-of-the-art interactive computer graphics is used. In addition to easy-to-use pop-up menus, full color mapping and display capabilities are also incorporated. All of these features have been implemented on commonly available personal computers. 6 figs., 2 tabs.

  17. A computational framework for supporting environmental-climate-energy decision-making

    EPA Science Inventory

    GLIMPSE is a effort in which the U.S. EPA Office of Research and Development is developing tools to support long-term, coordinated environmental, climate, and energy planning. The purpose of this presentation is to discuss the underlying science questions; provide an overview of ...

  18. Hybrid expert system for decision supporting in the medical area: complexity and cognitive computing.

    PubMed

    Brasil, L M; de Azevedo, F M; Barreto, J M

    2001-09-01

    This paper proposes a hybrid expert system (HES) to minimise some complexity problems pervasive to the artificial intelligence such as: the knowledge elicitation process, known as the bottleneck of expert systems; the model choice for knowledge representation to code human reasoning; the number of neurons in the hidden layer and the topology used in the connectionist approach; the difficulty to obtain the explanation on how the network arrived to a conclusion. Two algorithms applied to developing of HES are also suggested. One of them is used to train the fuzzy neural network and the other to obtain explanations on how the fuzzy neural network attained a conclusion. To overcome these difficulties the cognitive computing was integrated to the developed system. A case study is presented (e.g. epileptic crisis) with the problem definition and simulations. Results are also discussed.

  19. Development of computer automated decision support system for surface water quality assessment

    NASA Astrophysics Data System (ADS)

    Sharma, Asheesh; Naidu, Madhuri; Sargaonkar, Aabha

    2013-02-01

    The Overall Index of Pollution (OIP) is a single number that expresses the overall water quality by integrating measurements of 14 different physicochemical, toxicological, and bacteriological water quality parameters. It provides a simple and concise method for water quality classification as, 'Excellent', 'Acceptable', 'Slightly Polluted', 'Polluted', and 'Heavily Polluted'. OIP values range from 0 to 16. A high OIP value signals poor water quality, while a low value signals good water quality based on the classification scheme developed for India. In this paper, we present a computer-automated, user-friendly, and standalone Surface Water Quality Assessment Tool (SWQAT), which calculates OIP values and displays it on Google map. The software is developed in VB.Net and SQL database. The software application is demonstrated through water quality assessment of two rivers of India, namely Cauvery and Tungabhadra. OIP values are estimated at 10 sampling stations on the river Cauvery and at eight sampling stations on the river Tungabhadra. The Cauvery river OIP scores in the range 0.85-7.91 while for Tungabhadra river, it is in range 2.08 to 8.97. The results are useful to analyze the variations in the water quality of different sites at different times. SWQAT improves understanding of general water quality issues, communicates water quality status, and draws the need for and effectiveness of protection measures.

  20. Computational Cognition and Robust Decision Making

    DTIC Science & Technology

    2013-03-06

    AFOSR: 1.8 BRIEF DESCRIPTION OF PORTFOLIO Support experimental and computational modeling work in: 1. Understanding cognitive...AREAS IN PORTFOLIO 1. Mathematical and Computational Cognition 2. Robust Decision Making in Human-System Interface 3. Computational and Machine...Interactions with Other Organizations ONR (Paul Bello) • Perception, Metacognition , and Cognitive Control Program ONR (Tom McKenna) • Computational

  1. CHESS: a computer-based system for providing information, referrals, decision support and social support to people facing medical and other health-related crises.

    PubMed

    Gustafson, D H; Bosworth, K; Hawkins, R P; Boberg, E W; Bricker, E

    1992-01-01

    CHESS (the Comprehensive Health Enhancement Support System) is an interactive, computer-based system to support people facing health-related crises or concerns. CHESS provides information, referral to service providers, support in making tough decisions and networking to experts and others facing the same concerns. CHESS will improve access to health and human services for people who would otherwise face psychological, social, economic or geographic barriers to receiving services. CHESS has developed programs in five specific topic areas: Academic Crisis, Adult Children of Alcoholics, AIDS/HIV Infection, Breast Cancer and Sexual Assault. The lessons learned, and the structures developed, will serve as a model for future implementation of CHESS programs in a broad range of other topic areas. CHESS is designed around three major desired outcomes: 1) improving the emotional health status of users; 2) increasing the cost-effective use of health and human services; and 3) reducing the incidence of risk-taking behaviors that can lead to injury or illness. Pilot-testing and initial analysis of controlled evaluation data has shown that CHESS is extensively used, is useful and easy-to-use, and produces positive emotional outcomes. Further evaluation in continuing.

  2. Computeer-based decision support tools for evaluation of actions affecting flow and water quality in the San Joaquin Basin

    SciTech Connect

    Quinn, N.W.T.

    1993-01-01

    This document is a preliminary effort to draw together some of the important simulation models that are available to Reclamation or that have been developed by Reclamation since 1987. This document has also attempted to lay out a framework by which these models might be used both for the purposes for which they were originally intended and to support the analysis of other issues that relate to the hydrology and to salt and water quality management within the San Joaquin Valley. To be successful as components of a larger Decision Support System the models should to be linked together using custom designed interfaces that permit data sharing between models and that are easy to use. Several initiatives are currently underway within Reclamation to develop GIS - based and graphics - based decision support systems to improve the general level of understanding of the models currently in use, to standardize the methodology used in making planning and operations studies and to permit improved data analysis, interpretation and display. The decision support systems should allow greater participation in the planning process, allow the analysis of innovative actions that are currently difficult to study with present models and should lead to better integrated and more comprehensive plans and policy decisions in future years.

  3. Information gap decision support for contaminant remediation

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Uncertainty quantifications and decision analyses under severe lack of information are ubiquitous in every applied field of engineering, policy, and science. A severe lack of information precludes our ability to determine unbiased probabilistic distributions for model parameters and model predictions; therefore, model and decision uncertainties due to a severe lack of information cannot be characterized probabilistically. To circumvent this problem, information gap (info-gap) theory has been developed to explicitly recognize and quantify the implications of information gaps in decision making. Here we present a decision analysis based on info-gap theory developed for a source identification problem where the locations and mass fluxes of contaminants impacting groundwater resources are unknown. The problem is characterized with a lack of information related to (1) model parameters representing contaminant migration in the aquifer, and (2) observed contamination concentration in the existing monitoring wells. These two sources of uncertainty are coupled through an inverse model where the observed concentrations are applied to estimate model parameters. The decision goal is based on contaminant predictions at points of compliance. The decision analysis is demonstrated for synthetic and real-world test cases. The applied uncertainty-quantification, decision-support techniques and computational algorithms are implemented in code MADS (Model Analyses for Decision Support; http://mads.lanl.gov). MADS is C/C++ code that provides a framework for model-based decision support. MADS performs various types of model analyses including sensitivity analysis, parameter estimation, uncertainty quantification, model calibration, selection and averaging. To perform the analyses, MADS can be coupled with any external simulators. Our efforts target development of an interactive computer-based Decision Support System (DSS) that will help domain scientist, managers, regulators, and

  4. Using computer decision support systems in NHS emergency and urgent care: ethnographic study using normalisation process theory

    PubMed Central

    2013-01-01

    Background Information and communication technologies (ICTs) are often proposed as ‘technological fixes’ for problems facing healthcare. They promise to deliver services more quickly and cheaply. Yet research on the implementation of ICTs reveals a litany of delays, compromises and failures. Case studies have established that these technologies are difficult to embed in everyday healthcare. Methods We undertook an ethnographic comparative analysis of a single computer decision support system in three different settings to understand the implementation and everyday use of this technology which is designed to deal with calls to emergency and urgent care services. We examined the deployment of this technology in an established 999 ambulance call-handling service, a new single point of access for urgent care and an established general practice out-of-hours service. We used Normalization Process Theory as a framework to enable systematic cross-case analysis. Results Our data comprise nearly 500 hours of observation, interviews with 64 call-handlers, and stakeholders and documents about the technology and settings. The technology has been implemented and is used distinctively in each setting reflecting important differences between work and contexts. Using Normalisation Process Theory we show how the work (collective action) of implementing the system and maintaining its routine use was enabled by a range of actors who established coherence for the technology, secured buy-in (cognitive participation) and engaged in on-going appraisal and adjustment (reflexive monitoring). Conclusions Huge effort was expended and continues to be required to implement and keep this technology in use. This innovation must be understood both as a computer technology and as a set of practices related to that technology, kept in place by a network of actors in particular contexts. While technologies can be ‘made to work’ in different settings, successful implementation has been

  5. Spatial Decision Support Workshop 2011

    DTIC Science & Technology

    2011-01-01

    report are those of the author(s) and should not contrued as an official Department of the Army position, policy or decision, unless so designated by...and temporal development of phenomena and processes ;  Complex multi-dimensional and heterogeneous data describing decision situations;  Large or...information is an integral part of DoD operations and installation management. Spatial decision support processes and systems combine GIS and other

  6. Evaluation of selected environmental decision support software

    SciTech Connect

    Sullivan, T.M.; Moskowitz, P.D.; Gitten, M.

    1997-06-01

    Decision Support Software (DSS) continues to be developed to support analysis of decisions pertaining to environmental management. Decision support systems are computer-based systems that facilitate the use of data, models, and structured decision processes in decision making. The optimal DSS should attempt to integrate, analyze, and present environmental information to remediation project managers in order to select cost-effective cleanup strategies. The optimal system should have a balance between the sophistication needed to address the wide range of complicated sites and site conditions present at DOE facilities, and ease of use (e.g., the system should not require data that is typically unknown and should have robust error checking of problem definition through input, etc.). In the first phase of this study, an extensive review of the literature, the Internet, and discussions with sponsors and developers of DSS led to identification of approximately fifty software packages that met the preceding definition.

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

    DTIC Science & Technology

    2015-04-01

    test the clinical effects of a Computer Assisted Decision Support (CADS) System for the management of Type 2 diabetes (T2D) by primary care... Diabetes mellitus (DM) affects more than 29 million people in the United States and is associated with devastating complications in both personal and...financial terms. Diabetes is the leading cause of blindness, non-traumatic amputations, and renal failure in adults and reduces life expectancy by 5

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

    EPA Science Inventory

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

  9. A shotgun wedding: business decision support meets clinical decision support.

    PubMed

    Oliveira, Jason

    2002-01-01

    By effectively closing the loop between the data, analytics, processes, and methods supporting business and clinical decision making, a healthcare organization closes the loop between its knowledge generation activities and its actions at the bedside: knowledge guiding actions, actions generating knowledge.

  10. Automating hypertext for decision support

    NASA Technical Reports Server (NTRS)

    Bieber, Michael

    1990-01-01

    A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.

  11. Using computational modeling to assess the impact of clinical decision support on cancer screening improvement strategies within the community health centers.

    PubMed

    Carney, Timothy Jay; Morgan, Geoffrey P; Jones, Josette; McDaniel, Anna M; Weaver, Michael; Weiner, Bryan; Haggstrom, David A

    2014-10-01

    Our conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman's Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability.

  12. EVALUATING ENVIRONMENTAL DECISION SUPPORT TOOLS.

    SciTech Connect

    SULLIVAN, T.

    2004-10-01

    Effective contaminated land management requires a number of decisions addressing a suite of technical, economic, and social concerns. These concerns include human health risks, ecological risks, economic costs, technical feasibility of proposed remedial actions, and the value society places on clean-up and re-use of formerly contaminated lands. Decision making, in the face of uncertainty and multiple and often conflicting objectives, is a vital and challenging role in environmental management that affects a significant economic activity. Although each environmental remediation problem is unique and requires a site-specific analysis, many of the key decisions are similar in structure. This has led many to attempt to develop standard approaches. As part of the standardization process, attempts have been made to codify specialist expertise into decision support tools. This activity is intended to facilitate reproducible and transparent decision making. The process of codifying procedures has also been found to be a useful activity for establishing and rationalizing management processes. This study will have two primary objectives. The first is to develop taxonomy for Decision Support Tools (DST) to provide a framework for understanding the different tools and what they are designed to address in the context of environmental remediation problems. The taxonomy will have a series of subject areas for the DST. From these subjects, a few key areas will be selected for further study and software in these areas will be identified. The second objective, will be to review the existing DST in the selected areas and develop a screening matrix for each software product.

  13. Joint Command Decision Support System

    DTIC Science & Technology

    2011-06-01

    Greenley et al. 2006) resulted in the identification of a set of overarching principles for the implementation of Joint Command Decision Support (Hales...and adjustment of resources, and longer term feasibility planning. As highlighted in the Joint Staff Front End Analysis report ( Greenley et al. 2006...Townsend (2006). The Federal Response to Hurricane Katrina Lessons Learned, Washington, D.C. February 2006. Greenley , A., Baker, K. & Cochran, L. (2006

  14. Application of Voice Recognition Input to Decision Support Systems

    DTIC Science & Technology

    1988-12-01

    Support System (GDSS) Talkwriter Human Computer Interface Voice Input Individual Decision Support System (IDSS) Voice Input/Output Man Machine Voice ... Interface Voice Processing Natural Language Voice Input Voice Recognition Natural Language Accessed Voice Recognizer Speech Entry Voice Vocabulary

  15. Decision Support Methods and Tools

    NASA Technical Reports Server (NTRS)

    Green, Lawrence L.; Alexandrov, Natalia M.; Brown, Sherilyn A.; Cerro, Jeffrey A.; Gumbert, Clyde r.; Sorokach, Michael R.; Burg, Cecile M.

    2006-01-01

    This paper is one of a set of papers, developed simultaneously and presented within a single conference session, that are intended to highlight systems analysis and design capabilities within the Systems Analysis and Concepts Directorate (SACD) of the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). This paper focuses on the specific capabilities of uncertainty/risk analysis, quantification, propagation, decomposition, and management, robust/reliability design methods, and extensions of these capabilities into decision analysis methods within SACD. These disciplines are discussed together herein under the name of Decision Support Methods and Tools. Several examples are discussed which highlight the application of these methods within current or recent aerospace research at the NASA LaRC. Where applicable, commercially available, or government developed software tools are also discussed

  16. Decision support for financial forecasting

    SciTech Connect

    Jairam, B.N.; Morris, J.D.; Emrich, M.L.; Hardee, H.K.

    1988-10-01

    A primary mission of the Budget Management Division of the Air Force is fiscal analysis. This involves formulating, justifying, and tracking financial data during budget preparation and execution. An essential requirement of this process is the ready availability and easy manipulation of past and current budget data. This necessitates the decentralization of the data. A prototypical system, BAFS (Budget Analysis and Forecasting System), that provides such a capability is presented. In its current state, the system is designed to be a decision support tool. A brief report of the budget decisions and activities is presented. The system structure and its major components are discussed. An insight into the implementation strategies and the tool used is provided. The paper concludes with a discussion of future enhancements and the system's evolution into an expert system. 4 refs., 3 figs.

  17. Role of Remotely Sensed Observations and Computational Systems in Support of Decision-Making in Developing and Fragile States

    NASA Technical Reports Server (NTRS)

    Khan, Maudood; Rickman, Doug; Limaye, Ashutosh; Crosson, Bill; Layman, Charles; Hemmings, Sarah

    2010-01-01

    The topics covered in this slide presentation are: (1) Post-war growth of U.S scientific enterprise, (2) Success of air quality regulations, (3) Complexity and coupled systems, (4) Advances in remote sensing technology, (5) Development planning in the 21stcentury, (5a) The challenge for policy maker and scientist, (5b) Decision-making science, (5c) Role of public-private partnerships.

  18. The Contribution of a Decision Support System to Educational Decision-Making Processes

    ERIC Educational Resources Information Center

    Klein, Joseph; Ronen, Herman

    2003-01-01

    In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest…

  19. A Framework for Classifying Decision Support Systems

    PubMed Central

    Sim, Ida; Berlin, Amy

    2003-01-01

    Background Computer-based clinical decision support systems (CDSSs) vary greatly in design and function. A taxonomy for classifying CDSS structure and function would help efforts to describe and understand the variety of CDSSs in the literature, and to explore predictors of CDSS effectiveness and generalizability. Objective To define and test a taxonomy for characterizing the contextual, technical, and workflow features of CDSSs. Methods We retrieved and analyzed 150 English language articles published between 1975 and 2002 that described computer systems designed to assist physicians and/or patients with clinical decision making. We identified aspects of CDSS structure or function and iterated our taxonomy until additional article reviews did not result in any new descriptors or taxonomic modifications. Results Our taxonomy comprises 95 descriptors along 24 descriptive axes. These axes are in 5 categories: Context, Knowledge and Data Source, Decision Support, Information Delivery, and Workflow. The axes had an average of 3.96 coded choices each. 75% of the descriptors had an inter-rater agreement kappa of greater than 0.6. Conclusions We have defined and tested a comprehensive, multi-faceted taxonomy of CDSSs that shows promising reliability for classifying CDSSs reported in the literature. PMID:14728243

  20. Visual Decision Support Tool for Supporting Asset ...

    EPA Pesticide Factsheets

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

  1. The design of aircraft using the decision support problem technique

    NASA Technical Reports Server (NTRS)

    Mistree, Farrokh; Marinopoulos, Stergios; Jackson, David M.; Shupe, Jon A.

    1988-01-01

    The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems.

  2. 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

  3. Clinical Decision Support and Palivizumab

    PubMed Central

    Hogan, A.; Michel, J.; Localio, A.R.; Karavite, D.; Song, L.; Ramos, M.J.; Fiks, A.G.; Lorch, S.; Grundmeier, R.W.

    2015-01-01

    Background and Objectives Palivizumab can reduce hospitalizations due to respiratory syncytial virus (RSV), but many eligible infants fail to receive the full 5-dose series. The efficacy of clinical decision support (CDS) in fostering palivizumab receipt has not been studied. We sought a comprehensive solution for identifying eligible patients and addressing barriers to palivizumab administration. Methods We developed workflow and CDS tools targeting patient identification and palivizumab administration. We randomized 10 practices to receive palivizumab-focused CDS and 10 to receive comprehensive CDS for premature infants in a 3-year longitudinal cluster-randomized trial with 2 baseline and 1 intervention RSV seasons. Results There were 356 children eligible to receive palivizumab, with 194 in the palivizumab-focused group and 162 in the comprehensive CDS group. The proportion of doses administered to children in the palivizumab-focused intervention group increased from 68.4% and 65.5% in the two baseline seasons to 84.7% in the intervention season. In the comprehensive intervention group, proportions of doses administered declined during the baseline seasons (from 71.9% to 62.4%) with partial recovery to 67.9% during the intervention season. The palivizumab-focused group improved by 19.2 percentage points in the intervention season compared to the prior baseline season (p < 0.001), while the comprehensive intervention group only improved 5.5 percentage points (p = 0.288). The difference in change between study groups was significant (p = 0.05). Conclusions Workflow and CDS tools integrated in an EHR may increase the administration of palivizumab. The support focused on palivizumab, rather than comprehensive intervention, was more effective at improving palivizumab administration. PMID:26767069

  4. Intelligent decision support in process environments

    SciTech Connect

    Hollnagel, E.; Mancini, G.; Woods, D.D.

    1986-01-01

    This book deals with the basis for design of intelligent systems to support human decision-making in supervisory control, and provides a view of how human and artificial cognitive systems can interact. It covers the design and development of intelligent decision aiding systems, as well as the testing and evaluation. Topics discussed include: decision theory; cognitive engineering; systems engineering; and artificial intelligence.

  5. Decision Support Systems for Academic Administration.

    ERIC Educational Resources Information Center

    Moore, Laurence J.; Greenwood, Allen G.

    1984-01-01

    The history and features of Decision Support Systems (DSS) and use of the approach by academic administrators are discussed. The objective of DSS is to involve the manager/decision maker in the decision-analysis process while simultaneously relieving that person of the burden of developing and performing detailed analysis. DSS represents a…

  6. Technical challenges, past and future, in implementing THERESA: a one million patient, one billion item computer-based patient record and decision support system

    NASA Astrophysics Data System (ADS)

    Camp, Henry N.

    1996-02-01

    Challenges in implementing a computer-based patient record (CPR)--such as absolute data integrity, high availability, permanent on-line storage of very large complex records, rapid search times, ease of use, commercial viability, and portability to other hospitals and doctor's offices--are given along with their significance, the solutions, and their successes. The THERESA CPR has been used sine 1983 in direct patient care by a public hospital that is the primary care provider to 350,000 people. It has 1000 beds with 45,000 admissions and 750,000 outpatient visits annually. The system supports direct provider entry, including by physicians, of complete medical `documents'. Its demonstration site currently contains 1.1 billion data items on 1 million patients. It is also a clinical decision-aiding tool used for quality assurance and cost containment, for teaching as faculty and students can easily find and `thumb through' all cases similar to a particular study, and for research with over a billion medical items that can be searched and analyzed on-line within context and with continuity. The same software can also run in a desktop microcomputer managing a private practice physician's office.

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

    PubMed Central

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

    2016-01-01

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

  8. Personalizing Drug Selection Using Advanced Clinical Decision Support

    PubMed Central

    Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A.; Glauser, Tracy

    2009-01-01

    This article describes the process of developing an advanced pharmacogenetics clinical decision support at one of the United States’ leading pediatric academic medical centers. This system, called CHRISTINE, combines clinical and genetic data to identify the optimal drug therapy when treating patients with epilepsy or Attention Deficit Hyperactivity Disorder. In the discussion a description of clinical decision support systems is provided, along with an overview of neurocognitive computing and how it is applied in this setting. PMID:19898682

  9. Personalizing Drug Selection Using Advanced Clinical Decision Support.

    PubMed

    Pestian, John; Spencer, Malik; Matykiewicz, Pawel; Zhang, Kejian; Vinks, Alexander A; Glauser, Tracy

    2009-06-23

    This article describes the process of developing an advanced pharmacogenetics clinical decision support at one of the United States' leading pediatric academic medical centers. This system, called CHRISTINE, combines clinical and genetic data to identify the optimal drug therapy when treating patients with epilepsy or Attention Deficit Hyperactivity Disorder. In the discussion a description of clinical decision support systems is provided, along with an overview of neurocognitive computing and how it is applied in this setting.

  10. Computer Graphics and Administrative Decision-Making.

    ERIC Educational Resources Information Center

    Yost, Michael

    1984-01-01

    Reduction in prices now makes it possible for almost any institution to use computer graphics for administrative decision making and research. Current and potential uses of computer graphics in these two areas are discussed. (JN)

  11. Using Visualization in Cockpit Decision Support Systems

    SciTech Connect

    Aragon, Cecilia R.

    2005-07-01

    In order to safely operate their aircraft, pilots must makerapid decisions based on integrating and processing large amounts ofheterogeneous information. Visual displays are often the most efficientmethod of presenting safety-critical data to pilots in real time.However, care must be taken to ensure the pilot is provided with theappropriate amount of information to make effective decisions and notbecome cognitively overloaded. The results of two usability studies of aprototype airflow hazard visualization cockpit decision support systemare summarized. The studies demonstrate that such a system significantlyimproves the performance of helicopter pilots landing under turbulentconditions. Based on these results, design principles and implicationsfor cockpit decision support systems using visualization arepresented.

  12. Computational Toxicology as Implemented by the U.S. EPA: Providing High Throughput Decision Support Tools for Screening and Assessing Chemical Exposure, Hazard and Risk

    EPA Science Inventory

    Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environ...

  13. Computers and the Development of Design Decision Making Skills.

    ERIC Educational Resources Information Center

    Blandford, Ann; And Others

    1994-01-01

    Discussion of how to teach decision-making skills to undergraduate engineering design students highlights a computer-based decision support tool, WOMBAT (Weighted Objectives Method by Arguing with the Tutor). Changes in WOMBAT from an earlier version are described, and an example of dialog between a user and the system is included. (Contains 24…

  14. New approaches for real time decision support systems

    NASA Technical Reports Server (NTRS)

    Hair, D. Charles; Pickslay, Kent

    1994-01-01

    NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.

  15. A decision-supported outpatient practice system.

    PubMed Central

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

    1996-01-01

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

  16. Geospatial decision support systems for societal decision making

    USGS Publications Warehouse

    Bernknopf, R.L.

    2005-01-01

    While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the

  17. Multi-Objective Markov Decision Processes for Data-Driven Decision Support

    PubMed Central

    Lizotte, Daniel J.; Laber, Eric B.

    2016-01-01

    We present new methodology based on Multi-Objective Markov Decision Processes for developing sequential decision support systems from data. Our approach uses sequential decision-making data to provide support that is useful to many different decision-makers, each with different, potentially time-varying preference. To accomplish this, we develop an extension of fitted-Q iteration for multiple objectives that computes policies for all scalarization functions, i.e. preference functions, simultaneously from continuous-state, finite-horizon data. We identify and address several conceptual and computational challenges along the way, and we introduce a new solution concept that is appropriate when different actions have similar expected outcomes. Finally, we demonstrate an application of our method using data from the Clinical Antipsychotic Trials of Intervention Effectiveness and show that our approach offers decision-makers increased choice by a larger class of optimal policies. PMID:28018133

  18. Prolog: A Practical Language for Decision Support Systems in Nursing?

    PubMed Central

    Ozbolt, Judy G.

    1987-01-01

    Developing decision support systems for nursing has been limited by difficulties in defining and representing nursing's knowledge base and by a lack of knowledge of how nurses make decisions. Recent theoretical and empirical work offers solutions to those problems. The challenge now is to represent nursing knowledge in a way that is comprehensible to both nurse and computer and to design decision support modalities that are accurate, efficient, and appropriate for nurses with different levels of expertise. This paper reviews the issues and critically evaluates Prolog as a tool for meeting the challenge.

  19. Burn Resuscitation Decision Support System (BRDSS)

    DTIC Science & Technology

    2013-09-01

    CONTRACTING ORGANIZATION: Arcos , Inc. HoustonTX77018-5308 REPORT DATE: September 2013 TYPE OF REPORT: Annual PREPARED FOR: U.S. Army Medical... Arcos , Inc. 866 W. 41st St. Houston TX 77018-5308 The Burn Resuscitation Decision Support System (BRDSS) is a medical device designed to guide and...project: The Burn Resuscitation Decision Support System (BRDSS) Tablet project will be broken into four major phases. Throughout the project Arcos will

  20. Decision Support for Attack Submarine Commanders.

    DTIC Science & Technology

    1980-10-01

    AD-AO95 892 DECISION SCIENCE CONSORTIUM INC FALLS CHURCH VA F./e 12/2 DECISION SUPPORT FOR ATTACK SUBMARINE COMMANDERS. (U) OCT 80 M S COHEN, R V...BROWN N00014-80-C-0046 UNCLASSIFIED TR-8S-11 ML DECISIN IEN$CE CUIVSURTiUM, MrC. DECISION SUPPORT FOR A TTA CK SUBMARINE COMMANDERS Marvin S . Cohen and...on reverse) DDI ,o..ŕ 1473 EDITION OF I NOV 65 IS OISOLCTZ Unclassified S /N 0102-014-6601 1 SECURITY CLASIFICATION OF TNIS PAGE (10bon DW& tateo* 01

  1. Group decision support using Toulmin argument structures

    SciTech Connect

    Janssen, T. |; Sage, A.P.

    1996-12-31

    This paper addresses the need for sound science, technology, and management assessment relative to environmental policy decision making through an approach that involves a logical structure for evidence, a framed decision-making process, and an environment that encourages group participation. Toulmin-based logic possesses these characteristics and is used as the basis for development of a group decision support system. This system can support several user groups, such as pesticide policy-making experts, who can use the support system to state arguments for or against an important policy issue, and pest management experts, who can use the system to assist in identifying and evaluating alternatives for controlling pests on agricultural commodities. The resulting decision support system assists in improving the clarity of the lines of reasoning used in specific situations; the warrants, grounds, and backings that are used to support claims and specific lines of reasoning; and the contradictions, rebuttals, and arguments surrounding each step in the reasoning process associated with evaluating a claim or counterclaim. Experts and decisions makers with differing views can better understand each other`s thought processes. The net effect is enhanced communications and understanding of the whole picture and, in many cases, consensus on decisions to be taken.

  2. Using Visualization in Cockpit Decision Support Systems

    NASA Technical Reports Server (NTRS)

    Aragon, Cecilia R.

    2005-01-01

    In order to safely operate their aircraft, pilots must make rapid decisions based on integrating and processing large amounts of heterogeneous information. Visual displays are often the most efficient method of presenting safety-critical data to pilots in real time. However, care must be taken to ensure the pilot is provided with the appropriate amount of information to make effective decisions and not become cognitively overloaded. The results of two usability studies of a prototype airflow hazard visualization cockpit decision support system are summarized. The studies demonstrate that such a system significantly improves the performance of helicopter pilots landing under turbulent conditions. Based on these results, design principles and implications for cockpit decision support systems using visualization are presented.

  3. A decision support system for rainfed agricultural areas of Mexico

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rural inhabitants of arid lands lack sufficient water to fulfill their agricultural and household needs. They do not have readily available technical information to support decisions regarding the course of action they should follow to handle the agro-climatic risk. In this paper, a computer model (...

  4. Bayesian Decision Support for Adaptive Lung Treatments

    NASA Astrophysics Data System (ADS)

    McShan, Daniel; Luo, Yi; Schipper, Matt; TenHaken, Randall

    2014-03-01

    Purpose: A Bayesian Decision Network will be demonstrated to provide clinical decision support for adaptive lung response-driven treatment management based on evidence that physiologic metrics may correlate better with individual patient response than traditional (population-based) dose and volume-based metrics. Further, there is evidence that information obtained during the course of radiation therapy may further improve response predictions. Methods: Clinical factors were gathered for 58 patients including planned mean lung dose, and the bio-markers IL-8 and TGF-β1 obtained prior to treatment and two weeks into treatment along with complication outcomes for these patients. A Bayesian Decision Network was constructed using Netica 5.0.2 from Norsys linking these clinical factors to obtain a prediction of radiation induced lung disese (RILD) complication. A decision node was added to the network to provide a plan adaption recommendation based on the trade-off between the RILD prediction and complexity of replanning. A utility node provides the weighting cost between the competing factors. Results: The decision node predictions were optimized against the data for the 58 cases. With this decision network solution, one can consider the decision result for a new patient with specific findings to obtain a recommendation to adaptively modify the originally planned treatment course. Conclusions: A Bayesian approach allows handling and propagating probabilistic data in a logical and principled manner. Decision networks provide the further ability to provide utility-based trade-offs, reflecting non-medical but practical cost/benefit analysis. The network demonstrated illustrates the basic concept, but many other factors may affect these decisions and work on building better models are being designed and tested. Acknowledgement: Supported by NIH-P01-CA59827

  5. LIMSI @ 2014 Clinical Decision Support Track

    DTIC Science & Technology

    2014-11-01

    Clinical Decision Support 1 Introduction The goal of the Clinical Decision Support Track is to retrieve relevant biomedical articles given a patient record...queries: • Diagnosis: "diagnosis"[MeSH Terms] OR "diagnosis, oral"[MeSH Terms] OR "diagnostic equipment "[MeSH Terms] OR "diagnostic services"[MeSH Terms...particular biomedical domain or search strategy) that were created as part of the CISMeF project[2]3. The Test query was manually created for 3These and

  6. The Computer as Adaptive Instructional Decision Maker.

    ERIC Educational Resources Information Center

    Kopstein, Felix F.; Seidel, Robert J.

    The computer's potential for education, and most particularly for instruction, is contingent on the development of a class of instructional decision models (formal instructional strategies) that interact with the student through appropriate peripheral equipment (man-machine interfaces). Computer hardware and software by themselves should not be…

  7. Computerized Clinical Decision Support: Contributions from 2014

    PubMed Central

    Koutkias, V.

    2015-01-01

    Summary Objective To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term. PMID:26293858

  8. Computational toxicology as implemented by the U.S. EPA: providing high throughput decision support tools for screening and assessing chemical exposure, hazard and risk.

    PubMed

    Kavlock, Robert; Dix, David

    2010-02-01

    Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environmental Protection Agency EPA is developing robust and flexible computational tools that can be applied to the thousands of chemicals in commerce, and contaminant mixtures found in air, water, and hazardous-waste sites. The Office of Research and Development (ORD) Computational Toxicology Research Program (CTRP) is composed of three main elements. The largest component is the National Center for Computational Toxicology (NCCT), which was established in 2005 to coordinate research on chemical screening and prioritization, informatics, and systems modeling. The second element consists of related activities in the National Health and Environmental Effects Research Laboratory (NHEERL) and the National Exposure Research Laboratory (NERL). The third and final component consists of academic centers working on various aspects of computational toxicology and funded by the U.S. EPA Science to Achieve Results (STAR) program. Together these elements form the key components in the implementation of both the initial strategy, A Framework for a Computational Toxicology Research Program (U.S. EPA, 2003), and the newly released The U.S. Environmental Protection Agency's Strategic Plan for Evaluating the Toxicity of Chemicals (U.S. EPA, 2009a). Key intramural projects of the CTRP include digitizing legacy toxicity testing information toxicity reference database (ToxRefDB), predicting toxicity (ToxCast) and exposure (ExpoCast), and creating virtual liver (v-Liver) and virtual embryo (v-Embryo) systems models. U.S. EPA-funded STAR centers are also providing bioinformatics, computational toxicology data and models, and developmental toxicity data and models. The models and underlying data are being made publicly

  9. Quantitative Decision Support Requires Quantitative User Guidance

    NASA Astrophysics Data System (ADS)

    Smith, L. A.

    2009-12-01

    Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output

  10. Decision support system for nursing management control

    SciTech Connect

    Ernst, C.J.

    1983-01-01

    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.

  11. Query Reformulation for Clinical Decision Support Search

    DTIC Science & Technology

    2014-11-01

    Query Reformulation for Clinical Decision Support Search Luca Soldaini, Arman Cohan, Andrew Yates, Nazli Goharian, Ophir Frieder Information...work, we present a query reformulation approach that addresses the unique formulation of case reports, making them suitable to be used on a general... reformulation approach does not directly take into account the generic question type (diagnosis, test, treatment) provided with each approach. To ameliorate

  12. Modeling uncertainty in requirements engineering decision support

    NASA Technical Reports Server (NTRS)

    Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.

    2005-01-01

    One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

  13. System Engineering and Evolution Decision Support

    DTIC Science & Technology

    2007-11-02

    increasing the quality of service provided complex systems while reducing development risks, costs, and time. our work focused on decision support for...design synthesis. Mathematical models for implementing a set of automated and integrated engineering automation tools were also developed. Our work ...coordinating concurrent work by engineering teams. Our work will ensure design consistency and alleviate communication difficulties. The significance

  14. A Multiple Objective Decision Support Tool (MODS)

    SciTech Connect

    2003-12-14

    The Multiple Objective Decision Support (MODS) tool is an automated tool used to assist decision makers and policy analysts with multiple-objective decision problems. The classes of problems that this decision support tool addresses have both multiple objectives and multiple stakeholders. Decision problems, which have multiple objectives that in general cannot be maximized simultaneously, and multiple stakeholders, who have different perspectives about the relative importance of the objectives, require analytic approaches and tools that can provide flexible support to decision makers. This tool provides capabilities for the management, analysis, and graphical display for these types of decision problems drawn from diverse problem domains. The MODS tool is a unique integration of analysis algorithms, an information database, and a graphical user interface. This collection of algorithms, the combination of an information database with the analysis into a single tool, and the graphical user interface provides a technically advanced tool to decision makers and policy analysts. There are two main issues when addressing problems of this type: what set of attributes should be used to characterize the tokens in the domain of interest, and how should the values of these attributes and their weights be determined and combined to provide a relative ordering to the tokens. This tool addresses both of these issues. This decision support tool provides a flexible way to derive and use a chosen set of attributes. For example, the tool could be used to first perform a paired comparison of a large set of attributes and from this evaluation select those attributes that have the highest weights. The flexibility of the tool allows experimentation with various attribute sets and this capability, along with domain expertise, addresses the first issue. To address the second issue, several algorithms have been implemented. For example, two algorithms that have been implemented are the

  15. The conceptual foundation of environmental decision support.

    PubMed

    Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

    2015-05-01

    Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization.

  16. Management Needs for Computer Support.

    ERIC Educational Resources Information Center

    Irby, Alice J.

    University management has many and varied needs for effective computer services in support of their processing and information functions. The challenge for the computer center managers is to better understand these needs and assist in the development of effective and timely solutions. Management needs can range from accounting and payroll to…

  17. 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

  18. 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.

  19. Decision Support for Operations and Maintenance IV

    SciTech Connect

    2011-12-22

    DSOM (Decision Support for Operations and Maintenance) is an expert operations and maintenance system that integrates plant operations, fuel management, and maintenance processes. The DSOM package provides operators with the information they need for cost-effective operating decisions creating savings in fuel, personnel, maintenance, and plant life extension. DSOM provides operators real-time system performance information to allow them to determine if the plant is malfunctioning or running below expectations. By catching potential problems, DSOM enables plants to operate safely at peak efficiency, while providing a higher level of reliability and safety.

  20. Computer modeling of human decision making

    NASA Technical Reports Server (NTRS)

    Gevarter, William B.

    1991-01-01

    Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making.

  1. 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.

  2. Data Mining and Data Fusion for Enhanced Decision Support

    SciTech Connect

    Khan, Shiraj; Ganguly, Auroop R; Gupta, Amar

    2008-01-01

    The process of Data Mining converts information to knowledge by utilizing tools from the disciplines of computational statistics, database technologies, machine learning, signal processing, nonlinear dynamics, process modeling, simulation, and allied disciplines. Data Mining allows business problems to be analyzed from diverse perspectives, including dimensionality reduction, correlation and co-occurrence, clustering and classification, regression and forecasting, anomaly detection, and change analysis. The predictive insights generated from Data Mining can be further utilized through real-time analysis and decision sciences, as well as through human-driven analysis based on management by exceptions or by objectives, to generate actionable knowledge. The tools that enable the transformation of raw data to actionable predictive insights are collectively referred as Decision Support tools. This chapter presents a new formalization of the decision process, leading to a new Decision Superiority model, partially motivated by the Joint Directors of Laboratories (JDL) Data Fusion Model. In addition, it examines the growing importance of Data Fusion concepts.

  3. Executive Support Systems: An Innovation Decision Perspective

    DTIC Science & Technology

    1990-01-01

    account . The exception and annotation ability of MIDS alerted the executives to what was happening and prevented a ripple effect of overreactions...information directly to these executives, an executive support system (ESS) allows more effective analysis, control, planning, and decision making...Automated improve- ments to the management process have the potential to highly leverage the executive’s effectiveness . An ESS is a concept, a clustered IT

  4. Proactive and Adaptive Decision Support Study (PDS)

    DTIC Science & Technology

    2014-08-31

    Arlington, VA 22203-1995 703-696-2875 jeffrey.g.morrison@navy.mil Report Prepared By: Thomas G. Allen Boston Fusion Corp. 1 Van de Graaff Drive...7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Boston Fusion Corp.,1 Van de Graaff Drive, Suite 107,Burlington,MA,01803 8. PERFORMING...During August, the principal activities for Boston Fusion were related to the preparation for, and attendance at, the ONR Proactive Decision Support

  5. Best Practices in Clinical Decision Support

    PubMed Central

    Wright, Adam; Phansalkar, Shobha; Bloomrosen, Meryl; Jenders, Robert A.; Bobb, Anne M.; Halamka, John D.; Kuperman, Gilad; Payne, Thomas H.; Teasdale, S.; Vaida, A. J.; Bates, D. W.

    2010-01-01

    Background Evidence demonstrates that clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety. However, implementing and maintaining effective decision support interventions presents multiple technical and organizational challenges. Purpose To identify best practices for CDS, using the domain of preventive care reminders as an example. Methods We assembled a panel of experts in CDS and held a series of facilitated online and inperson discussions. We analyzed the results of these discussions using a grounded theory method to elicit themes and best practices. Results Eight best practice themes were identified as important: deliver CDS in the most appropriate ways, develop effective governance structures, consider use of incentives, be aware of workflow, keep content current, monitor and evaluate impact, maintain high quality data, and consider sharing content. Keys themes within each of these areas were also described. Conclusion Successful implementation of CDS requires consideration of both technical and socio-technical factors. The themes identified in this study provide guidance on crucial factors that need consideration when CDS is implemented across healthcare settings. These best practice themes may be useful for developers, implementers, and users of decision support. PMID:21991299

  6. SANDS - Sediment Analysis Network for Decision Support

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Hawkins, L.; He, M.; Ebersole, S.

    2010-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The SANDS project is also investigating the effects of sediment immersed oil from the Deepwater Horizon disaster in April 2010 which has the potential to resurface as a result of tropical storm activity. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The Sediment Analysis Network for Decision Support has generated a number of decision support products derived from MODIS, Landsat and SeaWiFS instruments that potentially support

  7. Sustaining the Army Training Mission by Re-Thinking Decision Support Systems: Shifting from Decision-Making Individuals to Sense-Making Agents

    DTIC Science & Technology

    2004-12-01

    traditional concept of decision making as a basically rational process ( Simon 1960). In an effort to reconceptualize decision making, this paper...originates in organization science ( Simon 1960). Decision Support Systems are computer technologies used to support complex decision making in...technical tools supporting the traditional concept of decision making as a basically rational process ( Simon 1960). The techno-centric character of DSS

  8. Supporting collaborative computing and interaction

    SciTech Connect

    Agarwal, Deborah; McParland, Charles; Perry, Marcia

    2002-05-22

    To enable collaboration on the daily tasks involved in scientific research, collaborative frameworks should provide lightweight and ubiquitous components that support a wide variety of interaction modes. We envision a collaborative environment as one that provides a persistent space within which participants can locate each other, exchange synchronous and asynchronous messages, share documents and applications, share workflow, and hold videoconferences. We are developing the Pervasive Collaborative Computing Environment (PCCE) as such an environment. The PCCE will provide integrated tools to support shared computing and task control and monitoring. This paper describes the PCCE and the rationale for its design.

  9. Issues of trust and ethics in computerized clinical decision support systems.

    PubMed

    Alexander, Gregory L

    2006-01-01

    Clinical decision support systems are computer technologies that model and provide support for human decision-making processes. Decision support mechanisms facilitate and enhance a clinician's ability to make decisions at the point of care. Decisions are facilitated through technology by using automated mechanisms that provide alerts or messages to clinicians about a potential patient problem. A clinician's level of trust in these technologies to support decision making is affected by how knowledge is represented in these tools, their ability to make reasonable decisions, and how they are designed. Furthermore, ethical tensions occur if these systems do not promote standards, if clinicians do not understand how to use these systems, and when professional relationships are affected. Issues of trust and ethical concerns will be examined in this article, using a research study of midwestern nursing homes that implemented a clinical decision support system.

  10. Business models for health care decision support.

    PubMed

    Gaughan, Phil

    2003-01-01

    CareScience, Inc. is a public company (NASDAQ: CARE) that originated ten years ago to commercialize risk adjustment and complication predictions developed by the Wharton School of Business and the University of Pennsylvania School of Medicine. Over the past decade, the company has grown to approximately 200 clients and 150 employees. Among the "firsts" recorded by the company, CareScience was the first to offer a clinical decision support system as an Application Service Provider (ASP), the first to offer peer-to-peer clinical data sharing among health care provider organizations and practitioners (Santa Barbara Care Data Exchange), and the first to provide a care management outsourcing arrangement.

  11. A Decision Support System for Optimum Use of Fertilizers

    SciTech Connect

    Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

  12. A Decision Support System for Optimum Use of Fertilizers

    SciTech Connect

    R. L. Hoskinson; J. R. Hess; R. K. Fink

    1999-07-01

    The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

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

    PubMed Central

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

    2016-01-01

    As utilization of clinical decision support (CDS) increases, it is important to continue the development and refinement of methods to accurately translate the intention of clinical practice guidelines (CPG) into a computable form. In this study, we validate and extend the 13 steps that Shiffman et al.5 identified for translating CPG knowledge for use in CDS. During an implementation project of ATHENA-CDS, we encoded complex CPG recommendations for five common chronic conditions for integration into an existing clinical dashboard. Major decisions made during the implementation process were recorded and categorized according to the 13 steps. During the implementation period, we categorized 119 decisions and identified 8 new categories required to complete the project. We provide details on an updated model that outlines all of the steps used to translate CPG knowledge into a CDS integrated with existing health information technology. PMID:28269916

  14. Linquistic geometry: new technology for decision support

    NASA Astrophysics Data System (ADS)

    Stilman, Boris; Yakhnis, Vladimir

    2003-09-01

    Linguistic Geometry (LG) is a revolutionary gaming approach which is ideally suited for military decision aids for Air, Ground, Naval, and Space-based operations, as well guiding robotic vehicles and traditional entertainment games. When thinking about modern or future military operations, the game metaphor comes to mind right away. Indeed, the air space together with the ground and seas may be viewed as a gigantic three-dimensional game board. Refining this picture, the LG approach is capable of providing an LG hypergame, that is, a system of multiple concurrent interconnected multi-player abstract board games (ABG) of various resolutions and time frames reflecting various kinds of hardware and effects involved in the battlespace and the solution space. By providing a hypergame representation of the battlespace, LG already provides a significant advance in situational awareness. However, the greatest advantage of the LG approach is an ability to provide commanders of campaigns and missions with decision options resulting in attainment of the commander's intent. At each game turn, an LG decision support tool assigns the best actions to each of the multitude of battlespace actors (UAVs, bombers, cruise missiles, etc.). This is done through utilization of algorithms finding winning strategies and tactics, which are the core of the LG approach.

  15. Creating clinical decision support systems for respiratory medicine.

    PubMed

    Tams, Carl G; Euliano, Neil R

    2015-01-01

    Clinical decision support systems are vital for advances in improving patient therapeutic care. We share lessons learned from creating two respiratory clinical decisions support systems for ventilating patients in a critical care setting.

  16. Sediment Analysis Network for Decision Support (SANDS)

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.

    2009-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The recently awarded Sediment Analysis Network for Decision Support will generate decision support products using NASA satellite observations from MODIS, Landsat and SeaWiFS instruments to support resource management, planning, and decision making activities in the Gulf of Mexico. Specifically, SANDS will generate decision support products that address the impacts of tropical storms

  17. Decision support software technology demonstration plan

    SciTech Connect

    SULLIVAN,T.; ARMSTRONG,A.

    1998-09-01

    The performance evaluation of innovative and alternative environmental technologies is an integral part of the US Environmental Protection Agency's (EPA) mission. Early efforts focused on evaluating technologies that supported the implementation of the Clean Air and Clean Water Acts. In 1986 the Agency began to demonstrate and evaluate the cost and performance of remediation and monitoring technologies under the Superfund Innovative Technology Evaluation (SITE) program (in response to the mandate in the Superfund Amendments and Reauthorization Act of 1986 (SARA)). In 1990, the US Technology Policy was announced. This policy placed a renewed emphasis on making the best use of technology in achieving the national goals of improved quality of life for all Americans, continued economic growth, and national security. In the spirit of the technology policy, the Agency began to direct a portion of its resources toward the promotion, recognition, acceptance, and use of US-developed innovative environmental technologies both domestically and abroad. Decision Support Software (DSS) packages integrate environmental data and simulation models into a framework for making site characterization, monitoring, and cleanup decisions. To limit the scope which will be addressed in this demonstration, three endpoints have been selected for evaluation: Visualization; Sample Optimization; and Cost/Benefit Analysis. Five topics are covered in this report: the objectives of the demonstration; the elements of the demonstration plan; an overview of the Site Characterization and Monitoring Technology Pilot; an overview of the technology verification process; and the purpose of this demonstration plan.

  18. Proceedings of the Workshop on The Human-Computer Partnership in Decision-Support Held in San Luis Obispo, California on May 2-4, 2000

    DTIC Science & Technology

    2000-09-01

    decision will rarely have a proportional cause. In other 6 Douglas C. Giancoli , The Ideas of Physics ...have a proportional cause. In other 6 Douglas C. Giancoli , The Ideas of Physics , Third Editon...until 1990. In 1990, he joined the Office of Naval Research as the Director of Chemistry. Since then, he has held the positions of Director of Physical

  19. Introduction to Decision Support Systems for Risk Based Management of Contaminated Sites

    EPA Science Inventory

    A book on Decision Support Systems for Risk-based Management of contaminated sites is appealing for two reasons. First, it addresses the problem of contaminated sites, which has worldwide importance. Second, it presents Decision Support Systems (DSSs), which are powerful comput...

  20. Intelligent Decisions? Intelligent Support? Agenda and Participants for the Internal Workshop on Intelligent Decision Support Systems : Retrospects and Prospects, August 29 - September 2, 2005, Certosa di Pontignano (Siena), Italy

    DTIC Science & Technology

    2005-09-01

    desired outcome obtains. This tradition is usually associated with Blaise Pascal and the invention of probability calculus, but can be found even earlier...41 12. KRAEMER, SARA & CARAYON, PASCALE : INFORMATION DECISION SUPPORT SYSTEMS IN COMPUTER AND INFORMATION SECURITY...KRAEMER, SARA & CARAYON, PASCALE : INFORMATION DECISION SUPPORT SYSTEMS IN COMPUTER AND INFORMATION SECURITY Over the past several decades, computer and

  1. How Decision Support Systems Can Benefit from a Theory of Change Approach.

    PubMed

    Allen, Will; Cruz, Jennyffer; Warburton, Bruce

    2017-03-09

    Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

  2. Decision investigation and support environment (DISE)

    NASA Astrophysics Data System (ADS)

    VonPlinsky, Michael J.; Johnson, Pete; Crowder, Ed

    2001-09-01

    The "Decision Integration and Support Environment" (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision process. FTI has developed two BNs to model these processes, incorporating aircraft, target, and overall mission priorities from the Air Operations Center (OAC) and the mission planners/command staff. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR Sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosectued, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process, including factors such as: * Fuel Level - amount of fuel in aircraft * Type of Weapon - available weapons on board aircraft * Probability of Survival - depends on the type of TST, time criticality and other factors * Potential Collateral Damage - amount of damage incurred on TST surroundings * Time Criticality of TST - how "critical" it is to attack the target depending on its launch status * Time to Target - aircraft's distance (in minutes) from the TST * Current Mission Priority - priority of the mission to which the aircraft is currently assigned * TST Mission Priority - determined when the target is originally nominated * Possible Reassignment - represents whether it is even possible to reassign the aircraft * Aircraft Re-tasking Availability - represents any factor not taken into account by the model, including commander override.

  3. Decision Support for Emergency Operations Centers

    NASA Technical Reports Server (NTRS)

    Harvey, Craig; Lawhead, Joel; Watts, Zack

    2005-01-01

    The Flood Disaster Mitigation Decision Support System (DSS) is a computerized information system that allows regional emergency-operations government officials to make decisions regarding the dispatch of resources in response to flooding. The DSS implements a real-time model of inundation utilizing recently acquired lidar elevation data as well as real-time data from flood gauges, and other instruments within and upstream of an area that is or could become flooded. The DSS information is updated as new data become available. The model generates realtime maps of flooded areas and predicts flood crests at specified locations. The inundation maps are overlaid with information on population densities, property values, hazardous materials, evacuation routes, official contact information, and other information needed for emergency response. The program maintains a database and a Web portal through which real-time data from instrumentation are gathered into the database. Also included in the database is a geographic information system, from which the program obtains the overlay data for areas of interest as needed. The portal makes some portions of the database accessible to the public. Access to other portions of the database is restricted to government officials according to various levels of authorization. The Flood Disaster Mitigation DSS has been integrated into a larger DSS named REACT (Real-time Emergency Action Coordination Tool), which also provides emergency operations managers with data for any type of impact area such as floods, fires, bomb

  4. Semantic technologies in a decision support system

    NASA Astrophysics Data System (ADS)

    Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

    2015-10-01

    The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

  5. A Customized Drought Decision Support Tool for Hsinchu Science Park

    NASA Astrophysics Data System (ADS)

    Huang, Jung; Tien, Yu-Chuan; Lin, Hsuan-Te; Liu, Tzu-Ming; Tung, Ching-Pin

    2016-04-01

    Climate change creates more challenges for water resources management. Due to the lack of sufficient precipitation in Taiwan in fall of 2014, many cities and counties suffered from water shortage during early 2015. Many companies in Hsinchu Science Park were significantly influenced and realized that they need a decision support tool to help them managing water resources. Therefore, a customized computer program was developed, which is capable of predicting the future status of public water supply system and water storage of factories when the water rationing is announced by the government. This program presented in this study for drought decision support (DDSS) is a customized model for a semiconductor company in the Hsinchu Science Park. The DDSS is programmed in Java which is a platform-independent language. System requirements are any PC with the operating system above Windows XP and an installed Java SE Runtime Environment 7. The DDSS serves two main functions. First function is to predict the future storage of Baoshan Reservoir and Second Baoshan Reservoir, so to determine the time point of water use restriction in Hsinchu Science Park. Second function is to use the results to help the company to make decisions to trigger their response plans. The DDSS can conduct real-time scenario simulations calculating the possible storage of water tank for each factory with pre-implementation and post-implementation of those response plans. In addition, DDSS can create reports in Excel to help decision makers to compare results between different scenarios.

  6. Evaluation of fuzzy relation method for medical decision support.

    PubMed

    Wagholikar, Kavishwar; Mangrulkar, Sanjeev; Deshpande, Ashok; Sundararajan, Vijayraghavan

    2012-02-01

    The potential of computer based tools to assist physicians in medical decision making, was envisaged five decades ago. Apart from factors like usability, integration with work-flow and natural language processing, lack of decision accuracy of the tools has hindered their utility. Hence, research to develop accurate algorithms for medical decision support tools, is required. Pioneering research in last two decades, has demonstrated the utility of fuzzy set theory for medical domain. Recently, Wagholikar and Deshpande proposed a fuzzy relation based method (FR) for medical diagnosis. In their case studies for heart and infectious diseases, the FR method was found to be better than naive bayes (NB). However, the datasets in their studies were small and included only categorical symptoms. Hence, more evaluative studies are required for drawing general conclusions. In the present paper, we compare the classification performance of FR with NB, for a variety of medical datasets. Our results indicate that the FR method is useful for classification problems in the medical domain, and that FR is marginally better than NB. However, the performance of FR is significantly better for datasets having high proportion of unknown attribute values. Such datasets occur in problems involving linguistic information, where FR can be particularly useful. Our empirical study will benefit medical researchers in the choice of algorithms for decision support tools.

  7. Decision Support for Patient Preference-based Care Planning

    PubMed Central

    Ruland, Cornelia M.

    1999-01-01

    Objective: While preference elicitation techniques have been effective in helping patients make decisions consistent with their preferences, little is known about whether information about patient preferences affects clinicians in clinical decision making and improves patient outcomes. The purpose of this study was to evaluate a decision support system for eliciting elderly patients' preferences for self-care capability and providing this information to nurses in clinical practice—specifically, its effect on nurses' care priorities and the patient outcomes of preference achievement and patient satisfaction. Design: Three-group quasi-experimental design with one experimental and two control groups (N = 151). In the experimental group computer-processed information about individual patient's preferences was placed in patients' charts to be used for care planning. Results: Information about patient preferences changed nurses' care priorities to be more consistent with patient preferences and improved patients' preference achievement and physical functioning. Further, higher consistency between patient preferences and nurses' care priorities was associated with higher preference achievement, and higher preference achievement with greater patient satisfaction. Conclusion: This study demonstrated that decision support for eliciting patient preferences and including them in nursing care planning is an effective and feasible strategy for improving nursing care and patient outcomes. PMID:10428003

  8. Reducing Risk with Clinical Decision Support

    PubMed Central

    Maloney, F.L.; Feblowitz, J.; Samal, L.; Sato, L.; Wright, A.

    2014-01-01

    Summary Objective Identify clinical opportunities to intervene to prevent a malpractice event and determine the proportion of malpractice claims potentially preventable by clinical decision support (CDS). Materials and Methods Cross-sectional review of closed malpractice claims over seven years from one malpractice insurance company and seven hospitals in the Boston area. For each event, clinical opportunities to intervene to avert the malpractice event and the presence or absence of CDS that might have a role in preventing the event, were assigned by a panel of expert raters. Compensation paid out to resolve a claim (indemnity), was associated with each CDS type. Results Of the 477 closed malpractice cases, 359 (75.3%) were categorized as substantiated and 195 (54%) had at least one opportunity to intervene. Common opportunities to intervene related to performance of procedure, diagnosis, and fall prevention. We identified at least one CDS type for 63% of substantiated claims. The 41 CDS types identified included clinically significant test result alerting, diagnostic decision support and electronic tracking of instruments. Cases with at least one associated intervention accounted for $40.3 million (58.9%) of indemnity. Discussion CDS systems and other forms of health information technology (HIT) are expected to improve quality of care, but their potential to mitigate risk had not previously been quantified. Our results suggest that, in addition to their known benefits for quality and safety, CDS systems within HIT have a potential role in decreasing malpractice payments. Conclusion More than half of malpractice events and over $40 million of indemnity were potentially preventable with CDS. PMID:25298814

  9. A Proposed Computer-Assisted Decision Making System for the Hellenic Navy Decision Makers

    DTIC Science & Technology

    1987-03-01

    creates and sustains a corporate moral code. It appears that nations with a long history, especially of fighting defensive wars, are’ more likely to...experiences and needs of the potential adopters. An idea that is not comnatible with the prevalent values and norms of a cultural and social Estem will...Decision Support Systems, ed: \\V. C. House, Petrocelli Books, New YorK/Princeton, 1983. " Corporate war rooms pluginto the computer," Business Week, August

  10. A Four-Phase Model of the Evolution of Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    Background A large body of evidence over many years suggests that clinical decision support systems can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. However, to this day, clinical decision support systems are not widely used outside of a small number of sites. One reason why decision support systems are not widely used is the relative difficulty of integrating such systems into clinical workflows and computer systems. Purpose To review and synthesize the history of clinical decision support systems, and to propose a model of various architectures for integrating clinical decision support systems with clinical systems. Methods The authors conducted an extensive review of the clinical decision support literature since 1959, sequenced the systems and developed a model. Results The model developed consists of four phases: standalone decision support systems, decision support integrated into clinical systems, standards for sharing clinical decision support content and service models for decision support. These four phases have not heretofore been identified, but they track remarkably well with the chronological history of clinical decision support, and show evolving and increasingly sophisticated attempts to ease integrating decision support systems into clinical workflows and other clinical systems. Conclusions Each of the four evolutionary approaches to decision support architecture has unique advantages and disadvantages. A key lesson was that there were common limitations that almost all the approaches faced, and no single approach has been able to entirely surmount: 1) fixed knowledge representation systems inherently circumscribe the type of knowledge that can be represented in them, 2) there are serious terminological issues, 3) patient data may be spread across several sources with no single source having a complete view of the patient, and 4) major difficulties exist in transferring successful interventions from one

  11. A rule-based clinical decision model to support interpretation of multiple data in health examinations.

    PubMed

    Kuo, Kuan-Liang; Fuh, Chiou-Shann

    2011-12-01

    Health examinations can obtain relatively complete health information and thus are important for the personal and public health management. For clinicians, one of the most important works in the health examinations is to interpret the health examination results. Continuously interpreting numerous health examination results of healthcare receivers is tedious and error-prone. This paper proposes a clinical decision support system to assist solving above problems. In order to customize the clinical decision support system intuitively and flexibly, this paper also proposes the rule syntax to implement computer-interpretable logic for health examinations. It is our purpose in this paper to describe the methodology of the proposed clinical decision support system. The evaluation was performed by the implementation and execution of decision rules on health examination results and a survey on clinical decision support system users. It reveals the efficiency and user satisfaction of proposed clinical decision support system. Positive impact of clinical data interpretation is also noted.

  12. Human Decision Processes: Implications for SSA Support Tools

    NASA Astrophysics Data System (ADS)

    Picciano, P.

    2013-09-01

    Despite significant advances in computing power and artificial intelligence (AI), few critical decisions are made without a human decision maker in the loop. Space Situational Awareness (SSA) missions are both critical and complex, typically adhering to the human-in-the-loop (HITL) model. The collection of human operators injects a needed diversity of expert knowledge, experience, and authority required to successfully fulfill SSA tasking. A wealth of literature on human decision making exists citing myriad empirical studies and offering a varied set of prescriptive and descriptive models of judgment and decision making (Hastie & Dawes, 2001; Baron, 2000). Many findings have been proven sufficiently robust to allow information architects or system/interface designers to take action to improve decision processes. For the purpose of discussion, these concepts are bifurcated in two groups: 1) vulnerabilities to mitigate, and 2) capabilities to augment. These vulnerabilities and capabilities refer specifically to the decision process and should not be confused with a shortcoming or skill of a specific human operator. Thus the framing of questions and orders, the automated tools with which to collaborate, priming and contextual data, and the delivery of information all play a critical role in human judgment and choice. Evaluating the merits of any decision can be elusive; in order to constrain this discussion, ‘rational choice' will tend toward the economic model characteristics such as maximizing utility and selection consistency (e.g., if A preferred to B, and B preferred to C, than A should be preferred to C). Simple decision models often encourage one to list the pros and cons of a decision, perhaps use a weighting schema, but one way or another weigh the future benefit (or harm) of making a selection. The result (sought by the rationalist models) should drive toward higher utility. Despite notable differences in researchers' theses (to be discussed in the full

  13. Emulation Modeling with Bayesian Networks for Efficient Decision Support

    NASA Astrophysics Data System (ADS)

    Fienen, M. N.; Masterson, J.; Plant, N. G.; Gutierrez, B. T.; Thieler, E. R.

    2012-12-01

    Bayesian decision networks (BDN) have long been used to provide decision support in systems that require explicit consideration of uncertainty; applications range from ecology to medical diagnostics and terrorism threat assessments. Until recently, however, few studies have applied BDNs to the study of groundwater systems. BDNs are particularly useful for representing real-world system variability by synthesizing a range of hydrogeologic situations within a single simulation. Because BDN output is cast in terms of probability—an output desired by decision makers—they explicitly incorporate the uncertainty of a system. BDNs can thus serve as a more efficient alternative to other uncertainty characterization methods such as computationally demanding Monte Carlo analyses and others methods restricted to linear model analyses. We present a unique application of a BDN to a groundwater modeling analysis of the hydrologic response of Assateague Island, Maryland to sea-level rise. Using both input and output variables of the modeled groundwater response to different sea-level (SLR) rise scenarios, the BDN predicts the probability of changes in the depth to fresh water, which exerts an important influence on physical and biological island evolution. Input variables included barrier-island width, maximum island elevation, and aquifer recharge. The variability of these inputs and their corresponding outputs are sampled along cross sections in a single model run to form an ensemble of input/output pairs. The BDN outputs, which are the posterior distributions of water table conditions for the sea-level rise scenarios, are evaluated through error analysis and cross-validation to assess both fit to training data and predictive power. The key benefit for using BDNs in groundwater modeling analyses is that they provide a method for distilling complex model results into predictions with associated uncertainty, which is useful to decision makers. Future efforts incorporate

  14. 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.

  15. Clinical Decision Support Systems for the Practice of Evidence-based Medicine

    PubMed Central

    Sim, Ida; Gorman, Paul; Greenes, Robert A.; Haynes, R. Brian; Kaplan, Bonnie; Lehmann, Harold; Tang, Paul C.

    2001-01-01

    Background: The use of clinical decision support systems to facilitate the practice of evidence-based medicine promises to substantially improve health care quality. Objective: To describe, on the basis of the proceedings of the Evidence and Decision Support track at the 2000 AMIA Spring Symposium, the research and policy challenges for capturing research and practice-based evidence in machine-interpretable repositories, and to present recommendations for accelerating the development and adoption of clinical decision support systems for evidence-based medicine. Results: The recommendations fall into five broad areas—capture literature-based and practice-based evidence in machine-interpretable knowledge bases; develop maintainable technical and methodological foundations for computer-based decision support; evaluate the clinical effects and costs of clinical decision support systems and the ways clinical decision support systems affect and are affected by professional and organizational practices; identify and disseminate best practices for work flow–sensitive implementations of clinical decision support systems; and establish public policies that provide incentives for implementing clinical decision support systems to improve health care quality. Conclusions: Although the promise of clinical decision support system–facilitated evidence-based medicine is strong, substantial work remains to be done to realize the potential benefits. PMID:11687560

  16. 12 CFR 944.4 - Decision on community support statements.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Decision on community support statements. 944.4 Section 944.4 Banks and Banking FEDERAL HOUSING FINANCE BOARD FEDERAL HOME LOAN BANK MISSION COMMUNITY SUPPORT REQUIREMENTS § 944.4 Decision on community support statements. (a) Action on community...

  17. WaterlooClarke: TREC 2015 Clinical Decision Support Track

    DTIC Science & Technology

    2015-11-20

    WaterlooClarke: TREC 2015 Clinical Decision Support Track Amira Ghenai1, Eldar Khalilov1, Pavel Valov1, and Charles L. A. Clarke1 1Department of...Abstract Clinical decision support systems help physicians with finding additional information about a partic- ular medical case. In this paper, we...develop a clinical decision support system that, based on a short medical case description, can recommend research articles to answer some common

  18. A Framework and Model for Evaluating Clinical Decision Support Architectures

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper, we develop a four-phase model for evaluating architectures for clinical decision support that focuses on: defining a set of desirable features for a decision support architecture; building a proof-of-concept prototype; demonstrating that the architecture is useful by showing that it can be integrated with existing decision support systems and comparing its coverage to that of other architectures. We apply this framework to several well-known decision support architectures, including Arden Syntax, GLIF, SEBASTIAN and SAGE PMID:18462999

  19. HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS

    EPA Science Inventory

    Decision makers using environmental decision support tools are often confronted with information that predicts a multitude of different human health effects due to environmental stressors. If these health effects need to be contrasted with costs or compared with alternative scena...

  20. Clinical Decision Support Systems and Prevention

    PubMed Central

    Njie, Gibril J.; Proia, Krista K.; Thota, Anilkrishna B.; Finnie, Ramona K.C.; Hopkins, David P.; Banks, Starr M.; Callahan, David B.; Pronk, Nicolaas P.; Rask, Kimberly J.; Lackland, Daniel T.; Kottke, Thomas E.

    2016-01-01

    Context Clinical decision support systems (CDSSs) can help clinicians assess cardiovascular disease (CVD) risk and manage CVD risk factors by providing tailored assessments and treatment recommendations based on individual patient data. The goal of this systematic review was to examine the effectiveness of CDSSs in improving screening for CVD risk factors, practices for CVD-related preventive care services such as clinical tests and prescribed treatments, and management of CVD risk factors. Evidence acquisition An existing systematic review (search period, January 1975–January 2011) of CDSSs for any condition was initially identified. Studies of CDSSs that focused on CVD prevention in that review were combined with studies identified through an updated search (January 2011–October 2012). Data analysis was conducted in 2013. Evidence synthesis A total of 45 studies qualified for inclusion in the review. Improvements were seen for recommended screening and other preventive care services completed by clinicians, recommended clinical tests completed by clinicians, and recommended treatments prescribed by clinicians (median increases of 3.8, 4.0, and 2.0 percentage points, respectively). Results were inconsistent for changes in CVD risk factors such as systolic and diastolic blood pressure, total and low-density lipoprotein cholesterol, and hemoglobin A1C levels. Conclusions CDSSs are effective in improving clinician practices related to screening and other preventive care services, clinical tests, and treatments. However, more evidence is needed from implementation of CDSSs within the broad context of comprehensive service delivery aimed at reducing CVD risk and CVD-related morbidity and mortality. PMID:26477805

  1. Real-time decision support and information gathering system for financial domain

    NASA Astrophysics Data System (ADS)

    Tseng, Chiu-Che; Gmytrasiewicz, Piotr J.

    2006-05-01

    The challenge of the investment domain is that a large amount of diverse information can be potentially relevant to an investment decision, and that, frequently, the decisions have to be made in a timely manner. This presents the potential for better decision support, but poses the challenge of building a decision support agent that gathers information from different sources and incorporates it for timely decision support. These problems motivate us to investigate ways in which the investors can be equipped with a flexible real-time decision support system to be practical in time-critical situations. The flexible real-time decision support system considers a tradeoff between decision quality and computation cost. For this purpose, we propose a system that uses the object oriented Bayesian knowledge base (OOBKB) design to create a decision model at the most suitable level of detail to guide the information gathering activities, and to produce an investment recommendation within a reasonable length of time. The decision models our system uses are implemented as influence diagrams. We validate our system with experiments in a simplified investment domain. The experiments show that our system produces a quality recommendation under different urgency situations. The contribution of our system is that it provides the flexible decision recommendation for an investor under time constraints in a complex environment.

  2. 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.

  3. Reliability analysis framework for computer-assisted medical decision systems

    SciTech Connect

    Habas, Piotr A.; Zurada, Jacek M.; Elmaghraby, Adel S.; Tourassi, Georgia D.

    2007-02-15

    We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

  4. Reef Ecosystem Services and Decision Support Database

    EPA Science Inventory

    This scientific and management information database utilizes systems thinking to describe the linkages between decisions, human activities, and provisioning of reef ecosystem goods and services. This database provides: (1) Hierarchy of related topics - Click on topics to navigat...

  5. Future of electronic health records: implications for decision support.

    PubMed

    Rothman, Brian; Leonard, Joan C; Vigoda, Michael M

    2012-01-01

    The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data

  6. Military Medical Decision Support for Homeland Defense During Emergency

    DTIC Science & Technology

    2004-12-01

    Integrated Decision Support ( MERMAIDS ) developed for training of emergency response teams using heterogeneous resources under a unified command and control...The MERMAIDS has been designed to contain a decision-centric interface, which is not only useful for emergency information management, but has...decision models to support response planning during emergency conditions. An expert heuristic evaluation of the MERMAIDS is encouraging. The expert

  7. Becoming a Mother: Supported Decision-Making in Context

    ERIC Educational Resources Information Center

    Jamieson, Rhiann; Theodore, Kate; Raczka, Roman

    2016-01-01

    Little is known about how women with intellectual disabilities make decisions in relation to pregnancy. Social support is important for mothers with intellectual disabilities in many areas. This study explored how the support network influenced the decision-making of women with intellectual disabilities in relation to pregnancy. The study extended…

  8. Development of Asset Management Decision Support Tools for Power Equipment

    NASA Astrophysics Data System (ADS)

    Okamoto, Tatsuki; Takahashi, Tsuguhiro

    Development of asset management decision support tools become very intensive in order to reduce maintenance cost of power equipment due to the liberalization of power business. This article reviews some aspects of present status of asset management decision support tools development for power equipment based on the papers published in international conferences, domestic conventions, and several journals.

  9. Automation and Accountability in Decision Support System Interface Design

    ERIC Educational Resources Information Center

    Cummings, Mary L.

    2006-01-01

    When the human element is introduced into decision support system design, entirely new layers of social and ethical issues emerge but are not always recognized as such. This paper discusses those ethical and social impact issues specific to decision support systems and highlights areas that interface designers should consider during design with an…

  10. Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

    ERIC Educational Resources Information Center

    Erskine, Michael A.

    2013-01-01

    As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…

  11. 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.

  12. Proactive and Adaptive Decision Support Study (PDS)

    DTIC Science & Technology

    2014-12-09

    Approved for public release; distribution unlimited. • DMOC-, N3- and N6-specific CCIRs • GCCS-M • C2RPC / MTC2 SOA • ENMS and other network health...Process RFI Request for Information SMDP Semi-Markov decision process SOA Service-Oriented Architecture SOP Standard Operating Procedure TTP Tactics, Techniques, and Procedures

  13. Environmental Decision Support with Consistent Metrics

    EPA Science Inventory

    One of the most effective ways to pursue environmental progress is through the use of consistent metrics within a decision making framework. The US Environmental Protection Agency’s Sustainable Technology Division has developed TRACI, the Tool for the Reduction and Assessment of...

  14. Management Needs for Computer Support.

    ERIC Educational Resources Information Center

    Irby, Alice J.

    1978-01-01

    The many and varied demands on university computer services are discussed and the importance of an effective data processing system for university management is emphasized. Case studies of computer use in admissions, registration, and billing are presented as well as the role of top level management in implementing data processing. (BH)

  15. Implementing an integrative multi-agent clinical decision support system with open source software.

    PubMed

    Sayyad Shirabad, Jelber; Wilk, Szymon; Michalowski, Wojtek; Farion, Ken

    2012-02-01

    Clinical decision making is a complex multi-stage process. Decision support can play an important role at each stage of this process. At present, the majority of clinical decision support systems have been focused on supporting only certain stages. In this paper we present the design and implementation of MET3-a prototype multi-agent system providing an integrative decision support that spans over the entire decision making process. The system helps physicians with data collection, diagnosis formulation, treatment planning and finding supporting evidence. MET3 integrates with external hospital information systems via HL7 messages and runs on various computing platforms available at the point of care (e.g., tablet computers, mobile phones). Building MET3 required sophisticated and reliable software technologies. In the past decade the open source software movement has produced mature, stable, industrial strength software systems with a large user base. Therefore, one of the decisions that should be considered before developing or acquiring a decision support system is whether or not one could use open source technologies instead of proprietary ones. We believe MET3 shows that the answer to this question is positive.

  16. Space-time statistics for decision support to smart farming.

    PubMed

    Stein, A; Hoosbeek, M R; Sterk, G

    1997-01-01

    This paper summarizes statistical procedures which are useful for precision farming at different scales. Three topics are addressed: spatial comparison of scenarios for land use, analysis of data in the space-time domain, and sampling in space and time. The first study compares six scenarios for nitrate leaching to ground water. Disjunctive cokriging reduces the computing time by 80% without loss of accuracy. The second study analyses wind erosion during four storms in a field in Niger measured with 21 devices. We investigated the use of temporal replicates to overcome the lack of spatial data. The third study analyses the effects of sampling in space and time for soil nutrient data in a Southwest African field. We concluded that statistical procedures are indispensable for decision support to smart farming.

  17. A computational framework for supporting environmental ...

    EPA Pesticide Factsheets

    GLIMPSE is a effort in which the U.S. EPA Office of Research and Development is developing tools to support long-term, coordinated environmental, climate, and energy planning. The purpose of this presentation is to discuss the underlying science questions; provide an overview of current and future GLIMPSE capabilities; introduce GCAM, the computational engine behind GLIMPSE; and, highlight relevant activities in China, including the ABaCAS framework and GCAM-China. A group of Chinese visitors will be on the EPA RTP campus July 28, 9-noon. The visitors are from the PowerChina Huadong Engineering Corporation (weblink is here: http://www.ecidi.com/en/introduction.aspx) and are in US for a training program at Duke. The group is interested in broad management topics such as international business development and managing environmental projects as well as interacting with practitioners to understand “real world” case studies and issues. Their background is primarily related to hydro power but their corporate mission is “Providing engineering services and promoting harmonious development between Man and Nature,” implying a broad interest in the environment. Several researchers with projects with connections to China have been asked to provide an overview of their research to the visitors. I will be talking about the GLIMPSE air-climate-energy decision support project.

  18. Exploration Clinical Decision Support System: Medical Data Architecture

    NASA Technical Reports Server (NTRS)

    Lindsey, Tony; Shetye, Sandeep; Shaw, Tianna (Editor)

    2016-01-01

    The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear

  19. Mobile decision support for transplantation patient data.

    PubMed

    Krause, Andreas; Hartl, Dominik; Theis, Fabian; Stangl, Manfred; Gerauer, Klaus E; Mehlhorn, Alexander T

    2004-06-15

    In high-critical medical fields instant information delivery is essential. Task-flow analyses within the transplantation unit of the Technische Universität München revealed that valuable time could be saved in pre-transplantation management being able to retrieve data of organ receivers ubiquitously. Inspired by this clinical scenario, a mobile application was designed and implemented providing surgeons with decision-relevant information on potential organ receivers. It assists them in considering the prospects of forthcoming organ transplantations and facilitates decision making and documentation with regard to high security demands. The described system services three organ receiver lists and is used by the surgeons in every transplantation procedure. After a 6-month period of clinical usage, the system has been evaluated in terms of handling, clinical benefit and total time savings. Intuitive, ubiquitous access to decision-relevant patient data and authenticated documentation were the major improvements with average total time savings of 50 min in comparison to the old system.

  20. Decision support for redesigning wastewater treatment technologies.

    PubMed

    McConville, Jennifer R; Künzle, Rahel; Messmer, Ulrike; Udert, Kai M; Larsen, Tove A

    2014-10-21

    This paper offers a methodology for structuring the design space for innovative process engineering technology development. The methodology is exemplified in the evaluation of a wide variety of treatment technologies for source-separated domestic wastewater within the scope of the Reinvent the Toilet Challenge. It offers a methodology for narrowing down the decision-making field based on a strict interpretation of treatment objectives for undiluted urine and dry feces and macroenvironmental factors (STEEPLED analysis) which influence decision criteria. Such an evaluation identifies promising paths for technology development such as focusing on space-saving processes or the need for more innovation in low-cost, energy-efficient urine treatment methods. Critical macroenvironmental factors, such as housing density, transportation infrastructure, and climate conditions were found to affect technology decisions regarding reactor volume, weight of outputs, energy consumption, atmospheric emissions, investment cost, and net revenue. The analysis also identified a number of qualitative factors that should be carefully weighed when pursuing technology development; such as availability of O&M resources, health and safety goals, and other ethical issues. Use of this methodology allows for coevolution of innovative technology within context constraints; however, for full-scale technology choices in the field, only very mature technologies can be evaluated.

  1. Decision support systems for robotic surgery and acute care

    NASA Astrophysics Data System (ADS)

    Kazanzides, Peter

    2012-06-01

    Doctors must frequently make decisions during medical treatment, whether in an acute care facility, such as an Intensive Care Unit (ICU), or in an operating room. These decisions rely on a various information sources, such as the patient's medical history, preoperative images, and general medical knowledge. Decision support systems can assist by facilitating access to this information when and where it is needed. This paper presents some research eorts that address the integration of information with clinical practice. The example systems include a clinical decision support system (CDSS) for pediatric traumatic brain injury, an augmented reality head- mounted display for neurosurgery, and an augmented reality telerobotic system for minimally-invasive surgery. While these are dierent systems and applications, they share the common theme of providing information to support clinical decisions and actions, whether the actions are performed with the surgeon's own hands or with robotic assistance.

  2. Computing support for High Energy Physics

    SciTech Connect

    Avery, P.; Yelton, J.

    1996-12-01

    This computing proposal (Task S) is submitted separately but in support of the High Energy Experiment (CLEO, Fermilab, CMS) and Theory tasks. The authors have built a very strong computing base at Florida over the past 8 years. In fact, computing has been one of the main contributions to their experimental collaborations, involving not just computing capacity for running Monte Carlos and data reduction, but participation in many computing initiatives, industrial partnerships, computing committees and collaborations. These facts justify the submission of a separate computing proposal.

  3. Decision Support Framework (DSF) Team Research Implementation Plan

    EPA Science Inventory

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

  4. Personal Computer Ownership--A Major Decision.

    ERIC Educational Resources Information Center

    Collins, Eleanor M.

    1982-01-01

    Considerations to be taken into account before buying a home computer include one's attitude toward computers, need, cost, and available space. A personal computer can be beneficial as a tutor, entertainer, record-keeper, and aid to the handicapped. Home economists must attempt to understand the implications of home computers for family life. (JOW)

  5. Neural and computational mechanisms of postponed decisions

    PubMed Central

    Martínez-García, Marina; Rolls, Edmund T.; Deco, Gustavo; Romo, Ranulfo

    2011-01-01

    We consider the mechanisms that enable decisions to be postponed for a period after the evidence has been provided. Using an information theoretic approach, we show that information about the forthcoming action becomes available from the activity of neurons in the medial premotor cortex in a sequential decision-making task after the second stimulus is applied, providing the information for a decision about whether the first or second stimulus is higher in vibrotactile frequency. The information then decays in a 3-s delay period in which the neuronal activity declines before the behavioral response can be made. The information then increases again when the behavioral response is required. We model this neuronal activity using an attractor decision-making network in which information reflecting the decision is maintained at a low level during the delay period, and is then selectively restored by a nonspecific input when the response is required. One mechanism for the short-term memory is synaptic facilitation, which can implement a mechanism for postponed decisions that can be correct even when there is little neuronal firing during the delay period before the postponed decision. Another mechanism is graded firing rates by different neurons in the delay period, with restoration by the nonspecific input of the low-rate activity from the higher-rate neurons still firing in the delay period. These mechanisms can account for the decision making and for the memory of the decision before a response can be made, which are evident in the activity of neurons in the medial premotor cortex. PMID:21709222

  6. The approaches for the decision support in case natural hazards

    NASA Astrophysics Data System (ADS)

    Vyazilov, Evgeny; Chunyaev, Nikita

    2013-04-01

    In spite of using highly automated systems of measurement, collecting, storing, handling, prediction and delivery of information on the marine environment, including natural hazards, the amount of damage from natural phenomena increases. Because information on the marine environment delivered to the industrial facilities not effectively used. To such information pays little attention by individual decision-makers and not always perform preventive measures necessary for reduce and prevent damage. Automation of information support will improve the efficiency management of the marine activities. In Russia develops "The Unified system of the information about World ocean" (ESIMO, http://esimo.ru/), that integrates observation, analysis, prognostic and climate data. Necessary to create tools to automatic selection natural disasters through all integrated data; notification decision-makers about arising natural hazards - software agent; provision of information in a compact form for the decision-makers; assessment of possible damage and costs to the preventive measures; providing information on the impacts of environment on economic facilities and recommendations for decision-making; the use of maps, diagrams, tables for reporting. Tools for automatic selection designed for identification of natural phenomena based on the resources ESIMO and corresponding critical values of the indicators environment. The result of this module will be constantly updated database of critical situations of environment for each object or technological process. To operational notify and provide current information about natural hazards proposes using a software agent that is installed on the computer decision-makers, which is activated in case critical situations and provides a minimum of information. In the event of natural disaster software agent should be able to inform decision-makers about this, providing information on the current situation, and the possibility for more and detailed

  7. A decision-support system for off-site nuclear emergencies.

    PubMed

    Yihua, X; Lin, G; Su, P; Tiefu, L; Honghui, X; Yongxing, Z; Xinzeng, S

    1998-03-01

    In the case of a nuclear emergency, quick, well-founded decisions must be made about the type of protective action, its region of application, and initiation time. These typically are tasks for computer-based systems. Even with emergency-preparedness, exercises, and training, the decision-support system is one of great importance. This paper describes a decision-support system recently developed by the China Institute of Atomic Energy; it can optimally rank actions during the early phase of an accident using multiattribute utility analysis, and for the intermediate and later phases by cost-benefit analysis. This system runs both on MICRO VAX II and PC systems.

  8. Public Databases Supporting Computational Toxicology

    EPA Science Inventory

    A major goal of the emerging field of computational toxicology is the development of screening-level models that predict potential toxicity of chemicals from a combination of mechanistic in vitro assay data and chemical structure descriptors. In order to build these models, resea...

  9. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    NASA Astrophysics Data System (ADS)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  10. The reliability of an epilepsy treatment clinical decision support system.

    PubMed

    Standridge, Shannon; Faist, Robert; Pestian, John; Glauser, Tracy; Ittenbach, Richard

    2014-10-01

    We developed a content validated computerized epilepsy treatment clinical decision support system to assist clinicians with selecting the best antiepilepsy treatments. Before disseminating our computerized epilepsy treatment clinical decision support system, further rigorous validation testing was necessary. As reliability is a precondition of validity, we verified proof of reliability first. We evaluated the consistency of the epilepsy treatment clinical decision support system in three areas including the preferred antiepilepsy drug choice, the top three recommended choices, and the rank order of the three choices. We demonstrated 100% reliability on 15,000 executions involving a three-step process on five different common pediatric epilepsy syndromes. Evidence for the reliability of the epilepsy treatment clinical decision support system was essential for the long-term viability of the system, and served as a crucial component for the next phase of system validation.

  11. DECISION SUPPORT FRAMEWORK FOR STORMWATER MANAGEMENT IN URBAN WATERSHEDS

    EPA Science Inventory

    To assist stormwater management professionals in planning for best management practices (BMPs) implementation, the U.S. Environmental Protection Agency (USEPA) is developing a decision support system for placement of BMPs at strategic locations in urban watersheds. This tool wil...

  12. Cyborg practices: call-handlers and computerised decision support systems in urgent and emergency care.

    PubMed

    Pope, Catherine; Halford, Susan; Turnbull, Joanne; Prichard, Jane

    2014-06-01

    This article draws on data collected during a 2-year project examining the deployment of a computerised decision support system. This computerised decision support system was designed to be used by non-clinical staff for dealing with calls to emergency (999) and urgent care (out-of-hours) services. One of the promises of computerised decisions support technologies is that they can 'hold' vast amounts of sophisticated clinical knowledge and combine it with decision algorithms to enable standardised decision-making by non-clinical (clerical) staff. This article draws on our ethnographic study of this computerised decision support system in use, and we use our analysis to question the 'automated' vision of decision-making in healthcare call-handling. We show that embodied and experiential (human) expertise remains central and highly salient in this work, and we propose that the deployment of the computerised decision support system creates something new, that this conjunction of computer and human creates a cyborg practice.

  13. Medical decision support systems and therapeutics: The role of autopilots.

    PubMed

    Woosley, R L; Whyte, J; Mohamadi, A; Romero, K

    2016-02-01

    For decades, medical practice has increasingly relied on prescription medicines to treat, cure, or prevent illness but their net benefit is reduced by prescribing errors that result in adverse drug reactions (ADRs) and tens of thousands of deaths each year. Optimal prescribing requires effective management of massive amounts of data. Clinical decision support systems (CDSS) can help manage information and support optimal therapeutic decisions before errors are made by operating as the prescribers' "autopilot."

  14. Decision Support System for ASD (Aeronatical Systems Division) Program Managers.

    DTIC Science & Technology

    1985-09-01

    quality of the decision depends on the depth of the program manager’s analysis . Recently, management has attempted to use the support of others to make...knowledge of system analysis and management techniques. 4. Program Managers will have access to the developed deci- sion support system. Definitions...the depth of the Progr a Managers analysis . A decision is more apt to be correct if the depth of analysis is increased (21:a-8). The depth of analysis

  15. Decision Support Systems: A Preliminary Study,

    DTIC Science & Technology

    1977-09-01

    goal for data management research is an integrated data system -12- _ _...__ _ _ ... ’ . ENGLISH LOGIC FORMAL DATA LISP OR SUBSET (KOWALSKI LANG FOR...studies are indicated to determine if cannonical forms can be used to make vector operations out of operations like COND (from LISP ). Studies of the...W.W., Boyer, Robert S., and Henneman , William H., (1972), "Computer Proofs of Limits Theorems", A.I. Jour., 3, pp. 27-60. 12. Bledsoe, W.W. and

  16. Interactive Decision Support for Academic Advising

    ERIC Educational Resources Information Center

    Mohamed, Abdallah

    2016-01-01

    Purpose: This paper aims to support academic advising, which plays a crucial role in student success and retention. The paper focuses on one of the most challenging tasks involved in academic advising: individual course scheduling. This task includes not only careful planning for different courses over several semesters according to students'…

  17. Supporting contractors' bidding decision: RBF neural networks application

    NASA Astrophysics Data System (ADS)

    Leśniak, Agnieszka

    2016-06-01

    A bidding decision, despite its being important for the contractor, often needs to be made quickly and within a limited timeframe. To facilitate the contractor's reasoning by limiting randomness that may lead to mistakes decision support models are frequently applied. This paper presents possible applications of an Artificial Neural Network (ANN) to support bidding decisions. The proposed model involving networks with radial basis functions (RBF) was to perform a classification task. On the basis of a set of input data, the network was to suggest either participation in the bid or resignation from it. The results, 93% of correctly classified cases, confirmed the usability of RBF network in solving the problem.

  18. Nurses' ethical decision-making role in artificial nutritional support.

    PubMed

    Tsaloglidou, A; Rammos, K; Kiriklidis, K; Zourladani, A; Matziari, C

    This study provides an insight into the process of ethical decision-making regarding the initiation or withdrawal of artificial nutritional support of seriously ill patients and explores the nursing involvement in it. Fifteen health carers were recruited from a clinical nutrition unit in the UK and qualitative research methods were used to gather data. The findings of the study indicate that nursing contribution to decision-making appeared to be in the 'back room' as the nurses feel that the decisions about difficult ethical dilemmas are 'out of their hands' because of lack of knowledge, experience and confidence. The medical staff and the clinical nurse specialist appear to be primarily responsible for making important decisions. It is clear from the study that to become more effective in the process, nurses need to enhance their knowledge in nutritional support and to develop their practical skills in ethical decision-making through experience and research.

  19. Fuzzy Cognitive Map scenario-based medical decision support systems for education.

    PubMed

    Georgopoulos, Voula C; Chouliara, Spyridoula; Stylios, Chrysostomos D

    2014-01-01

    Soft Computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if" scenarios in case studies and prepare for dealing with critical adverse events.

  20. Development and description of a decision analysis based decision support tool for stroke prevention in atrial fibrillation

    PubMed Central

    Thomson, R.; Robinson, A.; Greenaway, J.; Lowe, P.

    2002-01-01

    Background: There is an increasing move towards clinical decision making that engages the patient, which has led to the development and use of decision aids to support better decisions. The treatment of patients in atrial fibrillation (AF) with warfarin to prevent stroke is a decision that is sensitive to patient preferences as shown by a previous decision analysis. Aim: To develop a computerised decision support tool, building upon a previous decision analysis, which would engage individual patient preferences in reaching a shared decision on whether to take warfarin to prevent stroke. Methods: The development process had two main phases: (1) the development phase which employed focus groups and repeated interviews with GPs/practice nurses and patients alongside an iterative development of a computerised tool; (2) the training and testing phase in which GPs and practice nurses underwent training in the use of the tool, including the use of simulated patients. The tool was then used in a feasibility study in a small number of patients with AF to inform the design of a subsequent randomised controlled trial. Results: The prototype tool had three components: (1) derivation of an individual patient's values for relevant health states using a standard gamble; (2) presentation/discussion of a patient's risks of stroke using the Framingham equation and the benefits/risks of warfarin from a systematic literature review; and (3) decision making component incorporating the outcome of a Markov decision analysis model. Older patients could be taken through the decision analysis based computerised tool, and patients and clinicians welcomed information on risks and benefits of treatments. The tool required time and training to use. Patients' decisions in the feasibility phase did not necessarily coincide with the output of the decision analysis model, but decision conflict appeared to be reduced and both patients and GPs were satisfied with the process. Conclusions: It is

  1. Designing Colorectal Cancer Screening Decision Support: A Cognitive Engineering Enterprise

    PubMed Central

    Militello, Laura G.; Saleem, Jason J.; Borders, Morgan R.; Sushereba, Christen E.; Haverkamp, Donald; Wolf, Steven P.; Doebbeling, Bradley N.

    2016-01-01

    Adoption of clinical decision support has been limited. Important barriers include an emphasis on algorithmic approaches to decision support that do not align well with clinical work flow and human decision strategies, and the expense and challenge of developing, implementing, and refining decision support features in existing electronic health records (EHRs). We applied decision-centered design to create a modular software application to support physicians in managing and tracking colorectal cancer screening. Using decision-centered design facilitates a thorough understanding of cognitive support requirements from an end user perspective as a foundation for design. In this project, we used an iterative design process, including ethnographic observation and cognitive task analysis, to move from an initial design concept to a working modular software application called the Screening & Surveillance App. The beta version is tailored to work with the Veterans Health Administration’s EHR Computerized Patient Record System (CPRS). Primary care providers using the beta version Screening & Surveillance App more accurately answered questions about patients and found relevant information more quickly compared to those using CPRS alone. Primary care providers also reported reduced mental effort and rated the Screening & Surveillance App positively for usability. PMID:26973441

  2. System-Agnostic Clinical Decision Support Services: Benefits and Challenges for Scalable Decision Support

    PubMed Central

    Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F

    2010-01-01

    System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors’ formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors’ experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems. PMID:21603281

  3. System-agnostic clinical decision support services: benefits and challenges for scalable decision support.

    PubMed

    Kawamoto, Kensaku; Del Fiol, Guilherme; Orton, Charles; Lobach, David F

    2010-01-01

    System-agnostic clinical decision support (CDS) services provide patient evaluation capabilities that are independent of specific CDS systems and system implementation contexts. While such system-agnostic CDS services hold great potential for facilitating the widespread implementation of CDS systems, little has been described regarding the benefits and challenges of their use. In this manuscript, the authors address this need by describing potential benefits and challenges of using a system-agnostic CDS service. This analysis is based on the authors' formal assessments of, and practical experiences with, various approaches to developing, implementing, and maintaining CDS capabilities. In particular, the analysis draws on the authors' experience developing and leveraging a system-agnostic CDS Web service known as SEBASTIAN. A primary potential benefit of using a system-agnostic CDS service is the relative ease and flexibility with which the service can be leveraged to implement CDS capabilities across applications and care settings. Other important potential benefits include facilitation of centralized knowledge management and knowledge sharing; the potential to support multiple underlying knowledge representations and knowledge resources through a common service interface; improved simplicity and componentization; easier testing and validation; and the enabling of distributed CDS system development. Conversely, important potential challenges include the increased effort required to develop knowledge resources capable of being used in many contexts and the critical need to standardize the service interface. Despite these challenges, our experiences to date indicate that the benefits of using a system-agnostic CDS service generally outweigh the challenges of using this approach to implementing and maintaining CDS systems.

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

    PubMed Central

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

    2016-01-01

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

  5. Using Google Earth in Marine Research and Operational Decision Support

    NASA Astrophysics Data System (ADS)

    Blower, J. D.; Bretherton, D.; Haines, K.; Liu, C.; Rawlings, C.; Santokhee, A.; Smith, I.

    2006-12-01

    A key advantage of Virtual Globes ("geobrowsers") such as Google Earth is that they can display many different geospatial data types at a huge range of spatial scales. In this demonstration and poster display we shall show how marine data from disparate sources can be brought together in a geobrowser in order to support both scientific research and operational search and rescue activities. We have developed the Godiva2 interactive website for browsing and exploring marine data, mainly output from supercomputer analyses and predictions of ocean circulation. The user chooses a number of parameters (e.g. sea temperature at 100m depth on 1st July 2006) and can load an image of the resulting data in Google Earth. Through the use of an automatically-refreshing NetworkLink the user can explore the whole globe at a very large range of spatial scales: the displayed data will automatically be refreshed to show data at increasingly fine resolution as the user zooms in. This is a valuable research tool for exploring these terabyte- scale datasets. Many coastguard organizations around the world use SARIS, a software application produced by BMT Cordah Ltd., to predict the drift pattern of objects in the sea in order to support search and rescue operations. Different drifting objects have different trajectories depending on factors such as their buoyancy and windage and so a computer model, supported by meteorological and oceanographic data, is needed to help rescuers locate their targets. We shall demonstrate how Google Earth is used to display output from the SARIS model (including the search target location and associated error polygon) alongside meteorological data (wind vectors) and oceanographic data (sea temperature, surface currents) from Godiva2 in order to support decision-making. We shall also discuss the limitations of using Google Earth in this context: these include the difficulties of working with time- dependent data and the need to access data securely. essc

  6. An analysis of symbolic linguistic computing models in decision making

    NASA Astrophysics Data System (ADS)

    Rodríguez, Rosa M.; Martínez, Luis

    2013-01-01

    It is common that experts involved in complex real-world decision problems use natural language for expressing their knowledge in uncertain frameworks. The language is inherent vague, hence probabilistic decision models are not very suitable in such cases. Therefore, other tools such as fuzzy logic and fuzzy linguistic approaches have been successfully used to model and manage such vagueness. The use of linguistic information implies to operate with such a type of information, i.e. processes of computing with words (CWW). Different schemes have been proposed to deal with those processes, and diverse symbolic linguistic computing models have been introduced to accomplish the linguistic computations. In this paper, we overview the relationship between decision making and CWW, and focus on symbolic linguistic computing models that have been widely used in linguistic decision making to analyse if all of them can be considered inside of the CWW paradigm.

  7. Structured decision making as a method for linking quantitative decision support to community fundamental objectives

    EPA Science Inventory

    Decision support intended to improve ecosystem sustainability requires that we link stakeholder priorities directly to quantitative tools and measures of desired outcomes. Actions taken at the community level can have large impacts on production and delivery of ecosystem service...

  8. 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.

  9. Developing a Decision Support System: The Software and Hardware Tools.

    ERIC Educational Resources Information Center

    Clark, Phillip M.

    1989-01-01

    Describes some of the available software and hardware tools that can be used to develop a decision support system implemented on microcomputers. Activities that should be supported by software are discussed, including data entry, data coding, finding and combining data, and data compatibility. Hardware considerations include speed, storage…

  10. Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation.

    PubMed

    Linan, Margaret K; Sottara, Davide; Freimuth, Robert R

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines.

  11. Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation

    PubMed Central

    Linan, Margaret K.; Sottara, Davide; Freimuth, Robert R.

    2015-01-01

    Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema. The modeling and extraction processes developed here demonstrate how structured knowledge representations can be used to support the creation of shareable CDS rules from PGx guidelines. PMID:26958298

  12. Promoting Shared Decision Making in Disorders of Sex Development (DSD): Decision Aids and Support Tools.

    PubMed

    Siminoff, L A; Sandberg, D E

    2015-05-01

    Specific complaints and grievances from adult patients with disorders of sex development (DSD), and their advocates center around the lack of information or misinformation they were given about their condition and feeling stigmatized and shamed by the secrecy surrounding their condition and its management. Many also attribute poor sexual function to damaging genital surgery and/or repeated, insensitive genital examinations. These reports suggest the need to reconsider the decision-making process for the treatment of children born with DSD. This paper proposes that shared decision making, an important concept in adult health care, be operationalized for the major decisions commonly encountered in DSD care and facilitated through the utilization of decision aids and support tools. This approach may help patients and their families make informed decisions that are better aligned with their personal values and goals. It may also lead to greater confidence in decision making with greater satisfaction and less regret. A brief review of the past and current approach to DSD decision making is provided, along with a review of shared decision making and decision aids and support tools. A case study explores the need and potential utility of this suggested new approach.

  13. Risk Analysis Based Business Rule Enforcement for Intelligent Decision Support

    NASA Astrophysics Data System (ADS)

    Vasilecas, Olegas; Smaizys, Aidas; Brazinskas, Ramunas

    Intelligent information systems are acting by structured rules and do not deal with possible impact on the business environment or future consequences. That is the main reason why automated decisions based on such rules cannot take responsibility and requires involvement or approval of dedicated business people. This limits decision automation possibilities in information systems. However, business rules describe business policy and represent business logics. This can be used in intelligent information systems, together with risk assessment model to simulate real business environment and evaluate possible impact of automated decisions, to support intelligent decision automation. The chapter proposes risk and business rule model integration to provide full intelligent decision automation model used for business rule enforcement and implementation into intelligent software systems of information systems.

  14. Periodicals collection management using a decision support system

    SciTech Connect

    Compton, M.L.; Moser, E.C.

    1993-12-31

    Sandia National Laboratories is a multiprogram national laboratory established in 1949. The Library currently uses DOBIS for its automated system, including the Periodicals Control function for periodical check-in. DOBIS performs processing and control functions adequately, but could not meet our reporting needs. Therefore the Library`s Periodicals Decision Team decided that they needed another ``system`` for collection management. A Periodicals Decision Support System was created using information downloaded from DOBIS and uploaded into dBASE IV. The Periodical Decision Support System functions as an information-processing system that has aided us in making collection management decisions for periodicals. It certainly allows us to do interactive ad-hoc analysis; although there are no modeling tools currently incorporated in the system. We hope that these modeling tools will come later. We have been gathering information and developing needed reports to achieve this goal.

  15. Computer Maintenance Operations Center (CMOC), additional computer support equipment ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Computer Maintenance Operations Center (CMOC), additional computer support equipment - Beale Air Force Base, Perimeter Acquisition Vehicle Entry Phased-Array Warning System, Techinical Equipment Building, End of Spencer Paul Road, north of Warren Shingle Road (14th Street), Marysville, Yuba County, CA

  16. ClinicalAccess: a clinical decision support tool.

    PubMed

    Crowell, Karen; Vardell, Emily

    2015-01-01

    ClinicalAccess is a new clinical decision support tool that uses a question-and-answer format to mirror clinical decision-making strategies. The unique format of ClinicalAccess delivers concise, authoritative answers to more than 120,000 clinical questions. This column presents a review of the product, a sample search, and a comparison with other point-of-care search engines.

  17. Computational study of developing high-quality decision trees

    NASA Astrophysics Data System (ADS)

    Fu, Zhiwei

    2002-03-01

    Recently, decision tree algorithms have been widely used in dealing with data mining problems to find out valuable rules and patterns. However, scalability, accuracy and efficiency are significant concerns regarding how to effectively deal with large and complex data sets in the implementation. In this paper, we propose an innovative machine learning approach (we call our approach GAIT), combining genetic algorithm, statistical sampling, and decision tree, to develop intelligent decision trees that can alleviate some of these problems. We design our computational experiments and run GAIT on three different data sets (namely Socio- Olympic data, Westinghouse data, and FAA data) to test its performance against standard decision tree algorithm, neural network classifier, and statistical discriminant technique, respectively. The computational results show that our approach outperforms standard decision tree algorithm profoundly at lower sampling levels, and achieves significantly better results with less effort than both neural network and discriminant classifiers.

  18. Human-Computer Interactions and Decision Behavior

    DTIC Science & Technology

    1984-01-01

    Narang A. Cohill J. Pittman J. Elkerton M. Revesman R. Fainter C. Rieger L. Folley J. Schurick M. Hakkinen A. Siochi D. Johnson T. Spine C. Ku M. Sti...W., Yunten, T., , Johnson , D. H. DMS: A comprehensive system for managing human- computer dialogue. In Proceedings of Human Factors in Computer...interactive system. Wel! known software metrics are used in this analysis. 3. The Dialogue Author a. Reports Johnson , D. H., Hartson, H. R. The role

  19. 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.

  20. An Artificial Neural Network-Based Decision-Support System for Integrated Network Security

    DTIC Science & Technology

    2014-09-01

    AN ARTIFICIAL NEURAL NETWORK-BASED DECISION-SUPPORT SYSTEM FOR INTEGRATED NETWORK SECURITY THESIS ...The views expressed in this thesis are those of the author and do not reflect the official policy or position of the United States Air Force... THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force

  1. APPLICATION OF THE US DECISION SUPPORT TOOL FOR MATERIALS AND WASTE MANAGEMENT

    EPA Science Inventory

    EPA¿s National Risk Management Research Laboratory has led the development of a municipal solid waste decision support tool (MSW-DST). The computer software can be used to calculate life-cycle environmental tradeoffs and full costs of different waste management plans or recycling...

  2. OASIS: A GEOGRAPHICAL DECISION SUPPORT SYSTEM FOR GROUND-WATER CONTAMINANT MODELING

    EPA Science Inventory

    Three new software technologies were applied to develop an efficient and easy to use decision support system for ground-water contaminant modeling. Graphical interfaces create a more intuitive and effective form of communication with the computer compared to text-based interfaces...

  3. Modular analytics management architecture for interoperability and decision support

    NASA Astrophysics Data System (ADS)

    Marotta, Stephen; Metzger, Max; Gorman, Joe; Sliva, Amy

    2016-05-01

    The Dual Node Decision Wheels (DNDW) architecture is a new approach to information fusion and decision support systems. By combining cognitive systems engineering organizational analysis tools, such as decision trees, with the Dual Node Network (DNN) technical architecture for information fusion, the DNDW can align relevant data and information products with an organization's decision-making processes. In this paper, we present the Compositional Inference and Machine Learning Environment (CIMLE), a prototype framework based on the principles of the DNDW architecture. CIMLE provides a flexible environment so heterogeneous data sources, messaging frameworks, and analytic processes can interoperate to provide the specific information required for situation understanding and decision making. It was designed to support the creation of modular, distributed solutions over large monolithic systems. With CIMLE, users can repurpose individual analytics to address evolving decision-making requirements or to adapt to new mission contexts; CIMLE's modular design simplifies integration with new host operating environments. CIMLE's configurable system design enables model developers to build analytical systems that closely align with organizational structures and processes and support the organization's information needs.

  4. Machine Learning Techniques for Decision Support in Intelligent Data Management

    NASA Astrophysics Data System (ADS)

    Lynnes, C.; Miller, J.; Ramapriyan, H.; Isaac, D.; Harberts, R.

    2002-12-01

    NASA's growth in remote sensing data volumes has kept pace with Moore's Law, i.e., doubling every 18 months, with future growth likely from new instruments. Also, advances in instrumental design (e.g., hyperspectral scanners) and science algorithms are enabling more near-real-time applications of the data. The confluence of low-latency requirements with high data volumes and numbers of files poses major challenges for archive data management. In order to make the right data available at the right time, an archive will need to apply knowledge of the data content in its data management decisions. This decision support domain includes aspects such as automatic quality assessment, feature detection to support caching decisions, and content-based metadata to support efficient data selection. In this study, we evaluate a variety of machine learning algorithms for use in several decision support roles in intelligent data management. Machine learning algorithms such as neural networks and clustering have been used for decision support in business and policy domains. These techniques have found some use in remote sensing, e.g., for cloud and land cover classification. Yet most research on remote sensing data rests on science-based algorithms, such as those based on radiative transfer equations. Machine learning for scientific applications faces challenges such as discretization constraints, non-physical basis, and the difficulty of assembling training sets. However, these difficulties may be less significant in the decision support role. For instance, it is often enough to know whether a data attribute exceeds a certain threshold when selecting it for an application, without knowing the exact value. The training data problem can be surmounted by using products output by the science-based algorithms. On the other hand, an advantage of machine learning algorithms for decision support is their speed once they have been trained. Data management decisions must be made while the

  5. Shared decision making in Chile: supportive policies and research initiatives.

    PubMed

    Bravo, Paulina; Cabieses, Báltica; Bustamante, Claudia; Campos, Solange; Stacey, Dawn

    2011-01-01

    WHAT ABOUT POLICY REGARDING SDM? Since 1999, there has been a small but growing interest by academics, the government, and society as a whole in strengthening patients' and professionals' involvement in shared decision making (SDM). Two governmental policy documents that indicate support for SDM are (1) Health Reform in 2003 and (2) Sanitary Objectives 2011-2020, which includes a brief section on client participation and SDM. WHAT ABOUT TOOLS - DECISION SUPPORT FOR PATIENTS? Research by Chilean academics has highlighted the patients' desire to participate in health decisions and effective approaches for enhancing health professionals' skills in interprofessional SDM; however, little has been done to support this need and the work is centralised in only one academic institution. Decision support tools and coaching interventions are limited to patients considering decisions about managing type 2 diabetes. WHAT ABOUT PROFESSIONAL INTEREST AND IMPLEMENTATION? Although there is increasing attention to studying patients' participation and involvement on their healthcare, little has been studied in relation to professionals' interest in SDM. As well, there are significant challenges for implementation of a country-wide SDM policy. WHAT DOES THE FUTURE LOOK LIKE? The future looks promising given the new health policies, local Chilean research projects, and international initiatives. Collaboration between health professionals, academics, and government policy makers, with public involvement needs to be strengthened in order to promote concrete strategies to implement SDM in Chile.

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

    PubMed Central

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

    2016-01-01

    Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however

  7. Decision Support Systems for Research and Management in Advanced Life Support

    NASA Technical Reports Server (NTRS)

    Rodriquez, Luis F.

    2004-01-01

    Decision support systems have been implemented in many applications including strategic planning for battlefield scenarios, corporate decision making for business planning, production planning and control systems, and recommendation generators like those on Amazon.com(Registered TradeMark). Such tools are reviewed for developing a similar tool for NASA's ALS Program. DSS are considered concurrently with the development of the OPIS system, a database designed for chronicling of research and development in ALS. By utilizing the OPIS database, it is anticipated that decision support can be provided to increase the quality of decisions by ALS managers and researchers.

  8. Decision support system for the provision of emergency sanitation.

    PubMed

    Zakaria, F; Garcia, H A; Hooijmans, C M; Brdjanovic, D

    2015-04-15

    Proper provision of sanitation in emergencies is considered a life-saving intervention. Without access to sanitation, refugees at emergency camps are at a high risk of contracting diseases. Even the most knowledgeable relief agencies have experienced difficulties providing sanitation alternatives in such challenging scenarios. This study developed a computer-based decision support system (DSS) to plan a sanitation response in emergencies. The sanitation alternatives suggested by the DSS are based on a sanitation chain concept that considers different steps in the faecal sludge management, from the toilet or latrine to the safe disposal of faecal matters. The DSS first screens individual sanitation technologies using the user's given input. Remaining sanitation options are then built into a feasible sanitation chain. Subsequently, each technology in the chain is evaluated on a scoring system. Different sanitation chains can later be ranked based on the total evaluation scores. The DSS addresses several deficiencies encountered in the provision of sanitation in emergencies including: the application of standard practices and intuition, the omission of site specific conditions, the limited knowledge exhibited by emergency planners, and the provision of sanitation focused exclusively on the collection step (i.e., just the provision of toilets).

  9. Systems Analysis and Design for Decision Support Systems on Economic Feasibility of Projects

    NASA Astrophysics Data System (ADS)

    Balaji, S. Arun

    2010-11-01

    This paper discuss about need for development of the Decision Support System (DSS) software for economic feasibility of projects in Rwanda, Africa. The various economic theories needed and the corresponding formulae to compute payback period, internal rate of return and benefit cost ratio of projects are clearly given in this paper. This paper is also deals with the systems flow chart to fabricate the system in any higher level computing language. The various input requirements from the projects and the output needed for the decision makers are also included in this paper. The data dictionary used for input and output data structure is also explained.

  10. E-DECIDER Decision Support Gateway For Earthquake Disaster Response

    NASA Astrophysics Data System (ADS)

    Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.

    2013-12-01

    Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that

  11. Technology Infusion Challenges from a Decision Support Perspective

    NASA Technical Reports Server (NTRS)

    Adumitroaie, V.; Weisbin, C. R.

    2009-01-01

    In a restricted science budget environment and increasingly numerous required technology developments, the technology investment decisions within NASA are objectively more and more difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Under these conditions it is rationally desirable to build an investment portfolio, which has the highest possible technology infusion rate. Arguably the path to infusion is subject to many influencing factors, but here only the challenges associated with the very initial stages are addressed: defining the needs and the subsequent investment decision-support process. It is conceivable that decision consistency and possibly its quality suffer when the decision-making process has limited or no traceability. This paper presents a structured decision-support framework aiming to provide traceable, auditable, infusion- driven recommendations towards a selection process in which these recommendations are used as reference points in further discussions among stakeholders. In this framework addressing well-defined requirements, different measures of success can be defined based on traceability to specific selection criteria. As a direct result, even by using simplified decision models the likelihood of infusion can be probed and consequently improved.

  12. Decision support model for introduction of gamification solution using AHP.

    PubMed

    Kim, Sangkyun

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.

  13. Decision Support Model for Introduction of Gamification Solution Using AHP

    PubMed Central

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

  14. Using High Performance Computing to Support Water Resource Planning

    SciTech Connect

    Groves, David G.; Lembert, Robert J.; May, Deborah W.; Leek, James R.; Syme, James

    2015-10-22

    In recent years, decision support modeling has embraced deliberation-withanalysis— an iterative process in which decisionmakers come together with experts to evaluate a complex problem and alternative solutions in a scientifically rigorous and transparent manner. Simulation modeling supports decisionmaking throughout this process; visualizations enable decisionmakers to assess how proposed strategies stand up over time in uncertain conditions. But running these simulation models over standard computers can be slow. This, in turn, can slow the entire decisionmaking process, interrupting valuable interaction between decisionmakers and analytics.

  15. Distributed decision support for the 21st century mission space

    NASA Astrophysics Data System (ADS)

    McQuay, William K.

    2002-07-01

    The past decade has produced significant changes in the conduct of military operations: increased humanitarian missions, asymmetric warfare, the reliance on coalitions and allies, stringent rules of engagement, concern about casualties, and the need for sustained air operations. Future mission commanders will need to assimilate a tremendous amount of information, make quick-response decisions, and quantify the effects of those decisions in the face of uncertainty. Integral to this process is creating situational assessment-understanding the mission space, simulation to analyze alternative futures, current capabilities, planning assessments, course-of-action assessments, and a common operational picture-keeping everyone on the same sheet of paper. Decision support tools in a distributed collaborative environment offer the capability of decomposing these complex multitask processes and distributing them over a dynamic set of execution assets. Decision support technologies can semi-automate activities, such as planning an operation, that have a reasonably well-defined process and provide machine-level interfaces to refine the myriad of information that is not currently fused. The marriage of information and simulation technologies provides the mission commander with a collaborative virtual environment for planning and decision support.

  16. Computing and Systems Applied in Support of Coordinated ...

    EPA Pesticide Factsheets

    This talk focuses on how Dr. Loughlin is applying Computing and Systems models, tools and methods to more fully understand the linkages among energy systems, environmental quality, and climate change. Dr. Loughlin will highlight recent and ongoing research activities, including: applying sensitivity analysis to assess the impacts of clean energy technologies, conducting scenario analysis to explore the efficacy of environmental regulations under deep uncertainty, and developing decision support systems that allow analysts and decision-makers to examine state-level climate actions. Dr. Loughlin will conclude with a brief discussion of the lessons learned over the first half of his career. Dr. Loughlin has been invited to give the keynote talk at the 1st Annual Computing and Systems Graduate Research Symposium, sponsored by the Department of Civil, Construction and Environmental Engineering at North Carolina State University.

  17. Web-LCCA: decision support system for military display acquisition

    NASA Astrophysics Data System (ADS)

    Binder, Michael L.; Calvo, Alberto B.; Gibson, Gregory J.

    2000-08-01

    This paper describes a Decision Support System for military display acquisition being developed under U.S. Display Consortium (USDC) sponsorship. The core of the system is a standard Life-Cycle Cost model. The system will use World Wide Web technology to make it widely accessible to Industry and Government Program Offices for use in the Display Acquisition Decision Process. Web-LCCA (Life-Cycle Cost Analyzer), a derivative of TASC's LCCATM, has been designed to aid in the evaluation of different Display System acquisition options. The target users of Web-LCCA are display vendors (Industry) and buyers (Government Program Offices). Web-LCCA will be USDC's standard tool for supporting cost tradeoffs and acquisition decisions among current operational displays and new flat panel display products.

  18. Clinical decision support: the power behind the electronic health record.

    PubMed

    Glaser, John

    2008-07-01

    There are six strategic objectives for promoting adoption of clinical decision support: Use a standardized format for representing clinical data and CDS interventions. Ensure appropriate access to clinical data and CDS interventions. Provide support and incentives for providers to use CDS. Disseminate information about best practices for system design, CDS delivery, and CDS implementation. Continue national demonstrations and evaluation of CDS use. Leverage data interchange between EHRs.

  19. Behavior-aware decision support systems : LDRD final report.

    SciTech Connect

    Hirsch, Gary B.; Homer, Jack; Chenoweth, Brooke N.; Backus, George A.; Strip, David R.

    2007-11-01

    As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.

  20. A Decision Support System for Solving Multiple Criteria Optimization Problems

    ERIC Educational Resources Information Center

    Filatovas, Ernestas; Kurasova, Olga

    2011-01-01

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

  1. Team Machine: A Decision Support System for Team Formation

    ERIC Educational Resources Information Center

    Bergey, Paul; King, Mark

    2014-01-01

    This paper reports on the cross-disciplinary research that resulted in a decision-support tool, Team Machine (TM), which was designed to create maximally diverse student teams. TM was used at a large United States university between 2004 and 2012, and resulted in significant improvement in the performance of student teams, superior overall balance…

  2. DECISION SUPPORT FRAMEWORK FOR PLACEMENT OF BMPS IN URBAN WATERSHEDS

    EPA Science Inventory

    To assist stormwater management professionals in planning for best management practices (BMPs) implementation, the U.S. Environmental Protection Agency (USEPA) initiated a research in 2003 to develop a decision support system for placement of BMPs at strategic locations in urban ...

  3. Implementation problems of decision support system for nosocomial infection.

    PubMed

    Rems, M; Bohanec, M; Urh, B; Kramar, Z

    1997-01-01

    Decision support system for nosocomial infection therapy Ptah can reduce antibiotic misuse with data about bacteria resistance and antibiotic ineffectiveness. Resistance vectors in time series show epidemiological problems with resistant bacterias, named house-bacteria. Most important implementation factors are integrated hospital information system and doctors, nurses and managers interested in problems of nosocomial infection.

  4. Knowledge Flow Mesh and Its Dynamics: A Decision Support Environment

    DTIC Science & Technology

    2008-06-01

    Upper Saddle River, NJ, USA. 23 Mataxiotis, K. (2004). Decision support through knowledge management: The role of t artificial intelligence ...paper was the ability of the United States military to achieve dominance through information superiority. The use of intelligent sensors and... Intelligence Agency, National Security Agency, Defense Intelligence Agency, and individual Service intelligence agencies). In fact, these edge entities would

  5. Decision Support System for Disability Assessment and Intervention.

    ERIC Educational Resources Information Center

    Dowler, Denetta L.; And Others

    1991-01-01

    Constructed decision support system to aid referral of good candidates for rehabilitation from Social Security Administration to rehabilitation counselors. Three layers of system were gross screening based on policy guidelines, training materials, and interviews with experts; physical and mental functional capacity items derived from policy…

  6. Integrated decision support tools for Puget Sound salmon recovery planning

    EPA Science Inventory

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

  7. A knowledge-based decision support system for payload scheduling

    NASA Technical Reports Server (NTRS)

    Tyagi, Rajesh; Tseng, Fan T.

    1988-01-01

    This paper presents the development of a prototype Knowledge-based Decision Support System, currently under development, for scheduling payloads/experiments on space station missions. The DSS is being built on Symbolics, a Lisp machine, using KEE, a commercial knowledge engineering tool.

  8. Enabling computer decisions based on EEG input

    NASA Technical Reports Server (NTRS)

    Culpepper, Benjamin J.; Keller, Robert M.

    2003-01-01

    Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.

  9. COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS

    EPA Science Inventory

    Computer Support Systems for Estimating Chemical Toxicity: Present Capabilities and Future Trends

    A wide variety of computer-based artificial intelligence (AI) and decision support systems exist currently to aid in the assessment of toxicity for environmental chemicals. T...

  10. Security Aspects of Computer Supported Collaborative Work

    DTIC Science & Technology

    1993-09-01

    its enabling software. CSCW has been described by some as computer- based tools which can be used to facilitate the exchange and sharing of...information by work groups. Others have described it as a computer- based shared environment that supports two or more users. [Bock92] CSCW is a rapidly...Groupware applications according to the type of work they are designed 6 to accomplish. Based on this first criteria, they recognize four general classes

  11. Advanced Crew Personal Support Computer (CPSC) task

    NASA Technical Reports Server (NTRS)

    Muratore, Debra

    1991-01-01

    The topics are presented in view graph form and include: background; objectives of task; benefits to the Space Station Freedom (SSF) Program; technical approach; baseline integration; and growth and evolution options. The objective is to: (1) introduce new computer technology into the SSF Program; (2) augment core computer capabilities to meet additional mission requirements; (3) minimize risk in upgrading technology; and (4) provide a low cost way to enhance crew and ground operations support.

  12. Tools to support evidence-informed public health decision making

    PubMed Central

    2014-01-01

    Background Public health professionals are increasingly expected to engage in evidence-informed decision making to inform practice and policy decisions. Evidence-informed decision making involves the use of research evidence along with expertise, existing public health resources, knowledge about community health issues, the local context and community, and the political climate. The National Collaborating Centre for Methods and Tools has identified a seven step process for evidence-informed decision making. Tools have been developed to support public health professionals as they work through each of these steps. This paper provides an overview of tools used in three Canadian public health departments involved in a study to develop capacity for evidence-informed decision making. Methods As part of a knowledge translation and exchange intervention, a Knowledge Broker worked with public health professionals to identify and apply tools for use with each of the steps of evidence-informed decision making. The Knowledge Broker maintained a reflective journal and interviews were conducted with a purposive sample of decision makers and public health professionals. This paper presents qualitative analysis of the perceived usefulness and usability of the tools. Results Tools were used in the health departments to assist in: question identification and clarification; searching for the best available research evidence; assessing the research evidence for quality through critical appraisal; deciphering the ‘actionable message(s)’ from the research evidence; tailoring messages to the local context to ensure their relevance and suitability; deciding whether and planning how to implement research evidence in the local context; and evaluating the effectiveness of implementation efforts. Decision makers provided descriptions of how the tools were used within the health departments and made suggestions for improvement. Overall, the tools were perceived as valuable for advancing

  13. Collaborative Brain-Computer Interface for Aiding Decision-Making

    PubMed Central

    Poli, Riccardo; Valeriani, Davide; Cinel, Caterina

    2014-01-01

    We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making. PMID:25072739

  14. Workflow Technology to Enrich a Computerized Clinical Chart with Decision Support Facilities

    PubMed Central

    Panzarasa, Silvia; Quaglini, Silvana; Cavallini, Anna; Micieli, Giuseppe; Pernice, Corrado; Pessina, Mauro; Stefanelli, Mario

    2006-01-01

    Literature results and personal experience show that intrusive modalities of presenting suggestions of computerized clinical practice guidelines are detrimental to the routine use of an information system. This paper describes a solution for smoothly integrating a guideline-based decision support system into an existing computerized clinical chart for patients admitted to a Stroke Unit. Since many years, the healthcare personnel were using a commercial product for the ordinary patients’ data management, and they were satisfied with it. Thus, the decision support system has been integrated keeping attention to minimize changes and preserve existing human-computer interaction. Our decision support system is based on workflow technology. The paper illustrates the middleware layer developed to allow communication between the workflow management system and the clinical chart. At the same time, the consequent modification of the graphical users' interface is illustrated. PMID:17238415

  15. 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.

  16. Computational Biology Support: RECOMB Conference Series (Conference Support)

    SciTech Connect

    Michael Waterman

    2006-06-15

    This funding was support for student and postdoctoral attendance at the Annual Recomb Conference from 2001 to 2005. The RECOMB Conference series was founded in 1997 to provide a scientific forum for theoretical advances in computational biology and their applications in molecular biology and medicine. The conference series aims at attracting research contributions in all areas of computational molecular biology. Typical, but not exclusive, the topics of interest are: Genomics, Molecular sequence analysis, Recognition of genes and regulatory elements, Molecular evolution, Protein structure, Structural genomics, Gene Expression, Gene Networks, Drug Design, Combinatorial libraries, Computational proteomics, and Structural and functional genomics. The origins of the conference came from the mathematical and computational side of the field, and there remains to be a certain focus on computational advances. However, the effective use of computational techniques to biological innovation is also an important aspect of the conference. The conference had a growing number of attendees, topping 300 in recent years and often exceeding 500. The conference program includes between 30 and 40 contributed papers, that are selected by a international program committee with around 30 experts during a rigorous review process rivaling the editorial procedure for top-rate scientific journals. In previous years papers selection has been made from up to 130--200 submissions from well over a dozen countries. 10-page extended abstracts of the contributed papers are collected in a volume published by ACM Press and Springer, and are available at the conference. Full versions of a selection of the papers are published annually in a special issue of the Journal of Computational Biology devoted to the RECOMB Conference. A further point in the program is a lively poster session. From 120-300 posters have been presented each year at RECOMB 2000. One of the highlights of each RECOMB conference is a

  17. Making the Right Decisions: Leadership in 1-to-1 Computing in Education

    ERIC Educational Resources Information Center

    Towndrow, Phillip A.; Vallance, Michael

    2013-01-01

    Purpose: The purpose of this paper is to detail the necessity for more informed decision making and leadership in the implementation of 1-to-1 computing in education. Design/methodology/approach: The contexts of high-tech countries of Singapore and Japan are used as case studies to contextualize and support four evidence-based recommendations for…

  18. Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation

    PubMed Central

    2017-01-01

    People are often aware of their mistakes, and report levels of confidence in their choices that correlate with objective performance. These metacognitive assessments of decision quality are important for the guidance of behavior, particularly when external feedback is absent or sporadic. However, a computational framework that accounts for both confidence and error detection is lacking. In addition, accounts of dissociations between performance and metacognition have often relied on ad hoc assumptions, precluding a unified account of intact and impaired self-evaluation. Here we present a general Bayesian framework in which self-evaluation is cast as a “second-order” inference on a coupled but distinct decision system, computationally equivalent to inferring the performance of another actor. Second-order computation may ensue whenever there is a separation between internal states supporting decisions and confidence estimates over space and/or time. We contrast second-order computation against simpler first-order models in which the same internal state supports both decisions and confidence estimates. Through simulations we show that second-order computation provides a unified account of different types of self-evaluation often considered in separate literatures, such as confidence and error detection, and generates novel predictions about the contribution of one’s own actions to metacognitive judgments. In addition, the model provides insight into why subjects’ metacognition may sometimes be better or worse than task performance. We suggest that second-order computation may underpin self-evaluative judgments across a range of domains. PMID:28004960

  19. Toward image analysis and decision support for ultrasound technology.

    PubMed

    Crofts, Gillian; Padman, Rema; Maharaja, Nisha

    2013-01-01

    Ultrasound is a low cost and efficient method of detecting diseases and abnormalities in the body. Yet there is a lack of precision and reliability associated with the technology, partly due to the operator dependent nature of ultrasound scanning. When scanning is performed to an agreed protocol, ultrasound has been shown to be highly reliable. This research aims to minimize these limitations that arise during ultrasound training, scanning and reporting by developing and evaluating an image analysis and decision support system that can aid the decision making process. We hypothesize that this intervention will likely increase the role of ultrasound in diagnosis when compared with other imaging technologies, particularly in low resource settings.

  20. Semantic Interoperability in Clinical Decision Support Systems: A Systematic Review.

    PubMed

    Marco-Ruiz, Luis; Bellika, Johan Gustav

    2015-01-01

    The interoperability of Clinical Decision Support (CDS) systems with other health information systems has become one of the main limitations to their broad adoption. Semantic interoperability must be granted in order to share CDS modules across different health information systems. Currently, numerous standards for different purposes are available to enable the interoperability of CDS systems. We performed a literature review to identify and provide an overview of the available standards that enable CDS interoperability in the areas of clinical information, decision logic, terminology, and web service interfaces.

  1. Virtual medical record implementation for enhancing clinical decision support.

    PubMed

    Gomoi, Valentin-Sergiu; Dragu, Daniel; Stoicu-Tivadar, Vasile

    2012-01-01

    Development of clinical decision support systems (CDS) is a process which highly depends on the local databases, this resulting in low interoperability. To increase the interoperability of CDS a standard representation of clinical information is needed. The paper suggests a CDS architecture which integrates several HL7 standards and the new vMR (virtual Medical Record). The clinical information for the CDS systems (the vMR) is represented with Topic Maps technology. Beside the implementation of the vMR, the architecture integrates: a Data Manager, an interface, a decision making system (based on Egadss), a retrieving data module. Conclusions are issued.

  2. Computer-Supported Co-operative Learning.

    ERIC Educational Resources Information Center

    Florea, Adina Magda

    1998-01-01

    Discusses the impact of computer-supported cooperative work tools in the creation of educational environments and the facilities such tools bring to teaching methods, and examines the relationship between new techniques and the learner-centered, active learning approach in higher education. The importance of collaborative learning in this context…

  3. Advances in Computer-Supported Learning

    ERIC Educational Resources Information Center

    Neto, Francisco; Brasileiro, Francisco

    2007-01-01

    The Internet and growth of computer networks have eliminated geographic barriers, creating an environment where education can be brought to a student no matter where that student may be. The success of distance learning programs and the availability of many Web-supported applications and multimedia resources have increased the effectiveness of…

  4. Summary Street: Interactive Computer Support for Writing

    ERIC Educational Resources Information Center

    Wade-Stein, David; Kintsch, Eileen

    2004-01-01

    Summary Street is educational software based on latent semantic analysis (LSA), a computer method for representing the content of texts. The classroom trial described here demonstrates the power of LSA to support an educational goal by providing automatic feedback on the content of students' summaries. Summary Street provides this feedback in an…

  5. Specifying Computer-Supported Collaboration Scripts

    ERIC Educational Resources Information Center

    Kobbe, Lars; Weinberger, Armin; Dillenbourg, Pierre; Harrer, Andreas; Hamalainen, Raija; Hakkinen, Paivi; Fischer, Frank

    2007-01-01

    Collaboration scripts facilitate social and cognitive processes of collaborative learning by shaping the way learners interact with each other. Computer-supported collaboration scripts generally suffer from the problem of being restrained to a specific learning platform. A standardization of collaboration scripts first requires a specification of…

  6. A decision support system for managing forest fire casualties.

    PubMed

    Bonazountas, Marc; Kallidromitou, Despina; Kassomenos, Pavlos; Passas, Nikos

    2007-09-01

    Southern Europe is exposed to anthropogenic and natural forest fires. These result in loss of lives, goods and infrastructure, but also deteriorate the natural environment and degrade ecosystems. The early detection and combating of such catastrophes requires the use of a decision support system (DSS) for emergency management. The current literature reports on a series of efforts aimed to deliver DSSs for the management of the forest fires by utilising technologies like remote sensing and geographical information systems (GIS), yet no integrated system exists. This manuscript presents the results of scientific research aiming to the development of a DSS for managing forest fires. The system provides a series of software tools for the assessment of the propagation and combating of forest fires based on Arc/Info, ArcView, Arc Spatial Analyst, Arc Avenue, and Visual C++ technologies. The system integrates GIS technologies under the same data environment and utilises a common user interface to produce an integrated computer system based on semi-automatic satellite image processing (fuel maps), socio-economic risk modelling and probabilistic models that would serve as a useful tool for forest fire prevention, planning and management. Its performance has been demonstrated via real time up-to-date accurate information on the position and evolution of the fire. The system can assist emergency assessment, management and combating of the incident. A site demonstration and validation has been accomplished for the island of Evoia, Greece, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns.

  7. CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

    SciTech Connect

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

    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.

  8. Insurance Contract Analysis for Company Decision Support in Acquisition Management

    NASA Astrophysics Data System (ADS)

    Chernovita, H. P.; Manongga, D.; Iriani, A.

    2017-01-01

    One of company activities to retain their business is marketing the products which include in acquisition management to get new customers. Insurance contract analysis using ID3 to produce decision tree and rules to be decision support for the insurance company. The decision tree shows 13 rules that lead to contract termination claim. This could be a guide for the insurance company in acquisition management to prevent contract binding with these contract condition because it has a big chance for the customer to terminate their insurance contract before its expired date. As the result, there are several strong points that could be the determinant of contract termination such as: 1) customer age whether too young or too old, 2) long insurance period (above 10 years), 3) big insurance amount, 4) big amount of premium charges, and 5) payment method.

  9. Middle Mississippi River decision support system: user's manual

    USGS Publications Warehouse

    Rohweder, Jason J.; Zigler, Steven J.; Fox, Timothy J.; Hulse, Steven N.

    2005-01-01

    This user's manual describes the Middle Mississippi River Decision Support System (MMRDSS) and gives detailed examples on its use. The MMRDSS provides a framework to assist decision makers regarding natural resource issues in the Middle Mississippi River floodplain. The MMRDSS is designed to provide users with a spatially explicit tool for tasks, such as inventorying existing knowledge, developing models to investigate the potential effects of management decisions, generating hypotheses to advance scientific understanding, and developing scientifically defensible studies and monitoring. The MMRDSS also includes advanced tools to assist users in evaluating differences in complexity, connectivity, and structure of aquatic habitats among river reaches. The Environmental Systems Research Institute ArcView 3.x platform was used to create and package the data and tools of the MMRDSS.

  10. Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

    NASA Technical Reports Server (NTRS)

    Tavana, Madjid

    1995-01-01

    The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

  11. A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

    ERIC Educational Resources Information Center

    Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

    2015-01-01

    In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

  12. Using nursing clinical decision support systems to achieve meaningful use.

    PubMed

    Harrison, Roberta L; Lyerla, Frank

    2012-07-01

    The Health Information Technology and Clinical Health Act (one component of the American Recovery and Reinvestment Act) is responsible for providing incentive payments to hospitals and eligible providers in an effort to support the adoption of electronic health records. Future penalties are planned for electronic health record noncompliance. In order to receive incentives and avoid penalties, hospitals and eligible providers must demonstrate "meaningful use" of their electronic health records. One of the meaningful-use objectives established by the Centers for Medicare & Medicaid Services involves the use of a clinical decision support rule that addresses a hospital-defined, high-priority condition. This article describes the Plan-Do-Study-Act process for creating and implementing a nursing clinical decision support system designed to improve guideline adherence for hypoglycemia management. This project identifies hypoglycemia management as the high-priority area. However, other facilities with different high-priority conditions may find the process presented in this article useful for implementing additional clinical decision support rules geared toward improving outcomes and meeting federal mandates.

  13. Computer-Assisted Community Planning and Decision Making.

    ERIC Educational Resources Information Center

    College of the Atlantic, Bar Harbor, ME.

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

  14. Forecasting for Computer Aided Career Decisions: Prospects and Procedures.

    ERIC Educational Resources Information Center

    Durstine, Richard M.

    This paper is the second step in the preparation of forecasts of occupational and industrial information which will meet the needs of the Information System for Vocational Decisions (ISVD). The author discusses the computation routines which need to be developed, tested and operationalized toward the goal of combining occupational and industrial…

  15. Computer Simulation of Small Group Decisions: Model Three.

    ERIC Educational Resources Information Center

    Hare, A.P.; Scheiblechner, Hartmann

    In a test of three computer models to simulate group decisions, data were used from 31 American and Austrian groups on a total of 307 trials. The task for each group was to predict a series of answers of an unknown subject on a value-orientation questionnaire, after being given a sample of his typical responses. The first model, used the mean of…

  16. Supported decision making: a review of the international literature.

    PubMed

    Davidson, Gavin; Kelly, Berni; Macdonald, Geraldine; Rizzo, Maria; Lombard, Louise; Abogunrin, Oluwaseye; Clift-Matthews, Victoria; Martin, Alison

    2015-01-01

    Supported decision making (SDM) refers to the process of supporting people, whose decision making ability may be impaired, to make decisions and so promote autonomy and prevent the need for substitute decision making. There have been developments in SDM but mainly in the areas of intellectual disabilities and end-of-life care rather than in mental health. The main aim of this review was to provide an overview of the available evidence relevant to SDM and so facilitate discussion of how this aspect of law, policy and practice may be further developed in mental health services. The method used for this review was a Rapid Evidence Assessment which involved: developing appropriate search strategies; searching relevant databases and grey literature; then assessing, including and reviewing relevant studies. Included studies were grouped into four main themes: studies reporting stakeholders' views on SDM; studies identifying barriers to the implementation of SDM; studies highlighting ways to improve implementation; and studies on the impact of SDM. The available evidence on implementation and impact, identified by this review, is limited but there are important rights-based, effectiveness and pragmatic arguments for further developing and researching SDM for people with mental health problems.

  17. Designing Real-time Decision Support for Trauma Resuscitations

    PubMed Central

    Yadav, Kabir; Chamberlain, James M.; Lewis, Vicki R.; Abts, Natalie; Chawla, Shawn; Hernandez, Angie; Johnson, Justin; Tuveson, Genevieve; Burd, Randall S.

    2016-01-01

    Background Use of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool. Objectives The objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use. Methods This mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the

  18. What can Natural Language Processing do for Clinical Decision Support?

    PubMed Central

    Demner-Fushman, Dina; Chapman, Wendy W.; McDonald, Clement J.

    2009-01-01

    Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural Language Processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed. PMID:19683066

  19. Decision support system based semantic web for personalized patient care.

    PubMed

    Douali, Nassim; De Roo, Jos; Jaulent, Marie-Christine

    2012-01-01

    Personalized medicine may be considered an extension of traditional approaches to understanding and treating diseases, but with greater precision. A profile of a patient's genetic variation can guide the selection of drugs or treatment protocols that minimize harmful side effects or ensure a more successful outcome. In this paper we describe a decision support system designed to assist physicians for personalized care, and methodology for integration in the clinical workflow. A reasoning method for interacting heterogeneous knowledge and data is a necessity in the context of personalized medicine. Development of clinical decision support based semantic web for personalized patient care is to achieve its potential and improve the quality, safety and efficiency of healthcare.

  20. A Flight Deck Decision Support Tool for Autonomous Airborne Operations

    NASA Technical Reports Server (NTRS)

    Ballin, Mark G.; Sharma, Vivek; Vivona, Robert A.; Johnson, Edward J.; Ramiscal, Ermin

    2002-01-01

    NASA is developing a flight deck decision support tool to support research into autonomous operations in a future distributed air/ground traffic management environment. This interactive real-time decision aid, referred to as the Autonomous Operations Planner (AOP), will enable the flight crew to plan autonomously in the presence of dense traffic and complex flight management constraints. In assisting the flight crew, the AOP accounts for traffic flow management and airspace constraints, schedule requirements, weather hazards, aircraft operational limits, and crew or airline flight-planning goals. This paper describes the AOP and presents an overview of functional and implementation design considerations required for its development. Required AOP functionality is described, its application in autonomous operations research is discussed, and a prototype software architecture for the AOP is presented.

  1. Query Modification through External Sources to Support Clinical Decisions

    DTIC Science & Technology

    2014-11-01

    Query Modification through External Sources to Support Clinical Decisions Raymond Wan1, Jannifer Hiu-Kwan Man2, and Ting-Fung Chan1 1School of Life...query modifications that use either external data sources or a domain expert. While each method gave slightly different results, we discovered that...biomedical literature offers many possible paths of investigation, our study focused on modifications to the query using external data sources. We submitted 5

  2. Visualizing Non-Physical, Logical Constructs for Command Decision Support

    DTIC Science & Technology

    2004-04-01

    NY 14260 USA llinas@eng.buffalo.edu T. Kesavadas, Ph.D 315 Bell Hall University at Buffalo Buffalo, NY 14260 USA kesh @eng.buffalo.edu...Decision- Making Support Dr. James Llinas Dr. “ Kesh ” Kesavadas Center for Multisource Information Fusion (CMIF) State University of New York at...Buffalo Buffalo, New York, USA llinas@eng.buffalo.edu kesh @eng.buffalo.edu 7-2 Visualization, Info. Fusion and Logical Constructs Info Fusion Traditional

  3. Clinical Decision Support for Vascular Disease in Community Family Practice

    PubMed Central

    Keshavjee, K; Holbrook, AM; Lau, E; Esporlas-Jewer, I; Troyan, S

    2006-01-01

    The COMPETE III Vascular Disease Tracker (C3VT) is a personalized, Web-based, clinical decision support tool that provides patients and physicians access to a patient’s 16 individual vascular risk markers, specific advice for each marker and links to best practices in vascular disease management. It utilizes the chronic care model1 so that physicians can better manage patients with chronic diseases. Over 1100 patients have been enrolled into the COMPETE III study to date.

  4. NASA's past, current and potential future support in bringing climate projection information to the decision support level

    NASA Astrophysics Data System (ADS)

    Lee, T. J.

    2015-12-01

    It is common that we use global climate models or Earth system models to perform climate projection into the future. Because of the long integration time and the tremendous computing resources required for such a projection, the model resolution is typically not at a spatial scale fine enough for climate assessment or decision support purposes. A number of "downscaling technologies" have been developed over the years to bring the climate projection information to the local level for management and policy decision support purposes. In the past couple of years, NASA supported a number of regional to local climate projection activities: NASA Climate Adaption Science Investigators focused on climate resilience at NASA center level, National Climate Assessment (NCA) Capacity Building focused on data sets and tools to support NCA, NCA Indicators focused on creating simple indicators specifically designed for decision support, Assessing the Fidelity of Dynamical Downscaling with the NASA Unifies-WRF Model focused on understanding the credibility of dynamical downscaling technique using a regional climate model. All of these projects have a component in creating or using downscaled climate information. With the consequence of climate change beginning to emerge, there is a continuous need to better quantify the quality of downscaled climate projections. In this talk I will give an overview on NASA's efforts to understand the various techniques, the limitations including the risks of using these techniques, and finally, I will provide a view on possible future researches in this area.

  5. An Oceanographic Decision Support System for Scientific Field Experiments

    NASA Astrophysics Data System (ADS)

    Maughan, T.; Das, J.; McCann, M. P.; Rajan, K.

    2011-12-01

    . The ODSS was used for automated shore-based control of mobile assets and was also used to compute safety bounds for operation of MBARI AUVs and provide projections of drifters advected [1,4] due to surface conditions. Scientist and operations teams use the ODSS during the daily planning meetings for situation awareness and real time access to data to support decisions on sampling strategies and platform logistics. References 1. J.Das, F. Py, T. Maughan, J Ryan , K. Rajan & G. Sukhatme, Simultaneous Tracking and Sampling of Dynamic Oceanographic Features with Autonomous Underwater Vehicles and Lagrangian Drifters, Accepted, Intnl. Symp. on Experimental Robotics (ISER), N. Delhi, India, Dec 2010. 2. S. Jiminez, F. Py & K. Rajan, Learning Identification Models for In-situ Sampling of Ocean features, Working notes of the RSS'10 Workshop on Active Learning for Robotics. Robotics Systems Sciences, Spain. 2010 3. Py, F. , Jiminez, S. , and Rajan, K. "Modeling dynamic coastal ocean features for in-situ identication and adaptive sampling", Journal of Atmospheric and Ocean Technology-Ocean(2010). Submitted, in Review. 4. J. Das, K. Rajan, S. Frolov, J. Ryan, F. Py, D. Caron & G. Sukhatme, Towards Marine Bloom Trajectory Prediction for AUV Mission Planning, ICRA, May 2010, Anchorage

  6. Decision making technical support study for the US Army's Chemical Stockpile Disposal Program

    SciTech Connect

    Feldman, D.L.; Dobson, J.E.

    1990-08-01

    This report examines the adequacy of current command and control systems designed to make timely decisions that would enable sufficient warning and protective response to an accident at the Edgewood area of Aberdeen Proving Ground (APG), Maryland, and at Pine Bluff Arsenal (PBA), Arkansas. Institutional procedures designed to facilitate rapid accident assessment, characterization, warning, notification, and response after the onset of an emergency and computer-assisted decision-making aids designed to provide salient information to on- and-off-post emergency responders are examined. The character of emergency decision making at APG and PBA, as well as potential needs for improvements to decision-making practices, procedures, and automated decision-support systems (ADSSs), are described and recommendations are offered to guide equipment acquisition and improve on- and off-post command and control relationships. We recommend that (1) a continued effort be made to integrate on- and off-post command control, and decision-making procedures to permit rapid decision making; (2) the pathways for alert and notification among on- and off-post officials be improved and that responsibilities and chain of command among off-post agencies be clarified; (3) greater attention be given to organizational and social context factors that affect the adequacy of response and the likelihood that decision-making systems will work as intended; and (4) faster improvements be made to on-post ADSSs being developed at APG and PBA, which hold considerable promise for depicting vast amounts of information. Phased development and procurement of computer-assisted decision-making tools should be undertaken to balance immediate needs against available resources and to ensure flexibility, equity among sites, and compatibility among on- and off-post systems. 112 refs., 6 tabs.

  7. Disaster Management with a Next Generation Disaster Decision Support System

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2015-12-01

    As populations become increasingly concentrated in large cities, the world is experiencing an inevitably growing trend towards the urbanisation of disasters. Scientists have contributed significant advances in understanding the geophysical causes of natural hazards and have developed sophisticated tools to predict their effects; while, much less attention has been devoted to tools that increase situational awareness, facilitate leadership, provide effective communication channels and data flow and enhance the cognitive abilities of decision makers and first responders. In this paper, we envisioned the capabilities of a next generation disaster decision support system and hence proposed a state-of-the-art system architecture design to facilitate the decision making process in natural catastrophes such as flood and bushfire by utilising a combination of technologies for multi-channel data aggregation, disaster modelling, visualisation and optimisation. Moreover, we put our thoughts into action by implementing an Intelligent Disaster Decision Support System (IDDSS). The developed system can easily plug in to external disaster models and aggregate large amount of heterogeneous data from government agencies, sensor networks, and crowd sourcing platforms in real-time to enhance the situational awareness of decision makers and offer them a comprehensive understanding of disaster impacts from diverse perspectives such as environment, infrastructure and economy, etc. Sponsored by the Australian Government and the Victorian Department of Justice (Australia), the system was built upon a series of open-source frameworks (see attached figure) with four key components: data management layer, model application layer, processing service layer and presentation layer. It has the potential to be adopted by a range of agencies across Australian jurisdictions to assist stakeholders in accessing, sharing and utilising available information in their management of disaster events.

  8. Model-driven decision support for monitoring network design: methods and applications

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Harp, D. R.; Mishra, P. K.; Katzman, D.

    2012-12-01

    A crucial aspect of any decision-making process for environmental management of contaminated sites and protection of groundwater resources is the identification of scientifically defensible remediation scenarios. The selected scenarios are ranked based on both their protective and cost effectiveness. The decision-making process is facilitated by implementation of site-specific data- and model-driven analyses for decision support (DS) taking into account existing uncertainties to evaluate alternative characterization and remedial activities. However, due to lack of data and/or complex interdependent uncertainties (conceptual elements, model parameters, measurement/computational errors, etc.), the DS optimization problem is ill posed (non unique) and the model-prediction uncertainties are difficult to quantify. Recently, we have developed and implemented several novel theoretical approaches and computational algorithms for model-driven decision support. New and existing DS tools have been employed for model analyses of the fate and extent of a chromium plume in the regional aquifer at Sandia Canyon Site, LANL. Since 2007, we have performed three iterations of DS analyses implementing different models, decision-making tools, and data sets providing guidance on design of a subsurface monitoring network for (1) characterization of the flow and transports processes, and (2) protection of the water users. The monitoring network is augmented by new wells at locations where acquired new data can effectively reduce uncertainty in model predicted contaminant concentrations. A key component of the DS analyses is contaminant source identification. Due to data and conceptual uncertainties, subsurface processes controlling the contaminant arrival at the top of the regional aquifer are not well defined. Nevertheless, the model-based analyses of the existing data and conceptual knowledge, including respective uncertainties, provide constrained probabilistic estimates of the

  9. Proactive Decision Support Via Narrative-Integrated Multi-Level Support System (NIMSS)

    DTIC Science & Technology

    2014-11-30

    unlimited Overall objective is to create and test (using specific applications) a theory and model-based technology for enabling and advancing a...decision-makers build, maintain, and represent situational context. Integrate multiple existing theories and conceptual models of context that address...Develop NIMSS Theory & Formalism In this task, we will develop the NIM context model and develop a Decision Support model based on the underlying context

  10. Personalization and Patient Involvement in Decision Support Systems: Current Trends

    PubMed Central

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

    2015-01-01

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

  11. Decision support system for economic value of irrigation water

    NASA Astrophysics Data System (ADS)

    El-Gafy, Inas; El-Ganzori, Akram

    2012-06-01

    The mismatch between the supply and demand, inequitable distribution and the over irrigation of water consuming crops are the main constraints that are faced in the implementation of the integrated water resources management in Egypt. With water scarcity, the problem under consideration is that the current cropping pattern is not economically efficient in the utilization of the available water resource. Moreover, in consequence of the importance of the agricultural sector to the national economies, it is necessary to be aware of the economic performance of water use in the crops production. The scope of this study is to develop economic value of irrigation water maps of Egypt. The objective of the study is carried out by acquiring a Decision Support System for economic value of irrigation water of Egypt. This Decision Support System is applied for developing economic value maps for the irrigation water that is used for cultivating 45 crops under cereal, fiber, legumes, and vegetables, herbalist, and forages categories at each governorate of Egypt in year 2008 and 2009. The crops that achieve the highest and lowest economic value of irrigation water at each governorate of Egypt were identified. The reasons of the variations in the economic value of irrigation water at the governorates of Egypt were determined. The developed Decision Support System could be used yearly as a tool for demonstrating a picture about the economic value of irrigation water for the decision makers in the areas of water resources and agriculture. The developed economic value of irrigation water maps can be used in proposing a cropping pattern that maximizes the economic value of irrigation water in each governorate of Egypt.

  12. Demonstration of Decision Support Tools for Sustainable Development

    SciTech Connect

    Shropshire, David Earl; Jacobson, Jacob Jordan; Berrett, Sharon; Cobb, D. A.; Worhach, P.

    2000-11-01

    The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.

  13. The economic valuation of improved process plant decision support technology.

    PubMed

    White, Douglas C

    2007-06-01

    How can investments that would potentially improve a manufacturing plant's decision process be economically justified? What is the value of "better information," "more flexibility," or "improved integration" and the technologies that provide these effects? Technology investments such as improved process modelling, new real time historians and other databases, "smart" instrumentation, better data analysis and visualization software, and/or improved user interfaces often include these benefits as part of their valuation. How are these "soft" benefits to be converted to a quantitative economic return? Quantification is important if rational management decisions are to be made about the correct amount of money to invest in the technologies, and which technologies to choose among the many available ones. Modelling the plant operational decision cycle-detect, analyse, forecast, choose and implement--provides a basis for this economic quantification. In this paper a new economic model is proposed for estimation of the value of decision support investments based on their effect upon the uncertainty in forecasting plant financial performance. This model leads to quantitative benefit estimates that have a realistic financial basis. An example is presented demonstrating the application of the method.

  14. Bridging groundwater models and decision support with a Bayesian network

    USGS Publications Warehouse

    Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert

    2013-01-01

    Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

  15. A Semantic Approach with Decision Support for Safety Service in Smart Home Management

    PubMed Central

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-01-01

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

  16. A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-08-03

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

  17. Decision Integration and Support Engine (DISE) for dynamic aircraft and ISR asset tasking/retasking decision support for the AOC

    NASA Astrophysics Data System (ADS)

    VonPlinsky, Michael J.; Crowder, Ed

    2002-07-01

    The Decision Integration and Support Environment (DISE) is a Bayesian network (BN) based modeling and simulation of the target nomination and aircraft tasking decision processes. DISE operates in event driven interactions with FTI's AOC model, being triggered from within the Time Critical Target (TCT) Operations cell. As new target detections are received by the AOC from off-board ISR sources and processed by the Automatic Target Recognition (ATR) module in the AOC, DISE is called to determine if the target should be prosecuted, and if so, which of the available aircraft should be tasked to attack it. A range of decision criteria, with priorities established off-line and input into the tool, are associated with this process. DISE, when running in its constructive mode, automatically selects the best-suited aircraft and assigns the new target. In virtual mode, with a human operator, DISE presents the user with a suitability ranked list of the available aircraft for assignment. Recent DISE enhancements are applying this concept to the prioritization and scheduling of ISR support requests from Users to support both latent and dynamic tasking and scheduling of both space-based and airborne ISR assets.

  18. Decision support framework for oil-spill response

    SciTech Connect

    Octavio, K.H.

    1986-01-01

    A review of the state of oil spill response planning and an interpretation of the administrative, procedural and political climate surrounding response in general and in the Venezuelan case in particular reveals critical areas where things go wrong, affecting speed and appropriateness of response. Generic issues faced by any region preparing contingency plans are identified and techniques for resolving them and the appropriate institutional setting are suggested. The first reported design of an integrated interactive graphic microcomputer based decision Support System for operational oil spill response is presented. The integrated DSS with its status display and log entries provides a formal mechanism for recording activities, and their justifications at the time of occurrence so that activities and their consequences can be reviewed to improve procedures and priorities. There is an identifiable dearth of realistic training exercises meant to hone decision making skills under the pressures of an ongoing major spill event. The design of an operational oil spill response training system based directly on the framework of an interactive, graphics oriented Decision Support System for operational response to oil spills is presented. This training framework not only develops skills needed by new spill response coordinators in devising and carrying out action plans, it also identified flaws or gaps in managerial or institutional arrangements before the response system is tested by an actual spill. The underlying concepts of both the DSS and the training exercise are general and can be readily applied to any region concerned with organizing oil spill response.

  19. North Slope Decision Support for Water Resource Planning and Management

    SciTech Connect

    Schnabel, William; Brumbelow, Kelly

    2013-03-31

    The objective of this project was to enhance the water resource decision-making process with respect to oil and gas exploration/production activities on Alaska’s North Slope. To this end, a web-based software tool was developed to allow stakeholders to assemble, evaluate, and communicate relevant information between and amongst themselves. The software, termed North Slope Decision Support System (NSDSS), is a visually-referenced database that provides a platform for running complex natural system, planning, and optimization models. The NSDSS design was based upon community input garnered during a series of stakeholder workshops, and the end product software is freely available to all stakeholders via the project website. The tool now resides on servers hosted by the UAF Water and Environmental Research Center, and will remain accessible and free-of-charge for all interested stakeholders. The development of the tool fostered new advances in the area of data evaluation and decision support technologies, and the finished product is envisioned to enhance water resource planning activities on Alaska’s North Slope.

  20. Technosocial Predictive Analytics in Support of Naturalistic Decision Making

    SciTech Connect

    Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.; Riensche, Roderick M.; Thomas, James J.; Unwin, Stephen D.; Whitney, Paul D.; Wong, Pak C.

    2009-06-23

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

  1. A highly scalable, interoperable clinical decision support service

    PubMed Central

    Goldberg, Howard S; Paterno, Marilyn D; Rocha, Beatriz H; Schaeffer, Molly; Wright, Adam; Erickson, Jessica L; Middleton, Blackford

    2014-01-01

    Objective To create a clinical decision support (CDS) system that is shareable across healthcare delivery systems and settings over large geographic regions. Materials and methods The enterprise clinical rules service (ECRS) realizes nine design principles through a series of enterprise java beans and leverages off-the-shelf rules management systems in order to provide consistent, maintainable, and scalable decision support in a variety of settings. Results The ECRS is deployed at Partners HealthCare System (PHS) and is in use for a series of trials by members of the CDS consortium, including internally developed systems at PHS, the Regenstrief Institute, and vendor-based systems deployed at locations in Oregon and New Jersey. Performance measures indicate that the ECRS provides sub-second response time when measured apart from services required to retrieve data and assemble the continuity of care document used as input. Discussion We consider related work, design decisions, comparisons with emerging national standards, and discuss uses and limitations of the ECRS. Conclusions ECRS design, implementation, and use in CDS consortium trials indicate that it provides the flexibility and modularity needed for broad use and performs adequately. Future work will investigate additional CDS patterns, alternative methods of data passing, and further optimizations in ECRS performance. PMID:23828174

  2. Decision support for integrated water-energy planning.

    SciTech Connect

    Tidwell, Vincent Carroll; Malczynski, Leonard A.; Kobos, Peter Holmes; Castillo, Cesar; Hart, William Eugene; Klise, Geoffrey T.

    2009-10-01

    Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 39% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Coupled to this water use is the required pumping, conveyance, treatment, storage and distribution of the water which requires on average 3% of all electric power generated. While water and energy use are tightly coupled, planning and management of these fundamental resources are rarely treated in an integrated fashion. Toward this need, a decision support framework has been developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to identify trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., national, state, county, watershed, NERC region). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. Ultimately, this open and interactive modeling framework provides a tool for evaluating competing policy and technical options relevant to the energy-water nexus.

  3. Modeling access, cost, and perceived quality: computer simulation benefits orthodontic clinic staffing decisions.

    PubMed

    Montgomery, J B; LaFrancois, G G; Perry, M J

    2000-02-01

    Given limited financial resources, simulation permits a financial analysis of the optimum staffing levels for orthodontists and dental assistants in an orthodontic clinic. A computer simulation provides the information for managerial review. This study, by building a computer simulation of an orthodontic service, set out to determine the most efficient mix between providers and support staff to maximize access, maximize perceived quality, and minimize expenditures. Six combinations of providers and support staff were compared during an animated, computer-generated what-if analysis. Based on the clinic workload and size, on the cost per patient, and on the cost per quality point, the research team recommended a staffing mix of one orthodontist and three assistants. This study shows that computer simulation is an enormous asset as a decision support tool for management.

  4. Coordinated machine learning and decision support for situation awareness.

    SciTech Connect

    Draelos, Timothy John; Zhang, Peng-Chu.; Wunsch, Donald C.; Seiffertt, John; Conrad, Gregory N.; Brannon, Nathan Gregory

    2007-09-01

    For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator's input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario.

  5. Clinical decision support systems: data quality management and governance.

    PubMed

    Liaw, Siaw-Teng

    2013-01-01

    This chapter examines data quality management (DQM) and information governance (IG) of electronic decision support (EDS) systems so that they are safe and fit for use by clinicians and patients and their carers. This is consistent with the ISO definition of data quality as being fit for purpose. The scope of DQM & IG should range from data creation and collection in clinical settings, through cleaning and, where obtained from multiple sources, linkage, storage, use by the EDS logic engine and algorithms, knowledge base and guidance provided, to curation and presentation. It must also include protocols and mechanisms to monitor the safety of EDS, which will feedback into DQM & IG activities. Ultimately, DQM & IG must be integrated across the data cycle to ensure that the EDS systems provide guidance that leads to safe and effective clinical decisions and care.

  6. Combining decision support and image processing: a PROforma model.

    PubMed

    Sordo, M; Fox, J; Blum, C; Taylor, P; Lee, R; Alberdi, E

    2001-01-01

    This paper addresses two important problems in medical image interpretation:(1) integration of numeric and symbolic information, (2) access to external sources of medical knowledge. We have developed a prototype in which image processing algorithms are combined with symbolic representations for reasoning, decision making and task management in an integrated, platform-independent system for the differential diagnosis of abnormalities in mammograms. The prototype is based on PROforma, a generic technology for building decision support systems based on clinical guidelines. The PROforma language defines a set of tasks, one of which, the enquiry, is used as means of interaction with the outside world. However, the current enquiry model has proved to be too limited for our purposes. In this paper we outline a more general model, which can be used as an interface between symbolic functions and image or other signal data.

  7. Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications

    PubMed Central

    Fan, Aihua; Tang, Yu

    2017-01-01

    In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically, we address the architecture of a CDSS by characterizing it from three layers and discuss the algorithms in each layer. Also we address the applications of CDSSs in a few real scenarios and analyze the accuracy of a CDSS in consideration of the potential conflicts when using multiple clinical practice guidelines concurrently. Finally, we compare the system performance in our design with that in the other design schemes. Our study shows that our proposed design can achieve a clinical decision in a shorter time than the other designs, while ensuring a high level of system accuracy. PMID:28373881

  8. Improving the implementation of clinical decision support systems.

    PubMed

    Rüping, Stefan; Anguita, Alberto; Bucur, Anca; Cirstea, Traian Cristian; Jacobs, Björn; Torge, Antje

    2013-01-01

    Clinical decision support (CDS) systems promise to improve the quality of clinical care by helping physicians to make better, more informed decisions efficiently. However, the design and testing of CDS systems for practical medical use is cumbersome. It has been recognized that this may easily lead to a problematic mismatch between the developers' idea of the system and requirements from clinical practice. In this paper, we will present an approach to reduce the complexity of constructing a CDS system. The approach is based on an ontological annotation of data resources, which improves standardization and the semantic processing of data. This, in turn, allows to use data mining tools to automatically create hypotheses for CDS models, which reduces the manual workload in the creation of a new model. The approach is implemented in the context of EU research project p-medicine. A proof of concept implementation on data from an existing Leukemia study is presented.

  9. 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.

  10. FWFA Optimization based Decision Support System for Road Traffic Engineering

    NASA Astrophysics Data System (ADS)

    Utama, D. N.; Zaki, F. A.; Munjeri, I. J.; Putri, N. U.

    2017-01-01

    Several ways and efforts have been already conducted to formally solve the road traffic congestion. However, the objective strategy type of road traffic engineering could not be proven truly. Try and error is one inefficient way in road traffic engineering to degrade the level of congestion. The combination between fuzzy-logic and water flow algorithm methods (called FWFA) was used as a main method to construct the decision support system (DSS) for selecting the objective strategy in road traffic engineering. The proposed DSS can suggest the most optimal strategy decision in road traffic engineering. Here, a main traffic road of Juanda in area Ciputat, Tangerang Selatan, province Banten, Indonesia; was selected as a research object in this study. The constructed DSS for road traffic engineering was structurally delivered in this paper.

  11. Dynamic clinical data mining: search engine-based decision support.

    PubMed

    Celi, Leo Anthony; Zimolzak, Andrew J; Stone, David J

    2014-06-23

    The research world is undergoing a transformation into one in which data, on massive levels, is freely shared. In the clinical world, the capture of data on a consistent basis has only recently begun. We propose an operational vision for a digitally based care system that incorporates data-based clinical decision making. The system would aggregate individual patient electronic medical data in the course of care; query a universal, de-identified clinical database using modified search engine technology in real time; identify prior cases of sufficient similarity as to be instructive to the case at hand; and populate the individual patient's electronic medical record with pertinent decision support material such as suggested interventions and prognosis, based on prior outcomes. Every individual's course, including subsequent outcomes, would then further populate the population database to create a feedback loop to benefit the care of future patients.

  12. Impact of a decision-support tool on decision making at the district level in Kenya

    PubMed Central

    2013-01-01

    Background In many countries, the responsibility for planning and delivery of health services is devolved to the subnational level. Health programs, however, often fall short of efficient use of data to inform decisions. As a result, programs are not as effective as they can be at meeting the health needs of the populations they serve. In Kenya, a decision-support tool, the District Health Profile (DHP) tool was developed to integrate data from health programs, primarily HIV, at the district level and to enable district health management teams to review and monitor program progress for specific health issues to make informed service delivery decisions. Methods Thirteen in-depth interviews were conducted with ten tool users and three non-users in six districts to qualitatively assess the process of implementing the tool and its effect on data-informed decision making at the district level. The factors that affected use or non-use of the tool were also investigated. Respondents were selected via convenience sample from among those that had been trained to use the DHP tool except for one user who was self-taught to use the tool. Selection criteria also included respondents from urban districts with significant resources as well as respondents from more remote, under-resourced districts. Results Findings from the in-depth interviews suggest that among those who used it, the DHP tool had a positive effect on data analysis, review, interpretation, and sharing at the district level. The automated function of the tool allowed for faster data sharing and immediate observation of trends that facilitated data-informed decision making. All respondents stated that the DHP tool assisted them to better target existing services in need of improvement and to plan future services, thus positively influencing program improvement. Conclusions This paper stresses the central role that a targeted decision-support tool can play in making data aggregation, analysis, and presentation

  13. Dynamic remapping decisions in multi-phase parallel computations

    NASA Technical Reports Server (NTRS)

    Nicol, D. M.; Reynolds, P. F., Jr.

    1986-01-01

    The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.

  14. Decision Support Methods for Finding Phenotype — Disorder Associations in the Bone Dysplasia Domain

    PubMed Central

    Paul, Razan; Groza, Tudor; Hunter, Jane; Zankl, Andreas

    2012-01-01

    A lack of mature domain knowledge and well established guidelines makes the medical diagnosis of skeletal dysplasias (a group of rare genetic disorders) a very complex process. Machine learning techniques can facilitate objective interpretation of medical observations for the purposes of decision support. However, building decision support models using such techniques is highly problematic in the context of rare genetic disorders, because it depends on access to mature domain knowledge. This paper describes an approach for developing a decision support model in medical domains that are underpinned by relatively sparse knowledge bases. We propose a solution that combines association rule mining with the Dempster-Shafer theory (DST) to compute probabilistic associations between sets of clinical features and disorders, which can then serve as support for medical decision making (e.g., diagnosis). We show, via experimental results, that our approach is able to provide meaningful outcomes even on small datasets with sparse distributions, in addition to outperforming other Machine Learning techniques and behaving slightly better than an initial diagnosis by a clinician. PMID:23226331

  15. Sequential decision making in computational sustainability via adaptive submodularity

    USGS Publications Warehouse

    Andreas Krause,; Daniel Golovin,; Converse, Sarah J.

    2015-01-01

    Many problems in computational sustainability require making a sequence of decisions in complex, uncertain environments. Such problems are generally notoriously difficult. In this article, we review the recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems. Problems exhibiting the adaptive submodularity property can be efficiently and provably near-optimally solved using simple myopic policies. We illustrate this concept in several case studies of interest in computational sustainability: First, we demonstrate how it can be used to efficiently plan for resolving uncertainty in adaptive management scenarios. Secondly, we show how it applies to dynamic conservation planning for protecting endangered species, a case study carried out in collaboration with the US Geological Survey and the US Fish and Wildlife Service.

  16. New Decision Support for Landslide and Other Disaster Events

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of

  17. Gaussian quantum computation with oracle-decision problems

    NASA Astrophysics Data System (ADS)

    Adcock, Mark R. A.; Høyer, Peter; Sanders, Barry C.

    2013-04-01

    We study a simple-harmonic-oscillator quantum computer solving oracle decision problems. We show that such computers can perform better by using nonorthogonal Gaussian wave functions rather than orthogonal top-hat wave functions as input to the information encoding process. Using the Deutsch-Jozsa problem as an example, we demonstrate that Gaussian modulation with optimized width parameter results in a lower error rate than for the top-hat encoding. We conclude that Gaussian modulation can allow for an improved trade-off between encoding, processing and measurement of the information.

  18. Integrated decision support in a hospital cancer registry.

    PubMed

    Tafazzoli, A G; Altmann, U; Bürkle, T; Hölzer, S; Dudeck, J

    2002-03-01

    In this paper we present (a) a shell for integrated knowledge-based functions that is destined to support decision processes of the users of the Giessener Tumordokumentationssystem (GTDS) and (b) some results we obtained during a 6-month observation period at one of the customers of the GTDS. A special characteristic of the provided decision support is the high degree of integration in the underlying information system GTDS, i.e. the functions are triggered by events in the patient database, existing patient data is reused as input for the reasoning process and generated alerts are presented instantly to the end-user. The first routine field of application was supporting registrars to adhere to integrity constraints as defined by the International Agency of Research on Cancer (IARC) during the documentation process. This information is important for the registrars since the checks of the IARC are an accepted standard for data quality in cancer registries. The expected benefit of this application area is less effort in achieving adherence to the specification of the IARC by preventing the costly rectification at a later time. During the last 5 months of the observation period 164 alerts were displayed. About 65% of the assessed alerts were considered to be correct. Especially, the analysis of the incorrect alerts revealed some shortcomings in the knowledge behind some of the integrity constraints of the IARC. The general feedback from the end-users indicate positive user satisfaction. Currently, the shell is in use in six hospital cancer registries.

  19. Embedded systems for supporting computer accessibility.

    PubMed

    Mulfari, Davide; Celesti, Antonio; Fazio, Maria; Villari, Massimo; Puliafito, Antonio

    2015-01-01

    Nowadays, customized AT software solutions allow their users to interact with various kinds of computer systems. Such tools are generally available on personal devices (e.g., smartphones, laptops and so on) commonly used by a person with a disability. In this paper, we investigate a way of using the aforementioned AT equipments in order to access many different devices without assistive preferences. The solution takes advantage of open source hardware and its core component consists of an affordable Linux embedded system: it grabs data coming from the assistive software, which runs on the user's personal device, then, after processing, it generates native keyboard and mouse HID commands for the target computing device controlled by the end user. This process supports any operating system available on the target machine and it requires no specialized software installation; therefore the user with a disability can rely on a single assistive tool to control a wide range of computing platforms, including conventional computers and many kinds of mobile devices, which receive input commands through the USB HID protocol.

  20. A decision support system for assessing landfill performance

    SciTech Connect

    Celik, Basak; Girgin, Sertan; Yazici, Adnan; Unlue, Kahraman

    2010-01-15

    Designing environmentally sound landfills is a challenging engineering task due to complex interactions of numerous design variables; such as landfill size, waste characteristics, and site hydrogeology. Decision support systems (DSS) can be utilized to handle these complex interactions and to aid in a performance-based landfill design by coupling system simulation models (SSM). The aim of this paper is to present a decision support system developed for a performance-based landfill design. The developed DSS is called Landfill Design Decision Support System - LFDSS. A two-step DSS framework, composed of preliminary design and detailed design phases, is set to effectively couple and run the SSMs and calculation modules. In preliminary design phase, preliminary design alternatives are proposed using general site data. In detailed design phase, proposed design alternatives are further simulated under site-specific data using SSMs for performance evaluation. LFDSS calculates the required landfill volume, performs landfill base contour design, proposes preliminary design alternatives based on general site conditions, evaluates the performance of the proposed designs, calculates the factor of safety values for slope stability analyses, and performs major cost calculations. The DSS evaluates the results of all landfill design alternatives, and determines whether the design satisfies the predefined performance criteria. The DSS ultimately enables comparisons among different landfill designs based on their performances (i.e. leachate head stability, and groundwater contamination), constructional stability and costs. The developed DSS was applied to a real site, and the results demonstrated the strengths of the developed system on designing environmentally sound and feasible landfills.

  1. A decision support system for assessing landfill performance.

    PubMed

    Celik, Başak; Girgin, Sertan; Yazici, Adnan; Unlü, Kahraman

    2010-01-01

    Designing environmentally sound landfills is a challenging engineering task due to complex interactions of numerous design variables; such as landfill size, waste characteristics, and site hydrogeology. Decision support systems (DSS) can be utilized to handle these complex interactions and to aid in a performance-based landfill design by coupling system simulation models (SSM). The aim of this paper is to present a decision support system developed for a performance-based landfill design. The developed DSS is called Landfill Design Decision Support System - LFDSS. A two-step DSS framework, composed of preliminary design and detailed design phases, is set to effectively couple and run the SSMs and calculation modules. In preliminary design phase, preliminary design alternatives are proposed using general site data. In detailed design phase, proposed design alternatives are further simulated under site-specific data using SSMs for performance evaluation. LFDSS calculates the required landfill volume, performs landfill base contour design, proposes preliminary design alternatives based on general site conditions, evaluates the performance of the proposed designs, calculates the factor of safety values for slope stability analyses, and performs major cost calculations. The DSS evaluates the results of all landfill design alternatives, and determines whether the design satisfies the predefined performance criteria. The DSS ultimately enables comparisons among different landfill designs based on their performances (i.e. leachate head stability, and groundwater contamination), constructional stability and costs. The developed DSS was applied to a real site, and the results demonstrated the strengths of the developed system on designing environmentally sound and feasible landfills.

  2. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success

    PubMed Central

    Kawamoto, Kensaku; Houlihan, Caitlin A; Balas, E Andrew; Lobach, David F

    2005-01-01

    Objective To identify features of clinical decision support systems critical for improving clinical practice. Design Systematic review of randomised controlled trials. Data sources Literature searches via Medline, CINAHL, and the Cochrane Controlled Trials Register up to 2003; and searches of reference lists of included studies and relevant reviews. Study selection Studies had to evaluate the ability of decision support systems to improve clinical practice. Data extraction Studies were assessed for statistically and clinically significant improvement in clinical practice and for the presence of 15 decision support system features whose importance had been repeatedly suggested in the literature. Results Seventy studies were included. Decision support systems significantly improved clinical practice in 68% of trials. Univariate analyses revealed that, for five of the system features, interventions possessing the feature were significantly more likely to improve clinical practice than interventions lacking the feature. Multiple logistic regression analysis identified four features as independent predictors of improved clinical practice: automatic provision of decision support as part of clinician workflow (P < 0.00001), provision of recommendations rather than just assessments (P = 0.0187), provision of decision support at the time and location of decision making (P = 0.0263), and computer based decision support (P = 0.0294). Of 32 systems possessing all four features, 30 (94%) significantly improved clinical practice. Furthermore, direct experimental justification was found for providing periodic performance feedback, sharing recommendations with patients, and requesting documentation of reasons for not following recommendations. Conclusions Several features were closely correlated with decision support systems' ability to improve patient care significantly. Clinicians and other stakeholders should implement clinical decision support systems that incorporate these

  3. 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

  4. Use of decision support systems as a drought management tool

    USGS Publications Warehouse

    Frevert, D.; Lins, H.; ,

    2005-01-01

    Droughts present a unique challenge to water managers throughout the world and the current drought in the western United States is taxing facilities to the limit. Coping with this severe drought requires state of the art decision support systems including efficient and accurate hydrologic process models, detailed hydrologic data bases and effective river systems management modeling frameworks. This paper will outline a system of models developed by the Bureau of Reclamation, the US Geological Survey, the University of Colorado and a number of other governmental and university partners. The application of the technology to drought management in several key western river basins will be discussed.

  5. Clinical Decision Support for Immunizations (CDSi): A Comprehensive, Collaborative Strategy

    PubMed Central

    Arzt, Noam H.

    2016-01-01

    This article focuses on the requirements and current developments in clinical decision support technologies for immunizations (CDSi) in both the public health and clinical communities, with an emphasis on shareable solutions. The requirements of the Electronic Health Record Incentive Programs have raised some unique challenges for the clinical community, including vocabulary mapping, update of changing guidelines, single immunization schedule, and scalability. This article discusses new, collaborative approaches whose long-term goal is to make CDSi more sustainable for both the public and private sectors. PMID:27789956

  6. Decision support system for individualized nursing procedures: SAPIEN-Tx.

    PubMed

    Ito, M; Ramos, M P; Chern, M S; Espósito, S R; Carmagnani, M I; Cunha, I C; Piveta, V M; Nespoulos, E; Iwasa, A T; Anção, M S

    1995-01-01

    The present work proposes a Decision Support System for nursing procedures: SAPIEN-Tx. The discussion includes the acquisition, modeling , and implementation of nursing expertise professionals in Renal Transplant. It was developed to obtain better quality healthcare services, as well as an effective contribution to the nursing professional in the global assistance of their clientele. We used the KADS methodology to develop the system knowledge base. This methodology permitted us to perform the knowledge modeling with quality and organization. In opposition to the old method, errors were detected before the implementation, avoiding possible modification on the whole project structure.

  7. Decision-Making Amplification under Uncertainty: An Exploratory Study of Behavioral Similarity and Intelligent Decision Support Systems

    ERIC Educational Resources Information Center

    Campbell, Merle Wayne

    2013-01-01

    Intelligent decision systems have the potential to support and greatly amplify human decision-making across a number of industries and domains. However, despite the rapid improvement in the underlying capabilities of these "intelligent" systems, increasing their acceptance as decision aids in industry has remained a formidable challenge.…

  8. Critical infrastructure protection decision support system decision model : overview and quick-start user's guide.

    SciTech Connect

    Samsa, M.; Van Kuiken, J.; Jusko, M.; Decision and Information Sciences

    2008-12-01

    The Critical Infrastructure Protection Decision Support System Decision Model (CIPDSS-DM) is a useful tool for comparing the effectiveness of alternative risk-mitigation strategies on the basis of CIPDSS consequence scenarios. The model is designed to assist analysts and policy makers in evaluating and selecting the most effective risk-mitigation strategies, as affected by the importance assigned to various impact measures and the likelihood of an incident. A typical CIPDSS-DM decision map plots the relative preference of alternative risk-mitigation options versus the annual probability of an undesired incident occurring once during the protective life of the investment, assumed to be 20 years. The model also enables other types of comparisons, including a decision map that isolates a selected impact variable and displays the relative preference for the options of interest--parameterized on the basis of the contribution of the isolated variable to total impact, as well as the likelihood of the incident. Satisfaction/regret analysis further assists the analyst or policy maker in evaluating the confidence with which one option can be selected over another.

  9. A Decision Support System approach for rivers monitoring and sustainable management.

    PubMed

    Manos, B; Bournaris, Th; Silleos, N; Antonopoulos, V; Papathanasiou, J

    2004-01-01

    This paper presents a Decision Support System (DSS) approach developed in the context of the Copernicus project entitled System for Water Monitoring and Sustainable Management based on Ground Stations and Satellite Images (WATERMAN). The main objective of WATERMAN is the monitoring and management of the Strymon River in the Southern Balkans. The specific DSS integrates the main components of WATERMAN and helps the decision maker to monitor the Strymon region; to control and forecast the quantity and quality of the river water; as well as to make objective decisions about the state of the water based on data provided by radio computers, earth stations and satellite images processed by mathematical and statistical models and Geographical Information Systems (GIS).

  10. A Model to Support Shared Decision Making in Electronic Health Records Systems

    PubMed Central

    Lenert, Leslie; Dunlea, Robert; Del Fio, Guilherme; KellyHall, Leslie

    2014-01-01

    Shared Decision Making (SDM) is an approach to medical care based on collaboration between provider and patient with both sharing in medical decisions. When patients’ values and preferences are incorporated in decision-making, then care is more appropriate, ethically sound, and often lower in cost. However, SDM is difficult to implement in routine practice because of the time required for SDM methods, the lack of integration of SDM approaches into electronic health records systems (EHRs), and absence of explanatory mechanisms for providers on the results of patients’ use of decision aids. This paper discusses potential solutions including the concept of a “Personalize Button” for EHRs. Leveraging a four-phased clinical model for SDM, this article describes how computer decision support (CDS) technologies integrated into EHRs can help insure that healthcare is delivered in a way that is respectful of those preferences. The architecture described herein, called CDS for SDM, is built upon recognized standards that are currently integrated into certification requirements for EHRs as part of Meaningful Use regulations. While additional work is needed on modeling of preferences and on techniques for rapid communication models of preferences to clinicians, unless EHRs are re-designed to support SDM around and during clinical encounters, they are likely to continue to be an unintended barrier to SDM. With appropriate development, EHRs could be a powerful tool to promote SDM by reminding providers of situations for SDM and monitoring on going care to insure treatments are consistent with patients’ preferences. PMID:25224366

  11. 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.

  12. Striatal prediction errors support dynamic control of declarative memory decisions

    PubMed Central

    Scimeca, Jason M.; Katzman, Perri L.; Badre, David

    2016-01-01

    Adaptive memory requires context-dependent control over how information is retrieved, evaluated and used to guide action, yet the signals that drive adjustments to memory decisions remain unknown. Here we show that prediction errors (PEs) coded by the striatum support control over memory decisions. Human participants completed a recognition memory test that incorporated biased feedback to influence participants' recognition criterion. Using model-based fMRI, we find that PEs—the deviation between the outcome and expected value of a memory decision—correlate with striatal activity and predict individuals' final criterion. Importantly, the striatal PEs are scaled relative to memory strength rather than the expected trial outcome. Follow-up experiments show that the learned recognition criterion transfers to free recall, and targeting biased feedback to experimentally manipulate the magnitude of PEs influences criterion consistent with PEs scaled relative to memory strength. This provides convergent evidence that declarative memory decisions can be regulated via striatally mediated reinforcement learning signals. PMID:27713407

  13. A JAVA implementation of a medical knowledge base for decision support.

    PubMed

    Ambrosiadou, V; Goulis, D; Shankararaman, V; Shamtani, G

    1999-01-01

    Distributed decision support is a challenging issue requiring the implementation of advanced computer science techniques together with tools of development which offer ease of communication and efficiency of searching and control performance. This paper presents a JAVA implementation of a knowledge base model called ARISTOTELES which may be used in order to support the development of the medical knowledge base by clinicians in diverse specialised areas of interest. The advantages that are evident by the application of such a cognitive model are ease of knowledge acquisition, modular construction of the knowledge base and greater acceptance from clinicians.

  14. The 2013 symposium on pathology data integration and clinical decision support and the current state of field

    PubMed Central

    Baron, Jason M.; Dighe, Anand S.; Arnaout, Ramy; Balis, Ulysses J.; Black-Schaffer, W. Stephen; Carter, Alexis B.; Henricks, Walter H.; Higgins, John M.; Jackson, Brian R.; Kim, JiYeon; Klepeis, Veronica E.; Le, Long P.; Louis, David N.; Mandelker, Diana; Mermel, Craig H.; Michaelson, James S.; Nagarajan, Rakesh; Platt, Mihae E.; Quinn, Andrew M.; Rao, Luigi; Shirts, Brian H.; Gilbertson, John R.

    2014-01-01

    Background: Pathologists and informaticians are becoming increasingly interested in electronic clinical decision support for pathology, laboratory medicine and clinical diagnosis. Improved decision support may optimize laboratory test selection, improve test result interpretation and permit the extraction of enhanced diagnostic information from existing laboratory data. Nonetheless, the field of pathology decision support is still developing. To facilitate the exchange of ideas and preliminary studies, we convened a symposium entitled: Pathology data integration and clinical decision support. Methods: The symposium was held at the Massachusetts General Hospital, on May 10, 2013. Participants were selected to represent diverse backgrounds and interests and were from nine different institutions in eight different states. Results: The day included 16 plenary talks and three panel discussions, together covering four broad areas. Summaries of each presentation are included in this manuscript. Conclusions: A number of recurrent themes emerged from the symposium. Among the most pervasive was the dichotomy between diagnostic data and diagnostic information, including the opportunities that laboratories may have to use electronic systems and algorithms to convert the data they generate into more useful information. Differences between human talents and computer abilities were described; well-designed symbioses between humans and computers may ultimately optimize diagnosis. Another key theme related to the unique needs and challenges in providing decision support for genomics and other emerging diagnostic modalities. Finally, many talks relayed how the barriers to bringing decision support toward reality are primarily personnel, political, infrastructural and administrative challenges rather than technological limitations. PMID:24672737

  15. Evaluation of RxNorm for Medication Clinical Decision Support

    PubMed Central

    Freimuth, Robert R.; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G.

    2014-01-01

    We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS. PMID:25954360

  16. Evaluation of RxNorm for Medication Clinical Decision Support.

    PubMed

    Freimuth, Robert R; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G

    2014-01-01

    We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS.

  17. 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.

  18. SANDS: An Architecture for Clinical Decision Support in a National Health Information Network

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2007-01-01

    A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics. PMID:18693950

  19. Integrated Decision Support for Global Environmental Change Adaptation

    NASA Astrophysics Data System (ADS)

    Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

    2011-12-01

    Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this

  20. Comparing decision-support systems in adopting sustainable intensification criteria.

    PubMed

    Ahmadi, Bouda Vosough; Moran, Dominic; Barnes, Andrew P; Baret, Philippe V

    2015-01-01

    Sustainable intensification (SI) is a multifaceted concept incorporating the ambition to increase or maintain the current level of agricultural yields while reduce negative ecological and environmental impacts. Decision-support systems (DSS) that use integrated analytical methods are often used to support decision making processes in agriculture. However, DSS often consist of set of values, objectives, and assumptions that may be inconsistent or in conflict with merits and objectives of SI. These potential conflicts will have consequences for adoption and up-take of agricultural research, technologies and related policies and regulations such as genetic technology in pursuit of SI. This perspective paper aimed at comparing a number of frequently used socio-economic DSS with respect to their capacity in incorporating various dimensions of SI, and discussing their application to analyzing farm animal genetic resources (FAnGR) policies. The case of FAnGR policies was chosen because of its great potential in delivering merits of SI. It was concluded that flexible DSS, with great integration capacity with various natural and social sciences, are needed to provide guidance on feasibility, practicality, and policy implementation for SI.

  1. Atigeo at TREC 2014 Clinical Decision Support Task

    DTIC Science & Technology

    2014-11-01

    configurable suite of natural language processing ( NLP ) compo- nents, to compute a relevance score for each article and topic. We describe our ensemble...approach, the strategies and tools we use to create labeled data to support this approach, the components in our IR / NLP pipeline, and our results on...Indri/Lemur5 – and includes several text processing and natural lan- guage processing ( NLP ) modules, such as negation tagging, age grouping, and

  2. The Experiences of Using a Computerized Decision Support System

    PubMed Central

    Fossum, Mariann; Ehnfors, Margareta; Fruhling, Ann; Ehrenberg, Anna

    2012-01-01

    The aim was to describe the facilitators and barriers influencing the ability of nursing personnel to effectively use a CDSS for planning and treating pressure ulcers and malnutrition in nursing homes. Usability evaluations and group interviews were conducted. Facilitators were ease of use, usefulness and a supportive work environment. Lack of training, resistance to using computers and limited integration of the CDSS with the electronic health record system were reported. PMID:24199144

  3. Model-Driven Development of Decision Support Systems: Tackling the Variability Problem

    NASA Astrophysics Data System (ADS)

    Cabello, María Eugenia; Ramos, Isidro

    In this chapter, we present software variability management using conceptual models for diagnostic decision support information systems (DSS) development. We use a software product line (SPL) approach. In the construction of the SPL, two orthogonal variabilities are used to capture domain (i.e., diagnosis) and application domain (i.e., medical diagnosis) particularities. In this context, we describe how variability is managed by using our BOM (baseline-oriented modeling) approach. BOM is a framework that automatically generates applications as PRISMA software architectural models using model transformations and SPL techniques. We use model-driven architecture (MDA) to build domain models (i.e., computational-independent models, CIMs), which are automatically transformed into platform-independent models, PIMs, and then compiled to a executable application (i.e., platform-specific model, PSM). In order to illustrate BOM, we focus on a type of information system, the decision support system, specifically in the diagnostic domain.

  4. Verification and Validation of NASA-Supported Enhancements to Decision Support Tools of PECAD

    NASA Technical Reports Server (NTRS)

    Ross, Kenton W.; McKellip, Rodney; Moore, Roxzana F.; Fendley, Debbie

    2005-01-01

    This section of the evaluation report summarizes the verification and validation (V&V) of recently implemented, NASA-supported enhancements to the decision support tools of the Production Estimates and Crop Assessment Division (PECAD). The implemented enhancements include operationally tailored Moderate Resolution Imaging Spectroradiometer (MODIS) products and products of the Global Reservoir and Lake Monitor (GRLM). The MODIS products are currently made available through two separate decision support tools: the MODIS Image Gallery and the U.S. Department of Agriculture (USDA) Foreign Agricultural Service (FAS) MODIS Normalized Difference Vegetation Index (NDVI) Database. Both the Global Reservoir and Lake Monitor and MODIS Image Gallery provide near-real-time products through PECAD's CropExplorer. This discussion addresses two areas: 1. Assessments of the standard NASA products on which these enhancements are based. 2. Characterizations of the performance of the new operational products.

  5. Aggregation of Environmental Model Data for Decision Support

    NASA Astrophysics Data System (ADS)

    Alpert, J. C.

    2013-12-01

    model output offering access to probability and calibrating information for real time decision making. The aggregation content server reports over ensemble component and forecast time in addition to the other data dimensions of vertical layer and position for each variable. The unpacking, organization and reading of many binary packed files is accomplished most efficiently on the server while weather element event probability calculations, the thresholds for more accurate decision support, or display remain for the client. Our goal is to reduce uncertainty for variables of interest, e.g, agricultural importance. The weather service operational GFS model ensemble and short range ensemble forecasts can make skillful probability forecasts to alert users if and when their selected weather events will occur. A description of how this framework operates and how it can be implemented using existing NOMADS content services and applications is described.

  6. A Methodology to Support Decision Making in Flood Plan Mitigation

    NASA Astrophysics Data System (ADS)

    Biscarini, C.; di Francesco, S.; Manciola, P.

    2009-04-01

    The focus of the present document is on specific decision-making aspects of flood risk analysis. A flood is the result of runoff from rainfall in quantities too great to be confined in the low-water channels of streams. Little can be done to prevent a major flood, but we may be able to minimize damage within the flood plain of the river. This broad definition encompasses many possible mitigation measures. Floodplain management considers the integrated view of all engineering, nonstructural, and administrative measures for managing (minimizing) losses due to flooding on a comprehensive scale. The structural measures are the flood-control facilities designed according to flood characteristics and they include reservoirs, diversions, levees or dikes, and channel modifications. Flood-control measures that modify the damage susceptibility of floodplains are usually referred to as nonstructural measures and may require minor engineering works. On the other hand, those measures designed to modify the damage potential of permanent facilities are called non-structural and allow reducing potential damage during a flood event. Technical information is required to support the tasks of problem definition, plan formulation, and plan evaluation. The specific information needed and the related level of detail are dependent on the nature of the problem, the potential solutions, and the sensitivity of the findings to the basic information. Actions performed to set up and lay out the study are preliminary to the detailed analysis. They include: defining the study scope and detail, the field data collection, a review of previous studies and reports, and the assembly of needed maps and surveys. Risk analysis can be viewed as having many components: risk assessment, risk communication and risk management. Risk assessment comprises an analysis of the technical aspects of the problem, risk communication deals with conveying the information and risk management involves the decision process

  7. A Collaborative Decision Environment to Support UAV Wildfire Monitoring Missions

    NASA Astrophysics Data System (ADS)

    Frost, C. R.; Enomoto, F. Y.; D'Ortenzio, M. V.; Nguyen, Q. B.

    2006-12-01

    NASA developed the Collaborative Decision Environment (CDE), the ground-based component of its Intelligent Mission Management (IMM) technology for science missions employing long endurance unmanned aerial vehicles (UAVs). The CDE was used to support science mission planning and decision-making for a NASA- and U.S. Forest Service-sponsored mission to monitor wildfires in the western United States using a multi- spectral imager flown onboard the General Atomics Altair UAV in summer of 2006. The CDE is a ground-based system that provides the mission/science team with situational awareness, collaboration, and decision tools. The CDE is used for pre-flight planning, mission monitoring, and visualization of acquired data. It integrates external data products used for planning and executing a mission, such as weather, large wildfire locations, satellite-derived fire detection data, temporarily restricted airspace, and satellite imagery. While a prototype CDE was developed as a Java-based client/server application in 2004-2005, the team investigated the use of Google Earth to take advantage of its 3-D visualization capabilities, friendly user interface, and enhanced graphics performance. External data is acquired via the Internet by leveraging established and emerging Open Geospatial Consortium (OGC) standards and is re-formatted into the Keyhole Markup Language (KML) specification used by Google Earth. Aircraft flight position and sensor data products are relayed from the instrument ground station to CDE servers where they are made available to users. An instant messaging chat server is used to facilitate real-time communication between remote users. This paper will present an overview of the CDE system architecture, and discuss how science user input was crucial to shaping and developing the system. Examples from the UAV mission will be used to illustrate the presentation. Plans for future development work to improve mission operations, such as integration with

  8. Decision theory for computing variable and value ordering decisions for scheduling problems

    NASA Technical Reports Server (NTRS)

    Linden, Theodore A.

    1993-01-01

    Heuristics that guide search are critical when solving large planning and scheduling problems, but most variable and value ordering heuristics are sensitive to only one feature of the search state. One wants to combine evidence from all features of the search state into a subjective probability that a value choice is best, but there has been no solid semantics for merging evidence when it is conceived in these terms. Instead, variable and value ordering decisions should be viewed as problems in decision theory. This led to two key insights: (1) The fundamental concept that allows heuristic evidence to be merged is the net incremental utility that will be achieved by assigning a value to a variable. Probability distributions about net incremental utility can merge evidence from the utility function, binary constraints, resource constraints, and other problem features. The subjective probability that a value is the best choice is then derived from probability distributions about net incremental utility. (2) The methods used for rumor control in Bayesian Networks are the primary way to prevent cycling in the computation of probable net incremental utility. These insights lead to semantically justifiable ways to compute heuristic variable and value ordering decisions that merge evidence from all available features of the search state.

  9. Supporting large-scale computational science

    SciTech Connect

    Musick, R

    1998-10-01

    A study has been carried out to determine the feasibility of using commercial database management systems (DBMSs) to support large-scale computational science. Conventional wisdom in the past has been that DBMSs are too slow for such data. Several events over the past few years have muddied the clarity of this mindset: 1. 2. 3. 4. Several commercial DBMS systems have demonstrated storage and ad-hoc quer access to Terabyte data sets. Several large-scale science teams, such as EOSDIS [NAS91], high energy physics [MM97] and human genome [Kin93] have adopted (or make frequent use of) commercial DBMS systems as the central part of their data management scheme. Several major DBMS vendors have introduced their first object-relational products (ORDBMSs), which have the potential to support large, array-oriented data. In some cases, performance is a moot issue. This is true in particular if the performance of legacy applications is not reduced while new, albeit slow, capabilities are added to the system. The basic assessment is still that DBMSs do not scale to large computational data. However, many of the reasons have changed, and there is an expiration date attached to that prognosis. This document expands on this conclusion, identifies the advantages and disadvantages of various commercial approaches, and describes the studies carried out in exploring this area. The document is meant to be brief, technical and informative, rather than a motivational pitch. The conclusions within are very likely to become outdated within the next 5-7 years, as market forces will have a significant impact on the state of the art in scientific data management over the next decade.

  10. Modeling decision support rule interactions in a clinical setting.

    PubMed

    Sordo, Margarita; Rocha, Beatriz H; Morales, Alfredo A; Maviglia, Saverio M; Oglio, Elisa Dell'Oglio; Fairbanks, Amanda; Aroy, Teal; Dubois, David; Bouyer-Ferullo, Sharon; Rocha, Roberto A

    2013-01-01

    Traditionally, rule interactions are handled at implementation time through rule task properties that control the order in which rules are executed. By doing so, knowledge about the behavior and interactions of decision rules is not captured at modeling time. We argue that this is important knowledge that should be integrated in the modeling phase. In this project, we build upon current work on a conceptual schema to represent clinical knowledge for decision support in the form of if then rules. This schema currently captures provenance of the clinical content, context where such content is actionable (i.e. constraints) and the logic of the rule itself. For this project, we borrowed concepts from both the Semantic Web (i.e., Ontologies) and Complex Adaptive Systems (CAS), to explore a conceptual approach for modeling rule interactions in an enterprise-wide clinical setting. We expect that a more comprehensive modeling will facilitate knowledge authoring, editing and update; foster consistency in rules implementation and maintenance; and develop authoritative knowledge repositories to promote quality, safety and efficacy of healthcare.

  11. Integrated models to support multiobjective ecological restoration decisions.

    PubMed

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

    2017-03-24

    Many objectives motivate ecological restoration including improving vegetation condition, increasing the range and abundance of threatened species, and improving aggregate measures of biodiversity such as richness and diversity. While ecological models have been used to examine the outcomes of ecological restoration, there are few attempts to develop models to account for multiple, potentially competing objectives. We develop the first predictive model that integrates a vegetation-focused state-and-transition model with species distribution models for birds. We demonstrate how this integrated model can be used to identify effective restoration options for vegetation and bird species under a constrained budget. For example, using a typical agricultural land management scenario from south-eastern Australia, we demonstrate how the optimal management actions for promoting the occurrence of the Brown Treecreeper, an iconic threatened species, may be suboptimal for meeting vegetation condition objectives. This highlights that any 'preferred' management decision depends on the value assigned to the different objectives. An exploration of sensitivity to value weightings highlighted that 'no management' or 'weed control' were most likely to be the best management options to meet multiple objectives in the scenario we explored. We thus illustrate an approach to using the model outputs to explore trade-offs between bird and vegetation objectives. Our approach to exploring management outcomes and trade-offs using integrated modelling and structured decision support approaches has wide application for conservation management problems in which trade-offs exist between competing objectives. This article is protected by copyright. All rights reserved.

  12. Decision support in medical practice: a physician's perspective

    NASA Astrophysics Data System (ADS)

    Shieh, Yao-Yang; Roberson, Glenn H.

    1998-03-01

    A physician's decision support system consists of three components: (1) a comprehensive patient record and medical knowledge database, (2) information infrastructure for data storage, transfer, and (3) an analytical inference engine, accompanied by business operation database. Medical knowledge database provides the guideline for the selection of powerful clinical features or tests to be observed so that an accurate diagnosis as well as effective treatment can be quickly reached. With a tremendous amount of information stored in multiple data centers, it takes an effective information infrastructure to provide streamlined flow of information to the physician in a timely fashion. A real-time analytical inference engine mimics the physician's reasoning process. However due to incomplete, imperfect data and medical knowledge, a realistic output from this engine will be a list of options with associated confidence level, expected risk, so that the physician can make a well-informed final decision. Physicians are challenged to pursue the objective of ensuring an acceptable quality of care in an economically restrained environment. Therefore, business operation data have to be factored into the calculation of overall loss. Follow-up of diagnosis and treatment provides retrospective assessment of the accuracy and effectiveness of the existing inference engine.

  13. Decision Support Systems for Launch and Range Operations Using Jess

    NASA Technical Reports Server (NTRS)

    Thirumalainambi, Rajkumar

    2007-01-01

    The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

  14. Making Risk Models Operational for Situational Awareness and Decision Support

    SciTech Connect

    Paulson, Patrick R.; Coles, Garill A.; Shoemaker, Steven V.

    2012-06-12

    Modernization of nuclear power operations control systems, in particular the move to digital control systems, creates an opportunity to modernize existing legacy infrastructure and extend plant life. We describe here decision support tools that allow the assessment of different facets of risk and support the optimization of available resources to reduce risk as plants are upgraded and maintained. This methodology could become an integrated part of the design review process and a part of the operations management systems. The methodology can be applied to the design of new reactors such as small nuclear reactors (SMR), and be helpful in assessing the risks of different configurations of the reactors. Our tool provides a low cost evaluation of alternative configurations and provides an expanded safety analysis by considering scenarios while early in the implementation cycle where cost impacts can be minimized. The effects of failures can be modeled and thoroughly vetted to understand their potential impact on risk. The process and tools presented here allow for an integrated assessment of risk by supporting traditional defense in depth approaches while taking into consideration the insertion of new digital instrument and control systems.

  15. Clinical decision support for perioperative information management systems.

    PubMed

    Wanderer, Jonathan P; Ehrenfeld, Jesse M

    2013-12-01

    Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered.

  16. FRAMEWORK FOR DECISION SUPPORT USED IN CONTAMINATED LAND MANAGEMENT IN EUROPE AND NORTH AMERICA.

    SciTech Connect

    SULLIVAN,T.; BARDOS,R.P.; MAROT,C.; MARIOTTI,R.

    2000-06-01

    Effective contaminated land management requires a number of decisions addressing a suite of technical, economic and social concerns. This paper offers a common framework and terminology for describing decision support approaches, along with an overview of recent applications of decision support tools in Europe and the USA. A common problem with work on decision support approaches is a lack of a common framework and terminology to describe the process. These have been proposed in this paper.

  17. A Clinical Decision Support System for Breast Cancer Patients

    NASA Astrophysics Data System (ADS)

    Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

    This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

  18. Studying the Vendor Perspective on Clinical Decision Support

    PubMed Central

    Ash, Joan S.; Sittig, Dean F.; McMullen, Carmit K.; McCormack, James L.; Wright, Adam; Bunce, Arwen; Wasserman, Joseph; Mohan, Vishnu; Cohen, Deborah J.; Shapiro, Michael; Middleton, Blackford

    2011-01-01

    In prior work, using a Rapid Assessment Process (RAP), we have investigated clinical decision support (CDS) in ambulatory clinics and hospitals. We realized that individuals in these settings provide only one perspective related to the CDS landscape, which also includes content vendors and electronic health record (EHR) vendors. To discover content vendors’ perspectives and their perceived challenges, we modified RAP for industrial settings. We describe how we employed RAP, and show its utility by describing two illustrative themes. We found that while the content vendors believe they provide unique much-needed services, the amount of labor involved in content development is underestimated by others. We also found that the content vendors believe their products are resources to be used by practitioners, so they are somewhat protected from liability issues. To promote adequate understanding about these issues, we recommend a “three way conversation” among content vendors, EHR vendors, and user organizations. PMID:22195058

  19. Clinical decision support for physician order-entry: design challenges.

    PubMed

    Broverman, C A; Clyman, J I; Schlesinger, J M; Want, E

    1996-01-01

    We report on a joint development effort between ALLTEL Information Services Health Care Division and IBM Worldwide Healthcare Industry to demonstrate concurrent clinical decision support using Arden Syntax at order-entry time. The goal of the partnership is to build a high performance CDS toolkit that may be easily customized for multiple health care enterprises. Our work uses and promotes open technologies and health care standards while building a generalizable interface to a legacy patient-care system and clinical database. This paper identifies four areas of design challenges and solutions unique to a concurrent order-entry environment: the clinical information model, the currency of the patient virtual chart, the granularity of event triggers and rule evaluation context, and performance.

  20. Impact Decision Support Services in the Arctic - A Case Study

    NASA Astrophysics Data System (ADS)

    Scott, C. A.

    2015-12-01

    The National Weather Service Alaska Region's (AR) Regional Operation Center (ROC) provided weather and ice decision support services for the Bureau of Ocean and Energy Management (BOEM) oversight of Royal Dutch Shell's exploratory drilling operations in the Chukchi Sea during the summer and early fall of 2015. The AR ROC, coordinated input from WFO's Anchorage and Fairbanks, the NCEP/Ocean Prediction Center and Climate Prediction Center, and NOAA's National Ice Center. Briefings began in early Spring 2015, focused on melt-out and freeze up dates in the vicinity of the "Burger" drill site. Initially packages were prepared and briefed twice weekly. The frequency increased as the drilling season progressed, and included marine and aviation weather forecasts, current and forecast sea ice conditions as it impacts vessels and aircraft transiting to and from the drilling sites in the Chukchi Sea. Spot forecasts are also available for specific missions as needed.

  1. Protective jacket enabling decision support for workers in cold climate.

    PubMed

    Seeberg, Trine M; Vardoy, Astrid-Sofie B; Austad, Hanne O; Wiggen, Oystein; Stenersen, Henning S; Liverud, Anders E; Storholmen, Tore Christian B; Faerevik, Hilde

    2013-01-01

    The cold and harsh climate in the High North represents a threat to safety and work performance. The aim of this study was to show that sensors integrated in clothing can provide information that can improve decision support for workers in cold climate without disturbing the user. Here, a wireless demonstrator consisting of a working jacket with integrated temperature, humidity and activity sensors has been developed. Preliminary results indicate that the demonstrator can provide easy accessible information about the thermal conditions at the site of the worker and local cooling effects of extremities. The demonstrator has the ability to distinguish between activity and rest, and enables implementation of more sophisticated sensor fusion algorithms to assess work load and pre-defined activities. This information can be used in an enhanced safety perspective as an improved tool to advice outdoor work control for workers in cold climate.

  2. Decision support systems and methods for complex networks

    DOEpatents

    Huang, Zhenyu [Richland, WA; Wong, Pak Chung [Richland, WA; Ma, Jian [Richland, WA; Mackey, Patrick S [Richland, WA; Chen, Yousu [Richland, WA; Schneider, Kevin P [Seattle, WA

    2012-02-28

    Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

  3. Studying the vendor perspective on clinical decision support.

    PubMed

    Ash, Joan S; Sittig, Dean F; McMullen, Carmit K; McCormack, James L; Wright, Adam; Bunce, Arwen; Wasserman, Joseph; Mohan, Vishnu; Cohen, Deborah J; Shapiro, Michael; Middleton, Blackford

    2011-01-01

    In prior work, using a Rapid Assessment Process (RAP), we have investigated clinical decision support (CDS) in ambulatory clinics and hospitals. We realized that individuals in these settings provide only one perspective related to the CDS landscape, which also includes content vendors and electronic health record (EHR) vendors. To discover content vendors' perspectives and their perceived challenges, we modified RAP for industrial settings. We describe how we employed RAP, and show its utility by describing two illustrative themes. We found that while the content vendors believe they provide unique much-needed services, the amount of labor involved in content development is underestimated by others. We also found that the content vendors believe their products are resources to be used by practitioners, so they are somewhat protected from liability issues. To promote adequate understanding about these issues, we recommend a "three way conversation" among content vendors, EHR vendors, and user organizations.

  4. Clinical Decision Support for Early Recognition of Sepsis.

    PubMed

    Amland, Robert C; Hahn-Cover, Kristin E

    2016-01-01

    Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient's infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours.

  5. New decision support tool for acute lymphoblastic leukemia classification

    NASA Astrophysics Data System (ADS)

    Madhukar, Monica; Agaian, Sos; Chronopoulos, Anthony T.

    2012-03-01

    In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL. The developed system includes different methods to accurately measure furthermore cell properties in microscope blood film images. The blood images are exposed to series of pre-processing steps which include color correlation, and contrast enhancement. By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. The results show that the proposed system robustly segments and classifies acute lymphoblastic leukemia based on complete microscopic blood images.

  6. Decision support environment for medical product safety surveillance.

    PubMed

    Botsis, Taxiarchis; Jankosky, Christopher; Arya, Deepa; Kreimeyer, Kory; Foster, Matthew; Pandey, Abhishek; Wang, Wei; Zhang, Guangfan; Forshee, Richard; Goud, Ravi; Menschik, David; Walderhaug, Mark; Woo, Emily Jane; Scott, John

    2016-12-01

    We have developed a Decision Support Environment (DSE) for medical experts at the US Food and Drug Administration (FDA). The DSE contains two integrated systems: The Event-based Text-mining of Health Electronic Records (ETHER) and the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment (PANACEA). These systems assist medical experts in reviewing reports submitted to the Vaccine Adverse Event Reporting System (VAERS) and the FDA Adverse Event Reporting System (FAERS). In this manuscript, we describe the DSE architecture and key functionalities, and examine its potential contributions to the signal management process by focusing on four use cases: the identification of missing cases from a case series, the identification of duplicate case reports, retrieving cases for a case series analysis, and community detection for signal identification and characterization.

  7. Decision Support for Iteration Scheduling in Agile Environments

    NASA Astrophysics Data System (ADS)

    Szőke, Ákos

    Today’s software business development projects often lay claim to low-risk value to the customers in order to be financed. Emerging agile processes offer shorter investment periods, faster time-to-market and better customer satisfaction. To date, however, in agile environments there is no sound methodological schedule support contrary to the traditional plan-based approaches. To address this situation, we present an agile iteration scheduling method whose usefulness is evaluated with post-mortem simulation. It demonstrates that the method can significantly improve load balancing of resources (cca. 5×), produce higher quality and lower-risk feasible schedule, and provide more informed and established decisions by optimized schedule production. Finally, the paper analyzes benefits and issues from the use of this method.

  8. Research design of decision support system for team sport

    NASA Astrophysics Data System (ADS)

    Abidin, Mohammad Zukuwwan Zainol; Nawawi, Mohd Kamal Mohd; Kasim, Maznah Mat

    2016-10-01

    This paper proposes a suitable research procedure that can be referred to while conducting a Decision Support System (DSS) study, especially when the development activity of system artifacts becomes one of the research objectives. The design of the research procedure was based on the completion of a football DSS development that can help in determining the position of a player and the best team formation to be used during a game. After studying the relevant literature, we found that it is necessary to combine the conventional rainfall System Development Life Cycle (SDLC) approach with Case Study approach to help in structuring the research task and phases, which can contribute to the fulfillment of the research aim and objectives.

  9. PATHway: Decision Support in Exercise Programmes for Cardiac Rehabilitation.

    PubMed

    Filos, Dimitris; Triantafyllidis, Andreas; Chouvarda, Ioanna; Buys, Roselien; Cornelissen, Véronique; Budts, Werner; Walsh, Deirdre; Woods, Catherine; Moran, Kieran; Maglaveras, Nicos

    2016-01-01

    Rehabilitation is important for patients with cardiovascular diseases (CVD) to improve health outcomes and quality of life. However, adherence to current exercise programmes in cardiac rehabilitation is limited. We present the design and development of a Decision Support System (DSS) for telerehabilitation, aiming to enhance exercise programmes for CVD patients through ensuring their safety, personalising the programme according to their needs and performance, and motivating them toward meeting their physical activity goals. The DSS processes data originated from a Microsoft Kinect camera, a blood pressure monitor, a heart rate sensor and questionnaires, in order to generate a highly individualised exercise programme and improve patient adherence. Initial results within the EU-funded PATHway project show the potential of our approach.

  10. NOAA Climate Information and Tools for Decision Support Services

    NASA Astrophysics Data System (ADS)

    Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

    2013-12-01

    NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to

  11. Support for Diagnosis of Custom Computer Hardware

    NASA Technical Reports Server (NTRS)

    Molock, Dwaine S.

    2008-01-01

    The Coldfire SDN Diagnostics software is a flexible means of exercising, testing, and debugging custom computer hardware. The software is a set of routines that, collectively, serve as a common software interface through which one can gain access to various parts of the hardware under test and/or cause the hardware to perform various functions. The routines can be used to construct tests to exercise, and verify the operation of, various processors and hardware interfaces. More specifically, the software can be used to gain access to memory, to execute timer delays, to configure interrupts, and configure processor cache, floating-point, and direct-memory-access units. The software is designed to be used on diverse NASA projects, and can be customized for use with different processors and interfaces. The routines are supported, regardless of the architecture of a processor that one seeks to diagnose. The present version of the software is configured for Coldfire processors on the Subsystem Data Node processor boards of the Solar Dynamics Observatory. There is also support for the software with respect to Mongoose V, RAD750, and PPC405 processors or their equivalents.

  12. Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

    PubMed

    Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

    2009-04-01

    Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

  13. Facilitating knowledge transfer: decision support tools in environment and health.

    PubMed

    Liu, Hai-Ying; Bartonova, Alena; Neofytou, Panagiotis; Yang, Aileen; Kobernus, Michael J; Negrenti, Emanuele; Housiadas, Christos

    2012-06-28

    The HENVINET Health and Environment Network aimed to enhance the use of scientific knowledge in environmental health for policy making. One of the goals was to identify and evaluate Decision Support Tools (DST) in current use. Special attention was paid to four "priority" health issues: asthma and allergies, cancer, neurodevelopment disorders, and endocrine disruptors.We identified a variety of tools that are used for decision making at various levels and by various stakeholders. We developed a common framework for information acquisition about DSTs, translated this to a database structure and collected the information in an online Metadata Base (MDB).The primary product is an open access web-based MDB currently filled with 67 DSTs, accessible through the HENVINET networking portal http://www.henvinet.eu and http://henvinet.nilu.no. Quality assurance and control of the entries and evaluation of requirements to use the DSTs were also a focus of the work. The HENVINET DST MDB is an open product that enables the public to get basic information about the DSTs, and to search the DSTs using pre-designed attributes or free text. Registered users are able to 1) review and comment on existing DSTs; 2) evaluate each DST's functionalities, and 3) add new DSTs, or change the entry for their own DSTs. Assessment of the available 67 DSTs showed: 1) more than 25% of the DSTs address only one pollution source; 2) 25% of the DSTs address only one environmental stressor; 3) almost 50% of the DSTs are only applied to one disease; 4) 41% of the DSTs can only be applied to one decision making area; 5) 60% of the DSTs' results are used only by national authority and/or municipality/urban level administration; 6) almost half of the DSTs are used only by environmental professionals and researchers. This indicates that there is a need to develop DSTs covering an increasing number of pollution sources, environmental stressors and health end points, and considering links to other 'Driving

  14. Observations to support adaptation: Principles, scales and decision-making

    NASA Astrophysics Data System (ADS)

    Pulwarty, R. S.

    2012-12-01

    As has been long noted, a comprehensive, coordinated observing system is the backbone of any Earth information system. Demands are increasingly placed on earth observation and prediction systems and attendant services to address the needs of economically and environmentally vulnerable sectors and investments, including energy, water, human health, transportation, agriculture, fisheries, tourism, biodiversity, and national security. Climate services include building capacity to interpret information and recognize standards and limitations of data in the promotion of social and economic development in a changing climate. This includes improving the understanding of climate in the context of a variety of temporal and spatial scales (including the influence of decadal scale forcings and land surface feedbacks on seasonal forecast reliability). Climate data and information are central for developing decision options that are sensitive to climate-related uncertainties and the design of flexible adaptation pathways. Ideally monitoring should be action oriented to support climate risk assessment and adaptation including informing robust decision making to multiple risks over the long term. Based on the experience of global observations programs and empirical research we outline- Challenges in developing effective monitoring and climate information systems to support adaptation. The types of observations of critical importance needed for sector planning to enhance food, water and energy security, and to improve early warning for disaster risk reduction Observations needed for ecosystem-based adaptation including the identification of thresholds, maintenance of biological diversity and land degradation The benefits and limits of linking regional model output to local observations including analogs and verification for adaptation planning To support these goals a robust systems of integrated observations are needed to characterize the uncertainty surrounding emergent risks

  15. Improvements in agricultural water decision support using remote sensing

    NASA Astrophysics Data System (ADS)

    Marshall, M. T.

    2012-12-01

    Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of

  16. WEB-GIS Decision Support System for CO2 storage

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  17. Developing an Atrial Fibrillation Guideline Support Tool (AFGuST) for Shared Decision Making

    PubMed Central

    Eckman, Mark H.; Wise, Ruth E.; Naylor, Katherine; Arduser, Lora; Lip, Gregory Y.H.; Kissela, Brett; Flaherty, Matthew; Kleindorfer, Dawn; Khan, Faisal; Schauer, Daniel P.; Kues, John; Costea, Alexandru

    2015-01-01

    Objective Patient values and preferences are an important component to decision making when tradeoffs exist that impact quality of life, such as tradeoffs between stroke prevention and hemorrhage in patients with atrial fibrillation (AF) contemplating anticoagulant therapy. Our objective is to describe the development of an Atrial Fibrillation Guideline Support Tool (AFGuST) to assist the process of integrating patients’ preferences into this decision. Materials and Methods CHA2DS2VASc and HAS-BLED were used to calculate risks for stroke and hemorrhage. We developed a Markov decision analytic model as a computational “engine” to integrate patient-specific risk for stroke and hemorrhage and individual patient values for relevant outcomes in decisions about anticoagulant therapy. Results Individual patient preferences for health-related outcomes may have greater or lesser impact on the choice of optimal antithrombotic therapy, depending upon the balance of patient-specific risks for ischemic stroke and major bleeding. These factors have been incorporated into patient-tailored booklets which, along with an informational video were developed through an iterative process with clinicians and patient focus groups. Key Limitations Current risk prediction models for hemorrhage, such as the HAS-BLED, used in the AFGuST, do not incorporate all potentially significant risk factors. Novel oral anticoagulant agents recently approved for use in the United States, Canada, and Europe have not been included in the AFGuST. Rather, warfarin has been used as a conservative proxy for all oral anticoagulant therapy. Conclusions We present a proof of concept that a patient-tailored decision-support tool could bridge the gap between guidelines and practice by incorporating individual patient’s stroke and bleeding risks and their values for major bleeding events and stroke to facilitate a shared decision making process. If effective, the AFGuST could be used as an adjunct to

  18. Sequential decisions: a computational comparison of observational and reinforcement accounts.

    PubMed

    Mohammadi Sepahvand, Nazanin; Stöttinger, Elisabeth; Danckert, James; Anderson, Britt

    2014-01-01

    Right brain damaged patients show impairments in sequential decision making tasks for which healthy people do not show any difficulty. We hypothesized that this difficulty could be due to the failure of right brain damage patients to develop well-matched models of the world. Our motivation is the idea that to navigate uncertainty, humans use models of the world to direct the decisions they make when interacting with their environment. The better the model is, the better their decisions are. To explore the model building and updating process in humans and the basis for impairment after brain injury, we used a computational model of non-stationary sequence learning. RELPH (Reinforcement and Entropy Learned Pruned Hypothesis space) was able to qualitatively and quantitatively reproduce the results of left and right brain damaged patient groups and healthy controls playing a sequential version of Rock, Paper, Scissors. Our results suggests that, in general, humans employ a sub-optimal reinforcement based learning method rather than an objectively better statistical learning approach, and that differences between right brain damaged and healthy control groups can be explained by different exploration policies, rather than qualitatively different learning mechanisms.

  19. Adriatic Sea Decision Support System (ADRI-DSS)

    NASA Astrophysics Data System (ADS)

    Coppini, Giovanni; Lyubartsev, Vladyslav; Pinardi, Nadia; Montanari, Giuseppe; Rinaldi, Attilio; Serra, Stefano; Santoleri, Rosalia

    2010-05-01

    The Adriatic Sea decision support system (ADRI-DSS) consists of an on-line service built upon a set of integrated operational oceanography products. ADRI-DSS integrates the Adriatic Sea monitoring and forecasting system (AFS) with local in-situ observations and is built to support the Emilia-Romagna coastal monitoring system for marine environment and ecosystem health. The target user is the Regional Environment Prevention Agency from Emilia-Romagna (Italy) called ARPA-EMR. Specifically ADRI-DSS will support the daily action of the oceanographic section of ARPA-EMR called ARPA-DAPHNE providing all the available products (forecast, observations, simulations) from Adriatic Forecasting System. The product is shaped as required by the user and moreover ADRI-DSS also integrates with the routinely observations that the user carry out on a weekly basis. The system has been designed through the interaction with ARPA-DAPHNE and consists of a online portal containing simulation and forecast for the relevant north Adriatic region. Moreover the model products are compared with in-situ observations of temperature and salinity collected by the ARPA-DAPHNE itself. In the coming future also satellite observations and indicators will be made available by ADRI-DSS. The final aim of ADRI-DSS is to integrate selected products from the AFS with the insitu and satellite observation to support the monitoring activities of ARPA-DAPNHE and to improve ARPA-DAPHNE capabilities for the Emilia-Romagna marine environment status assessment. ADRI-DSS has been developed within ECOOP project (European COastal-shelf sea OPerational Observing and forecasting system Integrated Project). ADRI-DSS is a web-based application available via internet browsers with JavaScript capability. The server part is implemented on PHP (data management) and NCL (graphics production). The NCL is NCAR Command Language, a free interpreted language designed specifically for scientific data processing and visualization, see

  20. Verification and Validation of NASA-Supported Enhancements to PECAD's Decision Support Tools

    NASA Technical Reports Server (NTRS)

    McKellipo, Rodney; Ross, Kenton W.

    2006-01-01

    The NASA Applied Sciences Directorate (ASD), part of the Earth-Sun System Division of NASA's Science Mission Directorate, has partnered with the U.S. Department of Agriculture (USDA) to enhance decision support in the area of agricultural efficiency-an application of national importance. The ASD integrated the results of NASA Earth science research into USDA decision support tools employed by the USDA Foreign Agricultural Service (FAS) Production Estimates and Crop Assessment Division (PECAD), which supports national decision making by gathering, analyzing, and disseminating global crop intelligence. Verification and validation of the following enhancements are summarized: 1) Near-real-time Moderate Resolution Imaging Spectroradiometer (MODIS) products through PECAD's MODIS Image Gallery; 2) MODIS Normalized Difference Vegetation Index (NDVI) time series data through the USDA-FAS MODIS NDVI Database; and 3) Jason-1 and TOPEX/Poseidon lake level estimates through PECAD's Global Reservoir and Lake Monitor. Where possible, each enhanced product was characterized for accuracy, timeliness, and coverage, and the characterized performance was compared to PECAD operational requirements. The MODIS Image Gallery and the GRLM are more mature and have achieved a semi-operational status, whereas the USDA-FAS MODIS NDVI Database is still evolving and should be considered

  1. Research on web-based decision support system for sports competitions

    NASA Astrophysics Data System (ADS)

    Huo, Hanqiang

    2010-07-01

    This paper describes the system architecture and implementation technology of the decision support system for sports competitions, discusses the design of decision-making modules, management modules and security of the system, and proposes the development idea of building a web-based decision support system for sports competitions.

  2. Developing a Software for Fuzzy Group Decision Support System: A Case Study

    ERIC Educational Resources Information Center

    Baba, A. Fevzi; Kuscu, Dincer; Han, Kerem

    2009-01-01

    The complex nature and uncertain information in social problems required the emergence of fuzzy decision support systems in social areas. In this paper, we developed user-friendly Fuzzy Group Decision Support Systems (FGDSS) software. The software can be used for multi-purpose decision making processes. It helps the users determine the main and…

  3. A decision support system for telemedicine through the mobile telecommunications platform.

    PubMed

    Eren, Ali; Subasi, Abdulhamit; Coskun, Osman

    2008-02-01

    In this paper we have discussed the application of artificial intelligence in telemedicine using mobile device. The main goal of our research is to develop methods and systems to collect, analyze, distribute and use medical diagnostics information from multiple knowledge sources and areas of expertise. Physicians may collect and analyze information obtained from experts worldwide with the help of a medical decision support system. In this information retrieval system, modern communication tools such as computers and mobile phones can be used efficiently. In this work we propose a medical decision support system using the general packet radio service (GPRS). GPRS, a data extension of the mobile telephony standard Global system for mobile communications (GSM) is emerging as the first true packet-switched architecture to allow mobile subscribers to benefit from high-speed transmission rates and run JAVA based applications from their mobile terminals. An academic prototype of a medical decision support system using mobile device was implemented. The results reveal that the system could find acceptance from the medical community and it could be an effective means of providing quality health care in developing countries.

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

    PubMed Central

    Bodenreider, O.

    2008-01-01

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

  5. Question Master: An Evaluation of a Web-Based Decision-Support System for Use in Reference Environments.

    ERIC Educational Resources Information Center

    Richardson, John V., Jr.

    1998-01-01

    Question Master (QM) is a decision-support system automating some more routine, fact-type reference questions encountered by guiding librarians through a set of clarifying questions before recommending appropriate print or electronic resource from WorldCat, the OCLC (Online Computer Library Center) Online Union Catalog. This study found that the…

  6. Creating a GIS-Based Decision-Support System

    NASA Technical Reports Server (NTRS)

    Alvarado, Lori; Gates, Ann Q.; Gray, Bob; Reyes, Raul

    1998-01-01

    Tilting the Balance: Climate Variability and Water Resource Management in the Southwest, a regional conference hosted by the Pan American Center for Environmental Studies, will be held at The University of Texas at El Paso on March 2-4, 1998. The conference is supported through the US Global Change Research Program (USGCRP) established by the President in 1989, and codified by Congress in the Global Change Research Act of 1990. The NASA Mission to Planet Earth program is one of the workshops sponsors. The purpose of the regional workshops is to improve understanding of the consequences of global change. This workshop will be focused on issues along the border and the Rio Grande River and thus will bring together stakeholders from Mexico, California, Texas, New Mexico, Arizona and Colorado representing federal, state, and local governments; universities and laboratories; industry, agricultural and natural resource managers; and non-governmental organizations. This paper discusses the efforts of the NASA PACES center create a GIS-based decision-support system that can be used to facilitate discussion of the complex issues of resource management within the targeted international region.

  7. Documentation of a decision framework to support enhanced sludge washing

    SciTech Connect

    Brothers, A.J.

    1995-12-31

    This document describes a proposed decision model that, if developed to its fullest, can provide a wide range of analysis options and insights to pretreatment/sludge washing alternatives. A recent decision has been made to terminate this work

  8. Decision support system for emergency management of oil spill accidents in the Mediterranean Sea

    NASA Astrophysics Data System (ADS)

    Liubartseva, Svitlana; Coppini, Giovanni; Pinardi, Nadia; De Dominicis, Michela; Lecci, Rita; Turrisi, Giuseppe; Cretì, Sergio; Martinelli, Sara; Agostini, Paola; Marra, Palmalisa; Palermo, Francesco

    2016-08-01

    This paper presents an innovative web-based decision support system to facilitate emergency management in the case of oil spill accidents, called WITOIL (Where Is The Oil). The system can be applied to create a forecast of oil spill events, evaluate uncertainty of the predictions, and calculate hazards based on historical meteo-oceanographic datasets. To compute the oil transport and transformation, WITOIL uses the MEDSLIK-II oil spill model forced by operational meteo-oceanographic services. Results of the modeling are visualized through Google Maps. A special application for Android is designed to provide mobile access for competent authorities, technical and scientific institutions, and citizens.

  9. Decision support systems for morphology-based diagnosis and prognosis of prostate neoplasms: a methodological approach.

    PubMed

    Montironi, Rodolfo; Cheng, Liang; Lopez-Beltran, Antonio; Mazzucchelli, Roberta; Scarpelli, Marina; Bartels, Peter H

    2009-07-01

    Recent advances in computer and information technologies have allowed the integration of both numeric and non-numeric data, that is, descriptive, linguistic terms. This has led at 1 end of the spectrum of technology development to machine vision based on image understanding and, at the other, to decision support systems. This has had a significant impact on our capability to derive diagnostic and prognostic information from histopathological material with prostate neoplasms. Cancer 2009;115(13 suppl):3068-77. (c) 2009 American Cancer Society.

  10. Preaching What We Practice: Teaching Ethical Decision-Making to Computer Security Professionals

    NASA Astrophysics Data System (ADS)

    Fleischmann, Kenneth R.

    The biggest challenge facing computer security researchers and professionals is not learning how to make ethical decisions; rather it is learning how to recognize ethical decisions. All too often, technology development suffers from what Langdon Winner terms technological somnambulism - we sleepwalk through our technology design, following past precedents without a second thought, and fail to consider the perspectives of other stakeholders [1]. Computer security research and practice involves a number of opportunities for ethical decisions. For example, decisions about whether or not to automatically provide security updates involve tradeoffs related to caring versus user autonomy. Decisions about online voting include tradeoffs between convenience and security. Finally, decisions about routinely screening e-mails for spam involve tradeoffs of efficiency and privacy. It is critical that these and other decisions facing computer security researchers and professionals are confronted head on as value-laden design decisions, and that computer security researchers and professionals consider the perspectives of various stakeholders in making these decisions.

  11. Is there a need for hydrological modelling in decision support systems for nuclear emergencies.

    PubMed

    Raskob, W; Heling, R; Zheleznyak, M

    2004-01-01

    This paper discusses the role of hydrological modelling in decision support systems for nuclear emergencies. In particular, most recent developments such as, the radionuclide transport models integrated in to the decision support system RODOS will be explored. Recent progress in the implementation of physically-based distributed hydrological models for operational forecasting in national and supranational centres, may support a closer cooperation between national hydrological services and therefore, strengthen the use of hydrological and radiological models implemented in decision support systems.

  12. Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

    NASA Technical Reports Server (NTRS)

    Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.

    2013-01-01

    Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

  13. Enhancing Drought Risk Management: Tools and Services for Decision Support

    NASA Astrophysics Data System (ADS)

    Svoboda, M. D.; Hayes, M. J.

    2011-12-01

    The National Drought Mitigation Center (NDMC) (http://drought.unl.edu) has been working with the National Integrated Drought Information System (NIDIS) (http://drought.gov) and other partners with a goal of developing tools, products, services and outreach with a goal of contributing to a U.S. drought early warning system (DEWS) as well as contributing to efforts underway toward building a virtual and collaborative global drought early warning system (GDEWS). The NDMC's mission is to work to reduce societal vulnerability to drought by helping decision makers at all levels to: develop and implement DEWS, understand and prevent drought impacts and increase long-term resilience to drought through proactive risk management planning. The NDMC is a national center founded in 1995 and located at the University of Nebraska-Lincoln. The NDMC conducts basic and applied research, services and decision support applications, along with the maintaining of a number of operational drought-related tools, products and outreach activities, including the U.S. Drought Monitor (USDM), Drought Impact Reporter (DIR), Vegetation Drought Response Index (VegDRI) along with the newly developed and enhanced National Drought Atlas, Drought Ready Communities Guide to Community Drought Preparedness and our Managing Drought Risk on the Ranch planning section on our newly revamped web site at http://drought.unl.edu. This presentation will describe in more detail the various drought resources, tools, research efforts, services and collaborations already being provided by the NDMC and its partners toward developing a collaborative DEWS in the U.S. and around the world.

  14. NWS Alaska Sea Ice Program: Operations and Decision Support Services

    NASA Astrophysics Data System (ADS)

    Schreck, M. B.; Nelson, J. A., Jr.; Heim, R.

    2015-12-01

    The National Weather Service's Alaska Sea Ice Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska Sea Ice Program offers daily sea ice and sea surface temperature analysis products. The program also delivers a five day sea ice forecast 3 times each week, provides a 3 month sea ice outlook at the end of each month, and has staff available to respond to sea ice related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer sea ice free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska Sea Ice Program. The ASIP is in constant contact with the National Ice Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on sea ice outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska Sea Ice Program as well as delve into what we see as the future of the ASIP.

  15. Guided medication dosing for elderly emergency patients using real-time, computerized decision support

    PubMed Central

    Lo, Helen G; Burdick, Elisabeth; Keohane, Carol; Bates, David W

    2011-01-01

    Objective To evaluate the impact of a real-time computerized decision support tool in the emergency department that guides medication dosing for the elderly on physician ordering behavior and on adverse drug events (ADEs). Design A prospective controlled trial was conducted over 26 weeks. The status of the decision support tool alternated OFF (7/17/06–8/29/06), ON (8/29/06–10/10/06), OFF (10/10/06–11/28/06), and ON (11/28/06–1/16/07) in consecutive blocks during the study period. In patients ≥65 who were ordered certain benzodiazepines, opiates, non-steroidals, or sedative-hypnotics, the computer application either adjusted the dosing or suggested a different medication. Physicians could accept or reject recommendations. Measurements The primary outcome compared medication ordering consistent with recommendations during ON versus OFF periods. Secondary outcomes included the admission rate, emergency department length of stay for discharged patients, 10-fold dosing orders, use of a second drug to reverse the original medication, and rate of ADEs using previously validated explicit chart review. Results 2398 orders were placed for 1407 patients over 1548 visits. The majority (49/53; 92.5%) of recommendations for alternate medications were declined. More orders were consistent with dosing recommendations during ON (403/1283; 31.4%) than OFF (256/1115; 23%) periods (p≤0.0001). 673 (43%) visits were reviewed for ADEs. The rate of ADEs was lower during ON (8/237; 3.4%) compared with OFF (31/436; 7.1%) periods (p=0.02). The remaining secondary outcomes showed no difference. Limitations Single institution study, retrospective chart review for ADEs. Conclusion Though overall agreement with recommendations was low, real-time computerized decision support resulted in greater acceptance of medication recommendations. Fewer ADEs were observed when computerized decision support was active. PMID:22052899

  16. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality

    PubMed Central

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-01-01

    Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks. PMID:26610496

  17. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-11-19

    Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

  18. AQUATOOL, a generalized decision-support system for water-resources planning and operational management

    NASA Astrophysics Data System (ADS)

    Andreu, J.; Capilla, J.; Sanchís, E.

    1996-04-01

    This paper describes a generic decision-support system (DSS) which was originally designed for the planning stage of dicision-making associated with complex river basins. Subsequently, it was expanded to incorporate modules relating to the operational stage of decision-making. Computer-assisted design modules allow any complex water-resource system to be represented in graphical form, giving access to geographically referenced databases and knowledge bases. The modelling capability includes basin simulation and optimization modules, an aquifer flow modelling module and two modules for risk assessment. The Segura and Tagus river basins have been used as case studies in the development and validation phases. The value of this DSS is demonstrated by the fact that both River Basin Agencies currently use a version for the efficient management of their water resources.

  19. 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.

  20. Decision support and data warehousing tools boost competitive advantage.

    PubMed

    Waldo, B H

    1998-01-01

    The ability to communicate across the care continuum is fast becoming an integral component of the successful health enterprise. As integrated delivery systems are formed and patient care delivery is restructured, health care professionals must be able to distribute, access, and evaluate information across departments and care settings. The Aberdeen Group, a computer and communications research and consulting organization, believes that "the single biggest challenge for next-generation health care providers is to improve on how they consolidate and manage information across the continuum of care. This involves building a strategic warehouse of clinical and financial information that can be shared and leveraged by health care professionals, regardless of the location or type of care setting" (Aberdeen Group, Inc., 1997). The value and importance of data and systems integration are growing. Organizations that create a strategy and implement DSS tools to provide decision-makers with the critical information they need to face the competition and maintain quality and costs will have the advantage.

  1. Visualization Component of Vehicle Health Decision Support System

    NASA Technical Reports Server (NTRS)

    Jacob, Joseph; Turmon, Michael; Stough, Timothy; Siegel, Herbert; Walter, patrick; Kurt, Cindy

    2008-01-01

    The visualization front-end of a Decision Support System (DSS) also includes an analysis engine linked to vehicle telemetry, and a database of learned models for known behaviors. Because the display is graphical rather than text-based, the summarization it provides has a greater information density on one screen for evaluation by a flight controller.This tool provides a system-level visualization of the state of a vehicle, and drill-down capability for more details and interfaces to separate analysis algorithms and sensor data streams. The system-level view is a 3D rendering of the vehicle, with sensors represented as icons, tied to appropriate positions within the vehicle body and colored to indicate sensor state (e.g., normal, warning, anomalous state, etc.). The sensor data is received via an Information Sharing Protocol (ISP) client that connects to an external server for real-time telemetry. Users can interactively pan, zoom, and rotate this 3D view, as well as select sensors for a detail plot of the associated time series data. Subsets of the plotted data can be selected and sent to an external analysis engine to either search for a similar time series in an historical database, or to detect anomalous events. The system overview and plotting capabilities are completely general in that they can be applied to any vehicle instrumented with a collection of sensors. This visualization component can interface with the ISP for data streams used by NASA s Mission Control Center at Johnson Space Center. In addition, it can connect to, and display results from, separate analysis engine components that identify anomalies or that search for past instances of similar behavior. This software supports NASA's Software, Intelligent Systems, and Modeling element in the Exploration Systems Research and Technology Program by augmenting the capability of human flight controllers to make correct decisions, thus increasing safety and reliability. It was designed specifically as a

  2. Towards a Decision Support System for Space Flight Operations

    NASA Technical Reports Server (NTRS)

    Meshkat, Leila; Hogle, Charles; Ruszkowski, James

    2013-01-01

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

  3. Integrating Climate and Risk-Informed Science to Support Critical Decisions

    ScienceCinema

    None

    2016-08-10

    The PNNL Environmental Health and Remediation Sector stewards several decision support capabilities to integrate climate- and risk-informed science to support critical decisions. Utilizing our expertise in risk and decision analysis, integrated Earth systems modeling, and remote sensing and geoinformatics, PNNL is influencing the way science informs high level decisions at national, regional and local scales to protect and preserve our most critical assets.

  4. Integrating Climate and Risk-Informed Science to Support Critical Decisions

    SciTech Connect

    2016-07-27

    The PNNL Environmental Health and Remediation Sector stewards several decision support capabilities to integrate climate- and risk-informed science to support critical decisions. Utilizing our expertise in risk and decision analysis, integrated Earth systems modeling, and remote sensing and geoinformatics, PNNL is influencing the way science informs high level decisions at national, regional and local scales to protect and preserve our most critical assets.

  5. Will decision-support systems be widely used for the management of plant diseases?

    PubMed

    Shtienberg, Dani

    2013-01-01

    Decision-support systems (DSSs) are interactive computer-based systems that help decision makers solve unstructured problems under complex, uncertain conditions. Experimental use of DSSs has resulted in improved disease suppression and lowered risks of crop damage. In many cases, it has also led to the use of smaller quantities of active substances, as compared with standard spraying practices. Hundreds of DSSs have been developed over the years and are readily available and affordable. However, most farm managers do not use them as part of their integrated pest management (IPM) practices. Since the mid-1980s, the author of this paper, together with numerous colleagues, has developed DSSs and decision rules for the management of diseases in a variety of crops, including extensive crops, such as wheat, sunflower, and pea; semi-intensive crops, such as pear, chickpea, cotton, and tarragon; and intensive crops, such as tomato, potato, cucumber, sweet pepper, carrot, and grapevine. Some of these systems were used widely, but others were not. This experience may allow us to draw general conclusions regarding the use of DSSs and decision rules. Possible explanations for the widely varying acceptance rates are presented, and the effects of anticipated changes in the agribusiness sector on the future use of DSSs are discussed.

  6. Generalized Tumor Dose for Treatment Planning Decision Support

    NASA Astrophysics Data System (ADS)

    Zuniga, Areli A.

    Modern radiation therapy techniques allow for improved target conformity and normal tissue sparing. These highly conformal treatment plans have allowed dose escalation techniques increasing the probability of tumor control. At the same time this conformation has introduced inhomogeneous dose distributions, making delivered dose characterizations more difficult. The concept of equivalent uniform dose (EUD) characterizes a heterogeneous dose distribution within irradiated structures as a single value and has been used in biologically based treatment planning (BBTP); however, there are no substantial validation studies on clinical outcome data supporting EUD's use and therefore has not been widely adopted as decision-making support. These highly conformal treatment plans have also introduced the need for safety margins around the target volume. These margins are designed to minimize geometrical misses, and to compensate for dosimetric and treatment delivery uncertainties. The margin's purpose is to reduce the chance of tumor recurrence. This dissertation introduces a new EUD formulation designed especially for tumor volumes, called generalized Tumor Dose (gTD). It also investigates, as a second objective, margins extensions for potential improvements in local control while maintaining or minimizing toxicity. The suitability of gTD to rank LC was assessed by means of retrospective studies in a head and neck (HN) squamous cell carcinoma (SCC) and non-small cell lung cancer (NSCLC) cohorts. The formulation was optimized based on two datasets (one of each type) and then, model validation was assessed on independent cohorts. The second objective of this dissertation was investigated by ranking the probability of LC of the primary disease adding different margin sizes. In order to do so, an already published EUD formula was used retrospectively in a HN and a NSCLC datasets. Finally, recommendations for the viability to implement this new formulation into a routine treatment

  7. Machine Learning and Decision Support in Critical Care

    PubMed Central

    Johnson, Alistair E. W.; Ghassemi, Mohammad M.; Nemati, Shamim; Niehaus, Katherine E.; Clifton, David A.; Clifford, Gari D.

    2016-01-01

    Clinical data management systems typically provide caregiver teams with useful information, derived from large, sometimes highly heterogeneous, data sources that are often changing dynamically. Over the last decade there has been a significant surge in interest in using these data sources, from simply re-using the standard clinical databases for event prediction or decision support, to including dynamic and patient-specific information into clinical monitoring and prediction problems. However, in most cases, commercial clinical databases have been designed to document clinical activity for reporting, liability and billing reasons, rather than for developing new algorithms. With increasing excitement surrounding “secondary use of medical records” and “Big Data” analytics, it is important to understand the limitations of current databases and what needs to change in order to enter an era of “precision medicine.” This review article covers many of the issues involved in the collection and preprocessing of critical care data. The three challenges in critical care are considered: compartmentalization, corruption, and complexity. A range of applications addressing these issues are covered, including the modernization of static acuity scoring; on-line patient tracking; personalized prediction and risk assessment; artifact detection; state estimation; and incorporation of multimodal data sources such as genomic and free text data. PMID:27765959

  8. Geospatial decision support framework for critical infrastructure interdependency assessment

    NASA Astrophysics Data System (ADS)

    Shih, Chung Yan

    Critical infrastructures, such as telecommunications, energy, banking and finance, transportation, water systems and emergency services are the foundations of modern society. There is a heavy dependence on critical infrastructures at multiple levels within the supply chain of any good or service. Any disruptions in the supply chain may cause profound cascading effect to other critical infrastructures. A 1997 report by the President's Commission on Critical Infrastructure Protection states that a serious interruption in freight rail service would bring the coal mining industry to a halt within approximately two weeks and the availability of electric power could be reduced in a matter of one to two months. Therefore, this research aimed at representing and assessing the interdependencies between coal supply, transportation and energy production. A proposed geospatial decision support framework was established and applied to analyze interdependency related disruption impact. By utilizing the data warehousing approach, geospatial and non-geospatial data were retrieved, integrated and analyzed based on the transportation model and geospatial disruption analysis developed in the research. The results showed that by utilizing this framework, disruption impacts can be estimated at various levels (e.g., power plant, county, state, etc.) for preventative or emergency response efforts. The information derived from the framework can be used for data mining analysis (e.g., assessing transportation mode usages; finding alternative coal suppliers, etc.).

  9. Decision Support System for Aquifer Recharge (AR) and ...

    EPA Pesticide Factsheets

    Aquifer recharge (AR) is a technical method being utilized to enhance groundwater resources through man-made replenishment means, such as infiltration basins and injections wells. Aquifer storage and recovery (ASR) furthers the AR techniques by withdrawal of stored groundwater at a later time for beneficial use. It is a viable adaptation technique for water availability problems. Variants of the water storage practices include recharge through urban green infrastructure and the subsurface injection of reclaimed water, i.e., wastewater, which has been treated to remove solids and impurities. In addition to a general overview of ASR variations, this report focuses on the principles and technical basis for an ASR decision support system (DSS), with the necessary technical references provided. The DSS consists of three levels of tools and methods for ASR system planning and assessment, design, and evaluation. Level 1 of the system is focused on ASR feasibility, for which four types of data and technical information are organized around: 1) ASR regulations and permitting needs, 2) Water demand projections, 3) Climate change and water availability, and 4) ASR sites and technical information. These technical resources are integrated to quantify water availability gaps and the feasibility of using ASR to meet the volume and timing of the water resource shortages. A systemic analysis of water resources was conducted for sustainable water supplies in Las Vegas, Nevada f

  10. Development and commissioning of decision support tools for sewerage management.

    PubMed

    Manic, G; Printemps, C; Zug, M; Lemoine, C

    2006-01-01

    Managing sewerage systems is a highly complex task due to the dynamic nature of the facilities. Their performance strongly depends on the know-how applied by the operators. In order to define optimal operational settings, two decision support tools based on mathematical models have been developed. Moreover, easy-to-use interfaces have been created as well, aiding operators who presumably do not have the necessary skills to use modelling software. The two developed programs simulate the behaviour of both wastewater treatment plants (WWTP) and sewer network systems, respectively. They have essentially the same structure, including raw data management and statistical analysis, a simulation layer using the application programming interface of the applied software and a layer responsible for the representation of the obtained results. Four user modes are provided in the two software including the simulation of historical data using the applied and novel operational settings, as well as modes concerning prediction of possible operation periods and updates. Concerning the WWTP software, it was successfully installed in Nantes (France) in June 2004. Moreover, the one managing sewer networks has been deployed in Saint-Malo (France) in January 2005. This paper presents the structure of the developed software and the first results obtained during the commissioning phase.

  11. A semantic sensor web for environmental decision support applications.

    PubMed

    Gray, Alasdair J G; Sadler, Jason; Kit, Oles; Kyzirakos, Kostis; Karpathiotakis, Manos; Calbimonte, Jean-Paul; Page, Kevin; García-Castro, Raúl; Frazer, Alex; Galpin, Ixent; Fernandes, Alvaro A A; Paton, Norman W; Corcho, Oscar; Koubarakis, Manolis; De Roure, David; Martinez, Kirk; Gómez-Pérez, Asunción

    2011-01-01

    Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.

  12. [Decision support system for watershed management: a review].

    PubMed

    Cao, Yu; Yan, Jing

    2012-07-01

    Watershed management decision support system (DSS) is an intellectual system developed for the optimal allocation of water resources by watershed managers, and the simulation results of the system can directly affect the scientificity and practicability of watershed management. This paper summarized the related researches from the aspects of water quantity simulation and deployment systems, water quality monitoring and evaluation systems, and integrated watershed management systems. The main features and problems in existing DSS were analyzed, and the model structure and development status of the representative systems such as AQUA-Tool, Elbe-DSS, and HD were introduced. It was suggested that the accuracy and stability of simulated results, the succinctness of working process, and the high degree of user visualization would be the focuses in developing the DSS in the future, and the optimization of program-selecting models and 3D visualization tools, the research and development of inter-basin integrated management DSS, and the improvement of stakeholder participation would be the development trend for the future watershed management DSS.

  13. Clinical Decision Support Systems (CDSS) in GRID Environments.

    PubMed

    Blanquer, Ignacio; Hernández, Vicente; Segrelles, Damià; Robles, Montserrat; García, Juan Miguel; Robledo, Javier Vicente

    2005-01-01

    This paper presents an architecture defined for searching and executing Clinical Decision Support Systems (CDSS) in a LCG2/GT2 Grid environment, using web-based protocols. A CDSS is a system that provides a classification of the patient illness according to the knowledge extracted from clinical practice and using the patient's information in a structured format. The CDSS classification engines can be installed in any site and can be used by different medical users from a Virtual Organization (VO). All users in a VO can consult and execute different classification engines that have been installed in the Grid independently of the platform, architecture or site where the engines are installed or the users are located. The present paper present a solution to requirements such as short-job execution, reducing the response delay on LCG2 environments and providing grid-enabled authenticated access through web portals. Resource discovering and job submission is performed through web services, which are also described in the article.

  14. Agricultural Model for the Nile Basin Decision Support System

    NASA Astrophysics Data System (ADS)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

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

  15. A Semantic Sensor Web for Environmental Decision Support Applications

    PubMed Central

    Gray, Alasdair J. G.; Sadler, Jason; Kit, Oles; Kyzirakos, Kostis; Karpathiotakis, Manos; Calbimonte, Jean-Paul; Page, Kevin; García-Castro, Raúl; Frazer, Alex; Galpin, Ixent; Fernandes, Alvaro A. A.; Paton, Norman W.; Corcho, Oscar; Koubarakis, Manolis; De Roure, David; Martinez, Kirk; Gómez-Pérez, Asunción

    2011-01-01

    Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England. PMID:22164110

  16. Clinical Decision Support for Early Recognition of Sepsis

    PubMed Central

    Amland, Robert C.; Hahn-Cover, Kristin E.

    2014-01-01

    Sepsis is an inflammatory response triggered by infection, with a high in-hospital mortality rate. Early recognition and treatment can reverse the inflammatory response, with evidence of improved patient outcomes. One challenge clinicians face is identifying the inflammatory syndrome against the background of the patient’s infectious illness and comorbidities. An approach to this problem is implementation of computerized early warning tools for sepsis. This multicenter retrospective study sought to determine clinimetric performance of a cloud-based computerized sepsis clinical decision support system (CDS), understand the epidemiology of sepsis, and identify opportunities for quality improvement. Data encompassed 6200 adult hospitalizations from 2012 through 2013. Of 13% patients screened-in, 51% were already suspected to have an infection when the system activated. This study focused on a patient cohort screened-in before infection was suspected; median time from arrival to CDS activation was 3.5 hours, and system activation to diagnostic collect was another 8.6 hours. PMID:25385815

  17. Computational Psychometrics in Communication and Implications in Decision Making

    PubMed Central

    Cipresso, Pietro; Villani, Daniela; Repetto, Claudia; Bosone, Lucia; Balgera, Anna; Mauri, Maurizio; Villamira, Marco; Antonietti, Alessandro; Riva, Giuseppe

    2015-01-01

    Recent investigations emphasized the role of communication features on behavioral trust and reciprocity in economic decision making but no studies have been focused on the effect of communication on affective states in such a context. Thanks to advanced methods of computational psychometrics, in this study, affective states were deeply examined using simultaneous and synchronized recordings of gazes and psychophysiological signals in 28 female students during an investment game. Results showed that participants experienced different affective states according to the type of communication (personal versus impersonal). In particular, participants involved in personal communication felt more relaxed than participants involved in impersonal communication. Moreover, personal communication influenced reciprocity and participants' perceptions about trust and reciprocity. Findings were interpreted in the light of the Arousal/Valence Model and self-disclosure process. PMID:26339285

  18. Supporting large-scale computational science

    SciTech Connect

    Musick, R., LLNL

    1998-02-19

    Business needs have driven the development of commercial database systems since their inception. As a result, there has been a strong focus on supporting many users, minimizing the potential corruption or loss of data, and maximizing performance metrics like transactions per second, or TPC-C and TPC-D results. It turns out that these optimizations have little to do with the needs of the scientific community, and in particular have little impact on improving the management and use of large-scale high-dimensional data. At the same time, there is an unanswered need in the scientific community for many of the benefits offered by a robust DBMS. For example, tying an ad-hoc query language such as SQL together with a visualization toolkit would be a powerful enhancement to current capabilities. Unfortunately, there has been little emphasis or discussion in the VLDB community on this mismatch over the last decade. The goal of the paper is to identify the specific issues that need to be resolved before large-scale scientific applications can make use of DBMS products. This topic is addressed in the context of an evaluation of commercial DBMS technology applied to the exploration of data generated by the Department of Energy`s Accelerated Strategic Computing Initiative (ASCI). The paper describes the data being generated for ASCI as well as current capabilities for interacting with and exploring this data. The attraction of applying standard DBMS technology to this domain is discussed, as well as the technical and business issues that currently make this an infeasible solution.

  19. Demand driven decision support for efficient water resources allocation in irrigated agriculture

    NASA Astrophysics Data System (ADS)

    Schuetze, Niels; Grießbach, Ulrike Ulrike; Röhm, Patric; Stange, Peter; Wagner, Michael; Seidel, Sabine; Werisch, Stefan; Barfus, Klemens

    2014-05-01

    Due to climate change, extreme weather conditions, such as longer dry spells in the summer months, may have an increasing impact on the agriculture in Saxony (Eastern Germany). For this reason, and, additionally, declining amounts of rainfall during the growing season the use of irrigation will be more important in future in Eastern Germany. To cope with this higher demand of water, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from the optimized agronomic response at farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF) which provide the estimated yield subject to the minimum amount of irrigation water. These functions take into account the different soil types, crops and stochastically generated climate scenarios. By applying mathematical interpolation and optimization techniques, the SCWPF's are used to compute the water demand considering different constraints, for instance variable and fix costs or the producer price. This generic approach enables the computation for both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance Irrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies for an effective and efficient utilization of water in order to meet future demands. The prototype is implemented as a web-based decision support system and it is based on a service-oriented geo-database architecture.

  20. The Use of Decision Support Systems in Social Work: A Scoping Study Literature Review.

    PubMed

    Liedgren, Pernilla; Elvhage, Gudrun; Ehrenberg, Anna; Kullberg, Christian

    2016-01-01

    Decision support systems are known to be helpful for professionals in many medical professions. In social work, decision support systems have had modest use, accompanied by strong criticism from the profession but often by praise from political management. In this study the aim of the authors was to collect and report on the published evidence on decision support systems in social work. The conclusion of the authors is that a decision support system gives support to social workers in conducting a thorough investigation, but at the same time gives them the freedom to make autonomous decisions that might be the most helpful for and used by social workers. Their results also indicate that decision support systems focusing on atypical rather than typical cases are perceived as the most useful among experienced staff.

  1. Let the Games Begin: New Opportunities to Address Climate Change Communication, Education, and Decision Support

    NASA Astrophysics Data System (ADS)

    Rooney-varga, J. N.; Sterman, J.; Jones, A.; Johnston, E.; Rath, K.; Nease, J.

    2014-12-01

    A rapid transition to a low-carbon, climate-resilient society is not only possible, but could also bring many co-benefits for public health, economic wellbeing, social equity, and more. The science supporting an urgent need for such a transition has never been clearer. Yet, social science data are also clear: the public in the US (and many other similar developed economies) does not, on average, share this sense of urgency, nor have policymakers shown a willingness to put scientific evidence above the perceptions of their constituents. The gulf between scientific and public understanding of climate change has spurred research on climate change communication, learning, and decision-making, identifying barriers such as misconceptions and faulty mental models of the climate and energy systems; poor understanding of complex, dynamic systems generally; and affective and social barriers to learning and action. There is also a growing opportunity to address these barriers, through tools that rely on active learning, that are social, engaging (and even fun), and that are grounded in rigorous science. An increasing number of decision-support computer simulations are being developed, intended to make complex technical problems accessible to non-experts in an interactive format. At the same time, the use of scenario planning, role-playing games, and active learning approaches are gaining ground in policy and education spheres. Simulation-based role-playing games bring these approaches together and can provide powerful learning experiences: they offer the potential to compress time and reality; create experiences without requiring the 'real thing;' explore the consequences of our decisions that often unfold over decades; and open affective and social learning pathways. Here, we offer a perspective on the potential of these tools in climate change education, communication, and decision-support, and a brief demonstration of one tool we have developed, World Energy.

  2. 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.

  3. Computer Simulation as a Tool for Assessing Decision-Making in Pandemic Influenza Response Training

    PubMed Central

    Leaming, James M.; Adoff, Spencer; Terndrup, Thomas E.

    2013-01-01

    Introduction: We sought to develop and test a computer-based, interactive simulation of a hypothetical pandemic influenza outbreak. Fidelity was enhanced with integrated video and branching decision trees, built upon the 2007 federal planning assumptions. We conducted a before-and-after study of the simulation effectiveness to assess the simulations' ability to assess participants' beliefs regarding their own hospitals' mass casualty incident preparedness. Methods: Development: Using a Delphi process, we finalized a simulation that serves up a minimum of over 50 key decisions to 6 role-players on networked laptops in a conference area. The simulation played out an 8-week scenario, beginning with pre-incident decisions. Testing: Role-players and trainees (N=155) were facilitated to make decisions during the pandemic. Because decision responses vary, the simulation plays out differently, and a casualty counter quantifies hypothetical losses. The facilitator reviews and critiques key factors for casualty control, including effective communications, working with external organizations, development of internal policies and procedures, maintaining supplies and services, technical infrastructure support, public relations and training. Pre- and post-survey data were compared on trainees. Results: Post-simulation trainees indicated a greater likelihood of needing to improve their organization in terms of communications, mass casualty incident planning, public information and training. Participants also recognized which key factors required immediate attention at their own home facilities. Conclusion: The use of a computer-simulation was effective in providing a facilitated environment for determining the perception of preparedness, evaluating general preparedness concepts and introduced participants to critical decisions involved in handling a regional pandemic influenza surge. PMID:23687542

  4. Attitudes to Technology, Perceived Computer Self-Efficacy and Computer Anxiety as Predictors of Computer Supported Education

    ERIC Educational Resources Information Center

    Celik, Vehbi; Yesilyurt, Etem

    2013-01-01

    There is a large body of research regarding computer supported education, perceptions of computer self-efficacy, computer anxiety and the technological attitudes of teachers and teacher candidates. However, no study has been conducted on the correlation between and effect of computer supported education, perceived computer self-efficacy, computer…

  5. Transforming Fleet Network Operations with Collaborative Decision Support and Augmented Reality Technologies

    DTIC Science & Technology

    2004-03-01

    NETWORK OPERATIONS WITH COLLABORATIVE DECISION SUPPORT AND AUGMENTED REALITY TECHNOLOGIES by John J. Fay March 2004 Thesis Advisor: Alex...Network Operations with Collaborative Decision Support and Augmented Reality Technologies 6. AUTHOR(S) John J Fay 5. FUNDING NUMBERS 7. PERFORMING...management for distributed sea-based forces using existing technologies. Combining a collaborative tool, Decision Support System (DSS), and Augmented Reality (AR

  6. Decision-support tools for the assessment process

    SciTech Connect

    Whelan, Gene; Pelton, Mitch A.; Dorow, Kevin E.

    2004-06-14

    A new software system is under development that provides a framework to link disparate assessment software and databases for site-specific, regional, or national analyses. This system represents the merger of the Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES), which performs site-specific assessments, and Multi-media, Multi-pathway, Multi-receptor Risk Assessment (3MRA) methodology, which performs regional and national assessments. This Merged System is an icon-driven, site-layout platform, which represents an interactive means by which the user graphically constructs a conceptualization of the problem by visually expressing the assessment, indicating sources of contamination, contaminant travel pathways through the environment, linkages between contamination and people or wildlife, and impacts associated with the contamination. It processes data as part of a systems-based assessment and is an open-architecture, object-oriented framework, which contains ''sockets'' for a collection of databases and computer codes that will transparently simulate elements of transport, exposure, and risk assessment, including contaminant source and release to and through overland soils, vadose and saturated zones, air, surface water, food supply, intake human health impacts, sensitivity/uncertainty, ecological impacts, with the ability to expand into areas including Geographical Information System (GIS), remediation technology, cost analysis, Data Quality Objectives, life-cycle management, and conceptual site design. A user can choose from a list of models, and the assessment path forward can be visually presented, which describes the models and their linkages from source through receptor to the decision-making endpoint.

  7. SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

    PubMed

    Wright, Adam; Sittig, Dean F

    2008-12-01

    In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:

  8. A decision support framework for sustainable urban water planning and management in new urban areas.

    PubMed

    Makropoulos, C K; Morley, M; Memon, F A; Butler, D; Savic, D; Ashley, R A

    2006-01-01

    The paper discusses issues of decision support within the context of sustainable development and more specifically sustainable water cycle management to provide a context and a rationale for the decision support approach adopted within an on-going U.K. EPSRC-funded project, WaND. The paper proposes a set-up for a flexible, upgradeable, efficient and modular decision support framework and associated tools. Furthermore, the paper presents early prototypes of three decision support tools developed within the proposed framework including initial results for one of them.

  9. Development of a Mixed Scanning Interactive System for Decision Support.

    DTIC Science & Technology

    1984-07-01

    Spetzler and C. A. von Holstein . "Probability encoding in [3871 R. D. Tweney, M. E. Doherty. W. 1. Warner, D. B. Pliske. C.. . . decision analysis...different frames of the decision The significance of this observation is that a situation as indicated in Figure 10, which is cow - knowledge of information

  10. Virtual Beach: Decision Support Tools for Beach Pathogen Prediction

    EPA Science Inventory

    The Virtual Beach Managers Tool (VB) is decision-making software developed to help local beach managers make decisions as to when beaches should be closed due to predicted high levels of water borne pathogens. The tool is being developed under the umbrella of EPA's Advanced Monit...

  11. Air Traffic Control Decision Support Tools for Noise Mitigation

    NASA Technical Reports Server (NTRS)

    Tobias, Leonard

    2001-01-01

    NASA has initiated a new five year program this year, the Quiet Aircraft Technology (QAT) Program, a program which will investigate airframe and engine system noise reduction. QAT will also address community noise impact. As part of this community noise impact component, NASA will investigate air traffic management (ATM) challenges in reducing noise. In particular, controller advisory automation aids will be developed to aid the air traffic controller in addressing noise concerns as he/she manages traffic in busy terminal areas. NASA has developed controller automation tools to address capacity concerns and the QAT strategy for ATM Low Noise Operations is to build upon this tool set to create added advisories for noise mitigation. The tools developed for capacity will be briefly reviewed, followed by the QAT plans to address ATM noise concerns. A major NASA goal in global civil aviation is to triple the aviation system throughput in all-weather conditions while maintaining safety. A centerpiece of this activity is the Center/TRACON Automation System (CTAS), an evolving suite of air traffic controller decision support tools (DSTs) to enhance capacity of arrivals and departures in both the enroute center and the TRACON. Two of these DSTs, the Traffic Management Advisor (TMA) and the passive Final approach Spacing Tool (pFAST), are in daily use at the Fort Worth Center and the Dallas/Fort Worth (DFW) TRACON, respectively, where capacity gains of 5-13% have been reported in recent NASA evaluations. Under the Federal Aviation Administration's (FAA) Free Flight Phase One Program, TMA and pFAST are each being implemented at six to eight additional sites. In addition, other DSTs are being developed by NASA under the umbrella of CTAS. This means that new software will be built upon CTAS, and the paradigm of real-time simulation evaluation followed by field site development and evaluation will be the pathway for the new tools. Additional information is included in the

  12. Assessing the sensibility of two clinical decision support systems.

    PubMed

    Graham, Timothy A D; Bullard, Michael J; Kushniruk, Andre W; Holroyd, Brian R; Rowe, Brian H

    2008-10-01

    Clinicians in Emergency Medicine (EM) are increasingly exposed to guidelines and treatment recommendations. To help access and recall these recommendations, electronic Clinical Decision Support Systems (CDSS) have been developed. This study examined the use and sensibility of two CDSS designed for emergency physicians. CDDS for community acquired pneumonia (CAP) and neutropenic fever (NF) were developed by multidisciplinary teams and have been accessed via an intranet-based homepage (eCPG) for several years. Sensibility is a term coined by Feinstein that describes common sense aspects of a survey instrument. It was modified by emergency researchers to include four main headings: (1) Appropriateness; (2) Objectivity; (3) Content; and (4) Discriminative Power. Sensibility surveys were developed using an iterative approach for both the CAP and NF CDSS and distributed to all 25 emergency physicians at one Canadian site. The overall response rate was 88%. Respondents were 88% male and 83% were less than 40; all were attending EM physicians with specialty designations. A number reported never having used the CAP (21%) or NF (33%) CDSS; 54% (CAP) and 21% (NF) of respondents had used the respective CDSS less than 10 times. Overall, both CDSS were rated highly by users with a mean response of 4.95 (SD 0.56) for CAP and 5.62 (SD 0.62) for NF on a seven-point Likert scale. The majority or respondents (CAP 59%, NF 80%) felt that the NF CDSS was more likely than the CAP CDSS to decrease the chances of making a medical error in medication dose, antibiotic choice or patient disposition (4.61 vs. 5.81, p=0.008). Despite being in place for several years, CDSS for CAP and NF are not used by all EM clinicians. Users were generally satisfied with the CDSS and felt that the NF was more likely than the CAP CDSS to decrease medical errors. Additional research is required to determine the barriers to CDSS use.

  13. Interactive decision support system to predict print quality.

    PubMed

    Leman, Sugani; Lehto, Mark R

    2003-01-15

    Customers using printers occasionally experience problems such as fuzzy images, bands, or streaks. The customer may call or otherwise contact the manufacturer, who attempts to diagnose the problem based on the customer's description of the problem. This study evaluated Bayesian inference as a tool for identifying or diagnosing 16 different types of print defects from such descriptions. The Bayesian model was trained using 1701 narrative descriptions of print defects obtained from 60 subjects with varying technical backgrounds. The Bayesian model was then implemented as an interactive decision support system, which was used by eight 'agents' to diagnose print defects reported by 16 'customers' in a simulated call centre. The 'agents' and 'customers' in the simulated call centre were all students at Purdue University. Each customer made eight telephone calls, resulting in a total of 128 telephone calls in which the customer reported defects to the agents. The results showed that the Bayesian model closely fitted the data in the training set of narratives. Overall, the model correctly predicted the actual defect category with its top prediction 70% of the time. The actual defect was in the top five predictions 94% of the time. The model in the simulated call centre performed nearly as well for the test subjects. The top prediction was correct 50% of the time, and the defect was one of the top five predictions 80% of the time. Agent accuracy in diagnosing the problem improved when using the tool. These results demonstrated that the Bayesian system learned enough from the existing narratives to accurately classify print defect categories.

  14. A Medical Decision Support System for the Space Station Health Maintenance Facility

    PubMed Central

    Ostler, David V.; Gardner, Reed M.; Logan, James S.

    1988-01-01

    NASA is developing a Health Maintenance Facility (HMF) to provide the equipment and supplies necessary to deliver medical care in the Space Station. An essential part of the Health Maintenance Facility is a computerized Medical Decision Support System (MDSS) that will enhance the ability of the medical officer (“paramedic” or “physician”) to maintain the crew's health, and to provide emergency medical care. The computer system has four major functions: 1) collect and integrate medical information into an electronic medical record from Space Station medical officers, HMF instrumentation, and exercise equipment; 2) provide an integrated medical record and medical reference information management system; 3) manage inventory for logistical support of supplies and secure pharmaceuticals; 4) supply audio and electronic mail communications between the medical officer and ground based flight surgeons. ImagesFigure 1

  15. Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

    NASA Technical Reports Server (NTRS)

    Cole, Rod; Green, Steve; Jardin, Matt; Schwartz, Barry; Benjamin, Stan

    2000-01-01

    The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an

  16. Decision Support Model for Municipal Solid Waste Management at Department of Defense Installations.

    DTIC Science & Technology

    1995-12-01

    This research focuses on the development of a decision support model to identify the preferred strategy for managing municipal solid waste using the...principles of decision analysis theory. The model provides an effective decision making tool to evaluate and compare different municipal solid waste management

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  18. The Spartan attitude control system - Ground support computer

    NASA Technical Reports Server (NTRS)

    Schnurr, R. G., Jr.

    1986-01-01

    The Spartan Attitude Control System (ACS) contains a command and control computer. This computer is optimized for the activities of the flight and contains very little human interface hardware and software. The computer system provides the technicians testing of Spartan ACS with a convenient command-oriented interface to the flight ACS computer. The system also decodes and time tags data automatically sent out by the flight computer as key events occur. The duration and magnitude of all system maneuvers is also derived and displayed by this system. The Ground Support Computer is also the primary Ground Support Equipment for the flight sequencer which controls all payload maneuvers, and long term program timing.

  19. A Computing Infrastructure for Supporting Climate Studies

    NASA Astrophysics Data System (ADS)

    Yang, C.; Bambacus, M.; Freeman, S. M.; Huang, Q.; Li, J.; Sun, M.; Xu, C.; Wojcik, G. S.; Cahalan, R. F.; NASA Climate @ Home Project Team

    2011-12-01

    Climate change is one of the major challenges facing us on the Earth planet in the 21st century. Scientists build many models to simulate the past and predict the climate change for the next decades or century. Most of the models are at a low resolution with some targeting high resolution in linkage to practical climate change preparedness. To calibrate and validate the models, millions of model runs are needed to find the best simulation and configuration. This paper introduces the NASA effort on Climate@Home project to build a supercomputer based-on advanced computing technologies, such as cloud computing, grid computing, and others. Climate@Home computing infrastructure includes several aspects: 1) a cloud computing platform is utilized to manage the potential spike access to the centralized components, such as grid computing server for dispatching and collecting models runs results; 2) a grid computing engine is developed based on MapReduce to dispatch models, model configuration, and collect simulation results and contributing statistics; 3) a portal serves as the entry point for the project to provide the management, sharing, and data exploration for end users; 4) scientists can access customized tools to configure model runs and visualize model results; 5) the public can access twitter and facebook to get the latest about the project. This paper will introduce the latest progress of the project and demonstrate the operational system during the AGU fall meeting. It will also discuss how this technology can become a trailblazer for other climate studies and relevant sciences. It will share how the challenges in computation and software integration were solved.

  20. Merging Energy Policy Decision Support, Education, and Communication: The 'World Energy' Simulation Role-Playing Game

    NASA Astrophysics Data System (ADS)

    Rooney-varga, J. N.; Franck, T.; Jones, A.; Sterman, J.; Sawin, E.

    2013-12-01

    To meet international goals for climate change mitigation and adaptation, as well as energy access and equity, there is an urgent need to explore and define energy policy paths forward. Despite this need, students, citizens, and decision-makers often hold deeply flawed mental models of the energy and climate systems. Here we describe a simulation role-playing game, World Energy, that provides an immersive learning experience in which participants can create their own path forward for global energy policy and learn about the impact of their policy choices on carbon dioxide emissions, temperature rise, energy supply mix, energy prices, and energy demand. The game puts players in the decision-making roles of advisors to the United Nations Sustainable Energy for All Initiative (drawn from international leaders from industry, governments, intergovernmental organizations, and citizens groups) and, using a state-of-the-art decision-support simulator, asks them to negotiate a plan for global energy policy. We use the En-ROADS (Energy Rapid Overview and Decision Support) simulator, which runs on a laptop computer in <0.1 sec. En-ROADS enables users to specify many factors, including R&D-driven cost reductions in fossil fuel-based, renewable, or carbon-neutral energy technologies; taxes and subsidies for different energy sources; performance standards and energy efficiency; emissions prices; policies to address other greenhouse gas emissions (e.g., methane, nitrous oxide, chlorofluorocarbons, etc.); and assumptions about GDP and population. In World Energy, participants must balance climate change mitigation goals with equity, prices and access to energy, and the political feasibility of policies. Initial results indicate participants gain insights into the dynamics of the energy and climate systems and greater understanding of the potential impacts policies.

  1. SADA: Ecological Risk Based Decision Support System for Selective Remediation

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

  2. Extracting clinical information to support medical decision based on standards.

    PubMed

    Gomoi, Valentin; Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Stoicu-Tivadar, Vasile

    2011-01-01

    The paper presents a method connecting medical databases to a medical decision system, and describes a service created to extract the necessary information that is transferred based on standards. The medical decision can be improved based on many inputs from different medical locations. The developed solution is described for a concrete case concerning the management for chronic pelvic pain, based on the information retrieved from diverse healthcare databases.

  3. Knowledge-Based Decision Support in Department of Defense Acquisitions

    DTIC Science & Technology

    2010-09-01

    2005) reviewed and analyzed the National Aeronautics and Space Administration ( NASA ) project management policies and compared them to the GAO’s best...practices on knowledge-based decision making. The study was primarily focused on the Goddard Space Flight Center, the Jet Propulsion Lab, Johnson ...Space Center, and Marshall Space Flight Center. During its investigation, the GAO found NASA deficient in key criteria and decision reviews to fully

  4. Visualization support for risk-informed decision making when planning and managing software developments

    NASA Technical Reports Server (NTRS)

    Feather, Martin S.; Kiper, James D.; Menzies, Tim

    2005-01-01

    Key decisions are made in the early stages of planning and management of software developments. The information basis for these decisions is often a mix of analogy with past developments, and the best judgments of domain experts. Visualization of this information can support to such decision making by clarifying the status of the information and yielding insights into the ramifications of that information vis-a-vis decision alternatives.

  5. Software Support for Transiently Powered Computers

    SciTech Connect

    Van Der Woude, Joel Matthew

    2015-06-01

    With the continued reduction in size and cost of computing, power becomes an increasingly heavy burden on system designers for embedded applications. While energy harvesting techniques are an increasingly desirable solution for many deeply embedded applications where size and lifetime are a priority, previous work has shown that energy harvesting provides insufficient power for long running computation. We present Ratchet, which to the authors knowledge is the first automatic, software-only checkpointing system for energy harvesting platforms. We show that Ratchet provides a means to extend computation across power cycles, consistent with those experienced by energy harvesting devices. We demonstrate the correctness of our system under frequent failures and show that it has an average overhead of 58.9% across a suite of benchmarks representative for embedded applications.

  6. Academic Support Services and Career Decision-Making Self-Efficacy in Student Athletes

    ERIC Educational Resources Information Center

    Burns, Gary N.; Jasinski, Dale; Dunn, Steve; Fletcher, Duncan

    2013-01-01

    This study examined the relationship between evaluations of academic support services and student athletes' career decision-making self-efficacy. One hundred and fifty-eight NCAA athletes (68% male) from 11 Division I teams completed measures of satisfaction with their academic support services, career decision-making self-efficacy, general…

  7. Validation of a decision support system for improving irrigation system performance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To address water shortage and improve water delivery operations, decision support systems have been developed and utilized throughout the United States and the world. One critical aspect that is often neglected during the development and implementation of decision support systems is validation, whi...

  8. Decision Support Tool Prototype for the Enlistment Incentive Review Board: Phase 2

    DTIC Science & Technology

    2014-07-01

    51 ARMY ENLISTMENT INCENTIVE REVIEW BOARD DECISION SUPPORT TOOL .........53 Introduction ...50 ARMY ENLISTMENT INCENTIVE REVIEW BOARD DECISION SUPPORT TOOL Introduction One of the objectives of this...application to travel demand. Cambridge, MA: MIT Press. Bierlaire, M. (2003). An introduction to BIOGEME (Version 1.3) http://roso.epfl.ch/biogeme

  9. Methodology for the use of DSSAT Models for Precision Agriculture Decision Support

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A prototype decision support system (DSS) called Apollo was developed to assist researchers in using the Decision Support System for Agrotechnology Transfer (DSSAT) crop growth models to analyze precision farming datasets. Because the DSSAT models are written to simulate crop growth and development...

  10. Structured decision making as a framework for linking quantitative decision support to community values

    EPA Science Inventory

    Community-level decisions can have large impacts on production and delivery of ecosystem services, which ultimately affects community well-being. But engaging stakeholders in a process to explore these impacts is a significant challenge. The principles of Structured Decision Ma...

  11. Computer-Supported Collaborative Learning in Higher Education

    ERIC Educational Resources Information Center

    Roberts, Tim, Ed.

    2005-01-01

    "Computer-Supported Collaborative Learning in Higher Education" provides a resource for researchers and practitioners in the area of computer-supported collaborative learning (also known as CSCL); particularly those working within a tertiary education environment. It includes articles of relevance to those interested in both theory and practice in…

  12. Computational Support for Diverse Research Projects.

    DTIC Science & Technology

    1986-06-06

    tensi- ve use of the purclasecl computer system are given. .,A i ’I)P ABSTRACT 21 ABSTRACT SECURIJY CLASSIFICATION ’ w ir) rr LI SAME AS RP E]OTIC USERS...on widely disparate time and length scales . Before- hand knowledge of these scales can be used profitably to generate numerical schemes capable of

  13. Computer Support Of Engineering Development And Test At Martin Marietta

    NASA Astrophysics Data System (ADS)

    Israel, Richard E.

    1985-10-01

    The Technical Computer Center has been providing computer aided engineering support from the origin of Orlando Aerospace engineering. These computer aids have evolved as the computer technologies have evolved. Historically, TCC's hybrid lab has supported Systems Engineering activities of trajectory analysis, autopilot and guidance analysis, and design verification. Also, TCC's MADRE lab has traditionally supported engineering data acquisition, reduction, and analysis. More recently the capabilities of TCC have been expanded to meet the requirements of Electro-optic, Electronic, and Mechanical engineering analysis and design.

  14. Spatial decision supporting for winter wheat irrigation and fertilizer optimizing in North China Plain

    NASA Astrophysics Data System (ADS)

    Yang, Xiaodong; Yang, Hao; Dong, Yansheng; Yu, Haiyang

    2014-11-01

    Production management of winter wheat is more complicated than other crops since its growth period is covered all four seasons and growth environment is very complex with frozen injury, drought, insect or disease injury and others. In traditional irrigation and fertilizer management, agricultural technicians or farmers mainly make decision based on phenology, planting experience to carry out artificial fertilizer and irrigation management. For example, wheat needs more nitrogen fertilizer in jointing and booting stage by experience, then when the wheat grow to the two growth periods, the farmer will fertilize to the wheat whether it needs or not. We developed a spatial decision support system for optimizing irrigation and fertilizer measures based on WebGIS, which monitoring winter wheat growth and soil moisture content by combining a crop model, remote sensing data and wireless sensors data, then reasoning professional management schedule from expert knowledge warehouse. This system is developed by ArcIMS, IDL in server-side and JQuery, Google Maps API, ASP.NET in client-side. All computing tasks are run on server-side, such as computing 11 normal vegetable indexes (NDVI/ NDWI/ NDWI2/ NRI/ NSI/ WI/ G_SWIR/ G_SWIR2/ SPSI/ TVDI/ VSWI) and custom VI of remote sensing image by IDL; while real-time building map configuration file and generating thematic map by ArcIMS.

  15. Decision support systems in water and wastewater treatment process selection and design: a review.

    PubMed

    Hamouda, M A; Anderson, W B; Huck, P M

    2009-01-01

    The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.

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

    PubMed Central

    Aronsky, D.; Haug, P. J.

    1999-01-01

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

  17. Numerical Package in Computer Supported Numeric Analysis Teaching

    ERIC Educational Resources Information Center

    Tezer, Murat

    2007-01-01

    At universities in the faculties of Engineering, Sciences, Business and Economics together with higher education in Computing, it is stated that because of the difficulty, calculators and computers can be used in Numerical Analysis (NA). In this study, the learning computer supported NA will be discussed together with important usage of the…

  18. Decision Support Services provided by the NWS Alaska Regional Operations Center in 2015

    NASA Astrophysics Data System (ADS)

    van Breukelen, C. M.; Osiensky, J. M.

    2015-12-01

    The NWS Alaska Region's Regional Operations Center (AR ROC) provides a variety of decision support services to partners and customers across the state. The AR ROC is virtual most times but can flex to stand up support for partners as needed. Support can vary from briefings over the phone or in person to dedicated virtual support to providing on-site meteorologist at an Emergency Operations Center or Incident Command Post to provide tailored support services. During 2015 there have been a number of situations where the AR ROC provided unique support services. This presentation will outline a few examples of how these unique support services benefitted partner agency decisions.

  19. Multi-agent System for Rapid TST Decision Support

    DTIC Science & Technology

    2008-06-01

    13th ICCRTS: C2 for Complex Endeavors “ Multi - agent System for Rapid TST Decision Support” Topic #5, #8 and #9 Joseph Barker, Dr. Robert...OMB control number. 1. REPORT DATE JUN 2008 2. REPORT TYPE 3. DATES COVERED 00-00-2008 to 00-00-2008 4. TITLE AND SUBTITLE Multi - agent System for...unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 13th ICCRTS: C2 for Complex Endeavors Multi - agent System for Rapid TST Decision

  20. Mountaineer`s gas facilities decision support system

    SciTech Connect

    1997-02-01

    Mountaineer Gas Co. of Charleston, W.Va., is justifiably proud of its capacity to combine electronic maps with a full database of information about its facilities and customers, and use that mix to make the decisions required in operating a gas company with better information and more quickly. Determining when a pipeline needs replacement or repair used to take several days at Mountaineer. With the new system in place, the decision can be made in a matter of minutes. The paper describes the system and its development, then discusses adding customer information as the next step.

  1. Decision support system to study climate change impacts on crop production

    SciTech Connect

    Hoogenboom, G.; Tsuji, G.Y.; Pickering, N.B.; Curry, R.B.; Jones, J.W.; Singh, U. |; Godwin, D.C.

    1995-12-31

    Under the auspices of the International Benchmark Sites Network for Agrotechnology Transfer (IBSNAT) Project a Decision Support System for Agrotechnology Transfer (DSSAT) has been developed. DSSAT operates on a personal compute rand includes data base management programs for climate, soil, and cultural practice information; crop simulation models for cereal grains, grain legumes, and root crops; and seasonal strategy and risk analysis programs. The IBSNAT crop models use daily weather data, i.e., maximum and minimum air temperature, solar radiation, and precipitation, as inputs. One of the applications of DSSAT is, therefore, to study the potential impact of climate change on agricultural production. A new and special version of DSSAT (Version 2.5) was developed to facilitate studies of the effect of climate change on crop performance. In this version, the daily canopy photosynthesis and transpiration sections of the CERES and GRO models were modified to respond to changes in CO{sub 2} concentration. The management sections of the models and the strategy analysis program were expanded to include the option to modify weather data interactively. This decision support system has been used to study changes in crop yield, irrigation requirements, and other responses to global climate change in various regional, national, and international research programs. 65 refs., 7 figs., 6 tabs.

  2. Developing a framework to support shared decision making for youth mental health medication treatment.

    PubMed

    Crickard, Elizabeth L; O'Brien, Megan S; Rapp, Charles A; Holmes, Cheryl L

    2010-10-01

    Medical shared decision making has demonstrated success in increasing collaboration between clients and practitioners for various health decisions. As the importance of a shared decision making approach becomes increasingly valued in the adult mental health arena, transfer of these ideals to youth and families of youth in the mental health system is a logical next step. A review of the literature and preliminary, formative feedback from families and staff at a Midwestern urban community mental health center guided the development of a framework for youth shared decision making. The framework includes three functional areas (1) setting the stage for youth shared decision making, (2) facilitating youth shared decision making, and (3) supporting youth shared decision making. While still in the formative stages, the value of a specific framework for a youth model in support of moving from a client-practitioner value system to a systematic, intentional process is evident.

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

    PubMed Central

    2011-01-01

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

  4. Decision Support from Local Data: Creating Adaptive Order Menus from Past Clinician Behavior

    PubMed Central

    Klann, Jeffrey G.; Szolovits, Peter; Downs, Stephen; Schadow, Gunther

    2014-01-01

    Objective Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based clinical decision support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. Materials and Methods We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the urgent visit clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. Results A short order menu on average contained the next order (weighted average length 3.91–5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714–.844 (depending on domain). However, AUC had high variance (.50–.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an association rule mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less

  5. Improving Information Products for System 2 Decision Support

    ERIC Educational Resources Information Center

    Gibson, Neal

    2010-01-01

    The creation, maintenance, and management of Information Product (IP) systems that are used by organizations for complex decisions represent a unique set of challenges. These challenges are compounded when the purpose of such a systems is also for knowledge creation and dissemination. Information quality research to date has focused mainly upon…

  6. Managerial Analysis and Decision Support: A Guidebook and Case Studies

    ERIC Educational Resources Information Center

    National Association of College and University Business Officers (NJ3), 2004

    2004-01-01

    Developed and edited by the National Association of College and University Business Officers' (NACUBO's) Accounting Principles Council, this guidebook, written by highly experienced, seasoned college and university leaders, is designed to help readers make sense of today's world and provide the right tools to make the right decisions. The book,…

  7. Fuzzy Comprehensive Evaluation (FCE) in Military Decision Support Processes

    DTIC Science & Technology

    2013-12-01

    Fuzzy logic , Fuzzy Comprehensive Evaluation (FCE), Decision Making, simulation 15. NUMBER OF PAGES 69 16. PRICE CODE 17. SECURITY CLASSIFICATION...COMPREHENSIVE ANALYSIS (FCE) METHOD ....................... 5   A.   FUZZY LOGIC ...as well as military applications (Li, Ma, & Liu, 2004). Lotfi A. Zadeh, the creator of fuzzy logic , noted in a 1994 interview with Azerbaijan

  8. ENVIRONMENTAL FEATURE FINDER: A REMOTE SENSING DECISION SUPPORT TOOL

    EPA Science Inventory

    Land cover maps are essential to sound environmental stewardship and EPA’s mission to protect human health and the environment, but existing maps are not always sufficiently current, detailed, or appropriate for a given application. Consequently, we are developing a decision sup...

  9. Estimating Supply-Chain Burdens in Support of Acquisition Decisions

    DTIC Science & Technology

    2013-03-20

    Acquisition decisions drive supply - chain requirements that incur financial costs and other critical impacts. To account properly for the resource...operational scenario. This research uses economic input/output analysis to model the Department of Defense supply chain to estimate the fully burdened cost

  10. Factors Influencing the Adoption of Cloud Computing by Decision Making Managers

    ERIC Educational Resources Information Center

    Ross, Virginia Watson

    2010-01-01

    Cloud computing is a growing field, addressing the market need for access to computing resources to meet organizational computing requirements. The purpose of this research is to evaluate the factors that influence an organization in their decision whether to adopt cloud computing as a part of their strategic information technology planning.…

  11. Decision support: Applying climate information for practical insights and actionable information (Invited)

    NASA Astrophysics Data System (ADS)

    Moss, R. H.

    2013-12-01

    A wide range of decision-makers - including policy makers and many categories of professionals - should be considering climate information in their decisions and plans. AGU members may increasingly be called on to provide this information. This presentation will explore the importance of a broad approach to developing information of use in decision making. Traditional climate research must be supplemented with climate change decision science that incorporates climate information and includes decision analysis and qualitative research on institutions, perceptions, and other socioeconomic processes essential to implementing adaptation and mitigation decisions. Adoption of this broader paradigm and development of partnerships with decision and social scientists is essential to render climate data into actionable insights. The talk will draw on recent experience with applying modeling in decision support and introduce some practical suggestions.

  12. Hydrologic Drought Decision Support System (HyDroDSS)

    USGS Publications Warehouse

    Granato, Gregory E.

    2014-01-01

    The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions

  13. RECOVER: An Automated, Cloud-Based Decision Support System for Post-Fire Rehabilitation Planning

    NASA Astrophysics Data System (ADS)

    Schnase, J. L.; Carroll, M. L.; Weber, K. T.; Brown, M. E.; Gill, R. L.; Wooten, M.; May, J.; Serr, K.; Smith, E.; Goldsby, R.; Newtoff, K.; Bradford, K.; Doyle, C.; Volker, E.; Weber, S.

    2014-11-01

    RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

  14. RECOVER: An Automated Cloud-Based Decision Support System for Post-fire Rehabilitation Planning

    NASA Technical Reports Server (NTRS)

    Schnase, John L.; Carroll, Mark; Weber, K. T.; Brown, Molly E.; Gill, Roger L.; Wooten, Margaret; May J.; Serr, K.; Smith, E.; Goldsby, R.; Newtoff, Kiersten; Bradford, Kathryn; Doyle Colin S.; Volker, Emily; Weber, Samuel J.

    2014-01-01

    RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

  15. Applicability of aquifer impact models to support decisions at CO2 sequestration sites

    SciTech Connect

    Keating, Elizabeth; Bacon, Diana; Carroll, Susan; Mansoor, Kayyum; Sun, Yunwei; Zheng, Liange; Harp, Dylan; Dai, Zhenxue

    2016-09-01

    The National Risk Assessment Partnership has developed a suite of tools to assess and manage risk at CO2 sequestration sites (www.netldoe.gov/nrap). This capability includes polynomial or look-up table based reduced-order models (ROMs) that predict the impact of CO2 and brine leaks on overlying aquifers. The development of these computationally-efficient models and the underlying reactive transport simulations they emulate has been documented elsewhere (Carroll et al., 2014, Dai et al., 2014, Keating et al., 2015). The ROMs reproduce the ensemble behavior of large numbers of simulations and are well-suited to applications that consider a large number of scenarios to understand parameter sensitivity and uncertainty on the risk of CO2 leakage to groundwater quality. In this paper, we seek to demonstrate applicability of ROM-based ensemble analysis by considering what types of decisions and aquifer types would benefit from the ROM analysis. We present four hypothetical four examples where applying ROMs, in ensemble mode, could support decisions in the early stages in a geologic CO2 sequestration project. These decisions pertain to site selection, site characterization, monitoring network evaluation, and health impacts. In all cases, we consider potential brine/CO2 leak rates at the base of the aquifer to be uncertain. We show that derived probabilities provide information relevant to the decision at hand. Although the ROMs were developed using site-specific data from two aquifers (High Plains and Edwards), the models accept aquifer characteristics as variable inputs and so they may have more broad applicability. We conclude that pH and TDS predictions are the most transferable to other aquifers based on the analysis of the nine water quality metrics (pH, TDS, 4 trace metals, 3 organic compounds). Guidelines are presented for determining the aquifer types for which the ROMs should be applicable.

  16. Interventions to support children’s engagement in health-related decisions: a systematic review

    PubMed Central

    2014-01-01

    Background Children often need support in health decision-making. The objective of this study was to review characteristics and effectiveness of interventions that support health decision-making of children. Methods A systematic review. Electronic databases (PubMed, the Cochrane Library, Web of Science, Scopus, ProQuest Dissertations and Theses, CINAHL, PsycINFO, MEDLINE, and EMBASE) were searched from inception until March 2012. Two independent reviewers screened eligibility: a) intervention studies; b) involved supporting children (≤18 years) considering health-related decision(s); and c) measured decision quality or decision-making process outcomes. Data extraction and quality appraisal were conducted by one author and verified by another using a standardized data extraction form. Quality appraisal was based on the Cochrane Risk of Bias tool. Results Of 4313 citations, 5 studies were eligible. Interventions focused on supporting decisions about risk behaviors (n = 3), psycho-educational services (n = 1), and end of life (n = 1). Two of 5 studies had statistically significant findings: i) compared to attention placebo, decision coaching alone increased values congruence between child and parent, and child satisfaction with decision-making process (lower risk of bias); ii) compared to no intervention, a workshop with weekly assignments increased overall decision-making quality (higher risk of bias). Conclusions Few studies have focused on interventions to support children’s participation in decisions about their health. More research is needed to determine effective methods for supporting children’s health decision-making. PMID:24758566

  17. The {open_quotes}leak-before-break{close_quotes} applicability in decision support system {open_quotes}strength{close_quotes}

    SciTech Connect

    Torop, V.M.; Orynyak, I.V.; Kutovoy, O.L.

    1997-04-01

    A software decision support system, STRENGTH, for application of leak before break analysis, is described. The background methodology and sample application are outlined. The program allows multioptional computation of loading parameters for different types of defects, and variable properties for metals and welded joints. Structural strength is assessed, and service life predictions are made. The program is used to analyze specific defects identified by nondestructive testing.

  18. Expert validation of the knowledge base for E-CAD - a pre-hospital dispatch triage decision support system.

    PubMed

    Mirza, Muzna; Saini, Devashish; Brown, Todd B; Orthner, Helmuth F; Mazza, Giovanni; Battles, Marcie M

    2007-10-11

    The knowledge base (KB) for E-CAD (Enhanced Computer-Aided Dispatch), a triage decision support system for Emergency Medical Dispatch (EMD) of medical resources in trauma cases, is being evaluated. We aim to achieve expert consensus for validation and refinement of the E-CAD KB using the modified Delphi technique. Evidence-based, expert-validated and refined KB will provide improved EMD practice guidelines and may facilitate acceptance of the E-CAD by state-wide professionals.

  19. Computer-Mediated Social Support, Older Adults, and Coping.

    ERIC Educational Resources Information Center

    Wright, Kevin

    2000-01-01

    Investigates social support for older adults in the computer-mediated environment. Finds that: satisfaction with Internet providers of social support was significantly higher for high Internet users than for low Internet users, whereas low Internet users were more satisfied with their non-Internet support networks than high Internet users; and…

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

    SciTech Connect

    Karmperis, Athanasios C.; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios

    2013-05-15

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

  1. A Visual Analytics Based Decision Support Methodology For Evaluating Low Energy Building Design Alternatives

    NASA Astrophysics Data System (ADS)

    Dutta, Ranojoy

    The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as

  2. 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.

  3. An Evolutionary Complex Systems Decision-Support Tool for the Management of Operations

    NASA Astrophysics Data System (ADS)

    Baldwin, J. S.; Allen, P. M.; Ridgway, K.

    2011-12-01

    This research aimed to add both to the development of complex systems thinking in the subject area of Operations and Production Management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision-support tools for operations and production managers. A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems model resulting in a series of simulations. The findings included both reassuring and some unexpected results. The simulation based on the CEO's opinions led the most cohesive and synergistic collection of practices describing the firm, closely followed by the Marketing and R&D Managers. The Manufacturing Manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised. By drawing directly from the opinions and views of managers rather than from logical 'if-then' rules and averaged mathematical representations of agents that characterise agent-based and other self-organisational models, this work builds on previous applications by capturing a micro-level description of diversity and a learning effect that has been problematical not only in terms of theory but also in application. This approach can be used as a decision-support tool for operations and other managers providing a forum with which to explore a) the strengths, weaknesses and consequences of different decision-making capacities within the firm; b) the introduction of new manufacturing technologies, practices and policies; and, c) the

  4. Design and implementation of a risk assessment module in a spatial decision support system

    NASA Astrophysics Data System (ADS)

    Zhang, Kaixi; van Westen, Cees; Bakker, Wim

    2014-05-01

    The spatial decision support system named 'Changes SDSS' is currently under development. The goal of this system is to analyze changing hydro-meteorological hazards and the effect of risk reduction alternatives to support decision makers in choosing the best alternatives. The risk assessment module within the system is to assess the current risk, analyze the risk after implementations of risk reduction alternatives, and analyze the risk in different future years when considering scenarios such as climate change, land use change and population growth. The objective of this work is to present the detailed design and implementation plan of the risk assessment module. The main challenges faced consist of how to shift the risk assessment from traditional desktop software to an open source web-based platform, the availability of input data and the inclusion of uncertainties in the risk analysis. The risk assessment module is developed using Ext JS library for the implementation of user interface on the client side, using Python for scripting, as well as PostGIS spatial functions for complex computations on the server side. The comprehensive consideration of the underlying uncertainties in input data can lead to a better quantification of risk assessment and a more reliable Changes SDSS, since the outputs of risk assessment module are the basis for decision making module within the system. The implementation of this module will contribute to the development of open source web-based modules for multi-hazard risk assessment in the future. This work is part of the "CHANGES SDSS" project, funded by the European Community's 7th Framework Program.

  5. Decision Support for Water Planning: the ZeroNet Water-Energy Initiative.

    SciTech Connect

    Rich, P. M.; Weintraub, Laura H. Z.; Ewers, Mary E.; Riggs, T. L.; Wilson, C. J.

    2005-01-01

    Rapid population growth and severe drought are impacting water availability for all sectors (agriculture, energy, municipal, industry...), particularly in arid regions. New generation decision support tools, incorporating recent advances in informatics and geographic information systems (GIS), are essential for responsible water planning at the basin scale. The ZeroNet water-energy initiative is developing a decision support system (DSS) for the San Juan River Basin, with a focus on drought planning and economic analysis. The ZeroNet DSS provides a computing environment (cyberinfrastructure) with three major components: Watershed Tools, a Quick Scenario Tool, and a Knowledge Base. The Watershed Tools, based in the Watershed Analysis Risk Management Framework (WARMF), provides capabilities (1) to model surface flows, both the natural and controlled, as well as water withdrawals, via an engineering module, and (2) to analyze and visualize results via a stakeholder module. A new ZeroNet module for WARMF enables iterative modeling and production of 'what if' scenario libraries to examine consequences of changes in climate, landuse, and water allocation. The Quick Scenario Tool uses system dynamics modeling for rapid analysis and visualization for a variety of uses, including drought planning, economic analysis, evaluation of management alternatives, and risk assessment. The Knowledge Base serves simultaneously as the 'faithful scribe' to organize and archive data in easily accessible digital libraries, and as the 'universal translator' to share data from diverse sources and for diverse uses. All of the decision tools depend upon GIS capabilities for data/model integration, map-based analysis, and advanced visualization. The ZeroNet DSS offers stakeholders an effective means to address complex water problems.

  6. Suitability analysis for siting MSW landfills and its multicriteria spatial decision support system: method, implementation and case study.

    PubMed

    Demesouka, O E; Vavatsikos, A P; Anagnostopoulos, K P

    2013-05-01

    Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of geographical information systems (GIS) and multiple criteria decision analysis (MCDA) methods for incorporating conflicting objectives and decision makers' (DMs') preferences into spatial decision models. This article presents a raster-based MC-SDSS that combines the analytic hierarchy process (AHP) and compromise programming methods, such as TOPSIS (technique for order preference by similarity to the ideal solution) and Ideal Point Methods. To the best of our knowledge it is the first time that a synergy of AHP and compromise programming methods is implemented in raster-driven GIS-based landfill suitability analysis. This procedure is supported by a spatial decision support system (SDSS) that was developed within a widely used commercial GIS software package. A real case study in the Thrace region in northeast Greece serves as a guide on how to conduct a suitability analysis for a MSW landfill site with the proposed MC-SDSS. Moreover, the procedure for identifying MSW disposal sites is accomplished by performing four computational models for synthesizing the DMs per criterion preferential system. Based on the case study results, a comparison analysis is performed according to suitability index estimations. According to them Euclidean distance metric and TOPSIS present strong similarities. When compared with Euclidean distance metric, TOPSIS seems to generate results closer to that derived by Manhattan distance metric. The comparison of Chebychev distance metric with all the other approaches revealed the greatest deviations.

  7. Decision support system for control and automation of dynamical processes. Master's thesis

    SciTech Connect

    Nann, S.

    1990-03-01

    The thesis presents the concept and development of a diagnostic decision support system for real-time control and automation of dynamic processes. This system, known as DECA (Diagnostic Evaluation and Corrective Action), will take advantage of the computer's ability to manipulate vast amounts of data, and employ qualitative reasoning for the monitoring and diagnosis of dynamical processes during time-constrained, routine, and emergency situations where an immediate response is necessary to avoid catastrophic failure of the system. The software system's architecture has been structured in such a manner that is can be applied to any dynamic process without reprogramming. DECA is written in Lisp and was verified using the data from the Three Mile Island Nuclear Reactor Accident.

  8. Development of a Common User Interface for the Launch Decision Support System

    NASA Technical Reports Server (NTRS)

    Scholtz, Jean C.

    1991-01-01

    The Launch Decision Support System (LDSS) is software to be used by the NASA Test Director (NTD) in the firing room during countdown. This software is designed to assist the NTD with time management, that is, when to resume from a hold condition. This software will assist the NTD in making and evaluating alternate plans and will keep him advised of the existing situation. As such, the interface to this software must be designed to provide the maximum amount of information in the clearest fashion and in a timely manner. This research involves applying user interface guidelines to a mature prototype of LDSS and developing displays that will enable the users to easily and efficiently obtain information from the LDSS displays. This research also extends previous work on organizing and prioritizing human-computer interaction knowledge.

  9. Medical decision support: experience with implementing the Arden Syntax at the Columbia-Presbyterian Medical Center.

    PubMed Central

    Jenders, R. A.; Hripcsak, G.; Sideli, R. V.; DuMouchel, W.; Zhang, H.; Cimino, J. J.; Johnson, S. B.; Sherman, E. H.; Clayton, P. D.

    1995-01-01

    We began implementation of a medical decision support system (MDSS) at the Columbia-Presbyterian Medical Center (CPMC) using the Arden Syntax in 1992. The Clinical Event Monitor which executes the Medical Logic Modules (MLMs) runs on a mainframe computer. Data are stored in a relational database and accessed via PL/I programs known as Data Access Modules (DAMs). Currently we have 18 clinical, 12 research and 10 administrative MLMs. On average, the clinical MLMs generate 50357 simple interpretations of laboratory data and 1080 alerts each month. The number of alerts actually read varies by subject of the MLM from 32.4% to 73.5%. Most simple interpretations are not read at all. A significant problem of MLMs is maintenance, and changes in laboratory testing and message output can impair MLM execution significantly. We are now using relational database technology and coded MLM output to study the process outcome of our MDSS. PMID:8563259

  10. A First Step towards a Clinical Decision Support System for Post-traumatic Stress Disorders

    PubMed Central

    Ma, Sisi; Galatzer-Levy, Isaac R; Wang, Xuya; Fenyö, David; Shalev, Arieh Y

    2016-01-01

    PTSD is distressful and debilitating, following a non-remitting course in about 10% to 20% of trauma survivors. Numerous risk indicators of PTSD have been identified, but individual level prediction remains elusive. As an effort to bridge the gap between scientific discovery and practical application, we designed and implemented a clinical decision support pipeline to provide clinically relevant recommendation for trauma survivors. To meet the specific challenge of early prediction, this work uses data obtained within ten days of a traumatic event. The pipeline creates personalized predictive model for each individual, and computes quality metrics for each predictive model. Clinical recommendations are made based on both the prediction of the model and its quality, thus avoiding making potentially detrimental recommendations based on insufficient information or suboptimal model. The current pipeline outperforms the acute stress disorder, a commonly used clinical risk factor for PTSD development, both in terms of sensitivity and specificity. PMID:28269880

  11. Climate Change, Public Health, and Decision Support: The New Threat of Vector-borne Disease

    NASA Astrophysics Data System (ADS)

    Grant, F.; Kumar, S.

    2011-12-01

    Climate change and vector-borne diseases constitute a massive threat to human development. It will not be enough to cut emissions of greenhouse gases-the tide of the future has already been established. Climate change and vector-borne diseases are already undermining the world's efforts to reduce extreme poverty. It is in the best interests of the world leaders to think in terms of concerted global actions, but adaptation and mitigation must be accomplished within the context of local community conditions, resources, and needs. Failure to act will continue to consign developed countries to completely avoidable health risks and significant expense. Failure to act will also reduce poorest of the world's population-some 2.6 billion people-to a future of diminished opportunity. Northrop Grumman has taken significant steps forward to develop the tools needed to assess climate change impacts on public health, collect relevant data for decision making, model projections at regional and local levels; and, deliver information and knowledge to local and regional stakeholders. Supporting these tools is an advanced enterprise architecture consisting of high performance computing, GIS visualization, and standards-based architecture. To address current deficiencies in local planning and decision making with respect to regional climate change and its effect on human health, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model to develop decision aids that translate the regional climate data into actionable information for users. For the present climate WRF was forced with the Max Planck Institute European Center/Hamburg Model version 5 (ECHAM5) General Circulation Model 20th century simulation. For the 21th century climate, we used an ECHAM5 simulation with the Special Report on Emissions (SRES) A1B emissions scenario. WRF was run in nested mode at spatial resolution of 108 km, 36 km and 12 km and 28 vertical levels

  12. SANDS: A Service-Oriented Architecture for Clinical Decision Support in a National Health Information Network

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. PMID:18434256

  13. Tethys: A Platform for Water Resources Modeling and Decision Support Apps

    NASA Astrophysics Data System (ADS)

    Nelson, J.; Swain, N. R.

    2015-12-01

    The interactive nature of web applications or "web apps" makes it an excellent medium for conveying complex scientific concepts to lay audiences and creating decision support tools that harness cutting edge modeling techniques. However, the technical expertise required to develop web apps represents a barrier for would-be developers. This barrier can be characterized by the following hurdles that developers must overcome: (1) identify, select, and install software that meet the spatial and computational capabilities commonly required for water resources modeling; (2) orchestrate the use of multiple free and open source (FOSS) projects and navigate their differing application programming interfaces; (3) learn the multi-language programming skills required for modern web development; and (4) develop a web-secure and fully featured web portal to host the app. Tethys Platform has been developed to lower the technical barrier and minimize the initial development investment that prohibits many scientists and engineers from making use of the web app medium. It includes (1) a suite of FOSS that address the unique data and computational needs common to water resources web app development, (2) a Python software development kit that streamlines development, and (3) a customizable web portal that is used to deploy the completed web apps. Tethys synthesizes several software projects including PostGIS, 52°North WPS, GeoServer, Google Maps™, OpenLayers, and Highcharts. It has been used to develop a broad array of web apps for water resources modeling and decision support for several projects including CI-WATER, HydroShare, and the National Flood Interoperability Experiment. The presentation will include live demos of some of the apps that have been developed using Tethys to demonstrate its capabilities.

  14. An Evaluation of the Usability of a Computerized Decision Support System for Nursing Homes

    PubMed Central

    Fossum, M.; Ehnfors, M.; Fruhling, A.; Ehrenberg, A.

    2011-01-01

    Background Computerized decision support systems (CDSSs) have the potential to significantly improve the quality of nursing care of older people by enhancing the decision making of nursing personnel. Despite this potential, health care organizations have been slow to incorporate CDSSs into nursing home practices. Objective This study describes facilitators and barriers that impact the ability of nursing personnel to effectively use a clinical CDSS for planning and treating pressure ulcers (PUs) and malnutrition and for following the suggested risk assessment guidelines for the care of nursing home residents. Methods We employed a qualitative descriptive design using varied methods, including structured group interviews, cognitive walkthrough observations and a graphical user interface (GUI) usability evaluation. Group interviews were conducted with 25 nursing personnel from four nursing homes in southern Norway. Five nursing personnel participated in cognitive walkthrough observations and the GUI usability evaluation. Text transcripts were analyzed using qualitative content analysis. Results Group interview participants reported that ease of use, usefulness and a supportive work environment were key facilitators of CDSS use. The barriers identified were lack of training, resistance to using computers and limited integration of the CDSS with the facility’s electronic health record (EHR) system. Key findings from the usability evaluation also identified the difficulty of using the CDSS within the EHR and the poorly designed GUI integration as barriers. Conclusion Overall, we found disconnect between two types of nursing personnel. Those who were comfortable with computer technology reported positive feedback about the CDSS, while others expressed resistance to using the CDSS for various reasons. This study revealed that organizations must invest more resources in educating nursing personnel on the seriousness of PUs and poor nutrition in the elderly, providing

  15. Design Evolution of a Fighter Training Scheduling Decision Support System.

    DTIC Science & Technology

    1987-03-01

    Holloman schedule includes classroom lecture, simulator training, and flying sorties. Second, cyclical scheduling literature does not consider leave...produces - a road map from blank paper to com- pleted schedule. It outlines the scheduling decision pro- cess using words or concepts and linking words or...questionnaire of multiple - choice, short statement, or open-ended questions should be used throughout the DSS implementation and development. Rating and

  16. Estimating Logistics Burdens in Support of Acquisition Decisions

    DTIC Science & Technology

    2012-04-30

    supply for fuel batteries , water, and other consumables as a function of variables that may be modeled during early (up to and including Milestone A...saved) by a given acquisition decision. This work explores methods to estimate the fully burdened cost of supply for fuel, batteries , water, and other...rich with applications to life cycle assessment ( LCA ), which is the estimation of the environmental impacts of consumption of products and services

  17. Risk Management for Weapon Systems Acquisition: A Decision Support System

    DTIC Science & Technology

    1985-02-28

    identification purposes. As another example, consider the well-known multiattribute utility theory approach. Such a method may be an appropriate risk...provide comprcbensive and balanced asseisnient unlcsted. B-25 B.5.1 Decision Analysis/Multiactribute Utility Theory (DA/ MAUT ) (Keeney and Raiffa...Perspective, Addison-Wesley, Boston, 1978. Keeney, R.L., "An Illustrated Procedure for Assessing Multiattributed Utility Functions," Sloan Management

  18. Developing Climate Resilience Toolkit Decision Support Training Sectio

    NASA Astrophysics Data System (ADS)

    Livezey, M. M.; Herring, D.; Keck, J.; Meyers, J. C.

    2014-12-01

    The Climate Resilience Toolkit (CRT) is a Federal government effort to address the U.S. President's Climate Action Plan and Executive Order for Climate Preparedness. The toolkit will provide access to tools and products useful for climate-sensitive decision making. To optimize the user experience, the toolkit will also provide access to training materials. The National Oceanic and Atmospheric Administration (NOAA) has been building a climate training capability for 15 years. The target audience for the training has historically been mainly NOAA staff with some modified training programs for external users and stakeholders. NOAA is now using this climate training capacity for the CRT. To organize the CRT training section, we collaborated with the Association of Climate Change Officers to determine the best strategy and identified four additional complimentary skills needed for successful decision making: climate literacy, environmental literacy, risk assessment and management, and strategic execution and monitoring. Developing the climate literacy skills requires knowledge of climate variability and change, as well as an introduction to the suite of available products and services. For the development of an environmental literacy category, specific topics needed include knowledge of climate impacts on specific environmental systems. Climate risk assessment and management introduces a process for decision making and provides knowledge on communication of climate information and integration of climate information in planning processes. The strategic execution and monitoring category provides information on use of NOAA climate products, services, and partnership opportunities for decision making. In order to use the existing training modules, it was necessary to assess their level of complexity, catalog them, and develop guidance for users on a curriculum to take advantage of the training resources to enhance their learning experience. With the development of this CRT

  19. Economic Evaluation of Environmental Health Interventions to Support Decision Making

    PubMed Central

    Hutton, Guy

    2008-01-01

    Environmental burden of disease represents one quarter of overall disease burden, hence necessitating greater attention from decision makers both inside and outside the health sector. Economic evaluation techniques such as cost-effectiveness analysis and cost-benefit analysis provide key information to health decision makers on the efficiency of environmental health interventions, assisting them in choosing interventions which give the greatest social return on limited public budgets and private resources. The aim of this article is to review economic evaluation studies in three environmental health areas—water, sanitation, hygiene (WSH), vector control, and air pollution—and to critically examine the policy relevance and scientific quality of the studies for selecting and funding public programmers. A keyword search of Medline from 1990–2008 revealed 32 studies, and gathering of articles from other sources revealed a further 18 studies, giving a total of 50 economic evaluation studies (13 WSH interventions, 16 vector control and 21 air pollution). Overall, the economic evidence base on environmental health interventions remains relatively weak—too few studies per intervention, of variable scientific quality and from diverse locations which limits generalisability of findings. Importantly, there still exists a disconnect between economic research, decision making and programmer implementation. This can be explained by the lack of translation of research findings into accessible documentation for policy makers and limited relevance of research findings, and the often low importance of economic evidence in budgeting decisions. These findings underline the importance of involving policy makers in the defining of research agendas and commissioning of research, and improving the awareness of researchers of the policy environment into which their research feeds. PMID:21572840

  20. Ensemble modelling and structured decision-making to support Emergency Disease Management.

    PubMed

    Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

    2017-03-01

    Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application.

  1. Translating Knowledge into Action: Supporting Adaptation in Australia's Coastal Zone through Information Provision and Decision Support

    NASA Astrophysics Data System (ADS)

    Palutikof, J. P.; Rissik, D.; Tonmoy, F. N.; Boulter, S.

    2015-12-01

    Adaptation to risks from climate change and sea-level rise is particularly important in Australia, where 70% of the population live in major coastal cities and 85% within 50km of the coast. Adaptation activity focuses at local government level and, in the absence of strong leadership from central government, the extent to which local councils have taken action to adapt is highly variable across the nation. Also, although a number of councils have proceeded as far as identifying their exposure to risk and considering adaptation options, this fails to translate into action. A principal reason for this is concern over the response from coastal residents to actions which may affect property values, and fear of litigation. A project is underway to support councils to understand their risks, evaluate adaptation options and proceed to action. This support will consist of a three-pronged framework: provision of information, a tool to support decision-making, and a community forum. Delivery involves research to understand the barriers to adaptation and how these may be overcome, optimal methods for delivery of information, and the information needs of organizations, action-takers and communities. The presentation will focus on the results of consultation undertaken to understand users' information needs around content and delivery, and how understanding of these needs has translated into design of the framework. A strongly preference was expressed to learn from peers, and a challenge for the framework is to understand how to inject adaptation knowledge which is up-to-date and accurate into peer-to-peer conversations. The community forum is one mechanism to achieve this. The basic structure and delivery mechanisms of the framework are shown in the attached.

  2. Big Data Architectures for Operationalized Seismic and Subsurface Monitoring and Decision Support Workflows

    NASA Astrophysics Data System (ADS)

    Irving, D. H.; Rasheed, M.; Hillman, C.; O'Doherty, N.

    2012-12-01

    Oilfield management is moving to a more operational footing with near-realtime seismic and sensor monitoring governing drilling, fluid injection and hydrocarbon extraction workflows within safety, productivity and profitability constraints. To date, the geoscientific analytical architectures employed are configured for large volumes of data, computational power or analytical latency and compromises in system design must be made to achieve all three aspects. These challenges are encapsulated by the phrase 'Big Data' which has been employed for over a decade in the IT industry to describe the challenges presented by data sets that are too large, volatile and diverse for existing computational architectures and paradigms. We present a data-centric architecture developed to support a geoscientific and geotechnical workflow whereby: ●scientific insight is continuously applied to fresh data ●insights and derived information are incorporated into engineering and operational decisions ●data governance and provenance are routine within a broader data management framework Strategic decision support systems in large infrastructure projects such as oilfields are typically relational data environments; data modelling is pervasive across analytical functions. However, subsurface data and models are typically non-relational (i.e. file-based) in the form of large volumes of seismic imaging data or rapid streams of sensor feeds and are analysed and interpreted using niche applications. The key architectural challenge is to move data and insight from a non-relational to a relational, or structured, data environment for faster and more integrated analytics. We describe how a blend of MapReduce and relational database technologies can be applied in geoscientific decision support, and the strengths and weaknesses of each in such an analytical ecosystem. In addition we discuss hybrid technologies that use aspects of both and translational technologies for moving data and analytics

  3. Exploring Effective Decision Making through Human-Centered and Computational Intelligence Methods

    SciTech Connect

    Han, Kyungsik; Cook, Kristin A.; Shih, Patrick C.

    2016-06-13

    Decision-making has long been studied to understand a psychological, cognitive, and social process of selecting an effective choice from alternative options. Its studies have been extended from a personal level to a group and collaborative level, and many computer-aided decision-making systems have been developed to help people make right decisions. There has been significant research growth in computational aspects of decision-making systems, yet comparatively little effort has existed in identifying and articulating user needs and requirements in assessing system outputs and the extent to which human judgments could be utilized for making accurate and reliable decisions. Our research focus is decision-making through human-centered and computational intelligence methods in a collaborative environment, and the objectives of this position paper are to bring our research ideas to the workshop, and share and discuss ideas.

  4. Ecosystem Decision Support: A Living Database of Existing Tools, Approaches and Techniques for Supporting Decisions Related to Ecosystem Services

    EPA Science Inventory

    Planners and decision makers are challenged to consider not only direct market costs, but also ecological externalities. There is an increasing emphasis on ecosystem services in the context of human well-being, and therefore the valuation and accounting of ecosystem services is b...

  5. 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

  6. 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.

  7. A platform for testing and comparing of real-time decision-support algorithms in mobile environments.

    PubMed

    Khitrov, Maxim Y; Rutishauser, Matthew; Montgomery, Kevin; Reisner, Andrew T; Reifman, Jaques

    2009-01-01

    The unavailability of a flexible system for realtime testing of decision-support algorithms in a pre-hospital clinical setting has limited their use. In this study, we describe a plug-and-play platform for real-time testing of decision-support algorithms during the transport of trauma casualties en route to a hospital. The platform integrates a standard-of-care vital-signs monitor, which collects numeric and waveform physiologic time-series data, with a rugged ultramobile personal computer. The computer time-stamps and stores data received from the monitor, and performs analysis on the collected data in real-time. Prior to field deployment, we assessed the performance of each component of the platform by using an emulator to simulate a number of possible fault scenarios that could be encountered in the field. Initial testing with the emulator allowed us to identify and fix software inconsistencies and showed that the platform can support a quick development cycle for real-time decision-support algorithms.

  8. Image-assisted knowledge discovery and decision support in radiation therapy planning.

    PubMed

    Liu, Brent J; Law, Maria Y Y; Documet, Jorge; Gertych, Arkadiusz

    2007-01-01

    The need for quantified knowledge and decision-support tools to handle complex radiation therapy (RT) imaging and informatics data is becoming steadily apparent. Lessons can be learned from current CAD applications in radiology. This paper proposes a methodology to develop this quantified knowledge and decision-support tools to facilitate RT treatment planning. The methodology is applied to cancer patient cases treated by intensity modulated radiation therapy (IMRT). The use of the "inverse treatment planning" and imaging intensive nature of IMRT allows for the development of such image-assisted tools for supporting decision-making thus providing better workflow efficiency and more precise dose predictions.

  9. An Agent-Based Framework for Building Decision Support System in Supply Chain Management

    NASA Astrophysics Data System (ADS)

    Kazemi, A.; Fazel Zarandi, M. H.

    In this study, two scenarios are presented for solving Production-Distribution Panning Problem (PDPP) in a Decision Support System (DSS) framework. In the first scenario, a Traditional Decision Support System (TDSS) is presented for PDPP and a Genetic Algorithm (GA) is used for solving it. In the second scenario, a Multi-agent Decision Support System (MADSS) is considered for PDPP and three algorithms are used for solving it: Genetic Algorithm (GA), Tabu Search (TS) and Simulated Annealing (SA). Then an algorithm is suggested by using multi-agent system and A Teams concept. The obtained results reveal that the use of MADSS delivers better solutions to us.

  10. A Description and Functional Taxonomy of Rule-based Decision Support Content at a Large Integrated Delivery Network

    PubMed Central

    Wright, Adam; Goldberg, Howard; Hongsermeier, Tonya; Middleton, Blackford

    2007-01-01

    Objective This study sought to develop a functional taxonomy of rule-based clinical decision support. Design The rule-based clinical decision support content of a large integrated delivery network with a long history of computer-based point-of-care decision support was reviewed and analyzed along four functional dimensions: trigger, input data elements, interventions, and offered choices. Results A total of 181 rule types were reviewed, comprising 7,120 different instances of rule usage. A total of 42 taxa were identified across the four categories. Many rules fell into multiple taxa in a given category. Entered order and stored laboratory result were the most common triggers; laboratory result, drug list, and hospital unit were the most frequent data elements used. Notify and log were the most common interventions, and write order, defer warning, and override rule were the most common offered choices. Conclusion A relatively small number of taxa successfully described a large body of clinical knowledge. These taxa can be directly mapped to functions of clinical systems and decision support systems, providing feature guidance for developers, implementers, and certifiers of clinical information systems. PMID:17460131

  11. Acutely-bereaved Surrogates' Stories about the Decision to Limit Life Support in the ICU

    PubMed Central

    Nunez, Eduardo R.; Schenker, Yael; Joel, Ian D.; Reynolds, Charles F.; Dew, Mary Amanda; Arnold, Robert M.; Barnato, Amber E.

    2015-01-01

    Objective Participating in a decision to limit life support for a loved one in the intensive care unit (ICU) is associated with adverse mental health consequences for surrogate decision makers. We sought to describe acutely-bereaved surrogates' experiences surrounding this decision. Design and setting Secondary analysis of interviews with surrogates approximately 4 weeks after a patient's death in one of 6 ICUs at 4 hospitals in Pittsburgh, Pennsylvania. Subjects Adults who participated in decisions about life support in the ICU. Interventions n/a Measurements We collected participant demographics, prior advance care planning, and decision control preferences. We used qualitative content analysis of transcribed interviews to identify themes in surrogates' experiences. Main results The 23 participants included the spouse (n=7), child/step-child (7), sibling (5), parent (3), or other relation (1) of the deceased patient. Their mean age was 55, 61% were women, all were white, 74% had prior treatment preferences discussions with the patient and 43% of patients had written advance directives. 15/23 (65%) surrogates preferred an active decision-making role, 8/23 (35%) preferred to share responsibility with the physician and no surrogates preferred a passive role. Surrogates report that key stressors in the ICU are the uncertainty and witnessed or empathic suffering. These factors contributed to surrogates' sense of helplessness in the ICU. Involvement in the decision to limit life support allowed surrogates to regain a sense of agency by making a decision consistent with the patient's wishes and values, counteracting surrogates' helplessness and ending the uncertainty and suffering. Conclusions In this all-white sample of surrogates with non-passive decision control preferences from a single US region, participating in decision making allowed surrogates to regain control, counteract feelings of helplessness, and end their empathic suffering. While prior research

  12. Computer-Based Administrative Support Systems: The Stanford Experience.

    ERIC Educational Resources Information Center

    Massy, William F.

    1983-01-01

    Computer-based administrative support tools are having a profound effect on the management of colleges and universities. Several such systems at Stanford University are discussed, including modeling, database management systems, networking, and electronic mail. (JN)

  13. Quality user support supporting quality users. [Historical trends and developments in computer support in the oil and gas industry

    SciTech Connect

    Woolley, T.C.

    1994-10-01

    This paper describes how Oryx Energy Co. addressed problems and opportunities created by the explosive growth in computing power and needs coupled with industry contraction. A successful user-support strategy is described. Characteristics of the program include (1) client-driven support, (2) empowerment of highly skilled professionals to fill the support role, (3) routine and ongoing modification of the support plan, (4) use of the support assignment to create highly trained advocates on the line, and (5) integration of the support role to the reservoir management team. Results of the plan include a highly trained work force, stakeholder teams that include support personnel, and global support from a centralized support organization.

  14. An Interactive Computer Aiding System for Group Decision Making

    DTIC Science & Technology

    1979-05-01

    In addition, system evaluation studies will continue. The specific items of work for the next period include: (1) Operational testing of the color...Aid with other DDF decision aids; and (3) continuation of full scale experimental studies of the Group Decision Aid. The following specific tasks were...experimental studies are in progress at Perceptronics’ California office. The previously completed experimental hypotheses and the CACI-developed scenario

  15. In and out of home care decisions: The influence of confirmation bias in developing decision supportive reasoning.

    PubMed

    Spratt, Trevor; Devaney, John; Hayes, David

    2015-11-01

    The aims of this study were to identify the themes Social Workers regard as important in supporting decisions to remove children from, or return them to, the care of their parents. To further elicit underlying hypotheses that are discernible in interpretation of evidence. A case study, comprising a two-part vignette with a questionnaire, recorded demographic information, child welfare attitudes and risk assessments, using scales derived from standardised instruments, was completed by 202 Social Workers in Northern Ireland. There were two manipulated variables, mother's attitude to removal and child's attitude to reunification 2 years later. In this paper we use data derived from respondents' qualitative comments explaining their reasoning for in and out of home care decisions. Some 60.9% of respondent's chose the parental care option at part one, with 94% choosing to have the child remain in foster care at part two. The manipulated variables were found to have no significant statistical effect. However, three underlying hypotheses were found to underpin decisions; (a) child rescue, (b) kinship defence and (c) a hedged position on calculation of risk subject to further assessment. Reasoning strategies utilised by social workers to support their decision making suggest that they tend to selectively interpret information either positively or negatively to support pre-existing underlying hypotheses. This finding is in keeping with the literature on 'confirmation bias.' The research further draws attention to the need to incorporate open questions in quantitative studies, to help guard against surface reading of data, which often does not 'speak for itself.'

  16. The development of a disease oriented eFolder for multiple sclerosis decision support

    NASA Astrophysics Data System (ADS)

    Ma, Kevin; Jacobs, Colin; Fernandez, James; Amezcua, Lilyana; Liu, Brent

    2010-03-01

    Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. The chronic nature of MS necessitates multiple MRI studies to track disease progression. Currently, MRI assessment of multiple sclerosis requires manual lesion measurement and yields an estimate of lesion volume and change that is highly variable and user-dependent. In the setting of a longitudinal study, disease trends and changes become difficult to extrapolate from the lesions. In addition, it is difficult to establish a correlation between these imaged lesions and clinical factors such as treatment course. To address these clinical needs, an MS specific e-Folder for decision support in the evaluation and assessment of MS has been developed. An e-Folder is a disease-centric electronic medical record in contrast to a patient-centric electronic health record. Along with an MS lesion computer aided detection (CAD) package for lesion load, location, and volume, clinical parameters such as patient demographics, disease history, clinical course, and treatment history are incorporated to make the e-Folder comprehensive. With the integration of MRI studies together with related clinical data and informatics tools designed for monitoring multiple sclerosis, it provides a platform to improve the detection of treatment response in patients with MS. The design and deployment of MS e-Folder aims to standardize MS lesion data and disease progression to aid in decision making and MS-related research.

  17. 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.

  18. Decision support system development at the Upper Midwest Environmental Sciences Center

    USGS Publications Warehouse

    Fox, Timothy J.; Nelson, J. C.; Rohweder, Jason J.

    2014-01-01

    A Decision Support System (DSS) can be defined in many ways. The working definition used by the U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) is, “A spatially based computer application or data that assists a researcher or manager in making decisions.” This is quite a broad definition—and it needs to be, because the possibilities for types of DSSs are limited only by the user group and the developer’s imagination. There is no one DSS; the types of DSSs are as diverse as the problems they help solve. This diversity requires that DSSs be built in a variety of ways, using the most appropriate methods and tools for the individual application. The skills of potential DSS users vary widely as well, further necessitating multiple approaches to DSS development. Some small, highly trained user groups may want a powerful modeling tool with extensive functionality at the expense of ease of use. Other user groups less familiar with geographic information system (GIS) and spatial data may want an easy-to-use application for a nontechnical audience. UMESC has been developing DSSs for almost 20 years. Our DSS developers offer our partners a wide variety of technical skills and development options, ranging from the most simple Web page or small application to complex modeling application development.

  19. Multi Criteria Decision Support Model for the Turkish Air Force Personnel Course/Education Planning System

    DTIC Science & Technology

    2011-03-01

    Making, Multiattribute Utility Theory : The Next Ten Years”. Management Science, 38(5):645–654, 1992. Fulop, Janos. “Introduction to Decision Making... Utility Theory . . . . . . . . . . . . . . . . . 21 2.2.4 ELECTRE Method . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2.5 PROMETHEE Method...10 DSS Decision Support Systems . . . . . . . . . . . . . . . . . . . . 16 MAUT Multi-Attribute Utility Theory

  20. Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

    ERIC Educational Resources Information Center

    Wolfenden, Andrew

    2012-01-01

    The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…