Science.gov

Sample records for computer decision support

  1. 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.

  2. Computer-Based Support of Organizational Decision Making.

    ERIC Educational Resources Information Center

    Bonczek, Robert H.; And Others

    1979-01-01

    Explores the extent to which computer facilities can be used to support organizational decision-making processes beyond mere performance of information retrieval. Human perceptual and judgmental processes, as they apply to organizational decisions, are examined as a basis for the design of a generalized, intelligent problem processor. (Author/RAO)

  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. Decision Support Systems and the Conflict Model of Decision Making: A Stimulus for New Computer-Assisted Careers Guidance Systems.

    ERIC Educational Resources Information Center

    Ballantine, R. Malcolm

    Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…

  5. 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…

  6. Computer aided decision support system for cervical cancer classification

    NASA Astrophysics Data System (ADS)

    Rahmadwati, Rahmadwati; Naghdy, Golshah; Ros, Montserrat; Todd, Catherine

    2012-10-01

    Conventional analysis of a cervical histology image, such a pap smear or a biopsy sample, is performed by an expert pathologist manually. This involves inspecting the sample for cellular level abnormalities and determining the spread of the abnormalities. Cancer is graded based on the spread of the abnormal cells. This is a tedious, subjective and time-consuming process with considerable variations in diagnosis between the experts. This paper presents a computer aided decision support system (CADSS) tool to help the pathologists in their examination of the cervical cancer biopsies. The main aim of the proposed CADSS system is to identify abnormalities and quantify cancer grading in a systematic and repeatable manner. The paper proposes three different methods which presents and compares the results using 475 images of cervical biopsies which include normal, three stages of pre cancer, and malignant cases. This paper will explore various components of an effective CADSS; image acquisition, pre-processing, segmentation, feature extraction, classification, grading and disease identification. Cervical histological images are captured using a digital microscope. The images are captured in sufficient resolution to retain enough information for effective classification. Histology images of cervical biopsies consist of three major sections; background, stroma and squamous epithelium. Most diagnostic information are contained within the epithelium region. This paper will present two levels of segmentations; global (macro) and local (micro). At the global level the squamous epithelium is separated from the background and stroma. At the local or cellular level, the nuclei and cytoplasm are segmented for further analysis. Image features that influence the pathologists' decision during the analysis and classification of a cervical biopsy are the nuclei's shape and spread; the ratio of the areas of nuclei and cytoplasm as well as the texture and spread of the abnormalities

  7. Reducing diagnostic error with computer-based clinical decision support.

    PubMed

    Greenes, Robert A

    2009-09-01

    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 making (Schiff). In addition, several other considerations relating to this topic are interesting to ponder. We are moving toward increased understanding of gene regulation and gene expression, identification of biomarkers, and the ability to predict patient response to disease and to tailor treatments to these individual variations-referred to as "personalized" or, more recently, "predictive" medicine. Consequently, diagnostic decision making is more and more linked to management decision making, and generic diagnostic labels like "diabetes" or "colon cancer" will no longer be sufficient, because they don't tell us what to do. Ultimately, if we have more complete data including more structured capture of phenomic data as well as the characterization of the patient's genome, direct prediction from responses of highly refined subsets of similar patients in a database can be used to select appropriate management, the effectiveness of which was demonstrated in projects in selected limited domains as early as the 1970s. In general, there are six classes of methodologies, including the above, which can be applied to delivering CDS. In addition, patients are becoming more knowledgeable and should be regarded as active participants, not only in helping to obtain data but also in their own status assessment and as recipients of decision support. With the above advances, this is a very promising time to be engaged in pursuit of methods of CDS. PMID:19669915

  8. 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…

  9. Group Decision Support Systems and Group Communication: A Comparison of Decision Making in Computer-Supported and Nonsupported Groups.

    ERIC Educational Resources Information Center

    Poole, Marshall Scott; And Others

    1993-01-01

    Explores the effects of Group Decision Support Systems (GDSS) on small group communication and decision-making processes. Finds that comparing GDSS, manual, and baseline conditions enables separation of effects resulting from procedural structures from those resulting from computerization. Results support some aspects of the research model and…

  10. 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…

  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-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.

  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. 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.

  15. 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. )

    1992-12-01

    Massive efforts are underway to clean up hazardous and radioactive waste sites located throughout the United States. 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. As a result, model selection is currently done on an ad hoc basis. This is administratively ineffective and costly, and can also result in technically inconsistent decision-making. 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. A mail survey was conducted to identify models in use. The survey was sent to [approx] 550 persons engaged in the cleanup of hazardous and radioactive waste sites; 87 individuals responded. They represented organizations including federal agencies, national laboratories, and contractor organizations. The respondents identified 127 computer models that were being used to help support cleanup decision-making. There were a few models that appeared to be used across a large number of sites (e.g., RESRAD). In contrast, the survey results also suggested that most sites were using models which were not reported in use elsewhere. Information is presented on the types of models being used and the characteristics of the models in use.

  16. 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. PMID:22874232

  17. 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.

  18. 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.

  19. A Compute Perspective: Delivering Decision Support Products in 24 Hours from the Airborne Snow Observatory

    NASA Astrophysics Data System (ADS)

    Ramirez, P.; Mattmann, C. A.; Painter, T. H.; Seidel, F. C.; Trangsrud, A.; Hart, A. F.; Goodale, C. E.; Boardman, J. W.; Heneghan, C.; Verma, R.; Khudikyan, S.; Boustani, M.; Zimdars, P. A.; Horn, J.; Neely, S.

    2013-12-01

    The JPL Airborne Snow Observatory (ASO) must process 100s of GB of raw data to 100s of Terabytes of derived data in 24 hour Near Real Time (NRT) latency in a geographically distributed mobile compute and data-intensive processing setting. ASO provides meaningful information to water resource managers in the Western US letting them know how much water to maintain; or release, and what the prospectus of the current snow season is in the Sierra Nevadas. Providing decision support products processed from airborne data in a 24 hour timeframe is an emergent field and required the team to develop a novel solution as this process is typically done over months. We've constructed a system that combines Apache OODT; with Apache Tika; with the Interactive Data Analysis (IDL)/ENVI programming environment to rapidly and unobtrusively generate, distribute and archive ASO data as soon as the plane lands near Mammoth Lakes, CA. Our system is flexible, underwent several redeployments and reconfigurations, and delivered this critical information to stakeholders during the recent "Snow On" campaign March 2013 - June 2013. This talk will take you through a day in the life of the compute team from data acquisition, delivery, processing, and dissemination. Within this context, we will discuss the architecture of ASO; the open source software we used; the data we stored; and how it was delivered to its users. Moreover we will discuss the logistics, system engineering, and staffing that went into the developing, deployment, and operation of the mobile compute system.

  20. 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

  1. 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.

  2. 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

  3. Decision Support Systems in Libraries.

    ERIC Educational Resources Information Center

    Heindel, Allan; Napier, H. Albert

    Following a review of the contributions of computers and managerial science/operations research to the management of libraries, this paper introduces the concept of decision support systems. DSS, a blending of these techniques, can lead to more effective decisions by library managers. A case study of the utilization of a DSS in the budgeting…

  4. Decision Support System Based on Computational Collective Intelligence in Campus Information Systems

    NASA Astrophysics Data System (ADS)

    Saito, Yoshihito; Matsuo, Tokuro

    Education institutions such as universities have a lot of information including book information, equipment administrative information, student information, and several others. The institutions also have multiple information in time series. As collective intelligence in campus, integrating and reusing these preserved information regarding career and taking a class, university can effectively support students' decision making of their getting jobs and subjects choice. Our purpose of support is to increase student's motivation. In this paper, we focus on course record and job information included in students' information, and propose the method to analyze correlation between a pattern of taking class and job lined up. Afterwards, we propose a support system regarding getting a job and taking class by using our proposed method. For a student who has his/her favorite job to get, the system supports his/her decision making of lecture choice by recommending a set of appropriate lecture groups. On another hand, for a student who does not have favorite job to get, the system supports his/her decision making of getting job by presenting appropriate job families related with lecture group in which he/she has ever taken. The contribution of this paper is showing a concrete method to reuse the campus collective information, implementing a system, and user perspectives.

  5. Decision Technology Systems: A Vehicle to Consolidate Decision Making Support.

    ERIC Educational Resources Information Center

    Forgionne, Guisseppi A.

    1991-01-01

    Discussion of management decision making and the support needed to manage successfully highlights a Decision Technology System (DTS) that integrates other information systems. Topics discussed include computer information systems (CISs); knowledge gateways; the decision-making process; decision support systems (DSS); expert systems; and facility…

  6. A secure communication using cascade chaotic computing systems on clinical decision support.

    PubMed

    Koksal, Ahmet Sertol; Er, Orhan; Evirgen, Hayrettin; Yumusak, Nejat

    2016-06-01

    Clinical decision support systems (C-DSS) provide supportive tools to the expert for the determination of the disease. Today, many of the support systems, which have been developed for a better and more accurate diagnosis, have reached a dynamic structure due to artificial intelligence techniques. However, in cases when important diagnosis studies should be performed in secret, a secure communication system is required. In this study, secure communication of a DSS is examined through a developed double layer chaotic communication system. The developed communication system consists of four main parts: random number generator, cascade chaotic calculation layer, PCM, and logical mixer layers. Thanks to this system, important patient data created by DSS will be conveyed to the center through a secure communication line.

  7. Anatomy of a Decision Support System.

    ERIC Educational Resources Information Center

    Chachra, Vinod; Heterick, Robert C.

    1982-01-01

    The decision support system (DSS) environment, the functional requirements of a DSS, and the architectural requirements of the computer systems and communications network necessary to support a DSS are discussed. Changes in the computing environment that are necessary to implement decision support systems are suggested. (Author/MLW)

  8. Decision Support Systems: The Need, The Challenge.

    ERIC Educational Resources Information Center

    Roberts, Michael M.

    1982-01-01

    The evolution of decision support systems (DSS) has enabled computer and information technology to assist the management process of decision making. Decision support systems are designed to look forward in time, to forecast outcomes of uncertain events. A 70-item bibliography is included. (MLW)

  9. Overview of environmental decision support software

    SciTech Connect

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

    1997-12-31

    Regulatory exposure limits form the basis for making decisions on the characterization, monitoring, and remediation of environmental contamination. This paper discusses the development of Decision Support Software (DSS) tools developed to support decisions pertaining to environmental management. Decision support software packages are computer-based programs that facilitate the use of data, models, and structured decision processes in decision making. They incorporate the information into an integrated package that presents results in a format useful for making environmental decisions. Six major analysis functions of DSS tools have been identified: site characterization, plume characterization, risk assessment including regulatory compliance assessment, remedy selection, remedy design optimization, and cost/benefit analysis. Decision support software is relatively new and is now beginning to see application in the field. This paper discusses existing DSS and the strengths and limitations of some of the DSS packages. General limitations of decision support software are also discussed.

  10. 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…

  11. Clinical decision support systems.

    PubMed

    Beeler, Patrick Emanuel; Bates, David Westfall; Hug, Balthasar Luzius

    2014-01-01

    Clinical decision support (CDS) systems link patient data with an electronic knowledge base in order to improve decision-making and computerised physician order entry (CPOE) is a requirement to set up electronic CDS. The medical informatics literature suggests categorising CDS tools into medication dosing support, order facilitators, point-of-care alerts and reminders, relevant information display, expert systems and workflow support. To date, CDS has particularly been recognised for improving processes. CDS successfully fostered prevention of deep-vein thrombosis, improved adherence to guidelines, increased the use of vaccinations, and decreased the rate of serious medication errors. However, CDS may introduce errors, and therefore the term "e-iatrogenesis" has been proposed to address unintended consequences. At least two studies reported severe treatment delays due to CPOE and CDS. In addition, the phenomenon of "alert fatigue" - arising from a high number of CDS alerts of low clinical significance - may facilitate overriding of potentially critical notifications. The implementation of CDS needs to be carefully planned, CDS interventions should be thoroughly examined in pilot wards only, and then stepwise introduced. A crucial feature of CPOE in combination with CDS is speed, since time consumption has been found to be a major factor determining failure. In the near future, the specificity of alerts will be improved, notifications will be prioritised and offer detailed advice, customisation of CDS will play an increasing role, and finally, CDS is heading for patient-centred decision support. The most important research question remains whether CDS is able to improve patient outcomes beyond processes.

  12. 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.

  13. Designing a Hydro-Economic Collaborative Computer Decision Support System: Approaches, Best Practices, Lessons Learned, and Future Trends

    NASA Astrophysics Data System (ADS)

    Rosenberg, D. E.

    2008-12-01

    Designing and implementing a hydro-economic computer model to support or facilitate collaborative decision making among multiple stakeholders or users can be challenging and daunting. Collaborative modeling is distinguished and more difficult than non-collaborative efforts because of a large number of users with different backgrounds, disagreement or conflict among stakeholders regarding problem definitions, modeling roles, and analysis methods, plus evolving ideas of model scope and scale and needs for information and analysis as stakeholders interact, use the model, and learn about the underlying water system. This presentation reviews the lifecycle for collaborative model making and identifies some key design decisions that stakeholders and model developers must make to develop robust and trusted, verifiable and transparent, integrated and flexible, and ultimately useful models. It advances some best practices to implement and program these decisions. Among these best practices are 1) modular development of data- aware input, storage, manipulation, results recording and presentation components plus ways to couple and link to other models and tools, 2) explicitly structure both input data and the meta data that describes data sources, who acquired it, gaps, and modifications or translations made to put the data in a form usable by the model, 3) provide in-line documentation on model inputs, assumptions, calculations, and results plus ways for stakeholders to document their own model use and share results with others, and 4) flexibly program with graphical object-oriented properties and elements that allow users or the model maintainers to easily see and modify the spatial, temporal, or analysis scope as the collaborative process moves forward. We draw on examples of these best practices from the existing literature, the author's prior work, and some new applications just underway. The presentation concludes by identifying some future directions for collaborative

  14. 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.

  15. The Effect of Level of Patient Acuity, Critical Care Experience, and ACLS Certification on Clinical Decision Making: Implications for Computer Decision Support Systems

    PubMed Central

    Henry, Suzanne Bakken

    1990-01-01

    This study examined the effect of patient acuity, critical care experience, and ACLS certification on clinical decision making. Each subject (N=68) completed two computerized clinical simulations. Ventricular tachycardia (VT) represented the high acuity situation and atrial flutter (AF) the lower acuity situation. Clinical decision making was measured by proficiency score, patient outcome (cure/die), and amount of data collected. In the AF simulation, proficiency scores were higher (p=.000), more dysrhythmias were cured (p<.005), and more data were collected (p=.040) than in the VT simulation. Experienced and inexperienced nurses did not differ on proficiency score, however, inexperienced nurses collected more data (p=.048) and cured fewer atrial flutter simulations (p=.04). ACLS certified nurses had higher proficiency scores (p=.033) and collected less data (p=.048). Clinical decision making on two simulations was affected by patient acuity, critical care experience, and ACLS certification. These findings have implications for the design and implementation of clinical decision support systems.

  16. 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

  17. Co-Design of a Computer-Assisted Medical Decision Support System to Manage Antibiotic Prescription in an ICU Ward.

    PubMed

    Gil, Miguel; Pinto, Pedro; Simões, Alexandra S; Póvoa, Pedro; Da Silva, Miguel Mira; Lapão, Luís Velez

    2016-01-01

    About 37 thousand people die per year in Europe due to infections by resistant bacteria. Fighting antimicrobial resistances (AR) is a top priority to save lives and reduce costs. AR is triggered mostly by uncritical antibiotic prescription. This paper presents HAITool, a decision-making information system to support antibiotic prescription. The system was co-developed together with health professionals using Design Science Research Methodology, empowered with innovative data visualization techniques to improve AR management. HAITool includes integrated visualizations of patient, microbiology, and pharmacy data, facilitating clinical decision support, antibiotic prescriptions quality and antibiotic-resistant bacteria monitoring. It also includes an alert module that monitors conformance of antibiotic prescriptions with norms and guidelines. HAITool is evaluated using both the Österle principles and interviews with physicians and infection control team from three participant hospitals. PMID:27577433

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. Strategic Decision Making and Group Decision Support Systems.

    ERIC Educational Resources Information Center

    McGrath, Michael Robert

    1986-01-01

    Institutional strategic decisions require the participation of every individual with a significant stake in the solution, and group decision support systems are being developed to respond to the political and consensual problems of collective decision-making. (MSE)

  3. 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.

  4. Computer Support Technician.

    ERIC Educational Resources Information Center

    Ohio State Univ., Columbus. Center on Education and Training for Employment.

    This publication contains 18 subjects appropriate for use in a competency list for the occupation of computer support technician, 1 of 12 12 occupations within the business/computer technologies cluster. Each unit consists of a number of competencies; a list of competency builders is provided for each competency. Titles of the 18 units are as…

  5. 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.

  6. 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

  7. 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.

  8. 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…

  9. Decision support for clinical laboratory capacity planning.

    PubMed

    van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

    1995-01-01

    The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

  10. Evaluation of the BlightPro Decision Support System for Management of Potato Late Blight Using Computer Simulation and Field Validation.

    PubMed

    Small, Ian M; Joseph, Laura; Fry, William E

    2015-12-01

    The objective of this study was to evaluate the utility of the BlightPro decision support system (DSS) for late blight management using computer simulation and field tests. Three fungicide schedules were evaluated: (i) calendar-based (weekly) applications, (ii) applications according to the DSS, or (iii) no fungicide. Simulation experiments utilized 14 years of weather data from 59 locations in potato-producing states. In situations with unfavorable weather for late blight, the DSS recommended fewer fungicide applications with no loss of disease suppression; and, in situations of very favorable weather for late blight, the DSS recommended more fungicide applications but with improved disease suppression. Field evaluation was conducted in 2010, 2011, 2012, and 2013. All experiments involved at least two cultivars with different levels of resistance. DSS-guided and weekly scheduled fungicide treatments were successful at protecting against late blight in all field experiments. As expected, DSS-guided schedules were influenced by prevailing weather (observed and forecast) and host resistance and resulted in schedules that maintained or improved disease suppression and average fungicide use efficiency relative to calendar-based applications. The DSS provides an interactive system that helps users maximize the efficiency of their crop protection strategy by enabling well-informed decisions. PMID:26312965

  11. Evaluation of the BlightPro Decision Support System for Management of Potato Late Blight Using Computer Simulation and Field Validation.

    PubMed

    Small, Ian M; Joseph, Laura; Fry, William E

    2015-12-01

    The objective of this study was to evaluate the utility of the BlightPro decision support system (DSS) for late blight management using computer simulation and field tests. Three fungicide schedules were evaluated: (i) calendar-based (weekly) applications, (ii) applications according to the DSS, or (iii) no fungicide. Simulation experiments utilized 14 years of weather data from 59 locations in potato-producing states. In situations with unfavorable weather for late blight, the DSS recommended fewer fungicide applications with no loss of disease suppression; and, in situations of very favorable weather for late blight, the DSS recommended more fungicide applications but with improved disease suppression. Field evaluation was conducted in 2010, 2011, 2012, and 2013. All experiments involved at least two cultivars with different levels of resistance. DSS-guided and weekly scheduled fungicide treatments were successful at protecting against late blight in all field experiments. As expected, DSS-guided schedules were influenced by prevailing weather (observed and forecast) and host resistance and resulted in schedules that maintained or improved disease suppression and average fungicide use efficiency relative to calendar-based applications. The DSS provides an interactive system that helps users maximize the efficiency of their crop protection strategy by enabling well-informed decisions.

  12. 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

  13. 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.

  14. Developing a New Computer-Aided Clinical Decision Support System for Prediction of Successful Postcardioversion Patients with Persistent Atrial Fibrillation

    PubMed Central

    Sterling, Mark; Huang, David T.; Ghoraani, Behnaz

    2015-01-01

    We propose a new algorithm to predict the outcome of direct-current electric (DCE) cardioversion for atrial fibrillation (AF) patients. AF is the most common cardiac arrhythmia and DCE cardioversion is a noninvasive treatment to end AF and return the patient to sinus rhythm (SR). Unfortunately, there is a high risk of AF recurrence in persistent AF patients; hence clinically it is important to predict the DCE outcome in order to avoid the procedure's side effects. This study develops a feature extraction and classification framework to predict AF recurrence patients from the underlying structure of atrial activity (AA). A multiresolution signal decomposition technique, based on matching pursuit (MP), was used to project the AA over a dictionary of wavelets. Seven novel features were derived from the decompositions and were employed in a quadratic discrimination analysis classification to predict the success of post-DCE cardioversion in 40 patients with persistent AF. The proposed algorithm achieved 100% sensitivity and 95% specificity, indicating that the proposed computational approach captures detailed structural information about the underlying AA and could provide reliable information for effective management of AF. PMID:26120354

  15. IPDS: Integrated Planning Decision Support System

    SciTech Connect

    Mejia-Navarro, M.; Garcia, L.A.

    1995-12-31

    The Integrated Planning Decision Support System (IPDS) is designed as a decision support system (DSS) to assist governments and communities in evaluation of geological hazards, vulnerability, and risk. The IPDS system incorporates the Geographic Information Systems (GIS) Geographic Resource Analysis Support System (GRASS) and engineering numerical models within a Graphic User Interface (GUI), to provide the user with comprehensive modelling capabilities for geological hazards, vulnerability, and risk assessment. The methodology that IPDS follows for the evaluation of hazards takes into account the weight of each influencing factor within hazardous geologic processes. IPDS interactive algorithms compute the following parameters for each cell (based on the maximum resolution of the data): the related hazard, the vulnerability to geological hazards, and the risk. IPDS is designed to assess any generic hazard, such as debris flows, subsidence, and floods, with probable maximum precipitation and seismicity as triggering factors for susceptibility scenarios. The regular items considered in vulnerability analysis are (1) ecosystem sensitivity, (2) economic vulnerability, and (3) social infrastructure vulnerability. The risk is assessed as a function of hazard and vulnerability.

  16. 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…

  17. 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.

  18. A decision class analysis of critical care life-support decision-making.

    PubMed

    Seiver, A

    1993-02-01

    Decision analysis is a powerful methodology that can help clinicians make good decisions. Because it is not practical to place a decision analyst at the bedside in critical care units, the application of this methodology will require leveraging the analyst through computer-based systems. A decision class analysis is a collective analysis of a group of decisions that provides the high-level specification for such a computer system. This paper presents a decision class analysis of critical care life-support decisions. Key elements of this analysis are: the simplification of an otherwise extremely complex multistage sequential decision problem by using a sequence of two-stage models, and the use of six generic knowledge maps that capture the extremely complex relevant medical knowledge. PMID:8326214

  19. 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

  20. 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...

  1. 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.

  2. 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)

  3. Costs Associated with Implementation of Computer-Assisted Clinical Decision Support System for Antenatal and Delivery Care: Case Study of Kassena-Nankana District of Northern Ghana

    PubMed Central

    Dalaba, Maxwell Ayindenaba; Akweongo, Patricia; Williams, John; Saronga, Happiness Pius; Tonchev, Pencho; Sauerborn, Rainer; Mensah, Nathan; Blank, Antje; Kaltschmidt, Jens; Loukanova, Svetla

    2014-01-01

    Objective This study analyzed cost of implementing computer-assisted Clinical Decision Support System (CDSS) in selected health care centres in Ghana. Methods A descriptive cross sectional study was conducted in the Kassena-Nankana district (KND). CDSS was deployed in selected health centres in KND as an intervention to manage patients attending antenatal clinics and the labour ward. The CDSS users were mainly nurses who were trained. Activities and associated costs involved in the implementation of CDSS (pre-intervention and intervention) were collected for the period between 2009–2013 from the provider perspective. The ingredients approach was used for the cost analysis. Costs were grouped into personnel, trainings, overheads (recurrent costs) and equipment costs (capital cost). We calculated cost without annualizing capital cost to represent financial cost and cost with annualizing capital costs to represent economic cost. Results Twenty-two trained CDSS users (at least 2 users per health centre) participated in the study. Between April 2012 and March 2013, users managed 5,595 antenatal clients and 872 labour clients using the CDSS. We observed a decrease in the proportion of complications during delivery (pre-intervention 10.74% versus post-intervention 9.64%) and a reduction in the number of maternal deaths (pre-intervention 4 deaths versus post-intervention 1 death). The overall financial cost of CDSS implementation was US$23,316, approximately US$1,060 per CDSS user trained. Of the total cost of implementation, 48% (US$11,272) was pre-intervention cost and intervention cost was 52% (US$12,044). Equipment costs accounted for the largest proportion of financial cost: 34% (US$7,917). When economic cost was considered, total cost of implementation was US$17,128–lower than the financial cost by 26.5%. Conclusions The study provides useful information in the implementation of CDSS at health facilities to enhance health workers' adherence to practice guidelines

  4. 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…

  5. 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.

  6. Isabel, a clinical decision support system.

    PubMed

    Vardell, Emily; Moore, Mary

    2011-01-01

    A clinical decision support system (CDSS) is an interactive tool designed to assist clinicians in making decisions, such as determining a diagnosis. The Isabel Database is a CDSS featuring a clinical checklist and topic-specific knowledge components. This column contains an overview of the database, provides searching tips, and places Isabel within the context of the CDSS field. PMID:21534115

  7. A Hyperknowledge Framework of Decision Support Systems.

    ERIC Educational Resources Information Center

    Chang, Ai-Mei; And Others

    1994-01-01

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

  8. 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

  9. A Decision Support System for Supervised Assignment in Banking Decisions

    NASA Astrophysics Data System (ADS)

    Rigopoulos, George; Psarras, John; Askounis, Dimitrios Th.

    This study presents a Decision Support System (DSS) which supports assignment of actions (e.g., numbers, projects, people etc.) into predefined categories according to their score on evaluation criteria. It implements a novel classification algorithm based on multicriteria analysis and fuzzy preference relations. More detailed, assignment to classes is based on the concept of category threshold, which defines at what degree an alternative can be included in a specific category. For each category a threshold is defined by the corresponding decision maker, which indicates its lower limit with respect to the evaluation criteria. Actions are then evaluated according to the criteria and fuzzy inclusion degrees are calculated for each category. Finally, an action is assigned to the category for which the inclusion degree is the maximum. The DSS implements the above classification algorithm, providing a user-friendly interface, which supports decision makers to formulate and solve similar problems. In addition to the DSS, we present a real world application at a classification problem within the environment of a Greek bank. Results derived from evaluation experiments in the business environment provide evidence that the proposed methodology and the DSS can effectively support decision makers in classification decisions. The methodology as well as the proposed DSS can be used to classification problems not only in financial domain but to a variety of domains such as production, environmental, or human resources.

  10. 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.

  11. 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.

  12. 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 (...

  13. 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

  14. 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

  15. 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

  16. Recent developments associated with decision support systems in water resources

    NASA Astrophysics Data System (ADS)

    Watkins, David W.; McKinney, Daene C.

    1995-07-01

    In order to limit the scope of this review, a working definition of a decision support system is needed. L. Adelman has defined decision support systems (DSSs) as "interactive computer programs that utilize analytical methods, such as decision analysis, optimization algorithms, program scheduling routines, and so on, for developing models to help decision makers formulate alternatives, analyze their impacts, and interpret and select appropriate options for implementation" (Adelman [1992], p. 2). Another definition has been offered by S. J. Andriole, who defined decision support as consisting of "any and all data, information, expertise or activities that contribute to option selection" (Andriole [1989], p. 3). A common idea explicit in each of these definitions is that DSSs integrate various technologies and aid in option selection. Implicit in each definition is that these are options for solving relatively large, unstructured problems. Thus, the following working definition of a DSS will be used in this review: A DSS is an integrated, interactive computer system, consisting of analytical tools and information management capabilities, designed to aid decision makers in solving relatively large, unstructured problems.

  17. Computers Help Students Make Wise Career Decisions.

    ERIC Educational Resources Information Center

    Gerardi, Robert J.; And Others

    1984-01-01

    Discusses advantages and disadvantages of utilizing computer information systems in making career and educational alternatives decisions, describes three types of computer-based guidance systems currently available, and describes three direct inquiry systems with monitoring--Educational and Career Exploration System, System of Interactive Guidance…

  18. 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…

  19. Decision Support and Knowledge-Based Systems.

    ERIC Educational Resources Information Center

    Konsynski, Benn R.; And Others

    1988-01-01

    A series of articles addresses issues concerning decision support and knowledge based systems. Topics covered include knowledge-based systems for information centers; object oriented systems; strategic information systems case studies; user perception; manipulation of certainty factors by individuals and expert systems; spreadsheet program use;…

  20. 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.

  1. 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.

  2. Decision Support Systems in Academic Administration.

    ERIC Educational Resources Information Center

    Turban, Efraim; And Others

    1988-01-01

    Presents an overview of a computerized Decision Support System (DSS) for academic administrators. Following a discussion of its capabilities, the various components of a DSS are examined as well as the development tools needed. Examples follow of DSS in two universities, and various development and implementation issues are considered. (TE)

  3. Transferring Decision Support Concepts to Evaluation.

    ERIC Educational Resources Information Center

    Sauter, Vicki L.; Mandell, Marvin B.

    1990-01-01

    Use of decision support systems (DSS) to increase the utilization of management science models and accounting information is discussed. It is argued that application of the conceptual foundations of DSS to evaluation and other forms of applied social research is an effective means of increasing evaluation utilization by policymakers. (TJH)

  4. A Multiple Objective Decision Support Tool (MODS)

    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 providemore » 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

  5. Computers in Medicine: A survey of decision aids for clinicians

    PubMed Central

    Young, D W

    1982-01-01

    Inconsistency in applying medical knowledge is a major reason for varying standards of medical care. Five types of aid have been introduced into medicine to help decision-making: questionnaires, algorithms, database systems, diagnostic systems, and, finally, computer-based decision-support systems. Of these, the most effective act as reminder or prompt systems to assist doctors without threatening their clinical freedom. PMID:6812701

  6. 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. PMID:25748599

  7. 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.

  8. 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.

  9. Decision support tools for policy and planning

    SciTech Connect

    Jacyk, P.; Schultz, D.; Spangenberg, L.

    1995-07-01

    A decision support system (DSS) is being developed at the Radioactive Liquid Waste Treatment Facility, Los Alamos National Laboratory (LANL). The DSS will be used to evaluate alternatives for improving LANL`s existing central radioactive waste water treatment plant and to evaluate new site-wide liquid waste treatment schemes that are required in order to handle the diverse waste streams produced at LANL. The decision support system consists of interacting modules that perform the following tasks: rigorous process simulation, configuration management, performance analysis, cost analysis, risk analysis, environmental impact assessment, transportation modeling, and local, state, and federal regulation compliance checking. Uncertainty handling techniques are used with these modules and also with a decision synthesis module which combines results from the modules listed above. We believe the DSS being developed can be applied to almost any other industrial water treatment facility with little modification because in most situations the waste streams are less complex, fewer regulations apply, and the political environment is simpler. The techniques being developed are also generally applicable to policy and planning decision support systems in the chemical process industry.

  10. 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.

  11. Decision Support for Operations and Maintenance IV

    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 plantsmore » to operate safely at peak efficiency, while providing a higher level of reliability and safety.« less

  12. 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

  13. 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.

  14. Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.

    PubMed

    Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru

    2015-07-01

    Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting. PMID:26066306

  15. 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.

  16. Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images

    PubMed Central

    Møllersen, Kajsa; Kirchesch, Herbert; Zortea, Maciel; Schopf, Thomas R.; Hindberg, Kristian; Godtliebsen, Fred

    2015-01-01

    Commercially available clinical decision support systems (CDSSs) for skin cancer have been designed for the detection of melanoma only. Correct use of the systems requires expert knowledge, hampering their utility for nonexperts. Furthermore, there are no systems to detect other common skin cancer types, that is, nonmelanoma skin cancer (NMSC). As early diagnosis of skin cancer is essential, there is a need for a CDSS that is applicable to all types of skin lesions and is suitable for nonexperts. Nevus Doctor (ND) is a CDSS being developed by the authors. We here investigate ND's ability to detect both melanoma and NMSC and the opportunities for improvement. An independent test set of dermoscopic images of 870 skin lesions, including 44 melanomas and 101 NMSCs, were analysed by ND. Its sensitivity to melanoma and NMSC was compared to that of Mole Expert (ME), a commercially available CDSS, using the same set of lesions. ND and ME had similar sensitivity to melanoma. For ND at 95% melanoma sensitivity, the NMSC sensitivity was 100%, and the specificity was 12%. The melanomas misclassified by ND at 95% sensitivity were correctly classified by ME, and vice versa. ND is able to detect NMSC without sacrificing melanoma sensitivity. PMID:26693486

  17. 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.

  18. 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.

  19. Supporting registration decisions during 3D medical volume reconstructions

    NASA Astrophysics Data System (ADS)

    Bajcsy, Peter; Lee, Sang-Chul; Clutter, David

    2006-03-01

    We propose a methodology for making optimal registration decisions during 3D volume reconstruction in terms of (a) anticipated accuracy of aligned images, (b) uncertainty of obtained results during the registration process, (c) algorithmic repeatability of alignment procedure, and (d) computational requirements. We researched and developed a web-enabled, web services based, data-driven, registration decision support system. The registration decisions include (1) image spatial size (image sub-area or entire image), (2) transformation model (e.g., rigid, affine or elastic), (3) invariant registration feature (intensity, morphology or a sequential combination of the two), (4) automation level (manual, semi-automated, or fully-automated), (5) evaluations of registration results (multiple metrics and methods for establishing ground truth), and (6) assessment of resources (computational resources and human expertise, geographically local or distributed). Our goal is to provide mechanisms for evaluating the tradeoffs of each registration decision in terms of the aforementioned impacts. First, we present a medical registration methodology for making registration decisions that lead to registration results with well-understood accuracy, uncertainty, consistency and computational complexity characteristics. Second, we have built software tools that enable geographically distributed researchers to optimize their data-driven registration decisions by using web services and supercomputing resources. The support developed for registration decisions about 3D volume reconstruction is available to the general community with the access to the NCSA supercomputing resources. We illustrate performance by considering 3D volume reconstruction of blood vessels in histological sections of uveal melanoma from serial fluorescent labeled paraffin sections labeled with antibodies to CD34 and laminin. The specimens are studied by fluorescence confocal laser scanning microscopy (CLSM) images.

  20. From hydrological modelling to decision support

    NASA Astrophysics Data System (ADS)

    Haberlandt, U.

    2010-08-01

    Decision support for planning and management of water resources needs to consider many target criteria simultaneously like water availability, water quality, flood protection, agriculture, ecology, etc. Hydrologic models provide information about the water balance components and are fundamental for the simulation of ecological processes. Objective of this contribution is to discuss the suitability of classical hydrologic models on one hand and of complex eco-hydrologic models on the other hand to be used as part of decision support systems. The discussion is based on results from two model comparison studies. It becomes clear that none of the hydrologic models tested fulfils all requirements in an optimal sense. Regarding the simulation of water quality parameters like nitrogen leaching a high uncertainty needs to be considered. Recommended for decision support is a hybrid metamodel approach, which comprises a hydrologic model, empirical relationships for the less dynamic processes and makes use of simulation results from complex eco-hydrologic models through second-order modelling at a generalized level.

  1. Decision Making in Computer-Simulated Experiments.

    ERIC Educational Resources Information Center

    Suits, J. P.; Lagowski, J. J.

    A set of interactive, computer-simulated experiments was designed to respond to the large range of individual differences in aptitude and reasoning ability generally exhibited by students enrolled in first-semester general chemistry. These experiments give students direct experience in the type of decision making needed in an experimental setting.…

  2. Web Support System for Group Collaborative Decisions

    NASA Astrophysics Data System (ADS)

    Rigopoulos, George; Psarras, John; Askounis, Dimitrios Th.

    In this research, we present a Group Decision Support System (GDSS) based on web technology, which can be used in asynchronous mode from group members. It supports small collaborative groups in classification decisions, implementing a supervised multicriteria methodology. A facilitator, who defines necessary parameters and initiates the procedure, coordinates the entire operation. Next, members evaluate the proposed parameter set and express their preferences in numeric format. Aggregation of individuals` preferences is executed at the parameter level by utilization of OWA operator and a group parameter set is produced which is used as input for the classification algorithm. A multicriteria classification algorithm is used for the classification of actions (people, projects etc.). Finally, group members evaluate results and consensus as well as satisfaction indexes are calculated. In case of low acceptance level, parameters are redefined and aggregation phase is repeated. The system has been utilized effectively to solve group classification problems in business environment. The overall architecture as well the methodology is presented, along with a sample application. Empirical findings from GDSS application and the methodology provide evidence that it is a valid approach for similar decision problems in numerous business environments, including production, human resources and operations.

  3. 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.

  4. 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.

  5. 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

  6. Computerized decision support system for kidney paired donation program.

    PubMed

    Chen, Yanhua; Song, Peter X-K

    2011-01-01

    In order to assist physicians and other health professionals for health care improvement, clinical decision support systems, through interactive computerized software, become very popular in clinical practice. The crisis associated with kidney organ shortage has triggered an innovative strategy, termed as Kidney Paired Donation (KPD) program, to address a rapidly expanding demand for donor kidneys. KPD program involves how to making optimal decision for allowing patients with incompatible living donors to receive compatible organs by best matching donors. Although some computerized optimization tools are being used in the current KPD program, there still lacks a general decision support system which enables us to evaluate and compare different kidney allocation strategies and effects of policy. In this paper, we discuss a general computer-based KPD decision model that appropriately reflects the real world clinical application. Also, the whole decision process is to be visualized by our Graphical User Interface (GUI) software, which offers a user friendly platform not only to provide a convenient interface for clinicians but also to assess different kidney exchange strategies of clinical importance. PMID:22255013

  7. Flood Impact Modelling to support decision making

    NASA Astrophysics Data System (ADS)

    Owen, Gareth; Quinn, Paul; O'Donnell, Greg

    2015-04-01

    Much of what is known about the impacts of landuse change and Natural Flood Management (NFM) is at the local/plot scale. Evidence of the downstream impacts at the larger catchment scale is limited. However, the strategic and financial decisions of land managers, stakeholders and policy makers are made at the larger scale. There are a number of techniques that have the potential to scale local impacts to the catchment scale. This poster will show findings for the 30km2 Leven catchment, North Yorkshire, England. A NFM approach has been adopted by the Environment Agency to reduce flood risk within the catchment. A dense network of stream level gauges were installed in the catchment at the commencement of this project to gain a detailed understanding of the catchment behaviour during storm events. A novel Flood Impact Modelling (FIM) approach has been adopted which uses the network of gauges to disaggregate the outlet hydrograph in terms of source locations. Using a combination of expert opinion and local evidence, the model can be used to assess the impacts of distributed changes in land use management and NFM on flood events. A number of potential future landuse and NFM scenarios have been modelled to investigate their impact on flood peaks. These modelled outcomes are mapped to a simple Decision Support Matrix (DSM). The DSM encourages end users (e.g. land managers and policy makers) to develop an NFM scheme by studying the degree to which local runoff can be attenuated and how that flow will propagate through the network to the point of impact. The DSM relates the impact on flood peaks in terms of alterations to soil management practices and landscape flow connectivity (e.g. soil underdrainage), which can be easily understood by farmers and land managers. The DSM and the FIM together provide a simple to use and transparent modelling tool, making best use of expert knowledge, to support decision making.

  8. Apply creative thinking of decision support in electrical nursing record.

    PubMed

    Hao, Angelica Te-Hui; Hsu, Chien-Yeh; Li-Fang, Huang; Jian, Wen-Shan; Wu, Li-Bin; Kao, Ching-Chiu; Lu, Mei-Show; Chang, Her-Kung

    2006-01-01

    The nursing process consists of five interrelated steps: assessment, diagnosis, planning, intervention, and evaluation. In the nursing process, the nurse collects a great deal of data and information. The amount of data and information may exceed the amount the nurse can process efficiently and correctly. Thus, the nurse needs assistance to become proficient in the planning of nursing care, due to the difficulty of simultaneously processing a large set of information. Computer systems are viewed as tools to expand the capabilities of the nurse's mind. Using computer technology to support clinicians' decision making may provide high-quality, patient-centered, and efficient healthcare. Although some existing nursing information systems aid in the nursing process, they only provide the most fundamental decision support--i.e., standard care plans associated with common nursing diagnoses. Such a computerized decision support system helps the nurse develop a care plan step-by-step. But it does not assist the nurse in the decision-making process. The decision process about how to generate nursing diagnoses from data and how to individualize the care plans still reminds of the nurse. The purpose of this study is to develop a pilot structure in electronic nursing record system integrated with international nursing standard for improving the proficiency and accuracy of plan of care in clinical pathway process. The proposed pilot systems not only assist both student nurses and nurses who are novice in nursing practice, but also experts who need to work in a practice area which they are not familiar with.

  9. 12 CFR 1290.4 - Decision on community support statements.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 12 Banks and Banking 7 2011-01-01 2011-01-01 false Decision on community support statements. 1290... COMMUNITY SUPPORT REQUIREMENTS § 1290.4 Decision on community support statements. (a) Action on community support statements. FHFA will act on each community support statement in accordance with the...

  10. 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...

  11. 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

  12. 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).

  13. Computerised clinical decision support for suspected PE.

    PubMed

    Jiménez, David; Resano, Santiago; Otero, Remedios; Jurkojc, Carolina; Portillo, Ana Karina; Ruiz-Artacho, Pedro; Corres, Jesús; Vicente, Agustina; den Exter, Paul L; Huisman, Menno V; Moores, Lisa; Yusen, Roger D

    2015-09-01

    This study aimed to determine the effect of an evidence-based clinical decision support (CDS) algorithm on the use and yield of CT pulmonary angiography (CTPA) and on outcomes of patients evaluated in the emergency department (ED) for suspected PE. The study included 1363 consecutive patients evaluated for suspected PE in an ED during 12 months before and 12 months after initiation of CDS use. Introduction of CDS was associated with decreased CTPA use (55% vs 49%; absolute difference (AD), 6.3%; 95% CI 1.0% to 11.6%; p=0.02). The use of CDS was associated with fewer symptomatic venous thromboembolic events during follow-up in patients with an initial negative diagnostic evaluation for PE (0.7% vs 3.2%; AD 2.5%; 95% CI 0.9% to 4.6%; p<0.01).

  14. 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.

  15. The ECG as decision support in STEMI.

    PubMed

    Ripa, Maria Sejersten

    2012-03-01

    The electrocardiogram (ECG) can be used for determining the presence, location and extent of jeopardized myocardium during acute coronary occlusion. Accordingly, the ECG has become essential in the treatment of patients with acute coronary syndrome (ACS). This thesis aims at optimizing the decision support, provided by the ECG, for choosing the best treatment strategy in the individual patient with ST-segment elevation acute myocardial infarction (STEMI). ECG recorded in the prehospital setting has become the standard of care in many communities, but to achieve the full advantage of this early approach it is important that the ECG is recorded from accurately placed electrodes to produce an ECG that resembles the standard 12-lead ECG. Accurate electrode placement is difficult especially in the acute setting, and we investigated an alternative lead system with fewer electrodes in easily identified positions. We showed that the system produced waveforms similar to the standard 12-lead ECG. However, occasional diagnostic errors were seen, compromising general acceptance of the system. Once the ECG has been recorded a decision regarding triage must be made on the basis of a correct ECG diagnosis. We found that trained paramedics can diagnose STEMI correctly in patients without ECG confounding factors, while the presence of ECG confounding factors decreased their ability substantially. Consequently, since many patients do present with ECG confounding factors, transmission to an on-call cardiologist for an early correct diagnosis is needed. We showed that time to pPCI was reduced by more than 1 hour by transmitting prehospital ECG to a cardiologist's handheld device for diagnosis, triage, and activation of the catheterization laboratory when needed. The optimal treatment strategy is dependent on the duration of ischemia however patient information is often inaccurate. Accordingly, it would be advantageous if the first available ECG can help identify patients who will

  16. User Centered Clinical Decision Support Tools

    PubMed Central

    Sofianou, A.; Kannry, J.; Mann, D.M.; McGinn, T.G.

    2014-01-01

    Summary Background Dissemination and adoption of clinical decision support (CDS) tools is a major initiative of the Affordable Care Act’s Meaningful Use program. Adoption of CDS tools is multipronged with personal, organizational, and clinical settings factoring into the successful utilization rates. Specifically, the diffusion of innovation theory implies that ‘early adopters’ are more inclined to use CDS tools and younger physicians tend to be ranked in this category. Objective This study examined the differences in adoption of CDS tools across providers’ training level. Participants From November 2010 to 2011, 168 residents and attendings from an academic medical institution were enrolled into a randomized controlled trial. Intervention The intervention arm had access to the CDS tool through the electronic health record (EHR) system during strep and pneumonia patient visits. Main Measures The EHR system recorded details on how intervention arm interacted with the CDS tool including acceptance of the initial CDS alert, completion of risk-score calculators and the signing of medication order sets. Using the EHR data, the study performed bivariate tests and general estimating equation (GEE) modeling to examine the differences in adoption of the CDS tool across residents and attendings. Key Results The completion rates of the CDS calculator and medication order sets were higher amongst first year residents compared to all other training levels. Attendings were the less likely to accept the initial step of the CDS tool (29.3%) or complete the medication order sets (22.4%) that guided their prescription decisions, resulting in attendings ordering more antibiotics (37.1%) during an CDS encounter compared to residents. Conclusion There is variation in adoption of CDS tools across training levels. Attendings tended to accept the tool less but ordered more medications. CDS tools should be tailored to clinicians’ training levels. PMID:25589914

  17. 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

  18. 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

  19. 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.

  20. 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...

  1. Case-based reasoning in Intelligent Health Decision Support Systems.

    PubMed

    González, Carolina; López, Diego M; Blobel, Bernd

    2013-01-01

    Decision-making is a crucial task for decision makers in healthcare, especially because decisions have to be made quickly, accurately and under uncertainty. Taking into account the importance of providing quality decisions, offering assistance in this complex process has been one of the main challenges of Artificial Intelligence throughout history. Decision Support Systems (DSS) have gained popularity in the medical field for their efficacy to assist decision-making. In this sense, many DSS have been developed, but only few of them consider processing and analysis of information contained in electronic health records, in order to identify individual or population health risk factors. This paper deals with Intelligent Decision Support Systems that are integrated into Electronic Health Records Systems (EHRS) or Public Health Information Systems (PHIS). It provides comprehensive support for a wide range of decisions with the purpose of improving quality of care delivered to patients or public health planning, respectively.

  2. 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...

  3. Using Group Decision Support Systems in Teaching the Small Group Communication Course.

    ERIC Educational Resources Information Center

    Scott, Craig R.

    The nature of group decision support systems (GDSS), its key advantages, and the experience of using it with several classes help illustrate that this type of computer technology can serve an important function in supplementing instruction of the small group course. The primary purpose of a GDSS is to improve group decision-making and…

  4. Decision Support System in the Management of Resource-Sharing Networks.

    ERIC Educational Resources Information Center

    Dubey, Yogendra P.

    1984-01-01

    Reports on emergence of decision support system (DSS) as a practical approach for applying computers and information to problems facing management. Information processing and decision making in organizations, simulation-model-based DSS in management of library resource sharing networks, and a resource-sharing simulation system are highlighted.…

  5. 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.

  6. 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...

  7. A conceptual evolutionary aseismic decision support framework for hospitals

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  8. 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

  9. 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

  10. Distributed computing support program`s databases

    SciTech Connect

    Parsons, Amy

    1996-05-01

    The Distributed Computing Support Program (DCSP) is the current system for keeping track of computer hardware maintenance throughout the Lawrence Livermore National Laboratory. DCSP consists of four separate Ingres databases each with their own support files. The process of updating and revising the support files, to make the business process more efficient is described in this paper.

  11. 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…

  12. 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.

  13. Decision Support Systems in Elementary and Secondary Educational Administration.

    ERIC Educational Resources Information Center

    Fisher, Janet Cameron; And Others

    1990-01-01

    A decision support system (DSS) is an interactive computerized system capable of providing direct, personal support for complex managerial decisions. This paper reviews DDSs and their general capabilities, describes potential benefits to school administrators, presents DDS applications in several school districts, and discusses implementation…

  14. Perfusion computed tomography to assist decision making for stroke thrombolysis.

    PubMed

    Bivard, Andrew; Levi, Christopher; Krishnamurthy, Venkatesh; McElduff, Patrick; Miteff, Ferdi; Spratt, Neil J; Bateman, Grant; Donnan, Geoffrey; Davis, Stephen; Parsons, Mark

    2015-07-01

    The use of perfusion imaging to guide selection of patients for stroke thrombolysis remains controversial because of lack of supportive phase three clinical trial evidence. We aimed to measure the outcomes for patients treated with intravenous recombinant tissue plasminogen activator (rtPA) at a comprehensive stroke care facility where perfusion computed tomography was routinely used for thrombolysis eligibility decision assistance. Our overall hypothesis was that patients with 'target' mismatch on perfusion computed tomography would have improved outcomes with rtPA. This was a prospective cohort study of consecutive ischaemic stroke patients who fulfilled standard clinical/non-contrast computed tomography eligibility criteria for treatment with intravenous rtPA, but for whom perfusion computed tomography was used to guide the final treatment decision. The 'real-time' perfusion computed tomography assessments were qualitative; a large perfusion computed tomography ischaemic core, or lack of significant perfusion lesion-core mismatch were considered relative exclusion criteria for thrombolysis. Specific volumetric perfusion computed tomography criteria were not used for the treatment decision. The primary analysis compared 3-month modified Rankin Scale in treated versus untreated patients after 'off-line' (post-treatment) quantitative volumetric perfusion computed tomography eligibility assessment based on presence or absence of 'target' perfusion lesion-core mismatch (mismatch ratio >1.8 and volume >15 ml, core <70 ml). In a second analysis, we compared outcomes of the perfusion computed tomography-selected rtPA-treated patients to an Australian historical cohort of non-contrast computed tomography-selected rtPA-treated patients. Of 635 patients with acute ischaemic stroke eligible for rtPA by standard criteria, thrombolysis was given to 366 patients, with 269 excluded based on visual real-time perfusion computed tomography assessment. After off-line quantitative

  15. 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...

  16. Supporting Medical Decision Making with Argumentation Tools

    ERIC Educational Resources Information Center

    Lu, Jingyan; Lajoie, Susanne P.

    2008-01-01

    This study investigated the collaborative decision-making and communicative discourse of groups of learners engaged in a simulated medical emergency in two conditions. In one condition subgroups used a traditional whiteboard (TW group) to document medical arguments on how to solve a medical emergency. In the other condition subgroups used…

  17. 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…

  18. Decision Support Systems and Line Performance: Case of Gold Coast University Hospital.

    PubMed

    Connor, Martin; Ghapanchi, Amir Hossein; Blumenstein, Michael; Amrollahi, Alireza; Najaftorkaman, Mohammadreza

    2015-01-01

    Computer-based decision support information systems have been promoted for their potential to improve physician performance and patient outcomes and support clinical decision making. The current case study reported design and implementation of a high-level decision support system (DSS) which facilitated the flow of data from operational level to top managers and leadership level of hospitals. The results shows that development of a DSS improve data connectivity, timing, and responsiveness issues via centralised sourcing and storing of principal health-related information in the hospital. The implementation of the system has resulted in significant enhancements in outpatient waiting times management.

  19. 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.

  20. [A decision-support system for hematology].

    PubMed

    Straka, L; Stránský, P; Kmonícek, M

    1998-01-01

    Thrombocytopenia and following bleeding at the treatment of hematological malignancies is a dangerous complication. The indication of thrombocyte transfusion is the key point for the therapy and proylaxy of bleeding. The all problem is divided into two parts. Evaluation of the risk of bleeding (80% of decision), estimation of the risk of aloimunization and risk of connected with the transfusion (20% decision). For now we are concentrated to the evaluation of the risk of bleeding. In the first stage we are concentrated to statistical evaluation of values to define factors possibly highering the risk of bleeding. Factors were determined with help of two test, GUHA method and using literature. For recognized factors were trained 3 layer neuron nets with a non-linear method pack propagation. After that an application was developed to determine the risk of bleeding for a routine use in clinical practice.

  1. Intelligent decision support technologies for design and manufacturing

    SciTech Connect

    Zacharia, T.; Allen, J.D.; Ivezic, N.; Ludtka, G.M.

    1997-06-01

    For many of today`s complex manufacturing processes, there exists a solid body of knowledge that enables direct simulations of such processes yielding predictions about the final product and process characteristics using finite element or finite difference methods. However, the computational complexities of these simulations are such that they do not lend themselves easily to routine and timely use in optimization and control of manufacturing processes. More recently, neural network-based decision support technologies have been developed which hold the promise of bringing the body of analytical and simulation knowledge closer to the design and optimization processes in manufacturing industries. The paper discusses the application of a holistic approach wherein existing finite element, neural-network, and optical metrology methods are combined to develop a real time tool for optimization and control of the sheet metal stamping process. Significant issues in the development of such a tool and results from its application to a deformation process are discussed.

  2. 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

  3. Decision Support Systems: Applications in Statistics and Hypothesis Testing.

    ERIC Educational Resources Information Center

    Olsen, Christopher R.; Bozeman, William C.

    1988-01-01

    Discussion of the selection of appropriate statistical procedures by educators highlights a study conducted to investigate the effectiveness of decision aids in facilitating the use of appropriate statistics. Experimental groups and a control group using a printed flow chart, a computer-based decision aid, and a standard text are described. (11…

  4. Telematics and the Decision Support Intermediary.

    ERIC Educational Resources Information Center

    Sheehan, Bernard S.

    1985-01-01

    Advanced communication and computing technologies create new resources and new opportunities in expanded role relationships for institutional research. Approaches to impact analysis and the rates of future change are discussed. (Author/MLW)

  5. 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...

  6. 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.

  7. 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.

  8. Mining multi-dimensional data for decision support

    SciTech Connect

    Donato, J.M.; Schryver, J.C.; Hinkel, G.C.; Schmoyer, R.L. Jr.; Grady, N.W.; Leuze, M.R. |

    1998-06-01

    While it is widely recognized that data can be a valuable resource for any organization, extracting information contained within the data is often a difficult problem. Attempts to obtain information from data may be limited by legacy data storage formats, lack of expert knowledge about the data, difficulty in viewing the data, or the volume of data needing to be processed. The rapidly developing field of Data Mining or Knowledge Data Discovery is a blending of Artificial Intelligence, Statistics, and Human-Computer Interaction. Sophisticated data navigation tools to obtain the information needed for decision support do not yet exist. Each data mining task requires a custom solution that depends upon the character and quantity of the data. This paper presents a two-stage approach for handling the prediction of personal bankruptcy using credit card account data, combining decision tree and artificial neural network technologies. Topics to be discussed include the pre-processing of data, including data cleansing, the filtering of data for pertinent records, and the reduction of data for attributes contributing to the prediction of bankruptcy, and the two steps in the mining process itself.

  9. 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...

  10. The Future of Decision Support Systems in Institutional Research.

    ERIC Educational Resources Information Center

    Rohrbaugh, John

    1986-01-01

    In the context of decision support systems (DSS) use, four perspectives on evaluating decisions (consensual, political, empirical, and rational) and four models of organizational effectiveness (human relations, open system, internal process, and rational goal) are examined for their implications for DSS implementation and evaluation. (MSE)

  11. Decision Support Systems: An Introduction for Program Evaluators.

    ERIC Educational Resources Information Center

    O'Sullivan, Elizabethann

    1985-01-01

    Decision Support Systems (DSS) are automated information systems designed to aid administrative decision making. A literature review on the design, implementation, and evaluation of DSS, suggests that evaluators act as liasons between designers and managers, identify and collect data for DSS, and evaluate DSS. (Author/EGS)

  12. 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

  13. 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

  14. 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...

  15. 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'…

  16. Clinical Decision Support Tools: The Evolution of a Revolution.

    PubMed

    Mould, D R; D'Haens, G; Upton, R N

    2016-04-01

    Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug monitoring. In the treatment of inflammatory bowel disease patients with infliximab, dashboards may reduce therapeutic failures and treatment costs. The history and future development of modern Bayesian dashboard systems is described. PMID:26785109

  17. Toward a synthesis of paradigms for decision support

    NASA Astrophysics Data System (ADS)

    Egner, Michael; Davis, Paul K.

    2004-08-01

    Over the past half-century, the study of human decision making has evolved from dry philosophy into a diverse set of experimentally-tested, behavior-centered theories. However, the sheer volume of disciplines and sub-disciplines-and the often-esoteric debates that divide them-threaten to obscure the very real advances that have been made in modeling human decision making. This paper, giving preliminary analysis from a longer study,[1] begins to address the "so-what" factor in decision making theory, specifically as related to Air Force modeling, simulation, and decision-support needs. While a general consensus is forming on how humans make decisions (descriptive), there are still major conflicts on how humans should make decisions (normative), and by extension, how human decision making can be improved (prescriptive). The first half of this paper surveys modern decision science, focusing on two of the most influential sub-disciplines: the heuristics & biases paradigm (HBP) and the naturalistic paradigm (NP). The second half of this paper will attempt to sketch out a normative/prescriptive synthesis between the two schools, and chart implications for design of decision support.

  18. Group decision support system for customer-driven product design

    NASA Astrophysics Data System (ADS)

    Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada

    2000-10-01

    This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.

  19. Family and Related Service Partnerships in Home Computer Decision-Making.

    ERIC Educational Resources Information Center

    Parette, Howard P.; Anderson, Cindy L.

    2001-01-01

    Provides a review of literature related to perceptions of home computers held by various cultural groups. Argues that families vary in their degree of involvement in working with professionals to make decisions about home computers. Describes training as a primary support required by many families to ensure effective implementation of home…

  20. 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

  1. Decision support system for theater missile defense

    NASA Astrophysics Data System (ADS)

    Gonsalves, Paul; Burge, Janet; Popp, Ben

    2003-08-01

    Military services require C4I systems that support a full spectrum of operations. This is specifically relevant to the theatre missile defense (TMD) mission planning and analysis community where there have been several recent concept changes; advancements in information technology, sensors, and weapons; and expansion in the diversity and capabilities of potential adversaries. To fully support campaign development and analysis in this new environment, there is a need for systems and tools that enhance understanding of adversarial behavior, assess potential threat capabilities and vulnerabilities, perform C4I system trades, and provide methods to identify macro-level novel or emergent combat tactics and behavior derived from simpler micro-level rules. Such systems must also be interactive, collaborative, and semi-autonomous, providing the INTEL analyst with the means for exploration and potential exploitation of novel enemy behavior patterns. To address these issues we have developed an Intelligent Threat Assessment Processor (ITAP) to provide prediction and interpretation of enemy courses of actions (eCOAs) for the TMD domain. This system uses a combination of genetic algorithm-based optimization in tandem with the spatial analysis and visualization capabilities of a commercial-off-the-shelf (COTS) geographic information system to generate and evaluate potential eCOAs.

  2. 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

  3. Object-oriented design and programming in medical decision support.

    PubMed

    Heathfield, H; Armstrong, J; Kirkham, N

    1991-12-01

    The concept of object-oriented design and programming has recently received a great deal of attention from the software engineering community. This paper highlights the realisable benefits of using the object-oriented approach in the design and development of clinical decision support systems. These systems seek to build a computational model of some problem domain and therefore tend to be exploratory in nature. Conventional procedural design techniques do not support either the process of model building or rapid prototyping. The central concepts of the object-oriented paradigm are introduced, namely encapsulation, inheritance and polymorphism, and their use illustrated in a case study, taken from the domain of breast histopathology. In particular, the dual roles of inheritance in object-oriented programming are examined, i.e., inheritance as a conceptual modelling tool and inheritance as a code reuse mechanism. It is argued that the use of the former is not entirely intuitive and may be difficult to incorporate into the design process. However, inheritance as a means of optimising code reuse offers substantial technical benefits.

  4. 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.

  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. Moving toward climate-informed agricultural decision support - can we use PRISM data for more than just monthly averages?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Decision support systems/models for agriculture are varied in target application and complexity, ranging from simple worksheets to near real-time forecast systems requiring significant computational and manpower resources. Until recently, most such decision support systems have been constructed with...

  7. Great expectations: neural computations underlying the use of social norms in decision-making.

    PubMed

    Chang, Luke J; Sanfey, Alan G

    2013-03-01

    Social expectations play a critical role in everyday decision-making. However, their precise neuro-computational role in the decision process remains unknown. Here we adopt a decision neuroscience framework by combining methods and theories from psychology, economics and neuroscience to outline a novel, expectation-based, computational model of social preferences. Results demonstrate that this model outperforms the standard inequity-aversion model in explaining decision behavior in a social interactive bargaining task. This is supported by fMRI findings showing that the tracking of social expectation violations is processed by anterior cingulate cortex, extending previous computational conceptualizations of this region to the social domain. This study demonstrates the usefulness of this interdisciplinary approach in better characterizing the psychological processes that underlie social interactive decision-making.

  8. 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...

  9. 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.

  10. 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…

  11. Life Lab Computer Support System's Manual.

    ERIC Educational Resources Information Center

    Lippman, Beatrice D.; Walfish, Stephen

    Step-by-step procedures for utilizing the computer support system of Miami-Dade Community College's Life Lab program are described for the following categories: (1) Registration--Student's Lists and Labels, including three separate computer programs for current listings, next semester listings, and grade listings; (2) Competence and Resource…

  12. 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

  13. Map-based decision aids for fire support

    NASA Astrophysics Data System (ADS)

    Yarosh, Victor

    1996-06-01

    The Fire Control Division at ARDEC is developing prototype decision aid tools to enable fire support echelons to rapidly respond to requests for fire support. Decision aids on fire support platforms can assist in route planning, site selection, and develop mobility overlays to enable the shooter to rapidly move into position and prepare for the fire mission. The Decision Aid system utilizes an integrated design approach which has each module interacting with the others by sharing data bases and common algorithms to provide recommended courses of action for route planning and generation, position selection, self defense, logistics estimates, situational awareness and fire mission planning aids such as tactical assessment, tactical planning, sustainment, etc. The Decision Aid system will use expert system artificial intelligence which will be developed from knowledge bases utilizing object oriented design. The modules currently reason on Defense Mapping Agency Interim Terrain Data and Digital Terrain Elevation Data and collect mission, intelligence, and sensor data from the digitized battlefield information distribution system to provide the crew or mission planners with intelligent recommendations. The system can provide a trade off analysis of time vs. safety, enable commanders to rapidly respond to fire support request, automatically generate OpOrders, and create overlays which depict mobility corridors, NBC areas, friendly units, overhead concealment, communications, and threat areas. The Decision Aids system can provide a vastly improved mobility, situational awareness, and decision cycle capabilities which can be utilized to increase the tempo of battle.

  14. Designing Computerized Decision Support That Works for Clinicians and Families

    PubMed Central

    Fiks, Alexander G.

    2011-01-01

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

  15. Tablet-based patient monitoring and decision support systems in hospital care.

    PubMed

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Linden, Maria

    2015-08-01

    Remote patient monitoring with evidence-based decision support is revolutionizing healthcare. This novel approach could enable both patients and healthcare providers to improve quality of care and reduce costs. Clinicians can also view patients' data within the hospital network on tablet computers as well as other ubiquitous devices. Today, a wide range of applications are available on tablet computers which are increasingly integrating into the healthcare mainstream as clinical decision support systems. Despite the benefits of tablet-based healthcare applications, there are concerns around the accuracy, security and stability of such applications. In this study, we developed five tablet-based application screens for remote patient monitoring at hospital care settings and identified related issues and challenges. The ultimate aim of this research is to integrate decision support algorithms into the monitoring system in order to improve inpatient care and the effectiveness of such applications. PMID:26736485

  16. 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

  17. Towards an intelligent decision support system for public health surveillance - a qualitative analysis of information needs.

    PubMed

    Mera, Maritza; González, Carolina; López, Diego M

    2014-01-01

    Public health information systems are often implemented considering the functionalities and requirements established by administrative staff or researchers, but sometimes ignoring the particular needs of decision makers. This paper describes a proposal to support the design of a Decision Support System for Public Health Surveillance in Colombia, by conducting a qualitative study to identify the real needs of people involved in decision making processes. Based on the study results, an intelligent computational component that supports Data Analysis Automation, Prediction of future scenarios and the identification of new Behavioral Patterns is proposed. The component will be implemented using the Case Based Reasoning methodology, which will be integrated as a new component of the Open Source DHIS2 Platform, enabling public health decision-making.

  18. 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.

  19. 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.

  20. Future of medical knowledge management and decision support.

    PubMed

    Greenes, Robert A

    2002-01-01

    Attempts to predict the future are typically off the mark. Beyond the challenges of forecasting the stock market or the weather, dramatic instances of notoriously inaccurate prognostications have been those by the US patent office in the late 1800s about the future of inventions, by Thomas Watson in the 1930s about the market for large computers, and by Bill Gates in the early 1990s about the significance of the Internet. When one seeks to make predictions about health care, one finds that, beyond the usual uncertainties regarding the future, additional impediments to forecasting are the discontinuities introduced by advances in biomedical science and technology, the impact of information technology, and the reorganizations and realignments attending various approaches to health care delivery and finance. Changes in all three contributing areas themselves can be measured in "PSPYs", or paradigm shifts per year. Despite these risks in forecasting, I believe that certain trends are sufficiently clear that I am willing to venture a few predictions. Further, the predictions I wish to make suggest a goal for the future that can be achieved, if we can align the prevailing political, financial, biomedical, and technical forces toward that end. Thus, in a sense this is a call to action, to shape the future rather than just let it happen. This chapter seeks to lay out the direction we are heading in knowledge management and decision support, and to delineate an information technology framework that appears desirable. I believe the framework to be discussed is of importance to the health care-related knowledge management and decision making activities of the consumer and patient, the health care provider, and health care delivery organizations and insurers. The approach is also relevant to the other dimensions of academic health care institution activities, notably the conduct of research and the processes of education and learning. PMID:12026135

  1. 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.

  2. 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.

  3. DocBot: a novel clinical decision support algorithm.

    PubMed

    Ninh, Andrew Q

    2014-01-01

    DocBot is a web-based clinical decision support system (CDSS) that uses patient interaction and electronic health record analytics to assist medical practitioners with decision making. It consists of two distinct HTML interfaces: a preclinical form wherein a patient inputs symptomatic and demographic information, and an interface wherein a medical practitioner views patient information and analysis. DocBot comprises an improved software architecture that uses patient information, electronic health records, and etiologically relevant binary decision questions (stored in a knowledgebase) to provide medical practitioners with information including, but not limited to medical assessments, treatment plans, and specialist referrals.

  4. 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.

  5. 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.

  6. 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...

  7. 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...

  8. Funder Report on Decision Support Systems Project Dissemination Activities, Fiscal Year 1985.

    ERIC Educational Resources Information Center

    Tetlow, William L.

    Dissemination activities for the Decision Support Systems (DSS) for fiscal year (FY) 1985 are reported by the National Center for Higher Education Management Systems (NCHEMS). The main means for disseminating results of the DSS research and development project has been through computer-generated video presentations at meetings of higher education…

  9. Trends in Facility Management Technology: The Emergence of the Internet, GIS, and Facility Assessment Decision Support.

    ERIC Educational Resources Information Center

    Teicholz, Eric

    1997-01-01

    Reports research on trends in computer-aided facilities management using the Internet and geographic information system (GIS) technology for space utilization research. Proposes that facility assessment software holds promise for supporting facility management decision making, and outlines four areas for its use: inventory; evaluation; reporting;…

  10. Temporal pattern mining for multivariate clinical decision support.

    PubMed

    Saini, Sheetal; Dua, Sumeet

    2013-01-01

    Multivariate temporal data are collections of contiguous data values that reflect complex temporal changes over a given duration. Technological advances have resulted in significant amounts of such data in high-throughput disciplines, including EEG and iEEG data for effective and efficient healthcare informatics, and decision support. Most data analytics and data-mining algorithms are effective in capturing global trends, but fail to capture localized behavioral changes in large temporal data sets. We present a two-step algorithmic methodology to uncover temporal patterns and exploiting them for an efficient and accurate decision support system. This methodology aids the discovery of previously unknown, nontrivial, and potentially useful temporal patterns for enhanced patient-specific clinical decision support with high degrees of sensitivity and specificity. Classification results on multivariate time series iEEG data for epileptic seizure detection also demonstrate the efficacy and accuracy of the technique to uncover interesting and effective domain class-specific temporal patterns.

  11. Aeromedical evacuation planning using geospatial decision-support.

    PubMed

    Bastian, Nathaniel D; Fulton, Lawrence V

    2014-02-01

    In this study, we proffer an algorithmic, geospatial-based decision-support methodology that assists military decision-makers in determining which aeromedical evacuation (MEDEVAC) assets to launch after receiving an injury location, given knowledge only of terrain, aircraft location, and aircraft capabilities. The objective is for military medical planners to use this decision-support tool (1) to improve real-time situational awareness by visualization of MEDEVAC coverage, showing which areas can be reached within established timelines; (2) to support medical planning by visualizing the impact of changes in the medical footprint to the MEDEVAC coverage; and (3) to support decision-making by providing a time-sorted list of MEDEVAC asset packages to select from, given the location of the patients. This same geospatial-based decision tool can be used for proper emplacement of evacuation assets such that the theater is covered within a truly representative 1-hour response time. We conclude with a discussion of applicability of this tool in medical force structure planning.

  12. Artificial neural networks for decision support in clinical medicine.

    PubMed

    Forsström, J J; Dalton, K J

    1995-10-01

    Connectionist models such as neural networks are alternatives to linear, parametric statistical methods. Neural networks are computer-based pattern recognition methods with loose similarities with the nervous system. Individual variables of the network, usually called 'neurones', can receive inhibitory and excitatory inputs from other neurones. The networks can define relationships among input data that are not apparent when using other approaches, and they can use these relationships to improve accuracy. Thus, neural nets have substantial power to recognize patterns even in complex datasets. Neural network methodology has outperformed classical statistical methods in cases where the input variables are interrelated. Because clinical measurements usually derive from multiple interrelated systems it is evident that neural networks might be more accurate than classical methods in multivariate analysis of clinical data. This paper reviews the use of neural networks in medical decision support. A short introduction to the basics of neural networks is given, and some practical issues in applying the networks are highlighted. The current use of neural networks in image analysis, signal processing and laboratory medicine is reviewed. It is concluded that neural networks have an important role in image analysis and in signal processing. However, further studies are needed to determine the value of neural networks in the analysis of laboratory data.

  13. 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.

  14. Judgmental biases in decision support for strike operations

    NASA Astrophysics Data System (ADS)

    Kulick, Jonathan D.; Davis, Paul K.

    2003-09-01

    Human decisionmaking does not typically fit the classical analytic model, and the heuristics employed may yield a variety of biased judgments. These biases are often considered inherently adverse, but may be functional in some cases. Decision support systems can mitigate some biases, but often introduce others. "Debiasing" decision support systems entails designing DSS to address expected biases, and to preclude inducing new ones. High-level C2 decisionmaking processes are poorly understood, but these general principles and lessons learned in other fields are expected to obtain. A notional air campaign illustrates potential biases in a commander"s judgment during planning and execution, and the role of debiasing operational DSS.

  15. 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

  16. 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.

  17. Improving the Slum Planning Through Geospatial Decision Support System

    NASA Astrophysics Data System (ADS)

    Shekhar, S.

    2014-11-01

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

  18. 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

  19. 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

  20. 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. PMID:24892075

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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…

  7. 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…

  8. 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 ...

  9. 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...

  10. A Web-Based Decision Support Tool for Academic Advising

    ERIC Educational Resources Information Center

    Feghali, Tony; Zbib, Imad; Hallal, Sophia

    2011-01-01

    Student advising is an important and time-consuming effort in academic life. This paper attempts to solve a technology-based "last mile" problem by developing and evaluating a web-based decision support tool (the Online Advisor) that helps advisors and students make better use of an already present university student information system. Two…

  11. 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...

  12. Supporting Parental Decisions About Genomic Sequencing for Newborn Screening: The NC NEXUS Decision Aid.

    PubMed

    Lewis, Megan A; Paquin, Ryan S; Roche, Myra I; Furberg, Robert D; Rini, Christine; Berg, Jonathan S; Powell, Cynthia M; Bailey, Donald B

    2016-01-01

    Advances in genomic sequencing technology have raised fundamental challenges to the traditional ways genomic information is communicated. These challenges will become increasingly complex and will affect a much larger population in the future if genomics is incorporated into standard newborn screening practice. Clinicians, public health officials, and other stakeholders will need to agree on the types of information that they should seek and communicate to parents. Currently, few evidence-based and validated tools are available to support parental informed decision-making. These tools will be necessary as genomics is integrated into clinical practice and public health systems. In this article we describe how the North Carolina Newborn Exome Sequencing for Universal Screening study is addressing the need to support parents in making informed decisions about the use of genomic testing in newborn screening. We outline the context for newborn screening and justify the need for parental decision support. We also describe the process of decision aid development and the data sources, processes, and best practices being used in development. By the end of the study, we will have an evidenced-based process and validated tools to support parental informed decision-making about the use of genomic sequencing in newborn screening. Data from the study will help answer important questions about which genomic information ought to be sought and communicated when testing newborns. PMID:26729698

  13. Supporting Parental Decisions About Genomic Sequencing for Newborn Screening: The NC NEXUS Decision Aid

    PubMed Central

    Lewis, Megan A.; Paquin, Ryan S.; Roche, Myra I.; Furberg, Robert D.; Rini, Christine; Berg, Jonathan S.; Powell, Cynthia M.; Bailey, Donald B.

    2016-01-01

    Advances in genomic sequencing technology have raised fundamental challenges to the traditional ways genomic information is communicated. These challenges will become increasingly complex and will affect a much larger population in the future if genomics is incorporated into standard newborn screening practice. Clinicians, public health officials, and other stakeholders will need to agree on the types of information that they should seek and communicate to parents. Currently, few evidence-based and validated tools are available to support parental informed decision-making. These tools will be necessary as genomics is integrated into clinical practice and public health systems. In this article we describe how the North Carolina Newborn Exome Sequencing for Universal Screening study is addressing the need to support parents in making informed decisions about the use of genomic testing in newborn screening. We outline the context for newborn screening and justify the need for parental decision support. We also describe the process of decision aid development and the data sources, processes, and best practices being used in development. By the end of the study, we will have an evidenced-based process and validated tools to support parental informed decision-making about the use of genomic sequencing in newborn screening. Data from the study will help answer important questions about which genomic information ought to be sought and communicated when testing newborns. PMID:26729698

  14. 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

  15. The Contribution of a Decision Support System to Complex Educational Decisions

    ERIC Educational Resources Information Center

    Klein, Joseph

    2005-01-01

    This study examined the effect of complexity of problems on the degree of disparity between intuitive (PDM) and computer-assisted (DSS) decision-making. 840 teachers chose intuitive solutions for educational dilemmas, and recorded the relative importance of the guiding criteria. Utilizing this information, DSS calculated preferred solutions. Of…

  16. Assessment of (Computer-Supported) Collaborative Learning

    ERIC Educational Resources Information Center

    Strijbos, J. -W.

    2011-01-01

    Within the (Computer-Supported) Collaborative Learning (CS)CL research community, there has been an extensive dialogue on theories and perspectives on learning from collaboration, approaches to scaffold (script) the collaborative process, and most recently research methodology. In contrast, the issue of assessment of collaborative learning has…

  17. 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…

  18. 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…

  19. 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.

  20. Studying Collective Human Decision Making and Creativity with Evolutionary Computation.

    PubMed

    Sayama, Hiroki; Dionne, Shelley D

    2015-01-01

    We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational, and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of ideas, each conducted by participating humans. Based on this evolutionary perspective, we generated hypotheses about collective human decision making, using agent-based computer simulations. The hypotheses were then tested through several experiments with real human subjects. Throughout this project, we utilized evolutionary computation (EC) in non-traditional ways-(1) as a theoretical framework for reinterpreting the dynamics of idea generation and selection, (2) as a computational simulation model of collective human decision-making processes, and (3) as a research tool for collecting high-resolution experimental data on actual collaborative design and decision making from human subjects. We believe our work demonstrates untapped potential of EC for interdisciplinary research involving human and social dynamics.

  1. Physician characteristics associated with decisions to withdraw life support.

    PubMed Central

    Christakis, N A; Asch, D A

    1995-01-01

    OBJECTIVE. This study was undertaken to identify attributes of physicians associated with physicians' decisions to withdraw life support. METHODS. Of the 862 Pennsylvania internists surveyed and asked to make decisions in response to hypothetical vignettes and to report their actual experience with the withdrawal of life support, 485 (56%) responded. The data were analyzed with regression models. RESULTS. With other factors controlled, physicians were more willing to withdraw life support if they were young, practiced in a tertiary care setting, or spent more time in clinical practice; they were less willing if they were Catholic or Jewish. Physicians reported a higher frequency of actually withdrawing life support if they were young, had more contact with ICU patients, spent more time in clinical practice, or were specialists. Physicians with a greater willingness to withdraw were more likely to report having done so. CONCLUSIONS. Physicians' personal characteristics are associated with both their preferences and their practice in the withdrawal of life support, and a greater willingness to withdraw is associated with a higher frequency of withdrawal. The influence of physician characteristics demonstrates that patient preferences and clinical circumstances do not exclusively govern such ethical decisions. PMID:7892921

  2. Needs assessment for diagnostic decision support systems (DDSS).

    PubMed Central

    Berner, E. S.; Shugerman, A. A.

    1991-01-01

    Diagnostic decision support systems are often developed without a clear idea of how well the system will meet the needs of its users. The present study was designed to assess the information needs of clinicians. A set of questions submitted to an information service by family physicians was used to determine how much need there was for diagnostic decision support, the types of support needed, and the general content areas of their questions. Results showed that less than half of the questions were related to diagnosis and that most of those were requests for general information about a given condition. In addition, the fewest diagnosis questions were for conditions that were seen frequently in ambulatory care in a survey of family practitioners. PMID:1807674

  3. Decision support for simulation-based operation planning

    NASA Astrophysics Data System (ADS)

    Schubert, Johan; Hörling, Pontus

    2016-05-01

    In this paper, we develop methods for analyzing large amounts of data from a military ground combat simulation system. Through a series of processes, we focus the big data set on situations that correspond to important questions and show advantageous outcomes. The result is a decision support methodology that provides commanders with results that answer specific questions of interest, such as what the consequences for the Blue side are in various Red scenarios or what a particular Blue force can withstand. This approach is a step toward taking the traditional data farming methodology from its analytical view into a prescriptive operation planning context and a decision making mode.

  4. 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.

  5. 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. PMID:26262260

  6. 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…

  7. 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. PMID:16928418

  8. 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.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

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

  11. Hospital management decision support: a balanced scorecard approach.

    PubMed

    Gordon, D; Chapman, R; Kunov, H; Dolan, A; Carter, M

    1998-01-01

    Hospital management teams receive voluminous data from a wide variety of sources, but are unable to distill the essential data they require to make good decisions. We have used a methodology, which helps teams define and use important management data coupled with an information system that makes this data accessible. Results of our evaluation indicate that the process of developing a Balanced Scorecard indicator system helps management teams to define meaningful strategic objectives and measurable performance indicators. The framework combined with the information acts as an integrating force, providing a shared understanding of the unit's goals. We conclude that a customized decision support system, which integrates multiple measures in a balanced Scorecard framework, is a powerful tool for enabling complex decision making by a management team. PMID:10384497

  12. 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.

  13. 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.

  14. 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…

  15. 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.

  16. 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…

  17. 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…

  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 for subjects exposed to heat stress.

    PubMed

    Seeberg, Trine M; Vardøy, Astrid-Sofie B; Taklo, Maaike M Visser; Austad, Hanne Opsahl

    2013-03-01

    The physiological and activity strain index (PASI) has been developed to improve the online decision support for workers exposed to heat stress. Fire fighters (smoke divers) which are exposed to both heat-stress and high-risk situations have been used as test case. PASI combines a modified version of the relatively well-known physiological strain index (PSI) with activity data from accelerometers. The algorithm has been developed based on tests in a laboratory, and it has been verified in two field tests performed by smoke divers exposed to heat stress. The verification demonstrates that it is possible to distinguish between high- and low-risk situations when data from accelerometers are added to the situation analysis. This indicates that PASI can contribute to an improved risk assessment and online decision support for smoke divers compared to using PSI alone. PMID:24235112

  20. On the heuristic nature of medical decision-support systems.

    PubMed

    Aliferis, C F; Miller, R A

    1995-03-01

    In the realm of medical decision-support systems, the term "heuristic systems" is often considered to be synonymous with "medical artificial intelligence systems" or with "systems employing informal model(s) of problem solving". Such a view may be inaccurate and possibly impede the conceptual development of future systems. This article examines the nature of heuristics and the levels at which heuristic solutions are introduced during system design and implementation. The authors discuss why heuristics are ubiquitous in all medical decision-support systems operating at non-trivial domains, and propose a unifying definition of heuristics that encompasses formal and ad hoc systems. System developers should be aware of the heuristic nature of all problem solving done in complex real world domains, and characterize their own use of heuristics in describing system development and implementation. PMID:9082138

  1. 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.

  2. 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.

  3. A decision support system for AIDS intervention and prevention.

    PubMed

    Xu, L D

    1994-08-01

    In recent years, the importance of information systems has been identified as a vital issue to continuing success in AIDS intervention and prevention (AIP). The advances in information technology have resulted in integrative information systems including decision support systems (DSS). The concept of DSS for AIP was created at the intersection of two trends. The first trend was a growing belief that AIP information systems are successful in automating operations in AIP programs. The second was a continuing improvement in modeling and software development in the AIP area. This paper presents an integrated DSS for AIP. The system is integrated with a database and achieves its efficiency by incorporating various algorithms and models to support AIP decision processes. The application examples include screening AIDS-risky behaviors, evaluating educational interventions, and scheduling AIP sessions. The implementation results present evidence of the usefulness of the system in AIP.

  4. Distributed collaborative decision support environments for predictive awareness

    NASA Astrophysics Data System (ADS)

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

    2005-05-01

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

  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. 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.

  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. 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

  9. An Advanced Decision Support Tool for Electricity Infrastructure Operations

    SciTech Connect

    Chen, Yousu; Huang, Zhenyu; Wong, Pak C.; Mackey, Patrick S.; Allwardt, Craig H.; Ma, Jian; Greitzer, Frank L.

    2010-01-31

    Electricity infrastructure, as one of the most critical infrastructures in the U.S., plays an important role in modern societies. Its failure would lead to significant disruption of people’s lives, industry and commercial activities, and result in massive economic losses. Reliable operation of electricity infrastructure is an extremely challenging task because human operators need to consider thousands of possible configurations in near real-time to choose the best option and operate the network effectively. In today’s practice, electricity infrastructure operation is largely based on operators’ experience with very limited real-time decision support, resulting in inadequate management of complex predictions and the inability to anticipate, recognize, and respond to situations caused by human errors, natural disasters, or cyber attacks. Therefore, a systematic approach is needed to manage the complex operational paradigms and choose the best option in a near-real-time manner. This paper proposes an advanced decision support tool for electricity infrastructure operations. The tool has the functions of turning large amount of data into actionable information to help operators monitor power grid status in real time; performing trend analysis to indentify system trend at the regional level or system level to help the operator to foresee and discern emergencies, studying clustering analysis to assist operators to identify the relationships between system configurations and affected assets, and interactively evaluating the alternative remedial actions to aid operators to make effective and timely decisions. This tool can provide significant decision support on electricity infrastructure operations and lead to better reliability in power grids. This paper presents examples with actual electricity infrastructure data to demonstrate the capability of this tool.

  10. [A computer-aided design assessment system for recovery life support technology options].

    PubMed

    Chen, J; Wang, F; Sun, J; Shang, C

    1997-04-01

    A specific computer-aided decision support system was designed and implemented for design computation and decision assessment of environmental control and life support system of manned space station. An advanced multiobjective decision methodology and a hierarchic structure model of assessment index of recovery life support system was developed. The program incorporates a database for each technology option, metabolic design loads associated with crew activity, mission model variables to accommodate evolving mission requirements, and algorithms to produce products criteria in order to provide recommendations relative to candidate technology selection and development. A specific structure was developed for the decision system which consists of a database, a methodology base and a model base as well as their management systems. Moreover, a centre control system with friendly user interface plays a very important role in the man-computer interaction.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. Expectation in perceptual decision making: neural and computational mechanisms.

    PubMed

    Summerfield, Christopher; de Lange, Floris P

    2014-11-01

    Sensory signals are highly structured in both space and time. These structural regularities in visual information allow expectations to form about future stimulation, thereby facilitating decisions about visual features and objects. Here, we discuss how expectation modulates neural signals and behaviour in humans and other primates. We consider how expectations bias visual activity before a stimulus occurs, and how neural signals elicited by expected and unexpected stimuli differ. We discuss how expectations may influence decision signals at the computational level. Finally, we consider the relationship between visual expectation and related concepts, such as attention and adaptation.

  17. 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.

  18. Healthcare Decision Support System for Administration of Chronic Diseases

    PubMed Central

    Woo, Ji-In; Yang, Jung-Gi; Lee, Young-Ho

    2014-01-01

    Objectives A healthcare decision-making support model and rule management system is proposed based on a personalized rule-based intelligent concept, to effectively manage chronic diseases. Methods A Web service was built using a standard message transfer protocol for interoperability of personal health records among healthcare institutions. An intelligent decision service is provided that analyzes data using a service-oriented healthcare rule inference function and machine-learning platform; the rules are extensively compiled by physicians through a developmental user interface that enables knowledge base construction, modification, and integration. Further, screening results are visualized for the self-intuitive understanding of personal health status by patients. Results A recommendation message is output through the Web service by receiving patient information from the hospital information recording system and object attribute values as input factors. The proposed system can verify patient behavior by acting as an intellectualized backbone of chronic diseases management; further, it supports self-management and scheduling of screening. Conclusions Chronic patients can continuously receive active recommendations related to their healthcare through the rule management system, and they can model the system by acting as decision makers in diseases management; secondary diseases can be prevented and health management can be performed by reference to patient-specific lifestyle guidelines. PMID:25152830

  19. Intelligent decision support tool for supply chain planning

    NASA Astrophysics Data System (ADS)

    Li, Dong; Barnes, Cathy; Axtell, C.; McKay, Alison; de Pennington, Alan

    2001-10-01

    A decision support system using extended quality function deployment model (EQFDM) and internet application for manufacturing supply chain (SC) planning has been developed in this research. In this paper, a customer-focused quality evaluation approach, the EQFDM with internet application is employed to develop a coordinated planning system in SCs and assist mapping decisions of strategic planning into each partner's internal planning processes. To facilitate cooperation of SC partners in strategic planning, the hybrid planning process has been programmed into a web tool. The local planning has been supported by fuzzy logic approach so that approximate optimal solutions can be obtained avoiding difficulties of acquiring quantitative data. Through this intelligent Web based architecture, individual planning processes can be efficiently co-ordinated by means of efficient communication and visualizing consequences of a decision to be made on SC performance. Case study in a manufacturing (packaging) SC has been conducted to implement a scenario planning process for strategies on re-engineering the manufacturing SC. The research result shows that the intelligent system could be a promising tool for assisting strategic planning in a SC cooperation context.

  20. 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.

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

    PubMed

    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.

  3. 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

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

    PubMed

    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

  5. 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.

  6. Effects on Decision Quality of Supporting Multi-attribute Evaluation in Groups

    PubMed

    Timmermans; Vlek

    1996-11-01

    In this study the effectiveness of multi-attribute utility (MAU) decision support in groups is evaluated for personnel selection problems differing in complexity. Subjects were asked to make an initial individual decision with or without MAU decision support. Next individuals formed small groups and were asked to reach a decision about the same problem. Groups received either MAU support or no support. Results show that for relatively simple problems the most effective method is to provide subjects with both individual and group decision support. Here, decision support had a clear impact on subjects' preferences and the level of agreement between group members. In addition, satisfaction with the decision and the decision procedure was relatively high. Overall, decision support improved communication; subjects reported to find the problem easier, to have more influence on the group decision, and to find it easier to express their opinions. For more complex problems, however, decision making without group support (whether preceded by individual support or not) was evaluated most favorably. Individual decision support in this condition was sometimes better than no support; i.e., there was a lower reported problem difficulty, a higher satisfaction with the group decision, and a higher reported influence on the group decision. The effectiveness of group MAU decision support for complex problems was evaluated less favorably.

  7. Use of Remote Sensing for Decision Support in Africa

    NASA Technical Reports Server (NTRS)

    Policelli, Frederick S.

    2007-01-01

    Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.

  8. 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. PMID:23920862

  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. Decision support for workload assessment - Introducing WC FIELDE

    NASA Technical Reports Server (NTRS)

    Casper, Patricia A.; Shively, Robert J.; Hart, Sandra G.

    1987-01-01

    Currently there is a great demand for mental workload evaluation in the course of system design and modification. In light of this demand, a microprocessor-based decision support system has been created called WC FIELDE: Workload Consultant for FIELD Evaluation. The system helps the user select workload measures appropriate to his or her application from the large pool of currently available techniques. Both novices and those with some workload experience may benefit from using WC FIELDE, since the system's operation is entirely transparent and all rules involved in the decision process are available for the user to examine. WC FIELDE recommends several assessment methodologies in decreasing order of appropriateness, and provides additional information on each measure at the end of the program in the form of text files.

  11. Decision System Integrating Preferences to Support Sleep Staging.

    PubMed

    Ugon, Adrien; Sedki, Karima; Kotti, Amina; Seroussi, Brigitte; Philippe, Carole; Ganascia, Jean-Gabriel; Garda, Patrick; Bouaud, Jacques; Pinna, Andrea

    2016-01-01

    Scoring sleep stages can be considered as a classification problem. Once the whole recording segmented into 30-seconds epochs, features, extracted from raw signals, are typically injected into machine learning algorithms in order to build a model able to assign a sleep stage, trying to mimic what experts have done on the training set. Such approaches ignore the advances in sleep medicine, in which guidelines have been published by the AASM, providing definitions and rules that should be followed to score sleep stages. In addition, these approaches are not able to solve conflict situations, in which criteria of different sleep stages are met. This work proposes a novel approach based on AASM guidelines. Rules are formalized integrating, for some of them, preferences allowing to support decision in conflict situations. Applied to a doubtful epoch, our approach has taken the appropriate decision. PMID:27577436

  12. Creating shareable decision support services: an interdisciplinary challenge.

    PubMed

    Paterno, Marilyn D; Maviglia, Saverio M; Ramelson, Harley Z; Schaeffer, Molly; Rocha, Beatriz H; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford; Goldberg, Howard S

    2010-01-01

    Creating shareable decision support services is a complex task requiring effort from multiple interdisciplinary role players with a wide variety of experience and expertise. The CDS Consortium research project has developed such a service, defining a multi-layer representation of knowledge and building upon an architectural service design created at Partners Health Care, and is demonstrating its use in both a local and an external institutional setting. The process was iterative, and we encountered unexpected requirements based on decisions made at various points. We report in this paper on challenges we faced while pursuing this research: knowledge representation and modeling, data interchange and standards adoption, the process of getting agreement on content, logistics of integrating into a system that already has multiple CDS interventions, legal issues around privacy and access, inter-team communication and organization.

  13. 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. PMID:26294501

  14. 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

  15. 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.

  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. Interactive decision-making support model in MOSD

    NASA Astrophysics Data System (ADS)

    Liu, Yang; Lan, Ze-ying; Liu, Yao-lin; Qin, Liang-jun

    2009-10-01

    The Multi-objective spatial optimization problem is common in the word, which usually has a set of non-dominated resolutions, also called Pareto resolutions, instead of a single ideal one. So, the Multi-objectives spatial decision support system (MOSDSS) has two vital basements: how to acquire all the Pareto resolutions by Multi-objective optimization arithmetic, and how to analysis and appraise the candidates to determinate the final satisfying solution. At present, there are abundant research fruit for the former problem, however the latter one hasn't attracted abroad attention in the field. Nowadays, the findings about analyzing and evaluating the Pareto resolutions mainly focus on three aspects: the visual expression of candidates, appraising the comparability among the solutions, and designing the prototype system of visual support tools, which are lack of systemic conclusion and summarization. Hence, this paper emphasizes the latter problem of MOSDSS and puts up an interactive decision-making support model to largely improve the efficiency of analyzing and evaluating the Pareto resolutions. This model is composed of 3 pivotal parts: the geographic brush mechanism, the similarity querying operators as well as the interactive searching method. Then, the paper designs a prototype system on the base of the model, which is successfully tested in the exam.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. Database and knowledge base integration in decision support systems.

    PubMed Central

    Johansson, B.; Shahsavar, N.; Ahlfeldt, H.; Wigertz, O.

    1996-01-01

    Since decision support systems (DSS) in medicine often are linked to clinical databases it is important to find methods that facilitate the work for DSS developers to implement database queries in the knowledge base (KB). This paper presents a method for linking clinical databases to a KB with Arden Syntax modules. The method is based on a query meta database including templates for SQL queries. During knowledge module authoring the medical expert only refers to a code in the query meta database. Our method uses standard tools so it can be implemented on different platforms and linked to different clinical databases. PMID:8947666

  4. Knowledge-analytics synergy in Clinical Decision Support.

    PubMed

    Slonim, Noam; Carmeli, Boaz; Goldsteen, Abigail; Keller, Oliver; Kent, Carmel; Rinott, Ruty

    2012-01-01

    Clinical Decision Support (CDS) systems hold tremendous potential for improving patient care. Most existing systems are knowledge-based tools that rely on relatively simple rules. More recent approaches rely on analytics techniques to automatically mine EHR data to reveal meaningful insights. Here, we propose the Knowledge-Analytics Synergy paradigm for CDS, in which we synergistically combine existing relevant knowledge with analytics applied to EHR data. We propose a framework for implementing such a paradigm and demonstrate its principles over real-world clinical and genomic data of hypertensive patients.

  5. 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.

  6. 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

  7. Supporting Coral Reef Ecosystem Management Decisions Appropriate to Climate Change

    NASA Astrophysics Data System (ADS)

    Hendee, J. C.; Fletcher, P.; Shein, K. A.

    2013-05-01

    There has been a perception that the myriad of environmental information products derived from satellite and other instrumental sources means ipso facto that there is a direct use for them by environmental managers. Trouble is, as information providers, for the most part we don't really know what decisions managers face daily, nor is it a trivial matter to ascertain the effect of management decisions on the environment, at least in a time frame that facilitates timely maintenance and enhancement of decision support software. To bridge this gap in understanding, we conducted a Needs Assessment (using methodology from the NOAA/Coastal Services Center's Product Design and Evaluation training program) from December, 2011 through May, 2012, in which we queried 15 resource managers in southeast Florida to identify the types of climate data and information products they needed to understand the effects of climate change in their region of purview, and how best these products should be delivered and subsequently enhanced or corrected. Our intent has been to develop a suite of software and information products customized specifically for environmental managers. This report summarizes our success to date, including a report on the development of software for gathering and presenting specific types of climate data, and a narrative about how some U.S. government sponsored efforts, such as Giovanni and TerraVis, as well as non-governmental sponsored efforts such as Marxan, Zonation, SimCLIM, and other off-the-shelf software might be customized for use in specific regions.

  8. 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

  9. 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.

  10. 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.

  11. Adoption of Clinical Decision Support in Multimorbidity: A Systematic Review

    PubMed Central

    Arguello Casteleiro, Mercedes; Ainsworth, John; Buchan, Iain

    2015-01-01

    Background Patients with multiple conditions have complex needs and are increasing in number as populations age. This multimorbidity is one of the greatest challenges facing health care. Having more than 1 condition generates (1) interactions between pathologies, (2) duplication of tests, (3) difficulties in adhering to often conflicting clinical practice guidelines, (4) obstacles in the continuity of care, (5) confusing self-management information, and (6) medication errors. In this context, clinical decision support (CDS) systems need to be able to handle realistic complexity and minimize iatrogenic risks. Objective The aim of this review was to identify to what extent CDS is adopted in multimorbidity. Methods This review followed PRISMA guidance and adopted a multidisciplinary approach. Scopus and PubMed searches were performed by combining terms from 3 different thesauri containing synonyms for (1) multimorbidity and comorbidity, (2) polypharmacy, and (3) CDS. The relevant articles were identified by examining the titles and abstracts. The full text of selected/relevant articles was analyzed in-depth. For articles appropriate for this review, data were collected on clinical tasks, diseases, decision maker, methods, data input context, user interface considerations, and evaluation of effectiveness. Results A total of 50 articles were selected for the full in-depth analysis and 20 studies were included in the final review. Medication (n=10) and clinical guidance (n=8) were the predominant clinical tasks. Four studies focused on merging concurrent clinical practice guidelines. A total of 17 articles reported their CDS systems were knowledge-based. Most articles reviewed considered patients’ clinical records (n=19), clinical practice guidelines (n=12), and clinicians’ knowledge (n=10) as contextual input data. The most frequent diseases mentioned were cardiovascular (n=9) and diabetes mellitus (n=5). In all, 12 articles mentioned generalist doctor(s) as the

  12. 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.…

  13. 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

  14. Towards a decision support system for hand dermatology.

    PubMed

    Mazzola, Luca; Cavazzina, Alice; Pinciroli, Francesco; Bonacina, Stefano; Pigatto, Paolo; Ayala, Fabio; De Pità, Ornella; Marceglia, Sara

    2014-01-01

    The complexity of the medical diagnosis is faced by practitioners relying mainly on their experiences. This can be acquired during daily practices and on-the-job training. Given the complexity and extensiveness of the subject, supporting tools that include knowledge extracted by highly specialized practitioners can be valuable. In the present work, a Decision Support System (DSS) for hand dermatology was developed based on data coming from a Visit Report Form (VRF). Using a Bayesian approach and factors significance difference over the population average for the case, we demonstrated the potentiality of creating an enhanced VRF that include a diagnoses distribution probability based on the DSS rules applied for the specific patient situation. PMID:25160145

  15. Knowledge-based decision support for patient monitoring in cardioanesthesia.

    PubMed

    Schecke, T; Langen, M; Popp, H J; Rau, G; Käsmacher, H; Kalff, G

    1992-01-01

    An approach to generating 'intelligent alarms' is presented that aggregates many information items, i.e. measured vital signs, recent medications, etc., into state variables that more directly reflect the patient's physiological state. Based on these state variables the described decision support system AES-2 also provides therapy recommendations. The assessment of the state variables and the generation of therapeutic advice follow a knowledge-based approach. Aspects of uncertainty, e.g. a gradual transition between 'normal' and 'below normal', are considered applying a fuzzy set approach. Special emphasis is laid on the ergonomic design of the user interface, which is based on color graphics and finger touch input on the screen. Certain simulation techniques considerably support the design process of AES-2 as is demonstrated with a typical example from cardioanesthesia. PMID:1402299

  16. Towards sustainable decision-support system facilitating EBM.

    PubMed

    Stolba, Nevena; Nguyen, Tho Manh; Tjoa, A Min

    2007-01-01

    Due to the immense volumes of medical data, the architecture of the future healthcare decision support systems focus more on interoperability than on integration. With the raising need for the creation of unified knowledge base, the federated approach to distributed data warehouses (DWH) is getting increasing attention. In this paper, we explore the idea of a federation technology and its uses within the domain of health, particularly in the conceptualization of DWH federation as a sustainable, appropriate and legitimate solution. Further, we present a federated DWH model which enables the interoperability between heterogeneous and distributed medical IS, which includes a sense and response mechanism and facilitates evidence-based medicine in order to primarily support the physicians at the point of care. A real-world scenario illustrates a possible application field in the area of emergency and intensive care.

  17. Decision Support for Integrated Energy-Water Planning

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  18. 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.

  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. Decision support system for predicting color change after tooth whitening.

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values. PMID:26657921

  1. Decision making by urgency gating: theory and experimental support.

    PubMed

    Thura, David; Beauregard-Racine, Julie; Fradet, Charles-William; Cisek, Paul

    2012-12-01

    It is often suggested that decisions are made when accumulated sensory information reaches a fixed accuracy criterion. This is supported by many studies showing a gradual build up of neural activity to a threshold. However, the proposal that this build up is caused by sensory accumulation is challenged by findings that decisions are based on information from a time window much shorter than the build-up process. Here, we propose that in natural conditions where the environment can suddenly change, the policy that maximizes reward rate is to estimate evidence by accumulating only novel information and then compare the result to a decreasing accuracy criterion. We suggest that the brain approximates this policy by multiplying an estimate of sensory evidence with a motor-related urgency signal and that the latter is primarily responsible for neural activity build up. We support this hypothesis using human behavioral data from a modified random-dot motion task in which motion coherence changes during each trial.

  2. Decision support system for predicting color change after tooth whitening.

    PubMed

    Thanathornwong, Bhornsawan; Suebnukarn, Siriwan; Ouivirach, Kan

    2016-03-01

    Tooth whitening is becoming increasingly popular among patients and dentists since it is a relatively noninvasive approach. However, the degree of color change after tooth whitening is known to vary substantially between studies. The present study aims to develop a clinical decision support system for predicting color change after in-office tooth whitening. We used the information from patients' data sets, and applied the multiple regression equation of CIELAB color coordinates including L*, a*, and b* of the original tooth color and the color difference (ΔE) that expresses the color change after tooth whitening. To evaluate the system performance, the patient's post-treatment color was used as "gold standard" to compare with the post-treatment color predicted by the system. There was a high degree of agreement between the patient's post-treatment color and the post-treatment color predicted by the system (kappa value=0.894). The results obtained have demonstrated that the decision support system is possible to predict the color change obtained using an in-office whitening system using colorimetric values.

  3. Ontology-based diagnostic decision support in radiology.

    PubMed

    Kahn, Charles E

    2014-01-01

    The Radiology Gamuts Ontology (RGO) is a knowledge model of diseases, interventions, and imaging manifestations. RGO incorporates 16,822 terms with their synonyms and abbreviations and 55,393 relationships between terms. Subsumption defines the relationship between more general and more specific terms; causality relates disorders and their imaging manifestations. We explored the application of the RGO to build an interactive decision support system for radiological diagnosis. The Gamuts DDx system was created to apply the RGO's knowledge: it identifies a list of potential diagnoses in response to one or more user-specified imaging observations. The system also identifies a set of observations that allow one to narrow the diagnosis, and dynamically narrows or expands the list of diagnoses as imaging findings are selected or deselected. The functionality has been implemented as a web-based user interface and as a web service. The current work demonstrates the feasibility of exploiting the RGO's causal knowledge to provide interactive decision support for diagnosis of imaging findings. Ongoing efforts include the further development of the system's knowledge base and evaluation of the system in clinical use. PMID:25160149

  4. How Turing and Wolf influenced my Decision Support Systems.

    PubMed

    Richards, Bernard

    2013-01-01

    Decision Support Systems (DSS) have a vital role to play in today's scenario for Patient Care. They can embody a vast knowledge not normally found in one individual where diagnosis and treatment are involved. This paper highlights the training in minute details and precise mathematics needed in a successful DSS and indicates how such attention-to-detail was instilled into the writer as a result of working with Alan Turing and Emil Wolf who have both since achieved world-wide recognition in their own fields as a result of international publicity by the current writer. The article discusses four Decision Support Systems written by the present writer all of which have been shown to improve patient treatment and care, and which are of such complexity that, without their use, patient care would fall short of optimum. The Systems considered are those for Intensive Care Units, Cardiovascular Surgery, a Programmed Investigation Unit, and Diagnosis of Congenital Abnormalities. All these Systems have performed better than the human alternatives and have shown their value in the improvement of patient care.

  5. Ontology-based diagnostic decision support in radiology.

    PubMed

    Kahn, Charles E

    2014-01-01

    The Radiology Gamuts Ontology (RGO) is a knowledge model of diseases, interventions, and imaging manifestations. RGO incorporates 16,822 terms with their synonyms and abbreviations and 55,393 relationships between terms. Subsumption defines the relationship between more general and more specific terms; causality relates disorders and their imaging manifestations. We explored the application of the RGO to build an interactive decision support system for radiological diagnosis. The Gamuts DDx system was created to apply the RGO's knowledge: it identifies a list of potential diagnoses in response to one or more user-specified imaging observations. The system also identifies a set of observations that allow one to narrow the diagnosis, and dynamically narrows or expands the list of diagnoses as imaging findings are selected or deselected. The functionality has been implemented as a web-based user interface and as a web service. The current work demonstrates the feasibility of exploiting the RGO's causal knowledge to provide interactive decision support for diagnosis of imaging findings. Ongoing efforts include the further development of the system's knowledge base and evaluation of the system in clinical use.

  6. How Turing and Wolf influenced my Decision Support Systems.

    PubMed

    Richards, Bernard

    2013-01-01

    Decision Support Systems (DSS) have a vital role to play in today's scenario for Patient Care. They can embody a vast knowledge not normally found in one individual where diagnosis and treatment are involved. This paper highlights the training in minute details and precise mathematics needed in a successful DSS and indicates how such attention-to-detail was instilled into the writer as a result of working with Alan Turing and Emil Wolf who have both since achieved world-wide recognition in their own fields as a result of international publicity by the current writer. The article discusses four Decision Support Systems written by the present writer all of which have been shown to improve patient treatment and care, and which are of such complexity that, without their use, patient care would fall short of optimum. The Systems considered are those for Intensive Care Units, Cardiovascular Surgery, a Programmed Investigation Unit, and Diagnosis of Congenital Abnormalities. All these Systems have performed better than the human alternatives and have shown their value in the improvement of patient care. PMID:23542962

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

    PubMed Central

    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. PMID:25717336

  8. 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

  9. Adoption and sustainability of decision support for patients facing health decisions: an implementation case study in nursing

    PubMed Central

    Stacey, Dawn; Pomey, Marie-Pascale; O'Connor, Annette M; Graham, Ian D

    2006-01-01

    Background Effective interventions prepare patients for making values-sensitive health decisions by helping them become informed and clarifying their values for each of the options. However, patient decision support interventions have not been widely implemented and little is known about effective models for delivering them to patients. The purpose of this study was to describe call centre nurses' adoption of a decision support protocol into practice following exposure to an implementation intervention and to identify factors influencing sustainable nursing practice changes. Methods Exploratory case study at a Canadian province-wide call centre guided by the Ottawa Model of Research Use. Data sources included a survey of nurses who participated in an implementation intervention (n = 31), 2 focus groups with nurses, interviews with 4 administrators, and a document review. Results Twenty-five of 31 nurses responded to the survey measuring adoption of decision support in practice. Of the 25 nurses, 11 had used the decision support protocol in their practice within one month of the intervention. Twenty-two of the 25 intended to use it within the next three months. Although some nurses found it challenging to begin using the protocol, most nurses reported that it: a) helped them recognize callers needing decision support; b) changed their approach to handling these calls; and c) was a positive enhancement to their practice. Strategies identified to promote sustainability of practice changes included integration of the decision support protocol in the call centre database, streamlining the patient decision aids for easier use via telephone, clarifying the administrative direction for the call centre's program, creating a call length guideline specific for these calls, incorporating decision support training in the staff development plan, and informing the public of this enhanced service. Conclusion Although most nurses adopted the decision support protocol for coaching

  10. Decision framework for technology choice. Volume 2: decision analysis user's manual. [TCM computer code

    SciTech Connect

    Sicherman, A.; Keeney, R.L.

    1982-03-01

    A computer program was developed to aid decision makers in choosing among alternatives. It facilitiates the implementation of the decision analysis approach to multiobjective decision-making problems. The program's main functions are to store the information and perform all the necessary computations required by the approach. The program is designed so that only a few basic commands need to be understood in order to use it effectively. The style of input can be both batch and interactively oriented. Detailed specification of preferences and alternatives is usually done in batch mode while sensitivity analysis can be performed interactively. The output consists of ranking, preference and alternative information displays. The program is quite general and should be applicable to a wide variety of problems. The code allows for an interface to user supplied models when that is desirable. It is designed to run on most computer systems without or with very minor system-specific modifications. This report presents a user's manual for the program that includes a simple illustrative example.

  11. 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

  12. 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.

  13. 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.

  14. Decision Support: The Keys to Success. AIR 1986 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Oerly, Diane

    Characteristics of a decision support system (DSS) and factors that influence system design are described, along with a decision support database at the University of Missouri-Columbia. Reasons that the institutional research office is in a unique position to support decision-making are identified. A review of the literature of DSS briefly covers…

  15. 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.

  16. Embodied cognition of movement decisions: a computational modeling approach.

    PubMed

    Johnson, Joseph G

    2009-01-01

    This chapter presents a cognitive computational view of decision making as the search for, and accumulation of, evidence for options under consideration. It is based on existing models that have been successful in traditional decision tasks involving preferential choice. The model assumes shifting attention over time that determines momentary inputs to an evolving preference state. In this chapter, the cognitive model is extended to illustrate how links from the motor system may be incorporated. These links can basically be categorized into one of three influences: modifying the subjective evaluation of choice options, restricting attention, and altering the options that are to be found in the choice set. The implications for the formal model are introduced and preliminary evidence is drawn from the extant literature.

  17. 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.

  18. Neural coding of computational factors affecting decision making.

    PubMed

    Dreher, Jean-Claude

    2013-01-01

    We constantly need to make decisions that can result in rewards of different amounts with different probabilities and at different timing. To characterize the neural coding of such computational factors affecting value-based decision making, we have investigated how reward information processing is influenced by parameters such as reward magnitude, probability, delay, effort, and uncertainty using either fMRI in healthy humans or intracranial recordings in patients with epilepsy. We decomposed brain signals modulated by these computational factors, showing that prediction error (PE), salient PE, and uncertainty signals are computed in partially overlapping brain circuits and that both transient and sustained uncertainty signals coexist in the brain. When investigating the neural representation of primary and secondary rewards, we found both a common brain network, including the ventromedial prefrontal cortex and ventral striatum, and a functional organization of the orbitofrontal cortex according to reward type. Moreover, separate valuation systems were engaged for delay and effort costs when deciding between options. Finally, genetic variations in dopamine-related genes influenced the response of the reward system and may contribute to individual differences in reward-seeking behavior and in predisposition to neuropsychiatric disorders.

  19. 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.

  20. 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.

  1. 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.

  2. Query-handling in MLM-based decision support systems.

    PubMed

    Arkad, K; Gao, X M; Ahlfeldt, H

    1995-01-01

    Arden Syntax for Medical Logic Modules is a standard specification for creation and sharing of knowledge bases. The standard specification focuses on knowledge that can be represented as a set of independent Medical Logic Modules (MLMs) such as rules, formulas and protocols. The basic functions of an MLM are to retrieve patient data, manipulate the data, come to some decision, and possibly perform an action. All connections to the world outside an MLM are collected in the data-slot of the MLM. The institution specific parts of these connections are inside the notation of curly brackets ([]) to facilitate sharing of MLM between institutions. This paper focuses on some of the problems that occur in relation to Arden Syntax and connections to a patient database such as database queries. Problems related to possibilities of moving one or several module(s) are also discussed, with emphasis on database connections. As an example, an MLM based Decision Support System (DSS) developed at Linköping University is described. PMID:8882561

  3. Seasonal Stream Flow Forecasting and Decision Support in Central Texas

    NASA Astrophysics Data System (ADS)

    Watkins, D. W.; Nykanen, D. K.; Mahmoud, M.; Wei, W.

    2003-12-01

    A decision support model based on stream flow ensemble forecasts has been developed for the Lower Colorado River Authority in Central Texas, and predictive skill is added to climatology-based forecasts by conditioning the ensembles on observable climate indicators. These indicators include stream flow (persistence), soil moisture, and large-scale recurrent patterns such as the El Nino-Southern Oscillation, Pacific Decadal Oscillation, and the North Atlantic Oscillation. In the absence of historical soil moisture measurements, the Variable Infiltration Capacity (VIC) Retrospective Land Surface Data Set is applied. Strong correlation between observed runoff volumes and runoff volumes simulated by the (uncalibrated) VIC model indicates the viability of this approach. Following correlation analysis to screen potential predictors, a Bayesian procedure for updating ensemble probabilities is outlined, and various skill scores are reviewed for evaluating forecast performance. Verification of the ensemble forecasts using a resampling procedure indicates a small but potentially significant improvement in forecast skill over climatology that could be exploited in seasonal water management decisions. Future work involves evaluation of seasonal soil moisture forecasts, further evaluation of annual flow forecasts, incorporation of climate forecasts in reservoir operating rules, and estimation of the value of the forecasts.

  4. 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.

  5. 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.

  6. Spatio-temporal Visualization for Environmental Decision Support

    SciTech Connect

    Bhaduri, Budhendra L.; Shankar, Mallikarjun; Sorokine, Alexandre; Ganguly, Auroop R.

    2009-01-01

    Traditional visualization of earth surface features has been addressed through visual exploration, analysis, synthesis, and presentation of observable geospatial data. However, characterizing the changes in their observable and unobservable properties of geospatial features is critical for planning and policy formulation. Recent approaches are addressing modeling and visualization of the temporal dynamics that describe observed and/or predicted physical and socioeconomic processes using vast volumes of earth observation (imagery and other geophysical) data from remote sensor networks. This paper provides an overview of selected geospatial modeling and simulation, exploratory analysis of earth observation data, and high performance visualization research at Oak Ridge National Laboratory for developing novel data driven approaches for geospatial knowledge discovery and visualization relevant to environmental decision support.

  7. 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.

  8. A Framework for Decision Support Systems Based on Zachman Framework

    NASA Astrophysics Data System (ADS)

    Ostadzadeh, S. Shervin; Habibi, Jafar; Ostadzadeh, S. Arash

    Recent challenges have brought about an inevitable tendency for enterprises to lunge towards organizing their information activities in a comprehensive way. In this respect, Enterprise Architecture (EA) has proven to be the leading option for development and maintenance of information systems. EA clearly provides a thorough outline of the whole information system comprising an enterprise. To establish such an outline, a logical framework needs to be laid upon the entire information system. Zachman framework (ZF) has been widely accepted as a standard scheme for identifying and organizing descriptive representations that have critical roles in enterprise management and system development. In this paper, we propose a framework based on ZF for Decision Support Systems (DSS). Furthermore, a modeling approach based on Model-Driven Architecture (MDA) is utilized to obtain compatible models for all cells in the framework. The efficiency of the proposed framework is examined through a case study.

  9. 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. PMID:25385815

  10. Clinical Decision Support Knowledge Management: Strategies for Success.

    PubMed

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

  11. 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

  12. Clinical Decision Support for Colon and Rectal Surgery: An Overview

    PubMed Central

    McCoy, Allison B.; Melton, Genevieve B.; Wright, Adam; Sittig, Dean F.

    2013-01-01

    Clinical decision support (CDS) has been shown to improve clinical processes, promote patient safety, and reduce costs in healthcare settings, and it is now a requirement for clinicians as part of the Meaningful Use Regulation. However, most evidence for CDS has been evaluated primarily in internal medicine care settings, and colon and rectal surgery (CRS) has unique needs with CDS that are not frequently described in the literature. The authors reviewed published literature in informatics and medical journals, combined with expert opinion to define CDS, describe the evidence for CDS, outline the implementation process for CDS, and present applications of CDS in CRS.CDS functionalities such as order sets, documentation templates, and order facilitation aids are most often described in the literature and most likely to be beneficial in CRS. Further research is necessary to identify and better evaluate additional CDS systems in the setting of CRS. PMID:24436644

  13. Clinical Decision Support Knowledge Management: Strategies for Success.

    PubMed

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital. PMID:26152955

  14. Examining the Relationship between Clinical Decision Support and Performance Measurement

    PubMed Central

    Haggstrom, David A.; Saleem, Jason J.; Militello, Laura G.; Arbuckle, Nicole; Flanagan, Mindy; Doebbeling, Bradley N.

    2009-01-01

    In concept and practice, clinical decision support (CDS) and performance measurement represent distinct approaches to organizational change, yet these two organizational processes are interrelated. We set out to better understand how the relationship between the two is perceived, as well as how they jointly influence clinical practice. To understand the use of CDS at benchmark institutions, we conducted semistructured interviews with key managers, information technology personnel, and clinical leaders during a qualitative field study. Improved performance was frequently cited as a rationale for the use of clinical reminders. Pay-for-performance efforts also appeared to provide motivation for the use of clinical reminders. Shared performance measures were associated with shared clinical reminders. The close link between clinical reminders and performance measurement causes these tools to have many of the same implementation challenges. PMID:20351854

  15. 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.

  16. The role of informatics and decision support in utilization management.

    PubMed

    Baron, Jason M; Dighe, Anand S

    2014-01-01

    Information systems provide a critical link between clinical laboratories and the clinicians and patients they serve. Strategic deployment of informatics resources can enable a wide array of utilization initiatives and can substantially improve the appropriateness of test selection and results interpretation. In this article, we review information systems including computerized provider order entry (CPOE) systems, laboratory information systems (LISs), electronic health records (EHRs), laboratory middleware, knowledge management systems and systems for data extraction and analysis, and describe the role that each can play in utilization management. We also discuss specific utilization strategies that laboratories can employ within these systems, citing examples both from our own institution and from the literature. Finally, we review how emerging applications of decision support technologies may help to further refine test utilization, "personalize" laboratory diagnosis, and enhance the diagnostic value of laboratory testing.

  17. Decision support systems and methods for complex networks

    DOEpatents

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

    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.

  18. Patterns of use of decision support tools by clinicians.

    PubMed

    Hayward, Robert S; El-Hajj, Mohamad; Voth, Tanya K; Deis, Kelly

    2006-01-01

    This paper analyses information behavior data automatically gathered by an integrated clinical information environment used by internal medicine physicians and trainees at the University of Alberta. The study reviews how clinical information systems, decision-support tools and evidence resources were used over a 13 month period. Aggregate and application-specific frequency and duration of use was compared for location, time of day, physician status, and application-type (clinical information system or 5 categories of knowledge resources). Significant differences are observed for when and where resources were used, diurnal patterns of use, minutes spent per encounter, and patterns of use for physicians and trainees. We find that evidence use is not restricted to either the place or time of clinical work, resources are used for very short periods at the point-of-care, and that use of filtered evidence-based resources is concentrated among trainees.

  19. 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. PMID:24111230

  20. 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.

  1. 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.

  2. SERVIR: A Regional Monitoring and Decision Support System for Mesoamerica

    NASA Astrophysics Data System (ADS)

    Irwin, D.; Hardin, D. M.; Sever, T.; Graves, S.

    2008-05-01

    Mesoamerica is a prime example of a multi-national region with natural and human induced stresses that benefits from information provided by observation systems. The region is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability of its population to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, the University of Alabama in Huntsville and numerous SERVIR* partners are developing data products, knowledge extraction methods and decision support tools for environmental monitoring, disaster response and sustainable growth planning in Mesoamerica. The combination of space- based observations from NASA's Earth Observing Satellites with information management and knowledge extraction technologies has yielded a robust system for use by scientists, educators, environmental ministers and policy makers. These resources enhance the ability to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. Now in its fourth year SERVIR has become a partner in the International Space and Major Disasters Charter. In the past year the Charter provided commercial satellite imagery to aid in disaster response to Hurricanes Dean, Felix and Noel. Overcoming roadblocks to coordination and data sharing between countries, organizations and disciplines SERVIR is providing environmental monitoring and decision support products and applications that directly map to several Observation GEOSS societal benefit areas. This paper provides an overview of the ongoing accomplishments of the SERVIR project. *SERVIR is a Spanish verb meaning "to serve" or "be useful" is also an acronym for the Spanish name of the capability: Sistema Regional de Visualizacion y Monitero.

  3. 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

    2012-01-01

    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

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. A critical assessment of supported decision-making for persons aging with intellectual disabilities.

    PubMed

    Kohn, Nina A; Blumenthal, Jeremy A

    2014-01-01

    Supported decision-making is increasingly being promoted as an alternative to guardianship for persons aging with intellectual disabilities. Proponents argue that supported decision-making, unlike guardianship, empowers persons with disabilities by providing them with help in making their own decisions, rather than simply providing someone else to make decisions for them. To evaluate the empirical support for these claims, we reviewed the evidence base on supported decision-making. Our review found little such empirical research, suggesting that significant further research is warranted to determine whether--and under what conditions--supported decision-making can benefit persons with intellectual disabilities. Indeed, without more empirical evidence as to how supported decision-making functions in practice, it is too early to rule out the possibility it may actually disempower individuals with disabilities by facilitating undue influence by their alleged supporters. We therefore suggest several key areas for future research.

  10. 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

  11. 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.

  12. Computer networks: making the decision to join one.

    PubMed

    Massy, W F

    1974-11-01

    too thinly. In other words, he can solve the problem of simultaneously improving the breadth of service and increasing operating efficiency. 4) Involvement in distributive networking will raise a new kind of question for the senior officers of colleges and universities. This is the decision concerning the development of computer services for export to users at other institutions. The effect on the university's own academic program (in the sense of its becoming a "center of excellence" in a particular computerrelated discipline), the risks involved in trying to attract outside users on the network, and the consequent responsibility for providing continuity of service at the peril of suffering in national academic reputation will be key considerations. The worth of, and probably the demand for, such services will be a function of the excellence of the development work, and this in turn will depend on its involvement with the university's academic resources. The "computer services export" question is fundamentally academic, as are decisions on the expansion or contraction of teaching and research programs, and it must be dealt with in the same terms. The next few years will be crucial ones for colleges and universities generally, and for their computing resources in particular. The advent of computer networking raises a host of academic, economic, technological, and organizational problems. In spite of these problems, I believe that distributive networking will have a significant and positive effect on campus computing services. PMID:17737119

  13. 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

  14. Continuous-Variable Quantum Computation of Oracle Decision Problems

    NASA Astrophysics Data System (ADS)

    Adcock, Mark R. A.

    Quantum information processing is appealing due its ability to solve certain problems quantitatively faster than classical information processing. Most quantum algorithms have been studied in discretely parameterized systems, but many quantum systems are continuously parameterized. The field of quantum optics in particular has sophisticated techniques for manipulating continuously parameterized quantum states of light, but the lack of a code-state formalism has hindered the study of quantum algorithms in these systems. To address this situation, a code-state formalism for the solution of oracle decision problems in continuously-parameterized quantum systems is developed. Quantum information processing is appealing due its ability to solve certain problems quantitatively faster than classical information processing. Most quantum algorithms have been studied in discretely parameterized systems, but many quantum systems are continuously parameterized. The field of quantum optics in particular has sophisticated techniques for manipulating continuously parameterized quantum states of light, but the lack of a code-state formalism has hindered the study of quantum algorithms in these systems. To address this situation, a code-state formalism for the solution of oracle decision problems in continuously-parameterized quantum systems is developed. In the infinite-dimensional case, we study continuous-variable quantum algorithms for the solution of the Deutsch--Jozsa oracle decision problem implemented within a single harmonic-oscillator. Orthogonal states are used as the computational bases, and we show that, contrary to a previous claim in the literature, this implementation of quantum information processing has limitations due to a position-momentum trade-off of the Fourier transform. We further demonstrate that orthogonal encoding bases are not unique, and using the coherent states of the harmonic oscillator as the computational bases, our formalism enables quantifying

  15. 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.

  16. Decision support system for managing oil spill events.

    PubMed

    Keramitsoglou, Iphigenia; Cartalis, Constantinos; Kassomenos, Pavlos

    2003-08-01

    The Mediterranean environment is exposed to various hazards, including oil spills, forest fires, and floods, making the development of a decision support system (DSS) for emergency management an objective of utmost importance. The present work presents a complete DSS for managing marine pollution events caused by oil spills. The system provides all the necessary tools for early detection of oil-spills from satellite images, monitoring of their evolution, estimation of the accident consequences and provision of support to responsible Public Authorities during clean-up operations. The heart of the system is an image processing-geographic information system and other assistant individual software tools that perform oil spill evolution simulation and all other necessary numerical calculations as well as cartographic and reporting tasks related to a specific management of the oil spill event. The cartographic information is derived from the extant general maps representing detailed information concerning several regional environmental and land-cover characteristics as well as financial activities of the application area. Early notification of the authorities with up-to-date accurate information on the position and evolution of the oil spill, combined with the detailed coastal maps, is of paramount importance for emergency assessment and effective clean-up operations that would prevent environmental hazard. An application was developed for the Region of Crete, an area particularly vulnerable to oil spills due to its location, ecological characteristics, and local economic activities.

  17. 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

  18. Towards public health decision support: a systematic review of bidirectional communication approaches

    PubMed Central

    Dixon, Brian E; Gamache, Roland E; Grannis, Shaun J

    2013-01-01

    Objective To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health. Materials and Methods A systematic review of English articles using MEDLINE and Google Scholar. Search terms included public health, epidemiology, electronic health records, decision support, expert systems, and decision-making. Only articles that described the communication of information regarding emerging health threats from public health agencies to clinicians or provider organizations were included. Each article was independently reviewed by two authors. Results Ten peer-reviewed articles highlight a nascent but promising area of research and practice related to alerting clinicians about emerging threats. Current literature suggests that additional research and development in bidirectional communication infrastructure should focus on defining a coherent architecture, improving interoperability, establishing clear governance, and creating usable systems that will effectively deliver targeted, specific information to clinicians in support of patient and population decision-making. Conclusions Increasingly available clinical information systems make it possible to deliver timely, relevant knowledge to frontline clinicians in support of population health. Future work should focus on developing a flexible, interoperable infrastructure for bidirectional communications capable of integrating public health knowledge into clinical systems and workflows. PMID:23467470

  19. 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

  20. 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…

  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. 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.

  3. 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.

  4. Information Systems to Support a Decision Process at Stanford.

    ERIC Educational Resources Information Center

    Chaffee, Ellen Earle

    1982-01-01

    When a rational decision process is desired, information specialists can contribute information and also contribute to the process in which that information is used, thereby promoting rational decision-making. The contribution of Stanford's information specialists to rational decision-making is described. (MLW)

  5. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    PubMed

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary. PMID:27350467

  6. Mobile Clinical Decision Support Systems in Our Hands - Great Potential but also a Concern.

    PubMed

    Masic, Izet; Begic, Edin

    2016-01-01

    Due to the powerful computer resources as well as the availability of today's mobile devices, a special field of mobile systems for clinical decision support in medicine has been developed. The benefits of these applications (systems) are: availability of necessary hardware (mobile phones, tablets and phablets are widespread, and can be purchased at a relatively affordable price), availability of mobile applications (free or for a "small" amount of money) and also mobile applications are tailored for easy use and save time of clinicians in their daily work. In these systems lies a huge potential, and certainly a great economic benefit, so this issue must be approached multidisciplinary.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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

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

    PubMed

    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

  13. 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

  14. Patient electronic health data-driven approach to clinical decision support.

    PubMed

    Mane, Ketan K; Bizon, Chris; Owen, Phillips; Gersing, Ken; Mostafa, Javed; Schmitt, Charles

    2011-10-01

    This article presents a novel visual analytics (VA)-based clinical decision support (CDS) tool prototype that was designed as a collaborative work between Renaissance Computing Institute and Duke University. Using Major Depressive Disorder data from MindLinc electronic health record system at Duke, the CDS tool shows an approach to leverage data from comparative population (patients with similar medical profile) to enhance a clinicians' decision making process at the point of care. The initial work is being extended in collaboration with the University of North Carolina CTSA to address the key challenges of CDS, as well as to show the use of VA to derive insight from large volumes of Electronic Health Record patient data.

  15. 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.

  16. 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.

  17. 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.

  18. Decentralizing Data through Decision-Support Systems: The Impact of Increased Access to Data on Decision Making

    ERIC Educational Resources Information Center

    Petrides, Lisa A.; McClelland, Sara I.

    2007-01-01

    This study examines the impact of a new Decision-Support System (DSS) on decision making in a community college in California. It looks at how attitudes and behaviors about data and their use were impacted by the implementation of a new DSS. The study found that the decentralization of data, through the DSS, produced a shift in terms of an…

  19. Demonstration of optical computing logics based on binary decision diagram.

    PubMed

    Lin, Shiyun; Ishikawa, Yasuhiko; Wada, Kazumi

    2012-01-16

    Optical circuits are low power consumption and fast speed alternatives for the current information processing based on transistor circuits. However, because of no transistor function available in optics, the architecture for optical computing should be chosen that optics prefers. One of which is Binary Decision Diagram (BDD), where signal is processed by sending an optical signal from the root through a serial of switching nodes to the leaf (terminal). Speed of optical computing is limited by either transmission time of optical signals from the root to the leaf or switching time of a node. We have designed and experimentally demonstrated 1-bit and 2-bit adders based on the BDD architecture. The switching nodes are silicon ring resonators with a modulation depth of 10 dB and the states are changed by the plasma dispersion effect. The quality, Q of the rings designed is 1500, which allows fast transmission of signal, e.g., 1.3 ps calculated by a photon escaping time. A total processing time is thus analyzed to be ~9 ps for a 2-bit adder and would scales linearly with the number of bit. It is two orders of magnitude faster than the conventional CMOS circuitry, ~ns scale of delay. The presented results show the potential of fast speed optical computing circuits.

  20. 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

  1. Optimizing Decision Support for Tailored Health Behavior Change Applications.

    PubMed

    Kukafka, Rita; Jeong, In cheol; Finkelstein, Joseph

    2015-01-01

    The Tailored Lifestyle Change Decision Aid (TLC DA) system was designed to provide support for a person to make an informed choice about which behavior change to work on when multiple unhealthy behaviors are present. TLC DA can be delivered via web, smartphones and tablets. The system collects a significant amount of information that is used to generate tailored messages to consumers to persuade them in certain healthy lifestyles. One limitation is the necessity to collect vast amounts of information from users who manually enter. By identifying an optimal set of self-reported parameters we will be able to minimize the data entry burden of the app users. The study was to identify primary determinants of health behavior choices made by patients after using the system. Using discriminant analysis an optimal set of predictors was identified. The resulting set included smoking status, smoking cessation success estimate, self-efficacy, body mass index and diet status. Predicting smoking cessation choice was the most accurate, followed by weight management. Physical activity and diet choices were better identified in a combined cluster. PMID:26262020

  2. 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.

  3. Automation, decision support, and expert systems in nephrology.

    PubMed

    Soman, Sandeep; Zasuwa, Gerard; Yee, Jerry

    2008-01-01

    Increasing data suggest that errors in medicine occur frequently and result in substantial harm to the patient. The Institute of Medicine report described the magnitude of the problem, and public interest in this issue, which was already large, has grown. The traditional approach in medicine has been to identify the persons making the errors and recommend corrective strategies. However, it has become increasingly clear that it is more productive to focus on the systems and processes through which care is provided. If these systems are set up in ways that would both make errors less likely and identify those that do occur and, at the same time, improve efficiency, then safety and productivity would be substantially improved. Clinical decision support systems (CDSSs) are active knowledge systems that use 2 or more items of patient data to generate case specific recommendations. CDSSs are typically designed to integrate a medical knowledge base, patient data, and an inference engine to generate case specific advice. This article describes how automation, templating, and CDSS improve efficiency, patient care, and safety by reducing the frequency and consequences of medical errors in nephrology. We discuss practical applications of these in 3 settings: a computerized anemia-management program (CAMP, Henry Ford Health System, Detroit, MI), vascular access surveillance systems, and monthly capitation notes in the hemodialysis unit.

  4. Effectively marketing prepaid medical care with decision support systems.

    PubMed

    Forgionne, G A

    1991-01-01

    The paper reports a decision support system (DSS) that enables health plan administrators to quickly and easily: (1) manage relevant medical care market (consumer preference and competitors' program) information and (2) convert the information into appropriate medical care delivery and/or payment policies. As the paper demonstrates, the DSS enables providers to design cost efficient and market effective medical care programs. The DSS provides knowledge about subscriber preferences, customer desires, and the program offerings of the competition. It then helps administrators structure a medical care plan in a way that best meets consumer needs in view of the competition. This market effective plan has the potential to generate substantial amounts of additional revenue for the program. Since the system's data base consists mainly of the provider's records, routine transactions, and other readily available documents, the DSS can be implemented at a nominal incremental cost. The paper also evaluates the impact of the information system on the general financial performance of existing dental and mental health plans. In addition, the paper examines how the system can help contain the cost of providing medical care while providing better services to more potential beneficiaries than current approaches.

  5. Computerized decision support systems: improving patient safety in nephrology

    PubMed Central

    Chang, Jamison; Ronco, Claudio; Rosner, Mitchell H.

    2016-01-01

    Incorrect prescription and administration of medications account for a substantial proportion of medical errors in the USA, causing adverse drug events (ADEs) that result in considerable patient morbidity and enormous costs to the health-care system. Patients with chronic kidney disease or acute kidney injury often have impaired drug clearance as well as polypharmacy, and are therefore at increased risk of experiencing ADEs. Studies have demonstrated that recognition of these conditions is not uniform among treating physicians, and prescribed drug doses are often incorrect. Early interventions that ensure appropriate drug dosing in this group of patients have shown encouraging results. Both computerized physician order entry and clinical decision support systems have been shown to reduce the rate of ADEs. Nevertheless, these systems have been implemented at surprisingly few institutions. Economic stimulus and health-care reform legislation present a rare opportunity to refine these systems and understand how they could be implemented more widely. Failure to explore this technology could mean that the opportunity to reduce the morbidity associated with ADEs is missed. PMID:21502973

  6. Why decision support systems are important for medical education.

    PubMed

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

    During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified.

  7. 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

  8. 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.

  9. Why decision support systems are important for medical education.

    PubMed

    Konstantinidis, Stathis Th; Bamidis, Panagiotis D

    2016-03-01

    During the last decades, the inclusion of digital tools in health education has rapidly lead to a continuously enlarging digital era. All the online interactions between learners and tutors, the description, creation, reuse and sharing of educational digital resources and the interlinkage between them in conjunction with cheap storage technology has led to an enormous amount of educational data. Medical education is a unique type of education due to accuracy of information needed, continuous changing competences required and alternative methods of education used. Nowadays medical education standards provide the ground for organising the educational data and the paradata. Analysis of such education data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research. To the best of our knowledge, there is a gap and a clear need for identifying the challenges for DSSs in medical education in the era of medical education standards. Thus, in this Letter the role and the attributes of such a DSS for medical education are delineated and the challenges and vision for future actions are identified. PMID:27222734

  10. 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.

  11. 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…

  12. 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.

  13. 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

  14. Computational Psychometrics in Communication and Implications in Decision Making.

    PubMed

    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

  15. Computational Psychometrics in Communication and Implications in Decision Making.

    PubMed

    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.

  16. Context as Support for Learning Computer Organization

    ERIC Educational Resources Information Center

    Tew, Allison Elliott; Dorn, Brian; Leahy, William D., Jr.; Guzdial, Mark

    2008-01-01

    The ubiquity of personal computational devices in the lives of today's students presents a meaningful context for courses in computer organization beyond the general-purpose or imaginary processors routinely used. This article presents results of a comparative study examining student performance in a conventional organization course and in one…

  17. 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.

  18. 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.

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

    PubMed Central

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

    2014-01-01

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

  20. 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.

  1. 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

  2. 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...

  3. Computer-Supported Individualized Testing Within Reach

    ERIC Educational Resources Information Center

    Calhoun, W. Ford; Frary, Robert B.

    1978-01-01

    A report on the development, implementation, and evaluation of an inexpensive support system providing for file maintenance, administration and scoring of tests, and feedback to the instructor. (Author)

  4. Utilizing Ecosystem Information to Improve Decision Support Systems for Marine Fisheries (Invited)

    NASA Astrophysics Data System (ADS)

    Chavez, F.; Chai, F.; Chao, Y.; Wells, B.; Safari Team

    2010-12-01

    Successful ecological forecasting of fishery yields has eluded resource managers for decades. However, recent advances in observing systems, computational power and understanding of ecosystem function offer credible evidence that the variability of the ocean ecosystem and its impact on fishery yield can be forecast accurately enough and with enough lead time to be useful to society. Advances in space-based real time sensors, high performance computing, very high-resolution physical models, and robust ecosystem theory make possible operational forecasts of both fish availability and ecosystem health. Accurate and timely forecasts can provide the information needed to maintain the long-term sustainability of fish stocks and protect the ecosystem of which the fish are an integral part, while maximizing social and economic benefits and preventing wasteful overinvestment of economic resources. Here we review progress in improving the decision support systems by forecasting two marine fisheries: 1) the coastal Peru small pelagic fishery and 2) the central California salmon fishery.

  5. A decision support system for the operational planning of solid waste collection.

    PubMed

    de Oliveira Simonetto, Eugênio; Borenstein, Denis

    2007-01-01

    This study presents the conception, modeling, and implementation of a decision support system applied to the operational planning of solid waste collection systems, called SCOLDSS. The main functionality of the system is the generation of alternatives to the decision processes concerning: (a) the allocation of separate collection vehicles, as well as the determination of their routes and (b) the determination of the daily amount of solid waste to be sent to each sorting unit, in order to avoid waste of labor force and to reduce the amount of waste sent to the landfills. To develop the computer system, a combination of quantitative techniques was used, such as: simulation of discrete events and algorithms/heuristics for vehicle allocation and routing. The system was developed using the Borland Delphi environment and the commercial software Arena to carry out the simulations. We also present a computational study with real-life data from the solid waste collection in Porto Alegre, Brazil, in which we show that the results provided by the computational system outperform the operation planning currently adopted. PMID:17005387

  6. 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.

  7. 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.

  8. Decision support system for monitoring environmental-human interactions.

    PubMed

    Delavari-Edalat, Farideh; Abdi, M Reza

    2009-06-01

    The specific aim of this study is to investigate popular attitudes toward trees. The paper is involved the understanding of biophilia tendencies with respect to people's views in an urban area. Biophilia is considered as the idea insisting on the dependency of human identity on his relationship with nature. The biophilia fundamental tendencies were explored to establish a biological framework for valuing and affiliating the natural world. Accordingly, the nine tendencies i.e. utilitarian, naturalistic, ecologistic-scientific, aesthetic, symbolic, humanistic, moralistic, dominionistic, and negativistic were investigate to find out how people relate to the nature especially trees. The investigation was based on a quantitative interview which was applied to the public population in the Liverpool urban parks. Data collected from the designed questionnaire was followed by analysis of the data to identify people's attitudes towards trees. The results indicated how important the physical appeal and beauty of trees was for the people and also showed the people's emotional attachments to trees. Furthermore, a decision support model was proposed to evaluate human instincts and preferences in relation to their surrounding areas using the Analytical Hierarchical Process (AHP). The proposed model composed the environmental factors and the biophilia tendencies as the criteria of evaluating environmental-human interactions. A case study was then conducted in Liverpool parks to examine theses interactions. The data gathered was used as the input to the AHP model for the attribute analysis. The AHP model would enable environment managers to compose the relevant information via a link between human feelings about urban trees, and environmental factors for monitoring purposes and performance analysis.

  9. 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

  10. MAROS: a decision support system for optimizing monitoring plans.

    PubMed

    Aziz, Julia J; Ling, Meng; Rifai, Hanadi S; Newell, Charles J; Gonzales, James R

    2003-01-01

    The Monitoring and Remediation Optimization System (MAROS), a decision-support software, was developed to assist in formulating cost-effective ground water long-term monitoring plans. MAROS optimizes an existing ground water monitoring program using both temporal and spatial data analyses to determine the general monitoring system category and the locations and frequency of sampling for future compliance monitoring at the site. The objective of the MAROS optimization is to minimize monitoring locations in the sampling network and reduce sampling frequency without significant loss of information, ensuring adequate future characterization of the contaminant plume. The interpretive trend analysis approach recommends the general monitoring system category for a site based on plume stability and site-specific hydrogeologic information. Plume stability is characterized using primary lines of evidence (i.e., Mann-Kendall analysis and linear regression analysis) based on concentration trends, and secondary lines of evidence based on modeling results and empirical data. The sampling optimization approach, consisting of a two-dimensional spatial sampling reduction method (Delaunay method) and a temporal sampling analysis method (Modified CES method), provides detailed sampling location and frequency results. The Delaunay method is designed to identify and eliminate redundant sampling locations without causing significant information loss in characterizing the plume. The Modified CES method determines the optimal sampling frequency for a sampling location based on the direction, magnitude, and uncertainty in its concentration trend. MAROS addresses a variety of ground water contaminants (fuels, solvents, and metals), allows import of various data formats, and is designed for continual modification of long-term monitoring plans as the plume or site conditions change over time.

  11. 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

  12. Managing urinary incontinence through hand-held real-time decision support aid.

    PubMed

    Koutsojannis, Constantinos; Lithari, Chrysa; Hatzilygeroudis, Ioannis

    2012-07-01

    In this paper, we present an intelligent system for the diagnosis and treatment of urinary incontinence (UI) for males as well as females, called e-URIN. e-URIN is an intelligent system for diagnosis and treatment of urinary incontinence according to symptoms that are realized in one patient and usually recorded through his clinical examination as well as specific test results. The user-friendly proposed intelligent system is accommodated on a hospital server supporting e-health tools, for use through pocket PCs under wireless connection as a decision support system for resident doctors, as well as an educational tool for medical students. It is based on expert system knowledge representation provided from urology experts in combination with rich bibliographic search and study ratified with statistical results from clinical practice. Preliminary experimental results on a real patient hospital database provide acceptable performance that can be improved using more than one computational intelligence approaches in the future.

  13. 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.

  14. Decision support systems for clinical radiological practice — towards the next generation

    PubMed Central

    Stivaros, S M; Gledson, A; Nenadic, G; Zeng, X-J; Keane, J; Jackson, A

    2010-01-01

    The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully. PMID:20965900

  15. Decision support systems for clinical radiological practice -- towards the next generation.

    PubMed

    Stivaros, S M; Gledson, A; Nenadic, G; Zeng, X-J; Keane, J; Jackson, A

    2010-11-01

    The huge amount of information that needs to be assimilated in order to keep pace with the continued advances in modern medical practice can form an insurmountable obstacle to the individual clinician. Within radiology, the recent development of quantitative imaging techniques, such as perfusion imaging, and the development of imaging-based biomarkers in modern therapeutic assessment has highlighted the need for computer systems to provide the radiological community with support for academic as well as clinical/translational applications. This article provides an overview of the underlying design and functionality of radiological decision support systems with examples tracing the development and evolution of such systems over the past 40 years. More importantly, we discuss the specific design, performance and usage characteristics that previous systems have highlighted as being necessary for clinical uptake and routine use. Additionally, we have identified particular failings in our current methodologies for data dissemination within the medical domain that must be overcome if the next generation of decision support systems is to be implemented successfully.

  16. 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.

  17. User Oriented Techniques to Support Interaction and Decision Making with Large Educational Databases

    ERIC Educational Resources Information Center

    Hartley, Roger; Almuhaidib, Saud M. Y.

    2007-01-01

    Information Technology is developing rapidly and providing policy/decision makers with large amounts of information that require processing and analysis. Decision support systems (DSS) aim to provide tools that not only help such analyses, but enable the decision maker to experiment and simulate the effects of different policies and selection…

  18. Investing in deliberation: a definition and classification of decision support interventions for people facing difficult health decisions.

    PubMed

    Elwyn, Glyn; Frosch, Dominick; Volandes, Angelo E; Edwards, Adrian; Montori, Victor M

    2010-01-01

    This article provides an analysis of 'decision aids', interventions to support patients facing tough decisions. Interest has increased since the concept of shared decision making has become widely considered to be a means of achieving desirable clinical outcomes. We consider the aims of these interventions and examine assumptions about their use. We propose three categories, interventions that are used in face-to-face encounters, those designed for use outside clinical encounters and those which are mediated, using telephone or other communication media. We propose the following definition: decision support interventions help people think about choices they face; they describe where and why choice exists; they provide information about options, including, where reasonable, the option of taking no action. These interventions help people to deliberate, independently or in collaboration with others, about options, by considering relevantattributes; they support people to forecast how they might feel about short, intermediate and long-term outcomes which have relevant consequences, in ways which help the process of constructing preferences and eventual decision making, appropriate to their individual situation. Although quality standards have been published for these interventions, we are also cautious about premature closure and consider that the need for short versions for use inside clinical encounters and long versions for external use requires further research. More work is also needed on the use of narrative formats and the translation of theory into practical designs. The interest in decision support interventions for patients heralds a transformation in clinical practice although many important areas remain unresolved.

  19. 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 ...

  20. 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

  1. 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.

  2. Securing Local Support for Your Computer Project.

    ERIC Educational Resources Information Center

    Roecks, Alan L.

    1979-01-01

    Guidelines for securing and maintaining local funding for computer-related projects include suggestions in the areas of establishing and maintaining project/school board relationships, encountering social and political factors, and defining guidelines for project implementation. Successes and failures of the MICA project are provided as…

  3. Organizational Strategies for End-User Computing Support.

    ERIC Educational Resources Information Center

    Blackmun, Robert R.; And Others

    1988-01-01

    Effective support for end users of computers has been an important issue in higher education from the first applications of general purpose mainframe computers through minicomputers, microcomputers, and supercomputers. The development of end user support is reviewed and organizational models are examined. (Author/MLW)

  4. 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…

  5. 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…

  6. 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.

  7. 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...

  8. A Decision Support System For Assisting With Stocking Rate Decisions During And Following Drought

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Ranchers and range managers in the West are at the mercy of climatic conditions that determine the amount of annual forge available on rangeland. Typically, stocking or de-stocking decisions need to be made before the final forage production level is known. Erroneous stocking rate decisions can have...

  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. 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...

  11. Decision Support Systems Project. Design Review Conference, October 14-15, 1984. Summary Report of Findings.

    ERIC Educational Resources Information Center

    Tetlow, William L.

    Findings of a conference that reviewed and evaluated design decisions concerning the Decision Support System (DSS) Demonstrator are summarized. The DSS Demonstrator was designed by the National Center for Higher Education Management Systems as an example of the way in which microcomputer technology can support and make more effective planning and…

  12. 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…

  13. Supporting patient autonomy: decision making in home care.

    PubMed

    Davitt, J K; Kaye, L W

    1996-01-01

    This study examines the policies and procedures that home health care agencies have developed to handle the incapacitated patient and life-sustaining treatment decisions. Data collected from a survey of 154 home health care agency directors and interviews with 92 local agency staff (including nurses and social workers) and 67 patients confirmed that directors, staff, and patients agree that patients are informed about their legal rights. When asked about specific rights, fewer patients were aware of their right to execute an advance directive, and even fewer patients had actually executed one. Only 67 percent of agencies reported having existing policies on advance directives and life-sustaining treatment decisions, whereas 41.5 percent had policies on how to handle the patient with questionable decision-making capacity. Consistent policies are needed for social workers, nurses, and other staff to handle such difficult ethical dilemmas. A review of specific agency policies is presented with recommendations for future policy changes and development.

  14. Nonword repetition in lexical decision: support for two opposing processes.

    PubMed

    Wagenmakers, Eric-Jan; Zeelenberg, René; Steyvers, Mark; Shiffrin, Richard; Raaijmakers, Jeroen

    2004-10-01

    We tested and confirmed the hypothesis that the prior presentation of nonwords in lexical decision is the net result of two opposing processes: (1) a relatively fast inhibitory process based on global familiarity; and (2) a relatively slow facilitatory process based on the retrieval of specific episodic information. In three studies, we manipulated speed-stress to influence the balance between the two processes. Experiment 1 showed item-specific improvement for repeated nonwords in a standard "respond-when-ready" lexical decision task. Experiment 2 used a 400-ms deadline procedure and showed performance for nonwords to be unaffected by up to four prior presentations. In Experiment 3 we used a signal-to-respond procedure with variable time intervals and found negative repetition priming for repeated nonwords. These results can be accounted for by dual-process models of lexical decision.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  17. 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.

  18. A Pain Management Decision Support System for Nurses

    PubMed Central

    Heriot, Cathy; Graves, Judith; Bouhaddou, Omar; Armstrong, Margaret; Wigertz, Gudrun; Ben Said, Mohamed

    1988-01-01

    This paper describes the development and uses of the Nursing Pain Management Consultation System, a prototype demonstration project for Integrated Academic Information Management System (IAIMS) at the University of Utah. A knowledge base representing the best current thinking regarding management of acute pain secondary to total hip arthroplasty (THA) is the knowledge core of the expert system. The decisions modeled range from assessment of the severity of pain to decisions related to both pharmacologic and non-pharmacologic approaches to the alleviation of pain. The system also advises the nurses on measures to assess and prevent complications of the treatments.

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

    PubMed

    Brannon, N G; Seiffertt, J E; Draelos, T J; Wunsch, D C

    2009-04-01

    Domains such as force protection require an effective decision maker to maintain a high level of situation awareness. A system that combines humans with neural networks is a desirable approach. Furthermore, it is advantageous for the calculation engine to operate in three learning modes: supervised for initial training and known updating, reinforcement for online operational improvement, and unsupervised in the absence of all external signaling. An Adaptive Resonance Theory based architecture capable of seamlessly switching among the three types of learning is discussed that can be used to help optimize the decision making of a human operator in such a scenario. This is followed by a situation assessment module.

  20. 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.

  1. Measuring Perceived Sociability of Computer-Supported Collaborative Learning Environments

    ERIC Educational Resources Information Center

    Kreijns, Karel; Kirschner, Paul A.; Jochems, Wim; van Buuren, Hans

    2007-01-01

    Most asynchronous computer-supported collaborative learning (CSCL) environments can be characterized as "functional" environments because they focus on functional, task-specific support, often disregarding explicit support for the social (emotional) aspects of learning in groups which are acknowledged by many educational researchers to be…

  2. Integrating Clinical Decision Support into EMR and PHR: a Case Study Using Anticoagulation.

    PubMed

    Chackery, Dave-Gregory; Keshavjee, Karim; Mirza, Kashif; Ghany, Ahmad; Holbrook, Anne M

    2015-01-01

    Clinical decision support (CDS) for atrial fibrillation is expected to ease the implementation of often-complex guidelines for atrial fibrillation and anticoagulation. Most clinical decision support systems (CDSS) for anticoagulation are stand-alone systems that do not integrate with electronic medical records (EMR). We have developed an architecture that consists of a computerized CDS that can integrate with multiple EMRs and multiple patient health records (PHRs). The design process revealed some significant issues that were resolved through systematic business/clinical analysis and creative clinical design in the diagnostic and treatment domains. Key issues identified and resolved include: 1) how to correctly allocate existing patients into various CDSS states (e.g., MAINTENANCE, HOLD, DISCONTINUE, etc), 2) identify when a patient becomes eligible for CDSS guidance over time, 3) how the CDSS maintains information about the patient's anticoagulation state and 4) how to transform vague human-readable concepts to explicit computable concepts. The management of anticoagulation for atrial fibrillation is no easy task and we believe our architecture will improve patient care at all levels and ultimately better balance the reduction of stroke risk while minimizing harms from major bleeding. In addition, the architecture presented is scalable to other treatment guidelines and is scalable to multiple EMRs and PHRs, making it suitable for use in a platform approach. PMID:25676955

  3. 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.

  4. 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...

  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. 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

  8. 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

  9. 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

  10. Optimal and Nonoptimal Computer-Based Test Designs for Making Pass-Fail Decisions

    ERIC Educational Resources Information Center

    Hambleton, Ronald K.; Xing, Dehui

    2006-01-01

    Now that many credentialing exams are being routinely administered by computer, new computer-based test designs, along with item response theory models, are being aggressively researched to identify specific designs that can increase the decision consistency and accuracy of pass-fail decisions. The purpose of this study was to investigate the…

  11. 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.

  12. 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.

  13. 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.…

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. Consensus oriented fuzzified decision support for oil spill contingency management.

    PubMed

    Liu, Xin; Wirtz, Kai W

    2006-06-30

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

  5. 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.

  6. 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

  7. 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. PMID:23453354

  8. 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.

  9. 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...

  10. 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

  11. The Selection of Test Items for Decision Making with a Computer Adaptive Test.

    ERIC Educational Resources Information Center

    Spray, Judith A.; Reckase, Mark D.

    The issue of test-item selection in support of decision making in adaptive testing is considered. The number of items needed to make a decision is compared for two approaches: selecting items from an item pool that are most informative at the decision point or selecting items that are most informative at the examinee's ability level. The first…

  12. Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review.

    PubMed

    Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S; Williams-Whitt, Kelly; Shaw, Nicola T; Hartvigsen, Jan; Qin, Ziling; Ha, Christine; Woodhouse, Linda J; Steenstra, Ivan A

    2016-09-01

    Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

  13. 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

  14. 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.

  15. Cost-Effectiveness of Clinical Decision Support System in Improving Maternal Health Care in Ghana

    PubMed Central

    Dalaba, Maxwell Ayindenaba; Akweongo, Patricia; Aborigo, Raymond Akawire; Saronga, Happiness Pius; Williams, John; Blank, Antje; Kaltschmidt, Jens; Sauerborn, Rainer; Loukanova, Svetla

    2015-01-01

    Objective This paper investigated the cost-effectiveness of a computer-assisted Clinical Decision Support System (CDSS) in the identification of maternal complications in Ghana. Methods A cost-effectiveness analysis was performed in a before- and after-intervention study. Analysis was conducted from the provider’s perspective. The intervention area was the Kassena- Nankana district where computer-assisted CDSS was used by midwives in maternal care in six selected health centres. Six selected health centers in the Builsa district served as the non-intervention group, where the normal Ghana Health Service activities were being carried out. Results Computer-assisted CDSS increased the detection of pregnancy complications during antenatal care (ANC) in the intervention health centres (before-intervention= 9 /1,000 ANC attendance; after-intervention= 12/1,000 ANC attendance; P-value=0.010). In the intervention health centres, there was a decrease in the number of complications during labour by 1.1%, though the difference was not statistically significant (before-intervention =107/1,000 labour clients; after-intervention= 96/1,000 labour clients; P-value=0.305). Also, at the intervention health centres, the average cost per pregnancy complication detected during ANC (cost –effectiveness ratio) decreased from US$17,017.58 (before-intervention) to US$15,207.5 (after-intervention). Incremental cost –effectiveness ratio (ICER) was estimated at US$1,142. Considering only additional costs (cost of computer-assisted CDSS), cost per pregnancy complication detected was US$285. Conclusions Computer –assisted CDSS has the potential to identify complications during pregnancy and marginal reduction in labour complications. Implementing computer-assisted CDSS is more costly but more effective in the detection of pregnancy complications compared to routine maternal care, hence making the decision to implement CDSS very complex. Policy makers should however be guided by whether

  16. How Effective Is Instructional Support for Learning with Computer Simulations?

    ERIC Educational Resources Information Center

    Eckhardt, Marc; Urhahne, Detlef; Conrad, Olaf; Harms, Ute

    2013-01-01

    The study examined the effects of two different instructional interventions as support for scientific discovery learning using computer simulations. In two well-known categories of difficulty, data interpretation and self-regulation, instructional interventions for learning with computer simulations on the topic "ecosystem water" were developed…

  17. Shaping Computer-Based Support for Curriculum Developers

    ERIC Educational Resources Information Center

    McKenney, Susan

    2008-01-01

    CASCADE-SEA stands for computer supported curriculum analysis, design and evaluation for science education in Africa. It is the name of a computer program designed to help secondary level science teachers in southern Africa create exemplary paper-based lesson materials. Research conducted alongside the design and development of the CASCADE-SEA…

  18. Strategizing Computer-Supported Collaborative Learning toward Knowledge Building

    ERIC Educational Resources Information Center

    Mukama, Evode

    2010-01-01

    The purpose of this paper is to explore how university students can develop knowledge in small task-based groups while acquiring hands-on computer skills. Inspired by the sociocultural perspective, this study presents a theoretical framework on co-construction of knowledge and on computer-supported collaborative learning. The participants were…

  19. A Proposed Clinical Decision Support Architecture Capable of Supporting Whole Genome Sequence Information

    PubMed Central

    Welch, Brandon M.; Rodriguez Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

    2014-01-01

    Whole genome sequence (WGS) information may soon be widely available to help clinicians personalize the care and treatment of patients. However, considerable barriers exist, which may hinder the effective utilization of WGS information in a routine clinical care setting. Clinical decision support (CDS) offers a potential solution to overcome such barriers and to facilitate the effective use of WGS information in the clinic. However, genomic information is complex and will require significant considerations when developing CDS capabilities. As such, this manuscript lays out a conceptual framework for a CDS architecture designed to deliver WGS-guided CDS within the clinical workflow. To handle the complexity and breadth of WGS information, the proposed CDS framework leverages service-oriented capabilities and orchestrates the interaction of several independently-managed components. These independently-managed components include the genome variant knowledge base, the genome database, the CDS knowledge base, a CDS controller and the electronic health record (EHR). A key design feature is that genome data can be stored separately from the EHR. This paper describes in detail: (1) each component of the architecture; (2) the interaction of the components; and (3) how the architecture attempts to overcome the challenges associated with WGS information. We believe that service-oriented CDS capabilities will be essential to using WGS information for personalized medicine. PMID:25411644

  20. Visual Cluster Analysis in Support of Clinical Decision Intelligence

    PubMed Central

    Gotz, David; Sun, Jimeng; Cao, Nan; Ebadollahi, Shahram

    2011-01-01

    Electronic health records (EHRs) contain a wealth of information about patients. In addition to providing efficient and accurate records for individual patients, large databases of EHRs contain valuable information about overall patient populations. While statistical insights describing an overall population are beneficial, they are often not specific enough to use as the basis for individualized patient-centric decisions. To address this challenge, we describe an approach based on patient similarity which analyzes an EHR database to extract a cohort of patient records most similar to a specific target patient. Clusters of similar patients are then visualized to allow interactive visual refinement by human experts. Statistics are then extracted from the refined patient clusters and displayed to users. The statistical insights taken from these refined clusters provide personalized guidance for complex decisions. This paper focuses on the cluster refinement stage where an expert user must interactively (a) judge the quality and contents of automatically generated similar patient clusters, and (b) refine the clusters based on his/her expertise. We describe the DICON visualization tool which allows users to interactively view and refine multidimensional similar patient clusters. We also present results from a preliminary evaluation where two medical doctors provided feedback on our approach. PMID:22195102

  1. Assembling Tools and Data for Climate Model Decision Support

    NASA Astrophysics Data System (ADS)

    Batcheller, A. L.; VanWijngaarden, F.

    2011-12-01

    The Global Earth Observation System of Systems (GEOSS) effort has identified nine areas in which society benefits from appropriate environmental information. We have targeted specific issues within these societal benefit areas by determining appropriate data sets needed and transforming these data into information useable by decision makers. Here we describe the service-oriented architecture that allows us to ingest real-time or static data into a database with a spatial data engine, make appropriate manipulations to the data using domain knowledge relevant to the problem, and expose the data as services. We then build custom portals using a library of common widgets to display and overlay the data for users to analyze. By using portals and a service-oriented architecture we can reuse services and widgets to rapidly assemble a view of geographic data, and assist decision-makers in applying and interpreting the latest scientific results. As a case study with our system, we have integrated data from Intergovernmental Panel on Climate Change (IPCC) climate models, crop yields, and environmental thresholds for crops to present a first level analysis of the impact of climate change on key crops grown in Mexico. Knowledge about changes in the regions that are favorable for crop growth is important for many stakeholders, ranging from individual farmers, to governments, to scientists working to create new seed varieties. Our work also highlights research opportunities in climate science by identifying the types and resolution of parameters modeled.

  2. 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.'

  3. 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.

  4. 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.

  5. 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.

  6. Distributed Computing with Centralized Support Works at Brigham Young.

    ERIC Educational Resources Information Center

    McDonald, Kelly; Stone, Brad

    1992-01-01

    Brigham Young University (Utah) has addressed the need for maintenance and support of distributed computing systems on campus by implementing a program patterned after a national business franchise, providing the support and training of a centralized administration but allowing each unit to operate much as an independent small business.…

  7. A psychiatric medication decision support guide for social work practice with pregnant and postpartum women.

    PubMed

    Bentley, Kia J; Price, Sarah Kye; Cummings, Cory R

    2014-10-01

    In their work in human services organizations and community agencies across service sectors, social workers encounter pregnant and postpartum women experiencing mental health challenges. This article offers an evidence-informed Decision Support Guide designed for use by social workers working with pregnant and postpartum women who are struggling with complicated decisions about psychiatric medication use. The guide is built on contemporary notions of health literacy and shared decision making and is informed by three areas: (1) research into the lived experiences of pregnant and postpartum women and health care providers around psychiatric medication decision making, (2) a critical review of existing decision aids, and (3) feedback on the strategy from social work practitioners who work with pregnant and postpartum women. Emphasizing the relational nature of social work in supporting effective health-related decision making, the guide relies on maintaining a collaborative practice milieu and using a decision aid that engages clients in discussions about mental health during and around the time of pregnancy. The guide offers social workers a practice tool to support responsive and compassionate care by embracing their roles in problem solving and decision making, providing emotional and psychosocial support, and making appropriate referrals to prescribers.

  8. Assessing Sustainability of Coral Reef Ecosystem Services using a Spatially-Explicit Decision Support Tool

    EPA Science Inventory

    Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...

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

    EPA Science Inventory

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

  10. 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…

  11. Inter-Rater Reliability of the Illinois Structured Decision Support Protocol

    ERIC Educational Resources Information Center

    Kang, Hyun-Ah; Poertner, John

    2006-01-01

    Objective: The purpose of this study was to determine the level of inter-rater reliability of the Illinois Structured Decision Support Protocol by examining the level of Child Protective Services (CPS) caseworkers' agreement regarding state interventions. The Protocol was designed to guide CPS workers to consistent decisions related to the level…

  12. Decision Support Systems (DSSs) For Contaminated Land Management - Gaps And Challenges

    EPA Science Inventory

    A plethora of information is available when considering decision support systems for risk-based management of contaminated land. Broad issues of what is contaminated land, what is a brownfield, and what is remediation are discussed in EU countries and the U.S. Making decisions ...

  13. A decision support system for pre-earthquake planning of lifeline networks

    SciTech Connect

    Liang, J.W.

    1996-12-01

    This paper describes the frame of a decision support system for pre-earthquake planning of gas and water networks. The system is mainly based on the earthquake experiences and lessons from the 1976 Tangshan earthquake. The objective of the system is to offer countermeasures and help make decisions for seismic strengthening, remaking, and upgrading of gas and water networks.

  14. Recycling decision support system: Design and development of a Web-based DSS. Master thesis

    SciTech Connect

    Tettelbach, C.G.

    1997-03-01

    The explosive growth of the World Wide Web creates new opportunities for the development and deployment of Decision Support Systems. No longer restricted by machine-specific limitations, Web-based Decision Support Systems (DSS) provide global access to widely diversified and geographically dispersed users through sharing of data, models, algorithms, and modeling environments. This thesis examines the design and development processes involved in the creation of a Web-based DSS. The Recycling Decision Support System utilizes a rapid prototype and refinement process to create a Web-based system focusing on supporting ordinary people and industrial users in making good decisions for recycling and disposal of household and industrial waste. Through abstraction of details from the specific Web-based DSS design, a generalized framework for supporting decision-making via the WWW is built which supports functionality in education, queries, and analysis of complex problems. An important aspect of this research is the development of a new architecture which conforms to the complexities specific to Web-based Decision Support Systems. Prompted by the additional interactions required for WWW connectivity, this architecture incorporates agents for negotiating transactions between the functional components of a standard DSS.

  15. Assessing environmental conditions of Antarctic footpaths to support management decisions.

    PubMed

    Tejedo, Pablo; Benayas, Javier; Cajiao, Daniela; Albertos, Belén; Lara, Francisco; Pertierra, Luis R; Andrés-Abellán, Manuela; Wic, Consuelo; Luciáñez, Maria José; Enríquez, Natalia; Justel, Ana; Reck, Günther K

    2016-07-15

    Thousands of tourists visit certain Antarctic sites each year, generating a wide variety of environmental impacts. Scientific knowledge of human activities and their impacts can help in the effective design of management measures and impact mitigation. We present a case study from Barrientos Island in which a management measure was originally put in place with the goal of minimizing environmental impacts but resulted in new undesired impacts. Two alternative footpaths used by tourist groups were compared. Both affected extensive moss carpets that cover the middle part of the island and that are very vulnerable to trampling. The first path has been used by tourists and scientists since over a decade and is a marked route that is clearly visible. The second one was created more recently. Several physical and biological indicators were measured in order to assess the environmental conditions for both paths. Some physical variables related to human impact were lower for the first path (e.g. soil penetration resistance and secondary treads), while other biochemical and microbiological variables were higher for the second path (e.g. β-glucosidase and phosphatase activities, soil respiration). Moss communities located along the new path were also more diverse and sensitive to trampling. Soil biota (Collembola) was also more abundant and richer. These data indicate that the decision to adopt the second path did not lead to the reduction of environmental impacts as this path runs over a more vulnerable area with more outstanding biological features (e.g. microbiota activity, flora and soil fauna diversity). In addition, the adoption of a new route effectively doubles the human footprint on the island. We propose using only the original path that is less vulnerable to the impacts of trampling. Finally from this process, we identify several key issues that may be taken into account when carrying out impact assessment and environmental management decision-making in the

  16. Assessing environmental conditions of Antarctic footpaths to support management decisions.

    PubMed

    Tejedo, Pablo; Benayas, Javier; Cajiao, Daniela; Albertos, Belén; Lara, Francisco; Pertierra, Luis R; Andrés-Abellán, Manuela; Wic, Consuelo; Luciáñez, Maria José; Enríquez, Natalia; Justel, Ana; Reck, Günther K

    2016-07-15

    Thousands of tourists visit certain Antarctic sites each year, generating a wide variety of environmental impacts. Scientific knowledge of human activities and their impacts can help in the effective design of management measures and impact mitigation. We present a case study from Barrientos Island in which a management measure was originally put in place with the goal of minimizing environmental impacts but resulted in new undesired impacts. Two alternative footpaths used by tourist groups were compared. Both affected extensive moss carpets that cover the middle part of the island and that are very vulnerable to trampling. The first path has been used by tourists and scientists since over a decade and is a marked route that is clearly visible. The second one was created more recently. Several physical and biological indicators were measured in order to assess the environmental conditions for both paths. Some physical variables related to human impact were lower for the first path (e.g. soil penetration resistance and secondary treads), while other biochemical and microbiological variables were higher for the second path (e.g. β-glucosidase and phosphatase activities, soil respiration). Moss communities located along the new path were also more diverse and sensitive to trampling. Soil biota (Collembola) was also more abundant and richer. These data indicate that the decision to adopt the second path did not lead to the reduction of environmental impacts as this path runs over a more vulnerable area with more outstanding biological features (e.g. microbiota activity, flora and soil fauna diversity). In addition, the adoption of a new route effectively doubles the human footprint on the island. We propose using only the original path that is less vulnerable to the impacts of trampling. Finally from this process, we identify several key issues that may be taken into account when carrying out impact assessment and environmental management decision-making in the

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

    EPA Science Inventory

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

  18. GET SMARTE: A DECISION SUPPORT SYSTEM TO REVITALIZE COMMUNITIES - CABERNET 2007

    EPA Science Inventory

    Sustainable Management Approaches and Revitalization Tools - electronic (SMARTe), is an open-source, web-based, decision support system for developing and evaluating future reuse scenarios for potentially contaminated land. SMARTe contains information and analysis tools for all a...

  19. The Integrated Medical Model: A Decision Support Tool for In-flight Crew Health Care

    NASA Technical Reports Server (NTRS)

    Butler, Doug

    2009-01-01

    This viewgraph presentation reviews the development of an Integrated Medical Model (IMM) decision support tool for in-flight crew health care safety. Clinical methods, resources, and case scenarios are also addressed.

  20. Framework for securing personal health data in clinical decision support systems.

    PubMed

    Sandell, Protik

    2007-01-01

    If appropriate security mechanisms aren't in place, individuals and groups can get unauthorized access to personal health data residing in clinical decision support systems (CDSS). These concerns are well founded; there has been a dramatic increase in reports of security incidents. The paper provides a framework for securing personal health data in CDSS. The framework breaks down CDSS into data gathering, data management and data delivery functions. It then provides the vulnerabilities that can occur in clinical decision support activities and the measures that need to be taken to protect the data. The framework is applied to protect the confidentiality, integrity and availability of personal health data in a decision support system. Using the framework, project managers and architects can assess the potential risk of unauthorized data access in their decision support system. Moreover they can design systems and procedures to effectively secure personal health data.