Bioregional monitoring design and occupancy estimation for two Sierra Nevadan amphibian taxa

EPA Science Inventory

Land-management agencies need quantitative, statistically rigorous monitoring data, often at large spatial and temporal scales, to support resource-management decisions. Monitoring designs typically must accommodate multiple ecological, logistical, political, and economic objec...

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

USGS Publications Warehouse

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

2010-01-01

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

Designing for knowledge: bridging socio-hydrological monitoring and beyond

NASA Astrophysics Data System (ADS)

Mao, F.; Clark, J.; Buytaert, W.; Ochoa-Tocachi, B. F.; Hannah, D. M.

2016-12-01

Many methods and applications have been developed to research socio-hydrological systems, such as participatory monitoring, environmental big data processing and sensor network data transmission. However, these data-centred activities are insufficient to guarantee successful knowledge co-generation, decision making or governance. This research suggests a shift of attentions in designing socio-hydrological monitoring tools, from designing for data to designing for knowledge (DfK). Compared to the former strategy, DfK has at least three features as follows. (1) Why monitor? DfK demands the data produced by the newly introduced monitoring application to have potentials to generate socio-hydrological knowledge that supports decision making or management. It means that when designing a monitoring tool, we should not only answer how to collect data, but also questions such as how to best use the collected data in the form of knowledge. (2) What is the role of monitoring? DfK admits that the socio-hydrological data and knowledge generated by monitoring is just one of many kinds to support decision making and management. It means that the importance of monitoring and scientific evidence should not be overestimated, and knowledge cogeneration and synthesis should be considered in advance in the monitoring design process. (3) Who participate? DfK implies a wider engagement of stakeholders, which is not restricted between volunteers as data collectors and providers, and scientist and researcher communities as main data users. It requires a broader consideration of users, including not only data collectors, processors and interpreters, but also local and indigenous knowledge providers, and decision makers who use the knowledge and data. In summary, this research proposes a knowledge-centred strategy in designing participatory socio-hydrological monitoring tools, in order to make monitoring more useful and effective.

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

PubMed

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

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

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

NASA Astrophysics Data System (ADS)

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

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

Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes.

PubMed

García-Sáez, Gema; Rigla, Mercedes; Martínez-Sarriegui, Iñaki; Shalom, Erez; Peleg, Mor; Broens, Tom; Pons, Belén; Caballero-Ruíz, Estefanía; Gómez, Enrique J; Hernando, M Elena

2014-03-01

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system. © 2014 Diabetes Technology Society.

Exploring morally relevant issues facing families in their decisions to monitor the health-related behaviours of loved ones.

PubMed

Gammon, D; Christiansen, E K; Wynn, R

2009-07-01

Patient self-management of disease is increasingly supported by technologies that can monitor a wide range of behavioural and biomedical parameters. Incorporated into everyday devices such as cell phones and clothes, these technologies become integral to the psychosocial aspects of everyday life. Many technologies are likely to be marketed directly to families with ill members, and families may enlist the support of clinicians in shaping use. Current ethical frameworks are mainly conceptualised from the perspective of caregivers, researchers, developers and regulators in order to ensure the ethics of their own practices. This paper focuses on families as autonomous decision-makers outside the regulated context of healthcare. We discuss some morally relevant issues facing families in their decisions to monitor the health-related behaviours of loved ones. An example - remote parental monitoring of adolescent blood glucose - is presented and discussed through the lens of two contrasting accounts of ethics; one reflecting the predominant focus on health outcomes within the health technology assessment (HTA) framework and the other that attends to the broader sociocultural contexts shaping technologies and their implications. Issues discussed include the focus of assessments, informed consent and child assent, and family co-creation of system characteristics and implications. The parents' decisions to remotely monitor their child has relational implications that are likely to influence conflict levels and thus also health outcomes. Current efforts to better integrate outcome assessments with social and ethical assessments are particularly relevant for informed decision-making about health monitoring technologies in families.

A pilot study of distributed knowledge management and clinical decision support in the cloud.

PubMed

Dixon, Brian E; Simonaitis, Linas; Goldberg, Howard S; Paterno, Marilyn D; Schaeffer, Molly; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford

2013-09-01

Implement and perform pilot testing of web-based clinical decision support services using a novel framework for creating and managing clinical knowledge in a distributed fashion using the cloud. The pilot sought to (1) develop and test connectivity to an external clinical decision support (CDS) service, (2) assess the exchange of data to and knowledge from the external CDS service, and (3) capture lessons to guide expansion to more practice sites and users. The Clinical Decision Support Consortium created a repository of shared CDS knowledge for managing hypertension, diabetes, and coronary artery disease in a community cloud hosted by Partners HealthCare. A limited data set for primary care patients at a separate health system was securely transmitted to a CDS rules engine hosted in the cloud. Preventive care reminders triggered by the limited data set were returned for display to clinician end users for review and display. During a pilot study, we (1) monitored connectivity and system performance, (2) studied the exchange of data and decision support reminders between the two health systems, and (3) captured lessons. During the six month pilot study, there were 1339 patient encounters in which information was successfully exchanged. Preventive care reminders were displayed during 57% of patient visits, most often reminding physicians to monitor blood pressure for hypertensive patients (29%) and order eye exams for patients with diabetes (28%). Lessons learned were grouped into five themes: performance, governance, semantic interoperability, ongoing adjustments, and usability. Remote, asynchronous cloud-based decision support performed reasonably well, although issues concerning governance, semantic interoperability, and usability remain key challenges for successful adoption and use of cloud-based CDS that will require collaboration between biomedical informatics and computer science disciplines. Decision support in the cloud is feasible and may be a reasonable path toward achieving better support of clinical decision-making across the widest range of health care providers. Published by Elsevier B.V.

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

Treesearch

David A. MacLean

2000-01-01

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

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

PubMed

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

2018-01-01

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

Enabling active and healthy ageing decision support systems with the smart collection of TV usage patterns

PubMed Central

Billis, Antonis S.; Batziakas, Asterios; Bratsas, Charalampos; Tsatali, Marianna S.; Karagianni, Maria

2016-01-01

Smart monitoring of seniors behavioural patterns and more specifically activities of daily living have attracted immense research interest in recent years. Development of smart decision support systems to support the promotion of health smart homes has also emerged taking advantage of the plethora of smart, inexpensive and unobtrusive monitoring sensors, devices and software tools. To this end, a smart monitoring system has been used in order to extract meaningful information about television (TV) usage patterns and subsequently associate them with clinical findings of experts. The smart TV operating state remote monitoring system was installed in four elderly women homes and gathered data for more than 11 months. Results suggest that TV daily usage (time the TV is turned on) can predict mental health change. Conclusively, the authors suggest that collection of smart device usage patterns could strengthen the inference capabilities of existing health DSSs applied in uncontrolled settings such as real senior homes. PMID:27284457

Enabling active and healthy ageing decision support systems with the smart collection of TV usage patterns.

PubMed

Billis, Antonis S; Batziakas, Asterios; Bratsas, Charalampos; Tsatali, Marianna S; Karagianni, Maria; Bamidis, Panagiotis D

2016-03-01

Smart monitoring of seniors behavioural patterns and more specifically activities of daily living have attracted immense research interest in recent years. Development of smart decision support systems to support the promotion of health smart homes has also emerged taking advantage of the plethora of smart, inexpensive and unobtrusive monitoring sensors, devices and software tools. To this end, a smart monitoring system has been used in order to extract meaningful information about television (TV) usage patterns and subsequently associate them with clinical findings of experts. The smart TV operating state remote monitoring system was installed in four elderly women homes and gathered data for more than 11 months. Results suggest that TV daily usage (time the TV is turned on) can predict mental health change. Conclusively, the authors suggest that collection of smart device usage patterns could strengthen the inference capabilities of existing health DSSs applied in uncontrolled settings such as real senior homes.

Concept of information technology of monitoring and decision-making support

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

CAN BIVALVES BE USEFUL INDICATORS OF ECOSYSTEM CONDITION?

EPA Science Inventory

Numerous management decisions are made to sustain multiple, and often competing, products and services from coastal ecosystems. Scientific support for these decisions emanate from environmental indicators or selected measurements used in a monitoring program. Indicators are surro...

Spatial decision support system for tobacco enterprise based on spatial data mining

NASA Astrophysics Data System (ADS)

Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong

2007-11-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

A Hybrid-Cloud Science Data System Enabling Advanced Rapid Imaging & Analysis for Monitoring Hazards

NASA Astrophysics Data System (ADS)

Hua, H.; Owen, S. E.; Yun, S.; Lundgren, P.; Moore, A. W.; Fielding, E. J.; Radulescu, C.; Sacco, G.; Stough, T. M.; Mattmann, C. A.; Cervelli, P. F.; Poland, M. P.; Cruz, J.

2012-12-01

Volcanic eruptions, landslides, and levee failures are some examples of hazards that can be more accurately forecasted with sufficient monitoring of precursory ground deformation, such as the high-resolution measurements from GPS and InSAR. In addition, coherence and reflectivity change maps can be used to detect surface change due to lava flows, mudslides, tornadoes, floods, and other natural and man-made disasters. However, it is difficult for many volcano observatories and other monitoring agencies to process GPS and InSAR products in an automated scenario needed for continual monitoring of events. Additionally, numerous interoperability barriers exist in multi-sensor observation data access, preparation, and fusion to create actionable products. Combining high spatial resolution InSAR products with high temporal resolution GPS products--and automating this data preparation & processing across global-scale areas of interests--present an untapped science and monitoring opportunity. The global coverage offered by satellite-based SAR observations, and the rapidly expanding GPS networks, can provide orders of magnitude more data on these hazardous events if we have a data system that can efficiently and effectively analyze the voluminous raw data, and provide users the tools to access data from their regions of interest. Currently, combined GPS & InSAR time series are primarily generated for specific research applications, and are not implemented to run on large-scale continuous data sets and delivered to decision-making communities. We are developing an advanced service-oriented architecture for hazard monitoring leveraging NASA-funded algorithms and data management to enable both science and decision-making communities to monitor areas of interests via seamless data preparation, processing, and distribution. Our objectives: * Enable high-volume and low-latency automatic generation of NASA Solid Earth science data products (InSAR and GPS) to support hazards monitoring. * Facilitate NASA-USGS collaborations to share NASA InSAR and GPS data products, which are difficult to process in high-volume and low-latency, for decision-support. * Enable interoperable discovery, access, and sharing of NASA observations and derived actionable products, and between the observation and decision-making communities. * Enable their improved understanding through visualization, mining, and cross-agency sharing. Existing InSAR & GPS processing packages and other software are integrated for generating geodetic decision support monitoring products. We employ semantic and cloud-based data management and processing techniques for handling large data volumes, reducing end product latency, codifying data system information with semantics, and deploying interoperable services for actionable products to decision-making communities.

Development of Decision Support System for Remote Monitoring of PIP Corn

EPA Science Inventory

The EPA is developing a multi-level approach that utilizes satellite and airborne remote sensing to locate and monitor genetically modified corn in the agricultural landscape and pest infestation. The current status of the EPA IRM monitoring program based on remote sensed imager...

Integrating environmental monitoring with cumulative effects management and decision making.

PubMed

Cronmiller, Joshua G; Noble, Bram F

2018-05-01

Cumulative effects (CE) monitoring is foundational to emerging regional and watershed CE management frameworks, yet monitoring is often poorly integrated with CE management and decision-making processes. The challenges are largely institutional and organizational, more so than scientific or technical. Calls for improved integration of monitoring with CE management and decision making are not new, but there has been limited research on how best to integrate environmental monitoring programs to ensure credible CE science and to deliver results that respond to the more immediate questions and needs of regulatory decision makers. This paper examines options for the integration of environmental monitoring with CE frameworks. Based on semistructured interviews with practitioners, regulators, and other experts in the Lower Athabasca, Alberta, Canada, 3 approaches to monitoring system design are presented. First, a distributed monitoring system, reflecting the current approach in the Lower Athabasca, where monitoring is delegated to different external programs and organizations; second, a 1-window system in which monitoring is undertaken by a single, in-house agency for the purpose of informing management and regulatory decision making; third, an independent system driven primarily by CE science and understanding causal relationships, with knowledge adopted for decision support where relevant to specific management questions. The strengths and limitations of each approach are presented. A hybrid approach may be optimal-an independent, nongovernment, 1-window model for CE science, monitoring, and information delivery-capitalizing on the strengths of distributed, 1-window, and independent monitoring systems while mitigating their weaknesses. If governments are committed to solving CE problems, they must invest in the long-term science needed to do so; at the same time, if science-based monitoring programs are to be sustainable over the long term, they must be responsive to the more immediate, often shorter term needs and CE information requirements of decision makers. Integr Environ Assess Manag 2018;14:407-417. © 2018 SETAC. © 2018 SETAC.

Experiences in Bridging the Gap Between Science and Decision Making at NASAs GSFC Earth Sciences Data and Information Services Center (GES DISC)

NASA Astrophysics Data System (ADS)

Kempler, S.; Teng, W.; Friedl, L.; Lynnes, C.

2008-12-01

In recognizing the significance of NASA remote sensing Earth science data in monitoring and better understanding our planet's natural environment, NASA has implemented the 'Decision Support Through Earth Science Research Results' program to solicit "proposals that develop and demonstrate innovative and practicable applications of NASA Earth science observations and research"that focus on improving decision making activities", as stated in the NASA ROSES-2008, A.18 solicitation. This very successful program has yielded several monitoring, surveillance, and decision support systems through collaborations with benefiting organizations in the areas of agriculture, air quality, disaster management, ecosystems, public health, water resources, and aviation weather. The Goddard Space Flight Center (GSFC) Earth Sciences Data and Information Services Center (GES DISC) has participated in this program on two projects (one complete, one ongoing), and has had opportune ad hoc collaborations gaining much experience in the formulation, management, development, and implementation of decision support systems utilizing NASA Earth science data. Coupling this experience with the GES DISC's total understanding and vast experience regarding Earth science missions and resulting data and information, including data structures, data usability and interpretation, data interoperability, and information management systems, the GES DISC is in the unique position to more readily identify challenges that come with bringing science data to decision makers. These challenges consist of those that can be met within typical science data usage frameworks, as well as those challenges that arise when utilizing science data for previously unplanned applications, such as decision support systems. The purpose of this presentation is to share GES DISC decision support system project experiences in regards to system sustainability, required data quality (versus timeliness), data provider understanding how decisions are made, which leads to the data receivers willingness to use new types of information to make decisions, as well as other topics. In addition, defining metrics that 'really' evaluate success will be exemplified.

Extending BPM Environments of Your Choice with Performance Related Decision Support

NASA Astrophysics Data System (ADS)

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

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

Using an Online Tool for Learning about and Implementing Algebra Progress Monitoring

ERIC Educational Resources Information Center

Foegen, Anne; Stecker, Pamela M.; Genareo, Vincent R.; Lyons, Renée; Olson, Jeannette R.; Simpson, Amber; Romig, John Elwood; Jones, Rachel

2016-01-01

Research supports special educators' use of progress-monitoring data for instructional decision-making purposes as an evidence-based practice for improving student achievement. This article describes the Professional Development for Algebra Progress Monitoring (PD-APM) system. PD-APM, is an online system that includes two "hubs" that…

Misremembrance of options past: source monitoring and choice.

PubMed

Mather, M; Shafir, E; Johnson, M K

2000-03-01

This study reveals that when remembering past decisions, people engage in choice-supportive memory distortion. When asked to make memory attributions of options' features, participants made source-monitoring errors that supported their decisions. They tended to attribute, both correctly and incorrectly, more positive features to the option they had selected than to its competitor. In addition, they sometimes attributed, both correctly and incorrectly, more negative features to the nonselected option. This pattern of distortion may be beneficial to people's general well-being, reducing regret for options not taken. At the same time, it is problematic for memory accuracy, for accountability, and for learning from past experience.

Integrating observation and statistical forecasts over sub-Saharan Africa to support Famine Early Warning

USGS Publications Warehouse

Funk, Chris; Verdin, James P.; Husak, Gregory

2007-01-01

Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to advance, discontinuities between monitoring and forecast systems inhibit effective decision making. Monitoring systems typically rely on high resolution satellite remote-sensed normalized difference vegetation index (NDVI) and rainfall imagery. Forecast systems provide information on a variety of scales and formats. Non-meteorologists are often unable or unwilling to connect the dots between these disparate sources of information. To mitigate these problem researchers at UCSB's Climate Hazard Group, NASA GIMMS and USGS/EROS are implementing a NASA-funded integrated decision support system that combines the monitoring of precipitation and NDVI with statistical one-to-three month forecasts. We present the monitoring/forecast system, assess its accuracy, and demonstrate its application in food insecure sub-Saharan Africa.

Towards a geophysical decision-support system for monitoring and managing unstable slopes

NASA Astrophysics Data System (ADS)

Chambers, J. E.; Meldrum, P.; Wilkinson, P. B.; Uhlemann, S.; Swift, R. T.; Inauen, C.; Gunn, D.; Kuras, O.; Whiteley, J.; Kendall, J. M.

2017-12-01

Conventional approaches for condition monitoring, such as walk over surveys, remote sensing or intrusive sampling, are often inadequate for predicting instabilities in natural and engineered slopes. Surface observations cannot detect the subsurface precursors to failure events; instead they can only identify failure once it has begun. On the other hand, intrusive investigations using boreholes only sample a very small volume of ground and hence small scale deterioration process in heterogeneous ground conditions can easily be missed. It is increasingly being recognised that geophysical techniques can complement conventional approaches by providing spatial subsurface information. Here we describe the development and testing of a new geophysical slope monitoring system. It is built around low-cost electrical resistivity tomography instrumentation, combined with integrated geotechnical logging capability, and coupled with data telemetry. An automated data processing and analysis workflow is being developed to streamline information delivery. The development of this approach has provided the basis of a decision-support tool for monitoring and managing unstable slopes. The hardware component of the system has been operational at a number of field sites associated with a range of natural and engineered slopes for up to two years. We report on the monitoring results from these sites, discuss the practicalities of installing and maintaining long-term geophysical monitoring infrastructure, and consider the requirements of a fully automated data processing and analysis workflow. We propose that the result of this development work is a practical decision-support tool that can provide near-real-time information relating to the internal condition of problematic slopes.

Putting intelligent structured intermittent auscultation (ISIA) into practice.

PubMed

Maude, Robyn M; Skinner, Joan P; Foureur, Maralyn J

2016-06-01

Fetal monitoring guidelines recommend intermittent auscultation for the monitoring of fetal wellbeing during labour for low-risk women. However, these guidelines are not being translated into practice and low-risk women birthing in institutional maternity units are increasingly exposed to continuous cardiotocographic monitoring, both on admission to hospital and during labour. When continuous fetal monitoring becomes routinised, midwives and obstetricians lose practical skills around intermittent auscultation. To support clinical practice and decision-making around auscultation modality, the intelligent structured intermittent auscultation (ISIA) framework was developed. The purpose of this discussion paper is to describe the application of intelligent structured intermittent auscultation in practice. The intelligent structured intermittent auscultation decision-making framework is a knowledge translation tool that supports the implementation of evidence into practice around the use of intermittent auscultation for fetal heart monitoring for low-risk women during labour. An understanding of the physiology of the materno-utero-placental unit and control of the fetal heart underpin the development of the framework. Intelligent structured intermittent auscultation provides midwives with a robust means of demonstrating their critical thinking and clinical reasoning and supports their understanding of normal physiological birth. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Midlevel Maternity Providers' Preferences of a Childbirth Monitoring Tool in Low-Income Health Units in Uganda.

PubMed

Balikuddembe, Michael S; Wakholi, Peter K; Tumwesigye, Nazarius M; Tylleskär, Thorkild

2018-01-01

A third of women in childbirth are inadequately monitored, partly due to the tools used. Some stakeholders assert that the current labour monitoring tools are not efficient and need improvement to become more relevant to childbirth attendants. The study objective was to explore the expectations of maternity service providers for a mobile childbirth monitoring tool in maternity facilities in a low-income country like Uganda. Semi-structured interviews of purposively selected midwives and doctors in rural-urban childbirth facilities in Uganda were conducted before thematic data analysis. The childbirth providers expected a tool that enabled fast and secure childbirth record storage and sharing. They desired a tool that would automatically and conveniently register patient clinical findings, and actively provide interactive clinical decision support on a busy ward. The tool ought to support agreed upon standards for good pregnancy outcomes but also adaptable to the patient and their difficult working conditions. The tool functionality should include clinical data management and real-time decision support to the midwives, while the non-functional attributes include versatility and security.

Development of system decision support tools for behavioral trends monitoring of machinery maintenance in a competitive environment

NASA Astrophysics Data System (ADS)

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani

2017-06-01

The article is centred on software system development for manufacturing company that produces polyethylene bags using mostly conventional machines in a competitive world where each business enterprise desires to stand tall. This is meant to assist in gaining market shares, taking maintenance and production decisions by the dynamism and flexibilities embedded in the package as customers' demand varies under the duress of meeting the set goals. The production and machine condition monitoring software (PMCMS) is programmed in C# and designed in such a way to support hardware integration, real-time machine conditions monitoring, which is based on condition maintenance approach, maintenance decision suggestions and suitable production strategies as the demand for products keeps changing in a highly competitive environment. PMCMS works with an embedded device which feeds it with data from the various machines being monitored at the workstation, and the data are read at the base station through transmission via a wireless transceiver and stored in a database. A case study was used in the implementation of the developed system, and the results show that it can monitor the machine's health condition effectively by displaying machines' health status, gives repair suggestions to probable faults, decides strategy for both production methods and maintenance, and, thus, can enhance maintenance performance obviously.

Weather monitoring and forecasting over eastern Attica (Greece) in the frame of FLIRE project

NASA Astrophysics Data System (ADS)

Kotroni, Vassiliki; Lagouvardos, Konstantinos; Chrysoulakis, Nektarios; Makropoulos, Christtos; Mimikou, Maria; Papathanasiou, Chrysoula; Poursanidis, Dimitris

2015-04-01

In the frame of FLIRE project a Decision Support System has been built with the aim to support decision making of Civil Protection Agencies and local stakeholders in the area of east Attica (Greece), in the cases of forest fires and floods. In this presentation we focus on a specific action that focuses on the provision of high resolution short-term weather forecasting data as well as of dense meteorological observations over the study area. Both weather forecasts and observations serve as an input in the Weather Information Management Tool (WIMT) of the Decision Support System. We focus on: (a) the description of the adopted strategy for setting-up the operational weather forecasting chain that provides the weather forecasts for the FLIRE project needs, (b) the presentation of the surface network station that provides real-time weather monitoring of the study area and (c) the strategy adopted for issuing smart alerts for thunderstorm forecasting based of real-time lightning observations as well as satellite observations.

An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

PubMed

Fan, Bi; Li, Han-Xiong; Hu, Yong

2016-02-01

Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions.

A National Crop Progress Monitoring and Decision Support System Based on NASA Earth Science Results

NASA Astrophysics Data System (ADS)

di, L.; Yang, Z.

2009-12-01

Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the adjustment of NASS survey data. This presentation will discuss the architecture, Earth observation data, and the crop progress model used in the decision support system.

Towards an Effective Decision Support System for Merapi Volcano (Yogyakarta Region, Indonesia)

NASA Astrophysics Data System (ADS)

Setijadji, L. D.

2011-12-01

The 2010 explosive eruption of Merapi has raised questions on how to develop a near real-time decision support system of multi volcanic hazards (e.g., ash plumes, pyroclastic flow and lahar floods) in populated volcanic terrains such as Yogyakarta region in Indonesia. Despite Merapi has been the most monitored volcano in the nation for a long time, the 2010 eruption behaviors have told us how dynamic a volcano is, and we have to anticipate for any scenarios. The Centre of Volcanology and Geo-hazards Mitigation (PVMBG) has long learned from the well-known Merapi-style eruption (i.e. typically starts with formation of lava dome and is followed by dome-collapse pyroclastic flows) to produce a long-established robust monitoring and prediction system for Merapi. However, the complex magmatic-volcanic system within volcano has proven that Merapi erupted violently in 2010 without a lava dome phase. The existing monitoring instruments which were mainly ground-based geophysical tools were destroyed and in large extent there were times during the crisis that no monitoring system was available in producing near real-time data input. Satellite images data could probably support this mission, but they were not part of existing monitoring systems of PVMBG. Partly as results of this failure, the 2010 eruption took large number of victims (reported loss of life 324) and as much as 320,000 citizens were displaced. The 2010 experience told us that we have to be ready with different styles of eruptions and that the current monitoring system needs to be supported by a reliable decision support system that allow scientists and decision makers to evaluate different scenarios quickly during the crisis, utilizing huge data sets from different instrumentations and platforms. For that purpose we initiated a research which is aimed to study the use of multi data sources such as satellite images and their integration within a Geographic Information System as key elements for a monitoring system during a volcanic eruption crisis and the following events, especially lahar hazards, using the case study of Merapi volcano. Remote sensing is still one of the most cost-effective tools, however the presence of so many different types of Earth Observation (EO) platforms and data make it difficult to select the most appropriate one, especially when we face a limited budget. Data are probably available within several institutions, but so far there is no strong coordination among governmental organizations who deal with geo-hazards. We are still on the progress to evaluate all possible sources of data, their platforms and formats, and building a scenario to use them within an integrative decision support system. We will test and improve the system when we now deal with the lahar flood hazards of Merapi that will likely to be the main hazard threat for people living surrounding Merapi for the next several years.

WETLAND MONITORING AND ASSESSMENT TO SUPPORT DECISION MAKING: A VISION FOR THE FUTURE

EPA Science Inventory

The recent report of the National Research Council on wetland mitigation again highlighted the need for regional watershed evaluation as a context from which to determine the efficacy of past regulatory decisions and to improve the effectiveness of future actions. Collaborative ...

Radiation monitoring systems as a tool for assessment of accidental releases at the Chernobyl and Fukushima NPPs

NASA Astrophysics Data System (ADS)

Shershakov, Vjacheslav; Bulgakov, Vladimir

2013-04-01

The experience gained during mitigation of the consequences of the accidents at the Chernobyl and Fukushima NPPs has shown that what makes different the decision-making in case of nuclear accidents is that the greatest benefit from decision-making can be achieved in the early phase of an accident. Support to such process can be provided only by a real-time decision-making support system. In case of a nuclear accident the analysis of the situation and decision-making is not feasible without an operational radiation monitoring system, international data exchange and automated data processing, and the use of computerized decision-making support systems. With this in mind, in the framework of different international programs on the Chernobyl-related issues numerous projects were undertaken to study and develop a set of methods, algorithms and programs providing effective support to emergency response decision-making, starting from accident occurrence to decision-making regarding countermeasures to mitigate effects of radioactive contamination of the environment. The presentation focuses results of the analysis of radiation monitoring data and, on this basis, refining or, for many short-lived radionuclides, reconstructing the source term, modeling dispersion of radioactivity in the environment and assessing its impacts. The obtained results allowed adding and refining the existing estimates and in some cases reconstructing doses for the public on the territories contaminated as a result of the Chernobyl accident. The activities were implemented in two stages. In the first stage, several scenarios for dispersion of Chernobyl-related radioactivity were developed. For each scenario cesium-137 dispersion was estimated and these estimates were compared with measurement data. In the second stage, the scenario which showed the best agreement of calculations and measurements was used for modeling the dispersion of iodine-131and other short-lived radionuclides. The described approach was used for assessing the consequences at the Fukushima NPP. These results are also provided in the presentation. References 1. Kelly G.N., Ehrhardt J., Shershakov V.M.. Decision Support for Off-Site Emergency Preparedness in Europe. Radiation Protection Dosimetry, Vol. 64 Nos. 1-2, 1996, pp. 129-142. 2. Ehrhardt J., Shershakov V.M. Real-time on-line decision support systems (RODOS) for off-site emergency management following a nuclear accident. EUR 16533, 1996 3. Kelly G.N., Shershakov V.M. (Editors). Environmental contamination, radiation doses and health consequences after the ?hernobyl accident. Radiation Protection Dosimetry. Special Commemorative Issue.Vol. 64, 1996 4. Shershakov V.M. Computer information technology for support of radiation monitoring problems. OECD Proceedings of an International Workshop «Nuclear Emergency Data Management», Zurich, Switzerland, 1998, pp. 377-388 5. Pitkevich V.A., Duba V.V., Ivanov V.K., Tsyb A.F., Shershakov V.M., Golubenkov A.V., Borodin R.V., V.A., Kosykh V.S. Reconstruction of External Dose to the Inhabitants Living in the Contaminated Territory of Russia by the Results of the Accident at the Chernobyl NPP. Health Phys., Vol. 30, No. 1, pp. 54-68, 1995. 6. Shershakov V., Fesenko S., Kryshev I., Semioshkina T. Decision-Aiding Tools for Remediation Strategies. In: Radioactivity in the Environment, Volume 14, Remediation of Contaminated Environments, 2009, pp 41- 120, Elsevier Ltd.

Visualizing Earth Science Data for Environmental Monitoring and Decision Support in Mesoamerica: The SERVIR Project

NASA Astrophysics Data System (ADS)

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

2005-05-01

In 2002 and 2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR). Mesoamerica - composed of the seven Central American countries and the five southernmost states of Mexico - makes up only a small fraction of the world's land surface. However, the region is home to approximately eight percent of the planet's biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Mesoamerica's biological and cultural diversity are severely threatened by human impact and natural disasters including extensive deforestation, illegal logging, water pollution, slash and burn agriculture, earthquakes, hurricanes, drought, and volcanic eruption. NASA Marshall Space Flight Center (NASA/MSFC), together with the University of Alabama in Huntsville (UAH) and the SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters, and better understand both natural and human induced effects. The decision support and environmental monitoring data products are typically formatted as conventional two-dimensional, static and animated imagery. However, in addition to conventional data products and as a major portion of our research, we are employing commercial applications that generate three-dimensional interactive visualizations that allow data products to be viewed from multiple angles and at different scales. One of these is a 15 meter resolution mosaic of the entire Mesoamerican region. This paper gives an overview of the SERVIR project and its associated visualization methods.

A decision support tool for adaptive management of native prairie ecosystems

USGS Publications Warehouse

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

2016-01-01

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

A Review of Decision Support Systems for Smart Homes in the Health Care System.

PubMed

Baumgärtel, Diana; Mielke, Corinna; Haux, Reinhold

2018-01-01

The use of decision support systems for smart homes can provide attractive solutions for challenges that have arisen in the Health Care System due to ageing of society. In order to provide an overview of current research projects in this field, a systematic literature review was performed according to the PRISMA approach. The aims of this work are to provide an overview of current research projects and to update a similar study from 2012. The literature search engines IEEE Xplore and PubMed were used. 23 papers were included. Most of the systems presented are developed for monitoring the patient regardless of their illness. For decision support, mainly rule-based approaches are used.

MonitoringResources.org—Supporting coordinated and cost-effective natural resource monitoring across organizations

USGS Publications Warehouse

Bayer, Jennifer M.; Scully, Rebecca A.; Weltzin, Jake F.

2018-05-21

Natural resource managers who oversee the Nation’s resources require data to support informed decision-making at a variety of spatial and temporal scales that often cross typical jurisdictional boundaries such as states, agency regions, and watersheds. These data come from multiple agencies, programs, and sources, often with their own methods and standards for data collection and organization. Coordinating standards and methods is often prohibitively time-intensive and expensive. MonitoringResources.org offers a suite of tools and resources that support coordination of monitoring efforts, cost-effective planning, and sharing of knowledge among organizations. The website was developed by the Pacific Northwest Aquatic Monitoring Partnership—a collaboration of Federal, state, tribal, local, and private monitoring programs—and the U.S. Geological Survey (USGS), with funding from the Bonneville Power Administration and USGS. It is a key component of a coordinated monitoring and information network.

Monitoring Drought Conditions in the Navajo Nation Using NASA Earth Observations

NASA Technical Reports Server (NTRS)

Ly, Vickie; Gao, Michael; Cary, Cheryl; Turnbull-Appell, Sophie; Surunis, Anton

2016-01-01

The Navajo Nation, a 65,700 sq km Native American territory located in the southwestern United States, has been increasingly impacted by severe drought events and changes in climate. These events are coupled with a lack of domestic water infrastructure and economic resources, leaving approximately one-third of the population without access to potable water in their homes. Current methods of monitoring drought are dependent on state-based monthly Standardized Precipitation Index value maps calculated by the Western Regional Climate Center. However, these maps do not provide the spatial resolution needed to illustrate differences in drought severity across the vast Nation. To better understand and monitor drought events and drought regime changes in the Navajo Nation, this project created a geodatabase of historical climate information specific to the area, and a decision support tool to calculate average Standardized Precipitation Index values for user-specified areas. The tool and geodatabase use Tropical Rainfall Monitoring Mission (TRMM) and Global Precipitation Monitor (GPM) observed precipitation data and Parameter-elevation Relationships on Independent Slopes Model modeled historical precipitation data, as well as NASA's modeled Land Data Assimilation Systems deep soil moisture, evaporation, and transpiration data products. The geodatabase and decision support tool will allow resource managers in the Navajo Nation to utilize current and future NASA Earth observation data for increased decision-making capacity regarding future climate change impact on water resources.

A systematic review and summarization of the recommendations and research surrounding Curriculum-Based Measurement of oral reading fluency (CBM-R) decision rules.

PubMed

Ardoin, Scott P; Christ, Theodore J; Morena, Laura S; Cormier, Damien C; Klingbeil, David A

2013-02-01

Research and policy have established that data are necessary to guide decisions within education. Many of these decisions are made within problem solving and response to intervention frameworks for service delivery. Curriculum-Based Measurement in Reading (CBM-R) is a widely used data collection procedure within those models of service delivery. Although the evidence for CBM-R as a screening and benchmarking procedure has been summarized multiple times in the literature, there is no comprehensive review of the evidence for its application to monitor and evaluate individual student progress. The purpose of this study was to identify and summarize the psychometric and empirical evidence for CBM-R as it is used to monitor and evaluate student progress. There was an emphasis on the recommended number of data points collected during progress monitoring and interpretive guidelines. The review identified 171 journal articles, chapters, and instructional manuals using online search engines and research databases. Recommendations and evidence from 102 documents that met the study criteria were evaluated and summarized. Results indicate that most decision-making practices are based on expert opinion and that there is very limited psychometric or empirical support for such practices. There is a lack of published evidence to support program evaluation and progress monitoring with CBM-R. More research is required to inform data collection procedures and interpretive guidelines. Copyright © 2012 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-01-01

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

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

PubMed

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

2010-03-01

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

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

PubMed

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

2018-03-01

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

Under which conditions, additional monitoring data are worth gathering for improving decision making? Application of the VOI theory in the Bayesian Event Tree eruption forecasting framework

NASA Astrophysics Data System (ADS)

Loschetter, Annick; Rohmer, Jérémy

2016-04-01

Standard and new generation of monitoring observations provide in almost real-time important information about the evolution of the volcanic system. These observations are used to update the model and contribute to a better hazard assessment and to support decision making concerning potential evacuation. The framework BET_EF (based on Bayesian Event Tree) developed by INGV enables dealing with the integration of information from monitoring with the prospect of decision making. Using this framework, the objectives of the present work are i. to propose a method to assess the added value of information (within the Value Of Information (VOI) theory) from monitoring; ii. to perform sensitivity analysis on the different parameters that influence the VOI from monitoring. VOI consists in assessing the possible increase in expected value provided by gathering information, for instance through monitoring. Basically, the VOI is the difference between the value with information and the value without additional information in a Cost-Benefit approach. This theory is well suited to deal with situations that can be represented in the form of a decision tree such as the BET_EF tool. Reference values and ranges of variation (for sensitivity analysis) were defined for input parameters, based on data from the MESIMEX exercise (performed at Vesuvio volcano in 2006). Complementary methods for sensitivity analyses were implemented: local, global using Sobol' indices and regional using Contribution to Sample Mean and Variance plots. The results (specific to the case considered) obtained with the different techniques are in good agreement and enable answering the following questions: i. Which characteristics of monitoring are important for early warning (reliability)? ii. How do experts' opinions influence the hazard assessment and thus the decision? Concerning the characteristics of monitoring, the more influent parameters are the means rather than the variances for the case considered. For the parameters that concern expert setting, the weight attributed to monitoring measurement ω, the mean of thresholds, the economic context and the setting of the decision threshold are very influential. The interest of applying the VOI theory (more precisely the value of imperfect information) in the BET framework was demonstrated as support for helping experts in the setting of the monitoring system or for helping managers to decide the installation of additional monitoring systems. Acknowledgments: This work was carried out in the framework of the project MEDSUV. This project is funded under the call FP7 ENV.2012.6.4-2: Long-term monitoring experiment in geologically active regions of Europe prone to natural hazards: the Supersite concept. Grant agreement n°308665.

Use of microcomputers for planning and managing silviculture habitat relationships.

Treesearch

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

1988-01-01

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

Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems

PubMed Central

Menychtas, Andreas; Tsanakas, Panayiotis

2016-01-01

The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging. PMID:27222731

Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems.

PubMed

Menychtas, Andreas; Tsanakas, Panayiotis; Maglogiannis, Ilias

2016-03-01

The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging.

Real-time decision support systems: the famine early warning system network

USGS Publications Warehouse

Funk, Christopher C.; Verdin, James P.

2010-01-01

A multi-institutional partnership, the US Agency for International Development’s Famine Early Warning System Network (FEWS NET) provides routine monitoring of climatic, agricultural, market, and socioeconomic conditions in over 20 countries. FEWS NET supports and informs disaster relief decisions that impact millions of people and involve billions of dollars. In this chapter, we focus on some of FEWS NET’s hydrologic monitoring tools, with a specific emphasis on combining “low frequency” and “high frequency” assessment tools. Low frequency assessment tools, tied to water and food balance estimates, enable us to evaluate and map long-term tendencies in food security. High frequency assessments are supported by agrohydrologic models driven by satellite rainfall estimates, such as the Water Requirement Satisfaction Index (WRSI). Focusing on eastern Africa, we suggest that both these high and low frequency approaches are necessary to capture the interaction of slow variations in vulnerability and the relatively rapid onset of climatic shocks.

A Digital Framework to Support Providers and Patients in Diabetes Related Behavior Modification.

PubMed

Abidi, Samina; Vallis, Michael; Piccinini-Vallis, Helena; Imran, Syed Ali; Abidi, Syed Sibte Raza

2017-01-01

We present Diabetes Web-Centric Information and Support Environment (D-WISE) that features: (a) Decision support tool to assist family physicians to administer Behavior Modification (BM) strategies to patients; and (b) Patient BM application that offers BM strategies and motivational interventions to engage patients. We take a knowledge management approach, using semantic web technologies, to model the social cognition theory constructs, Canadian diabetes guidelines and BM protocols used locally, in terms of a BM ontology that drives the BM decision support to physicians and BM strategy adherence monitoring and messaging to patients. We present the qualitative analysis of D-WISE usability by both physicians and patients.

Lessons learned from implementing service-oriented clinical decision support at four sites: A qualitative study.

PubMed

Wright, Adam; Sittig, Dean F; Ash, Joan S; Erickson, Jessica L; Hickman, Trang T; Paterno, Marilyn; Gebhardt, Eric; McMullen, Carmit; Tsurikova, Ruslana; Dixon, Brian E; Fraser, Greg; Simonaitis, Linas; Sonnenberg, Frank A; Middleton, Blackford

2015-11-01

To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Airborne Tactical Intent-Based Conflict Resolution Capability

NASA Technical Reports Server (NTRS)

Wing, David J.; Vivona, Robert A.; Roscoe, David A.

2009-01-01

Trajectory-based operations with self-separation involve the aircraft taking the primary role in the management of its own trajectory in the presence of other traffic. In this role, the flight crew assumes the responsibility for ensuring that the aircraft remains separated from all other aircraft by at least a minimum separation standard. These operations are enabled by cooperative airborne surveillance and by airborne automation systems that provide essential monitoring and decision support functions for the flight crew. An airborne automation system developed and used by NASA for research investigations of required functionality is the Autonomous Operations Planner. It supports the flight crew in managing their trajectory when responsible for self-separation by providing monitoring and decision support functions for both strategic and tactical flight modes. The paper focuses on the latter of these modes by describing a capability for tactical intent-based conflict resolution and its role in a comprehensive suite of automation functions supporting trajectory-based operations with self-separation.

Arctic Collaborative Environment: A New Multi-National Partnership for Arctic Science and Decision Support

NASA Technical Reports Server (NTRS)

Laymon, Charles A,; Kress, Martin P.; McCracken, Jeff E.; Spehn, Stephen L.; Tanner, Steve

2011-01-01

The Arctic Collaborative Environment (ACE) project is a new international partnership for information sharing to meet the challenges of addressing Arctic. The goal of ACE is to create an open source, web-based, multi-national monitoring, analysis, and visualization decision-support system for Arctic environmental assessment, management, and sustainability. This paper will describe the concept, system architecture, and data products that are being developed and disseminated among partners and independent users through remote access.

Leveraging Trillions of Pixels for Flood Mitigation Decisions Support in the Rio Salado Basin, Argentina

NASA Astrophysics Data System (ADS)

Sullivan, J.; Routh, D.; Tellman, B.; Doyle, C.; Tomlin, J. N.

2017-12-01

The Rio Salado River Basin in Argentina is an economically important region that generates 25-30 percent of Argentina's grain and meat production. Between 2000-2011, floods in the basin caused nearly US$4.5 billion in losses and affected 5.5 million people. With the goal of developing cost-efficient flood monitoring and prediction capabilities in the Rio Salado Basin to support decision making, Cloud to Street is developing satellite based analytics to cover information gaps and improve monitoring capacity. This talk will showcase the Flood Risk Dashboard developed by Cloud to Street to support monitoring and decision-making at the level of provincial and national water management agencies in the Rio Salado Watershed. The Dashboard is based on analyzing thousands of MODIS, Landsat, and Sentinel scenes in Google Earth Engine to reconstruct the spatial history of flooding in the basin. The tool, iteratively designed with the end-user, shows a history of floodable areas with specific return times, exposed land uses and population, precipitation hyetographs, and spatial and temporal flood trends in the basin. These trends are used to understand both the impact of past flood mitigation investments (i.e. wetland reconstruction) and identify shifting flood risks. Based on this experience, we will also describe best practices on making remote sensing "flood dashboards" for water agencies.

Knowledge base and sensor bus messaging service architecture for critical tsunami warning and decision-support

NASA Astrophysics Data System (ADS)

Sabeur, Z. A.; Wächter, J.; Middleton, S. E.; Zlatev, Z.; Häner, R.; Hammitzsch, M.; Loewe, P.

2012-04-01

The intelligent management of large volumes of environmental monitoring data for early tsunami warning requires the deployment of robust and scalable service oriented infrastructure that is supported by an agile knowledge-base for critical decision-support In the TRIDEC project (TRIDEC 2010-2013), a sensor observation service bus of the TRIDEC system is being developed for the advancement of complex tsunami event processing and management. Further, a dedicated TRIDEC system knowledge-base is being implemented to enable on-demand access to semantically rich OGC SWE compliant hydrodynamic observations and operationally oriented meta-information to multiple subscribers. TRIDEC decision support requires a scalable and agile real-time processing architecture which enables fast response to evolving subscribers requirements as the tsunami crisis develops. This is also achieved with the support of intelligent processing services which specialise in multi-level fusion methods with relevance feedback and deep learning. The TRIDEC knowledge base development work coupled with that of the generic sensor bus platform shall be presented to demonstrate advanced decision-support with situation awareness in context of tsunami early warning and crisis management.

Patchy 'coherence': using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC).

PubMed

Lloyd, Amy; Joseph-Williams, Natalie; Edwards, Adrian; Rix, Andrew; Elwyn, Glyn

2013-09-05

Implementing shared decision making into routine practice is proving difficult, despite considerable interest from policy-makers, and is far more complex than merely making decision support interventions available to patients. Few have reported successful implementation beyond research studies. MAking Good Decisions In Collaboration (MAGIC) is a multi-faceted implementation program, commissioned by The Health Foundation (UK), to examine how best to put shared decision making into routine practice. In this paper, we investigate healthcare professionals' perspectives on implementing shared decision making during the MAGIC program, to examine the work required to implement shared decision making and to inform future efforts. The MAGIC program approached implementation of shared decision making by initiating a range of interventions including: providing workshops; facilitating development of brief decision support tools (Option Grids); initiating a patient activation campaign ('Ask 3 Questions'); gathering feedback using Decision Quality Measures; providing clinical leads meetings, learning events, and feedback sessions; and obtaining executive board level support. At 9 and 15 months (May and November 2011), two rounds of semi-structured interviews were conducted with healthcare professionals in three secondary care teams to explore views on the impact of these interventions. Interview data were coded by two reviewers using a framework derived from the Normalization Process Theory. A total of 54 interviews were completed with 31 healthcare professionals. Partial implementation of shared decision making could be explained using the four components of the Normalization Process Theory: 'coherence,' 'cognitive participation,' 'collective action,' and 'reflexive monitoring.' Shared decision making was integrated into routine practice when clinical teams shared coherent views of role and purpose ('coherence'). Shared decision making was facilitated when teams engaged in developing and delivering interventions ('cognitive participation'), and when those interventions fit with existing skill sets and organizational priorities ('collective action') resulting in demonstrable improvements to practice ('reflexive monitoring'). The implementation process uncovered diverse and conflicting attitudes toward shared decision making; 'coherence' was often missing. The study showed that implementation of shared decision making is more complex than the delivery of patient decision support interventions to patients, a portrayal that often goes unquestioned. Normalizing shared decision making requires intensive work to ensure teams have a shared understanding of the purpose of involving patients in decisions, and undergo the attitudinal shifts that many health professionals feel are required when comprehension goes beyond initial interpretations. Divergent views on the value of engaging patients in decisions remain a significant barrier to implementation.

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.

Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

USGS Publications Warehouse

Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James

2015-01-01

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

Analytical approaches to quality assurance and quality control in rangeland monitoring data

USDA-ARS?s Scientific Manuscript database

Producing quality data to support land management decisions is the goal of every rangeland monitoring program. However, the results of quality assurance (QA) and quality control (QC) efforts to improve data quality are rarely reported. The purpose of QA and QC is to prevent and describe non-sampling...

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

ERIC Educational Resources Information Center

Ball, Carrie R.; Christ, Theodore J.

2012-01-01

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

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

PubMed

Peterson, James T; Freeman, Mary C

2016-12-01

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

Autonomous Task Management and Decision Support Tools

NASA Technical Reports Server (NTRS)

Burian, Barbara

2017-01-01

For some time aircraft manufacturers and researchers have been pursuing mechanisms for reducing crew workload and providing better decision support to the pilots, especially during non-normal situations. Some previous attempts to develop task managers or pilot decision support tools have not resulted in robust and fully functional systems. However, the increasing sophistication of sensors and automated reasoners, and the exponential surge in the amount of digital data that is now available create a ripe environment for the development of a robust, dynamic, task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This presentation will discuss the many significant challenges and issues associated with the development and functionality of such a system for use on the aircraft flight deck.

eHealth in the future of medications management: personalisation, monitoring and adherence.

PubMed

Car, Josip; Tan, Woan Shin; Huang, Zhilian; Sloot, Peter; Franklin, Bryony Dean

2017-04-05

Globally, healthcare systems face major challenges with medicines management and medication adherence. Medication adherence determines medication effectiveness and can be the single most effective intervention for improving health outcomes. In anticipation of growth in eHealth interventions worldwide, we explore the role of eHealth in the patients' medicines management journey in primary care, focusing on personalisation and intelligent monitoring for greater adherence. eHealth offers opportunities to transform every step of the patient's medicines management journey. From booking appointments, consultation with a healthcare professional, decision-making, medication dispensing, carer support, information acquisition and monitoring, to learning about medicines and their management in daily life. It has the potential to support personalisation and monitoring and thus lead to better adherence. For some of these dimensions, such as supporting decision-making and providing reminders and prompts, evidence is stronger, but for many others more rigorous research is urgently needed. Given the potential benefits and barriers to eHealth in medicines management, a fine balance needs to be established between evidence-based integration of technologies and constructive experimentation that could lead to a game-changing breakthrough. A concerted, transdisciplinary approach adapted to different contexts, including low- and middle-income contries is required to realise the benefits of eHealth at scale.

The neural system of metacognition accompanying decision-making in the prefrontal cortex

PubMed Central

Qiu, Lirong; Su, Jie; Ni, Yinmei; Bai, Yang; Zhang, Xuesong; Li, Xiaoli

2018-01-01

Decision-making is usually accompanied by metacognition, through which a decision maker monitors uncertainty regarding a decision and may then consequently revise the decision. These metacognitive processes can occur prior to or in the absence of feedback. However, the neural mechanisms of metacognition remain controversial. One theory proposes an independent neural system for metacognition in the prefrontal cortex (PFC); the other, that metacognitive processes coincide and overlap with the systems used for the decision-making process per se. In this study, we devised a novel “decision–redecision” paradigm to investigate the neural metacognitive processes involved in redecision as compared to the initial decision-making process. The participants underwent a perceptual decision-making task and a rule-based decision-making task during functional magnetic resonance imaging (fMRI). We found that the anterior PFC, including the dorsal anterior cingulate cortex (dACC) and lateral frontopolar cortex (lFPC), were more extensively activated after the initial decision. The dACC activity in redecision positively scaled with decision uncertainty and correlated with individual metacognitive uncertainty monitoring abilities—commonly occurring in both tasks—indicating that the dACC was specifically involved in decision uncertainty monitoring. In contrast, the lFPC activity seen in redecision processing was scaled with decision uncertainty reduction and correlated with individual accuracy changes—positively in the rule-based decision-making task and negatively in the perceptual decision-making task. Our results show that the lFPC was specifically involved in metacognitive control of decision adjustment and was subject to different control demands of the tasks. Therefore, our findings support that a separate neural system in the PFC is essentially involved in metacognition and further, that functions of the PFC in metacognition are dissociable. PMID:29684004

Difficult decisions: Migration from Small Island Developing States under climate change

NASA Astrophysics Data System (ADS)

Kelman, Ilan

2015-04-01

The impacts of climate change on Small Island Developing States (SIDS) are leading to discussions regarding decision-making about the potential need to migrate. Despite the situation being well-documented, with many SIDS aiming to raise the topic to prominence and to take action for themselves, limited support and interest has been forthcoming from external sources. This paper presents, analyzes, and critiques a decision-making flowchart to support actions for SIDS dealing with climate change-linked migration. The flowchart contributes to identifying the pertinent topics to consider and the potential support needed to implement decision-making. The flowchart has significant limitations and there are topics which it cannot resolve. On-the-ground considerations include who decides, finances, implements, monitors, and enforces each decision. Additionally, views within communities differ, hence mechanisms are needed for dealing with differences, while issues to address include moral and legal blame for any climate change-linked migration, the ultimate goal of the decision-making process, the wider role of migration in SIDS communities and the right to judge decision-making and decisions. The conclusions summarize the paper, emphasizing the importance of considering contexts beyond climate change and multiple SIDS voices.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Monitoring supports performance in a dual-task paradigm involving a risky decision-making task and a working memory task

PubMed Central

Gathmann, Bettina; Schiebener, Johannes; Wolf, Oliver T.; Brand, Matthias

2015-01-01

Performing two cognitively demanding tasks at the same time is known to decrease performance. The current study investigates the underlying executive functions of a dual-tasking situation involving the simultaneous performance of decision making under explicit risk and a working memory task. It is suggested that making a decision and performing a working memory task at the same time should particularly require monitoring—an executive control process supervising behavior and the state of processing on two tasks. To test the role of a supervisory/monitoring function in such a dual-tasking situation we investigated 122 participants with the Game of Dice Task plus 2-back task (GDT plus 2-back task). This dual task requires participants to make decisions under risk and to perform a 2-back working memory task at the same time. Furthermore, a task measuring a set of several executive functions gathered in the term concept formation (Modified Card Sorting Test, MCST) and the newly developed Balanced Switching Task (BST), measuring monitoring in particular, were used. The results demonstrate that concept formation and monitoring are involved in the simultaneous performance of decision making under risk and a working memory task. In particular, the mediation analysis revealed that BST performance partially mediates the influence of MCST performance on the GDT plus 2-back task. These findings suggest that monitoring is one important subfunction for superior performance in a dual-tasking situation including decision making under risk and a working memory task. PMID:25741308

Characterizing the Breadth and Depth of Volunteer Water Monitoring Programs in the United States.

PubMed

Stepenuck, Kristine F; Genskow, Kenneth D

2018-01-01

A survey of 345 volunteer water monitoring programs in the United States was conducted to document their characteristics, and perceived level of support for data to inform natural resource management or policy decisions. The response rate of 86% provided information from 46 states. Programs represented a range of ages, budgets, objectives, scopes, and level of quality assurance, which influenced data uses and perceived support by sponsoring agency administrators and external decision makers. Most programs focused on rivers, streams, and lakes. Programs had not made substantial progress to develop EPA or state-approved quality assurance plans since 1998, with only 48% reporting such plans. Program coordinators reported feeling slightly more support for data to be used for management as compared to policy decisions. Programs with smaller budgets may be at particular risk of being perceived to lack credibility due to failure to develop quality assurance plans. Over half of programs identified as collaborative, in that volunteers assisted scientists in program design, data analysis and/or dissemination of results. Just under a third were contributory, in which volunteers primarily collected data in a scientist-defined program. Recommendations to improve perceived data credibility, and to augment limited budgets include developing quality assurance plans and gaining agency approval, and developing partnerships with other organizations conducting monitoring in the area to share resources and knowledge. Funding agencies should support development of quality assurance plans to help ensure data credibility. Service providers can aid in plan development by providing training to program staff over time to address high staff turnover rates.

Characterizing the Breadth and Depth of Volunteer Water Monitoring Programs in the United States

NASA Astrophysics Data System (ADS)

Stepenuck, Kristine F.; Genskow, Kenneth D.

2018-01-01

A survey of 345 volunteer water monitoring programs in the United States was conducted to document their characteristics, and perceived level of support for data to inform natural resource management or policy decisions. The response rate of 86% provided information from 46 states. Programs represented a range of ages, budgets, objectives, scopes, and level of quality assurance, which influenced data uses and perceived support by sponsoring agency administrators and external decision makers. Most programs focused on rivers, streams, and lakes. Programs had not made substantial progress to develop EPA or state-approved quality assurance plans since 1998, with only 48% reporting such plans. Program coordinators reported feeling slightly more support for data to be used for management as compared to policy decisions. Programs with smaller budgets may be at particular risk of being perceived to lack credibility due to failure to develop quality assurance plans. Over half of programs identified as collaborative, in that volunteers assisted scientists in program design, data analysis and/or dissemination of results. Just under a third were contributory, in which volunteers primarily collected data in a scientist-defined program. Recommendations to improve perceived data credibility, and to augment limited budgets include developing quality assurance plans and gaining agency approval, and developing partnerships with other organizations conducting monitoring in the area to share resources and knowledge. Funding agencies should support development of quality assurance plans to help ensure data credibility. Service providers can aid in plan development by providing training to program staff over time to address high staff turnover rates.

Advancing beyond the system: telemedicine nurses' clinical reasoning using a computerised decision support system for patients with COPD - an ethnographic study.

PubMed

Barken, Tina Lien; Thygesen, Elin; Söderhamn, Ulrika

2017-12-28

Telemedicine is changing traditional nursing care, and entails nurses performing advanced and complex care within a new clinical environment, and monitoring patients at a distance. Telemedicine practice requires complex disease management, advocating that the nurses' reasoning and decision-making processes are supported. Computerised decision support systems are being used increasingly to assist reasoning and decision-making in different situations. However, little research has focused on the clinical reasoning of nurses using a computerised decision support system in a telemedicine setting. Therefore, the objective of the study is to explore the process of telemedicine nurses' clinical reasoning when using a computerised decision support system for the management of patients with chronic obstructive pulmonary disease. The factors influencing the reasoning and decision-making processes were investigated. In this ethnographic study, a combination of data collection methods, including participatory observations, the think-aloud technique, and a focus group interview was employed. Collected data were analysed using qualitative content analysis. When telemedicine nurses used a computerised decision support system for the management of patients with complex, unstable chronic obstructive pulmonary disease, two categories emerged: "the process of telemedicine nurses' reasoning to assess health change" and "the influence of the telemedicine setting on nurses' reasoning and decision-making processes". An overall theme, termed "advancing beyond the system", represented the connection between the reasoning processes and the telemedicine work and setting, where being familiar with the patient functioned as a foundation for the nurses' clinical reasoning process. In the telemedicine setting, when supported by a computerised decision support system, nurses' reasoning was enabled by the continuous flow of digital clinical data, regular video-mediated contact and shared decision-making with the patient. These factors fostered an in-depth knowledge of the patients and acted as a foundation for the nurses' reasoning process. Nurses' reasoning frequently advanced beyond the computerised decision support system recommendations. Future studies are warranted to develop more accurate algorithms, increase system maturity, and improve the integration of the digital clinical information with clinical experiences, to support telemedicine nurses' reasoning process.

Home blood pressure monitoring and self-titration of antihypertensive medications: Proposed patient selection criteria.

PubMed

Hill, James R

2016-05-01

Recent studies have demonstrated that home blood pressure monitoring (HBPM), coupled with self-titration of medications is a viable intervention to control hypertension. There are currently no established criteria to evaluate patients for inclusion in such a program. The purpose of this discussion is to propose criteria for determining if a patient is appropriate to participate in a program of HBPM and self-titration. Inclusion criteria for two self-titration trials were examined, and additional factors in clinical practice were identified and discussed. Additional selection criteria were proposed to support the decision to enroll a patient in an antihypertensive self-titration program. Inclusion criteria from self-titration trials provide a reasonable starting point for choosing appropriate patients in clinical practice, but additional research is necessary. Adaptation of these criteria and consideration of the identified factors can be used to develop decision support instruments. Such instruments should be evaluated for effectiveness and reliability prior to use in clinical practice. HBPM combined with self-titration is an effective patient-centered approach for hypertension management. Decision support instruments to determine appropriate patients are necessary for safe and effective use in clinical practice. ©2015 American Association of Nurse Practitioners.

Monitoring Citrus Soil Moisture and Nutrients Using an IoT Based System.

PubMed

Zhang, Xueyan; Zhang, Jianwu; Li, Lin; Zhang, Yuzhu; Yang, Guocai

2017-02-23

Chongqing mountain citrus orchard is one of the main origins of Chinese citrus. Its planting terrain is complex and soil parent material is diverse. Currently, the citrus fertilization, irrigation and other management processes still have great blindness. They usually use the same pattern and the same formula rather than considering the orchard terrain features, soil differences, species characteristics and the state of tree growth. With the help of the ZigBee technology, artificial intelligence and decision support technology, this paper has developed the research on the application technology of agricultural Internet of Things for real-time monitoring of citrus soil moisture and nutrients as well as the research on the integration of fertilization and irrigation decision support system. Some achievements were obtained including single-point multi-layer citrus soil temperature and humidity detection wireless sensor nodes and citrus precision fertilization and irrigation management decision support system. They were applied in citrus base in the Three Gorges Reservoir Area. The results showed that the system could help the grower to scientifically fertilize or irrigate, improve the precision operation level of citrus production, reduce the labor cost and reduce the pollution caused by chemical fertilizer.

Elements of an environmental decision support system for seasonal wetland salt management in a river basin subjected to water quality regulation

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

Quinn, N.W.T.

Seasonally managed wetlands in the Grasslands Basin on the west-side of California's San Joaquin Valley provide food and shelter for migratory wildfowl during winter months and sport for waterfowl hunters during the annual duck season. Surface water supply to these wetlands contain salt which, when drained to the San Joaquin River during the annual drawdown period, can negatively impact water quality and cause concern to downstream agricultural riparian water diverters. Recent environmental regulation, limiting discharges salinity to the San Joaquin River and primarily targeting agricultural non-point sources, now also targets return flows from seasonally managed wetlands. Real-time water quality managementmore » has been advocated as a means of continuously matching salt loads discharged from agricultural, wetland and municipal operations to the assimilative capacity of the San Joaquin River. Past attempts to build environmental monitoring and decision support systems (EDSS's) to implement this concept have enjoyed limited success for reasons that are discussed in this paper. These reasons are discussed in the context of more general challenges facing the successful implementation of a comprehensive environmental monitoring, modelling and decision support system for the San Joaquin River Basin.« less

The development of control and monitoring system on marine current renewable energy Case study: strait of Toyapakeh - Nusa Penida, Bali

NASA Astrophysics Data System (ADS)

Arief, I. S.; Suherman, I. H.; Wardani, A. Y.; Baidowi, A.

2017-05-01

Control and monitoring system is a continuous process of securing the asset in the Marine Current Renewable Energy. A control and monitoring system is existed each critical components which is embedded in Failure Mode Effect Analysis (FMEA) method. As the result, the process in this paper developed through a matrix sensor. The matrix correlated to critical components and monitoring system which supported by sensors to conduct decision-making.

Curriculum-Based Measurement of Reading: Is 6 Weeks of Daily Progress Monitoring Enough?

ERIC Educational Resources Information Center

Thornblad, Shannon C.; Christ, Theodore J.

2014-01-01

Curriculum-based measurement of reading (CBM-R) is used in research and practice to estimate the level and trend of student achievement. Although there is limited empirical or psychometric support to guide CBM-R progress monitoring practices, derived trend estimates are used to inform a variety of educational decisions including evaluations of…

Coupling of phenological information and simulated vegetation index time series: Limitations and potentials for the assessment and monitoring of soil erosion risk

USDA-ARS?s Scientific Manuscript database

Monitoring of agricultural used soils at frequent intervals is needed to get a sufficient understanding of soil erosion processes. This is crucial to support decision making and refining soil policies especially in the context of climate change. Along with rainfall erosivity, soil coverage by vegeta...

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

Treesearch

Gregory Elmes; Thomas Millette; Charles B. Yuill

1991-01-01

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

Organisational capacity and chronic disease care: an Australian general practice perspective.

PubMed

Proudfoot, Judith; Infante, Fernando; Holton, Christine; Powell-Davies, Gawaine; Bubner, Tanya; Beilby, Justin; Harris, Mark

2007-04-01

Although we are rapidly improving our understanding of how to manage patients with chronic illness in Australian general practice, many patients are still receiving suboptimal care. General practices have limited organisational capacity to provide the structured care that is required for managing chronic conditions: regular monitoring, decision support, patient recall, supporting patient self management, team work, and information management. This requires a shift away from episodic, acute models. Overseas research has shown that areas such as team work, clinical information systems, decision support, linkages and leadership are also important in managing chronic illness, but we do not know which of these are most important in Australia.

Flight deck engine advisor

NASA Technical Reports Server (NTRS)

Shontz, W. D.; Records, R. M.; Antonelli, D. R.

1992-01-01

The focus of this project is on alerting pilots to impending events in such a way as to provide the additional time required for the crew to make critical decisions concerning non-normal operations. The project addresses pilots' need for support in diagnosis and trend monitoring of faults as they affect decisions that must be made within the context of the current flight. Monitoring and diagnostic modules developed under the NASA Faultfinder program were restructured and enhanced using input data from an engine model and real engine fault data. Fault scenarios were prepared to support knowledge base development activities on the MONITAUR and DRAPhyS modules of Faultfinder. An analysis of the information requirements for fault management was included in each scenario. A conceptual framework was developed for systematic evaluation of the impact of context variables on pilot action alternatives as a function of event/fault combinations.

ENABLING SMART MANUFACTURING TECHNOLOGIES FOR DECISION-MAKING SUPPORT

PubMed Central

Helu, Moneer; Libes, Don; Lubell, Joshua; Lyons, Kevin; Morris, KC

2017-01-01

Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and simulation that generate more and better intelligence about manufacturing systems. However, challenges and barriers have impeded the adoption of smart manufacturing technologies. To begin to address this need, this paper defines requirements for data-driven decision making in manufacturing based on a generalized description of decision making. Using these requirements, we then focus on identifying key barriers that prevent the development and use of data-driven decision making in industry as well as examples of technologies and standards that have the potential to overcome these barriers. The goal of this research is to promote a common understanding among the manufacturing community that can enable standardization efforts and innovation needed to continue adoption and use of smart manufacturing technologies. PMID:28649678

Joint Command Decision Support for the 21st Century (JCDS 21) Technology Demonstration (TD) Project: Concept of Operations (CONOPs)

DTIC Science & Technology

2008-04-08

decision making. It 29 identified that it is equally critical for a Command and Control system to facilitate temporal mixing (the ability to integrate...Decision Superiority. They might well be characterized as a set of stocks. It follows that a holistic appreciation, continuous monitoring of market ...retained the following working defintion of EBO: “Operations designed to influence the long- or short-term state of a system through the achievement of

Prefrontal cortex contributions to episodic retrieval monitoring and evaluation.

PubMed

Cruse, Damian; Wilding, Edward L

2009-11-01

Although the prefrontal cortex (PFC) plays roles in episodic memory judgments, the specific processes it supports are not understood fully. Event-related potential (ERP) studies of episodic retrieval have revealed an electrophysiological modulation - the right-frontal ERP old/new effect - which is thought to reflect activity in PFC. The functional significance of this old/new effect remains a matter of debate, and this study was designed to test two accounts: (i) that the effect indexes processes linked to the monitoring or evaluation of the products of retrieval in service of task demands, or (ii) that it indexes the number of internal decisions required for a task judgment. Participants studied words in one of two colours. In a subsequent retrieval task, old (studied) and new words were presented in a neutral colour. Participants made initial old/new judgments, along with study colour judgments to words thought to be old. They also indicated their confidence (high/low) in the colour decision. Right-frontal ERP old/new effects were larger for high than for low confidence correct colour judgments, and the magnitude of the right-frontal effect was correlated with the proportions of low confidence judgments that were made. Because the numbers of decisions associated with these response categories are equivalent, these findings do not support a decision-based account of the right-frontal ERP old/new effect. Rather, the correlation between confidence and the magnitude of the effect links it with retrieval monitoring and evaluation processes.

A mobile and web-based clinical decision support and monitoring system for diabetes mellitus patients in primary care: a study protocol for a randomized controlled trial.

PubMed

Kart, Özge; Mevsim, Vildan; Kut, Alp; Yürek, İsmail; Altın, Ayşe Özge; Yılmaz, Oğuz

2017-11-29

Physicians' guideline use rates for diagnosis, treatment and monitoring of diabetes mellitus (DM) is very low. Time constraints, patient overpopulation, and complex guidelines require alternative solutions for real time patient monitoring. Rapidly evolving e-health technology combined with clinical decision support and monitoring systems (CDSMS) provides an effective solution to these problems. The purpose of the study is to develop a user-friendly, comprehensive, fully integrated web and mobile-based Clinical Decision Support and Monitoring System (CDSMS) for the screening, diagnosis, treatment, and monitoring of DM diseases which is used by physicians and patients in primary care and to determine the effectiveness of the system. The CDSMS will be based on evidence-based guidelines for DM disease. A web and mobile-based application will be developed in which the physician will remotely monitor patient data through mobile applications in real time. The developed CDSMS will be tested in two stages. In the first stage, the usability, understandability, and adequacy of the application will be determined. Five primary care physicians will use the developed application for at least 16 DM patients. Necessary improvements will be made according to physician feedback. In the second phase, a parallel, single-blind, randomized controlled trial will be implemented. DM diagnosed patients will be recruited for the CDSMS trial by their primary care physicians. Ten physicians and their 439 patients will be involved in the study. Eligible participants will be assigned to intervention and control groups with simple randomization. The significance level will be accepted as p < 0.05. In the intervention group, the system will make recommendations on patient monitoring, diagnosis, and treatment. These recommendations will be implemented at the physician's discretion. Patients in the control group will be treated by physicians according to current DM treatment standards. Patients in both groups will be monitored for 6 months. Patient data will be compared between 0th and 6th month of the study. . Clinical and laboratory outcomes will be assessed in person while others will be self-assessed online. The developed system will be the first of its kind to utilize evidence based guidelines to provide health services to DM patients. ClinicalTrials.gov NCT02917226 . 28 September 2016.

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

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

PubMed

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

2016-08-03

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

Unmanned aircraft systems for transportation decision support.

DOT National Transportation Integrated Search

2016-11-30

Our nation relies on accurate geospatial information to map, measure, and monitor transportation infrastructure and the surrounding landscapes. This project focused on the application of Unmanned Aircraft systems (UAS) as a novel tool for improving e...

Sure I'm Sure: Prefrontal Oscillations Support Metacognitive Monitoring of Decision Making.

PubMed

Wokke, Martijn E; Cleeremans, Axel; Ridderinkhof, K Richard

2017-01-25

Successful decision making critically involves metacognitive processes such as monitoring and control of our decision process. Metacognition enables agents to modify ongoing behavior adaptively and determine what to do next in situations in which external feedback is not (immediately) available. Despite the importance of metacognition for many aspects of life, little is known about how our metacognitive system operates or about what kind of information is used for metacognitive (second-order) judgments. In particular, it remains an open question whether metacognitive judgments are based on the same information as first-order decisions. Here, we investigated the relationship between metacognitive performance and first-order task performance by recording EEG signals while participants were asked to make a "diagnosis" after seeing a sample of fictitious patient data (a complex pattern of colored moving dots of different sizes). To assess metacognitive performance, participants provided an estimate about the quality of their diagnosis on each trial. Results demonstrate that the information that contributes to first-order decisions differs from the information that supports metacognitive judgments. Further, time-frequency analyses of EEG signals reveal that metacognitive performance is associated specifically with prefrontal theta-band activity. Together, our findings are consistent with a hierarchical model of metacognition and suggest a crucial role for prefrontal oscillations in metacognitive performance. Monitoring and control of our decision process (metacognition) is a crucial aspect of adaptive decision making. Crucially, metacognitive skills enable us to adjust ongoing behavior and determine future decision making when immediate feedback is not available. In the present study, we constructed a "diagnosis task" that allowed us to assess in what way first-order task performance and metacognition are related to each other. Results demonstrate that the contribution of sensory evidence (size, color, and motion direction) differs between first- and second-order decision making. Further, our results indicate that metacognitive performance specifically is orchestrated by means of prefrontal theta oscillations. Together, our findings suggest a hierarchical model of metacognition. Copyright © 2017 the authors 0270-6474/17/370781-09$15.00/0.

Intelligent instrumentation applied in environment management

NASA Astrophysics Data System (ADS)

Magheti, Mihnea I.; Walsh, Patrick; Delassus, Patrick

2005-06-01

The use of information and communications technology in environment management and research has witnessed a renaissance in recent years. From optical sensor technology, expert systems, GIS and communications technologies to computer aided harvesting and yield prediction, these systems are increasable used for applications developing in the management sector of natural resources and biodiversity. This paper presents an environmental decision support system, used to monitor biodiversity and present a risk rating for the invasion of pests into the particular systems being examined. This system will utilise expert mobile technology coupled with artificial intelligence and predictive modelling, and will emphasize the potential for expansion into many areas of intelligent remote sensing and computer aided decision-making for environment management or certification. Monitoring and prediction in natural systems, harnessing the potential of computing and communication technologies is an emerging technology within the area of environmental management. This research will lead to the initiation of a hardware and software multi tier decision support system for environment management allowing an evaluation of areas for biodiversity or areas at risk from invasive species, based upon environmental factors/systems.

A Regional Monitoring and Visualization System for Decision Support and Disaster Management Applications for the Mesoamerican Biological Corridor and Beyond

NASA Technical Reports Server (NTRS)

Irwin, Daniel

2002-01-01

The Mesoamerican Biological Corridor (MBC)-a network of managed and protected areas extending from Mexico to Columbia-is a crucial initiative for the Mesoamerican region, with a central development concept of integrating conservation and sustainable use of biodiversity within the framework of sustainable economic development. The MBC is of particular importance to the Central American Commission for Environment and Development (CCAD), which is comprised of the environmental ministers from the seven Central American countries. Responsible for determining priority areas for action in the corridor, CCAD decision makers require current and accurate information, and access to the dynamic knowledge of the changes in the MBC such as deforestation hotspots, fires, and the effects of natural disasters. Currently this information is not integrated and in disparate locations throughout the region and the world. Leveraging NASA technology, satellite data, and capability, we propose to team with the World Bank and the CCAD to develop a regional monitoring and visualization system-with central nodes at the NASA/Marshall Space Flight Center and at CCAD headquarters. This system will assimilate NASA spatial datasets (e.g. MODIS, Landsat, etc.), spatial data from other sources (commercial and public-domain), and ancillary data developed in each of the seven Central American countries (soils, transportation networks, biodiversity indicator maps, etc.). The system will function as a "virtual dashboard" for monitoring the MBC and provide the critical decision support tools for CCAD decision makers. The CCAD central node will also serve as a high-tech showcase for the corridor among the international community, other decision-makers, the media, and students.

Situation-Assessment And Decision-Aid Production-Rule Analysis System For Nuclear Plant Monitoring And Emergency Preparedness

NASA Astrophysics Data System (ADS)

Gvillo, D.; Ragheb, M.; Parker, M.; Swartz, S.

1987-05-01

A Production-Rule Analysis System is developed for Nuclear Plant Monitoring. The signals generated by the Zion-1 Plant are considered. A Situation-Assessment and Decision-Aid capability is provided for monitoring the integrity of the Plant Radiation, the Reactor Coolant, the Fuel Clad, and the Containment Systems. A total of 41 signals are currently fed as facts to an Inference Engine functioning in the backward-chaining mode and built along the same structure as the E-Mycin system. The Goal-Tree constituting the Knowledge Base was generated using a representation in the form of Fault Trees deduced from plant procedures information. The system is constructed in support of the Data Analysis and Emergency Preparedness tasks at the Illinois Radiological Emergency Assessment Center (REAC).

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

Research on tobacco enterprise spatial decision support system based on GIS

NASA Astrophysics Data System (ADS)

Mei, Xin; Cui, Weihong

2006-10-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique taking GIS as representation to construct spatial decision support system of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision is given. At last the example of tobacco enterprise spatial CRM (client relation management) system is set up.

Global Operational Remotely Sensed Evapotranspiration System for Water Resources Management: Case Study for the State of New Mexico

NASA Astrophysics Data System (ADS)

Halverson, G. H.; Fisher, J.; Magnuson, M.; John, L.

2017-12-01

An operational system to produce and disseminate remotely sensed evapotranspiration using the PT-JPL model and support its analysis and use in water resources decision making is being integrated into the New Mexico state government. A partnership between the NASA Western Water Applications Office (WWAO), the Jet Propulsion Laboratory (JPL), and the New Mexico Office of the State Engineer (NMOSE) has enabled collaboration with a variety of state agencies to inform decision making processes for agriculture, rangeland, and forest management. This system improves drought understanding and mobilization, litigation support, and economic, municipal, and ground-water planning through interactive mapping of daily rates of evapotranspiration at 1 km spatial resolution with near real-time latency. This is facilitated by daily remote sensing acquisitions of land-surface temperature and near-surface air temperature and humidity from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite as well as the short-term composites of Normalized Difference Vegetation Index (NDVI) and albedo provided by MODIS. Incorporating evapotranspiration data into agricultural water management better characterizes imbalances between water requirements and supplies. Monitoring evapotranspiration over rangeland areas improves remediation and prevention of aridification. Monitoring forest evapotranspiration improves wildlife management and response to wildfire risk. Continued implementation of this decision support system should enhance water and food security.

REVIEW OF THE RADNET AIR MONITORING NETWORK ...

EPA Pesticide Factsheets

RadNet, formerly known as ERAMS, has been operating since the 1970's, monitoring environmental radiation across the country, supporting responses to radiological emergencies, and providing important information on background levels of radiation in the environment. The original purpose of the system was to monitor fallout from weapons testing. Even though upgrades to and reconfiguration of the system have been planned for some time, the events of 9/11/01 gave impetus to a thorough upgrade of RadNet, primarily directed at providing more timely data and covering a larger portion of the nation's population. Moreover, the demands upon RadNet are now based upon homeland security support in addition to existing EPA monitoring responsibilities. Beginning in FY05 and continuing into FY13 up to135 near real-time air monitors will be put into operation across the country to provide decision making-data to EPA officials. Data will be transmitted from the monitors in all 50 states to a central database at the National Air and Radiation Environmental Laboratory (NAREL) in Montgomery, Alabama. The data will then be assessed and verified and made available to federal and state officials and, eventually, the public. A data flow model is being constructed to provide the most effective and efficient use of verified data obtained from the new radNet system The objective of the near-real time air monitoring component of RadNet is to provide verified decision-making data to fed

The Automated Logistics Element Planning System (ALEPS)

NASA Technical Reports Server (NTRS)

Schwaab, Douglas G.

1991-01-01

The design and functions of ALEPS (Automated Logistics Element Planning System) is a computer system that will automate planning and decision support for Space Station Freedom Logistical Elements (LEs) resupply and return operations. ALEPS provides data management, planning, analysis, monitoring, interfacing, and flight certification for support of LE flight load planning activities. The prototype ALEPS algorithm development is described.

Geographic Freedom

NASA Technical Reports Server (NTRS)

2000-01-01

Kennedy Space Center's need to conduct real-time monitoring of Space Shuttle operations led to the development of Netlander Inc.'s JTouch system. The technology behind JTouch allows engineers to view Space Shuttle and ground support data from any desktop computer using a web browser. Companies can make use of JTouch to better monitor locations scattered around the world, increasing decision-making speed and reducing travel costs for site visits.

An expert system/ion trap mass spectrometry approach for life support systems monitoring

NASA Technical Reports Server (NTRS)

Palmer, Peter T.; Wong, Carla M.; Yost, Richard A.; Johnson, Jodie V.; Yates, Nathan A.; Story, Michael

1992-01-01

Efforts to develop sensor and control system technology to monitor air quality for life support have resulted in the development and preliminary testing of a concept based on expert systems and ion trap mass spectrometry (ITMS). An ITMS instrument provides the capability to identify and quantitate a large number of suspected contaminants at trace levels through the use of a variety of multidimensional experiments. An expert system provides specialized knowledge for control, analysis, and decision making. The system is intended for real-time, on-line, autonomous monitoring of air quality. The key characteristics of the system, performance data and analytical capabilities of the ITMS instrument, the design and operation of the expert system, and results from preliminary testing of the system for trace contaminant monitoring are described.

Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans

PubMed Central

Bornstein, Aaron M.; Daw, Nathaniel D.

2013-01-01

How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward — such as when planning routes using a cognitive map or chess moves using predicted countermoves — and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. PMID:24339770

AERO: A Decision Support Tool for Wind Erosion Assessment in Rangelands and Croplands

NASA Astrophysics Data System (ADS)

Galloza, M.; Webb, N.; Herrick, J.

2015-12-01

Wind erosion is a key driver of global land degradation, with on- and off-site impacts on agricultural production, air quality, ecosystem services and climate. Measuring rates of wind erosion and dust emission across land use and land cover types is important for quantifying the impacts and identifying and testing practical management options. This process can be assisted by the application of predictive models, which can be a powerful tool for land management agencies. The Aeolian EROsion (AERO) model, a wind erosion and dust emission model interface provides access by non-expert land managers to a sophisticated wind erosion decision-support tool. AERO incorporates land surface processes and sediment transport equations from existing wind erosion models and was designed for application with available national long-term monitoring datasets (e.g. USDI BLM Assessment, Inventory and Monitoring, USDA NRCS Natural Resources Inventory) and monitoring protocols. Ongoing AERO model calibration and validation are supported by geographically diverse data on wind erosion rates and land surface conditions collected by the new National Wind Erosion Research Network. Here we present the new AERO interface, describe parameterization of the underpinning wind erosion model, and provide a summary of the model applications across agricultural lands and rangelands in the United States.

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

PubMed

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

Murphy, Elizabeth Drummond

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

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

USGS Publications Warehouse

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

2006-01-01

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

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review.

PubMed

Roshanov, Pavel S; Misra, Shikha; Gerstein, Hertzel C; Garg, Amit X; Sebaldt, Rolf J; Mackay, Jean A; Weise-Kelly, Lorraine; Navarro, Tamara; Wilczynski, Nancy L; Haynes, R Brian

2011-08-03

The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations). We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes. Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported. A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.

Computerized clinical decision support systems for chronic disease management: A decision-maker-researcher partnership systematic review

PubMed Central

2011-01-01

Background The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations). Methods We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes. Results Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported. Conclusions A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes. PMID:21824386

Decision Support Tools Evaluation Report for FAS/PECAD, Version 2.0

NASA Technical Reports Server (NTRS)

Ross, Kenton; McKellip, Rodney; Mason, Ted; Zanoni, Vicki; Morris, Keith

2004-01-01

Global agricultral intelligence is a key element of decision support eithin the U.S. Department of Agriculture (USDA). Estimeates of production and yield issued by the USDA for both foreign and domestic agriculture are primary sources of information for policy and management decision making. The USDA monitors the major global agricultural commodities through the Production Estimates and Crop Assessment Division (PECAD) of its Foreign Agricultural Service (FAS). Specifically, PECAD iintelligence focuses on global agricultural production and on conditions that affect food security. In conjunction with the USDA, NASA is evaluating the potential for products from NASA's Earth Science Enterprise (ESE) missions to add value to PECAD's decision support tools. NASA is usig a systems engineering approach to evaluate the potential enhancement of PECAD's decision support system (DSS)-first by understanding the components of the system and its input requirements, then by recommending NASA products that may be integrated as system inputs to improve the accuracy, quality, or efficiency of the DSS output. This report documents the evaluation phase of the systems engineering process and includes an examination of the system architecture, operations, and input requirements, as well as an initial assessment of specific ESE measurement systems and products that should be considered for their potential to enhance the PECAD DSS.

A web-based decision support tool for prognosis simulation in multiple sclerosis.

PubMed

Veloso, Mário

2014-09-01

A multiplicity of natural history studies of multiple sclerosis provides valuable knowledge of the disease progression but individualized prognosis remains elusive. A few decision support tools that assist the clinician in such task have emerged but have not received proper attention from clinicians and patients. The objective of the current work is to implement a web-based tool, conveying decision relevant prognostic scientific evidence, which will help clinicians discuss prognosis with individual patients. Data were extracted from a set of reference studies, especially those dealing with the natural history of multiple sclerosis. The web-based decision support tool for individualized prognosis simulation was implemented with NetLogo, a program environment suited for the development of complex adaptive systems. Its prototype has been launched online; it enables clinicians to predict both the likelihood of CIS to CDMS conversion, and the long-term prognosis of disability level and SPMS conversion, as well as assess and monitor the effects of treatment. More robust decision support tools, which convey scientific evidence and satisfy the needs of clinical practice by helping clinicians discuss prognosis expectations with individual patients, are required. The web-based simulation model herein introduced proposes to be a step forward toward this purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

MATERIALS SUPPORTING THE NEW RECREATIONAL ...

EPA Pesticide Factsheets

EPA is developing new, rapid methods for monitoring water quality at beaches to determine adequacy of water quality for swimming. The methods being developed rely upon quantitive polymerase chain reaction technology. They will permit real time decisions regarding beach closures. The methods are supported by a series of epidemiology studies evaluating the rate of GI illness resulting from swimming events. Implementation of BEACH Act amendments

A comprehensive infectious disease management system.

PubMed

Marcu, Alex; Farley, John D

2009-01-01

An efficient electronic management system is now an essential tool for the successful management and monitoring of those affected by communicable infectious diseases (Human Immunodeficiency Virus - HIV, hepatitis C - HEP C) during the course of the treatment. The current methods which depend heavily on manual collecting, compiling and disseminating treatment information are labor-intensive and time consuming. Clinics specialized in the treatment of infectious diseases use a mix of electronic systems that fail to interact with each other, result in data duplication, and do not support treatment of the patient as a whole. The purpose of the Infectious Disease Management System is to reduce the administrative overhead associated with data collection and analysis while providing correlation abilities and decision support in accordance with defined treatment guidelines. This Infectious Disease Management System was developed to: Ensure cost effectiveness by means of low software licensing costs, Introduce a centralized mechanism of collecting and monitoring all infectious disease management data, Automate electronic retrieval of laboratory findings, Introduce a decision support mechanism as per treatment guidelines, Seamlessly integrate of application modules, Provide comprehensive reporting capabilities, Maintain a high level of user friendliness.

Demonstration of the application of traffic management center decision support tools : [summary].

DOT National Transportation Integrated Search

2013-03-01

Among the most important advances in transportation systems in recent years has been the development and implementation of intelligent transportation systems (ITS), which relies on several means of monitoring traffic flows, coupled with real-time and...

Remote Sensing for Climate and Environmental Change

NASA Technical Reports Server (NTRS)

Evans, Diane

2011-01-01

Remote sensing is being used more and more for decision-making and policy development. Specific examples are: (1) Providing constraints on climate models used in IPCC assessments (2) Framing discussions about greenhouse gas monitoring (3) Providing support for hazard assessment and recovery.

Can Wide Consultation Help with Setting Priorities for Large-Scale Biodiversity Monitoring Programs?

PubMed Central

Boivin, Frédéric; Simard, Anouk; Peres-Neto, Pedro

2014-01-01

Climate and other global change phenomena affecting biodiversity require monitoring to track ecosystem changes and guide policy and management actions. Designing a biodiversity monitoring program is a difficult task that requires making decisions that often lack consensus due to budgetary constrains. As monitoring programs require long-term investment, they also require strong and continuing support from all interested parties. As such, stakeholder consultation is key to identify priorities and make sound design decisions that have as much support as possible. Here, we present the results of a consultation conducted to serve as an aid for designing a large-scale biodiversity monitoring program for the province of Québec (Canada). The consultation took the form of a survey with 13 discrete choices involving tradeoffs in respect to design priorities and 10 demographic questions (e.g., age, profession). The survey was sent to thousands of individuals having expected interests and knowledge about biodiversity and was completed by 621 participants. Overall, consensuses were few and it appeared difficult to create a design fulfilling the priorities of the majority. Most participants wanted 1) a monitoring design covering the entire territory and focusing on natural habitats; 2) a focus on species related to ecosystem services, on threatened and on invasive species. The only demographic characteristic that was related to the type of prioritization was the declared level of knowledge in biodiversity (null to high), but even then the influence was quite small. PMID:25525798

Can wide consultation help with setting priorities for large-scale biodiversity monitoring programs?

PubMed

Boivin, Frédéric; Simard, Anouk; Peres-Neto, Pedro

2014-01-01

Climate and other global change phenomena affecting biodiversity require monitoring to track ecosystem changes and guide policy and management actions. Designing a biodiversity monitoring program is a difficult task that requires making decisions that often lack consensus due to budgetary constrains. As monitoring programs require long-term investment, they also require strong and continuing support from all interested parties. As such, stakeholder consultation is key to identify priorities and make sound design decisions that have as much support as possible. Here, we present the results of a consultation conducted to serve as an aid for designing a large-scale biodiversity monitoring program for the province of Québec (Canada). The consultation took the form of a survey with 13 discrete choices involving tradeoffs in respect to design priorities and 10 demographic questions (e.g., age, profession). The survey was sent to thousands of individuals having expected interests and knowledge about biodiversity and was completed by 621 participants. Overall, consensuses were few and it appeared difficult to create a design fulfilling the priorities of the majority. Most participants wanted 1) a monitoring design covering the entire territory and focusing on natural habitats; 2) a focus on species related to ecosystem services, on threatened and on invasive species. The only demographic characteristic that was related to the type of prioritization was the declared level of knowledge in biodiversity (null to high), but even then the influence was quite small.

Minimising farm crop protection pressure supported by the multiple functionalities of the DISCUSS indicator set.

PubMed

Wustenberghs, Hilde; Fevery, Davina; Lauwers, Ludwig; Marchand, Fleur; Spanoghe, Pieter

2018-03-15

Sustainable crop protection (SCP) has many facets. Farmers may therefore perceive transition to SCP as very complex. The Dual Indicator Set for Crop Protection Sustainability (DISCUSS) can handle this complexity. To provide targeted support throughout the transition to SCP, complexity capture must be synchronised with the time course of on-farm decision-making. Tool use must be tuned to farmer awareness and appropriate level of data in consecutive stages. This paper thus explores the potential functionalities of DISCUSS in relation to both complexity and time. Results from apple and potato crop protection show three potential functions: DISCUSS can be used as (1) a simulation tool for communication and decision support, (2) an assessment and monitoring tool, and (3) a discussion support tool for farmer groups. Analysis of these functionalities using a framework for guiding on-farm sustainability assessment and strategic decision-making shows how each functionality can support the consecutive steps of transition to SCP, i.e. using the right tool functionality at the right time. Copyright © 2017 Elsevier B.V. All rights reserved.

LEEDS Decision Tools for E-Craft

DTIC Science & Technology

2011-02-15

currently valid 0MB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) 15-Feb-2011 2. REPORT TYPE Final... RIT has received no feedback regarding which system monitoring would be most beneficial to MSB. TASKS 1. Decision support research Data/analysis...project, a Project Initiation Document (PID) was written by RIT and submitted to MSB for its approval. This document is attached in Appendix A. It

Application of Domain Knowledge to Software Quality Assurance

NASA Technical Reports Server (NTRS)

Wild, Christian W.

1997-01-01

This work focused on capturing, using, and evolving a qualitative decision support structure across the life cycle of a project. The particular application of this study was towards business process reengineering and the representation of the business process in a set of Business Rules (BR). In this work, we defined a decision model which captured the qualitative decision deliberation process. It represented arguments both for and against proposed alternatives to a problem. It was felt that the subjective nature of many critical business policy decisions required a qualitative modeling approach similar to that of Lee and Mylopoulos. While previous work was limited almost exclusively to the decision capture phase, which occurs early in the project life cycle, we investigated the use of such a model during the later stages as well. One of our significant developments was the use of the decision model during the operational phase of a project. By operational phase, we mean the phase in which the system or set of policies which were earlier decided are deployed and put into practice. By making the decision model available to operational decision makers, they would have access to the arguments pro and con for a variety of actions and can thus make a more informed decision which balances the often conflicting criteria by which the value of action is measured. We also developed the concept of a 'monitored decision' in which metrics of performance were identified during the decision making process and used to evaluate the quality of that decision. It is important to monitor those decision which seem at highest risk of not meeting their stated objectives. Operational decisions are also potentially high risk decisions. Finally, we investigated the use of performance metrics for monitored decisions and audit logs of operational decisions in order to feed an evolutionary phase of the the life cycle. During evolution, decisions are revisisted, assumptions verified or refuted, and possible reassessments resulting in new policy are made. In this regard we implemented a machine learning algorithm which automatically defined business rules based on expert assessment of the quality of operational decisions as recorded during deployment.

Monitoring Style of Coping with Cancer Related Threats: A Review of the Literature

PubMed Central

Miller, Suzanne M.

2014-01-01

Building on the Cognitive-Social Health Information-Processing model, this paper provides a theoretically guided review of monitoring (i.e., attend to and amplify) cancer-related threats. Specifically, the goals of the review are to examine whether individuals high on monitoring are characterized by specific cognitive, affective, and behavioral responses to cancer-related health threats than individuals low on monitoring and the implications of these cognitive-affective responses for patient-centered outcomes, including patient-physician communication, decision-making and the development of interventions to promote adherence and adjustment. A total of 74 reports were found, based on 63 studies, 13 of which were intervention studies. The results suggest that although individuals high on monitoring are more knowledgeable about health threats, they are less satisfied with the information provided. Further, they tend to be characterized by greater perceived risk, more negative beliefs, and greater value of health-related information and experience more negative affective outcomes. Finally, individuals high on monitoring tend to be more demanding of the health providers in terms of desire for more information and emotional support, are more assertive during decision-making discussions, and subsequently experience more decisional regret. Psychoeducational interventions improve outcomes when the level and type of information provided is consistent with the individual's monitoring style and the demands of the specific health threat. Implications for patient-centered outcomes, in terms of tailoring of interventions, patient-provider communication, and decision-making, are discussed. PMID:24488543

Monitoring style of coping with cancer related threats: a review of the literature.

PubMed

Roussi, Pagona; Miller, Suzanne M

2014-10-01

Building on the Cognitive-Social Health Information-Processing model, this paper provides a theoretically guided review of monitoring (i.e., attend to and amplify) cancer-related threats. Specifically, the goals of the review are to examine whether individuals high on monitoring are characterized by specific cognitive, affective, and behavioral responses to cancer-related health threats than individuals low on monitoring and the implications of these cognitive-affective responses for patient-centered outcomes, including patient-physician communication, decision-making and the development of interventions to promote adherence and adjustment. A total of 74 reports were found, based on 63 studies, 13 of which were intervention studies. The results suggest that although individuals high on monitoring are more knowledgeable about health threats, they are less satisfied with the information provided. Further, they tend to be characterized by greater perceived risk, more negative beliefs, and greater value of health-related information and experience more negative affective outcomes. Finally, individuals high on monitoring tend to be more demanding of the health providers in terms of desire for more information and emotional support, are more assertive during decision-making discussions, and subsequently experience more decisional regret. Psychoeducational interventions improve outcomes when the level and type of information provided is consistent with the individual's monitoring style and the demands of the specific health threat. Implications for patient-centered outcomes, in terms of tailoring of interventions, patient-provider communication, and decision-making, are discussed.

Clinical genomics information management software linking cancer genome sequence and clinical decisions.

PubMed

Watt, Stuart; Jiao, Wei; Brown, Andrew M K; Petrocelli, Teresa; Tran, Ben; Zhang, Tong; McPherson, John D; Kamel-Reid, Suzanne; Bedard, Philippe L; Onetto, Nicole; Hudson, Thomas J; Dancey, Janet; Siu, Lillian L; Stein, Lincoln; Ferretti, Vincent

2013-09-01

Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician. Copyright © 2013 Elsevier Inc. All rights reserved.

MATERIALS SUPPORTING THE NEW RECREATIONAL WATER QUALITY CRITERIA FOR PATHOGENS

EPA Science Inventory

EPA is developing new, rapid methods for monitoring water quality at beaches to determine adequacy of water quality for swimming. The methods being developed rely upon quantitive polymerase chain reaction technology. They will permit real time decisions regarding beach closures...

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

NASA Astrophysics Data System (ADS)

Eni, Yuli; Aryanto, Rudy

2014-03-01

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

SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

NASA Technical Reports Server (NTRS)

Irwin, D. E.; Sever, T. L.; Graves, S.; Hardin, Dan

2004-01-01

In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica, composed of the seven Central American countries and the five southernmost states of Mexico, make up only a small fraction of the world's land surface. However, the region is home to seven to eight percent of the planet's biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica's biological and cultural diversity 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 to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in the development of SIAM-SERVIR and the plans for the future.

Maritime Situational Awareness: The MARISS Experience

NASA Astrophysics Data System (ADS)

Margarit, G.; Tabasco, A.; Gomez, C.

2010-04-01

This paper presents the operational solution developed by GMV to provide support to maritime situational awareness via Earth Observation (EO) technologies. The concept falls on integrating the information retrieved from Synthetic Aperture Radar (SAR) images and transponder-based polls (AIS and similar) in an advanced GeoPortal web. The service has been designed in the framework of the MARISS project, a project conceived to help improving ship monitoring with the support of a large user segment. In this context, the interaction with official agencies has provided good feedback about system performance and its usefulness in supporting monitoring and surveillance tasks. Some representative samples are analyzed along the paper in order to validate key kernel utilities, such as ship and coastline detection, and ship classification. They justify the promotion of extended R&D activities to increase monitoring performance and to include advanced added- value tools, such as decision making and route tracking.

Nursing implications of personalized and precision medicine.

PubMed

Vorderstrasse, Allison A; Hammer, Marilyn J; Dungan, Jennifer R

2014-05-01

Identify and discuss the nursing implications of personalized and precision oncology care. PubMed, CINAHL. The implications in personalized and precision cancer nursing care include interpretation and clinical use of novel and personalized information including genetic testing; patient advocacy and support throughout testing, anticipation of results and treatment; ongoing chronic monitoring; and support for patient decision-making. Attention must also be given to the family and ethical implications of a personalized approach to care. Nurses face increasing challenges and opportunities in communication, support, and advocacy for patients given the availability of advanced testing, care and treatment in personalized and precision medicine. Nursing education and continuing education, clinical decision support, and health systems changes will be necessary to provide personalized multidisciplinary care to patients, in which nurses play a key role. Copyright © 2014 Elsevier Inc. All rights reserved.

Building a Predictive Capability for Decision-Making that Supports MultiPEM

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

Carmichael, Joshua Daniel

Multi-phenomenological explosion monitoring (multiPEM) is a developing science that uses multiple geophysical signatures of explosions to better identify and characterize their sources. MultiPEM researchers seek to integrate explosion signatures together to provide stronger detection, parameter estimation, or screening capabilities between different sources or processes. This talk will address forming a predictive capability for screening waveform explosion signatures to support multiPEM.

Frequencies of decision making and monitoring in adaptive resource management

PubMed Central

Johnson, Fred A.

2017-01-01

Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions. PMID:28800591

Frequencies of decision making and monitoring in adaptive resource management

USGS Publications Warehouse

Williams, Byron K.; Johnson, Fred A.

2017-01-01

Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions.

Solutions Network Formulation Report. Improving NOAA's Tides and Currents Through Enhanced Data Inputs from NASA's Ocean Surface Topography Mission

NASA Technical Reports Server (NTRS)

Guest, DeNeice C.

2006-01-01

The Nation uses water-level data for a variety of practical purposes, including hydrography, nautical charting, maritime navigation, coastal engineering, and tsunami and storm surge warnings (NOAA, 2002; Digby et al., 1999). Long-term applications include marine boundary determinations, tidal predictions, sea-level trend monitoring, oceanographic research, and climate research. Accurate and timely information concerning sea-level height, tide, and ocean current is needed to understand their impact on coastal management, disaster management, and public health. Satellite altimeter data products are currently used by hundreds of researchers and operational users to monitor ocean circulation and to improve scientists understanding of the role of the oceans in climate and weather. The NOAA (National Oceanic and Atmospheric Administration) National Ocean Service has been monitoring sea-level variations for many years (NOAA, 2006). NOAA s Tides & Currents DST (decision support tool, managed by the Center for Operational Oceanographic Products and Services, is the portal to a vast collection of oceanographic and meteorological data (historical and real-time), predictions, and nowcasts and forecasts. This report assesses the capacity of NASA s satellite altimeter data to meet societal decision support needs through incorporation into NOAA s Tides & Currents.

Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

NASA Astrophysics Data System (ADS)

Jegadeeshwaran, R.; Sugumaran, V.

2015-02-01

Hydraulic brakes in automobiles are important components for the safety of passengers; therefore, the brakes are a good subject for condition monitoring. The condition of the brake components can be monitored by using the vibration characteristics. On-line condition monitoring by using machine learning approach is proposed in this paper as a possible solution to such problems. The vibration signals for both good as well as faulty conditions of brakes were acquired from a hydraulic brake test setup with the help of a piezoelectric transducer and a data acquisition system. Descriptive statistical features were extracted from the acquired vibration signals and the feature selection was carried out using the C4.5 decision tree algorithm. There is no specific method to find the right number of features required for classification for a given problem. Hence an extensive study is needed to find the optimum number of features. The effect of the number of features was also studied, by using the decision tree as well as Support Vector Machines (SVM). The selected features were classified using the C-SVM and Nu-SVM with different kernel functions. The results are discussed and the conclusion of the study is presented.

A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs.

PubMed

Forkan, Abdur Rahim Mohammad; Khalil, Ibrahim

2017-02-01

In home-based context-aware monitoring patient's real-time data of multiple vital signs (e.g. heart rate, blood pressure) are continuously generated from wearable sensors. The changes in such vital parameters are highly correlated. They are also patient-centric and can be either recurrent or can fluctuate. The objective of this study is to develop an intelligent method for personalized monitoring and clinical decision support through early estimation of patient-specific vital sign values, and prediction of anomalies using the interrelation among multiple vital signs. In this paper, multi-label classification algorithms are applied in classifier design to forecast these values and related abnormalities. We proposed a completely new approach of patient-specific vital sign prediction system using their correlations. The developed technique can guide healthcare professionals to make accurate clinical decisions. Moreover, our model can support many patients with various clinical conditions concurrently by utilizing the power of cloud computing technology. The developed method also reduces the rate of false predictions in remote monitoring centres. In the experimental settings, the statistical features and correlations of six vital signs are formulated as multi-label classification problem. Eight multi-label classification algorithms along with three fundamental machine learning algorithms are used and tested on a public dataset of 85 patients. Different multi-label classification evaluation measures such as Hamming score, F1-micro average, and accuracy are used for interpreting the prediction performance of patient-specific situation classifications. We achieved 90-95% Hamming score values across 24 classifier combinations for 85 different patients used in our experiment. The results are compared with single-label classifiers and without considering the correlations among the vitals. The comparisons show that multi-label method is the best technique for this problem domain. The evaluation results reveal that multi-label classification techniques using the correlations among multiple vitals are effective ways for early estimation of future values of those vitals. In context-aware remote monitoring this process can greatly help the doctors in quick diagnostic decision making. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Map of Life - A Dashboard for Monitoring Planetary Species Distributions

NASA Astrophysics Data System (ADS)

Jetz, W.

2016-12-01

Geographic information about biodiversity is vital for understanding the many services nature provides and their potential changes, yet remains unreliable and often insufficient. By integrating a wide range of knowledge about species distributions and their dynamics over time, Map of Life supports global biodiversity education, monitoring, research and decision-making. Built on a scalable web platform geared for large biodiversity and environmental data, Map of Life endeavors provides species range information globally and species lists for any area. With data and technology provided by NASA and Google Earth Engine, tools under development use remote sensing-based environmental layers to enable on-the-fly predictions of species distributions, range changes, and early warning signals for threatened species. The ultimate vision is a globally connected, collaborative knowledge- and tool-base for regional and local biodiversity decision-making, education, monitoring, and projection. For currently available tools, more information and to follow progress, go to MOL.org.

Successful integration efforts in water quality from the integrated Ocean Observing System Regional Associations and the National Water Quality Monitoring Network

USGS Publications Warehouse

Ragsdale, R.; Vowinkel, E.; Porter, D.; Hamilton, P.; Morrison, R.; Kohut, J.; Connell, B.; Kelsey, H.; Trowbridge, P.

2011-01-01

The Integrated Ocean Observing System (IOOS??) Regional Associations and Interagency Partners hosted a water quality workshop in January 2010 to discuss issues of nutrient enrichment and dissolved oxygen depletion (hypoxia), harmful algal blooms (HABs), and beach water quality. In 2007, the National Water Quality Monitoring Council piloted demonstration projects as part of the National Water Quality Monitoring Network (Network) for U.S. Coastal Waters and their Tributaries in three IOOS Regional Associations, and these projects are ongoing. Examples of integrated science-based solutions to water quality issues of major concern from the IOOS regions and Network demonstration projects are explored in this article. These examples illustrate instances where management decisions have benefited from decision-support tools that make use of interoperable data. Gaps, challenges, and outcomes are identified, and a proposal is made for future work toward a multiregional water quality project for beach water quality.

Water quality success stories: Integrated assessments from the IOOS regional associations and national water quality monitoring network

USGS Publications Warehouse

Ragsdale, Rob; Vowinkel, Eric; Porter, Dwayne; Hamilton, Pixie; Morrison, Ru; Kohut, Josh; Connell, Bob; Kelsey, Heath; Trowbridge, Phil

2011-01-01

The Integrated Ocean Observing System (IOOS®) Regional Associations and Interagency Partners hosted a water quality workshop in January 2010 to discuss issues of nutrient enrichment and dissolved oxygen depletion (hypoxia), harmful algal blooms (HABs), and beach water quality. In 2007, the National Water Quality Monitoring Council piloted demonstration projects as part of the National Water Quality Monitoring Network (Network) for U.S. Coastal Waters and their Tributaries in three IOOS Regional Associations, and these projects are ongoing. Examples of integrated science-based solutions to water quality issues of major concern from the IOOS regions and Network demonstration projects are explored in this article. These examples illustrate instances where management decisions have benefited from decision-support tools that make use of interoperable data. Gaps, challenges, and outcomes are identified, and a proposal is made for future work toward a multiregional water quality project for beach water quality.

Art to science: Tools for greater objectivity in resource monitoring

USDA-ARS?s Scientific Manuscript database

The earliest inventories of western US rangelands were “ocular” estimates. Now, objective data consistent with formal scientific inquiry is needed to support management decisions that sustain the resource while balancing numerous competing land uses and sometimes-vociferous stakeholders. Yet, the co...

Contributions of Participatory Modeling to Development and Support of Coastal and Marine Management Plans

EPA Science Inventory

The role of participatory modeling- at various scales- to assist in developing shared visions, understanding the decision landscape, identifying and selecting management options, and monitoring outcomes will be explored in the context of coastal and marine planning, ecosystem ser...

CyAN satellite-derived Cyanobacteria products in support of Public Health Protection

EPA Science Inventory

The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management decision-making and for targeted deployment of existing government and non-government water quality monitoring resources. The Cyanobacteria Assessment Network (CyAN) is a...

Technological innovations in the development of cardiovascular clinical information systems.

PubMed

Hsieh, Nan-Chen; Chang, Chung-Yi; Lee, Kuo-Chen; Chen, Jeen-Chen; Chan, Chien-Hui

2012-04-01

Recent studies have shown that computerized clinical case management and decision support systems can be used to assist surgeons in the diagnosis of disease, optimize surgical operation, aid in drug therapy and decrease the cost of medical treatment. Therefore, medical informatics has become an extensive field of research and many of these approaches have demonstrated potential value for improving medical quality. The aim of this study was to develop a web-based cardiovascular clinical information system (CIS) based on innovative techniques, such as electronic medical records, electronic registries and automatic feature surveillance schemes, to provide effective tools and support for clinical care, decision-making, biomedical research and training activities. The CIS developed for this study contained monitoring, surveillance and model construction functions. The monitoring layer function provided a visual user interface. At the surveillance and model construction layers, we explored the application of model construction and intelligent prognosis to aid in making preoperative and postoperative predictions. With the use of the CIS, surgeons can provide reasonable conclusions and explanations in uncertain environments.

Improving performance with clinical decision support.

PubMed

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

1996-07-01

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

Monitoring And Modeling Environmental Water Quality To Support Environmental Water Purchase Decision-making

NASA Astrophysics Data System (ADS)

Null, S. E.; Elmore, L.; Mouzon, N. R.; Wood, J. R.

2016-12-01

More than 25 million cubic meters (20,000 acre feet) of water has been purchased from willing agricultural sellers for environmental flows in Nevada's Walker River to improve riverine habitat and connectivity with downstream Walker Lake. Reduced instream flows limit native fish populations, like Lahontan cutthroat trout, through warm daily stream temperatures and low dissolved oxygen concentrations. Environmental water purchases maintain instream flows, although effects on water quality are more varied. We use multi-year water quality monitoring and physically-based hydrodynamic and water quality modeling to estimate streamflow, water temperature, and dissolved oxygen concentrations with alternative environmental water purchases. We simulate water temperature and dissolved oxygen changes from increased streamflow to prioritize the time periods and locations that environmental water purchases most enhance trout habitat as a function of water quality. Monitoring results indicate stream temperature and dissolved oxygen limitations generally exist in the 115 kilometers upstream of Walker Lake (about 37% of the study area) from approximately May through September, and this reach acts as a water quality barrier for fish passage. Model results indicate that low streamflows generally coincide with critically warm stream temperatures, water quality refugia exist on a tributary of the Walker River, and environmental water purchases may improve stream temperature and dissolved oxygen conditions for some reaches and seasons, especially in dry years and prolonged droughts. This research supports environmental water purchase decision-making and allows water purchase decisions to be prioritized with other river restoration alternatives.

Clinical decision support systems: data quality management and governance.

PubMed

Liaw, Siaw-Teng

2013-01-01

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

Integrating NASA Earth Science Enterprise (ESE) Data Into Global Agricultural Decision Support Systems

NASA Astrophysics Data System (ADS)

Teng, W.; Kempler, S.; Chiu, L.; Doraiswamy, P.; Liu, Z.; Milich, L.; Tetrault, R.

2003-12-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of U.S. agricultural products and for global food security. Two major operational users of satellite remote sensing for global crop monitoring are the USDA Foreign Agricultural Service (FAS) and the U.N. World Food Programme (WFP). The primary goal of FAS is to improve foreign market access for U.S. agricultural products. The WFP uses food to meet emergency needs and to support economic and social development. Both use global agricultural decision support systems that can integrate and synthesize a variety of data sources to provide accurate and timely information on global crop conditions. The Goddard Space Flight Center Earth Sciences Distributed Active Archive Center (GES DAAC) has begun a project to provide operational solutions to FAS and WFP, by fully leveraging results from previous work, as well as from existing capabilities of the users. The GES DAAC has effectively used its recently developed prototype TRMM Online Visualization and Analysis System (TOVAS) to provide ESE data and information to the WFP for its agricultural drought monitoring efforts. This prototype system will be evolved into an Agricultural Information System (AIS), which will operationally provide ESE and other data products (e.g., rainfall, land productivity) and services, to be integrated into and thus enhance the existing GIS-based, decision support systems of FAS and WFP. Agriculture-oriented, ESE data products (e.g., MODIS-based, crop condition assessment product; TRMM derived, drought index product) will be input to a crop growth model in collaboration with the USDA Agricultural Research Service, to generate crop condition and yield prediction maps. The AIS will have the capability for remotely accessing distributed data, by being compliant with community-based interoperability standards, enabling easy access to agriculture-related products from other data producers. The AIS? system approach will provide a generic mechanism for easily incorporating new products and making them accessible to users.

Development of an intelligent hydroinformatic system for real-time monitoring and assessment of civil infrastructure

NASA Astrophysics Data System (ADS)

Cahill, Paul; Michalis, Panagiotis; Solman, Hrvoje; Kerin, Igor; Bekic, Damir; Pakrashi, Vikram; McKeogh, Eamon

2017-04-01

With the effects of climate change becoming more apparent, extreme weather events are now occurring with greater frequency throughout the world. Such extreme events have resulted in increased high intensity flood events which are having devastating consequences on hydro-structures, especially on bridge infrastructure. The remote and often inaccessible nature of such bridges makes inspections problematic, a major concern if safety assessments are required during and after extreme flood events. A solution to this is the introduction of smart, low cost sensing solutions at locations susceptible to hydro-hazards. Such solutions can provide real-time information on the health of the bridge and its environments, with such information aiding in the mitigation of the risks associated with extreme weather events. This study presents the development of an intelligent system for remote, real-time monitoring of hydro-hazards to bridge infrastructure. The solution consists of two types of remote monitoring stations which have the capacity to monitor environmental conditions and provide real-time information to a centralized, big data database solution, from which an intelligent decision support system will accommodate the results to control and manage bridge, river and catchment assets. The first device developed as part of the system is the Weather Information Logging Device (WILD), which monitors rainfall, temperature and air and soil moisture content. The ability of the WILD to monitor rainfall in real time enables flood early warning alerts and predictive river flow conditions, thereby enabling decision makers the ability to make timely and effective decisions about critical infrastructures in advance of extreme flood events. The WILD is complemented by a second monitoring device, the Bridge Information Recording Device (BIRD), which monitors water levels at a given location in real-time. The monitoring of water levels of a river allows for, among other applications, hydraulic modelling to assess the likely impact that severe flood events will have on a bridges foundation, particularly due to scour. The process of reading and validating data from the WILD and BIRD buffer servers is outlined, as is the transmission protocol used for the sending of recorded data to a centralized repository for further use and analysis. Finally, the development of a centralized repository for the collection of data from the WILD and BIRD devices is presented. Eventually the big data solution would be used to receive, store and send the monitored data to the hydrological models, whether existing or developed, and the results would be transmitted to the intelligent decision support system based on a web-based platform, for managing, planning and executing data, processes and procedures for bridge assets. The development of intelligent hydroinformatic system is an important tool for the protection of key infrastructure assets from the increasingly common effects of climate change. Acknowledgement The authors wish to acknowledge the financial support of the European Commission, through the Marie Curie Industry-Academia Partnership and Pathways Network BRIDGE SMS (Intelligent Bridge Assessment Maintenance and Management System) - FP7-People-2013-IAPP- 612517.

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 including overcoming unrealistically precise information demands. While monitoring systems design and operation should be guided by the standards and requirements of management, those who provide information to the system (e.g. hydromet services) should also derive benefits. Drawing on identified information needs to support climate risk management (in drought, water resources and other areas) we outline principles of effective monitoring and develop preliminary strategic guidance for information systems being developed through the GEO, GCOS and Global and national frameworks for climate services. The efficacy of such services are improved by a problem-solving orientation, participatory planning, extension management and improvements in the use and value of existing data to legitimize new investments.

A multidisciplinary decision support system for forest fire crisis management.

PubMed

Keramitsoglou, Iphigenia; Kiranoudis, Chris T; Sarimveis, Haralambos; Sifakis, Nicolaos

2004-02-01

A wildland fire is a serious threat for forest ecosystems in Southern Europe affecting severely and irreversibly regions of significant ecological value as well as human communities. To support decision makers during large-scale forest fire incidents, a multidisciplinary system has been developed that provides rational and quantitative information based on the site-specific circumstances and the possible consequences. The system's architecture consists of several distinct supplementary modules of near real-time satellite monitoring and fire forecast using an integrated framework of satellite Remote Sensing, GIS, and RDBMS technologies equipped with interactive communication capabilities. The system may handle multiple fire ignitions and support decisions regarding dispatching of utilities, equipment, and personnel that would appropriately attack the fire front. The operational system was developed for the region of Penteli Mountain in Attika, Greece, one of the mountain areas in the country most hit by fires. Starting from a real fire incident in August 2000, a scenario is presented to illustrate the effectiveness of the proposed approach.

The Deep Space Network information system in the year 2000

NASA Technical Reports Server (NTRS)

Markley, R. W.; Beswick, C. A.

1992-01-01

The Deep Space Network (DSN), the largest, most sensitive scientific communications and radio navigation network in the world, is considered. Focus is made on the telemetry processing, monitor and control, and ground data transport architectures of the DSN ground information system envisioned for the year 2000. The telemetry architecture will be unified from the front-end area to the end user. It will provide highly automated monitor and control of the DSN, automated configuration of support activities, and a vastly improved human interface. Automated decision support systems will be in place for DSN resource management, performance analysis, fault diagnosis, and contingency management.

Integrated Drought Monitoring and Forecasts for Decision Making in Water and Agricultural Sectors over the Southeastern US under Changing Climate

NASA Astrophysics Data System (ADS)

Arumugam, S.; Mazrooei, A.; Ward, R.

2017-12-01

Changing climate arising from structured oscillations such as ENSO and rising temperature poses challenging issues in meeting the increasing water demand (due to population growth) for public supply and agriculture over the Southeast US. This together with infrastructural (e.g., most reservoirs being within-year systems) and operational (e.g., static rule curves) constraints requires an integrated approach that seamlessly monitors and forecasts water and soil moisture conditions to support adaptive decision making in water and agricultural sectors. In this talk, we discuss the utility of an integrated drought management portal that both monitors and forecasts streamflow and soil moisture over the southeast US. The forecasts are continuously developed and updated by forcing monthly-to-seasonal climate forecasts with a land surface model for various target basins. The portal also houses a reservoir allocation model that allows water managers to explore different release policies in meeting the system constraints and target storages conditioned on the forecasts. The talk will also demonstrate how past events (e.g., 2007-2008 drought) could be proactively monitored and managed to improve decision making in water and agricultural sectors over the Southeast US. Challenges in utilizing the portal information from institutional and operational perspectives will also be presented.

A decision support system-based procedure for evaluation and monitoring of protected areas sustainability for the Mediterranean region

NASA Astrophysics Data System (ADS)

Pediaditi, K.; Buono, F.; Pompigna, F.; Bogliotti, C.; Nurlu, E.; Ladisa, G.; Petropoulos, G. P.

2011-10-01

Despite common acknowledgement of the value of protected areas as instruments in ensuring sustainability, and their promotion for the achievement of policies on halting the loss of biodiversity, there is no common approach today for monitoring and evaluating them. This paper presents a novel integrated nature conservation management procedure developed to monitor and evaluate the sustainability of Mediterranean protected areas. This procedure was successfully implemented and formally evaluated by protected area managers in six Mediterranean countries, results of which are presented here together with an overview of the web-based Decision Support System (DSS) developed to facilitate its wide adoption. The DSS and procedure has been designed and evaluated by managers as a useful tool, which facilitates and provides needed procedural guidance for protected area monitoring whilst minimizing input requirements to do so. The procedure and DSS were developed following a review of existing protected area assessment tools and a detailed primary investigation of the needs and capacity of its intended users. Essentially, the procedure and DSS guides provide the facilities for protected area managers, in following a participatory approach to develop a context-specific sustainability monitoring strategy, for their protected area. Consequently, the procedure is, by design, participatory, context specific, holistic and relevant to protected area management and institutional procedures. The procedure was piloted and formally evaluated in Greece, Italy, Turkey, Egypt, Malta and Cyprus. Feedback collected from the pilot evaluations is also summarised herein.

Integrating SAR and derived products into operational volcano monitoring and decision support systems

NASA Astrophysics Data System (ADS)

Meyer, F. J.; McAlpin, D. B.; Gong, W.; Ajadi, O.; Arko, S.; Webley, P. W.; Dehn, J.

2015-02-01

Remote sensing plays a critical role in operational volcano monitoring due to the often remote locations of volcanic systems and the large spatial extent of potential eruption pre-cursor signals. Despite the all-weather capabilities of radar remote sensing and its high performance in monitoring of change, the contribution of radar data to operational monitoring activities has been limited in the past. This is largely due to: (1) the high costs associated with radar data; (2) traditionally slow data processing and delivery procedures; and (3) the limited temporal sampling provided by spaceborne radars. With this paper, we present new data processing and data integration techniques that mitigate some of these limitations and allow for a meaningful integration of radar data into operational volcano monitoring decision support systems. Specifically, we present fast data access procedures as well as new approaches to multi-track processing that improve near real-time data access and temporal sampling of volcanic systems with SAR data. We introduce phase-based (coherent) and amplitude-based (incoherent) change detection procedures that are able to extract dense time series of hazard information from these data. For a demonstration, we present an integration of our processing system with an operational volcano monitoring system that was developed for use by the Alaska Volcano Observatory (AVO). Through an application to a historic eruption, we show that the integration of SAR into systems such as AVO can significantly improve the ability of operational systems to detect eruptive precursors. Therefore, the developed technology is expected to improve operational hazard detection, alerting, and management capabilities.

Monitoring the southwestern Wyoming landscape—A foundation for management and science

USGS Publications Warehouse

Manier, Daniel J.; Anderson, Patrick J.; Assal, Timothy J.; Chong, Geneva W.; Melcher, Cynthia P.

2017-08-29

Natural resource monitoring involves repeated collections of resource condition data and analyses to detect possible changes and identify underlying causes of changes. For natural resource agencies, monitoring provides the foundation for management and science. Specifically, analyses of monitoring data allow managers to better understand effects of land-use and other changes on important natural resources and to achieve their conservation and management goals. Examples of natural resources monitored on public lands include wildlife habitats, plant productivity, animal movements and population trends, soil chemistry, and water quality and quantity. Broader definitions of monitoring also recognize the need for scientifically valid data to help support planning efforts and informed decisions, to develop adaptive management strategies, and to provide the means for evaluating management outcomes.

Criteria for Space-Based Sensor Applied to Bt Crop Monitoring

EPA Science Inventory

A joint agro-ecosystem research effort of NASA and USEPA has focused on the development of a decision support system designed to predict the development of insect pest resistance to transgenic toxins in maize. The use of NASA-developed remote sensing technologies that significant...

Coordinating Aircraft During Field Campaigns: Real Time Mission Monitor Tool

NASA Technical Reports Server (NTRS)

Goodman, Michael

2012-01-01

RTMM has evolved into a powerful and easy to use application in support of planning, situational awareness and strategic decision-making during airborne field campaigns. NASA is very open to sharing these capabilities with any interested group through interagency collaborations in future field activities.

A Virtual Information-Action Workspace for Command and Control

NASA Astrophysics Data System (ADS)

Lintern, Gavan; Naikar, Neelam

2002-10-01

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

Sensor Networking Testbed with IEEE 1451 Compatibility and Network Performance Monitoring

NASA Technical Reports Server (NTRS)

Gurkan, Deniz; Yuan, X.; Benhaddou, D.; Figueroa, F.; Morris, Jonathan

2007-01-01

Design and implementation of a testbed for testing and verifying IEEE 1451-compatible sensor systems with network performance monitoring is of significant importance. The performance parameters measurement as well as decision support systems implementation will enhance the understanding of sensor systems with plug-and-play capabilities. The paper will present the design aspects for such a testbed environment under development at University of Houston in collaboration with NASA Stennis Space Center - SSST (Smart Sensor System Testbed).

Preclinical Evaluation of a Decision Support Medical Monitoring System for Early Detection of Potential Hemodynamic Decompensation During Blood Loss in Humans

DTIC Science & Technology

2013-09-01

Hemodynamic Decompensation During Blood Loss in Humans PRINCIPAL INVESTIGATOR: Michael J. Joyner, M.D. CONTRACTING ORGANIZATION: Mayo Clinic...Medical Monitoring System for Early Detection of Potential Hemodynamic Decompensation During Blood Loss in Humans 5c. PROGRAM ELEMENT NUMBER 6...loss and hemorrhage in humans. The aim Is to be able to detect subtle changes in hemodynamic variables that provide prodromal clues to Impending

Fuzzy-Arden-Syntax-based, Vendor-agnostic, Scalable Clinical Decision Support and Monitoring Platform.

PubMed

Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea

2015-01-01

This study's objective is to develop and use a scalable genuine technology platform for clinical decision support based on Arden Syntax, which was extended by fuzzy set theory and fuzzy logic. Arden Syntax is a widely recognized formal language for representing clinical and scientific knowledge in an executable format, and is maintained by Health Level Seven (HL7) International and approved by the American National Standards Institute (ANSI). Fuzzy set theory and logic permit the representation of knowledge and automated reasoning under linguistic and propositional uncertainty. These forms of uncertainty are a common feature of patients' medical data, the body of medical knowledge, and deductive clinical reasoning.

Optimization of monitoring networks based on uncertainty quantification of model predictions of contaminant transport

NASA Astrophysics Data System (ADS)

Vesselinov, V. V.; Harp, D.

2010-12-01

The process of decision making to protect groundwater resources requires a detailed estimation of uncertainties in model predictions. Various uncertainties associated with modeling a natural system, such as: (1) measurement and computational errors; (2) uncertainties in the conceptual model and model-parameter estimates; (3) simplifications in model setup and numerical representation of governing processes, contribute to the uncertainties in the model predictions. Due to this combination of factors, the sources of predictive uncertainties are generally difficult to quantify individually. Decision support related to optimal design of monitoring networks requires (1) detailed analyses of existing uncertainties related to model predictions of groundwater flow and contaminant transport, (2) optimization of the proposed monitoring network locations in terms of their efficiency to detect contaminants and provide early warning. We apply existing and newly-proposed methods to quantify predictive uncertainties and to optimize well locations. An important aspect of the analysis is the application of newly-developed optimization technique based on coupling of Particle Swarm and Levenberg-Marquardt optimization methods which proved to be robust and computationally efficient. These techniques and algorithms are bundled in a software package called MADS. MADS (Model Analyses for Decision Support) is an object-oriented code that is capable of performing various types of model analyses and supporting model-based decision making. The code can be executed under different computational modes, which include (1) sensitivity analyses (global and local), (2) Monte Carlo analysis, (3) model calibration, (4) parameter estimation, (5) uncertainty quantification, and (6) model selection. The code can be externally coupled with any existing model simulator through integrated modules that read/write input and output files using a set of template and instruction files (consistent with the PEST I/O protocol). MADS can also be internally coupled with a series of built-in analytical simulators. MADS provides functionality to work directly with existing control files developed for the code PEST (Doherty 2009). To perform the computational modes mentioned above, the code utilizes (1) advanced Latin-Hypercube sampling techniques (including Improved Distributed Sampling), (2) various gradient-based Levenberg-Marquardt optimization methods, (3) advanced global optimization methods (including Particle Swarm Optimization), and (4) a selection of alternative objective functions. The code has been successfully applied to perform various model analyses related to environmental management of real contamination sites. Examples include source identification problems, quantification of uncertainty, model calibration, and optimization of monitoring networks. The methodology and software codes are demonstrated using synthetic and real case studies where monitoring networks are optimized taking into account the uncertainty in model predictions of contaminant transport.

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

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

The Lenfest Ocean Program's experience in building institutional support for connecting science and decision-making in marine systems

NASA Astrophysics Data System (ADS)

Bednarek, A.; Close, S.; Curran, K.; Hudson, C.

2017-12-01

Addressing contemporary sustainability challenges requires attention to the integration of scientific knowledge into decision-making and deliberation. However, this remains a challenge in practice. We contend that careful stewardship of this process of integration can result in positive, durable outcomes by reconciling the production and use of scientific knowledge, and improve its relevance and utility to decision-makers. We will share lessons learned from a grantmaking program that has addressed this challenge through programmatic innovations, including by supporting staff devoted to an intermediary role. Over the past 13 years, the Lenfest Ocean Program served in a boundary spanning role by integrating decision-makers into the scoping and outreach of program supported scientific research grants. Program staff engage with decision-makers and influencers to identify policy-relevant research questions and approaches, ensuring that the research direction addresses users' needs. As research progresses, the staff monitor the grant's progress to improve the match between the research and user needs. The process is resource-intensive, however, and raises interesting questions about the role and development of this kind of specialist within different kinds of institutions, including funding agencies. We suggest that nurturing this role as a practice and profession could ultimately help the scientific community more efficiently respond to sustainability challenges.

Pollution characterization of liquid waste of the factory complex Fertial (Arzew, Algeria).

PubMed

Redouane, Fares; Mourad, Lounis

2016-03-01

The industrial development in Algeria has made a worrying situation for all socioeconomic stakeholders. Indeed, this economic growth is marked in recent years by the establishment of factories and industrial plants that discharge liquid waste in marine shorelines. These releases could destabilize the environmental balance in the coming years, hence the need to support the processing of all sources of pollution. Remediation of such discharges requires several steps of identifying the various pollutants to their treatments. Therefore, the authors conducted this first work of characterization of industrial effluents generated by the mineral fertilizer factory complex Fertial (Arzew), and discussed the pollution load generated by this type of industry. This monitoring would establish a tool for reflection and decision support developed by a management system capable of ensuring effective and sustainable management of effluents from industrial activities of Fertial. The authors conducted this first work of characterization of industrial effluents generated by the mineral fertilizer factory complex Fertial (Arzew), and discussed the pollution load generated by this type of industry. This monitoring would establish a tool for reflection and decision support developed by a management system capable of ensuring effective and sustainable management of effluents from industrial activities of Fertial.

Developing and Transitioning Numerical Air Quality Models to Improve Air Quality and Public Health Decision-Making in El Salvador and Costa Rica As Part of the Servir Applied Sciences Team

NASA Astrophysics Data System (ADS)

Thomas, A.; Huff, A. K.; Gomori, S. G.; Sadoff, N.

2014-12-01

In order to enhance the capacity for air quality modeling and improve air quality monitoring and management in the SERVIR Mesoamerica region, members of SERVIR's Applied Sciences Team (AST) are developing national numerical air quality models for El Salvador and Costa Rica. We are working with stakeholders from the El Salvador Ministry of the Environment and Natural Resources (MARN); National University of Costa Rica (UNA); the Costa Rica Ministry of the Environment, Energy, and Telecommunications (MINAET); and Costa Rica National Meteorological Institute (IMN), who are leaders in air quality monitoring and management in the Mesoamerica region. Focusing initially on these institutions will build sustainability in regional modeling activities by developing air quality modeling capability that can be shared with other countries in Mesoamerica. The air quality models are based on the Community Multi-scale Air Quality (CMAQ) model and incorporate meteorological inputs from the Weather Research and Forecasting (WRF) model, as well as national emissions inventories from El Salvador and Costa Rica. The models are being optimized for urban air quality, which is a priority of decision-makers in Mesoamerica. Once experimental versions of the modeling systems are complete, they will be transitioned to servers run by stakeholders in El Salvador and Costa Rica. The numerical air quality models will provide decision support for stakeholders to identify 1) high-priority areas for expanding national ambient air monitoring networks, 2) needed revisions to national air quality regulations, and 3) gaps in national emissions inventories. This project illustrates SERVIR's goal of the transition of science to support decision-making through capacity building in Mesoamerica, and it aligns with the Group on Earth Observations' health societal benefit theme. This presentation will describe technical aspects of the development of the models and outline key steps in our successful collaboration with the Mesoamerican stakeholders, including the processes of identifying and engaging decision-makers, understanding their requirements and limitations, communicating status updates on a regular basis, and providing sufficient training for end users to be able to utilize the models in a decision-making context.

A Novel Software Platform Extending Advances in Monitoring Technologies to On-demand Decision Support

NASA Astrophysics Data System (ADS)

Ormerod, R.; Scholl, M.

2017-12-01

Rapid evolution is occurring in the monitoring and assessment of air emissions and their impacts. The development of next generation lower cost sensor technologies creates the potential for much more intensive and far-reaching monitoring networks that provide spatially rich data. While much attention at present is being directed at the types and performance characteristics of sensor technologies, it is important also that the full potential of rich data sources be realized. Parallel to sensor developments, software platforms to display and manage data in real time are increasingly common adjuncts to sensor networks. However, the full value of data can be realized by extending platform capabilities to include complex scientific functions that are integrated into an action-oriented management framework. Depending on the purpose and nature of a monitoring network, there will be a variety of potential uses of the data or its derivatives, for example: statistical analysis for policy development, event analysis, real-time issue management including emergency response and complaints, and predictive management. Moving these functions into an on-demand, optionally mobile, environment greatly increases the value and accessibility of the data. Increased interplay between monitoring data and decision-making in an operational environment is optimised by a system that is designed with equal weight on technical robustness and user experience. A system now being used by several regulatory agencies and a larger number of industries in the US, Latin America, Europe, Australia and Asia has been developed to provide a wide range of on-demand decision-support in addition to the basic data collection, display and management that most platforms offer. With stable multi-year operation, the platform, known as Envirosuite, is assisting organisations to both reduce operating costs and improve environmental performance. Some current examples of its application across a range of applications for regulatory and industry organisations is described and demonstrated.

Integrating Clarus weather station data and state crash data into a travel decision support tool.

DOT National Transportation Integrated Search

2011-09-23

2009 crash data from the State of Michigan was combined with weather data from four Clarus weather stations in the Upper Peninsula of Michigan. Crashes were monitored within a 50 mile radius and associated with weather conditions at the Clarus statio...

Iowa flood studies (IFloodS) in the South Fork experimental watershed: soil moisture and precipitation monitoring

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are valuable for hydrologic modeling and agricultural decision support. These estimates are typically produced via a combination of sparse ¬in situ networks and remotely-sensed products or where sensory grids and quality satellite estimates are unavailable, through derived h...

Student Satisfaction Survey: The Utrecht University Approach

ERIC Educational Resources Information Center

Moller, Onno

2006-01-01

Increasing attention on quality assurance, a decentralisation of responsibilities and need for quantitative data in accountability and decision support led to the development of a student satisfaction monitoring instrument at Utrecht University (UU). Initially marketing worked as a catalyst activity to prove the added value. At a later stage the…

Microbial load monitor

NASA Technical Reports Server (NTRS)

Holen, J. T.; Royer, E. R.

1976-01-01

A card configuration which combines the functions of identification, enumeration and antibiotic sensitivity into one card was developed. An instrument package was designed around the card to integrate the card filling, incubation reading, computation and decision making process into one compact unit. Support equipment was also designed to prepare the expandable material used in the MLM.

Developmental Evaluation: Applying Complexity Concepts to Enhance Innovation and Use

ERIC Educational Resources Information Center

Patton, Michael Quinn

2010-01-01

Developmental evaluation (DE) offers a powerful approach to monitoring and supporting social innovations by working in partnership with program decision makers. In this book, eminent authority shows how to conduct evaluations within a DE framework. Patton draws on insights about complex dynamic systems, uncertainty, nonlinearity, and emergence. He…

A Decision Support System for Tele-Monitoring COPD-Related Worrisome Events.

PubMed

Merone, Mario; Pedone, Claudio; Capasso, Giuseppe; Incalzi, Raffaele Antonelli; Soda, Paolo

2017-03-01

Chronic Obstructive Pulmonary Disease (COPD) is a preventable, treatable, and slowly progressive disease, whose course is aggravated by a periodic worsening of symptoms and lung function lasting for several days. The development of home telemonitoring systems has made possible to collect symptoms and physiological data in electronic records, boosting the development of decision support systems (DSSs). Current DSSs work with physiological measurements collected by means of several measuring and communication devices as well as with symptoms gathered by questionnaires submitted to COPD subjects. However, this contrasts with the advices provided by the World Health Organization and the Global initiative for chronic Obstructive Lung Disease that recommend to avoid invasive or complex daily measurements. For these reasons this manuscript presents a DSS detecting the onset of worrisome events in COPD subjects. It uses the hearth rate and the oxygen saturation, which can be collected via a pulse oximeter. The DSS consists in a binary finite state machine, whose training stage allows a subject specific personalization of the predictive model, triggering warnings, and alarms as the health status evolves over time. The experiments on data collected from 22 COPD patients tele-monitored at home for six months show that the system recognition performance is better than the one achieved by medical experts. Furthermore, the support offered by the system in the decision-making process allows to increase the agreement between the specialists, largely impacting the recognition of the worrisome events.

Comparison of Veteran experiences of low-cost, home-based diet and exercise interventions.

PubMed

Holtz, Bree; Krein, Sarah L; Bentley, Douglas R; Hughes, Maria E; Giardino, Nicholas D; Richardson, Caroline R

2014-01-01

Obesity is a significant health problem among Veterans who receive care from the Department of Veterans Affairs, as it is for so many other Americans. Veterans from Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) experience a myriad of chronic conditions, which can make it difficult to maintain a physically active lifestyle. This pilot study tested the feasibility and user satisfaction with three low-cost, home-based diet and exercise programs, as well as point-of-decision prompts among these Veterans. The three programs target mechanisms that have been shown to improve healthy behavior change, including (1) online mediated social support, (2) objective monitoring of physical activity, and (3) structured high-intensity workouts. This was a randomized crossover trial; each participant used two of the three programs, and all used the point-of-decision prompts. Our qualitative results identified five overall themes related to social support, objective monitoring, structured activity, awareness and understanding, and the point-of-decision prompts. In general, participants were satisfied with and lost weight with each of the interventions. This study demonstrated that these low-cost interventions could be successful with the OIF/OEF Veteran population. A larger and longer study is planned to further investigate the effectiveness of these interventions.

Reflections on a vision for integrated research and monitoring after 15 years

USGS Publications Warehouse

Murdoch, Peter S.; McHale, Michael; Baron, Jill S.

2014-01-01

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.

MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring

NASA Technical Reports Server (NTRS)

Saeed, M.; Lieu, C.; Raber, G.; Mark, R. G.

2002-01-01

Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.

Posterior cingulate cortex mediates outcome-contingent allocation of behavior

PubMed Central

Hayden, Benjamin Y.; Nair, Amrita C.; McCoy, Allison N.; Platt, Michael L.

2008-01-01

SUMMARY Adaptive decision making requires selecting an action and then monitoring its consequences to improve future decisions. The neuronal mechanisms supporting action evaluation and subsequent behavioral modification, however, remain poorly understood. To investigate the contribution of posterior cingulate cortex (CGp) to these processes, we recorded activity of single neurons in monkeys performing a gambling task in which the reward outcome of each choice strongly influenced subsequent choices. We found that CGp neurons signaled reward outcomes in a nonlinear fashion, and that outcome-contingent modulations in firing rate persisted into subsequent trials. Moreover, firing rate on any one trial predicted switching to the alternative option on the next trial. Finally, microstimulation in CGp following risky choices promoted a preference reversal for the safe option on the following trial. Collectively, these results demonstrate that CGp directly contributes to the evaluative processes that support dynamic changes in decision making in volatile environments. PMID:18940585

Evaluation and prioritization of stream habitat monitoring in the Lower Columbia Salmon and Steelhead Recovery Domain as related to the habitat monitoring needs of ESA recovery plans

USGS Publications Warehouse

Puls, Amy L.; Anlauf Dunn, Kara; Graham Hudson, Bernadette

2014-01-01

The lower Columbia River and its tributaries once supported abundant runs of salmon and steelhead; however, there are five species currently listed under the federal Endangered Species Act (ESA). The National Marine Fisheries Service has completed, and is proposing for adoption, a comprehensive ESA Recovery Plan for the Lower Columbia Evolutionarily Significant Units (ESUs) based on the recovery plans developed by Oregon and Washington. One of the primary factors attributed to the decline of these species is habitat degradation. There are numerous entities conducting status and/or trends monitoring of instream habitat in the lower Columbia River Basin, but because the programs were developed for agency specific reasons, the existing monitoring efforts are not well coordinated, and often lack the spatial coverage, certainty, or species coverage necessary to answer questions related to status and trends of the ESA listed populations. The Pacific Northwest Aquatic Monitoring Partnership’s Integrated Status and Trends Monitoring (ISTM) project was initiated to improve integration of existing and new monitoring efforts by developing recommendations for sampling frames, protocols, and data sharing. In an effort to meet the ISTM project goals, five objectives were identified: (1) identify and prioritize decisions, questions, and monitoring objectives, (2) evaluate how existing programs align with these management decisions, questions, and objectives, (3) identify the most appropriate monitoring design to inform priority management decisions, questions, and objectives, (4) use trade-off analysis to develop specific recommendations for monitoring based on outcomes of Objectives 1-3 and (5) recommend implementation and reporting mechanisms. This report summarizes the effort to address Objectives 1 and 2, detailing the commonalities among the habitat characteristics that all entities measure and monitor, and how the metrics align with the priorities listed in the comprehensive recovery plan for the Lower Columbia ESUs.

Fidelity to a behavioral intervention to improve goals of care decisions for nursing home residents with advanced dementia.

PubMed

Hanson, Laura C; Song, Mi-Kyung; Zimmerman, Sheryl; Gilliam, Robin; Rosemond, Cherie; Chisholm, Latarsha; Lin, Feng-Chang

2016-12-01

Ensuring fidelity to a behavioral intervention implemented in nursing homes requires awareness of the unique considerations of this setting for research. The purpose of this article is to describe the goals of care cluster-randomized trial and the methods used to monitor and promote fidelity to a goals of care decision aid intervention delivered in nursing homes. The cluster randomized trial tested whether a decision aid for goals of care in advanced dementia could improve (1) the quality of communication and decision-making, (2) the quality of palliative care, and (3) the quality of dying for nursing home residents with advanced dementia. In 11 intervention nursing homes, family decision-makers for residents with advanced dementia received a two-component intervention: viewing a video decision aid about goals of care choices and then participating in a structured decision-making discussion with the nursing home care plan team, ideally within 3 months after the decision aid was viewed. Following guidelines from the National Institutes of Health Behavior Change Consortium, fidelity was assessed in study design, in nursing home staff training for intervention implementation, and in monitoring and receipt of the intervention. We also monitored the content and timing of goals of care discussions. Investigators enrolled 151 family decision-maker/resident dyads in intervention sites; of those, 136 (90%) received both components of the intervention, and 92%-99% of discussions addressed each of four recommended content areas-health status, goals of care, choice of a goal, and treatment planning. A total of 94 (69%) of the discussions between family decision-makers and the nursing home care team were completed within 3 months. The methods we used for intervention fidelity allowed nursing home staff to implement a goals of care decision aid intervention for advanced dementia. Key supports for implementation included design features that aligned with nursing home practice, efficient staff training, and a structured guide for goals of care discussions between family decision-makers and staff. These approaches may be used to promote fidelity to behavioral interventions in future clinical trials. © The Author(s) 2016.

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

PubMed

Haynes, R Brian; Wilczynski, Nancy L

2010-02-05

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

Improving Decision-Making Activities for Meningitis and Malaria

NASA Astrophysics Data System (ADS)

Ceccato, P.; Trzaska, S.; Perez, C.; Kalashnikova, O. V.; del Corral, J.; Cousin, R.; Blumenthal, M. B.; Connor, S.; Thomson, M. C.

2012-12-01

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use, and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular Meningitis and Malaria. In this paper we present the new and improved products that have been developed for monitoring dust, temperature, rainfall and vectorial capacity model for monitoring and forecasting risks of Meningitis and Malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

AI based HealthCare Platform for Real Time, Predictive and Prescriptive Analytics using Reactive Programming

NASA Astrophysics Data System (ADS)

Kaur, Jagreet; Singh Mann, Kulwinder, Dr.

2018-01-01

AI in Healthcare needed to bring real, actionable insights and Individualized insights in real time for patients and Doctors to support treatment decisions., We need a Patient Centred Platform for integrating EHR Data, Patient Data, Prescriptions, Monitoring, Clinical research and Data. This paper proposes a generic architecture for enabling AI based healthcare analytics Platform by using open sources Technologies Apache beam, Apache Flink Apache Spark, Apache NiFi, Kafka, Tachyon, Gluster FS, NoSQL- Elasticsearch, Cassandra. This paper will show the importance of applying AI based predictive and prescriptive analytics techniques in Health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real-time through an intelligent process analysis and big data processing.

Neural signatures of experience-based improvements in deterministic decision-making.

PubMed

Tremel, Joshua J; Laurent, Patryk A; Wolk, David A; Wheeler, Mark E; Fiez, Julie A

2016-12-15

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural signatures of experience-based improvements in deterministic decision-making

PubMed Central

Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

2016-01-01

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644

Effects of Simulated Pathophysiology on the Performance of a Decision Support Medical Monitoring System for Early Detection of Hemodynamic Decompensation in Humans

DTIC Science & Technology

2015-10-01

Arterial oxygen saturation was monitored 130 using a finger pulse oximeter and end-tidal CO2 (ETCO2) was collected from a nasal cannula 131 (Cardiocap/5...Johnson et al, J Appl Physiol 2014 PMID 24876357. 5 Keywords Trauma, coagulation, central venous pressure, stroke volume, pulse pressure...Johnson BD, Curry TB, Convertino VA, & Joyner MJ. The association between pulse pressure and stroke volume during lower body negative pressure and

Informal and formal trail monitoring protocols and baseline conditions: Acadia National Park

USGS Publications Warehouse

Marion, Jeffrey L.; Wimpey, Jeremy F.; Park, L.

2011-01-01

At Acadia National Park, changing visitor use levels and patterns have contributed to an increasing degree of visitor use impacts to natural and cultural resources. To better understand the extent and severity of these resource impacts and identify effective management techniques, the park sponsored this research to develop monitoring protocols, collect baseline data, and identify suggestions for management strategies. Formal and informal trails were surveyed and their resource conditions were assessed and characterized to support park planning and management decision-making.

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 across these platforms. Moving to a data-centric architecture requires data management methodologies to be overhauled by default and we show how end-to-end data provenancing and dependency management is implicit in such an environment and how it benefits system administration as well as the user community. Whilst the architectural experiences are drawn from the oil industry, we believe that they are more broadly applicable in academic and government settings where large volumes of data are added to incrementally and require revisiting with low analytical latency and we suggest application to earthquake monitoring and remote sensing networks.

The Value of Information from a GRACE-Enhanced Drought Severity Index

NASA Astrophysics Data System (ADS)

Kuwayama, Y.; Bernknopf, R.; Brookshire, D.; Macauley, M.; Zaitchik, B. F.; Rodell, M.; Vail, P.; Thompson, A.

2015-12-01

In this project, we develop a framework to estimate the economic value of information from the Gravity and Climate Experiment (GRACE) for drought monitoring and to understand how the GRACE Data Assimilation (GRACE-DA) system can inform decision making to improve regional economic outcomes. Specifically, we consider the potential societal value of further incorporating GRACE-DA information into the U.S. Drought Monitor mapmaking process. Research activities include (a) a literature review, (b) a series of listening sessions with experts and stakeholders, (c) the development of a conceptual economic framework based on a Bayesian updating procedure, and (d) an econometric analysis and retrospective case study to understand the GRACE-DA contribution to agricultural policy and production decisions. Taken together, the results from these research activities support our conclusion that GRACE-DA has the potential to lower the variance associated with our understanding of drought and that this improved understanding has the potential to change policy decisions that lead to tangible societal benefits.

Resources monitoring and automatic management system for multi-VO distributed computing system

NASA Astrophysics Data System (ADS)

Chen, J.; Pelevanyuk, I.; Sun, Y.; Zhemchugov, A.; Yan, T.; Zhao, X. H.; Zhang, X. M.

2017-10-01

Multi-VO supports based on DIRAC have been set up to provide workload and data management for several high energy experiments in IHEP. To monitor and manage the heterogeneous resources which belong to different Virtual Organizations in a uniform way, a resources monitoring and automatic management system based on Resource Status System(RSS) of DIRAC has been presented in this paper. The system is composed of three parts: information collection, status decision and automatic control, and information display. The information collection includes active and passive way of gathering status from different sources and stores them in databases. The status decision and automatic control is used to evaluate the resources status and take control actions on resources automatically through some pre-defined policies and actions. The monitoring information is displayed on a web portal. Both the real-time information and historical information can be obtained from the web portal. All the implementations are based on DIRAC framework. The information and control including sites, policies, web portal for different VOs can be well defined and distinguished within DIRAC user and group management infrastructure.

Embedded sensor systems for health - providing the tools in future healthcare.

PubMed

Lindén, Maria; Björkman, Mats

2014-01-01

Wearable, embedded sensor systems for health applications are foreseen to be enablers in the future healthcare. They will provide ubiquitous monitoring of multiple parameters without restricting the person to stay at home or in the hospital. By following trend changes in the health status, early deteriorations will be detected and treatment can start earlier. Also health prevention will be supported. Such future healthcare requires technology development, including miniaturized sensors, smart textiles and wireless communication. The tremendous amount of data generated by these systems calls for both signal processing and decision support to guarantee the quality of data and avoid overflow of information. Safe and secure communications have to protect the integrity of the persons monitored.

Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor.

PubMed

Pérez-Gandía, Carmen; García-Sáez, Gema; Subías, David; Rodríguez-Herrero, Agustín; Gómez, Enrique J; Rigla, Mercedes; Hernando, M Elena

2018-03-01

In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabetes in decision making and allow them to react at time scales shorter than the scheduled face-to-face visits. This work presents a decision support system (DSS), based on glucose prediction, to assist patients in a mobile environment. The system's impact on therapeutic corrective actions has been evaluated in a randomized crossover pilot study focused on interprandial periods. Twelve people with type 1 diabetes treated with insulin pump participated in two phases: In the experimental phase (EP) patients used the DSS to modify initial corrective decisions in presence of hypoglycemia or hyperglycemia events. In the control phase (CP) patients were asked to follow decisions without knowing the glucose prediction. A telemedicine platform allowed participants to register monitoring data and decisions and allowed endocrinologists to supervise data at the hospital. The study period was defined as a postprediction (PP) time window. After knowing the glucose prediction, participants modified the initial decision in 20% of the situations. No statistically significant differences were found in the PP Kovatchev's risk index change (-1.23 ± 11.85 in EP vs -0.56 ± 6.06 in CP). Participants had a positive opinion about the DSS with an average score higher than 7 in a usability questionnaire. The DSS had a relevant impact in the participants' decision making while dealing with T1DM and showed a high confidence of patients in the use of glucose prediction.

Use of monitoring data to support conservation management and policy decisions in Micronesia.

PubMed

Montambault, Jensen Reitz; Wongbusarakum, Supin; Leberer, Trina; Joseph, Eugene; Andrew, Wayne; Castro, Fran; Nevitt, Brooke; Golbuu, Yimnang; Oldiais, Noelle W; Groves, Craig R; Kostka, Willy; Houk, Peter

2015-10-01

Adaptive management implies a continuous knowledge-based decision-making process in conservation. Yet, the coupling of scientific monitoring and management frameworks remains rare in practice because formal and informal communication pathways are lacking. We examined 4 cases in Micronesia where conservation practitioners are using new knowledge in the form of monitoring data to advance marine conservation. These cases were drawn from projects in Micronesia Challenge jurisdictions that received funding for coupled monitoring-to-management frameworks and encompassed all segments of adaptive management. Monitoring in Helen Reef, Republic of Palau, was catalyzed by coral bleaching and revealed evidence of overfishing that led to increased enforcement and outreach. In Nimpal Channel, Yap, Federated States of Micronesia (FSM), monitoring the recovery of marine food resources after customary restrictions were put in place led to new, more effective enforcement approaches. Monitoring in Laolao Bay, Saipan, Commonwealth of the Northern Mariana Islands, was catalyzed by observable sediment loads from poor land-use practices and resulted in actions that reduced land-based threats, particularly littering and illegal burning, and revealed additional threats from overfishing. Pohnpei (FSM) began monitoring after observed declines in grouper spawning aggregations. This data led to adjusting marine conservation area boundaries and implementing market-based size class restrictions. Two themes emerged from these cases. First, in each case monitoring was conducted in a manner relevant to the social and ecological systems and integrated into the decision-making process. Second, conservation practitioners and scientists in these cases integrated culturally appropriate stakeholder engagement throughout all phases of the adaptive management cycle. More broadly, our study suggests, when describing adaptive management, providing more details on how monitoring and management activities are linked at similar spatial scales and across similar time frames can enhance the application of knowledge. © 2015 The Authors Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Restoration handbook for sagebrush steppe ecosystems with emphasis on greater sage-grouse habitat—Part 3. Site level restoration decisions

USGS Publications Warehouse

Pyke, David A.; Chambers, Jeanne C.; Pellant, Mike; Miller, Richard F.; Beck, Jeffrey L.; Doescher, Paul S.; Roundy, Bruce A.; Schupp, Eugene W.; Knick, Steven T.; Brunson, Mark; McIver, James D.

2017-02-14

Sagebrush steppe ecosystems in the United States currently (2016) occur on only about one-half of their historical land area because of changes in land use, urban growth, and degradation of land, including invasions of non-native plants. The existence of many animal species depends on the existence of sagebrush steppe habitat. The greater sage-grouse (Centrocercus urophasianus) depends on large landscapes of intact habitat of sagebrush and perennial grasses for their existence. In addition, other sagebrush-obligate animals have similar requirements and restoration of landscapes for greater sage-grouse also will benefit these animals. Once sagebrush lands are degraded, they may require restoration actions to make those lands viable habitat for supporting sagebrush-obligate animals, livestock, and wild horses, and to provide ecosystem services for humans now and for future generations.When a decision is made on where restoration treatments should be applied, there are a number of site-specific decisions managers face before selecting the appropriate type of restoration. This site-level decision tool for restoration of sagebrush steppe ecosystems is organized in nine steps.Step 1 describes the process of defining site-level restoration objectives.Step 2 describes the ecological site characteristics of the restoration site. This covers soil chemistry and texture, soil moisture and temperature regimes, and the vegetation communities the site is capable of supporting.Step 3 compares the current vegetation to the plant communities associated with the site State and Transition models.Step 4 takes the manager through the process of current land uses and past disturbances that may influence restoration success.Step 5 is a brief discussion of how weather before and after treatments may impact restoration success.Step 6 addresses restoration treatment types and their potential positive and negative impacts on the ecosystem and on habitats, especially for greater sage-grouse. We discuss when passive restoration options may be sufficient and when active restoration may be necessary to achieve restoration objectives.Step 7 addresses decisions regarding post-restoration livestock grazing management.Step 8 addresses monitoring of the restoration; we discuss important aspects associated with implementation monitoring as well as effectiveness monitoring.Step 9 takes the information learned from monitoring to determine how restoration actions in the future might be adapted to improve restoration success.

More than just consumers: Integrating local observations into drought monitoring to better support decision making

NASA Astrophysics Data System (ADS)

Ferguson, D. B.; Masayesva, A.; Meadow, A. M.; Crimmins, M.

2016-12-01

Drought monitoring and drought planning are complex endeavors. Measures of precipitation or streamflow provide little context for understanding how social and environmental systems impacted by drought are responding. In arid and semi-arid regions of the world, this challenge is particularly acute since social-ecological systems are already well-adapted to dry conditions. Understanding what drought means in these regions is an important first step in developing a decision-relevant monitoring system. Traditional drought indices may be of some use, but local observations may ultimately be more relevant for informing difficult decisions in response to unusually dry conditions. This presentation will focus on insights gained from a collaborative project between the University of Arizona and the Hopi Tribe-a Native American community in the U.S. Southwest-to develop a drought information system that is responsive to local needs. The primary goal of the project was to develop a system that: is based on how drought is experienced by Hopi citizens and resource managers, can incorporate local observations of drought impacts as well as conventional indicators, and brings together local expertise with conventional science-based observations. This kind of drought monitoring system can harnesses as much available information as possible to inform resource managers, political leaders, and citizens about drought conditions, but such a system can also engage these local drought stakeholders in observing, thinking about, and helping guide planning for drought.

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.

The use of control charts by laypeople and hospital decision-makers for guiding decision making.

PubMed

Schmidtke, K A; Watson, D G; Vlaev, I

2017-07-01

Graphs presenting healthcare data are increasingly available to support laypeople and hospital staff's decision making. When making these decisions, hospital staff should consider the role of chance-that is, random variation. Given random variation, decision-makers must distinguish signals (sometimes called special-cause data) from noise (common-cause data). Unfortunately, many graphs do not facilitate the statistical reasoning necessary to make such distinctions. Control charts are a less commonly used type of graph that support statistical thinking by including reference lines that separate data more likely to be signals from those more likely to be noise. The current work demonstrates for whom (laypeople and hospital staff) and when (treatment and investigative decisions) control charts strengthen data-driven decision making. We present two experiments that compare people's use of control and non-control charts to make decisions between hospitals (funnel charts vs. league tables) and to monitor changes across time (run charts with control lines vs. run charts without control lines). As expected, participants more accurately identified the outlying data using a control chart than using a non-control chart, but their ability to then apply that information to more complicated questions (e.g., where should I go for treatment?, and should I investigate?) was limited. The discussion highlights some common concerns about using control charts in hospital settings.

Current Directions in Adding Value to Earth Observation Products for Decision Support

NASA Astrophysics Data System (ADS)

Ryker, S. J.

2015-12-01

Natural resource managers and infrastructure planners face increasingly complex challenges, given competing demands for resources and changing conditions due to climate and land use change. These pressures create demand for high-quality, timely data; for both one-time decision support and long-term monitoring; and for techniques to articulate the value of resources in monetary and nonmonetary terms. To meet the need for data, the U.S. government invests several billion dollars per year in Earth observations collected from satellite, airborne, terrestrial, and ocean-based systems. Earth observation-based decision support is coming of age; user surveys show that these data are used in an increasing variety of analyses. For example, since the U.S. Department of the Interior/U.S. Geological Survey's (USGS) 2008 free and open data policy for the Landsat satellites, downloads from the USGS archive have increased from 20,000 Landsat scenes per year to 10 million per year and climbing, with strong growth in both research and decision support fields. However, Earth observation-based decision support still poses users a number of challenges. Many of those Landsat downloads support a specialized community of remote sensing scientists, though new technologies promise to increase the usability of remotely sensed data for the larger GIS community supporting planning and resource management. Serving this larger community also requires supporting the development of increasingly interpretive products, and of new approaches to host and update products. For example, automating updates will add value to new essential climate variable products such as surface water extent and wildfire burned area extent. Projections of future urbanization in the southeastern U.S. are most useful when long-term land cover trends are integrated with street-level community data and planning tools. The USGS assessment of biological carbon sequestration in vegetation and shallow soils required a significant research investment in satellite and in situ measurements and biogeochemical and climate modeling, and is already providing decision support at a variety of scales; once operationalized, it will be a tool for adaptive management from field-scale soil and wetland conservation projects to national-scale policy.

Collaboration pathway(s) using new tools for optimizing operational climate monitoring from space

NASA Astrophysics Data System (ADS)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2014-10-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the needs of decision makers, scientific investigators and global users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent (2014) rulebased decision engine modeling runs that targeted optimizing the intended NPOESS architecture, becomes a surrogate for global operational climate monitoring architecture(s). This rule-based systems tools provide valuable insight for Global climate architectures, through the comparison and evaluation of alternatives considered and the exhaustive range of trade space explored. A representative optimization of Global ECV's (essential climate variables) climate monitoring architecture(s) is explored and described in some detail with thoughts on appropriate rule-based valuations. The optimization tools(s) suggest and support global collaboration pathways and hopefully elicit responses from the audience and climate science shareholders.

Cover estimations using object-based image analysis rule sets developed across multiple scales in pinyon-juniper woodlands

USDA-ARS?s Scientific Manuscript database

Numerous studies have been conducted that evaluate the utility of remote sensing for monitoring and assessing vegetation and ground cover to support land management decisions and complement ground-measurements. However, few land cover comparisons have been made using high-resolution imagery and obj...

Soil moisture and precipitation monitoring in the South Fork experimental watershed during the Iowa flood studies (IFloodS)

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are valuable for hydrologic modeling and agricultural decision support. These estimates are typically produced via a combination of sparse in situ networks and remotely-sensed products or where sensory grids and quality satellite estimates are unavailable, through derived hy...

An Automated Approach to Peanut dring with real-time monitoring of in-shell Kernel Moisture Content with a Microwave Sensor

USDA-ARS?s Scientific Manuscript database

Today’s peanut drying processes utilize decision support software based on modeling and require substantial human interaction for moisture sampling. These conditions increase the likelihood of peanuts being overdried or underdried. This research addresses the need for an automated controller with re...

Interactive Genetic Algorithm - An Adaptive and Interactive Decision Support Framework for Design of Optimal Groundwater Monitoring Plans

NASA Astrophysics Data System (ADS)

Babbar-Sebens, M.; Minsker, B. S.

2006-12-01

In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives that met the DM's preference criteria, therefore allowing the expert to select among several strong candidate designs depending on her/his LTM budget, c) two of the methodologies - Case-Based Micro Interactive Genetic Algorithm (CBMIGA) and Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) - were also able to assist in controlling human fatigue and adapt to the DM's learning process.

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

Decision Analysis Tools for Volcano Observatories

NASA Astrophysics Data System (ADS)

Hincks, T. H.; Aspinall, W.; Woo, G.

2005-12-01

Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.

Distributed decision-making in electric power system transmission maintenance scheduling using multi-agent systems (MAS)

NASA Astrophysics Data System (ADS)

Zhang, Zhong

In this work, motivated by the need to coordinate transmission maintenance scheduling among a multiplicity of self-interested entities in restructured power industry, a distributed decision support framework based on multiagent negotiation systems (MANS) is developed. An innovative risk-based transmission maintenance optimization procedure is introduced. Several models for linking condition monitoring information to the equipment's instantaneous failure probability are presented, which enable quantitative evaluation of the effectiveness of maintenance activities in terms of system cumulative risk reduction. Methodologies of statistical processing, equipment deterioration evaluation and time-dependent failure probability calculation are also described. A novel framework capable of facilitating distributed decision-making through multiagent negotiation is developed. A multiagent negotiation model is developed and illustrated that accounts for uncertainty and enables social rationality. Some issues of multiagent negotiation convergence and scalability are discussed. The relationships between agent-based negotiation and auction systems are also identified. A four-step MAS design methodology for constructing multiagent systems for power system applications is presented. A generic multiagent negotiation system, capable of inter-agent communication and distributed decision support through inter-agent negotiations, is implemented. A multiagent system framework for facilitating the automated integration of condition monitoring information and maintenance scheduling for power transformers is developed. Simulations of multiagent negotiation-based maintenance scheduling among several independent utilities are provided. It is shown to be a viable alternative solution paradigm to the traditional centralized optimization approach in today's deregulated environment. This multiagent system framework not only facilitates the decision-making among competing power system entities, but also provides a tool to use in studying competitive industry relative to monopolistic industry.

Incorporating geodiversity into conservation decisions.

PubMed

Comer, Patrick J; Pressey, Robert L; Hunter, Malcolm L; Schloss, Carrie A; Buttrick, Steven C; Heller, Nicole E; Tirpak, John M; Faith, Daniel P; Cross, Molly S; Shaffer, Mark L

2015-06-01

In a rapidly changing climate, conservation practitioners could better use geodiversity in a broad range of conservation decisions. We explored selected avenues through which this integration might improve decision making and organized them within the adaptive management cycle of assessment, planning, implementation, and monitoring. Geodiversity is seldom referenced in predominant environmental law and policy. With most natural resource agencies mandated to conserve certain categories of species, agency personnel are challenged to find ways to practically implement new directives aimed at coping with climate change while retaining their species-centered mandate. Ecoregions and ecological classifications provide clear mechanisms to consider geodiversity in plans or decisions, the inclusion of which will help foster the resilience of conservation to climate change. Methods for biodiversity assessment, such as gap analysis, climate change vulnerability analysis, and ecological process modeling, can readily accommodate inclusion of a geophysical component. We adapted others' approaches for characterizing landscapes along a continuum of climate change vulnerability for the biota they support from resistant, to resilient, to susceptible, and to sensitive and then summarized options for integrating geodiversity into planning in each landscape type. In landscapes that are relatively resistant to climate change, options exist to fully represent geodiversity while ensuring that dynamic ecological processes can change over time. In more susceptible landscapes, strategies aiming to maintain or restore ecosystem resilience and connectivity are paramount. Implementing actions on the ground requires understanding of geophysical constraints on species and an increasingly nimble approach to establishing management and restoration goals. Because decisions that are implemented today will be revisited and amended into the future, increasingly sophisticated forms of monitoring and adaptation will be required to ensure that conservation efforts fully consider the value of geodiversity for supporting biodiversity in the face of a changing climate. © 2015 Society for Conservation Biology.

Support to the Air Force Installation and Mission Support Center: Enabling AFIMSC’s Role in Agile Combat Support Planning, Execution, Monitoring, and Control

DTIC Science & Technology

2017-06-23

field of organizational design is that decisions should be made by those who have the necessary information, something AFIMSC does not yet have. See...data system designator , D087X. EXPRESS is the Air Force’s implemented version of the tool DRIVE, which was developed at RAND in the early 1990s. The...The UMMIPS system could also serve as a pattern. UMMIPS works by assigning a priority designator based on a force activity designator (FAD) (the

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

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

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

Investigation assessing the publicly available evidence supporting postmarketing withdrawals, revocations and suspensions of marketing authorisations in the EU since 2012

PubMed Central

Lynn, Elizabeth; Shakir, Saad

2018-01-01

Objectives To assess the sources of publicly available evidence supporting withdrawal, revocation or suspension of marketing authorisations (‘regulatory actions’) due to safety reasons in the EU since 2012 and to investigate the time taken since initial marketing authorisation to reach these regulatory decisions. Setting This investigation examined the sources of evidence supporting 18 identified prescription medicinal products which underwent regulatory action due to safety reasons within the EU in the period 1 July 2012 to 31 December 2016. Results Eighteen single or combined active substances (‘medicinal products’) withdrawn, revoked or suspended within the EU for safety reasons between 2012 and 2016 met the inclusion criteria. Case reports were most commonly cited, supporting 94.4% of regulatory actions (n=17), followed by randomised controlled trial, meta-analyses, animal and in vitro, ex vivo or in silico study designs, each cited in 72.2% of regulatory actions (n=13). Epidemiological study designs were least commonly cited (n=8, 44.4%). Multiple sources of evidence contributed to 94.4% of regulatory decisions (n=17). Death was the most common adverse drug reaction leading to regulatory action (n=5; 27.8%), with four of these related to medication error or overdose. Median (IQR) time taken to reach a decision from the start of regulatory review was found to be 204.5 days (143, 535 days) and decreased across the study period. Duration of marketing prior to regulatory action, from the medicinal product’s authorisation date, increased across the period 2012–2016. Conclusions The sources of evidence supporting pharmacovigilance regulatory activities appear to have changed since implementation of Directive 2010/84/EU and Regulation (EU) No. 1235/2010. This, together with a small improvement in regulatory efficiency, suggests progress towards more rapid regulatory decisions based on more robust evidence. Future research should continue to monitor sources of evidence supporting regulatory decisions and the time taken to reach these decisions over time. PMID:29362275

Assessment of readiness for clinical decision support to aid laboratory monitoring of immunosuppressive care at U.S. liver transplant centers.

PubMed

Jacobs, J; Weir, C; Evans, R S; Staes, C

2014-01-01

Following liver transplantation, patients require lifelong immunosuppressive care and monitoring. Computerized clinical decision support (CDS) has been shown to improve post-transplant immunosuppressive care processes and outcomes. The readiness of transplant information systems to implement computerized CDS to support post-transplant care is unknown. a) Describe the current clinical information system functionality and manual and automated processes for laboratory monitoring of immunosuppressive care, b) describe the use of guidelines that may be used to produce computable logic and the use of computerized alerts to support guideline adherence, and c) explore barriers to implementation of CDS in U.S. liver transplant centers. We developed a web-based survey using cognitive interviewing techniques. We surveyed 119 U.S. transplant programs that performed at least five liver transplantations per year during 2010-2012. Responses were summarized using descriptive analyses; barriers were identified using qualitative methods. Respondents from 80 programs (67% response rate) completed the survey. While 98% of programs reported having an electronic health record (EHR), all programs used paper-based manual processes to receive or track immunosuppressive laboratory results. Most programs (85%) reported that 30% or more of their patients used external laboratories for routine testing. Few programs (19%) received most external laboratory results as discrete data via electronic interfaces while most (80%) manually entered laboratory results into the EHR; less than half (42%) could integrate internal and external laboratory results. Nearly all programs had guidelines regarding pre-specified target ranges (92%) or testing schedules (97%) for managing immunosuppressive care. Few programs used computerized alerting to notify transplant coordinators of out-of-range (27%) or overdue laboratory results (20%). Use of EHRs is common, yet all liver transplant programs were largely dependent on manual paper-based processes to monitor immunosuppression for post-liver transplant patients. Similar immunosuppression guidelines provide opportunities for sharing CDS once integrated laboratory data are available.

Water quality monitoring strategies - A review and future perspectives.

PubMed

Behmel, S; Damour, M; Ludwig, R; Rodriguez, M J

2016-11-15

The reliable assessment of water quality through water quality monitoring programs (WQMPs) is crucial in order for decision-makers to understand, interpret and use this information in support of their management activities aiming at protecting the resource. The challenge of water quality monitoring has been widely addressed in the literature since the 1940s. However, there is still no generally accepted, holistic and practical strategy to support all phases of WQMPs. The purpose of this paper is to report on the use cases a watershed manager has to address to plan or optimize a WQMP from the challenge of identifying monitoring objectives; selecting sampling sites and water quality parameters; identifying sampling frequencies; considering logistics and resources to the implementation of actions based on information acquired through the WQMP. An inventory and critique of the information, approaches and tools placed at the disposal of watershed managers was proposed to evaluate how the existing information could be integrated in a holistic, user-friendly and evolvable solution. Given the differences in regulatory requirements, water quality standards, geographical and geological differences, land-use variations, and other site specificities, a one-in-all solution is not possible. However, we advance that an intelligent decision support system (IDSS) based on expert knowledge that integrates existing approaches and past research can guide a watershed manager through the process according to his/her site-specific requirements. It is also necessary to tap into local knowledge and to identify the knowledge needs of all the stakeholders through participative approaches based on geographical information systems and adaptive survey-based questionnaires. We believe that future research should focus on developing such participative approaches and further investigate the benefits of IDSS's that can be updated quickly and make it possible for a watershed manager to obtain a timely, holistic view and support for every aspect of planning and optimizing a WQMP. Copyright © 2016 Elsevier B.V. All rights reserved.

Science and Systems in Support of Multi-hazard Early Warnings and Decisions

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2015-12-01

The demand for improved climate knowledge and information is well documented. As noted in the IPCC (SREX, AR5), the UNISDR Global Assessment Reports and other assessments, this demand has increased pressure for information to support planning under changing rates and emergence of multiple hazards including climate extremes (drought, heat waves, floods). "Decision support" is now a popular term in the climate applications research community. While existing decision support activities can be identified in many disparate settings (e.g. federal, academic, private), the challenge of changing environments (coupled physical and social) is actually one of crafting implementation strategies for improving decision quality (not just meeting "user needs"). This includes overcoming weaknesses in co-production models, moving beyond DSSs as simply "software", coordinating innovation mapping and diffusion, and providing fora and gaming tools to identify common interests and differences in the way risks are perceived and managed among the affected groups. We outline the development and evolution of multi-hazard early warning systems in the United States and elsewhere, focusing on climate-related hazards. In particular, the presentation will focus on the climate science and information needed for (1) improved monitoring and modeling, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds, (4) the net benefits of using new information (5) characterizing and bridging the "last mile" in the context of longer-term risk management.

Reduction of streamflow monitoring networks by a reference point approach

NASA Astrophysics Data System (ADS)

Cetinkaya, Cem P.; Harmancioglu, Nilgun B.

2014-05-01

Adoption of an integrated approach to water management strongly forces policy and decision-makers to focus on hydrometric monitoring systems as well. Existing hydrometric networks need to be assessed and revised against the requirements on water quantity data to support integrated management. One of the questions that a network assessment study should resolve is whether a current monitoring system can be consolidated in view of the increased expenditures in time, money and effort imposed on the monitoring activity. Within the last decade, governmental monitoring agencies in Turkey have foreseen an audit on all their basin networks in view of prevailing economic pressures. In particular, they question how they can decide whether monitoring should be continued or terminated at a particular site in a network. The presented study is initiated to address this question by examining the applicability of a method called “reference point approach” (RPA) for network assessment and reduction purposes. The main objective of the study is to develop an easily applicable and flexible network reduction methodology, focusing mainly on the assessment of the “performance” of existing streamflow monitoring networks in view of variable operational purposes. The methodology is applied to 13 hydrometric stations in the Gediz Basin, along the Aegean coast of Turkey. The results have shown that the simplicity of the method, in contrast to more complicated computational techniques, is an asset that facilitates the involvement of decision makers in application of the methodology for a more interactive assessment procedure between the monitoring agency and the network designer. The method permits ranking of hydrometric stations with regard to multiple objectives of monitoring and the desired attributes of the basin network. Another distinctive feature of the approach is that it also assists decision making in cases with limited data and metadata. These features of the RPA approach highlight its advantages over the existing network assessment and reduction methods.

SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

NASA Technical Reports Server (NTRS)

Irwin, Daniel E.; Sever, Tom; Graves, Sara; Hardin, Danny

2005-01-01

In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica - composed of the seven Central American countries and the five southernmost states of Mexico - make up only a small fraction of the world s land surface. However, the region is home to seven to eight percent of the planet s biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica s biological and cultural diversity 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 to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in the development of SIAM-SERVIR and the plans for the future.

Objectives, priorities, reliable knowledge, and science-based management of Missouri River interior least terns and piping plovers

USGS Publications Warehouse

Sherfy, Mark; Anteau, Michael J.; Shaffer, Terry; Sovada, Marsha; Stucker, Jennifer

2011-01-01

Supporting recovery of federally listed interior least tern (Sternula antillarum athalassos; tern) and piping plover (Charadrius melodus; plover) populations is a desirable goal in management of the Missouri River ecosystem. Many tools are implemented in support of this goal, including habitat management, annual monitoring, directed research, and threat mitigation. Similarly, many types of data can be used to make management decisions, evaluate system responses, and prioritize research and monitoring. The ecological importance of Missouri River recovery and the conservation status of terns and plovers place a premium on efficient and effective resource use. Efficiency is improved when a single data source informs multiple high-priority decisions, whereas effectiveness is improved when decisions are informed by reliable knowledge. Seldom will a single study design be optimal for addressing all data needs, making prioritization of needs essential. Data collection motivated by well-articulated objectives and priorities has many advantages over studies in which questions and priorities are determined retrospectively. Research and monitoring for terns and plovers have generated a wealth of data that can be interpreted in a variety of ways. The validity and strength of conclusions from analyses of these data is dependent on compatibility between the study design and the question being asked. We consider issues related to collection and interpretation of biological data, and discuss their utility for enhancing the role of science in management of Missouri River terns and plovers. A team of USGS scientists at Northern Prairie Wildlife Research Center has been conducting tern and plover research on the Missouri River since 2005. The team has had many discussions about the importance of setting objectives, identifying priorities, and obtaining reliable information to answer pertinent questions about tern and plover management on this river system. The objectives of this presentation are to summarize those conversations and to share insights about concepts that could contribute to rigorous science support for management of this river system.

Indicators and protocols for monitoring impacts of formal and informal trails in protected areas

USGS Publications Warehouse

Marion, Jeffrey L.; Leung, Yu-Fai

2011-01-01

Trails are a common recreation infrastructure in protected areas and their conditions affect the quality of natural resources and visitor experiences. Various trail impact indicators and assessment protocols have been developed in support of monitoring programs, which are often used for management decision-making or as part of visitor capacity management frameworks. This paper reviews common indicators and assessment protocols for three types of trails, surfaced formal trails, unsurfaced formal trails, and informal (visitor-created) trails. Monitoring methods and selected data from three U.S. National Park Service units are presented to illustrate some common trail impact indicators and assessment options.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Medical knowledge packages and their integration into health-care information systems and the World Wide Web.

PubMed

Adlassnig, Klaus-Peter; Rappelsberger, Andrea

2008-01-01

Software-based medical knowledge packages (MKPs) are packages of highly structured medical knowledge that can be integrated into various health-care information systems or the World Wide Web. They have been established to provide different forms of clinical decision support such as textual interpretation of combinations of laboratory rest results, generating diagnostic hypotheses as well as confirmed and excluded diagnoses to support differential diagnosis in internal medicine, or for early identification and automatic monitoring of hospital-acquired infections. Technically, an MKP may consist of a number of inter-connected Arden Medical Logic Modules. Several MKPs have been integrated thus far into hospital, laboratory, and departmental information systems. This has resulted in useful and widely accepted software-based clinical decision support for the benefit of the patient, the physician, and the organization funding the health care system.

A "simulation chain" to define a Multidisciplinary Decision Support System for landslide risk management in pyroclastic soils

NASA Astrophysics Data System (ADS)

Damiano, E.; Mercogliano, P.; Netti, N.; Olivares, L.

2012-04-01

This paper proposes a Multidisciplinary Decision Support System (MDSS) as an approach to manage rainfall-induced shallow landslides of the flow type (flowslides) in pyroclastic deposits. We stress the need to combine information from the fields of meteorology, geology, hydrology, geotechnics and economics to support the agencies engaged in land monitoring and management. The MDSS consists of a "simulation chain" to link rainfall to effects in terms of infiltration, slope stability and vulnerability. This "simulation chain" was developed at the Euro-Mediterranean Centre for Climate Change (CMCC) (meteorological aspects), at the Geotechnical Laboratory of the Second University of Naples (hydrological and geotechnical aspects) and at the Department of Economics of the University of Naples "Federico II" (economic aspects). The results obtained from the application of this simulation chain in the Cervinara area during eleven years of research allowed in-depth analysis of the mechanisms underlying a flowslide in pyroclastic soil.

Application of Remote Sensing for Forest Management in Nepal

NASA Astrophysics Data System (ADS)

Bajracharya, B.; Matin, M. A.

2016-12-01

Large area of the Hindu Kush Himalayan (HKH) region is covered by forest that is playing a vital role to address the challenges of climate change and livelihood options for a growing population. Effective management of forest cover needs establishment of regular monitoring system for forest. Supporting REDD assessment needs reliable baseline assessment of forest biomass and its monitoring at multiple scale. Adaptation of forest to climate change needs understanding vulnerability of forests and dependence of local communities on these forest. We present here different forest monitoring products developed under the SERVIR-Himalaya programme to address these issues. Landsat 30 meter images were used for decadal land cover change assessment and annual forest change hotspot monitoring. Methodology developed for biomass estimation at national and sub-national level biomass estimation. Decision support system was developed for analysis of forest vulnerability and dependence and selection of adaptation options based on resource availability. These products are forming the basis for development of an integrated system that will be very useful for comprehensive forest monitoring and long term strategy development for sustainable forest management.

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

PubMed

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

2008-07-01

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

[Concepts and monitoring of pulmonary mechanic in patients under ventilatory support in intensive care unit].

PubMed

Faustino, Eduardo Antonio

2007-06-01

In mechanical ventilation, invasive and noninvasive, the knowledge of respiratory mechanic physiology is indispensable to take decisions and into the efficient management of modern ventilators. Monitoring of pulmonary mechanic parameters is been recommended from all the review works and clinical research. The objective of this study was review concepts of pulmonary mechanic and the methods used to obtain measures in the bed side, preparing a rational sequence to obtain this data. It was obtained bibliographic review through data bank LILACS, MedLine and PubMed, from the last ten years. This review approaches parameters of resistance, pulmonary compliance and intrinsic PEEP as primordial into comprehension of acute respiratory failure and mechanic ventilatory support, mainly in acute respiratory distress syndrome (ARDS) and in chronic obstructive pulmonary disease (COPD). Monitoring pulmonary mechanics in patients under mechanical ventilation in intensive care units gives relevant informations and should be implemented in a rational and systematic way.

SUPPORT Tools for evidence-informed health Policymaking (STP) 3: Setting priorities for supporting evidence-informed policymaking

PubMed Central

2009-01-01

This article is part of a series written for people responsible for making decisions about health policies and programmes and for those who support these decision makers. Policymakers have limited resources for developing – or supporting the development of – evidence-informed policies and programmes. These required resources include staff time, staff infrastructural needs (such as access to a librarian or journal article purchasing), and ongoing professional development. They may therefore prefer instead to contract out such work to independent units with more suitably skilled staff and appropriate infrastructure. However, policymakers may only have limited financial resources to do so. Regardless of whether the support for evidence-informed policymaking is provided in-house or contracted out, or whether it is centralised or decentralised, resources always need to be used wisely in order to maximise their impact. Examples of undesirable practices in a priority-setting approach include timelines to support evidence-informed policymaking being negotiated on a case-by-case basis (instead of having clear norms about the level of support that can be provided for each timeline), implicit (rather than explicit) criteria for setting priorities, ad hoc (rather than systematic and explicit) priority-setting process, and the absence of both a communications plan and a monitoring and evaluation plan. In this article, we suggest questions that can guide those setting priorities for finding and using research evidence to support evidence-informed policymaking. These are: 1. Does the approach to prioritisation make clear the timelines that have been set for addressing high-priority issues in different ways? 2. Does the approach incorporate explicit criteria for determining priorities? 3. Does the approach incorporate an explicit process for determining priorities? 4. Does the approach incorporate a communications strategy and a monitoring and evaluation plan? PMID:20018110

SUPPORT Tools for evidence-informed health Policymaking (STP) 3: Setting priorities for supporting evidence-informed policymaking.

PubMed

Lavis, John N; Oxman, Andrew D; Lewin, Simon; Fretheim, Atle

2009-12-16

This article is part of a series written for people responsible for making decisions about health policies and programmes and for those who support these decision makers. Policymakers have limited resources for developing--or supporting the development of--evidence-informed policies and programmes. These required resources include staff time, staff infrastructural needs (such as access to a librarian or journal article purchasing), and ongoing professional development. They may therefore prefer instead to contract out such work to independent units with more suitably skilled staff and appropriate infrastructure. However, policymakers may only have limited financial resources to do so. Regardless of whether the support for evidence-informed policymaking is provided in-house or contracted out, or whether it is centralised or decentralised, resources always need to be used wisely in order to maximise their impact. Examples of undesirable practices in a priority-setting approach include timelines to support evidence-informed policymaking being negotiated on a case-by-case basis (instead of having clear norms about the level of support that can be provided for each timeline), implicit (rather than explicit) criteria for setting priorities, ad hoc (rather than systematic and explicit) priority-setting process, and the absence of both a communications plan and a monitoring and evaluation plan. In this article, we suggest questions that can guide those setting priorities for finding and using research evidence to support evidence-informed policymaking. These are: 1. Does the approach to prioritisation make clear the timelines that have been set for addressing high-priority issues in different ways? 2. Does the approach incorporate explicit criteria for determining priorities? 3. Does the approach incorporate an explicit process for determining priorities? 4. Does the approach incorporate a communications strategy and a monitoring and evaluation plan?

Decision support for water quality management of contaminants of emerging concern.

PubMed

Fischer, Astrid; Ter Laak, Thomas; Bronders, Jan; Desmet, Nele; Christoffels, Ekkehard; van Wezel, Annemarie; van der Hoek, Jan Peter

2017-05-15

Water authorities and drinking water companies are challenged with the question if, where and how to abate contaminants of emerging concern in the urban water cycle. The most effective strategy under given conditions is often unclear to these stakeholders as it requires insight into several aspects of the contaminants such as sources, properties, and mitigation options. Furthermore the various parties in the urban water cycle are not always aware of each other's requirements and priorities. Processes to set priorities and come to agreements are lacking, hampering the articulation and implementation of possible solutions. To support decision makers with this task, a decision support system was developed to serve as a point of departure for getting the relevant stakeholders together and finding common ground. The decision support system was iteratively developed in stages. Stakeholders were interviewed and a decision support system prototype developed. Subsequently, this prototype was evaluated by the stakeholders and adjusted accordingly. The iterative process lead to a final system focused on the management of contaminants of emerging concern within the urban water cycle, from wastewater, surface water and groundwater to drinking water, that suggests mitigation methods beyond technical solutions. Possible wastewater and drinking water treatment techniques in combination with decentralised and non-technical methods were taken into account in an integrated way. The system contains background information on contaminants of emerging concern such as physical/chemical characteristics, toxicity and legislative frameworks, water cycle entrance pathways and a database with associated possible mitigation methods. Monitoring data can be uploaded to assess environmental and human health risks in a specific water system. The developed system was received with great interest by potential users, and implemented in an international water cycle network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Design and Development of Patient Monitoring System

NASA Astrophysics Data System (ADS)

Hazwanie Azizulkarim, Azra; Jamil, Muhammad Mahadi Abdul; Ambar, Radzi

2017-08-01

Patient monitoring system allows continuous monitoring of patient vital signs, support decision making among medical personnel and help enhance patient care. This system can consist of devices that measure, display and record human’s vital signs, including body temperature, heart rate, blood pressure and other health-related criteria. This paper proposes a system to monitor the patient’s conditions by monitoring the body temperature and pulse rate. The system consists of a pulse rate monitoring software and a wearable device that can measure a subject’s temperature and pulse rate only by using a fingertip. The device is able to record the measurement data and interface to PC via Arduino microcontroller. The recorded data can be viewed as a historical file or can be archived for further analysis. This work also describes the preliminary experimental results of the selected sensors to show the usefulness of the sensors for the proposed patient monitoring system.

Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC)

PubMed Central

2013-01-01

Background Implementing shared decision making into routine practice is proving difficult, despite considerable interest from policy-makers, and is far more complex than merely making decision support interventions available to patients. Few have reported successful implementation beyond research studies. MAking Good Decisions In Collaboration (MAGIC) is a multi-faceted implementation program, commissioned by The Health Foundation (UK), to examine how best to put shared decision making into routine practice. In this paper, we investigate healthcare professionals’ perspectives on implementing shared decision making during the MAGIC program, to examine the work required to implement shared decision making and to inform future efforts. Methods The MAGIC program approached implementation of shared decision making by initiating a range of interventions including: providing workshops; facilitating development of brief decision support tools (Option Grids); initiating a patient activation campaign (‘Ask 3 Questions’); gathering feedback using Decision Quality Measures; providing clinical leads meetings, learning events, and feedback sessions; and obtaining executive board level support. At 9 and 15 months (May and November 2011), two rounds of semi-structured interviews were conducted with healthcare professionals in three secondary care teams to explore views on the impact of these interventions. Interview data were coded by two reviewers using a framework derived from the Normalization Process Theory. Results A total of 54 interviews were completed with 31 healthcare professionals. Partial implementation of shared decision making could be explained using the four components of the Normalization Process Theory: ‘coherence,’ ‘cognitive participation,’ ‘collective action,’ and ‘reflexive monitoring.’ Shared decision making was integrated into routine practice when clinical teams shared coherent views of role and purpose (‘coherence’). Shared decision making was facilitated when teams engaged in developing and delivering interventions (‘cognitive participation’), and when those interventions fit with existing skill sets and organizational priorities (‘collective action’) resulting in demonstrable improvements to practice (‘reflexive monitoring’). The implementation process uncovered diverse and conflicting attitudes toward shared decision making; ‘coherence’ was often missing. Conclusions The study showed that implementation of shared decision making is more complex than the delivery of patient decision support interventions to patients, a portrayal that often goes unquestioned. Normalizing shared decision making requires intensive work to ensure teams have a shared understanding of the purpose of involving patients in decisions, and undergo the attitudinal shifts that many health professionals feel are required when comprehension goes beyond initial interpretations. Divergent views on the value of engaging patients in decisions remain a significant barrier to implementation. PMID:24006959

TEMPO Early Adopters in Air-Quality Forecasting, Planning and Assessment, Pollution Emissions, Health, Agriculture, and Environmental Impacts: Applications and Decision Support

NASA Astrophysics Data System (ADS)

Newchurch, M.; Zavodsky, B.; Chance, K.; Haynes, J.; Lefer, B. L.; Naeger, A.

2016-12-01

The AQ research community has a long legacy of using space-based observations (e.g., Solar Backscatter Ultraviolet Instrument [SBUV], Global Ozone Monitoring Experiment [GOME], Ozone Monitoring Instrument [OMI], and the Ozone Mapping & Profiler Suite [OMPS]) to study atmospheric chemistry. These measurements have been used to observe day-to-day and year-to-year changes in atmospheric constituents. However, they have not been able to capture the diurnal variability of pollution with enough temporal or spatial fidelity and a low enough latency for regular use by operational decision makers. As a result, the operational AQ community has traditionally relied on ground-based (e.g., collection stations, LIDAR) and airborne observing systems to study tropospheric chemistry. In order to maximize its utility for applications and decision support, there is a need to educate the community about the game-changing potential for the geostationary TEMPO mission well ahead of its expected launch date early in the third decade of this millinium. This NASA mission will engage user communities and enable science across the NASA Applied Science Focus Areas of Health and Air Quality, Disasters, Water Resources, and Ecological Forecasting, In addition, topics discussed will provide opportunities for collaborations extending TEMPO applications to future program areas in Agriculture, Weather and Climate (including Numerical Weather Prediction), Energy, and Oceans.

Connecting World Heritage Nominations and Monitoring with the Support of the Silk Roads Cultural Heritage Resource Information System

NASA Astrophysics Data System (ADS)

Vileikis, O.; Dumont, B.; Serruys, E.; Van Balen, K.; Tigny, V.; De Maeyer, P.

2013-07-01

Serial transnational World Heritage nominations are challenging the way cultural heritage has been managed and evaluated in the past. Serial transnational World Heritage nominations are unique in that they consist of multiple sites listed as one property, distributed in different countries, involving a large diversity of stakeholders in the process. As a result, there is a need for precise baseline information for monitoring, reporting and decision making. This type of nomination requires different methodologies and tools to improve the monitoring cycle from the beginning of the nomination towards the periodic reporting. The case study of the Silk Roads Cultural Heritage Resource Information System (CHRIS) illustrates the use of a Geographical Content Management System (Geo-CMS) supporting the serial transnational World Heritage nomination and the monitoring of the Silk Roads in the five Central Asian countries. The Silk Roads CHRIS is an initiative supported by UNESCO World Heritage Centre (WHC) and the Belgian Federal Science Policy Office (BELSPO), and developed by a consortium headed by the Raymond Lemaire International Centre for Conservation (RLICC) at the KULeuven. The Silk Roads CHRIS has been successfully assisting in the preparation of the nomination dossiers of the Republics of Kazakhstan, Tajikistan and Uzbekistan and will be used as a tool for monitoring tool in the Central Asian countries.

Integrated data visualisation: an approach to capture older adults’ wellness

PubMed Central

Wilamowska, Katarzyna; Demiris, George; Thompson, Hilaire

2013-01-01

Informatics tools can help support the health and independence of older adults. In this paper, we present an approach towards integrating health-monitoring data and describe several techniques for the assessment and visualisation of integrated health and well-being of older adults. We present three different visualisation techniques to provide distinct alternatives towards display of the same information, focusing on reducing the cognitive load of data interpretation. We demonstrate the feasibility of integrating health-monitoring information into a comprehensive measure of wellness, while also highlighting the challenges of designing visual displays targeted at multiple user groups. These visual displays of wellness can be incorporated into personal health records and can be an effective support for informed decision-making. PMID:23079025

Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Advanced Microwave Scanning Radiometer Data Products for National Drought Monitor Decision Support

NASA Technical Reports Server (NTRS)

Estep, Leland

2007-01-01

Drought effects are either direct or indirect depending on location, population, and regional economic vitality. Common direct effects of drought are reduced crop, rangeland, and forest productivity; increased fire hazard; reduced water levels; increased livestock and wildlife mortality rates; and damage to wildlife and fish habitat. Indirect impacts follow on the heels of direct impacts. For example, a reduction in crop, rangeland, and forest productivity may result in reduced income for farmers and agribusiness, increased prices for food and timber, unemployment, reduced tax revenues, increased crime, foreclosures on bank loans to farmers and businesses, migration, and disaster relief programs. In the United States alone, drought is estimated to result in annual losses of between $6 - 8 billion. Recent sustained drought in the United States has made decision-makers aware of the impacts of climate change on society and environment. The eight major droughts that occurred in the United States between 1980 and 1999 accounted for the largest percentage of weather-related monetary losses. Monitoring drought and its impact that occurs at a variety of scales is an important government activity -- not only nationally but internationally as well. The NDMC (National Drought Mitigation Center) and the USDA (U.S. Department of Agriculture) RMA (Risk Management Agency) have partnered together to develop a DM-DSS (Drought Monitoring Decision Support System). This monitoring system will be an interactive portal that will provide users the ability to visualize and assess drought at all levels. This candidate solution incorporates atmospherically corrected VIIRS data products, such as NDVI (Normalized Difference Vegetation Index) and Ocean SST (sea surface temperature), and AMSR-E soil moisture data products into two NDMC vegetation indices -- VegDRI (Vegetation Drought Response Index) and VegOUT (Vegetation Outlook) -- which are then input into the DM-DSS.

Big data and high-performance analytics in structural health monitoring for bridge management

NASA Astrophysics Data System (ADS)

Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed

2016-04-01

Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.

Measuring, managing and maximizing refinery performance

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

Bascur, O.A.; Kennedy, J.P.

1996-01-01

Implementing continuous quality improvement is a confluence of total quality management, people empowerment, performance indicators and information engineering. Supporting information technologies allow a refiner to narrow the gap between management objectives and the process control level. Dynamic performance monitoring benefits come from production cost savings, improved communications and enhanced decision making. A refinery workgroup information flow model helps automate continuous improvement of processes, performance and the organization. The paper discusses the rethinking of refinery operations, dynamic performance monitoring, continuous process improvement, the knowledge coordinator and repository manager, an integrated plant operations workflow, and successful implementation.

The Application of Wireless Sensor Networks in Management of Orchard

NASA Astrophysics Data System (ADS)

Zhu, Guizhi

A monitoring system based on wireless sensor network is established, aiming at the difficulty of information acquisition in the orchard on the hill at present. The temperature and humidity sensors are deployed around fruit trees to gather the real-time environmental parameters, and the wireless communication modules with self-organized form, which transmit the data to a remote central server, can realize the function of monitoring. By setting the parameters of data intelligent analysis judgment, the information on remote diagnosis and decision support can be timely and effectively feed back to users.

75 FR 24958 - Decision To Evaluate a Petition To Designate a Class of Employees From the Hanford Site, Richland...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-06

... warranted by the evaluation, is as follows: Facility: Hanford site. Location: Richland, Washington. Job Titles and/or Job Duties: All personnel who were internally monitored (urine or fecal), who worked at the... Analysis and Support, National Institute for Occupational Safety and Health (NIOSH), 4676 Columbia Parkway...

Interdisciplinary Distinguished Seminar Series

DTIC Science & Technology

2014-08-29

official Department of the Army position, policy or decision, unless so designated by other documentation. 9. SPONSORING/MONITORING AGENCY NAME(S) AND...Received Book TOTAL: Patents Submitted Patents Awarded Awards Graduate Students Names of Post Doctorates Names of Faculty Supported Names of Under...capabilities, estimation and optimization techniques, image and color standards, efficient programming methods and efficient ASIC designs . This seminar will

Soil Quality Standards Monitoring Program administration and implementation

Treesearch

Randy L. Davis; Felipe Sanchez; Sharon DeHart

2010-01-01

Forest managers and resource scientists and specialists are engaged in a partnership to sustain the natural resource value of our national forests. Managers are faced with deciding which activities provide the best resource benefits with the least resource damage. Many, but not all, aspects of the decision process must be based on the science supporting our current...

An Ecobehavioral Analysis of Child Academic Engagement: Implications for Preschool Children Not Responding to Instructional Intervention

ERIC Educational Resources Information Center

Greenwood, Charles R.; Beecher, Constance; Atwater, Jane; Petersen, Sarah; Schiefelbusch, Jean; Irvin, Dwight

2018-01-01

A gap exists in the information needed to make intervention decisions with preschool children who are unresponsive to instructional intervention. "Multi-Tiered System of Supports/Response to Intervention" (MTSS/RTI) progress monitoring is helpful in indicating when an intervention change is needed but provides little information on what…

Lessons from COASST: How Does Citizen Science Contribute to Natural Resource Management & Decision-Making?

NASA Astrophysics Data System (ADS)

Metes, J.; Ballard, H. L.; Parrish, J.

2016-12-01

As many scholars and practitioners in the environmental field turn to citizen science to collect robust scientific data as well as engage with wider audiences, it is crucial to build a more complete understanding of how citizen science influences and affects different interests within a social-ecological system. This research investigates how federal, state, and tribal natural resource managers interact with data from the Coastal Observation & Seabird Survey Team (COASST) project—a citizen science program that trains participants to monitor species and abundance of beach-cast birds on the Pacific Northwest Coast. Fifteen coastal and fisheries managers who previously requested COASST data were interviewed about how and why they used data from the project and were asked to describe how information gained from COASST affected their management decisions. Results suggest that broadly, managers value and learn from the program's capacity to gather data spanning a wide spatial-temporal range. This contribution to baseline monitoring helps managers signal and track both short- and long-term environmental change. More specifically, managers use COASST data in conjunction with other professional monitoring programs, such as the National Marine Fisheries Observer Program, to build higher degrees of reliability into management decisions. Although managers offered diverse perspectives and experiences about what the role of citizen science in natural resource management generally should be, there was agreement that agencies on their own often lack personnel and funding required to sufficiently monitor many crucial resources. Additionally, managers strongly suggested that COASST and other citizen science projects increased public awareness and support for agency decision-making and policies, and indirect yet important contribution to natural resource management.

Actionable Science in the Gulf of Mexico: Connecting Researchers and Resource Managers

NASA Astrophysics Data System (ADS)

Lartigue, J.; Parker, F.; Allee, R.; Young, C.

2017-12-01

The National Oceanic and Atmospheric Administration (NOAA) RESTORE Science Program was established in the wake of the Deepwater Horizon oil spill to to carry out research, observation, and monitoring to support the long-term sustainability of the Gulf of Mexico ecosystem, including its fisheries. Administered in partnership with the US Fish and Wildlife Service, the Science Program emphasizes a connection between science and decision-making. This emphasis translated into an engagement process that allowed for resource managers and other users of information about the ecosystem to provide direct input into the science plan for the program. In developing funding opportunities, the Science Program uses structured conversations with resource managers and other decision makers to focus competitions on specific end user needs. When evaluating proposals for funding, the Science Program uses criteria that focus on applicability of a project's findings and products, end user involvement in project planning, and the approach for transferring findings and products to the end user. By including resource managers alongside scientific experts on its review panels, the Science Program ensures that these criteria are assessed from both the researcher and end user perspectives. Once funding decisions are made, the Science Program assigns a technical monitor to each award to assist with identifying and engaging end users. Sharing of best practices among the technical monitors has provided the Science Program insight on how best to bridge the gap between research and resource management and how to build successful scientist-decision maker partnerships. During the presentation, we will share two case studies: 1) design of a cooperative (fisheries scientist, fisheries managers, and fishers), Gulf-wide conservation and monitoring program for fish spawning aggregations and 2) development of habitat-specific ecosystem indicators for use by federal and state resource managers.

Rotorcraft Diagnostics

NASA Technical Reports Server (NTRS)

Haste, Deepak; Azam, Mohammad; Ghoshal, Sudipto; Monte, James

2012-01-01

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

An integrated information system for the acquisition, management and sharing of environmental data aimed to decision making

NASA Astrophysics Data System (ADS)

La Loggia, Goffredo; Arnone, Elisa; Ciraolo, Giuseppe; Maltese, Antonino; Noto, Leonardo; Pernice, Umberto

2012-09-01

This paper reports the first results of the Project SESAMO - SistEma informativo integrato per l'acquisizione, geStione e condivisione di dati AMbientali per il supportO alle decisioni (Integrated Information System for the acquisition, management and sharing of environmental data aimed to decision making). The main aim of the project is to design and develop an integrated environmental information platform able to provide monitoring services for decision support, integrating data from different environmental monitoring systems (including WSN). This ICT platform, based on a service-oriented architecture (SOA), will be developed to coordinate a wide variety of data acquisition systems, based on heterogeneous technologies and communication protocols, providing different sort of environmental monitoring services. The implementation and validation of the SESAMO platform and its services will involve three specific environmental domains: 1) Urban water losses; 2) Early warning system for rainfall-induced landslides; 3) Precision irrigation planning. Services in the first domain are enabled by a low cost sensors network collecting and transmitting data, in order to allow the pipeline network managers to analyze pressure, velocity and discharge data for reducing water losses in an urban contest. This paper outlines the SESAMO functional and technological structure and then gives a concise description of the service design and development process for the second and third domain. Services in the second domain are enabled by a prototypal early warning system able to identify in near-real time high-risk zones of rainfall-induced landslides. Services in the third domain are aimed to optimize irrigation planning of vineyards depending on plant water stress.

Enhancing access and usage of earth observations to support environmental decision making in Eastern and Southern Africa

NASA Astrophysics Data System (ADS)

Shukla, S.; Husak, G. J.; Macharia, D.; Peterson, P.; Landsfeld, M. F.; Funk, C.; Flores, A.

2017-12-01

Remote sensing, reanalysis and model based earth observations (EOs) are crucial for environmental decision making, particularly in a region like Eastern and Southern Africa, where ground-based observations are sparse. NASA and the Famine Early Warning System Network (FEWS NET) provide several EOs relevant for monitoring, providing early warning of agroclimatic conditions. Nonetheless, real-time application of those EOs for decision making in the region is still limited. This presentation reports on an ongoing SERVIR-supported Applied Science Team (AST) project that aims to fill that gap by working in close collaboration with Regional Centre for Mapping of Resources for Development (RCMRD), the NASA SERVIR regional hub. The three main avenues being taken to enhance access and usage of EOs in the region are: (1) Transition and implementation of web-based tools to RCMRD to allow easy processing and visualization of EOs (2) Capacity building of personnel from regional and national agroclimate service agencies in using EOs, through training using targeted case studies, and (3) Development of new datasets to meet the specific needs of RCMRD and regional stakeholders. The presentation will report on the initial success, lessons learned, and feedback thus far in this project regarding the implementation of web-based tool and capacity building efforts. It will also briefly describe three new datasets, currently in development, to improve agroclimate monitoring in the region, which are: (1) Satellite infrared and stations based temperature maximum dataset (CHIRTS) (2) NASA's GEOS5 and NCEP's CFSv2 based seasonal scale reference evapotranspiration forecasts and (3) NCEP's GEFS based medium range weather forecasts which are bias-corrected to USGS and UCSB's rainfall monitoring dataset (CHIRPS).

Personnel reliability impact on petrochemical facilities monitoring system's failure skipping probability

NASA Astrophysics Data System (ADS)

Kostyukov, V. N.; Naumenko, A. P.

2017-08-01

The paper dwells upon urgent issues of evaluating impact of actions conducted by complex technological systems operators on their safe operation considering application of condition monitoring systems for elements and sub-systems of petrochemical production facilities. The main task for the research is to distinguish factors and criteria of monitoring system properties description, which would allow to evaluate impact of errors made by personnel on operation of real-time condition monitoring and diagnostic systems for machinery of petrochemical facilities, and find and objective criteria for monitoring system class, considering a human factor. On the basis of real-time condition monitoring concepts of sudden failure skipping risk, static and dynamic error, monitoring systems, one may solve a task of evaluation of impact that personnel's qualification has on monitoring system operation in terms of error in personnel or operators' actions while receiving information from monitoring systems and operating a technological system. Operator is considered as a part of the technological system. Although, personnel's behavior is usually a combination of the following parameters: input signal - information perceiving, reaction - decision making, response - decision implementing. Based on several researches on behavior of nuclear powers station operators in USA, Italy and other countries, as well as on researches conducted by Russian scientists, required data on operator's reliability were selected for analysis of operator's behavior at technological facilities diagnostics and monitoring systems. The calculations revealed that for the monitoring system selected as an example, the failure skipping risk for the set values of static (less than 0.01) and dynamic (less than 0.001) errors considering all related factors of data on reliability of information perception, decision-making, and reaction fulfilled is 0.037, in case when all the facilities and error probability are under control - not more than 0.027. In case when only pump and compressor units are under control, the failure skipping risk is not more than 0.022, when the probability of error in operator's action is not more than 0.011. The work output shows that on the basis of the researches results an assessment of operators' reliability can be made in terms of almost any kind of production, but considering only technological capabilities, since operators' psychological and general training considerable vary in different production industries. Using latest technologies of engineering psychology and design of data support systems, situation assessment systems, decision-making and responding system, as well as achievement in condition monitoring in various production industries one can evaluate hazardous condition skipping risk probability considering static, dynamic errors and human factor.

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants.

PubMed

Mueller, Martina; Wagner, Carol L; Annibale, David J; Knapp, Rebecca G; Hulsey, Thomas C; Almeida, Jonas S

2006-03-01

Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0-1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide.

The SARVIEWS Project: Automated SAR Processing in Support of Operational Near Real-time Volcano Monitoring

NASA Astrophysics Data System (ADS)

Meyer, F. J.; Webley, P. W.; Dehn, J.; Arko, S. A.; McAlpin, D. B.; Gong, W.

2016-12-01

Volcanic eruptions are among the most significant hazards to human society, capable of triggering natural disasters on regional to global scales. In the last decade, remote sensing has become established in operational volcano monitoring. Centers like the Alaska Volcano Observatory rely heavily on remote sensing data from optical and thermal sensors to provide time-critical hazard information. Despite this high use of remote sensing data, the presence of clouds and a dependence on solar illumination often limit their impact on decision making. Synthetic Aperture Radar (SAR) systems are widely considered superior to optical sensors in operational monitoring situations, due to their weather and illumination independence. Still, the contribution of SAR to operational volcano monitoring has been limited in the past due to high data costs, long processing times, and low temporal sampling rates of most SAR systems. In this study, we introduce the automatic SAR processing system SARVIEWS, whose advanced data analysis and data integration techniques allow, for the first time, a meaningful integration of SAR into operational monitoring systems. We will introduce the SARVIEWS database interface that allows for automatic, rapid, and seamless access to the data holdings of the Alaska Satellite Facility. We will also present a set of processing techniques designed to automatically generate a set of SAR-based hazard products (e.g. change detection maps, interferograms, geocoded images). The techniques take advantage of modern signal processing and radiometric normalization schemes, enabling the combination of data from different geometries. Finally, we will show how SAR-based hazard information is integrated in existing multi-sensor decision support tools to enable joint hazard analysis with data from optical and thermal sensors. We will showcase the SAR processing system using a set of recent natural disasters (both earthquakes and volcanic eruptions) to demonstrate its robustness. We will also show the benefit of integrating SAR with data from other sensors to support volcano monitoring. For historic eruptions at Okmok and Augustine volcano, both located in the North Pacific, we will demonstrate that the addition of SAR can lead to a significant improvement in activity detection and eruption forecasting.

Data Mining for Web-Based Support Systems: A Case Study in e-Custom Systems

NASA Astrophysics Data System (ADS)

Razmerita, Liana; Kirchner, Kathrin

This chapter provides an example of a Web-based support system (WSS) used to streamline trade procedures, prevent potential security threats, and reduce tax-related fraud in cross-border trade. The architecture is based on a service-oriented architecture that includes smart seals and Web services. We discuss the implications and suggest further enhancements to demonstrate how such systems can move toward a Web-based decision support system with the support of data mining methods. We provide a concrete example of how data mining can help to analyze the vast amount of data collected while monitoring the container movements along its supply chain.

Modeling of afforestation possibilities on one part of Hungary

NASA Astrophysics Data System (ADS)

Bozsik, Éva; Riczu, Péter; Tamás, János; Burriel, Charles; Helilmeier, Hermann

2015-04-01

Agroforestry systems are part of the history of the European Union rural landscapes, but the regional increase of size of agricultural parcels had a significant effect on European land use in the 20th century, thereby it has radically reduced the coverage of natural forest. However, this cause conflicts between interest of agricultural and forestry sectors. The agroforestry land uses could be a solution of this conflict management. One real - ecological - problem with the remnant forests and new forest plantation is the partly missing of network function without connecting ecological green corridors, the other problem is verifiability for the agroforestry payment system, monitoring the arable lands and plantations. Remote sensing methods are currently used to supervise European Union payments. Nowadays, next to use satellite imagery the airborne hyperspectral and LiDAR (Light Detection And Ranging) remote sensing technologies are becoming more widespread use for nature, environmental, forest, agriculture protection, conservation and monitoring and it is an effective tool for monitoring biomass production. In this Hungarian case study we made a Spatial Decision Support System (SDSS) to create agroforestry site selection model. The aim of model building was to ensure the continuity of ecological green corridors, maintain the appropriate land use of regional endowments. The investigation tool was the more widely used hyperspectral and airborne LiDAR remote sensing technologies which can provide appropriate data acquisition and data processing tools to build a decision support system

Intelligent Work Process Engineering System

NASA Technical Reports Server (NTRS)

Williams, Kent E.

2003-01-01

Optimizing performance on work activities and processes requires metrics of performance for management to monitor and analyze in order to support further improvements in efficiency, effectiveness, safety, reliability and cost. Information systems are therefore required to assist management in making timely, informed decisions regarding these work processes and activities. Currently information systems regarding Space Shuttle maintenance and servicing do not exist to make such timely decisions. The work to be presented details a system which incorporates various automated and intelligent processes and analysis tools to capture organize and analyze work process related data, to make the necessary decisions to meet KSC organizational goals. The advantages and disadvantages of design alternatives to the development of such a system will be discussed including technologies, which would need to bedesigned, prototyped and evaluated.

Solutions Network Formulation Report: Improving NOAA's PORTS(R) Through Enhanced Data Inputs from NASA's Ocean Surface Topography Mission

NASA Technical Reports Server (NTRS)

Guest, DeNeice

2007-01-01

The Nation uses water-level data for a variety of practical purposes, including nautical charting, maritime navigation, hydrography, coastal engineering, and tsunami and storm surge warnings. Long-term applications include marine boundary determinations, tidal predictions, sea-level trend monitoring, oceanographic research, and climate research. Accurate and timely information concerning sea-level height, tide, and ocean current is needed to understand their impact on coastal management, disaster management, and public health. Satellite altimeter data products are currently used by hundreds of researchers and operational users to monitor ocean circulation and to improve scientists understanding of the role of the oceans in climate and weather. The NOAA (National Oceanic and Atmospheric Administration) National Ocean Service has been monitoring sea-level variations for many years. NOAA s PORTS (Physical Oceanographic Real-Time System) DST (decision support tool), managed by the Center for Operational Oceanographic Products and Services, supports safe and cost-efficient navigation by providing ship masters and pilots with accurate real-time information required to avoid groundings and collisions. This report assesses the capacity of NASA s satellite altimeter data to meet societal decision support needs through incorporation into NOAA s PORTS. NASA has a long heritage of collecting data for ocean research, including its current Terra and Aqua missions. Numerous other missions provide additional important information for coastal management issues, and data collection will continue in the coming decade with such missions as the OSTM (Ocean Surface Topography Mission). OSTM will provide data on sea-surface heights for determining ocean circulation, climate change, and sea-level rise. We suggest that NASA incorporate OSTM altimeter data (C- and Ku-band) into NOAA s PORTS DST in support of NASA s Coastal Management National Application with secondary support to the Disaster Management and Public Health National Applications.

Generic Sensor Data Fusion Services for Web-enabled Environmental Risk Management and Decision-Support Systems

NASA Astrophysics Data System (ADS)

Sabeur, Zoheir; Middleton, Stuart; Veres, Galina; Zlatev, Zlatko; Salvo, Nicola

2010-05-01

The advancement of smart sensor technology in the last few years has led to an increase in the deployment of affordable sensors for monitoring the environment around Europe. This is generating large amounts of sensor observation information and inevitably leading to problems about how to manage large volumes of data as well as making sense out the data for decision-making. In addition, the various European Directives (Water Framework Diectives, Bathing Water Directives, Habitat Directives, etc.. ) which regulate human activities in the environment and the INSPIRE Directive on spatial information management regulations have implicitely led the designated European Member States environment agencies and authorities to put in place new sensor monitoring infrastructure and share information about environmental regions under their statutory responsibilities. They will need to work cross border and collectively reach environmental quality standards. They will also need to regularly report to the EC on the quality of the environments of which they are responsible and make such information accessible to the members of the public. In recent years, early pioneering work on the design of service oriented architecture using sensor networks has been achieved. Information web-services infrastructure using existing data catalogues and web-GIS map services can now be enriched with the deployment of new sensor observation and data fusion and modelling services using OGC standards. The deployment of the new services which describe sensor observations and intelligent data-processing using data fusion techniques can now be implemented and provide added value information with spatial-temporal uncertainties to the next generation of decision support service systems. The new decision support service systems have become key to implement across Europe in order to comply with EU environmental regulations and INSPIRE. In this paper, data fusion services using OGC standards with sensor observation data streams are described in context of a geo-distributed service infrastructure specialising in multiple environmental risk management and decision-support. The sensor data fusion services are deployed and validated in two use cases. These are respectively concerned with: 1) Microbial risks forecast in bathing waters; and 2) Geohazards in urban zones during underground tunneling activities. This research was initiated in the SANY Integrated Project(www.sany-ip.org) and funded by the European Commission under the 6th Framework Programme.

Environmental-Socio-Economic Monitoring as a Tool of Region’s Environmental-Economic System Management

NASA Astrophysics Data System (ADS)

Galanina, T. V.; Baumgarten, M. I.; Mikhailov, V. G.; Koroleva, T. G.; Mikhailov, G. S.

2017-01-01

The paper deals with the region’s environmental-economic system management through a tool such as the environmental-socio-economic monitoring. The purpose of research - is analysis and development of theoretical assumptions of environmental-socio-economic monitoring system for the effective management of geographically distributed environmental-economic system. The main elements of environmental-socio-economic monitoring are identified, taking into account the characteristics of the studied area. The main result of the research is the development of multi-functional integrated monitoring system for the evaluation of the indicators "gross domestic product" and "gross national product", taking into account the influence of environmental factors. The results of the study conducted may be recommended to the regional and federal governments to support the effective, environment-friendly management decision-making consistent with the overall development concept.

Enhancing wind erosion monitoring and assessment for U.S. rangelands

USGS Publications Warehouse

Webb, Nicholas P.; Van Zee, Justin W.; Karl, Jason W.; Herrick, Jeffrey E.; Courtright, Ericha M.; Billings, Benjamin J.; Boyd, Robert C.; Chappell, Adrian; Duniway, Michael C.; Derner, Justin D.; Hand, Jenny L.; Kachergis, Emily; McCord, Sarah E.; Newingham, Beth A.; Pierson, Frederick B.; Steiner, Jean L.; Tatarko, John; Tedela, Negussie H.; Toledo, David; Van Pelt, R. Scott

2017-01-01

On the GroundWind erosion is a major resource concern for rangeland managers because it can impact soil health, ecosystem structure and function, hydrologic processes, agricultural production, and air quality.Despite its significance, little is known about which landscapes are eroding, by how much, and when.The National Wind Erosion Research Network was established in 2014 to develop tools for monitoring and assessing wind erosion and dust emissions across the United States.The Network, currently consisting of 13 sites, creates opportunities to enhance existing rangeland soil, vegetation, and air quality monitoring programs.Decision-support tools developed by the Network will improve the prediction and management of wind erosion across rangeland ecosystems.

Reasoning, learning, and creativity: frontal lobe function and human decision-making.

PubMed

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

PubMed Central

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control—that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior. PMID:22479152

Integrating Social Media and Mobile Sensor Data for Clinical Decision Support: Concept and Requirements.

PubMed

Denecke, Kerstin

2016-01-01

Social media are increasingly used by individuals for the purpose of collecting data and reporting on the personal health status, on health issues, symptoms and experiences with treatments. Beyond, fitness trackers are more used by individuals to monitor their fitness and health. The health data that is becoming available due to these developments could provide a valuable source for continuous health monitoring, prevention of unexpected health events and clinical decision making since it gives insights into behavior and life habits. However, an integration of the data is challenging. This paper aims triggering the discussion about this current topic. We present a concept for integrating social media data with mobile sensor data and clinical data using digital patient modelling. Further, we collect requirements and challenges for a possible realization of the concept. Challenges include the data volume, reliability and semantic interoperability.

Enhanced Adaptive Management: Integrating Decision Analysis, Scenario Analysis and Environmental Modeling for the Everglades

PubMed Central

Convertino, Matteo; Foran, Christy M.; Keisler, Jeffrey M.; Scarlett, Lynn; LoSchiavo, Andy; Kiker, Gregory A.; Linkov, Igor

2013-01-01

We propose to enhance existing adaptive management efforts with a decision-analytical approach that can guide the initial selection of robust restoration alternative plans and inform the need to adjust these alternatives in the course of action based on continuously acquired monitoring information and changing stakeholder values. We demonstrate an application of enhanced adaptive management for a wetland restoration case study inspired by the Florida Everglades restoration effort. We find that alternatives designed to reconstruct the pre-drainage flow may have a positive ecological impact, but may also have high operational costs and only marginally contribute to meeting other objectives such as reduction of flooding. Enhanced adaptive management allows managers to guide investment in ecosystem modeling and monitoring efforts through scenario and value of information analyses to support optimal restoration strategies in the face of uncertain and changing information. PMID:24113217

Hydra: A web-based system for cardiovascular analysis, diagnosis and treatment.

PubMed

Novo, J; Hermida, A; Ortega, M; Barreira, N; Penedo, M G; López, J E; Calvo, C

2017-02-01

Cardiovascular (CV) risk stratification is a highly complex process involving an extensive set of clinical trials to support the clinical decision-making process. There are many clinical conditions (e.g. diabetes, obesity, stress, etc.) that can lead to the early diagnosis or establishment of cardiovascular disease. In order to determine all these clinical conditions, a complete set of clinical patient analyses is typically performed, including a physical examination, blood analysis, electrocardiogram, blood pressure (BP) analysis, etc. This article presents a web-based system, called Hydra, which integrates a full and detailed set of services and functionalities for clinical decision support in order to help and improve the work of clinicians in cardiovascular patient diagnosis, risk assessment, treatment and monitoring over time. Hydra integrates a number of different services: a service for inputting all the information gathered by specialists (physical examination, habits, BP, blood analysis, electrocardiogram, etc.); a tool to automatically determine the CV risk stratification, including well-known standard risk stratification tables; and, finally, various tools to incorporate, analyze and graphically present the records of the ambulatory BP monitoring that provides BP analysis over a given period of time (24 or 48 hours). In addition, the platform presents a set of reports derived from all the information gathered from the patient in order to support physicians in their clinical decisions. Hydra was tested and validated in a real domain. In particular, internal medicine specialists at the Hypertension Unit of the Santiago de Compostela University Hospital (CHUS) validated the platform and used it in different clinical studies to demonstrate its utility. It was observed that the platform increased productivity and accuracy in the assessment of patient data yielding a cost reduction in clinical practice. This paper proposes a complete platform that includes different services for cardiovascular clinical decision support. It was also run as a web-based application to facilitate its use by clinicians, who can access the platform from any remote computer with Internet access. Hydra also includes different automated methods to facilitate the physicians' work and avoid potential errors in the analysis of patient data. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Diabetes management using modern information and communication technologies and new care models.

PubMed

Spanakis, Emmanouil G; Chiarugi, Franco; Kouroubali, Angelina; Spat, Stephan; Beck, Peter; Asanin, Stefan; Rosengren, Peter; Gergely, Tamas; Thestrup, Jesper

2012-10-04

Diabetes, a metabolic disorder, has reached epidemic proportions in developed countries. The disease has two main forms: type 1 and type 2. Disease management entails administration of insulin in combination with careful blood glucose monitoring (type 1) or involves the adjustment of diet and exercise level, the use of oral anti-diabetic drugs, and insulin administration to control blood sugar (type 2). State-of-the-art technologies have the potential to assist healthcare professionals, patients, and informal carers to better manage diabetes insulin therapy, help patients understand their disease, support self-management, and provide a safe environment by monitoring adverse and potentially life-threatening situations with appropriate crisis management. New care models incorporating advanced information and communication technologies have the potential to provide service platforms able to improve health care, personalization, inclusion, and empowerment of the patient, and to support diverse user preferences and needs in different countries. The REACTION project proposes to create a service-oriented architectural platform based on numerous individual services and implementing novel care models that can be deployed in different settings to perform patient monitoring, distributed decision support, health care workflow management, and clinical feedback provision. This paper presents the work performed in the context of the REACTION project focusing on the development of a health care service platform able to support diabetes management in different healthcare regimes, through clinical applications, such as monitoring of vital signs, feedback provision to the point of care, integrative risk assessment, and event and alarm handling. While moving towards the full implementation of the platform, three major areas of research and development have been identified and consequently approached: the first one is related to the glucose sensor technology and wearability, the second is related to the platform architecture, and the third to the implementation of the end-user services. The Glucose Management System, already developed within the REACTION project, is able to monitor a range of parameters from various sources including glucose levels, nutritional intakes, administered drugs, and patient's insulin sensitivity, offering decision support for insulin dosing to professional caregivers on a mobile tablet platform that fulfills the need of the users and supports medical workflow procedures in compliance with the Medical Device Directive requirements. Good control of diabetes, as well as increased emphasis on control of lifestyle factors, may reduce the risk profile of most complications and contribute to health improvement. The REACTION project aims to respond to these challenges by providing integrated, professional, management, and therapy services to diabetic patients in different health care regimes across Europe in an interoperable communication platform.

Agricultural Productivity Forecasts for Improved Drought Monitoring

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh; McNider, Richard; Moss, Donald; Alhamdan, Mohammad

2010-01-01

Water stresses on agricultural crops during critical phases of crop phenology (such as grain filling) has higher impact on the eventual yield than at other times of crop growth. Therefore farmers are more concerned about water stresses in the context of crop phenology than the meteorological droughts. However the drought estimates currently produced do not account for the crop phenology. US Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) have developed a drought monitoring decision support tool: The U.S. Drought Monitor, which currently uses meteorological droughts to delineate and categorize drought severity. Output from the Drought Monitor is used by the States to make disaster declarations. More importantly, USDA uses the Drought Monitor to make estimates of crop yield to help the commodities market. Accurate estimation of corn yield is especially critical given the recent trend towards diversion of corn to produce ethanol. Ethanol is fast becoming a standard 10% ethanol additive to petroleum products, the largest traded commodity. Thus the impact of large-scale drought will have dramatic impact on the petroleum prices as well as on food prices. USDA's World Agricultural Outlook Board (WAOB) serves as a focal point for economic intelligence and the commodity outlook for U.S. WAOB depends on Drought Monitor and has emphatically stated that accurate and timely data are needed in operational agrometeorological services to generate reliable projections for agricultural decision makers. Thus, improvements in the prediction of drought will reflect in early and accurate assessment of crop yields, which in turn will improve commodity projections. We have developed a drought assessment tool, which accounts for the water stress in the context of crop phenology. The crop modeling component is done using various crop modules within Decision Support System for Agrotechnology Transfer (DSSAT). DSSAT is an agricultural crop simulation system, which integrates the effects of soil, crop phenotype, weather, and management options. It has been in use for more than 15 years by researchers, growers and has become a de-facto standard in crop modeling communities spanning over 100 countries. The meteorological forcings to DSSAT are provided by NASA s National Land Data Assimilation System (NLDAS) datasets. NLDAS is a framework that incorporates atmospheric forcing and land parameter values along with land surface models to diagnose and predict the state of the land surface.

Using landsat time-series and lidar to inform aboveground carbon baseline estimation in Minnesota

Treesearch

Ram K. Deo; Grant M. Domke; Matthew B. Russell; Christopher W. Woodall; Michael J. Falkowski

2015-01-01

Landsat data has long been used to support forest monitoring and management decisions despite the limited success of passive optical remote sensing for accurate estimation of structural attributes such as aboveground biomass. The archive of publicly available Landsat images dating back to the 1970s can be used to predict historic forest biomass dynamics. In addition,...

A Decision Support Personnel Monitoring Database System Prototype for the United States Marine Corps.

DTIC Science & Technology

1985-12-19

Officer. The second space represents the current pay grade. The third space E indi- cates the officer has a least four years of enlisted active service...second space can only be 1-6. The third space can only be E or blank. Warrant Officers and PGRD 04 and above will have the third space blank even if

Method of calculation of critical values of financial indicators for developing food security strategy

NASA Astrophysics Data System (ADS)

Aigyl Ilshatovna, Sabirova; Svetlana Fanilevna, Khasanova; Vildanovna, Nagumanova Regina

2018-05-01

On the basis of decision making theory (minimax and maximin approaches) the authors propose a technique with the results of calculations of the critical values of effectiveness indicators of agricultural producers in the Republic of Tatarstan for 2013-2015. There is justified necessity of monitoring the effectiveness of the state support and the direction of its improvement.

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

The Role of Consumer-Controlled Personal Health Management Systems in the Evolution of Employer-Based Health Care Benefits.

PubMed

Jones, Spencer S; Caloyeras, John; Mattke, Soeren

2011-01-01

The passage of the Patient Protection and Affordable Care Act has piqued employers' interest in new benefit designs because it includes numerous provisions that favor cost-reducing strategies, such as workplace wellness programs, value-based insurance design (VBID), and consumer-directed health plans (CDHPs). Consumer-controlled personal health management systems (HMSs) are a class of tools that provide encouragement, data, and decision support to individuals. Their functionalities fall into the following three categories: health information management, promotion of wellness and healthy lifestyles, and decision support. In this study, we review the evidence for many of the possible components of an HMS, including personal health records, web-based health risk assessments, integrated remote monitoring data, personalized health education and messaging, nutrition solutions and physical activity monitoring, diabetes-management solutions, medication reminders, vaccination and preventive-care applications, integrated incentive programs, social-networking tools, comparative data on price and value of providers, telehealth consultations, virtual coaching, and an integrated nurse hotline. The value of the HMS will be borne out as employers begin to adopt and implement these emerging technologies, enabling further assessment as their benefits and costs become better understood.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

NASA Astrophysics Data System (ADS)

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

2012-06-01

It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes, implementation results of the developed fusion algorithms on structural health monitoring data collected from experimental tests are reported in this paper.

Integrated wetland management for waterfowl and shorebirds at Mattamuskeet National Wildlife Refuge, North Carolina

USGS Publications Warehouse

Tavernia, Brian G.; Stanton, John D.; Lyons, James E.

2017-11-22

Mattamuskeet National Wildlife Refuge (MNWR) offers a mix of open water, marsh, forest, and cropland habitats on 20,307 hectares in coastal North Carolina. In 1934, Federal legislation (Executive Order 6924) established MNWR to benefit wintering waterfowl and other migratory bird species. On an annual basis, the refuge staff decide how to manage 14 impoundments to benefit not only waterfowl during the nonbreeding season, but also shorebirds during fall and spring migration. In making these decisions, the challenge is to select a portfolio, or collection, of management actions for the impoundments that optimizes use by the three groups of birds while respecting budget constraints. In this study, a decision support tool was developed for these annual management decisions.Within the decision framework, there are three different management objectives: shorebird-use days during fall and spring migrations, and waterfowl-use days during the nonbreeding season. Sixteen potential management actions were identified for impoundments; each action represents a combination of hydroperiod and vegetation manipulation. Example hydroperiods include semi-permanent and seasonal drawdowns, and vegetation manipulations include mechanical-chemical treatment, burning, disking, and no action. Expert elicitation was used to build a Bayesian Belief Network (BBN) model that predicts shorebird- and waterfowl-use days for each potential management action. The BBN was parameterized for a representative impoundment, MI-9, and predictions were re-scaled for this impoundment to predict outcomes at other impoundments on the basis of size. Parameter estimates in the BBN model can be updated using observations from ongoing monitoring that is part of the Integrated Waterbird Management and Monitoring (IWMM) program.The optimal portfolio of management actions depends on the importance, that is, weights, assigned to the three objectives, as well as the budget. Five scenarios with a variety of objective weights and budgets were developed. Given the large number of possible portfolios (1614), a heuristic genetic algorithm was used to identify a management action portfolio that maximized use-day objectives while respecting budget constraints. The genetic algorithm identified a portfolio of management actions for each of the five scenarios, enabling refuge staff to explore the sensitivity of their management decisions to objective weights and budget constraints.The decision framework developed here provides a transparent, defensible, and testable foundation for decision making at MNWR. The BBN model explicitly structures and parameterizes a mental model previously used by an expert to assign management actions to the impoundments. With ongoing IWMM monitoring, predictions from the model can be tested, and model parameters updated, to reflect empirical observations. This framework is intended to be a living document that can be updated to reflect changes in the decision context (for example, new objectives or constraints, or new models to compete with the current BBN model). Rather than a mandate to refuge staff, this framework is intended to be a decision support tool; tool outputs can become part of the deliberations of refuge staff when making difficult management decisions for multiple objectives.

Exploiting the Free Landsat Archive for Operational Monitoring of Ecosystem Condition and Change Across the Chesapeake Bay Watershed

NASA Technical Reports Server (NTRS)

BrowndeColstoun, Eric

2010-01-01

For the first time, all imagery acquired by the Landsat series of satellites is being made available by the USGS to users at no cost. This represents a key opportunity to use Landsat in a truly operational monitoring framework: large regions of the U.S. such as the Chesapeake Bay Watershed can now be analyzed using "wall-to-wall" imagery at timescales from approximately 1 month to several years. With the future launch of the Landsat Data Continuity Mission (LDCM) and Decadal Survey missions such as the hyperspectral HyspIRI, it is imperative to develop robust processing systems to perform annual ecosystem assessments over large regions such as the Chesapeake Bay. We have been working at NASA's Goddard Space Flight Center (GSFC) to develop an integrative framework for inserting 30m, annual, Landsat based data and derived products into the existing decision support system for the Bay, with a particular focus on ecosystem condition and changes over the entire watershed. The basic goal is to use a 'stack' of Landsat imagery with 40% or less cloud cover to produce multi-date (2005-2009 period), cloud/shadow/gap-free composited surface reflectance products that will support the creation of watershed scale land cover/ use products and the monitoring of ecosystem change across the Bay. Our scientific focus extends beyond the conventional definition of land cover (i.e. a classification of vegetation type) as we propose to monitor both changes in surface type (e.g. forest to urban), vegetation structure (e.g. forest disturbance due to logging or insect damage), as well as winter crop cover. These processes represent a continuum from large, interannual changes in land cover type, to subtler, intra-annual changes associated with short-term disturbance. The free Landsat data are being processed to surface reflectance and composited using the existing Landsat Ecosystem Disturbance Adaptive Processing System here at NASA/ GSFC, and land cover products (type, tree cover, impervious cover, winter cover) are being produced using well-established decision tree and regression tree algorithms. The goal of this session is to present the data products that we have been developing to the Bay science community and to discuss potential avenues for improvements and usage of the products for decision support.

Strengthening Agricultural Decisions in Countries at Risk of Food Insecurity: The GEOGLAM Crop Monitor for Early Warning

NASA Astrophysics Data System (ADS)

Becker-Reshef, I.; Barker, B.; McGaughey, K.; Humber, M. L.; Sanchez, A.; Justice, C. O.; Rembold, F.; Verdin, J. P.

2016-12-01

Timely, reliable information on crop conditions, and prospects at the subnational scale, is critical for making informed policy and agricultural decisions for ensuring food security, particularly for the most vulnerable countries. However, such information is often incomplete or lacking. As such, the Crop Monitor for Early Warning (CM for EW) was developed with the goal to reduce uncertainty and strengthen decision support by providing actionable information on a monthly basis to national, regional and global food security agencies through timely consensus assessments of crop conditions. This information is especially critical in recent years, given the extreme weather conditions impacting food supplies including the most recent El Nino event. This initiative brings together the main international food security monitoring agencies and organizations to develop monthly crop assessments based on satellite observations, meteorological information, field observations and ground reports, which reflect an international consensus. This activity grew out of the successful Crop Monitor for the G20 Agricultural Market Information System (AMIS), which provides operational monthly crop assessments of the main producing countries of the world. The CM for EW was launched in February 2016 and has already become a trusted source of information internationally and regionally. Its assessments have been featured in a large number of news articles, reports, and press releases, including a joint statement by the USAID's FEWS NET, UN World Food Program, European Commission Joint Research Center, and the UN Food and Agriculture Organziation, on the devastating impacts of the southern African drought due to El Nino. One of the main priorities for this activity going forward is to expand its partnership with regional and national monitoring agencies, and strengthen capacity for national crop condition assessments.

Design of decision support interventions for medication prescribing.

PubMed

Horsky, Jan; Phansalkar, Shobha; Desai, Amrita; Bell, Douglas; Middleton, Blackford

2013-06-01

Describe optimal design attributes of clinical decision support (CDS) interventions for medication prescribing, emphasizing perceptual, cognitive and functional characteristics that improve human-computer interaction (HCI) and patient safety. Findings from published reports on success, failures and lessons learned during implementation of CDS systems were reviewed and interpreted with regard to HCI and software usability principles. We then formulated design recommendations for CDS alerts that would reduce unnecessary workflow interruptions and allow clinicians to make informed decisions quickly, accurately and without extraneous cognitive and interactive effort. Excessive alerting that tends to distract clinicians rather than provide effective CDS can be reduced by designing only high severity alerts as interruptive dialog boxes and less severe warnings without explicit response requirement, by curating system knowledge bases to suppress warnings with low clinical utility and by integrating contextual patient data into the decision logic. Recommended design principles include parsimonious and consistent use of color and language, minimalist approach to the layout of information and controls, the use of font attributes to convey hierarchy and visual prominence of important data over supporting information, the inclusion of relevant patient data in the context of the alert and allowing clinicians to respond with one or two clicks. Although HCI and usability principles are well established and robust, CDS and EHR system interfaces rarely conform to the best known design conventions and are seldom conceived and designed well enough to be truly versatile and dependable tools. These relatively novel interventions still require careful monitoring, research and analysis of its track record to mature. Clarity and specificity of alert content and optimal perceptual and cognitive attributes, for example, are essential for providing effective decision support to clinicians. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

New technology continues to invade healthcare. What are the strategic implications/outcomes?

PubMed

Smith, Coy

2004-01-01

Healthcare technology continues to advance and be implemented in healthcare organizations. Nurse executives must strategically evaluate the effectiveness of each proposed system or device using a strategic planning process. Clinical information systems, computer-chip-based clinical monitoring devices, advanced Web-based applications with remote, wireless communication devices, clinical decision support software--all compete for capital and registered nurse salary dollars. The concept of clinical transformation is developed with new models of care delivery being supported by technology rather than driving care delivery. Senior nursing leadership's role in clinical transformation and healthcare technology implementation is developed. Proposed standards, expert group action, business and consumer groups, and legislation are reviewed as strategic drivers in the development of an electronic health record and healthcare technology. A matrix of advancing technology and strategic decision-making parameters are outlined.

Offshore oil spill response practices and emerging challenges.

PubMed

Li, Pu; Cai, Qinhong; Lin, Weiyun; Chen, Bing; Zhang, Baiyu

2016-09-15

Offshore oil spills are of tremendous concern due to their potential impact on economic and ecological systems. A number of major oil spills triggered worldwide consciousness of oil spill preparedness and response. Challenges remain in diverse aspects such as oil spill monitoring, analysis, assessment, contingency planning, response, cleanup, and decision support. This article provides a comprehensive review of the current situations and impacts of offshore oil spills, as well as the policies and technologies in offshore oil spill response and countermeasures. Correspondingly, new strategies and a decision support framework are recommended for improving the capacities and effectiveness of oil spill response and countermeasures. In addition, the emerging challenges in cold and harsh environments are reviewed with recommendations due to increasing risk of oil spills in the northern regions from the expansion of the Arctic Passage. Copyright © 2016 Elsevier Ltd. All rights reserved.

Network information attacks on the control systems of power facilities belonging to the critical infrastructure

NASA Astrophysics Data System (ADS)

Loginov, E. L.; Raikov, A. N.

2015-04-01

The most large-scale accidents occurred as a consequence of network information attacks on the control systems of power facilities belonging to the United States' critical infrastructure are analyzed in the context of possibilities available in modern decision support systems. Trends in the development of technologies for inflicting damage to smart grids are formulated. A volume matrix of parameters characterizing attacks on facilities is constructed. A model describing the performance of a critical infrastructure's control system after an attack is developed. The recently adopted measures and legislation acts aimed at achieving more efficient protection of critical infrastructure are considered. Approaches to cognitive modeling and networked expertise of intricate situations for supporting the decision-making process, and to setting up a system of indicators for anticipatory monitoring of critical infrastructure are proposed.

The influence of health system organizational structure and culture on integration of health services: the example of HIV service monitoring in South Africa.

PubMed

Kawonga, Mary; Blaauw, Duane; Fonn, Sharon

2016-11-01

Administrative integration of disease control programmes (DCPs) within the district health system has been a health sector reform priority in South Africa for two decades. The reforms entail district managers assuming authority for the planning and monitoring of DCPs in districts, with DCP managers providing specialist support. There has been little progress in achieving this, and a dearth of research exploring why. Using a case study of HIV programme monitoring and evaluation (M&E), this article explores whether South Africa's health system is configured to support administrative integration. The article draws on data from document reviews and interviews with 54 programme and district managers in two of nine provinces, exploring their respective roles in decision-making regarding HIV M&E system design and in using HIV data for monitoring uptake of HIV interventions in districts. Using Mintzberg's configurations framework, we describe three organizational parameters: (a) extent of centralization (whether district managers play a role in decisions regarding the design of the HIV M&E system); (b) key part of the organization (extent to which sub-national programme managers vs district managers play the central role in HIV monitoring in districts); and (c) coordination mechanisms used (whether highly formalized and rules-based or more output-based to promote agency). We find that the health system can be characterized as Mintzberg's machine bureaucracy. It is centralized and highly formalized with structures, management styles and practices that promote programme managers as lead role players in the monitoring of HIV interventions within districts. This undermines policy objectives of district managers assuming this leadership role. Our study enhances the understanding of organizational factors that may limit the success of administrative integration reforms and suggests interventions that may mitigate this. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Using data from monitoring combined sewer overflows to assess, improve, and maintain combined sewer systems.

PubMed

Montserrat, A; Bosch, Ll; Kiser, M A; Poch, M; Corominas, Ll

2015-02-01

Using low-cost sensors, data can be collected on the occurrence and duration of overflows in each combined sewer overflow (CSO) structure in a combined sewer system (CSS). The collection and analysis of real data can be used to assess, improve, and maintain CSSs in order to reduce the number and impact of overflows. The objective of this study was to develop a methodology to evaluate the performance of CSSs using low-cost monitoring. This methodology includes (1) assessing the capacity of a CSS using overflow duration and rain volume data, (2) characterizing the performance of CSO structures with statistics, (3) evaluating the compliance of a CSS with government guidelines, and (4) generating decision tree models to provide support to managers for making decisions about system maintenance. The methodology is demonstrated with a case study of a CSS in La Garriga, Spain. The rain volume breaking point from which CSO structures started to overflow ranged from 0.6 mm to 2.8 mm. The structures with the best and worst performance in terms of overflow (overflow probability, order, duration and CSO ranking) were characterized. Most of the obtained decision trees to predict overflows from rain data had accuracies ranging from 70% to 83%. The results obtained from the proposed methodology can greatly support managers and engineers dealing with real-world problems, improvements, and maintenance of CSSs. Copyright © 2014 Elsevier B.V. All rights reserved.

Is it worth changing pattern recognition methods for structural health monitoring?

NASA Astrophysics Data System (ADS)

Bull, L. A.; Worden, K.; Cross, E. J.; Dervilis, N.

2017-05-01

The key element of this work is to demonstrate alternative strategies for using pattern recognition algorithms whilst investigating structural health monitoring. This paper looks to determine if it makes any difference in choosing from a range of established classification techniques: from decision trees and support vector machines, to Gaussian processes. Classification algorithms are tested on adjustable synthetic data to establish performance metrics, then all techniques are applied to real SHM data. To aid the selection of training data, an informative chain of artificial intelligence tools is used to explore an active learning interaction between meaningful clusters of data.

Elements of an integrated health monitoring framework

NASA Astrophysics Data System (ADS)

Fraser, Michael; Elgamal, Ahmed; Conte, Joel P.; Masri, Sami; Fountain, Tony; Gupta, Amarnath; Trivedi, Mohan; El Zarki, Magda

2003-07-01

Internet technologies are increasingly facilitating real-time monitoring of Bridges and Highways. The advances in wireless communications for instance, are allowing practical deployments for large extended systems. Sensor data, including video signals, can be used for long-term condition assessment, traffic-load regulation, emergency response, and seismic safety applications. Computer-based automated signal-analysis algorithms routinely process the incoming data and determine anomalies based on pre-defined response thresholds and more involved signal analysis techniques. Upon authentication, appropriate action may be authorized for maintenance, early warning, and/or emergency response. In such a strategy, data from thousands of sensors can be analyzed with near real-time and long-term assessment and decision-making implications. Addressing the above, a flexible and scalable (e.g., for an entire Highway system, or portfolio of Networked Civil Infrastructure) software architecture/framework is being developed and implemented. This framework will network and integrate real-time heterogeneous sensor data, database and archiving systems, computer vision, data analysis and interpretation, physics-based numerical simulation of complex structural systems, visualization, reliability & risk analysis, and rational statistical decision-making procedures. Thus, within this framework, data is converted into information, information into knowledge, and knowledge into decision at the end of the pipeline. Such a decision-support system contributes to the vitality of our economy, as rehabilitation, renewal, replacement, and/or maintenance of this infrastructure are estimated to require expenditures in the Trillion-dollar range nationwide, including issues of Homeland security and natural disaster mitigation. A pilot website (http://bridge.ucsd.edu/compositedeck.html) currently depicts some basic elements of the envisioned integrated health monitoring analysis framework.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2014-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2015-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients.

PubMed

Mougiakakou, Stavroula G; Bartsocas, Christos S; Bozas, Evangelos; Chaniotakis, Nikos; Iliopoulou, Dimitra; Kouris, Ioannis; Pavlopoulos, Sotiris; Prountzou, Aikaterini; Skevofilakas, Marios; Tsoukalis, Alexandre; Varotsis, Kostas; Vazeou, Andrianni; Zarkogianni, Konstantia; Nikita, Konstantina S

2010-05-01

SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

Unmanned Aircraft Systems for Monitoring Department of the Interior Lands

NASA Astrophysics Data System (ADS)

Hutt, M. E.; Quirk, B.

2013-12-01

Unmanned Aircraft Systems (UAS) technology is quickly evolving and will have a significant impact on Earth science research. The U.S. Geological Survey (USGS) is conducting an operational test and evaluation of UAS to see how this technology supports the mission of the Department of the Interior (DOI). Over the last 4 years, the USGS, working with many partners, has been actively conducting proof of concept UAS operations, which are designed to evaluate the potential of UAS technology to support the mandated DOI scientific, resource and land management missions. UAS technology is being made available to monitor environmental conditions, analyze the impacts of climate change, respond to natural hazards, understand landscape change rates and consequences, conduct wildlife inventories and support related land management and law enforcement missions. Using small UAS (sUAS), the USGS is able to tailor solutions to meet project requirements by obtaining very high resolution video data, acquiring thermal imagery, detecting chemical plumes, and generating digital terrain models at a fraction of the cost of conventional surveying methods. UAS technology is providing a mechanism to collect timely remote sensing data at a low cost and at low risk over DOI lands that can be difficult to monitor and consequently enhances our ability to provide unbiased scientific information to better enable decision makers to make informed decisions. This presentation describes the UAS technology and infrastructure being employed, the application projects already accomplished, lessons learned and future of UAS within the DOI. We fully expect that by 2020 UAS will emerge as a primary platform for all DOI remote sensing applications. Much like the use of Internet technology, Geographic Information Systems (GIS) and Global Positioning Systems (GPS), UAS have the potential of enabling the DOI to be better stewards of the land.

Agricultural drought risk monitoring and yield loss forecast with remote sensing data

NASA Astrophysics Data System (ADS)

Nagy, Attila; Tamás, János; Fehér, János

2015-04-01

The World Meteorological Organization (WMO) and Global Water Partnership (GWP) have launched a joint Integrated Drought Management Programme (IDMP) to improve monitoring and prevention of droughts. In the frame of this project this study focuses on identification of agricultural drought characteristics and elaborates a monitoring method (with application of remote sensing data), which could result in appropriate early warning of droughts before irreversible yield loss and/or quality degradation occur. The spatial decision supporting system to be developed will help the farmers in reducing drought risk of the different regions by plant specific calibrated drought indexes. The study area was the Tisza River Basin, which is located in Central Europe within the Carpathian Basin. For the investigations normalized difference vegetation index (NDVI) was used calculated from 16 day moving average chlorophyll intensity and biomass quantity data. The results offer concrete identification of remote sensing and GIS data tools for agricultural drought monitoring and forecast, which eventually provides information on physical implementation of drought risk levels. In the first step, we statistically normalized the crop yield maps and the MODIS satellite data. Then the drought-induced crop yield loss values were classified. The crop yield loss data were validated against the regional meteorological drought index values (SPI), the water management and soil physical data. The objective of this method was to determine the congruency of data derived from spectral data and from field measurements. As a result, five drought risk levels were developed to identify the effect of drought on yields: Watch, Early Warning, Warning, Alert and Catastrophe. In the frame of this innovation such a data link and integration, missing from decision process of IDMP, are established, which can facilitate the rapid spatial and temporal monitoring of meteorological, agricultural drought phenomena and its economic relations, increasing the time factors effectiveness of decision support system. This methodology will be extendable for other Central European countries when country specific data are available and entered into the system. This new drought risk monitoring and forecasting method is an improvement for hydrologists, meteorologists and farmers, allowing to set up a complex drought monitoring system, where for a given period and respective catchment area the expected yield loss can be predicted, and the role of vegetation in the hydrological cycle could be more precisely quantified. Based on the results more water-saving agricultural land use alternatives could be planned on drought areas.

Participatory monitoring and evaluation approaches that influence decision-making: lessons from a maternal and newborn study in Eastern Uganda.

PubMed

Kananura, Rornald Muhumuza; Ekirapa-Kiracho, Elizabeth; Paina, Ligia; Bumba, Ahmed; Mulekwa, Godfrey; Nakiganda-Busiku, Dinah; Oo, Htet Nay Lin; Kiwanuka, Suzanne Namusoke; George, Asha; Peters, David H

2017-12-28

The use of participatory monitoring and evaluation (M&E) approaches is important for guiding local decision-making, promoting the implementation of effective interventions and addressing emerging issues in the course of implementation. In this article, we explore how participatory M&E approaches helped to identify key design and implementation issues and how they influenced stakeholders' decision-making in eastern Uganda. The data for this paper is drawn from a retrospective reflection of various M&E approaches used in a maternal and newborn health project that was implemented in three districts in eastern Uganda. The methods included qualitative and quantitative M&E techniques such as  key informant interviews, formal surveys and supportive supervision, as well as participatory approaches, notably participatory impact pathway analysis. At the design stage, the M&E approaches were useful for identifying key local problems and feasible local solutions and informing the activities that were subsequently implemented. During the implementation phase, the M&E approaches provided evidence that informed decision-making and helped identify emerging issues, such as weak implementation by some village health teams, health facility constraints such as poor use of standard guidelines, lack of placenta disposal pits, inadequate fuel for the ambulance at some facilities, and poor care for low birth weight infants. Sharing this information with key stakeholders prompted them to take appropriate actions. For example, the sub-county leadership constructed placenta disposal pits, the district health officer provided fuel for ambulances, and health workers received refresher training and mentorship on how to care for newborns. Diverse sources of information and perspectives can help researchers and decision-makers understand and adapt evidence to contexts for more effective interventions. Supporting districts to have crosscutting, routine information generating and sharing platforms that bring together stakeholders from different sectors is therefore crucial for the successful implementation of complex development interventions.

Public health policy decisions on medical innovations: what role can early economic evaluation play?

PubMed

Hartz, Susanne; John, Jürgen

2009-02-01

Our contribution aims to explore the different ways in which early economic data can inform public health policy decisions on new medical technologies. A literature research was conducted to detect methodological contributions covering the health policy perspective. Early economic data on new technologies can support public health policy decisions in several ways. Embedded in horizon scanning and HTA activities, it adds to monitoring and assessment of innovations. It can play a role in the control of technology diffusion by informing coverage and reimbursement decisions as well as the direct public promotion of healthcare technologies, leading to increased efficiency. Major problems include the uncertainty related to economic data at early stages as well as the timing of the evaluation of an innovation. Decision-makers can benefit from the information supplied by early economic data, but the actual use in practice is difficult to determine. Further empirical evidence should be gathered, while the use could be promoted by further standardization.

Smart telemedicine support for continuous glucose monitoring: the embryo of a future global agent for diabetes care.

PubMed

Rigla, Mercedes

2011-01-01

Although current systems for continuous glucose monitoring (CGM) are the result of progressive technological improvement, and although a beneficial effect on glucose control has been demonstrated, few patients are using them. Something similar has happened to telemedicine (TM); in spite of the long-term experience, which began in the early 1980s, no TM system has been widely adopted, and presential visits are still almost the only way diabetologists and patients communicate. The hypothesis developed in this article is that neither CGM nor TM will ever be routinely implemented separately, and their consideration as essential elements for standard diabetes care will one day come from their integration as parts of a telemedical monitoring platform. This platform, which should include artificial intelligence for giving decision support to patients and physicians, will represent the core of a more complex global agent for diabetes care, which will provide control algorithms and risk analysis among other essential functions. © 2010 Diabetes Technology Society.

Monitoring for the management of disease risk in animal translocation programmes

USGS Publications Warehouse

Nichols, James D.; Hollmen, Tuula E.; Grand, James B.

2017-01-01

Monitoring is best viewed as a component of some larger programme focused on science or conservation. The value of monitoring is determined by the extent to which it informs the parent process. Animal translocation programmes are typically designed to augment or establish viable animal populations without changing the local community in any detrimental way. Such programmes seek to minimize disease risk to local wild animals, to translocated animals, and in some cases to humans. Disease monitoring can inform translocation decisions by (1) providing information for state-dependent decisions, (2) assessing progress towards programme objectives, and (3) permitting learning in order to make better decisions in the future. Here we discuss specific decisions that can be informed by both pre-release and post-release disease monitoring programmes. We specify state variables and vital rates needed to inform these decisions. We then discuss monitoring data and analytic methods that can be used to estimate these state variables and vital rates. Our discussion is necessarily general, but hopefully provides a basis for tailoring disease monitoring approaches to specific translocation programmes.

The use of syndromic surveillance for decision-making during the H1N1 pandemic: a qualitative study.

PubMed

Chu, Anna; Savage, Rachel; Willison, Don; Crowcroft, Natasha S; Rosella, Laura C; Sider, Doug; Garay, Jason; Gemmill, Ian; Winter, Anne-Luise; Davies, Richard F; Johnson, Ian

2012-10-30

Although an increasing number of studies are documenting uses of syndromic surveillance by front line public health, few detail the value added from linking syndromic data to public health decision-making. This study seeks to understand how syndromic data informed specific public health actions during the 2009 H1N1 pandemic. Semi-structured telephone interviews were conducted with participants from Ontario's public health departments, the provincial ministry of health and federal public health agency to gather information about syndromic surveillance systems used and the role of syndromic data in informing specific public health actions taken during the pandemic. Responses were compared with how the same decisions were made by non-syndromic surveillance users. Findings from 56 interviews (82% response) show that syndromic data were most used for monitoring virus activity, measuring impact on the health care system and informing the opening of influenza assessment centres in several jurisdictions, and supporting communications and messaging, rather than its intended purpose of early outbreak detection. Syndromic data had limited impact on decisions that involved the operation of immunization clinics, school closures, sending information letters home with school children or providing recommendations to health care providers. Both syndromic surveillance users and non-users reported that guidance from the provincial ministry of health, communications with stakeholders and vaccine availability were driving factors in these public health decisions. Syndromic surveillance had limited use in decision-making during the 2009 H1N1 pandemic in Ontario. This study provides insights into the reasons why this occurred. Despite this, syndromic data were valued for providing situational awareness and confidence to support public communications and recommendations. Developing an understanding of how syndromic data are utilized during public health events provides valuable evidence to support future investments in public health surveillance.

Development of a decision analytic model to support decision making and risk communication about thrombolytic treatment.

PubMed

McMeekin, Peter; Flynn, Darren; Ford, Gary A; Rodgers, Helen; Gray, Jo; Thomson, Richard G

2015-11-11

Individualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke. A decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data. The model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA. We have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.

Automated lifestyle coaching for cerebro-cardiovascular disease prevention.

PubMed

Spassova, Lübomira; Vittore, Debora; Droste, Dirk; Rösch, Norbert

2013-01-01

As soon as telemedicine aims at supporting the prevention of ischemic events (e.g., stroke and myocardial infarction), the mere monitoring of vital parameters is not sufficient. Instead, the patients should be supported in their efforts to actively reduce their individual risk factors and to achieve and maintain a healthier lifestyle. The Luxembourg-based CAPSYS project (Computer-Aided Prevention System) aims at combining the advantages of telephone coaching with those of home telemonitoring and with methods of computer-aided decision support in direct contact with the patients. The suitability and user acceptance of the system is currently being evaluated in a first pilot study.

Integrated System of Structural Health Monitoring and Intelligent Management for a Cable-Stayed Bridge

PubMed Central

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system. PMID:25140342

Integrated system of structural health monitoring and intelligent management for a cable-stayed bridge.

PubMed

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

The Sustainment Management Support Project

DTIC Science & Technology

2010-09-01

on the market that incorporates all of the features of Decision Maker, in particular, the use of the objective weighted...These databases do not necessarily co-exist on the same computer server or even in the same physical location. They are disparate and owned by ...installation on HMAS Ballarat The SIU will be used to provide condition-monitoring (sensor and alarm) data from the FFH control and

U.S. Coast Guard Fleet Mix Planning: A Decision Support System Prototype

DTIC Science & Technology

1991-03-01

91-16785 Al ’ 1 1 1 Unclassified SECURITY CLASSIFICATION OF ThIS PAGE REPORT DOCUMENTATION PAGE I L REPORTSECURITY CLASSIFICATION lb. RESTRICTIVE...MARKINGS Unclassified 2a. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/ AVAILABITY OF REPORT Approved for public release; distribution is inlimited...2b. DECIASSIFICATION/DOWNGRADING SCHEDULE 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) 6a. NAME OF

Teaching the Whole Child: Instructional Practices That Support Social-Emotional Learning in Three Teacher Evaluation Frameworks. Research-to-Practice Brief. Revised Edition

ERIC Educational Resources Information Center

Yoder, Nicholas

2014-01-01

Teachers help promote the social and emotional learning skills students need to be college and career ready, such as collaborating with others, monitoring their own behavior, and making responsible decisions. Social-emotional learning (SEL) is critical to the introduction of college and career readiness standards. To bridge the connection between…

Systematization of climate data in the virtual research environment on the basis of ontology approach

NASA Astrophysics Data System (ADS)

Alipova, K. A.; Bart, A. A.; Fazliev, A. Z.; Gordov, E. P.; Okladnikov, I. G.; Privezentsev, A. I.; Titov, A. G.

2017-11-01

The first version of a primitive OWL-ontology of collections climate and meteorological data of Institute of Monitoring of Climatic and Ecological Systems SB RAS is presented. The ontology is a component of expert and decision support systems intended for quick search for climate and meteorological data required for solution of a certain class of applied problems.

Climate Change and Water Working Group - User Needs to Manage Hydrclimatic Risk from Days to Decades

NASA Astrophysics Data System (ADS)

Raff, D. A.; Brekke, L. D.; Werner, K.; Wood, A.; White, K. D.

2012-12-01

The Federal Climate Change Water Working Group (CCAWWG) provides engineering and scientific collaborations in support of water management. CCAWWG objectives include building working relationships across federal science and water management agencies, provide a forum to share expertise and leverage resources, develop education and training forums, to work with water managers to understand scientific needs and to foster collaborative efforts across the Federal and non-Federal water management and science communities to address those needs. Identifying and addressing water management needs has been categorized across two major time scales: days to a decade and multi-decadal, respectively. These two time periods are termed "Short-Term" and "Long-Term" in terms of the types of water management decisions they support where Short-Term roughly correlates to water management operations and Long-Term roughly correlates to planning activities. This presentation will focus on portraying the identified water management user needs across these two time periods. User Needs for Long-Term planning were identified in the 2011 Reclamation and USACE "Addressing Climate Change in Long-Term Water Resources Planning and Management: User Needs for Improving Tools and Information." User needs for Long-Term planning are identified across eight major categories: Summarize Relevant Literature, Obtain Climate Change Information, Make Decisions About How to Use the Climate Change Information, Assess Natural Systems Response, Assess Socioeconomic and Institutional Response, Assess System Risks and Evaluate Alternatives, Assess and Characterize Uncertainties, and Communicating Results and Uncertainties to Decisionmakers. User Needs for Short-Term operations are focused on needs relative to available or desired monitoring and forecast products from the hydroclimatic community. These needs are presenting in the 2012 USACE, Reclamation, and NOAA - NWS "Short-Term Water Management Decisions: User Needs for Improved Climate, Weather, and Hydrologic Information." Identified needs are presented in four categories: Monitoring, Forecasting, Understanding on Product Relationships and Utilization in Water Management, and Information Services Enterprise. These needs represent everything from continuation and enhancement of in situ monitoring products such as USGS water gages and precipitation networks to supporting product maintenance and evolution to accommodate newly developed technologies.

A Review of Emerging Technologies for the Management of Diabetes Mellitus.

PubMed

Zarkogianni, Konstantia; Litsa, Eleni; Mitsis, Konstantinos; Wu, Po-Yen; Kaddi, Chanchala D; Cheng, Chih-Wen; Wang, May D; Nikita, Konstantina S

2015-12-01

High prevalence of diabetes mellitus (DM) along with the poor health outcomes and the escalated costs of treatment and care poses the need to focus on prevention, early detection and improved management of the disease. The aim of this paper is to present and discuss the latest accomplishments in sensors for glucose and lifestyle monitoring along with clinical decision support systems (CDSSs) facilitating self-disease management and supporting healthcare professionals in decision making. A critical literature review analysis is conducted focusing on advances in: 1) sensors for physiological and lifestyle monitoring, 2) models and molecular biomarkers for predicting the onset and assessing the progress of DM, and 3) modeling and control methods for regulating glucose levels. Glucose and lifestyle sensing technologies are continuously evolving with current research focusing on the development of noninvasive sensors for accurate glucose monitoring. A wide range of modeling, classification, clustering, and control approaches have been deployed for the development of the CDSS for diabetes management. Sophisticated multiscale, multilevel modeling frameworks taking into account information from behavioral down to molecular level are necessary to reveal correlations and patterns indicating the onset and evolution of DM. Integration of data originating from sensor-based systems and electronic health records combined with smart data analytics methods and powerful user centered approaches enable the shift toward preventive, predictive, personalized, and participatory diabetes care. The potential of sensing and predictive modeling approaches toward improving diabetes management is highlighted and related challenges are identified.

Comparison of Two Sources of Clinical Audit Data to Assess the Delivery of Diabetes Care in Aboriginal Communities.

PubMed

Regan, Timothy; Paul, Christine; Ishiguchi, Paul; D'Este, Catherine; Koller, Claudia; Forshaw, Kristy; Noble, Natasha; Oldmeadow, Christopher; Bisquera, Alessandra; Eades, Sandra

2017-10-17

The objective of this study was to determine the concordance between data extracted from two Clinical Decision Support Systems regarding diabetes testing and monitoring at Aboriginal Community Controlled Health Services in Australia. De-identified PenCAT and Communicare Systems data were extracted from the services allocated to the intervention arm of a diabetes care trial, and intra-class correlations for each extracted item were derived at a service level. Strong to very strong correlations between the two data sources were found regarding the total number of patients with diabetes per service (Intra-class correlation [ICC] = 0.99), as well as the number (ICC = 0.98-0.99) and proportion (ICC = 0.96) of patients with diabetes by gender. The correlation was moderate for the number and proportion of Type 2 diabetes patients per service in the group aged 18-34 years (ICC = 0.65 and 0.8-0.82 respectively). Strong to very strong correlations were found for numbers and proportions of patients being tested for diabetes, and for appropriate monitoring of patients known to have diabetes (ICC = 0.998-1.00). This indicated a generally high degree of concordance between whole-service data extracted by the two Clinical Decision Support Systems. Therefore, the less expensive or less complex option (depending on the individual circumstances of the service) may be appropriate for monitoring diabetes testing and care. However, the extraction of data about subgroups of patients may not be interchangeable.

A Review of Emerging Technologies for the Management of Diabetes Mellitus

PubMed Central

Zarkogianni, Konstantia; Litsa, Eleni; Mitsis, Konstantinos; Wu, Po-Yen; Kaddi, Chanchala D.; Cheng, Chih-Wen; Wang, May D.; Nikita, Konstantina S.

2016-01-01

Objective High prevalence of diabetes mellitus (DM) along with the poor health outcomes and the escalated costs of treatment and care poses the need to focus on prevention, early detection and improved management of the disease. The aim of this paper is to present and discuss the latest accomplishments in sensors for glucose and lifestyle monitoring along with clinical decision support systems (CDSSs) facilitating self-disease management and supporting healthcare professionals in decision making. Methods A critical literature review analysis is conducted focusing on advances in: 1) sensors for physiological and lifestyle monitoring, 2) models and molecular biomarkers for predicting the onset and assessing the progress of DM, and 3) modeling and control methods for regulating glucose levels. Results Glucose and lifestyle sensing technologies are continuously evolving with current research focusing on the development of noninvasive sensors for accurate glucose monitoring. A wide range of modeling, classification, clustering, and control approaches have been deployed for the development of the CDSS for diabetes management. Sophisticated multiscale, multilevel modeling frameworks taking into account information from behavioral down to molecular level are necessary to reveal correlations and patterns indicating the onset and evolution of DM. Conclusion Integration of data originating from sensor-based systems and electronic health records combined with smart data analytics methods and powerful user centered approaches enable the shift toward preventive, predictive, personalized, and participatory diabetes care. Significance The potential of sensing and predictive modeling approaches toward improving diabetes management is highlighted and related challenges are identified. PMID:26292334

A decision support system for adaptive real-time management ofseasonal wetlands in California

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

Quinn, Nigel W.T.; Hanna, W. Mark

This paper describes the development of a comprehensive flow and salinity monitoring system and application of a decision support system (DSS) to improve management of seasonal wetlands in the San Joaquin Valley of California. The Environmental Protection Agency regulates salinity discharges from non-point sources to the San Joaquin River using a procedure known as the Total Maximum Daily Load (TMDL) to allocate the assimilative capacity of the River for salt among watershed sources. Management of wetland sources of salt load will require the development of monitoring systems, more integrative management strategies and coordination with other entities. To obtain local cooperationmore » the Grassland Water District, whose primary function is to supply surface water to private duck clubs and managed wetlands, needs to communicate to local landowners the likely impacts of salinity regulation on the long term health and function of wildfowl habitat. The project described in this paper will also provide this information. The models that form the backbone of the DSS develop salinity balances at both a regional and local scale. The regional scale concentrates on deliveries to and exports from the Grasland Water District while the local scale focuses on an individual wetland unit where more intensive monitoring is being conducted. The design of the DSS is constrained to meet the needs of busy wetland managers and is being designed from the bottom up utilizing tools and procedures familiar to these individuals.« less

Designing the Monitoring of Water-Related Sustainable Development Goals Based on Value of Information

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M. A.; de Sherbinin, A. M.; Fischer, A.

2015-12-01

The proposed Sustainable Development Goals (SDGs) represent an unprecedented international commitment to collective action and targeted interventions at global, regional, and national scales. Existing monitoring and data infrastructures are inadequate for producing the variety of environmental and socioeconomic information needed to ensure efficient and effective outcomes across the range of interlinked SDGs and targets. The scientific community needs to take a lead in developing new tools and approaches that, at reasonable cost, provide monitoring data of sufficient quality and spatial and temporal coverage to support informed decision making by diverse stakeholders. The expanded SDGs related to water offer the opportunity to explore potential new monitoring approaches and data system architectures in a key sector, building on existing water monitoring capabilities and incorporating new technologies and methods. Since additional investments in monitoring will undoubtedly be limited, it is important to assess carefully the value of information produced by different options and their associated risks and tradeoffs. We review here the existing set of water monitoring systems, known gaps and limitations, stakeholder inputs on data needs, and the potential value of information in light of alternative water sector interventions. Of particular interest are opportunities to share investments in monitoring across sectors and stakeholders (e.g., public and private entities) and to identify where incremental improvements in water monitoring could have significant benefits for other SDGs (e.g., related to health, energy, agriculture, and climate change). Value of information is also driven by the numbers of people affected by decisions or able to take advantage of improved data, which implies the need not only to collect and archive data, but also to invest in making data accessible and usable to diverse and geographically dispersed users.

Privacy versus autonomy: a tradeoff model for smart home monitoring technologies.

PubMed

Townsend, Daphne; Knoefel, Frank; Goubran, Rafik

2011-01-01

Smart homes are proposed as a new location for the delivery of healthcare services. They provide healthcare monitoring and communication services, by using integrated sensor network technologies. We validate a hypothesis regarding older adults' adoption of home monitoring technologies by conducting a literature review of articles studying older adults' attitudes and perceptions of sensor technologies. Using current literature to support the hypothesis, this paper applies the tradeoff model to decisions about sensor acceptance. Older adults are willing to trade privacy (by accepting a monitoring technology), for autonomy. As the information captured by the sensor becomes more intrusive and the infringement on privacy increases, sensors are accepted if the loss in privacy is traded for autonomy. Even video cameras, the most intrusive sensor type were accepted in exchange for the height of autonomy which is to remain in the home.

Clinic-Based Mobile Health Decision Support to Enhance Adult Epilepsy Self-Management: An Intervention Mapping Approach.

PubMed

Shegog, Ross; Begley, Charles E

2017-01-01

Epilepsy is a neurological disorder involving recurrent seizures. It affects approximately 5 million people in the U.S. To optimize their quality of life people with epilepsy are encouraged to engage in self-management (S-M) behaviors. These include managing their treatment (e.g., adhering to anti-seizure medication and clinical visit schedules), managing their seizures (e.g., responding to seizure episodes), managing their safety (e.g., monitoring and avoiding environmental seizure triggers), and managing their co-morbid conditions (e.g., anxiety, depression). The clinic-based Management Information Decision Support Epilepsy Tool (MINDSET) is a decision-support system founded on theory and empirical evidence. It is designed to increase awareness by adult patients (≥18 years) and their health-care provider regarding the patient's epilepsy S-M behaviors, facilitate communication during the clinic visit to prioritize S-M goals and strategies commensurate with the patient's needs, and increase the patient's self-efficacy to achieve those goals. The purpose of this paper is to describe the application of intervention mapping (IM) to develop, implement, and formatively evaluate the clinic-based MINDSET prototype and in developing implementation and evaluation plans. Deliverables comprised a logic model of the problem (IM Step 1); matrices of program objectives (IM Step 2); a program planning document comprising scope, sequence, theory-based methods, and practical strategies (IM Step 3); a functional MINDSET program prototype (IM Step 4); plans for implementation (IM Step 5); and evaluation (IM Step 6). IM provided a logical and systematic approach to developing and evaluating clinic-based decision support toward epilepsy S-M.

RF-CLASS: A Remote-sensing-based Interoperable Web service system for Flood Crop Loss Assessment

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Kang, L.

2014-12-01

Flood is one of the worst natural disasters in the world. Flooding often causes significant crop loss over large agricultural areas in the United States. Two USDA agencies, the National Agricultural Statistics Service (NASS) and Risk Management Agency (RMA), make decisions on flood statistics, crop insurance policy, and recovery management by collecting, analyzing, reporting, and utilizing flooded crop acreage and crop loss information. NASS has the mandate to report crop loss after all flood events. RMA manages crop insurance policy and uses crop loss information to guide the creation of the crop insurance policy and the aftermath compensation. Many studies have been conducted in the recent years on monitoring floods and assessing the crop loss due to floods with remote sensing and geographic information technologies. The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS), being developed with NASA and USDA support, aims to significantly improve the post-flood agricultural decision-making supports in USDA by integrating and advancing the recently developed technologies. RF-CLASS will operationally provide information to support USDA decision making activities on collecting and archiving flood acreage and duration, recording annual crop loss due to flood, assessing the crop insurance rating areas, investigating crop policy compliance, and spot checking of crop loss claims. This presentation will discuss the remote sensing and GIS based methods for deriving the needed information to support the decision making, the RF-CLASS cybersystem architecture, the standards and interoperability arrangements in the system, and the current and planned capabilities of the system.

Clinical Decision Support Improves Initial Dosing and Monitoring of Tobramycin and Amikacin

PubMed Central

Cox, Zachary L.; Nelsen, Cori L.; Waitman, Lemuel R.; McCoy, Jacob A.; Peterson, Josh F.

2010-01-01

Purpose Clinical decision support (CDS) systems could be valuable tools in reducing aminoglycoside prescribing errors. We evaluated the impact of CDS on initial dosing, interval, and pharmacokinetic outcomes of amikacin and tobramycin therapy. Methods A complex CDS advisor to provide guidance on initial dosing and monitoring, using both traditional and extended interval dosing strategies, was integrated into computerized provider order entry (CPOE) and compared to a control group which featured close pharmacy monitoring of all aminoglycoside orders. A random sample of 118 patients from an academic, tertiary care medical center prescribed amikacin and tobramycin prior to advisor implementation was compared to 98 patients admitted following advisor implementation. Primary outcome was an initial dose within 10% of a dose calculated to be adherent to published dose guidelines. Secondary outcomes were a guideline-adherent interval, trough and peak concentrations in goal range, and incidence of nephrotoxicity. Results Of 216 patients studied, 97 were prescribed amikacin and 119 were prescribed tobramycin. The primary outcome of initial dosing consistent with guideline-based care increased from 40% in the pre-advisor arm to 80% in the post-advisor arm (p<0.001), with a number needed to treat of 3 patients to prevent one incorrect dose. Correct initial interval based on renal function also increased from 63% to 87% (p<0.001). The changes in initial dosing and interval resulted in an increase of trough concentrations in the goal range from 59% pre-advisor to 89% post-advisor implementation (p=0.0004). There was no significant difference in peak concentrations in goal range or incidence of nephrotoxicity (25% vs. 17%, p=0.2). Conclusion An advisor for aminoglycoside dosing and monitoring integrated into CPOE significantly improves initial dosing, selection of interval, and trough concentrations at goal compared to unassisted physician dosing. PMID:21411805

Cognitive Abilities, Monitoring Confidence, and Control Thresholds Explain Individual Differences in Heuristics and Biases

PubMed Central

Jackson, Simon A.; Kleitman, Sabina; Howie, Pauline; Stankov, Lazar

2016-01-01

In this paper, we investigate whether individual differences in performance on heuristic and biases tasks can be explained by cognitive abilities, monitoring confidence, and control thresholds. Current theories explain individual differences in these tasks by the ability to detect errors and override automatic but biased judgments, and deliberative cognitive abilities that help to construct the correct response. Here we retain cognitive abilities but disentangle error detection, proposing that lower monitoring confidence and higher control thresholds promote error checking. Participants (N = 250) completed tasks assessing their fluid reasoning abilities, stable monitoring confidence levels, and the control threshold they impose on their decisions. They also completed seven typical heuristic and biases tasks such as the cognitive reflection test and Resistance to Framing. Using structural equation modeling, we found that individuals with higher reasoning abilities, lower monitoring confidence, and higher control threshold performed significantly and, at times, substantially better on the heuristic and biases tasks. Individuals with higher control thresholds also showed lower preferences for risky alternatives in a gambling task. Furthermore, residual correlations among the heuristic and biases tasks were reduced to null, indicating that cognitive abilities, monitoring confidence, and control thresholds accounted for their shared variance. Implications include the proposal that the capacity to detect errors does not differ between individuals. Rather, individuals might adopt varied strategies that promote error checking to different degrees, regardless of whether they have made a mistake or not. The results support growing evidence that decision-making involves cognitive abilities that construct actions and monitoring and control processes that manage their initiation. PMID:27790170

Cognitive Abilities, Monitoring Confidence, and Control Thresholds Explain Individual Differences in Heuristics and Biases.

PubMed

Jackson, Simon A; Kleitman, Sabina; Howie, Pauline; Stankov, Lazar

2016-01-01

In this paper, we investigate whether individual differences in performance on heuristic and biases tasks can be explained by cognitive abilities, monitoring confidence, and control thresholds. Current theories explain individual differences in these tasks by the ability to detect errors and override automatic but biased judgments, and deliberative cognitive abilities that help to construct the correct response. Here we retain cognitive abilities but disentangle error detection, proposing that lower monitoring confidence and higher control thresholds promote error checking. Participants ( N = 250) completed tasks assessing their fluid reasoning abilities, stable monitoring confidence levels, and the control threshold they impose on their decisions. They also completed seven typical heuristic and biases tasks such as the cognitive reflection test and Resistance to Framing. Using structural equation modeling, we found that individuals with higher reasoning abilities, lower monitoring confidence, and higher control threshold performed significantly and, at times, substantially better on the heuristic and biases tasks. Individuals with higher control thresholds also showed lower preferences for risky alternatives in a gambling task. Furthermore, residual correlations among the heuristic and biases tasks were reduced to null, indicating that cognitive abilities, monitoring confidence, and control thresholds accounted for their shared variance. Implications include the proposal that the capacity to detect errors does not differ between individuals. Rather, individuals might adopt varied strategies that promote error checking to different degrees, regardless of whether they have made a mistake or not. The results support growing evidence that decision-making involves cognitive abilities that construct actions and monitoring and control processes that manage their initiation.

A Possible Approach for Addressing Neglected Human Factors Issues of Systems Engineering

NASA Technical Reports Server (NTRS)

Johnson, Christopher W.; Holloway, C. Michael

2011-01-01

The increasing complexity of safety-critical applications has led to the introduction of decision support tools in the transportation and process industries. Automation has also been introduced to support operator intervention in safety-critical applications. These innovations help reduce overall operator workload, and filter application data to maximize the finite cognitive and perceptual resources of system operators. However, these benefits do not come without a cost. Increased computational support for the end-users of safety-critical applications leads to increased reliance on engineers to monitor and maintain automated systems and decision support tools. This paper argues that by focussing on the end-users of complex applications, previous research has tended to neglect the demands that are being placed on systems engineers. The argument is illustrated through discussing three recent accidents. The paper concludes by presenting a possible strategy for building and using highly automated systems based on increased attention by management and regulators, improvements in competency and training for technical staff, sustained support for engineering team resource management, and the development of incident reporting systems for infrastructure failures. This paper represents preliminary work, about which we seek comments and suggestions.

The Diagnosis and Treatment of Bipolar Disorder: Decision-Making in Primary Care

PubMed Central

2014-01-01

Bipolar disorder is a chronic episodic illness, characterized by recurrent episodes of manic or depressive symptoms. Patients with bipolar disorder frequently present first to primary care, but the diversity of the potential symptoms and a low index of suspicion among physicians can lead to misdiagnosis in many patients. Frequently, co-occurring psychiatric and medical conditions further complicate the differential diagnosis. A thorough diagnostic evaluation at clinical interview, combined with supportive case-finding tools, is essential to reach an accurate diagnosis. When treating bipolar patients, the primary care physician has an integral role in coordinating the multidisciplinary network. Pharmacologic treatment underpins both short- and long-term management of bipolar disorder. Maintenance treatment to prevent relapse is frequently founded on the same pharmacologic approaches that were effective in treating the acute symptoms. Regardless of the treatment approach that is selected, monitoring over the long term is essential to ensure continued symptom relief, functioning, safety, adherence, and general medical health. This article describes key decision-making steps in the management of bipolar disorder from the primary care perspective: from initial clinical suspicion to confirmation of the diagnosis to decision-making in acute and longer-term management and the importance of patient monitoring. PMID:25317368

A new parameterization for integrated population models to document amphibian reintroductions

USGS Publications Warehouse

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

2017-01-01

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

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

PubMed

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

2017-09-01

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

Decision support tool for diagnosing the source of variation

NASA Astrophysics Data System (ADS)

Masood, Ibrahim; Azrul Azhad Haizan, Mohamad; Norbaya Jumali, Siti; Ghazali, Farah Najihah Mohd; Razali, Hazlin Syafinaz Md; Shahir Yahya, Mohd; Azlan, Mohd Azwir bin

2017-08-01

Identifying the source of unnatural variation (SOV) in manufacturing process is essential for quality control. The Shewhart control chart patterns (CCPs) are commonly used to monitor the SOV. However, a proper interpretation of CCPs associated to its SOV requires a high skill industrial practitioner. Lack of knowledge in process engineering will lead to erroneous corrective action. The objective of this study is to design the operating procedures of computerized decision support tool (DST) for process diagnosis. The DST is an embedded tool in CCPs recognition scheme. Design methodology involves analysis of relationship between geometrical features, manufacturing process and CCPs. The DST contents information about CCPs and its possible root cause error and description on SOV phenomenon such as process deterioration in tool bluntness, offsetting tool, loading error, and changes in materials hardness. The DST will be useful for an industrial practitioner in making effective troubleshooting.

Cultivating Conformists or Raising Rebels? Connecting Parental Control and Autonomy Support to Adolescent Delinquency.

PubMed

Brauer, Jonathan R

2017-06-01

This study investigates short-term and long-term associations between parenting in early adolescence and delinquency throughout adolescence using data from the National Longitudinal Surveys. Multilevel longitudinal Poisson regressions show that behavioral control, psychological control, and decision-making autonomy in early adolescence (ages 10-11) are associated with delinquency trajectories throughout adolescence (ages 10-17). Path analyses reveal support for three mediation hypotheses. Parental monitoring (behavioral control) is negatively associated with delinquency in the short term and operates partly through changes in self-control. Parental pressure (psychological control) shows immediate and long-lasting associations with delinquency through changes in self-control and delinquent peer pressures. Decision-making autonomy is negatively associated with delinquency in the long term, yet may exacerbate delinquency in early adolescence by increasing exposure to delinquent peers. © 2016 The Author. Journal of Research on Adolescence © 2016 Society for Research on Adolescence.

[A computerised clinical decision-support system for the management of depression in Primary Care].

PubMed

Aragonès, Enric; Comín, Eva; Cavero, Myriam; Pérez, Víctor; Molina, Cristina; Palao, Diego

Despite its clinical relevance and its importance as a public health problem, there are major gaps in the management of depression. Evidence-based clinical guidelines are useful to improve processes and clinical outcomes. In order to make their implementation easier these guidelines have been transformed into computerised clinical decision support systems. In this article, a description is presented on the basics and characteristics of a new computerised clinical guideline for the management of major depression, developed in the public health system in Catalonia. This tool helps the clinician to establish reliable and accurate diagnoses of depression, to choose the best treatment a priori according to the disease and the patient characteristics. It also emphasises the importance of systematic monitoring to assess the clinical course, and to adjust therapeutic interventions to the patient's needs at all times. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

Southern California Disasters II

NASA Technical Reports Server (NTRS)

Nicholson, Heather; Todoroff, Amber L.; LeBoeuf, Madeline A.

2015-01-01

The USDA Forest Service (USFS) has multiple programs in place which primarily utilize Landsat imagery to produce burn severity indices for aiding wildfire damage assessment and mitigation. These indices provide widely-used wildfire damage assessment tools to decision makers. When the Hyperspectral Infrared Imager (HyspIRI) is launched in 2022, the sensor's hyperspectral resolution will support new methods for assessing natural disaster impacts on ecosystems, including wildfire damage to forests. This project used simulated HyspIRI data to study three southern California fires: Aspen, French, and King. Burn severity indices were calculated from the data and the results were quantitatively compared to the comparable USFS products currently in use. The final results from this project illustrate how HyspIRI data may be used in the future to enhance assessment of fire-damaged areas and provide additional monitoring tools for decision support to the USFS and other land management agencies.

A Business Analytics Software Tool for Monitoring and Predicting Radiology Throughput Performance.

PubMed

Jones, Stephen; Cournane, Seán; Sheehy, Niall; Hederman, Lucy

2016-12-01

Business analytics (BA) is increasingly being utilised by radiology departments to analyse and present data. It encompasses statistical analysis, forecasting and predictive modelling and is used as an umbrella term for decision support and business intelligence systems. The primary aim of this study was to determine whether utilising BA technologies could contribute towards improved decision support and resource management within radiology departments. A set of information technology requirements were identified with key stakeholders, and a prototype BA software tool was designed, developed and implemented. A qualitative evaluation of the tool was carried out through a series of semi-structured interviews with key stakeholders. Feedback was collated, and emergent themes were identified. The results indicated that BA software applications can provide visibility of radiology performance data across all time horizons. The study demonstrated that the tool could potentially assist with improving operational efficiencies and management of radiology resources.

[Development and clinical evaluation of an anesthesia information management system].

PubMed

Feng, Jing-yi; Chen, Hua; Zhu, Sheng-mei

2010-09-21

To study the design, implementation and clinical evaluation of an anesthesia information management system. To record, process and store peri-operative patient data automatically, all kinds of bedside monitoring equipments are connected into the system based on information integrating technology; after a statistical analysis of those patient data by data mining technology, patient status can be evaluated automatically based on risk prediction standard and decision support system, and then anesthetist could perform reasonable and safe clinical processes; with clinical processes electronically recorded, standard record tables could be generated, and clinical workflow is optimized, as well. With the system, kinds of patient data could be collected, stored, analyzed and archived, kinds of anesthesia documents could be generated, and patient status could be evaluated to support clinic decision. The anesthesia information management system is useful for improving anesthesia quality, decreasing risk of patient and clinician, and aiding to provide clinical proof.

Shared Decision Making Interventions: Theoretical and Empirical Evidence with Implications for Health Literacy.

PubMed

Stacey, Dawn; Hill, Sophie; McCaffery, Kirsten; Boland, Laura; Lewis, Krystina B; Horvat, Lidia

2017-01-01

Basic health literacy is required for making health decisions. The aim of this chapter is to discuss the use of shared decision making interventions for supporting patient involvement in making health decisions. The chapter provides a definition of shared decision making and discusses the link between shared decision making and the three levels of health literacy: functional, communicative/interactive, and critical. The Interprofessional Shared Decision Making Model is used to identify the various players involved: the patient, the family/surrogate/significant others, decision coach, and health care professionals. When patients are involved in shared decision making, they have better health outcomes, better healthcare experiences, and likely lower costs. Yet, their degree of involvement is influenced by their level of health literacy. Interventions to facilitate shared decision making are patient decision aids, decision coaching, and question prompt lists. Patient decision aids have been shown to improve knowledge, accurate risk perceptions, and chosen options congruent with patients' values. Decision coaching improves knowledge and patient satisfaction. Question prompts also improve satisfaction. When shared decision making interventions have been evaluated with patients presumed to have lower health literacy, they appeared to be more beneficial to disadvantaged groups compared to those with higher literacy or better socioeconomic status. However, special attention needs to be applied when designing these interventions for populations with lower literacy. Two case exemplars are provided to illustrate the design and choice of interventions to better support patients with varying levels of health literacy. Despite evidence indicating these interventions are effective for involving patients in shared decision making, few are used in routine clinical practice. To increase their uptake, implementation strategies need to overcome barriers interfering with their use. Implementation strategies include training health care professionals, adopting SDM interventions that target patients, such as patient decision aids, and monitor patients' decisional comfort using the SURE test. Integrating health literacy principles is important when developing interventions that facilitate shared decision making and essential to avoid inadvertently producing higher inequalities between patients with varying levels of health literacy.

Information Extraction and Dependency on Open Government Data (ogd) for Environmental Monitoring

NASA Astrophysics Data System (ADS)

Abdulmuttalib, Hussein

2016-06-01

Environmental monitoring practices support decision makers of different government / private institutions, besides environmentalists and planners among others. This support helps them act towards the sustainability of our environment, and also take efficient measures for protecting human beings in general, but it is difficult to explore useful information from 'OGD' and assure its quality for the purpose. On the other hand, Monitoring itself comprises detecting changes as happens, or within the mitigation period range, which means that any source of data, that is to be used for monitoring, should replicate the information related to the period of environmental monitoring, or otherwise it's considered almost useless or history. In this paper the assessment of information extraction and structuring from Open Government Data 'OGD', that can be useful to environmental monitoring is performed, looking into availability, usefulness to environmental monitoring of a certain type, checking its repetition period and dependences. The particular assessment is being performed on a small sample selected from OGD, bearing in mind the type of the environmental change monitored, such as the increase and concentrations of built up areas, and reduction of green areas, or monitoring the change of temperature in a specific area. The World Bank mentioned in its blog that Data is open if it satisfies both conditions of, being technically open, and legally open. The use of Open Data thus, is regulated by published terms of use, or an agreement which implies some conditions without violating the above mentioned two conditions. Within the scope of the paper I wish to share the experience of using some OGD for supporting an environmental monitoring work, that is performed to mitigate the production of carbon dioxide, by regulating energy consumption, and by properly designing the test area's landscapes, thus using Geodesign tactics, meanwhile wish to add to the results achieved by many efforts to make OGD useful In General and specifically for Environmental Monitoring purposes.

PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data.

PubMed

Shaban-Nejad, Arash; Lavigne, Maxime; Okhmatovskaia, Anya; Buckeridge, David L

2017-01-01

Population health decision makers must consider complex relationships between multiple concepts measured with differential accuracy from heterogeneous data sources. Population health information systems are currently limited in their ability to integrate data and present a coherent portrait of population health. Consequentially, these systems can provide only basic support for decision makers. The Population Health Record (PopHR) is a semantic web application that automates the integration and extraction of massive amounts of heterogeneous data from multiple distributed sources (e.g., administrative data, clinical records, and survey responses) to support the measurement and monitoring of population health and health system performance for a defined population. The design of the PopHR draws on the theories of the determinants of health and evidence-based public health to harmonize and explicitly link information about a population with evidence about the epidemiology and control of chronic diseases. Organizing information in this manner and linking it explicitly to evidence is expected to improve decision making related to the planning, implementation, and evaluation of population health and health system interventions. In this paper, we describe the PopHR platform and discuss the architecture, design, key modules, and its implementation and use. © 2016 New York Academy of Sciences.

Design of a decision-support architecture for management of remotely monitored patients.

PubMed

Basilakis, Jim; Lovell, Nigel H; Redmond, Stephen J; Celler, Branko G

2010-09-01

Telehealth is the provision of health services at a distance. Typically, this occurs in unsupervised or remote environments, such as a patient's home. We describe one such telehealth system and the integration of extracted clinical measurement parameters with a decision-support system (DSS). An enterprise application-server framework, combined with a rules engine and statistical analysis tools, is used to analyze the acquired telehealth data, searching for trends and shifts in parameter values, as well as identifying individual measurements that exceed predetermined or adaptive thresholds. An overarching business process engine is used to manage the core DSS knowledge base and coordinate workflow outputs of the DSS. The primary role for such a DSS is to provide an effective means to reduce the data overload and to provide a means of health risk stratification to allow appropriate targeting of clinical resources to best manage the health of the patient. In this way, the system may ultimately influence changes in workflow by targeting scarce clinical resources to patients of most need. A single case study extracted from an initial pilot trial of the system, in patients with chronic obstructive pulmonary disease and chronic heart failure, will be reviewed to illustrate the potential benefit of integrating telehealth and decision support in the management of both acute and chronic disease.

Coupling sensing to crop models for closed-loop plant production in advanced life support systems

NASA Astrophysics Data System (ADS)

Cavazzoni, James; Ling, Peter P.

1999-01-01

We present a conceptual framework for coupling sensing to crop models for closed-loop analysis of plant production for NASA's program in advanced life support. Crop status may be monitored through non-destructive observations, while models may be independently applied to crop production planning and decision support. To achieve coupling, environmental variables and observations are linked to mode inputs and outputs, and monitoring results compared with model predictions of plant growth and development. The information thus provided may be useful in diagnosing problems with the plant growth system, or as a feedback to the model for evaluation of plant scheduling and potential yield. In this paper, we demonstrate this coupling using machine vision sensing of canopy height and top projected canopy area, and the CROPGRO crop growth model. Model simulations and scenarios are used for illustration. We also compare model predictions of the machine vision variables with data from soybean experiments conducted at New Jersey Agriculture Experiment Station Horticulture Greenhouse Facility, Rutgers University. Model simulations produce reasonable agreement with the available data, supporting our illustration.

Burn Resuscitation Decision Support System (BRDSS)

DTIC Science & Technology

2014-11-01

agreement was to package the software into a mobile device (the BRDSS-M, trade name Burn Navigator™) with substantial input from caregivers at the USAISR...combat casualties with >30% TBSA burns developed abdominal compartment syndrome (ACS) and perished.2 Between January 2006 and June 2007, after the...or even an open-loop system, could integrate the urine output monitor and infusion pump and free up the caregiver from manual data entry tasks to

Parental influences on adolescent sexual behaviors.

PubMed

Rupp, Richard; Rosenthal, Susan L

2007-12-01

Parents play a significant role in the sexual development and behaviors of their children. Parental monitoring and supervision are important avenues for keeping adolescents from risky situations and activities while the teen develops responsible decision-making skills. A supportive relationship between the parent and adolescent is important for enhancing communication and supervision. In this article we discuss programs that were designed to improve parenting skills to decrease adolescent sexual risk behaviors.

Preparedness for radiological emergency situations in Austria.

PubMed

Ditto, Manfred

2012-02-01

This article presents the Austrian system of emergency preparedness for nuclear and radiological emergency situations. It demonstrates, in particular, the legal basis, the roles and competencies of the competent authorities, international and bilateral conventions on early notification of nuclear accidents, the Austrian emergency plans, the Austrian radiation monitoring system, the operated prognosis and decision support systems and the results of an estimation of possible impacts of nuclear power plant disasters on Austria.

The Mediterranean Decision Support System for Marine Safety dedicated to oil slicks predictions

NASA Astrophysics Data System (ADS)

Zodiatis, G.; De Dominicis, M.; Perivoliotis, L.; Radhakrishnan, H.; Georgoudis, E.; Sotillo, M.; Lardner, R. W.; Krokos, G.; Bruciaferri, D.; Clementi, E.; Guarnieri, A.; Ribotti, A.; Drago, A.; Bourma, E.; Padorno, E.; Daniel, P.; Gonzalez, G.; Chazot, C.; Gouriou, V.; Kremer, X.; Sofianos, S.; Tintore, J.; Garreau, P.; Pinardi, N.; Coppini, G.; Lecci, R.; Pisano, A.; Sorgente, R.; Fazioli, L.; Soloviev, D.; Stylianou, S.; Nikolaidis, A.; Panayidou, X.; Karaolia, A.; Gauci, A.; Marcati, A.; Caiazzo, L.; Mancini, M.

2016-11-01

In the Mediterranean sea the risk from oil spill pollution is high due to the heavy traffic of merchant vessels for transporting oil and gas, especially after the recent enlargement of the Suez canal and to the increasing coastal and offshore installations related to the oil industry in general. The basic response to major oil spills includes different measures and equipment. However, in order to strengthen the maritime safety related to oil spill pollution in the Mediterranean and to assist the response agencies, a multi-model oil spill prediction service has been set up, known as MEDESS-4MS (Mediterranean Decision Support System for Marine Safety). The concept behind the MEDESS-4MS service is the integration of the existing national ocean forecasting systems in the region with the Copernicus Marine Environmental Monitoring Service (CMEMS) and their interconnection, through a dedicated network data repository, facilitating access to all these data and to the data from the oil spill monitoring platforms, including the satellite data ones, with the well established oil spill models in the region. The MEDESS-4MS offer a range of service scenarios, multi-model data access and interactive capabilities to suite the needs of REMPEC (Regional Marine Pollution Emergency Response Centre for the Mediterranean Sea) and EMSA-CSN (European Maritime Safety Agency-CleanseaNet).

The Development of a Remote Sensor System and Decision Support Systems Architecture to Monitor Resistance Development in Transgenic Crops

NASA Technical Reports Server (NTRS)

Cacas, Joseph; Glaser, John; Copenhaver, Kenneth; May, George; Stephens, Karen

2008-01-01

The United States Environmental Protection Agency (EPA) has declared that "significant benefits accrue to growers, the public, and the environment" from the use of transgenic pesticidal crops due to reductions in pesticide usage for crop pest management. Large increases in the global use of transgenic pesticidal crops has reduced the amounts of broad spectrum pesticides used to manage pest populations, improved yield and reduced the environmental impact of crop management. A significant threat to the continued use of this technology is the evolution of resistance in insect pest populations to the insecticidal Bt toxins expressed by the plants. Management of transgenic pesticidal crops with an emphasis on conservation of Bt toxicity in field populations of insect pests is important to the future of sustainable agriculture. A vital component of this transgenic pesticidal crop management is establishing the proof of concept basic understanding, situational awareness, and monitoring and decision support system tools for more than 133650 square kilometers (33 million acres) of bio-engineered corn and cotton for development of insect resistance . Early and recent joint NASA, US EPA and ITD remote imagery flights and ground based field experiments have provided very promising research results that will potentially address future requirements for crop management capabilities.

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

NASA Astrophysics Data System (ADS)

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

2009-05-01

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

A decision tool for selecting trench cap designs

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

Paige, G.B.; Stone, J.J.; Lane, L.J.

1995-12-31

A computer based prototype decision support system (PDSS) is being developed to assist the risk manager in selecting an appropriate trench cap design for waste disposal sites. The selection of the {open_quote}best{close_quote} design among feasible alternatives requires consideration of multiple and often conflicting objectives. The methodology used in the selection process consists of: selecting and parameterizing decision variables using data, simulation models, or expert opinion; selecting feasible trench cap design alternatives; ordering the decision variables and ranking the design alternatives. The decision model is based on multi-objective decision theory and uses a unique approach to order the decision variables andmore » rank the design alternatives. Trench cap designs are evaluated based on federal regulations, hydrologic performance, cover stability and cost. Four trench cap designs, which were monitored for a four year period at Hill Air Force Base in Utah, are used to demonstrate the application of the PDSS and evaluate the results of the decision model. The results of the PDSS, using both data and simulations, illustrate the relative advantages of each of the cap designs and which cap is the {open_quotes}best{close_quotes} alternative for a given set of criteria and a particular importance order of those decision criteria.« less

Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing

USGS Publications Warehouse

Wylie, Bruce K.; Boyte, Stephen P.; Major, Donald J.

2012-01-01

Monitoring rangeland ecosystem dynamics, production, and performance is valuable for researchers and land managers. However, ecosystem monitoring studies can be difficult to interpret and apply appropriately if management decisions and disturbances are inseparable from the ecosystem's climate signal. This study separates seasonal weather influences from influences caused by disturbances and management decisions, making interannual time-series analysis more consistent and interpretable. We compared the actual ecosystem performance (AEP) of five rangeland vegetation types in the Owyhee Uplands for 9 yr to their expected ecosystem performance (EEP). Integrated growing season Normalized Difference Vegetation Index data for each of the nine growing seasons served as a proxy for annual AEP. Regression-tree models used long-term site potential, seasonal weather, and land cover data sets to generate annual EEP, an estimate of ecosystem performance incorporating annual weather variations. The difference between AEP and EEP provided a performance measure for each pixel in the study area. Ecosystem performance anomalies occurred when the ecosystem performed significantly better or worse than the model predicted. About 14% of the Owyhee Uplands showed a trend of significant underperformance or overperformance (P<0.10). Land managers can use results from weather-based rangeland ecosystem performance models to help support adaptive management strategies.

Predictive monitoring research: Summary of the PREMON system

NASA Technical Reports Server (NTRS)

Doyle, Richard J.; Sellers, Suzanne M.; Atkinson, David J.

1987-01-01

Traditional approaches to monitoring are proving inadequate in the face of two important issues: the dynamic adjustment of expectations about sensor values when the behavior of the device is too complex to enumerate beforehand, and the selective but effective interpretation of sensor readings when the number of sensors becomes overwhelming. This system addresses these issues by building an explicit model of a device and applying common-sense theories of physics to model causality in the device. The resulting causal simulation of the device supports planning decisions about how to efficiently yet reliably utilize a limited number of sensors to verify correct operation of the device.

Real World Data in Adaptive Biomedical Innovation: A Framework for Generating Evidence Fit for Decision-Making.

PubMed

Schneeweiss, S; Eichler, H-G; Garcia-Altes, A; Chinn, C; Eggimann, A-V; Garner, S; Goettsch, W; Lim, R; Löbker, W; Martin, D; Müller, T; Park, B J; Platt, R; Priddy, S; Ruhl, M; Spooner, A; Vannieuwenhuyse, B; Willke, R J

2016-12-01

Analyses of healthcare databases (claims, electronic health records [EHRs]) are useful supplements to clinical trials for generating evidence on the effectiveness, harm, use, and value of medical products in routine care. A constant stream of data from the routine operation of modern healthcare systems, which can be analyzed in rapid cycles, enables incremental evidence development to support accelerated and appropriate access to innovative medicines. Evidentiary needs by regulators, Health Technology Assessment, payers, clinicians, and patients after marketing authorization comprise (1) monitoring of medication performance in routine care, including the materialized effectiveness, harm, and value; (2) identifying new patient strata with added value or unacceptable harms; and (3) monitoring targeted utilization. Adaptive biomedical innovation (ABI) with rapid cycle database analytics is successfully enabled if evidence is meaningful, valid, expedited, and transparent. These principles will bring rigor and credibility to current efforts to increase research efficiency while upholding evidentiary standards required for effective decision-making in healthcare. © 2016 American Society for Clinical Pharmacology and Therapeutics.

Pervasive monitoring--an intelligent sensor pod approach for standardised measurement infrastructures.

PubMed

Resch, Bernd; Mittlboeck, Manfred; Lippautz, Michael

2010-01-01

Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a "digital skin for planet earth". The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making.

Assessing Climate-Induced Change in River Flow Using Satellite Remote Sensing and Process Modeling in High Mountain Asia

NASA Astrophysics Data System (ADS)

McDonald, K. C.

2017-12-01

Snow- and glacier-fed river systems originating from High Mountain Asia (HMA) support diverse ecosystems and provide the basis for food and energy production for more than a billion people living downstream. Climate-driven changes in the melting of snow and glaciers and in precipitation patterns are expected to significantly alter the flow of the rivers in the HMA region at various temporal scales, which in turn could heavily affect the socioeconomics of the region. Hence, climate change effects on seasonal and long-term hydrological conditions may have far reaching economic impact annually and over the century. We are developing a decision support tool utilizing integrated microwave remote sensing datasets, process modeling and economic models to inform water resource management decisions and ecosystem sustainability as related to the High Mountain Asia (HMA) region's response to climate change. The availability of consistent time-series microwave remote sensing datasets from Earth-orbiting scatterometers, radiometers and synthetic aperture radar (SAR) imagery provides the basis for the observational framework of this monitoring system. We discuss the assembly, processing and application of scatterometer and SAR data sets from the Advanced Scatterometer (ASCAT) and Sentinal-1 SARs, and the enlistment of these data to monitor seasonal melt and thaw status of glacier-dominated and surrounding regions. We present current status and future plans for this effort. Our team's study emphasizes processes and economic modeling within the Trishuli basin; our remote sensing analysis supports analyses across the HiMAT domain.

Use of an automated decision support tool optimizes clinicians' ability to interpret and appropriately respond to structured self-monitoring of blood glucose data.

PubMed

Rodbard, Helena W; Schnell, Oliver; Unger, Jeffrey; Rees, Christen; Amstutz, Linda; Parkin, Christopher G; Jelsovsky, Zhihong; Wegmann, Nathan; Axel-Schweitzer, Matthias; Wagner, Robin S

2012-04-01

We evaluated the impact of an automated decision support tool (DST) on clinicians' ability to identify glycemic abnormalities in structured self-monitoring of blood glucose (SMBG) data and then make appropriate therapeutic changes based on the glycemic patterns observed. In this prospective, randomized, controlled, multicenter study, 288 clinicians (39.6% family practice physicians, 37.9% general internal medicine physicians, and 22.6% nurse practitioners) were randomized to structured SMBG alone (STG; n = 72); structured SMBG with DST (DST; n = 72); structured SMBG with an educational DVD (DVD; n = 72); and structured SMBG with DST and the educational DVD (DST+DVD; n = 72). Clinicians analyzed 30 patient cases (type 2 diabetes), identified the primary abnormality, and selected the most appropriate therapy. A total of 222 clinicians completed all 30 patient cases with no major protocol deviations. Significantly more DST, DVD, and DST+DVD clinicians correctly identified the glycemic abnormality and selected the most appropriate therapeutic option compared with STG clinicians: 49, 51, and 55%, respectively, vs. 33% (all P < 0.0001) with no significant differences among DST, DVD, and DST+DVD clinicians. Use of structured SMBG, combined with the DST, the educational DVD, or both, enhances clinicians' ability to correctly identify significant glycemic patterns and make appropriate therapeutic decisions to address those patterns. Structured testing interventions using either the educational DVD or the DST are equally effective in improving data interpretation and utilization. The DST provides a viable alternative when comprehensive education is not feasible, and it may be integrated into medical practices with minimal training.

A prospective multiple case study of the impact of emerging scientific evidence on established colorectal cancer screening programs: a study protocol.

PubMed

Geddie, Hannah; Dobrow, Mark J; Hoch, Jeffrey S; Rabeneck, Linda

2012-06-01

Health-policy decision making is a complex and dynamic process, for which strong evidentiary support is required. This includes scientifically produced research, as well as information that relates to the context in which the decision takes place. Unlike scientific evidence, this "contextual evidence" is highly variable and often includes information that is not scientifically produced, drawn from sources such as political judgement, program management experience and knowledge, or public values. As the policy decision-making process is variable and difficult to evaluate, it is often unclear how this heterogeneous evidence is identified and incorporated into "evidence-based policy" decisions. Population-based colorectal cancer screening poses an ideal context in which to examine these issues. In Canada, colorectal cancer screening programs have been established in several provinces over the past five years, based on the fecal occult blood test (FOBT) or the fecal immunochemical test. However, as these programs develop, new scientific evidence for screening continues to emerge. Recently published randomized controlled trials suggest that the use of flexible sigmoidoscopy for population-based screening may pose a greater reduction in mortality than the FOBT. This raises the important question of how policy makers will address this evidence, given that screening programs are being established or are already in place. This study will examine these issues prospectively and will focus on how policy makers monitor emerging scientific evidence and how both scientific and contextual evidence are identified and applied for decisions about health system improvement. This study will employ a prospective multiple case study design, involving participants from Ontario, Alberta, Manitoba, Nova Scotia, and Quebec. In each province, data will be collected via document analysis and key informant interviews. Documents will include policy briefs, reports, meeting minutes, media releases, and correspondence. Interviews will be conducted in person with senior administrative leaders, government officials, screening experts, and high-level cancer system stakeholders. The proposed study comprises the third and final phase of an Emerging Team grant to address the challenges of health-policy decision making and colorectal cancer screening decisions in Canada. This study will contribute a unique prospective look at how policy makers address new, emerging scientific evidence in several different policy environments and at different stages of program planning and implementation. Findings will provide important insight into the various approaches that are or should be used to monitor emerging evidence, the relative importance of scientific versus contextual evidence for decision making, and the tools and processes that may be important to support challenging health-policy decisions.

Climate Change and Sea Level Rise: A Challenge to Science and Society

NASA Astrophysics Data System (ADS)

Plag, H.

2009-12-01

Society is challenged by the risk of an anticipated rise of coastal Local Sea Level (LSL) as a consequence of future global warming. Many low-lying and often subsiding and densely populated coastal areas are under risk of increased inundation, with potentially devastating consequences for the global economy, society, and environment. Faced with a trade-off between imposing the very high costs of coastal protection and adaptation upon today's national economies and leaving the costs of potential major disasters to future generations, governments and decision makers are in need of scientific support for the development of mitigation and adaptation strategies for the coastal zone. Low-frequency to secular changes in LSL are the result of many interacting Earth system processes. The complexity of the Earth system makes it difficult to predict Global Sea Level (GSL) rise and, even more so, LSL changes over the next 100 to 200 years. Humans have re-engineered the planet and changed major features of the Earth surface and the atmosphere, thus ruling out extrapolation of past and current changes into the future as a reasonable approach. The risk of rapid changes in ocean circulation and ice sheet mass balance introduces the possibility of unexpected changes. Therefore, science is challenged with understanding and constraining the full range of plausible future LSL trajectories and with providing useful support for informed decisions. In the face of largely unpredictable future sea level changes, monitoring of the relevant processes and development of a forecasting service on realistic time scales is crucial as decision support. Forecasting and "early warning" for LSL rise would have to aim at decadal time scales, giving coastal managers sufficient time to react if the onset of rapid changes would require an immediate response. The social, environmental, and economic risks associated with potentially large and rapid LSL changes are enormous. Therefore, in the light of the current uncertainties and the unpredictable nature of some of the forcing processes for LSL changes, the focus of scientific decision support may have to shift from projections of LSL trajectories on century time scales to the development of models and monitoring systems for a forecasting service on decadal time scales. The requirements for such a LSL forecasting service and the current obstacles will be discussed.

Three-Dimensional Model for Preservation and Restoration of Architectural Heritage

NASA Technical Reports Server (NTRS)

Marchis, Elena

2011-01-01

Thc aim of the research will be to create a model, three-dimensional mathematical. implementation. consultation and assistance to "large" restoration projects that will assist the structural analysis, allowing easier display of dynamic strain. analysis and lighting noise. It could also be a valuable tool for decision support. therefore. may simulate several possible scenarios for intervention, This model appears therefore an excellent support for recovering. ordering and monitoring information about materials and data (stage of restoration. photographs. sampling points. results of diagnostic tests, etc.) collected dynamically during the "life" of the cultural heritage. allowing to document its complete history

Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review

PubMed Central

Kim, Ben YB

2017-01-01

Background The emergence of smartphones and tablets featuring vastly advancing functionalities (eg, sensors, computing power, interactivity) has transformed the way mHealth interventions support chronic disease management for older adults. Baby boomers have begun to widely adopt smart devices and have expressed their desire to incorporate technologies into their chronic care. Although smart devices are actively used in research, little is known about the extent, characteristics, and range of smart device-based interventions. Objective We conducted a scoping review to (1) understand the nature, extent, and range of smart device-based research activities, (2) identify the limitations of the current research and knowledge gap, and (3) recommend future research directions. Methods We used the Arksey and O’Malley framework to conduct a scoping review. We identified relevant studies from MEDLINE, Embase, CINAHL, and Web of Science databases using search terms related to mobile health, chronic disease, and older adults. Selected studies used smart devices, sampled older adults, and were published in 2010 or after. The exclusion criteria were sole reliance on text messaging (short message service, SMS) or interactive voice response, validation of an electronic version of a questionnaire, postoperative monitoring, and evaluation of usability. We reviewed references. We charted quantitative data and analyzed qualitative studies using thematic synthesis. To collate and summarize the data, we used the chronic care model. Results A total of 51 articles met the eligibility criteria. Research activity increased steeply in 2014 (17/51, 33%) and preexperimental design predominated (16/50, 32%). Diabetes (16/46, 35%) and heart failure management (9/46, 20%) were most frequently studied. We identified diversity and heterogeneity in the collection of biometrics and patient-reported outcome measures within and between chronic diseases. Across studies, we found 8 self-management supporting strategies and 4 distinct communication channels for supporting the decision-making process. In particular, self-monitoring (38/40, 95%), automated feedback (15/40, 38%), and patient education (13/40, 38%) were commonly used as self-management support strategies. Of the 23 studies that implemented decision support strategies, clinical decision making was delegated to patients in 10 studies (43%). The impact on patient outcomes was consistent with studies that used cellular phones. Patients with heart failure and asthma reported improved quality of life. Qualitative analysis yielded 2 themes of facilitating technology adoption for older adults and 3 themes of barriers. Conclusions Limitations of current research included a lack of gerontological focus, dominance of preexperimental design, narrow research scope, inadequate support for participants, and insufficient evidence for clinical outcome. Recommendations for future research include generating evidence for smart device-based programs, using patient-generated data for advanced data mining techniques, validating patient decision support systems, and expanding mHealth practice through innovative technologies. PMID:28536089

Flooding During Drought: Learning from Stakeholder Engagement & Partner Coordination in the California-Nevada Drought Early Warning System (DEWS)

NASA Astrophysics Data System (ADS)

Sheffield, A. M.

2017-12-01

After more than 5 years of drought, extreme precipitation brought drought relief in California and Nevada and presents an opportunity to reflect upon lessons learned while planning for the future. NOAA's National Integrated Drought Information System (NIDIS) California-Nevada Drought Early Warning System (DEWS) in June 2017 convened a regional coordination workshop to provide a forum to discuss and build upon past drought efforts in the region and increase coordination, collaboration and information sharing across the region as a whole. Participants included federal, tribal, state, academic, and local partners who provided a post-mortem on the recent drought and impacts as well as recent innovations in drought monitoring, forecasts, and decision support tools in response to the historic drought. This presentation will highlight lessons learned from stakeholder outreach and engagement around flooding during drought, and pathways for moving forward coordination and collaboration in the region. Additional focus will be on the potential opportunities from examining California decision making calendars from this drought. Identified gaps and challenges will also be shared, such as the need to connect observations with social impacts, capacity building around available tools and resources, and future drought monitoring needs. Drought will continue to impact California and Nevada, and the CA-NV DEWS works to make climate and drought science readily available, easily understandable and usable for decision makers; and to improve the capacity of stakeholders to better monitor, forecast, plan for and cope with the impacts of drought.

DECISION-MAKING ALIGNED WITH RAPID-CYCLE EVALUATION IN HEALTH CARE.

PubMed

Schneeweiss, Sebastian; Shrank, William H; Ruhl, Michael; Maclure, Malcolm

2015-01-01

Availability of real-time electronic healthcare data provides new opportunities for rapid-cycle evaluation (RCE) of health technologies, including healthcare delivery and payment programs. We aim to align decision-making processes with stages of RCE to optimize the usefulness and impact of rapid results. Rational decisions about program adoption depend on program effect size in relation to externalities, including implementation cost, sustainability, and likelihood of broad adoption. Drawing on case studies and experience from drug safety monitoring, we examine how decision makers have used scientific evidence on complex interventions in the past. We clarify how RCE alters the nature of policy decisions; develop the RAPID framework for synchronizing decision-maker activities with stages of RCE; and provide guidelines on evidence thresholds for incremental decision-making. In contrast to traditional evaluations, RCE provides early evidence on effectiveness and facilitates a stepped approach to decision making in expectation of future regularly updated evidence. RCE allows for identification of trends in adjusted effect size. It supports adapting a program in midstream in response to interim findings, or adapting the evaluation strategy to identify true improvements earlier. The 5-step RAPID approach that utilizes the cumulating evidence of program effectiveness over time could increase policy-makers' confidence in expediting decisions. RCE enables a step-wise approach to HTA decision-making, based on gradually emerging evidence, reducing delays in decision-making processes after traditional one-time evaluations.

Application of Sensor Technology for the Efficient Positioningand Assembling of Ship Blocks

NASA Astrophysics Data System (ADS)

Lee, Sangdon; SeongbaeEun; Jung, Jai Jin; Song, Hacheol

2010-09-01

This paper proposes the application of sensor technology to assemble ship blocks efficiently. A sensor-based monitoring system is designed and implemented to improve shipbuilding productivity by reducing the labor cost for the adjustment of adequate positioning between ship blocks during pre-erection or erection stage. For the real-time remote monitoring of relative distances between two ship blocks, sensor nodes are applied to measure the distances between corresponding target points on the blocks. Highly precise positioning data can be transferred to a monitoring server via wireless network, and analyzed to support the decision making which needs to determine the next construction process; further adjustment or seam welding between the ship blocks. The developed system is expected to put to practical use, and increase the productivity during ship blocks assembly.

A proactive system for maritime environment monitoring.

PubMed

Moroni, Davide; Pieri, Gabriele; Tampucci, Marco; Salvetti, Ovidio

2016-01-30

The ability to remotely detect and monitor oil spills is becoming increasingly important due to the high demand of oil-based products. Indeed, shipping routes are becoming very crowded and the likelihood of oil slick occurrence is increasing. In this frame, a fully integrated remote sensing system can be a valuable monitoring tool. We propose an integrated and interoperable system able to monitor ship traffic and marine operators, using sensing capabilities from a variety of electronic sensors, along with geo-positioning tools, and through a communication infrastructure. Our system is capable of transferring heterogeneous data, freely and seamlessly, between different elements of the information system (and their users) in a consistent and usable form. The system also integrates a collection of decision support services providing proactive functionalities. Such services demonstrate the potentiality of the system in facilitating dynamic links among different data, models and actors, as indicated by the performed field tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

Challenges in building intelligent systems for space mission operations

NASA Technical Reports Server (NTRS)

Hartman, Wayne

1991-01-01

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

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

NASA Astrophysics Data System (ADS)

Jones, M.; Pitts, R.

2017-12-01

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

Balancing habitat delivery for breeding marsh birds and nonbreeding waterfowl: An integrated waterbird management and monitoring approach at Clarence Cannon National Wildlife Refuge, Missouri

USGS Publications Warehouse

Loges, Brian W.; Lyons, James E.; Tavernia, Brian G.

2017-08-23

The Clarence Cannon National Wildlife Refuge (CCNWR) in the Mississippi River flood plain of eastern Missouri provides high quality emergent marsh and moist-soil habitat benefitting both nesting marsh birds and migrating waterfowl. Staff of CCNWR manipulate water levels and vegetation in the 17 units of the CCNWR to provide conditions favorable to these two important guilds. Although both guilds include focal species at multiple planning levels and complement objectives to provide a diversity of wetland community types and water regimes, additional decision support is needed for choosing how much emergent marsh and moist-soil habitat should be provided through annual management actions.To develop decision guidance for balanced delivery of high-energy waterfowl habitat and breeding marsh bird habitat, two measureable management objectives were identified: nonbreeding Anas Linnaeus (dabbling duck) use-days and Rallus elegans (king rail) occupancy of managed units. Three different composite management actions were identified to achieve these objectives. Each composite management action is a unique combination of growing season water regime and soil disturbance. The three composite management actions are intense moist-soil management (moist-soil), intermediate moist-soil (intermediate), and perennial management, which idles soils disturbance (perennial). The two management objectives and three management options were used in a multi-criteria decision analysis to indicate resource allocations and inform annual decision making. Outcomes of the composite management actions were predicted in two ways and multi-criteria decision analysis was used with each set of predictions. First, outcomes were predicted using expert-elicitation techniques and a panel of subject matter experts. Second, empirical data from the Integrated Waterbird Management and Monitoring Initiative collected between 2010 and 2013 were used; where data were lacking, expert judgment was used. Also, a Bayesian decision model was developed that can be updated with monitoring data in an adaptive management framework.Optimal resource allocations were identified in the form of portfolios of composite management actions for the 17 units in the framework. A constrained optimization (linear programming) was used to maximize an objective function that was based on the sum of dabbling duck and king rail utility. The constraints, which included management costs and a minimum energetic carrying capacity (total moist-soil acres), were applied to balance habitat delivery for dabbling ducks and king rails. Also, the framework was constrained in some cases to apply certain management actions of interest to certain management units; these constraints allowed for a variety of hypothetical Habitat Management Plans, including one based on output from a hydrogeomorphic study of the refuge. The decision analysis thus created numerous refuge-wide scenarios, each representing a unique mix of options (one for each of 17 units) and associated benefits (i.e., outcomes with respect to two management objectives).Prepared in collaboration with the U.S. Fish and Wildlife Service, the decision framework presented here is designed as a decision-aiding tool for CCNWR managers who ultimately make difficult decisions each year with multiple objectives, multiple management units, and the complexity of natural systems. The framework also provides a way to document hypotheses about how the managed system functions. Furthermore, the framework identifies specific monitoring needs and illustrates precisely how monitoring data will be used for decision-aiding and adaptive management.

The potential of cellular technology to mediate social networks for support of chronic disease self-management.

PubMed

Roblin, Douglas W

2011-01-01

Productive interactions among patients, friends/family, and health care providers, as outlined by the Chronic Care Model, are important for promoting adherence to recommended care and good health outcomes among adults with a chronic illness. Characteristics of these interactions--active participation, collaboration, and data sharing among constituents--are the same as those of social networks organized around Web 2.0 principles and technology. Thus, the Web 2.0 framework can be used to configure social networks without the inherent spatiotemporal constraints of face-to-face interactions that remain prevalent in health care delivery. In this article, the author outlines various design principles and decisions for a pilot study in which cellular technology was used to mediate interactions between adults with Type 2 diabetes and supporters (i.e., family members or friends selected by the patients who agree provide support) to motivate regular self-monitoring of blood glucose (among the diabetes participants). Participants generally found the network to be relatively easy to use. Some diabetes patients reported improved attention to self-monitoring; and, patient-selected supporters indicated improvements in emotional and instrumental support that should benefit diabetes patients' lifestyle and health.

The application of unmanned aerial vehicle remote sensing for monitoring secondary geological disasters after earthquakes

NASA Astrophysics Data System (ADS)

Lei, Tianjie; Zhang, Yazhen; Wang, Xingyong; Fu, Jun'e.; Li, Lin; Pang, Zhiguo; Zhang, Xiaolei; Kan, Guangyuan

2017-07-01

Remote sensing system fitted on Unmanned Aerial Vehicle (UAV) can obtain clear images and high-resolution aerial photographs. It has advantages of strong real-time, flexibility and convenience, free from influence of external environment, low cost, low-flying under clouds and ability to work full-time. When an earthquake happened, it could go deep into the places safely and reliably which human staff can hardly approach, such as secondary geological disasters hit areas. The system can be timely precise in response to secondary geological disasters monitoring by a way of obtaining first-hand information as quickly as possible, producing a unique emergency response capacity to provide a scientific basis for overall decision-making processes. It can greatly enhance the capability of on-site disaster emergency working team in data collection and transmission. The great advantages of UAV remote sensing system played an irreplaceable role in monitoring secondary geological disaster dynamics and influences. Taking the landslides and barrier lakes for example, the paper explored the basic application and process of UAV remote sensing in the disaster emergency relief. UAV high-resolution remote sensing images had been exploited to estimate the situation of disaster-hit areas and monitor secondary geological disasters rapidly, systematically and continuously. Furthermore, a rapid quantitative assessment on the distribution and size of landslides and barrier lakes was carried out. Monitoring results could support relevant government departments and rescue teams, providing detailed and reliable scientific evidence for disaster relief and decision-making.

Quality tracing in meat supply chains

PubMed Central

Mack, Miriam; Dittmer, Patrick; Veigt, Marius; Kus, Mehmet; Nehmiz, Ulfert; Kreyenschmidt, Judith

2014-01-01

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production. PMID:24797136

Quality tracing in meat supply chains.

PubMed

Mack, Miriam; Dittmer, Patrick; Veigt, Marius; Kus, Mehmet; Nehmiz, Ulfert; Kreyenschmidt, Judith

2014-06-13

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

The Invasive Species Forecasting System

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Research and Development initiative of Satellite Technology Application for Environmental Issues in Asia Region

NASA Astrophysics Data System (ADS)

Hamamoto, K.; Kaneko, Y.; Sobue, S.; Oyoshi, K.

2016-12-01

Climate change and human activities are directly or indirectly influence the acceleration of environmental problems and natural hazards such as forest fires, drought and floods in the Asia-Pacific countries. Satellite technology has become one of the key information sources in assessment, monitoring and mitigation of these hazards and related phenomenon. However, there are still gaps between science and application of space technology in practical usage. Asia-Pacific Regional Space Agency Forum (APRSAF) recommended to initiate the Space Applications for Environment (SAFE) proposal providing opportunity to potential user agencies in the Asia Pacific region to develop prototype applications of space technology for number of key issues including forest resources management, coastal monitoring and management, agriculture and food security, water resource management and development user-friendly tools for application of space technology. The main activity of SAFE is SAFE prototyping. SAFE prototyping is a demonstration for end users and decision makers to apply space technology applications for solving environmental issues in Asia-Pacific region. By utilizing space technology and getting technical support by experts, prototype executers can develop the application system, which could support decision making activities. SAFE holds a workshop once a year. In the workshop, new prototypes are approved and the progress of on-going prototypes are confirmed. Every prototype is limited for two years period and all activities are operated by volunteer manner. As of 2016, 20 prototypes are completed and 6 prototypes are on-going. Some of the completed prototypes, for example drought monitoring in Indonesia were applied to operational use by a local official organization.

Model My Watershed: A high-performance cloud application for public engagement, watershed modeling and conservation decision support

NASA Astrophysics Data System (ADS)

Aufdenkampe, A. K.; Tarboton, D. G.; Horsburgh, J. S.; Mayorga, E.; McFarland, M.; Robbins, A.; Haag, S.; Shokoufandeh, A.; Evans, B. M.; Arscott, D. B.

2017-12-01

The Model My Watershed Web app (https://app.wikiwatershed.org/) and the BiG-CZ Data Portal (http://portal.bigcz.org/) and are web applications that share a common codebase and a common goal to deliver high-performance discovery, visualization and analysis of geospatial data in an intuitive user interface in web browser. Model My Watershed (MMW) was designed as a decision support system for watershed conservation implementation. BiG CZ Data Portal was designed to provide context and background data for research sites. Users begin by creating an Area of Interest, via an automated watershed delineation tool, a free draw tool, selection of a predefined area such as a county or USGS Hydrological Unit (HUC), or uploading a custom polygon. Both Web apps visualize and provide summary statistics of land use, soil groups, streams, climate and other geospatial information. MMW then allows users to run a watershed model to simulate different scenarios of human impacts on stormwater runoff and water-quality. BiG CZ Data Portal allows users to search for scientific and monitoring data within the Area of Interest, which also serves as a prototype for the upcoming Monitor My Watershed web app. Both systems integrate with CUAHSI cyberinfrastructure, including visualizing observational data from CUAHSI Water Data Center and storing user data via CUAHSI HydroShare. Both systems also integrate with the new EnviroDIY Water Quality Data Portal (http://data.envirodiy.org/), a system for crowd-sourcing environmental monitoring data using open-source sensor stations (http://envirodiy.org/mayfly/) and based on the Observations Data Model v2.

Monitoring in the nearshore: A process for making reasoned decisions

USGS Publications Warehouse

Bodkin, James L.; Dean, T.A.

2003-01-01

Over the past several years, a conceptual framework for the GEM nearshore monitoring program has been developed through a series of workshops. However, details of the proposed monitoring program, e.g. what to sample, where to sample, when to sample and at how many sites, have yet to be determined. In FY 03 we were funded under Project 03687 to outline a process whereby specific alternatives to monitoring are developed and presented to the EVOS Trustee Council for consideration. As part of this process, two key elements are required before reasoned decisions can be made. These are: 1) a comprehensive historical perspective of locations and types of past studies conducted in the nearshore marine communities within Gulf of Alaska, and 2) estimates of costs for each element of a proposed monitoring program. We have developed a GIS database that details available information from past studies of selected nearshore habitats and species in the Gulf of Alaska and provide a visual means of selecting sites based (in part) on the locations for which historical data of interest are available. We also provide cost estimates for specific monitoring plan alternatives and outline several alternative plans that can be accomplished within reasonable budgetary constraints. The products that we will provide are: 1) A GIS database and maps showing the location and types of information available from the nearshore in the Gulf of Alaska; 2) A list of several specific monitoring alternatives that can be conducted within reasonable budgetary constraints; and 3) Cost estimates for proposed tasks to be conducted as part of the nearshore program. Because data compilation and management will not be completed until late in FY03 we are requesting support for close-out of this project in FY 04.

An equity dashboard to monitor vaccination coverage.

PubMed

Arsenault, Catherine; Harper, Sam; Nandi, Arijit; Rodríguez, José M Mendoza; Hansen, Peter M; Johri, Mira

2017-02-01

Equity monitoring is a priority for Gavi, the Vaccine Alliance, and for those implementing The 2030 agenda for sustainable development . For its new phase of operations, Gavi reassessed its approach to monitoring equity in vaccination coverage. To help inform this effort, we made a systematic analysis of inequalities in vaccination coverage across 45 Gavi-supported countries and compared results from different measurement approaches. Based on our findings, we formulated recommendations for Gavi's equity monitoring approach. The approach involved defining the vulnerable populations, choosing appropriate measures to quantify inequalities, and defining equity benchmarks that reflect the ambitions of the sustainable development agenda. In this article, we explain the rationale for the recommendations and for the development of an improved equity monitoring tool. Gavi's previous approach to measuring equity was the difference in vaccination coverage between a country's richest and poorest wealth quintiles. In addition to the wealth index, we recommend monitoring other dimensions of vulnerability (maternal education, place of residence, child sex and the multidimensional poverty index). For dimensions with multiple subgroups, measures of inequality that consider information on all subgroups should be used. We also recommend that both absolute and relative measures of inequality be tracked over time. Finally, we propose that equity benchmarks target complete elimination of inequalities. To facilitate equity monitoring, we recommend the use of a data display tool - the equity dashboard - to support decision-making in the sustainable development period. We highlight its key advantages using data from Côte d'Ivoire and Haiti.

An equity dashboard to monitor vaccination coverage

PubMed Central

Harper, Sam; Nandi, Arijit; Rodríguez, José M Mendoza; Hansen, Peter M; Johri, Mira

2017-01-01

Abstract Equity monitoring is a priority for Gavi, the Vaccine Alliance, and for those implementing The 2030 agenda for sustainable development. For its new phase of operations, Gavi reassessed its approach to monitoring equity in vaccination coverage. To help inform this effort, we made a systematic analysis of inequalities in vaccination coverage across 45 Gavi-supported countries and compared results from different measurement approaches. Based on our findings, we formulated recommendations for Gavi’s equity monitoring approach. The approach involved defining the vulnerable populations, choosing appropriate measures to quantify inequalities, and defining equity benchmarks that reflect the ambitions of the sustainable development agenda. In this article, we explain the rationale for the recommendations and for the development of an improved equity monitoring tool. Gavi’s previous approach to measuring equity was the difference in vaccination coverage between a country’s richest and poorest wealth quintiles. In addition to the wealth index, we recommend monitoring other dimensions of vulnerability (maternal education, place of residence, child sex and the multidimensional poverty index). For dimensions with multiple subgroups, measures of inequality that consider information on all subgroups should be used. We also recommend that both absolute and relative measures of inequality be tracked over time. Finally, we propose that equity benchmarks target complete elimination of inequalities. To facilitate equity monitoring, we recommend the use of a data display tool – the equity dashboard – to support decision-making in the sustainable development period. We highlight its key advantages using data from Côte d’Ivoire and Haiti. PMID:28250513

Detention of American Citizens as Enemy Combatants

DTIC Science & Technology

2005-03-31

Padilla a limited right to meet with his attorney under government monitoring and appealed the decision to the Supreme Court, which heard the case on...an individual is an enemy combatant is conclusive, so long as it is supported by some evidence.182 In the first interlocutory appeal , the Fourth...a hearing to determine the status of those captured during hostilities. See CRS Report RL31367. 186 See Government’s Motion for Interlocutory Appeal

Estimating Logistics Burdens in Support of Acquisition Decisions

DTIC Science & Technology

2012-04-30

Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law , no person shall be subject to a penalty...CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING...ORGANIZATION NAME( S ) AND ADDRESS(ES) Naval Postgraduate School,Monterey,CA,93943 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING

Monitoring Score Change Patterns to Support "TOEIC"® Listening and Reading Test Quality. Research Report. ETS RR-17-54

ERIC Educational Resources Information Center

Wei, Youhua; Low, Albert

2017-01-01

In most large-scale programs of tests that aid in making high-stakes decisions, such as the "TOEIC"® family of products and service, it is not unusual for a significant portion of test takers to retake the test at multiple times.The study reported here used multilevel growth modeling to explore the score change patterns of nearly 20,000…

USGS Integration of New Science and Technology, Appendix A

USGS Publications Warehouse

Brey, Marybeth; Knights, Brent C.; Cupp, Aaron R.; Amberg, Jon J.; Chapman, Duane C.; Calfee, Robin D.; Duncker, James J.

2017-01-01

This product summarizes the USGS plans for integration of new science and technology into Asian Carp control efforts for 2017. This includes the 1) implementation and evaluation of new tactics and behavioral information for monitoring, surveillance, control and containment; 2) understanding behavior and reproduction of Asian carp in established and emerging populations to inform deterrent deployment, rapid response, and removal efforts; and 3) development and evaluation of databases, decision support tools and performance measures.

50 CFR 660.18 - Certification and decertification procedures for observers, catch monitors, catch monitor...

Code of Federal Regulations, 2010 CFR

2010-10-01

... designee) will designate a NMFS observer certification official who will make decisions for the Observer... of embezzlement, theft, forgery, bribery, falsification or destruction of records, making false... appeal pursuant to paragraph (c) of this section. (c) Appeals process—(1) Decisions. Decisions on appeals...

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

NASA Astrophysics Data System (ADS)

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

2003-09-01

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

Association of information satisfaction, psychological distress and monitoring coping style with post-decision regret following breast reconstruction.

PubMed

Sheehan, Joanne; Sherman, Kerry A; Lam, Thomas; Boyages, John

2007-04-01

Little is known of the psychosocial factors associated with decision regret in the context of breast reconstruction following mastectomy for breast cancer treatment. Moreover, there is a paucity of theoretically-based research in the area of post-decision regret. Adopting the theoretical framework of the Monitoring Process Model (Cancer 1995;76(1):167-177), the current study assessed the role of information satisfaction, current psychological distress and the moderating effect of monitoring coping style to the experience of regret over the decision to undergo reconstructive surgery. Women (N=123) diagnosed with breast cancer who had undergone immediate or delayed breast reconstruction following mastectomy participated in the study. The majority of participants (52.8%, n=65) experienced no decision regret, 27.6% experienced mild regret and 19.5% moderate to strong regret. Bivariate analyses indicated that decision regret was associated with low satisfaction with preparatory information, depression, anxiety and stress. Multinominal logistic regression analysis showed, controlling for mood state and time since last reconstructive procedure, that lower satisfaction with information and increased depression were associated with increased likelihood of experiencing regret. Monitoring coping style moderated the association between anxiety and regret (beta=-0.10, OR=0.91, p=0.01), whereby low monitors who were highly anxious had a greater likelihood of experiencing regret than highly anxious high monitors. Copyright (c) 2006 John Wiley & Sons, Ltd.

Monitoring as a partially observable decision problem

Treesearch

Paul L. Fackler; Robert G. Haight

2014-01-01

Monitoring is an important and costly activity in resource man-agement problems such as containing invasive species, protectingendangered species, preventing soil erosion, and regulating con-tracts for environmental services. Recent studies have viewedoptimal monitoring as a Partially Observable Markov Decision Pro-cess (POMDP), which provides a framework for...

Overcoming barriers to cancer-helpline professionals providing decision support for callers: an implementation study.

PubMed

Stacey, Dawn; Chambers, Suzanne K; Jacobsen, Mary Jane; Dunn, Jeff

2008-11-01

To evaluate the effect of an intervention on healthcare professionals' perceptions of barriers influencing their provision of decision support for callers facing cancer-related decisions. A pre- and post-test study guided by the Ottawa Model of Research Use. Australian statewide cancer call center that provides public access to information and supportive cancer services. 34 nurses, psychologists, and other allied healthcare professionals at the cancer call center. Participants completed baseline measures and, subsequently, were exposed to an intervention that included a decision support tutorial, coaching protocol, and skill-building workshop. Strategies were implemented to address organizational barriers. Perceived barriers and facilitators influencing provision of decision support, decision support knowledge, quality of decision support provided to standardized callers, and call length. Postintervention participants felt more prepared, confident in providing decision support, and aware of decision support resources. They had a stronger belief that providing decision support was within their role. Participants significantly improved their knowledge and provided higher-quality decision support to standardized callers without changing call length. The implementation intervention overcame several identified barriers that influenced call center professionals when providing decision support. Nurses and other helpline professionals have the potential to provide decision support designed to help callers understand cancer information, clarify their values associated with their options, and reduce decisional conflict. However, they require targeted education and organizational interventions to reduce their perceived barriers to providing decision support.

Results from three years on the prairie - improving management through volunteer-collected data

NASA Astrophysics Data System (ADS)

Hadley, N.; Force, A.; Holsinger, K.

2017-12-01

Citizen science is a nascent and diversifying field with the ability to support wide-ranging outcomes from volunteer education and empowerment to data-driven decisions. Adventure Scientists is a nonprofit organization that focuses on the latter. We approach citizen science through a solutions-oriented lens, in which quality data can influence decisions leading to improved policy, land management and business practices. All our work is interdisciplinary, as we collaborate with partners in government, academia, industry and nonprofits to help fill their data collection needs. In addressing our partners' data needs, it is critical that we align any newfound knowledge with tangible outcomes. Therefore, our projects and partnerships incorporate concrete theories of change and involve the collaborations and relationships necessary to support decision-making. In this presentation, we will highlight Landmark, a landscape-scale project spanning 30,000 acres of North American prairie in Montana, to illustrate one example of a partnership that resulted in improved management from our volunteer-collected data. This was a multi-year citizen science project, where we assisted the American Prairie Reserve's effort to create the largest grasslands and wildlife protected area in the continental U.S. Our partners identified a need to better understand the extent and diversity of wildlife inhabiting and migrating through the space. To provide this enhanced understanding, we helped design and implement a program to collect key wildlife data on the prairie. We recruited, trained and managed specialized volunteers from the outdoor adventure community. Volunteers were responsible for collecting data year-round on animals moving through the landscape to support their management and protection. After three years of data collection and over 19,000 wildlife observations made while monitoring 29 species, the grasslands preserve is now moving forward with an expansive wildlife dataset to inform conservation action. We will share key insights from our experience as well as how the project established the foundation for our partner to institute key management actions and monitor progress on restoration goals.

Global Drought Services: Collaborations Toward an Information System for Early Warning

NASA Astrophysics Data System (ADS)

Hayes, M. J.; Pulwarty, R. S.; Svoboda, M.

2014-12-01

Drought is a hazard that lends itself well to diligent, sustained monitoring and early warning. However, unlike most hazards, the fact that droughts typically evolve slowly, can last for months or years and cover vast areas spanning multiple political boundaries/jurisdictions and economic sectors can make it a daunting task to monitor, develop plans for, and identify appropriate, proactive mitigation strategies. The National Drought Mitigation Center (NDMC) and National Integrated Drought Information System (NIDIS) have been working together to reduce societal vulnerability to drought by helping decision makers at all levels to: 1) implement drought early warning/forecasting and decision support systems; 2) support and advocate for better collection of, and understanding of drought impacts; and 3) increase long-term resilience to drought through proactive planning. The NDMC and NIDIS risk management approach has been the basis from which many partners around the world are developing a collaboration and coordination nexus with an ultimate goal of building comprehensive global drought early warning information systems (GDEWIS). The core emphasis of this model is on developing and applying useful and usable information that can be integrated and transferred freely to other regions around the globe. The High-Level Ministerial Declaration on Drought, the Integrated Drought Management Programme (IDMP) co-led by the WMO and the Global Water Partnership (GWP), and the Global Framework for Climate Services are drawing extensively from the integrated NDMC-NIDIS risk management framework. This presentation will describe, in detail, the various drought resources, tools, services, and collaborations already being provided and undertaken at the national and regional scales by the NDMC, NIDIS, and their partners. The presentation will be forward-looking, identifying improvements in existing and proposed mechanisms to help strengthen national and international drought early warning information systems to support preparedness and adaptation decisions in a changing climate.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Gold coast seaway smartrelease decision support system: optimising recycled water release in a sub tropical estuarine environment.

PubMed

Stuart, G; Hollingsworth, A; Thomsen, F; Szylkarski, S; Khan, S; Tomlinson, R; Kirkpatrick, S; Catterall, K; Capati, B

2009-01-01

Gold Coast Water is responsible for the management of the water, recycled water and wastewater assets of the City of the Gold Coast on Australia's east coast. Excess treated recycled water is released at the Gold Coast Seaway, a man-made channel connecting the Broadwater Estuary with the Pacific Ocean, on an outgoing tide in order for the recycled water to be dispersed before the tide changes and re-enters the Broadwater estuary. Rapid population growth has placed increasing demands on the city's recycled water release system and an investigation of the capacity of the Broadwater to assimilate a greater volume of recycled water over a longer release period was undertaken in 2007. As an outcome, Gold Coast Water was granted an extension of the existing release licence from 10.5 hours per day to 13.3 hours per day from the Coombabah wastewater treatment plant (WWTP). The Seaway SmartRelease Project has been designed to optimise the release of the recycled water from the Coombabah WWTP in order to minimise the impact to the receiving estuarine water quality and maximise the cost efficiency of pumping. In order achieve this; an optimisation study that involves intensive hydrodynamic and water quality monitoring, numerical modelling and a web-based decision support system is underway. An intensive monitoring campaign provided information on water levels, currents, winds, waves, nutrients and bacterial levels within the Broadwater. This data was then used to calibrate and verify numerical models using the MIKE by DHI suite of software. The Decision Support System will then collect continually measured data such as water levels, interact with the WWTP SCADA system, run the numerical models and provide the optimal time window to release the required amount of recycled water from the WWTP within the licence specifications.

Improved monitoring framework for local planning in the water, sanitation and hygiene sector: From data to decision-making.

PubMed

Garriga, Ricard Giné; de Palencia, Alejandro Jiménez Fdez; Foguet, Agustí Pérez

2015-09-01

Today, a vast proportion of people still lack a simple pit latrine and a source of safe drinking water. To help end this appalling state of affairs, there is a pressing need to provide policymakers with evidences which may be the basis of effective planning, targeting and prioritization. Two major challenges often hinder this process: i) lack of reliable data to identify which areas are most in need; and ii) inadequate instruments for decision-making support. In tackling previous shortcomings, this paper proposes a monitoring framework to compile, analyze, interpret and disseminate water, sanitation and hygiene information. In an era of decentralization, where decision-making moves to local governments, we apply such framework at the local level. The ultimate goal is to develop appropriate tools for decentralized planning support. To this end, the study first implements a methodology for primary data collection, which combines the household and the waterpoint as information sources. In doing so, we provide a complete picture of the context in which domestic WASH services are delivered. Second, the collected data are analyzed to underline the emerging development challenges. The use of simple planning indicators serves as the basis to i) reveal which areas require policy attention, and to ii) identify the neediest. Third, a classification process is proposed to prioritize among various populations. Three different case studies from East and Southern African countries are presented. Results indicate that accurate and comprehensive data, if adequately exploited through simple instruments, may be the basis of effective targeting and prioritization, which are central to sector planning. The application of the proposed framework in the real world, however, is to a certain extent elusive; and we point out to conclude two specific challenges that remain unaddressed, namely the upgrade of existing decision-making processes to enhance transparency and inclusiveness, and the development of data updating mechanisms. Copyright © 2015 Elsevier B.V. All rights reserved.

An adaptive approach to invasive plant management on U.S. Fish and Wildlife Service-owned native prairies in the Prairie Pothole Region: decision support under uncertainity

USGS Publications Warehouse

Gannon, Jill J.; Moore, Clinton T.; Shaffer, Terry L.; Flanders-Wanner, Bridgette

2011-01-01

Much of the native prairie managed by the U.S. Fish and Wildlife Service (Service) in the Prairie Pothole Region (PPR) is extensively invaded by the introduced cool-season grasses smooth brome (Bromus inermis) and Kentucky bluegrass (Poa pratensis). The central challenge to managers is selecting appropriate management actions in the face of biological and environmental uncertainties. We describe the technical components of a USGS management project, and explain how the components integrate and inform each other, how data feedback from individual cooperators serves to reduce uncertainty across the whole region, and how a successful adaptive management project is coordinated and maintained on a large scale. In partnership with the Service, the U.S. Geological Survey is developing an adaptive decision support framework to assist managers in selecting management actions under uncertainty and maximizing learning from management outcomes. The framework is built around practical constraints faced by refuge managers and includes identification of the management objective and strategies, analysis of uncertainty and construction of competing decision models, monitoring, and mechanisms for model feedback and decision selection. Nineteen Service field stations, spanning four states of the PPR, are participating in the project. They share a common management objective, available management strategies, and biological uncertainties. While the scope is broad, the project interfaces with individual land managers who provide refuge-specific information and receive updated decision guidance that incorporates understanding gained from the collective experience of all cooperators.

INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING

PubMed Central

Kibira, Deogratias; Hatim, Qais; Kumara, Soundar; Shao, Guodong

2017-01-01

Modern manufacturing systems are installed with smart devices such as sensors that monitor system performance and collect data to manage uncertainties in their operations. However, multiple parameters and variables affect system performance, making it impossible for a human to make informed decisions without systematic methodologies and tools. Further, the large volume and variety of streaming data collected is beyond simulation analysis alone. Simulation models are run with well-prepared data. Novel approaches, combining different methods, are needed to use this data for making guided decisions. This paper proposes a methodology whereby parameters that most affect system performance are extracted from the data using data analytics methods. These parameters are used to develop scenarios for simulation inputs; system optimizations are performed on simulation data outputs. A case study of a machine shop demonstrates the proposed methodology. This paper also reviews candidate standards for data collection, simulation, and systems interfaces. PMID:28690363

Outlier Detection for Patient Monitoring and Alerting

PubMed Central

Hauskrecht, Milos; Batal, Iyad; Valko, Michal; Visweswaran, Shyam; Cooper, Gregory F.; Clermont, Gilles

2012-01-01

We develop and evaluate a data-driven approach for detecting unusual (anomalous) patient-management decisions using past patient cases stored in electronic health records (EHRs). Our hypothesis is that a patient-management decision that is unusual with respect to past patient care may be due to an error and that it is worthwhile to generate an alert if such a decision is encountered. We evaluate this hypothesis using data obtained from EHRs of 4,486 post-cardiac surgical patients and a subset of 222 alerts generated from the data. We base the evaluation on the opinions of a panel of experts. The results of the study support our hypothesis that the outlier-based alerting can lead to promising true alert rates. We observed true alert rates that ranged from 25% to 66% for a variety of patient-management actions, with 66% corresponding to the strongest outliers. PMID:22944172

Treatment decision making and adjustment to breast cancer: a longitudinal study.

PubMed

Stanton, A L; Estes, M A; Estes, N C; Cameron, C L; Danoff-Burg, S; Irving, L M

1998-04-01

This study monitored women (N = 76) with breast cancer from diagnosis through 1 year, and tested constructs from subjective expected utility theory with regard to their ability to predict patients' choice of surgical treatment as well as psychological distress and well-being over time. Women's positive expectancies for the consequences of treatment generally were maintained in favorable perceptions of outcome in several realms (i.e., physician agreement, likelihood of cancer cure or recurrence, self-evaluation, likelihood of additional treatment, partner support for option, attractiveness to partner). Assessed before the surgical decision-making appointment, women's expectancies for consequences of the treatment options, along with age, correctly classified 94% of the sample with regard to election of mastectomy versus breast-conserving procedures. Calculated from the point of decision making to 3 months later, expectancy disconfirmations and value discrepancies concerning particular treatment consequences predicted psychological adjustment 3 months and 1 year after diagnosis.

Decision-Making Accuracy of CBM Progress-Monitoring Data

ERIC Educational Resources Information Center

Hintze, John M.; Wells, Craig S.; Marcotte, Amanda M.; Solomon, Benjamin G.

2018-01-01

This study examined the diagnostic accuracy associated with decision making as is typically conducted with curriculum-based measurement (CBM) approaches to progress monitoring. Using previously published estimates of the standard errors of estimate associated with CBM, 20,000 progress-monitoring data sets were simulated to model student reading…

Monitoring in the context of structured decision-making and adaptive management

USGS Publications Warehouse

Lyons, J.E.; Runge, M.C.; Laskowski, H.P.; Kendall, W.L.

2008-01-01

In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play >3 roles. First, it is important for state-dependent decision-making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large-scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water-level manipulations in managed wetlands. Key uncertainties are related to the potential trade-offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill >1 of the roles identified above. We used observations from our monitoring to improve state-dependent decisions to control undesired plants, to evaluate management performance relative to shallow-water habitat objectives, and to evaluate potential trade-offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring programs that are used for decision-making, not comprehensive studies that elucidate all manner of ecological relationships.

Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Data and Tools for Dynamic Management and Decision Support

NASA Technical Reports Server (NTRS)

Humphries, G. R. W.; Naveen, R.; Schwaller, M.; Che-Castaldo, C.; McDowall, P.; Schrimpf, M.; Schrimpf, Michael; Lynch, H. J.

2017-01-01

The Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD) is a web-based, open access, decision-support tool designed to assist scientists, non-governmental organizations and policy-makers working to meet the management objectives as set forth by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and other components of the Antarctic Treaty System (ATS) (that is, Consultative Meetings and the ATS Committee on Environmental Protection). MAPPPD was designed specifically to complement existing efforts such as the CCAMLR Ecosystem Monitoring Program (CEMP) and the ATS site guidelines for visitors. The database underlying MAPPPD includes all publicly available (published and unpublished) count data on emperor, gentoo, Adelie) and chinstrap penguins in Antarctica. Penguin population models are used to assimilate available data into estimates of abundance for each site and year.Results are easily aggregated across multiple sites to obtain abundance estimates over any user-defined area of interest. A front end web interface located at www.penguinmap.com provides free and ready access to the most recent count and modelled data, and can act as a facilitator for data transfer between scientists and Antarctic stakeholders to help inform management decisions for the continent.

The Advanced Monitoring Systems Initiative--Performance Monitoring for DOE Environmental Remediation and Contaminant Containment

NASA Astrophysics Data System (ADS)

Haas, W. J.; Venedam, R. J.; Lohrstorfer, C. F.; Weeks, S. J.

2005-05-01

The Advanced Monitoring System Initiative (AMSI) is a new approach to accelerate the development and application of advanced sensors and monitoring systems in support of Department of Energy needs in monitoring the performance of environmental remediation and contaminant containment activities. The Nevada Site Office of the National Nuclear Security Administration (NNSA) and Bechtel Nevada manage AMSI, with funding provided by the DOE Office of Environmental Management (DOE EM). AMSI has easy access to unique facilities and capabilities available at the Nevada Test Site (NTS), including the Hazardous Materials (HazMat) Spill Center, a one-of-a-kind facility built and permitted for releases of hazardous materials for training purposes, field-test detection, plume dispersion experimentation, and equipment and materials testing under controlled conditions. AMSI also has easy access to the facilities and considerable capabilities of the DOE and NNSA National Laboratories, the Special Technologies Laboratory, Remote Sensing Laboratory, Desert Research Institute, and Nevada Universities. AMSI provides rapid prototyping, systems integration, and field-testing, including assistance during initial site deployment. The emphasis is on application. Important features of the AMSI approach are: (1) customer investment, involvement and commitment to use - including definition of needs, desired mode of operation, and performance requirements; and (2) employment of a complete systems engineering approach, which allows the developer to focus maximum attention on the essential new sensing element or elements while AMSI assumes principal responsibility for infrastructure support elements such as power, packaging, and general data acquisition, control, communication, visualization and analysis software for support of decisions. This presentation describes: (1) the needs for sensors and performance monitoring for environmental systems as seen by the DOE Long Term Stewardship Science and Technology Roadmap and the Long Term Monitoring Sensors and Analytical Methods Workshop, and (2) AMSI operating characteristics and progress in addressing those needs. Topics addressed will include: vadose zone and groundwater tritium monitoring, a wireless moisture monitoring system, Cr(VI) and CCl4 monitoring using a commercially available "universal sensor platform", strontium-90 and technetium-99 monitoring, and area chemical monitoring using an array of multi-chemical sensors.

Protocol for the evaluation of a decision aid for women with a breech-presenting baby [ISRCTN14570598

PubMed Central

Roberts, Christine L; Nassar, Natasha; Barratt, Alexandra; Raynes-Greenow, Camille H; Peat, Brian; Henderson-Smart, David

2004-01-01

Background There is now good evidence about the management options for pregnant women with a breech presentation (buttocks or feet rather than head-first) at term; external cephalic version (ECV) – the turning of a breech baby to a head-down position and/or planned caesarean section (CS). Each of these options has benefits and risks and the relative importance of these vary for each woman, subject to her personal values and preferences, a situation where a decision aid may be helpful. Decision aids are designed to assist patients and their doctors in making informed decisions using information that is unbiased and based on high quality research evidence. Decision aids are non-directive in the sense that they do not aim to steer the user towards any one option, but rather to support decision making which is informed and consistent with personal values. The ECV decision aid was developed using the Ottawa Decision Support Framework, including a systematic review of the evidence about the benefits and risks of the options for breech pregnancy. It comprises an audiotape with a supplementary booklet and worksheet, a format that can be taken home and discussed with a partner. This project aims to evaluate the ECV decision aid for women with a breech presenting baby in late pregnancy. Study design We aim to evaluate the effectiveness of the decision aid compared with usual care in a randomised controlled trial in maternity hospitals that offer ECV. The study group will receive the decision aid in addition to usual care and the control group will receive standard information on management options for breech presentation from their usual pregnancy care provider. Approximately 184 women with a single breech-presenting baby at greater than 34 weeks gestation and who are clinically eligible for ECV will be recruited for the trial. The primary outcomes of the study are knowledge, decisional conflict, anxiety and satisfaction with decision-making that will be assessed using self-administered questionnaires. The decision aid is not intended to influence either the uptake of either ECV or planned CS, however we will monitor health service utilisation rates and maternal and perinatal outcomes. PMID:15606926

A telemedicine support for diabetes management: the T-IDDM project.

PubMed

Bellazzi, R; Larizza, C; Montani, S; Riva, A; Stefanelli, M; d'Annunzio, G; Lorini, R; Gomez, E J; Hernando, E; Brugues, E; Cermeno, J; Corcoy, R; de Leiva, A; Cobelli, C; Nucci, G; Del Prato, S; Maran, A; Kilkki, E; Tuominen, J

2002-08-01

In the context of the EU funded Telematic Management of Insulin-Dependent Diabetes Mellitus (T-IDDM) project, we have designed, developed and evaluated a telemedicine system for insulin dependent diabetic patients management. The system relies on the integration of two modules, a Patient Unit (PU) and a Medical Unit (MU), able to communicate over the Internet and the Public Switched Telephone Network. Using the PU, patients are allowed to automatically download their monitoring data from the blood glucose monitoring device, and to send them to the hospital data-base; moreover, they are supported in their every day self monitoring activity. The MU provides physicians with a set of tools for data visualization, data analysis and decision support, and allows them to send messages and/or therapeutic advice to the patients. The T-IDDM service has been evaluated through the application of a formal methodology, and has been used by European patients and physicians for about 18 months. The results obtained during the project demonstration, even if obtained on a pilot study of 12 subjects, show the feasibility of the T-IDDM telemedicine service, and seem to substantiate the hypothesis that the use of the system could present an advantage in the management of insulin dependent diabetic patients, by improving communications and, potentially, clinical outcomes.

Human Activity Recognition from Smart-Phone Sensor Data using a Multi-Class Ensemble Learning in Home Monitoring.

PubMed

Ghose, Soumya; Mitra, Jhimli; Karunanithi, Mohan; Dowling, Jason

2015-01-01

Home monitoring of chronically ill or elderly patient can reduce frequent hospitalisations and hence provide improved quality of care at a reduced cost to the community, therefore reducing the burden on the healthcare system. Activity recognition of such patients is of high importance in such a design. In this work, a system for automatic human physical activity recognition from smart-phone inertial sensors data is proposed. An ensemble of decision trees framework is adopted to train and predict the multi-class human activity system. A comparison of our proposed method with a multi-class traditional support vector machine shows significant improvement in activity recognition accuracies.

An Online Risk Monitor System (ORMS) to Increase Safety and Security Levels in Industry

NASA Astrophysics Data System (ADS)

Zubair, M.; Rahman, Khalil Ur; Hassan, Mehmood Ul

2013-12-01

The main idea of this research is to develop an Online Risk Monitor System (ORMS) based on Living Probabilistic Safety Assessment (LPSA). The article highlights the essential features and functions of ORMS. The basic models and modules such as, Reliability Data Update Model (RDUM), running time update, redundant system unavailability update, Engineered Safety Features (ESF) unavailability update and general system update have been described in this study. ORMS not only provides quantitative analysis but also highlights qualitative aspects of risk measures. ORMS is capable of automatically updating the online risk models and reliability parameters of equipment. ORMS can support in the decision making process of operators and managers in Nuclear Power Plants.

Design of a multimedia PC-based telemedicine network for the monitoring of renal dialysis patients

NASA Astrophysics Data System (ADS)

Tohme, Walid G.; Winchester, James F.; Dai, Hailei L.; Khanafer, Nassib; Meissner, Marion C.; Collmann, Jeff R.; Schulman, Kevin A.; Johnson, Ayah E.; Freedman, Matthew T.; Mun, Seong K.

1997-05-01

This paper investigates the design and implementation of a multimedia telemedicine application being undertaken by the Imaging Science and Information Systems Center of the Department of Radiology and the Division of Nephrology of the Department of Medicine at the Georgetown University Medical Center (GUMC). The Renal Dialysis Patient Monitoring network links GUMC, a remote outpatient dialysis clinic, and a nephrologist's home. The primary functions of the network are to provide telemedicine services to renal dialysis patients, to create, manage, transfer and use electronic health data, and to provide decision support and information services for physicians, nurses and health care workers. The technical parameters for designing and implementing such a network are discussed.

Learning time series for intelligent monitoring

NASA Technical Reports Server (NTRS)

Manganaris, Stefanos; Fisher, Doug

1994-01-01

We address the problem of classifying time series according to their morphological features in the time domain. In a supervised machine-learning framework, we induce a classification procedure from a set of preclassified examples. For each class, we infer a model that captures its morphological features using Bayesian model induction and the minimum message length approach to assign priors. In the performance task, we classify a time series in one of the learned classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. We report results from experiments in a monitoring domain of interest to NASA.

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 easier and faster. The visual synthesis of data facilitates the use of information in health decision making at the district level of a health system and promotes program improvement. The experience in Kenya can be applied to other countries that face challenges making district-level, data-informed decisions with data from fragmented information systems. PMID:24011028

Improving management and effectiveness of home blood pressure monitoring: a qualitative UK primary care study.

PubMed

Grant, Sabrina; Greenfield, Sheila M; Nouwen, Arie; McManus, Richard J

2015-11-01

Self-monitoring blood pressure (SMBP) is becoming an increasingly prevalent practice in UK primary care, yet there remains little conceptual understanding of why patients with hypertension engage in self-monitoring. To identify psychological factors or processes prompting the decision to self-monitor blood pressure. A qualitative study of patients previously participating in a survey study about SMBP from four general practices in the West Midlands. Taped and transcribed in-depth interviews with 16 patients (6 currently monitoring, 2 used to self-monitor, and 8 had never self-monitored). Thematic analysis was undertaken. Three main themes emerged: 'self' and 'living with hypertension' described the emotional element of living with an asymptomatic condition; 'self-monitoring behaviour and medication' described overall views about self-monitoring, current practice, reasons for monitoring, and the impact on medication adherence; and 'the GP-patient transaction' described the power relations affecting decisions to self-monitor. Self-monitoring was performed by some as a protective tool against the fears of a silent but serious condition, whereas others self-monitor simply out of curiosity. People who self-monitored tended not to discuss this with their nurse or GP, partly due to perceiving minimal or no interest from their clinician about home monitoring, and partly due to fear of being prescribed additional medication. The decision to self-monitor appeared often to be an individual choice with no schedule or systems to integrate it with other medical care. Better recognition by clinicians that patients are self-monitoring, perhaps utilising the results in shared decision-making, might help integrate it into daily practice. © British Journal of General Practice 2015.

Development, deployment and usability of a point-of-care decision support system for chronic disease management using the recently-approved HL7 decision support service standard.

PubMed

Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight

2007-01-01

Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.

SUPPORT Tools for evidence-informed health Policymaking (STP)

PubMed Central

2009-01-01

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

Restoration of contaminated ecosystems: adaptive management in a changing climate

USGS Publications Warehouse

Farag, Aida; Larson, Diane L.; Stauber, Jenny; Stahl, Ralph; Isanhart, John; McAbee, Kevin T.; Walsh, Christopher J.

2017-01-01

Three case studies illustrate how adaptive management (AM) has been used in ecological restorations that involve contaminants. Contaminants addressed include mercury, selenium, and contaminants and physical disturbances delivered to streams by urban stormwater runoff. All three cases emphasize the importance of broad stakeholder input early and consistently throughout decision analysis for AM. Risk of contaminant exposure provided input to the decision analyses (e.g. selenium exposure to endangered razorback suckers, Stewart Lake; multiple contaminants in urban stormwater runoff, Melbourne) and was balanced with the protection of resources critical for a desired future state (e.g. preservation old growth trees, South River). Monitoring also played a critical role in the ability to conduct the decision analyses necessary for AM plans. For example, newer technologies in the Melbourne case provided a testable situation where contaminant concentrations and flow disturbance were reduced to support a return to good ecological condition. In at least one case (Stewart Lake), long-term monitoring data are being used to document the potential effects of climate change on a restoration trajectory. Decision analysis formalized the process by which stakeholders arrived at the priorities for the sites, which together constituted the desired future condition towards which each restoration is aimed. Alternative models were developed that described in mechanistic terms how restoration can influence the system towards the desired future condition. Including known and anticipated effects of future climate scenarios in these models will make them robust to the long-term exposure and effects of contaminants in restored ecosystems.

Study on an agricultural environment monitoring server system using Wireless Sensor Networks.

PubMed

Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

2010-01-01

This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information.

An Updated Decision Support Interface: A Tool for Remote Monitoring of Crop Growing Conditions

NASA Astrophysics Data System (ADS)

Husak, G. J.; Budde, M. E.; Rowland, J.; Verdin, J. P.; Funk, C. C.; Landsfeld, M. F.

2014-12-01

Remote sensing of agroclimatological variables to monitor food production conditions is a critical component of the Famine Early Warning Systems Network portfolio of tools for assessing food security in the developing world. The Decision Support Interface (DSI) seeks to integrate a number of remotely sensed and modeled variables to create a single, simplified portal for analysis of crop growing conditions. The DSI has been reformulated to incorporate more variables and give the user more freedom in exploring the available data. This refinement seeks to transition the DSI from a "first glance" agroclimatic indicator to one better suited for the differentiation of drought events. The DSI performs analysis of variables over primary agricultural zones at the first sub-national administrative level. It uses the spatially averaged rainfall, normalized difference vegetation index (NDVI), water requirement satisfaction index (WRSI), and actual evapotranspiration (ETa) to identify potential hazards to food security. Presenting this information in a web-based client gives food security analysts and decision makers a lightweight portal for information on crop growing conditions in the region. The crop zones used for the aggregation contain timing information which is critical to the DSI presentation. Rainfall and ETa are accumulated from different points in the crop phenology to identify season-long deficits in rainfall or transpiration that adversely affect the crop-growing conditions. Furthermore, the NDVI and WRSI serve as their own seasonal accumulated measures of growing conditions by capturing vegetation vigor or actual evapotranspiration deficits. The DSI is currently active for major growing regions of sub-Saharan Africa, with intention of expanding to other areas over the coming years.

Introduction of paramedic led Echo in Life Support into the pre-hospital environment: The PUCA study.

PubMed

Reed, Matthew J; Gibson, Louise; Dewar, Alistair; Short, Steven; Black, Polly; Clegg, Gareth R

2017-03-01

Can pre-hospital paramedic responders perform satisfactory pre-hospital Echo in Life Support (ELS) during the 10-s pulse check window, and does pre-hospital ELS adversely affect the delivery of cardiac arrest care. Prospective observational study of a cohort of ELS trained paramedics using saved ultrasound clips and wearable camera videos. Between 23rd June 2014 and 31st January 2016, seven Resuscitation Rapid Response Unit (3RU) paramedics attended 45 patients in Lothian suffering out-of-hospital CA where resuscitation was attempted and ELS was available and performed. 80% of first ELS attempts by paramedics produced an adequate view which was excellent/good or satisfactory in 68%. 44% of views were obtained within the 10-s pulse check window with a median time off the chest of 17 (IQR 13-20) seconds. A decision to perform ELS was communicated 67% of the time, and the 10-s pulse check was counted aloud in 60%. A manual pulse check was observed in around a quarter of patients and the rhythm on the monitor was checked 38% of the time. All decision changing scans involved a decision to stop resuscitation. Paramedics are able to obtain good ELS views in the pre-hospital environment but this may lead to longer hands off the chest time and possibly less pulse and monitor checking than is recommended. Future studies will need to demonstrate either improved outcomes or a benefit from identifying patients in whom further resuscitation and transportation is futile, before ELS is widely adopted in most pre-hospital systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Assisting the U.S. Forest Service in monitoring and managing the Pacific pine marten

NASA Astrophysics Data System (ADS)

Force, A.; Hadley, N.; Howell, B. L.; Holsinger, K.

2017-12-01

Innovative partnerships that bridge institutional sectors may be key in seizing many opportunities for highly effective projects. Adventure Scientists is a nonprofit organization that works in partnership with governments, universities, businesses and other nonprofits to support their need for actionable, research-grade data. In every partnership, it is critical that responsible decision-makers are involved and in place to use the data collected, such as to inform new resource management strategies or regulatory policies. In this presentation, we will highlight our experience working on one such partnership. In 2013, the U.S. Forest Service and Adventure Scientists collaborated on a two-year project to better understand Pacific pine marten (Martes caurina), a small native carnivore, in the Olympic National Forest. In response to the species' recent disappearance, Forest managers needed to gather more accurate data on martens' presence and abundance to support species management. Adventure Scientists was in a unique position to provide the agency this needed data-collection capacity. Volunteers collected data about the marten populations by positioning and monitoring camera traps throughout the area. Utilizing our volunteer-collected data, the U.S. Forest Service was able to inform the management and protection of these threatened species in U.S Forest Service Region 6. This project was also successful in establishing the foundation for an expanded, long-term relationship with the agency, where both parties continue to explore partnership opportunities for Adventure Scientists to collect data system-wide in support of U.S. Forest Service improved land management and policy decisions.

Deep space telecommunications, navigation, and information management - Support of the Space Exploration Initiative

NASA Technical Reports Server (NTRS)

Hall, Justin R.; Hastrup, Rolf C.

1990-01-01

The principal challenges in providing effective deep space navigation, telecommunications, and information management architectures and designs for Mars exploration support are presented. The fundamental objectives are to provide the mission with the means to monitor and control mission elements, obtain science, navigation, and engineering data, compute state vectors and navigate, and to move these data efficiently and automatically between mission nodes for timely analysis and decision making. New requirements are summarized, and related issues and challenges including the robust connectivity for manned and robotic links, are identified. Enabling strategies are discussed, and candidate architectures and driving technologies are described.

[Current situation and development trend of Chinese medicine information research].

PubMed

Dong, Yan; Cui, Meng

2013-04-01

Literature resource service was the main service that Chinese medicine (CM) information offered. But in recent years users have started to request the health information knowledge service. The CM information researches and application service mainly included: (1) the need of strength studies on theory, application of technology, information retrieval, and information standard development; (2) Information studies need to support clinical decision making, new drug research; (3) Quick response based on the network monitoring and support to emergency countermeasures. CM information researches have the following treads: (1) developing the theory system structure of CM information; (2) studying the methodology system of CM information; (3) knowledge discovery and knowledge innovation.

Deep space telecommunications, navigation, and information management - Support of the Space Exploration Initiative

NASA Astrophysics Data System (ADS)

Hall, Justin R.; Hastrup, Rolf C.

1990-10-01

The principal challenges in providing effective deep space navigation, telecommunications, and information management architectures and designs for Mars exploration support are presented. The fundamental objectives are to provide the mission with the means to monitor and control mission elements, obtain science, navigation, and engineering data, compute state vectors and navigate, and to move these data efficiently and automatically between mission nodes for timely analysis and decision making. New requirements are summarized, and related issues and challenges including the robust connectivity for manned and robotic links, are identified. Enabling strategies are discussed, and candidate architectures and driving technologies are described.

Contingency Base Energy Management System

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

2016-06-09

CB-EMS is the latest implementation of DSOM (Decision Support for Operations and Maintenance), which was previously patented by PNNL. CB-EMS WAS specifically designed for contingency bases for the US Army. It is a software package that is designed to monitor energy consumption at an Army contingency base to alert the camp manager when the systems are wasting energy. It's main feature that separates it from DSOM is it's ability to add systems using a plug and play menu system.

Literature Survey for Issues in Naval Decision Support: Phase 2

DTIC Science & Technology

1999-01-01

human cognition, the specific goals of Soar ( Congdon & Laird, 1996, cited in Kalus et al., 1996) are to: • Work on a full range of tasks from routine...leadership, and communication (Weaver et al., 1995). 5.5.4.4 Team Performance Assessment Battery (TPAB) TP AB is a more generic scenario...permits multiple tasks, including monitoring tasks, to be imposed on teams to assess factors related to workload. Thus, TP AB is suitable for assessing

A system to improve medication safety in the setting of acute kidney injury: initial provider response.

PubMed

McCoy, Allison B; McCoy, Allison Beck; Peterson, Josh F; Gadd, Cynthia S; Gadd, Cindy; Danciu, Ioana; Waitman, Lemuel R

2008-11-06

Clinical decision support systems can decrease common errors related to inappropriate or excessive dosing for nephrotoxic or renally cleared drugs. We developed a comprehensive medication safety intervention with varying levels of workflow intrusiveness within computerized provider order entry to continuously monitor for and alert providers about early-onset acute kidney injury. Initial provider response to the interventions shows potential success in improving medication safety and suggests future enhancements to increase effectiveness.

Web-Based Geographic Information System Tool for Accessing Hanford Site Environmental Data

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

Triplett, Mark B.; Seiple, Timothy E.; Watson, David J.

Data volume, complexity, and access issues pose severe challenges for analysts, regulators and stakeholders attempting to efficiently use legacy data to support decision making at the U.S. Department of Energy’s (DOE) Hanford Site. DOE has partnered with the Pacific Northwest National Laboratory (PNNL) on the PHOENIX (PNNL-Hanford Online Environmental Information System) project, which seeks to address data access, transparency, and integration challenges at Hanford to provide effective decision support. PHOENIX is a family of spatially-enabled web applications providing quick access to decades of valuable scientific data and insight through intuitive query, visualization, and analysis tools. PHOENIX realizes broad, public accessibilitymore » by relying only on ubiquitous web-browsers, eliminating the need for specialized software. It accommodates a wide range of users with intuitive user interfaces that require little or no training to quickly obtain and visualize data. Currently, PHOENIX is actively hosting three applications focused on groundwater monitoring, groundwater clean-up performance reporting, and in-tank monitoring. PHOENIX-based applications are being used to streamline investigative and analytical processes at Hanford, saving time and money. But more importantly, by integrating previously isolated datasets and developing relevant visualization and analysis tools, PHOENIX applications are enabling DOE to discover new correlations hidden in legacy data, allowing them to more effectively address complex issues at Hanford.« less

Era-Planet the European Network for Observing Our Changing Planet

NASA Astrophysics Data System (ADS)

Pirrone, N.; Cinnirella, S.; Nativi, S.; Sprovieri, F.; Hedgecock, I. M.

2016-06-01

In the last decade a significant number of projects and programmes in different domains of Earth Observation and environmental monitoring have generated a substantial amount of data and knowledge on different aspects related to environmental quality and sustainability. Big data generated by in-situ or satellite platforms are being collected and archived with a plethora of systems and instruments making difficult the sharing of data and transfer of knowledge to stakeholders and policy makers to support key economic and societal sectors. The overarching goal of ERAPLANET is to strengthen the European Research Area in the domain of Earth Observation in coherence with the European participation in the Group on Earth Observation (GEO) and Copernicus. The expected impact is to strengthen European leadership within the forthcoming GEO 2015-2025 Work Plan. ERA-PLANET is designed to reinforce the interface with user communities, whose needs the Global Earth Observation System of Systems (GEOSS) intends to address. It will provide more accurate, comprehensive and authoritative information to policy and decision-makers in key societal benefit areas, such as Smart Cities and Resilient Societies; Resource efficiency and Environmental management; Global changes and Environmental treaties; Polar areas and Natural resources. ERA-PLANET will provide advanced decision-support tools and technologies aimed to better monitor our global environment and share the information and knowledge available in the different domains of Earth Observation.

[Study on extraction method of Panax notoginseng plots in Wenshan of Yunnan province based on decision tree model].

PubMed

Shi, Ting-Ting; Zhang, Xiao-Bo; Guo, Lan-Ping; Huang, Lu-Qi

2017-11-01

The herbs used as the material for traditional Chinese medicine are always planted in the mountainous area where the natural environment is suitable. As the mountain terrain is complex and the distribution of planting plots is scattered, the traditional survey method is difficult to obtain accurate planting area. It is of great significance to provide decision support for the conservation and utilization of traditional Chinese medicine resources by studying the method of extraction of Chinese herbal medicine planting area based on remote sensing and realizing the dynamic monitoring and reserve estimation of Chinese herbal medicines. In this paper, taking the Panax notoginseng plots in Wenshan prefecture of Yunnan province as an example, the China-made GF-1multispectral remote sensing images with a 16 m×16 m resolution were obtained. Then, the time series that can reflect the difference of spectrum of P. notoginseng shed and the background objects were selected to the maximum extent, and the decision tree model of extraction the of P. notoginseng plots was constructed according to the spectral characteristics of the surface features. The results showed that the remote sensing classification method based on the decision tree model could extract P. notoginseng plots in the study area effectively. The method can provide technical support for extraction of P. notoginseng plots at county level. Copyright© by the Chinese Pharmaceutical Association.

Pupil dilation signals uncertainty and surprise in a learning gambling task.

PubMed

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2013-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.

Pupil dilation signals uncertainty and surprise in a learning gambling task

PubMed Central

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2014-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126

Emerging conservation challenges and prospects in an era of offshore hydrocarbon exploration and exploitation.

PubMed

Kark, Salit; Brokovich, Eran; Mazor, Tessa; Levin, Noam

2015-12-01

Globally, extensive marine areas important for biodiversity conservation and ecosystem functioning are undergoing exploration and extraction of oil and natural gas resources. Such operations are expanding to previously inaccessible deep waters and other frontier regions, while conservation-related legislation and planning is often lacking. Conservation challenges arising from offshore hydrocarbon development are wide-ranging. These challenges include threats to ecosystems and marine species from oil spills, negative impacts on native biodiversity from invasive species colonizing drilling infrastructure, and increased political conflicts that can delay conservation actions. With mounting offshore operations, conservationists need to urgently consider some possible opportunities that could be leveraged for conservation. Leveraging options, as part of multi-billion dollar marine hydrocarbon operations, include the use of facilities and costly equipment of the deep and ultra-deep hydrocarbon industry for deep-sea conservation research and monitoring and establishing new conservation research, practice, and monitoring funds and environmental offsetting schemes. The conservation community, including conservation scientists, should become more involved in the earliest planning and exploration phases and remain involved throughout the operations so as to influence decision making and promote continuous monitoring of biodiversity and ecosystems. A prompt response by conservation professionals to offshore oil and gas developments can mitigate impacts of future decisions and actions of the industry and governments. New environmental decision support tools can be used to explicitly incorporate the impacts of hydrocarbon operations on biodiversity into marine spatial and conservation plans and thus allow for optimum trade-offs among multiple objectives, costs, and risks. © 2015 Society for Conservation Biology.

Cross-scale phenological data integration to benefit resource management and monitoring

USGS Publications Warehouse

Richardson, Andrew D.; Weltzin, Jake F.; Morisette, Jeffrey T.

2017-01-01

Climate change is presenting new challenges for natural resource managers charged with maintaining sustainable ecosystems and landscapes. Phenology, a branch of science dealing with seasonal natural phenomena (bird migration or plant flowering in response to weather changes, for example), bridges the gap between the biosphere and the climate system. Phenological processes operate across scales that span orders of magnitude—from leaf to globe and from days to seasons—making phenology ideally suited to multiscale, multiplatform data integration and delivery of information at spatial and temporal scales suitable to inform resource management decisions.A workshop report: Workshop held June 2016 to investigate opportunities and challenges facing multi-scale, multi-platform integration of phenological data to support natural resource management decision-making.

Decision Support | Solar Research | NREL

Science.gov Websites

informed solar decision making with credible, objective, accessible, and timely resources. Solar Energy Decision Support Decision Support NREL provides technical and analytical support to support provide unbiased information on solar policies and issues for state and local government decision makers

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

PubMed

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

2016-04-01

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

An mHealth Monitoring System for Traditional Birth Attendant-led Antenatal Risk Assessment in Rural Guatemala

PubMed Central

Stroux, Lisa; Martinez, Boris; Ixen, Enma Coyote; King, Nora; Hall-Clifford, Rachel; Rohloff, Peter; Clifford, Gari D.

2016-01-01

Limited funding for medical technology, low levels of education and poor infrastructure for delivering and maintaining technology severely limit medical decision support in low- and middle-income countries. Perinatal and maternal mortality is of particular concern with millions dying every year from potentially treatable conditions. Guatemala has one of the worst maternal mortality ratios, the highest incidence of intrauterine growth restriction (IUGR), and one of the lowest gross national incomes per capita within Latin America. To address the lack of decision support in rural Guatemala, a smartphone-based system is proposed including peripheral sensors, such as a handheld Doppler for the identification of fetal compromise. Designed for use by illiterate birth attendants, the system uses pictograms, audio guidance, local and cloud processing, SMS alerts and voice calling. The initial prototype was evaluated on 22 women in highland Guatemala. Results were fed back into the refinement of the system, currently undergoing RCT evaluation. PMID:27696915

An mHealth monitoring system for traditional birth attendant-led antenatal risk assessment in rural Guatemala.

PubMed

Stroux, Lisa; Martinez, Boris; Coyote Ixen, Enma; King, Nora; Hall-Clifford, Rachel; Rohloff, Peter; Clifford, Gari D

Limited funding for medical technology, low levels of education and poor infrastructure for delivering and maintaining technology severely limit medical decision support in low- and middle-income countries. Perinatal and maternal mortality is of particular concern with millions dying every year from potentially treatable conditions. Guatemala has one of the worst maternal mortality ratios, the highest incidence of intra-uterine growth restriction (IUGR), and one of the lowest gross national incomes per capita within Latin America. To address the lack of decision support in rural Guatemala, a smartphone-based system is proposed including peripheral sensors, such as a handheld Doppler for the identification of foetal compromise. Designed for use by illiterate birth attendants, the system uses pictograms, audio guidance, local and cloud processing, SMS alerts and voice calling. The initial prototype was evaluated on 22 women in highland Guatemala. Results were fed back into the refinement of the system, currently undergoing RCT evaluation.

DCDS: A Real-time Data Capture and Personalized Decision Support System for Heart Failure Patients in Skilled Nursing Facilities.

PubMed

Zhu, Wei; Luo, Lingyun; Jain, Tarun; Boxer, Rebecca S; Cui, Licong; Zhang, Guo-Qiang

2016-01-01

Heart disease is the leading cause of death in the United States. Heart failure disease management can improve health outcomes for elderly community dwelling patients with heart failure. This paper describes DCDS, a real-time data capture and personalized decision support system for a Randomized Controlled Trial Investigating the Effect of a Heart Failure Disease Management Program (HF-DMP) in Skilled Nursing Facilities (SNF). SNF is a study funded by the NIH National Heart, Lung, and Blood Institute (NHLBI). The HF-DMP involves proactive weekly monitoring, evaluation, and management, following National HF Guidelines. DCDS collects a wide variety of data including 7 elements considered standard of care for patients with heart failure: documentation of left ventricular function, tracking of weight and symptoms, medication titration, discharge instructions, 7 day follow up appointment post SNF discharge and patient education. We present the design and implementation of DCDS and describe our preliminary testing results.

Diagnosing, monitoring and managing behavioural variant frontotemporal dementia.

PubMed

Piguet, Olivier; Kumfor, Fiona; Hodges, John

2017-09-02

Behavioural variant frontotemporal dementia is characterised by insidious changes in personality and interpersonal conduct that reflect progressive disintegration of the neural circuits involved in social cognition, emotion regulation, motivation and decision making. The underlying pathology is heterogeneous and classified according to the presence of intraneuronal inclusions of tau, TDP-43 or, occasionally, fused in sarcoma proteins. Biomarkers to detect these histopathological changes in life are increasingly important with the development of disease-modifying drugs. A number of gene abnormalities have been identified, the most common being an expansion in the C9orf72 gene, which together account for most familial cases. The 2011 international consensus criteria propose three levels of diagnostic certainty: possible, probable and definite. Detailed history taking from family members to elicit behavioural features underpins the diagnostic process, with support from neuropsychological testing designed to detect impairment in decision making, emotion processing and social cognition. Brain imaging is important for increasing the level of diagnosis certainty over time. Carer education and support remain of paramount importance.

Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

PubMed

Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

2014-01-01

The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

Drought: A comprehensive R package for drought monitoring, prediction and analysis

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.; Cheng, Hongguang

2015-04-01

Drought may impose serious challenges to human societies and ecosystems. Due to complicated causing effects and wide impacts, a universally accepted definition of drought does not exist. The drought indicator is commonly used to characterize drought properties such as duration or severity. Various drought indicators have been developed in the past few decades for the monitoring of a certain aspect of drought condition along with the development of multivariate drought indices for drought characterizations from multiple sources or hydro-climatic variables. Reliable drought prediction with suitable drought indicators is critical to the drought preparedness plan to reduce potential drought impacts. In addition, drought analysis to quantify the risk of drought properties would provide useful information for operation drought managements. The drought monitoring, prediction and risk analysis are important components in drought modeling and assessments. In this study, a comprehensive R package "drought" is developed to aid the drought monitoring, prediction and risk analysis (available from R-Forge and CRAN soon). The computation of a suite of univariate and multivariate drought indices that integrate drought information from various sources such as precipitation, temperature, soil moisture, and runoff is available in the drought monitoring component in the package. The drought prediction/forecasting component consists of statistical drought predictions to enhance the drought early warning for decision makings. Analysis of drought properties such as duration and severity is also provided in this package for drought risk assessments. Based on this package, a drought monitoring and prediction/forecasting system is under development as a decision supporting tool. The package will be provided freely to the public to aid the drought modeling and assessment for researchers and practitioners.

The development of a Simplified, Effective, Labour Monitoring-to-Action (SELMA) tool for Better Outcomes in Labour Difficulty (BOLD): study protocol.

PubMed

Souza, João Paulo; Oladapo, Olufemi T; Bohren, Meghan A; Mugerwa, Kidza; Fawole, Bukola; Moscovici, Leonardo; Alves, Domingos; Perdona, Gleici; Oliveira-Ciabati, Livia; Vogel, Joshua P; Tunçalp, Özge; Zhang, Jim; Hofmeyr, Justus; Bahl, Rajiv; Gülmezoglu, A Metin

2015-05-26

The partograph is currently the main tool available to support decision-making of health professionals during labour. However, the rate of appropriate use of the partograph is disappointingly low. Apart from limitations that are associated with partograph use, evidence of positive impact on labour-related health outcomes is lacking. The main goal of this study is to develop a Simplified, Effective, Labour Monitoring-to-Action (SELMA) tool. The primary objectives are: to identify the essential elements of intrapartum monitoring that trigger the decision to use interventions aimed at preventing poor labour outcomes; to develop a simplified, monitoring-to-action algorithm for labour management; and to compare the diagnostic performance of SELMA and partograph algorithms as tools to identify women who are likely to develop poor labour-related outcomes. A prospective cohort study will be conducted in eight health facilities in Nigeria and Uganda (four facilities from each country). All women admitted for vaginal birth will comprise the study population (estimated sample size: 7,812 women). Data will be collected on maternal characteristics on admission, labour events and pregnancy outcomes by trained research assistants at the participating health facilities. Prediction models will be developed to identify women at risk of intrapartum-related perinatal death or morbidity (primary outcomes) throughout the course of labour. These predictions models will be used to assemble a decision-support tool that will be able to suggest the best course of action to avert adverse outcomes during the course of labour. To develop this set of prediction models, we will use up-to-date techniques of prognostic research, including identification of important predictors, assigning of relative weights to each predictor, estimation of the predictive performance of the model through calibration and discrimination, and determination of its potential for application using internal validation techniques. This research offers an opportunity to revisit the theoretical basis of the partograph. It is envisioned that the final product would help providers overcome the challenging tasks of promptly interpreting complex labour information and deriving appropriate clinical actions, and thus increase efficiency of the care process, enhance providers' competence and ultimately improve labour outcomes. Please see related articles ' http://dx.doi.org/10.1186/s12978-015-0027-6 ' and ' http://dx.doi.org/10.1186/s12978-015-0028-5 '.

HydroGrid: Technologies for Global Water Quality and Sustainability

NASA Astrophysics Data System (ADS)

Yeghiazarian, L.

2017-12-01

Humans have been transforming planet Earth for millennia. We have recently come to understand that the collective impact of our decisions and actions has brought about severe water quality problems, which are likely to worsen in the light of rapid population growth to the projected nine billion by 2050. To sustainably manage our global water resources and possibly reverse these effects requires efforts in real-time monitoring of water contamination, analysis of monitoring data, and control of the state of water contamination. We develop technologies to address all three areas: monitoring, analysis and control. These efforts are carried out in the conceptual framework of the HydroGrid, an interconnected water system, which is (1) firmly rooted in the fundamental understanding of processes that govern microbial dynamics on multiple scales; and (2) used to develop watershed-specific management strategies. In the area of monitoring we are developing mobile autonomous sensors to detect surface water contamination, an effort supported by extensive materials research to provide multifunctional materials. We analyze environmental data within a stochastic modeling paradigm that bridges microscopic particle interactions to macroscopic manifestation of microbial population behavior in time and space in entire watersheds. These models are supported with laboratory and field experiments. Finally, we combine control and graph theories to derive controllability metrics of natural watersheds.

SERVIR: From Space to Village. A Regional Monitoring and Visualization System For Environmental Management Using Satellite Applications For Sustainable Development

NASA Technical Reports Server (NTRS)

Sever, Tom; Stahl, H. Philip; Irwin, Dan; Lee, Daniel

2007-01-01

NASA is committed to providing technological support and expertise to regional and national organizations for earth science monitoring and analysis. This commitment is exemplified by NASA's long-term relationship with Central America. The focus of these efforts has primarily been to measure the impact of human development on the environment and to provide data for the management of human settlement and expansion in the region. Now, NASA is planning to extend and expand this capability to other regions of the world including Africa and the Caribbean. NASA began using satellite imagery over twenty-five years ago to locate important Maya archeological sites in Mesoamerica and to quantify the affect of deforestation on those sites. Continuing that mission, NASA has partnered with the U.S. Agency for International Development (USAID), the World Bank, the Water Center for the Humid Tropics of Latin America and the Caribbean (CATHALAC) and the Central American Commission for Environment and Development (CCAD) to develop SERVIR (Sistema Regional de Visualizacion y Monitoreo), for the Mesoamerican Biological Corridor. SERVIR has become one of the most important aspects of NASA's geospatial efforts in Central America by establishing a common access portal for information that affects the lives, livelihood and future of everyone in the region. SERVIR, most commonly referred to as a regional visualization and monitoring system, is a scientific and technological platform that integrates satellite and other geospatial data sets to generate tools for improved decision-making capabilities. It has a collection of data and models that are easily accessible to earth science managers, first responders, NGO's (Non-Government Organizations) and a host of others. SERVIR is currently used to monitor and forecast ecological changes as well as provide information for decision support during severe events such as forest fires, red tides,and tropical storms. Additionally, SERVIR addresses the nine societal benefit areas of the Global Earth Observation System (GEOSS): disasters, ecosystems, biodiversity, weather, water, climate, health, agriculture and energy.

Smart Devices for Older Adults Managing Chronic Disease: A Scoping Review.

PubMed

Kim, Ben Yb; Lee, Joon

2017-05-23

The emergence of smartphones and tablets featuring vastly advancing functionalities (eg, sensors, computing power, interactivity) has transformed the way mHealth interventions support chronic disease management for older adults. Baby boomers have begun to widely adopt smart devices and have expressed their desire to incorporate technologies into their chronic care. Although smart devices are actively used in research, little is known about the extent, characteristics, and range of smart device-based interventions. We conducted a scoping review to (1) understand the nature, extent, and range of smart device-based research activities, (2) identify the limitations of the current research and knowledge gap, and (3) recommend future research directions. We used the Arksey and O'Malley framework to conduct a scoping review. We identified relevant studies from MEDLINE, Embase, CINAHL, and Web of Science databases using search terms related to mobile health, chronic disease, and older adults. Selected studies used smart devices, sampled older adults, and were published in 2010 or after. The exclusion criteria were sole reliance on text messaging (short message service, SMS) or interactive voice response, validation of an electronic version of a questionnaire, postoperative monitoring, and evaluation of usability. We reviewed references. We charted quantitative data and analyzed qualitative studies using thematic synthesis. To collate and summarize the data, we used the chronic care model. A total of 51 articles met the eligibility criteria. Research activity increased steeply in 2014 (17/51, 33%) and preexperimental design predominated (16/50, 32%). Diabetes (16/46, 35%) and heart failure management (9/46, 20%) were most frequently studied. We identified diversity and heterogeneity in the collection of biometrics and patient-reported outcome measures within and between chronic diseases. Across studies, we found 8 self-management supporting strategies and 4 distinct communication channels for supporting the decision-making process. In particular, self-monitoring (38/40, 95%), automated feedback (15/40, 38%), and patient education (13/40, 38%) were commonly used as self-management support strategies. Of the 23 studies that implemented decision support strategies, clinical decision making was delegated to patients in 10 studies (43%). The impact on patient outcomes was consistent with studies that used cellular phones. Patients with heart failure and asthma reported improved quality of life. Qualitative analysis yielded 2 themes of facilitating technology adoption for older adults and 3 themes of barriers. Limitations of current research included a lack of gerontological focus, dominance of preexperimental design, narrow research scope, inadequate support for participants, and insufficient evidence for clinical outcome. Recommendations for future research include generating evidence for smart device-based programs, using patient-generated data for advanced data mining techniques, validating patient decision support systems, and expanding mHealth practice through innovative technologies. ©Ben YB Kim, Joon Lee. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 23.05.2017.

Biasing moral decisions by exploiting the dynamics of eye gaze.

PubMed

Pärnamets, Philip; Johansson, Petter; Hall, Lars; Balkenius, Christian; Spivey, Michael J; Richardson, Daniel C

2015-03-31

Eye gaze is a window onto cognitive processing in tasks such as spatial memory, linguistic processing, and decision making. We present evidence that information derived from eye gaze can be used to change the course of individuals' decisions, even when they are reasoning about high-level, moral issues. Previous studies have shown that when an experimenter actively controls what an individual sees the experimenter can affect simple decisions with alternatives of almost equal valence. Here we show that if an experimenter passively knows when individuals move their eyes the experimenter can change complex moral decisions. This causal effect is achieved by simply adjusting the timing of the decisions. We monitored participants' eye movements during a two-alternative forced-choice task with moral questions. One option was randomly predetermined as a target. At the moment participants had fixated the target option for a set amount of time we terminated their deliberation and prompted them to choose between the two alternatives. Although participants were unaware of this gaze-contingent manipulation, their choices were systematically biased toward the target option. We conclude that even abstract moral cognition is partly constituted by interactions with the immediate environment and is likely supported by gaze-dependent decision processes. By tracking the interplay between individuals, their sensorimotor systems, and the environment, we can influence the outcome of a decision without directly manipulating the content of the information available to them.

Scientific monitoring plan in support of the selected alternative of the Glen Canyon Dam Long-Term Experimental and Management Plan

USGS Publications Warehouse

Vanderkooi, Scott P.; Kennedy, Theodore A.; Topping, David J.; Grams, Paul E.; Ward, David L.; Fairley, Helen C.; Bair, Lucas S.; Sankey, Joel B.; Yackulic, Charles B.; Schmidt, John C.

2017-01-18

IntroductionThe purpose of this document is to describe a strategy by which monitoring and research data in the natural and social sciences will be collected, analyzed, and provided to the U.S. Department of the Interior (DOI), its bureaus, and to the Glen Canyon Dam Adaptive Management Program (GCDAMP) in support of implementation of the Glen Canyon Dam Long-Term Experimental and Management Plan (LTEMP) (U.S. Department of the Interior, 2016a). The selected alternative identified in the LTEMP Record of Decision (ROD) (U.S. Department of the Interior, 2016b) describes various data collection, analysis, modeling, and interpretation efforts to be conducted by the U.S. Geological Survey’s (USGS) Grand Canyon Monitoring and Research Center (GCMRC), partner agencies, and cooperators that will inform decisions about operations of Glen Canyon Dam and management of downstream resources between 2017 and 2037, the performance period of the LTEMP. General data collection, analysis, modeling, and interpretation activities are described in this science plan, whereas specific monitoring and research activities and detailed study plans are to be described in the GCDAMP’s triennial work plans (TWPs) to be developed by the Bureau of Reclamation and GCMRC with input from partner agencies and cooperators during the LTEMP period, which are to be reviewed and recommended by the GCDAMP and approved by the Secretary of the Interior. The GCDAMP consists of several components, the primary committee being the Adaptive Management Work Group (AMWG). This Federal advisory committee is composed of 25 agencies and stakeholder groups and is chaired by the Secretary of the Interior’s designee. The AMWG makes recommendations to the Secretary of the Interior concerning operations of Glen Canyon Dam and other experimental management actions that are intended to fulfill some obligations of the Grand Canyon Protection Act of 1992. The Technical Work Group (TWG) is a subcommittee of the AMWG and provides technical advice to the AMWG. It is composed of technical and science representatives from the same agencies and stakeholder groups who serve on the AMWG. GCMRC is the primary science provider to the GCDAMP and also coordinates many aspects of the science performed by cooperators and partner agencies. The Science Advisors Program provides independent science reviews and advice at the request of the GCDAMP.The plan proposed here necessarily depends on (1) the protocol for decision-making and the requirements for scientific data reporting described in the LTEMP ROD, (2) the priorities of the GCDAMP as directed by the LTEMP ROD (see Department of the Interior, 2016b, section 6.1), (3) the priorities for monitoring and research in the conservation measures section of the Biological Opinion for the LTEMP (U.S. Department of the Interior, 2016b, LTEMP ROD attachment E), (4) the priorities for resource management and information needs established by Federal and State resource-management agencies within the GCDAMP, (5) scientific understanding about the linkage between the status of those resources and operations of Glen Canyon Dam, and (6) the need to resolve existing scientific uncertainties about the linkage between dam operations and the condition of resources. We note that resource-management prioritization is fundamentally a policy decision charged specifically to DOI for the Colorado River in Glen and Grand Canyons, as outlined most recently in the LTEMP ROD, and is not the responsibility of the GCMRC. However, it is the responsibility of the GCMRC to describe the nature of scientific understanding, the nature of scientific uncertainty, and the risk of making resourcemanagement decisions in the face of existing scientific uncertainty. The goals of science activities in the next 20 years are to inform operational decisions regarding Glen Canyon Dam operations described in the LTEMP ROD, resolve remaining scientific uncertainties, and to monitor resource trends that are affected entirely, or in part, by dam operations.

The Real Time Mission Monitor: A Situational Awareness Tool For Managing Experiment Assets

NASA Technical Reports Server (NTRS)

Blakeslee, Richard; Hall, John; Goodman, Michael; Parker, Philip; Freudinger, Larry; He, Matt

2007-01-01

The NASA Real Time Mission Monitor (RTMM) is a situational awareness tool that integrates satellite, airborne and surface data sets; weather information; model and forecast outputs; and vehicle state data (e.g., aircraft navigation, satellite tracks and instrument field-of-views) for field experiment management RTMM optimizes science and logistic decision-making during field experiments by presenting timely data and graphics to the users to improve real time situational awareness of the experiment's assets. The RTMM is proven in the field as it supported program managers, scientists, and aircraft personnel during the NASA African Monsoon Multidisciplinary Analyses experiment during summer 2006 in Cape Verde, Africa. The integration and delivery of this information is made possible through data acquisition systems, network communication links and network server resources built and managed by collaborators at NASA Dryden Flight Research Center (DFRC) and Marshall Space Flight Center (MSFC). RTMM is evolving towards a more flexible and dynamic combination of sensor ingest, network computing, and decision-making activities through the use of a service oriented architecture based on community standards and protocols.

Making an Informed Decision on Freshwater Management by Integrating Remote Sensing Data with Traditional Data

NASA Technical Reports Server (NTRS)

Hyon, Jason J.

2012-01-01

The US National Research Council (NRC) recommended that: "The U.S. government, working in concert with the private sector, academe, the public, and its international partners, should renew its investment in Earth-observing systems and restore its leadership in Earth science and applications." in response to the NASA Earth Science Division's request to prioritize research areas, observations, and notional missions to make those objectives. In this presentation, we will discuss our approach to connect remote sensing science to decision support applications by establishing a framework to integrate direct measurements, earth system models, inventories, and other information to accurately estimate fresh water resources in global, regional, and local scales. We will discuss our demonstration projects and lessons learned from the experience. Deploying a monitoring system that offers sustained, accurate, transparent and relevant information represents a challenge and opportunity to a broad community spanning earth science, water resource accounting and public policy. An introduction to some of the scientific and technical infrastructure issues associated with monitoring systems is offered here to encourage future treatment of these topics by other contributors as a concluding remark.

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.

Improving the use of health data for health system strengthening.

PubMed

Nutley, Tara; Reynolds, Heidi W

2013-02-13

Good quality and timely data from health information systems are the foundation of all health systems. However, too often data sit in reports, on shelves or in databases and are not sufficiently utilised in policy and program development, improvement, strategic planning and advocacy. Without specific interventions aimed at improving the use of data produced by information systems, health systems will never fully be able to meet the needs of the populations they serve. To employ a logic model to describe a pathway of how specific activities and interventions can strengthen the use of health data in decision making to ultimately strengthen the health system. A logic model was developed to provide a practical strategy for developing, monitoring and evaluating interventions to strengthen the use of data in decision making. The model draws on the collective strengths and similarities of previous work and adds to those previous works by making specific recommendations about interventions and activities that are most proximate to affect the use of data in decision making. The model provides an organizing framework for how interventions and activities work to strengthen the systematic demand, synthesis, review, and use of data. The logic model and guidance are presented to facilitate its widespread use and to enable improved data-informed decision making in program review and planning, advocacy, policy development. Real world examples from the literature support the feasible application of the activities outlined in the model. The logic model provides specific and comprehensive guidance to improve data demand and use. It can be used to design, monitor and evaluate interventions, and to improve demand for, and use of, data in decision making. As more interventions are implemented to improve use of health data, those efforts need to be evaluated.

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 training section, NOAA has made significant progress in sharing resources with the external community.

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

PubMed Central

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

2016-01-01

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

A decision-analytic approach to the optimal allocation of resources for endangered species consultation

USGS Publications Warehouse

Converse, Sarah J.; Shelley, Kevin J.; Morey, Steve; Chan, Jeffrey; LaTier, Andrea; Scafidi, Carolyn; Crouse, Deborah T.; Runge, Michael C.

2011-01-01

The resources available to support conservation work, whether time or money, are limited. Decision makers need methods to help them identify the optimal allocation of limited resources to meet conservation goals, and decision analysis is uniquely suited to assist with the development of such methods. In recent years, a number of case studies have been described that examine optimal conservation decisions under fiscal constraints; here we develop methods to look at other types of constraints, including limited staff and regulatory deadlines. In the US, Section Seven consultation, an important component of protection under the federal Endangered Species Act, requires that federal agencies overseeing projects consult with federal biologists to avoid jeopardizing species. A benefit of consultation is negotiation of project modifications that lessen impacts on species, so staff time allocated to consultation supports conservation. However, some offices have experienced declining staff, potentially reducing the efficacy of consultation. This is true of the US Fish and Wildlife Service's Washington Fish and Wildlife Office (WFWO) and its consultation work on federally-threatened bull trout (Salvelinus confluentus). To improve effectiveness, WFWO managers needed a tool to help allocate this work to maximize conservation benefits. We used a decision-analytic approach to score projects based on the value of staff time investment, and then identified an optimal decision rule for how scored projects would be allocated across bins, where projects in different bins received different time investments. We found that, given current staff, the optimal decision rule placed 80% of informal consultations (those where expected effects are beneficial, insignificant, or discountable) in a short bin where they would be completed without negotiating changes. The remaining 20% would be placed in a long bin, warranting an investment of seven days, including time for negotiation. For formal consultations (those where expected effects are significant), 82% of projects would be placed in a long bin, with an average time investment of 15. days. The WFWO is using this decision-support tool to help allocate staff time. Because workload allocation decisions are iterative, we describe a monitoring plan designed to increase the tool's efficacy over time. This work has general application beyond Section Seven consultation, in that it provides a framework for efficient investment of staff time in conservation when such time is limited and when regulatory deadlines prevent an unconstrained approach. ?? 2010.

Neural mechanisms underlying conflict monitoring over risky decision alternatives: evidence from ERP in a Go/Nogo task.

PubMed

Wang, Shuzhen; Hui, Ning; Zhou, Xinsheng; He, Kaifeng; Yu, Yuanyuan; Shuai, Jing

2014-09-01

This study assessed conflict monitoring during presentation of risky decision alternatives, as indexed by the Nogo-N2, Nogo-P3, N2d and P3d event-related potentials (ERP). Decision-makers were tested on a Go/Nogo gambling task in which gain/loss outcomes as well as stimulus type (Go/Nogo) were equiprobable. Frontal-central Nogo-N2 and Nogo-P3 did not significantly differ across risky decision alternatives, whereas N2d and P3d amplitudes were more sensitive to the nature of risky decision alternatives. Frontal-central N2d was moderated by the magnitude of alternatives, with N2d amplitude greater for large than small alternatives, a result that suggests a greater degree of conflict monitoring for the former. Central P3d was associated with alternative valence, such that P3d amplitude was greater for loss than gain valences, again suggestive of more conflict monitoring for the former. The N2d and P3d potentials in risky decision alternatives are discussed in terms of the functional significance of the N2/P3 complex.

Smart self management: assistive technology to support people with chronic disease.

PubMed

Zheng, Huiru; Nugent, Chris; McCullagh, Paul; Huang, Yan; Zhang, Shumei; Burns, William; Davies, Richard; Black, Norman; Wright, Peter; Mawson, Sue; Eccleston, Christopher; Hawley, Mark; Mountain, Gail

2010-01-01

We have developed a personalised self management system to support self management of chronic conditions with support from health-care professionals. Accelerometers are used to measure gross levels of activity, for example walking around the house, and used to infer higher level activity states, such as standing, sitting and lying. A smart phone containing an accelerometer and a global positioning system (GPS) module can be used to monitor outdoor activity, providing both activity and location based information. Heart rate, blood pressure and weight are recorded and input to the system by the user. A decision support system (DSS) detects abnormal activity and distinguishes life style patterns. The DSS is used to assess the self management process, and automates feedback to the user, consistent with the achievement of their life goals. We have found that telecare and assistive technology is feasible to support self management for chronic conditions within the home and local community environments.

The Global Drought Information System - A Decision Support Tool with Global Applications

NASA Astrophysics Data System (ADS)

Arndt, D. S.; Brewer, M.; Heim, R. R., Jr.

2014-12-01

Drought is a natural hazard which can cause famine in developing countries and severe economic hardship in developed countries. Given current concerns with the increasing frequency and magnitude of droughts in many regions of the world, especially in the light of expected climate change, drought monitoring and dissemination of early warning information in a timely fashion on a global scale is a critical concern as an important adaptation and mitigation strategy. While a number of nations, and a few continental-scale activities have developed drought information system activities, a global drought early warning system (GDEWS) remains elusive, despite the benefits highlighted by ministers to the Global Earth Observation System of System in 2008. In an effort to begin a process of drought monitoring with international collaboration, the National Integrated Drought Information System's (NIDIS) U.S. Drought Portal, a web-based information system created to address drought services and early warning in the United States, including drought monitoring, forecasting, impacts, mitigation, research, and education, volunteered to develop a prototype Global Drought Monitoring Portal (GDMP). Through integration of data and information at the global level, and with four continental-level partners, the GDMP has proven successful as a tool to monitor drought around the globe. At a past meeting between NIDIS, the World Meteorological Organization, and the Global Earth Observation System of Systems, it was recommended that the GDMP form the basis for a Global Drought Information System (GDIS). Currently, GDIS activities are focused around providing operational global drought monitoring products and assessments, incorporating additional drought monitoring information, especially from those areas without regional or continental-scale input, and incorporating drought-specific climate forecast information from the World Climate Research Programme. Additional GDIS pilot activities are underway with an emphasis on information and decision making, and how to effectively provide drought early warning. This talk will provide an update on the status of GDIS and its role in international drought monitoring.

Development of a Web-based GIS monitoring and environmental assessment system for the Black Sea: application in the Danube Delta area.

PubMed

Tziavos, Ilias N; Alexandridis, Thomas K; Aleksandrov, Borys; Andrianopoulos, Agamemnon; Doukas, Ioannis D; Grigoras, Ion; Grigoriadis, Vassilios N; Papadopoulou, Ioanna D; Savvaidis, Paraskevas; Stergioudis, Argyrios; Teodorof, Liliana; Vergos, Georgios S; Vorobyova, Lyudmila; Zalidis, Georgios C

2016-08-01

In this paper, the development of a Web-based GIS system for the monitoring and assessment of the Black Sea is presented. The integrated multilevel system is based on the combination of terrestrial and satellite Earth observation data through the technological assets provided by innovative information tools and facilities. The key component of the system is a unified, easy to update geodatabase including a wide range of appropriately selected environmental parameters. The collection procedure of current and historical data along with the methods employed for their processing in three test areas of the current study are extensively discussed, and special attention is given to the overall design and structure of the developed geodatabase. Furthermore, the information system includes a decision support component (DSC) which allows assessment and effective management of a wide range of heterogeneous data and environmental parameters within an appropriately designed and well-tested methodology. The DSC provides simplified and straightforward results based on a classification procedure, thus contributing to a monitoring system not only for experts but for auxiliary staff as well. The examples of the system's functionality that are presented highlight its usability as well as the assistance that is provided to the decision maker. The given examples emphasize on the Danube Delta area; however, the information layers of the integrated system can be expanded in the future to cover other regions, thus contributing to the development of an environmental monitoring system for the entire Black Sea.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Arden Syntax Clinical Foundation Framework for Event Monitoring in Intensive Care Units: Report on a Pilot Study.

PubMed

de Bruin, Jeroen S; Zeckl, Julia; Adlassnig, Katharina; Blacky, Alexander; Koller, Walter; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

2017-01-01

The creation of clinical decision support systems has received a strong impulse over the last years, but their integration into a clinical routine has lagged behind, partly due to a lack of interoperability and trust by physicians. We report on the implementation of a clinical foundation framework in Arden Syntax, comprising knowledge units for (a) preprocessing raw clinical data, (b) the determination of single clinical concepts, and (c) more complex medical knowledge, which can be modeled through the composition and configuration of knowledge units in this framework. Thus, it can be tailored to clinical institutions or patients' caregivers. In the present version, we integrated knowledge units for several infection-related clinical concepts into the framework and developed a clinical event monitoring system over the framework that employs three different scenarios for monitoring clinical signs of bloodstream infection. The clinical event monitoring system was tested using data from intensive care units at Vienna General Hospital, Austria.

Colorado Water Watch: real-time groundwater monitoring for possible contamination from oil and gas activities.

PubMed

Son, Ji-Hee; Hanif, Asma; Dhanasekar, Ashwin; Carlson, Kenneth H

2018-02-13

Currently, only a few states in the USA (e.g., Colorado and Ohio) require mandatory baseline groundwater sampling from nearby groundwater wells prior to drilling a new oil or gas well. Colorado is the first state to regulate groundwater testing before and after drilling, which requires one pre-drilling sample and two additional post-drilling samples within 6-12 months and 5-6 years of drilling. However, the monitoring method is limited to the state's regulatory agency and to ex situ sampling, which offers only a snapshot in time. To overcome the limitations and increase monitoring performance, a new groundwater monitoring system, Colorado Water Watch (CWW), was introduced as a decision-making tool to support the state's regulatory agency and also to provide real-time groundwater quality data to both the industry and the public. The CWW uses simple in situ water quality sensors based on the surrogate sensing technology that employs an event detection system to screen the incoming data in near real-time.

Building statistical associations to forecast ethylbenzene levels in European urban-traffic environments.

PubMed

Vlachokostas, Ch; Michailidou, A V; Spyridi, D; Moussiopoulos, N

2013-06-01

Emission from road traffic has become the most important source of local air pollution in numerous European cities. Epidemiological research community has established consistent associations between traffic-related substances and various health outcomes. Nevertheless, the vast majority of urban areas are characterised by infrastructure's absence to routinely monitor chemical health stressors, such as ethylbenzene. This paper aims at developing and presenting a tractable approach to reliably - and inexpensively - predict ethylbenzene trends in EU urban environments. The establishment of empirical relationships between rarely monitored pollutants such as ethylbenzene and more frequently or usually monitored, such as benzene and CO respectively, may cover the infrastructure's absence and support decision-making. Multiple regression analysis is adopted and the resulting statistical associations are applied to EU cities with available data for validation purposes. The results demonstrate that this approach is capable of capturing ethylbenzene concentration trends and should be considered as complementary to air quality monitoring. Copyright © 2013 Elsevier Ltd. All rights reserved.

CORS911:Real-Time Subsidence Monitoring of the Napoleonville Salt Dome Sinkhole Using GPS

NASA Astrophysics Data System (ADS)

Kent, J. D.

2013-12-01

The sinkhole associated with the Napoleonville salt dome in Assumption Parish, Louisiana, threatens the stability of Highway 70 - a state maintained route. To mitigate the potential damaging effects to the highway and address issues of public safety, a program of research and decision support has been implemented to provide long-term measurements of the surface stability using continuous operating GPS reference stations (CORS). Four CORS sites were installed in the vicinity of the sinkhole to measure the horizontal and vertical motions of each site relative to each other and a fixed location outside the study area. Differential motions measured by a integrity monitoring software are summarized for response agencies tasked with ensuring public safety and stability of the Highway, a designated hurricane evacuation route. Implementation experience and intermediate findings will be shared and discussed. Strategies for monitoring random and systematic biases detected in the system are presented. Figure depicting the location of CORS sites used to monitor surface stability along Highway 70 near the Bayou Corne Sinkhole.

Multimodal brain monitoring in fulminant hepatic failure

PubMed Central

Paschoal Jr, Fernando Mendes; Nogueira, Ricardo Carvalho; Ronconi, Karla De Almeida Lins; de Lima Oliveira, Marcelo; Teixeira, Manoel Jacobsen; Bor-Seng-Shu, Edson

2016-01-01

Acute liver failure, also known as fulminant hepatic failure (FHF), embraces a spectrum of clinical entities characterized by acute liver injury, severe hepatocellular dysfunction, and hepatic encephalopathy. Cerebral edema and intracranial hypertension are common causes of mortality in patients with FHF. The management of patients who present acute liver failure starts with determining the cause and an initial evaluation of prognosis. Regardless of whether or not patients are listed for liver transplantation, they should still be monitored for recovery, death, or transplantation. In the past, neuromonitoring was restricted to serial clinical neurologic examination and, in some cases, intracranial pressure monitoring. Over the years, this monitoring has proven insufficient, as brain abnormalities were detected at late and irreversible stages. The need for real-time monitoring of brain functions to favor prompt treatment and avert irreversible brain injuries led to the concepts of multimodal monitoring and neurophysiological decision support. New monitoring techniques, such as brain tissue oxygen tension, continuous electroencephalogram, transcranial Doppler, and cerebral microdialysis, have been developed. These techniques enable early diagnosis of brain hemodynamic, electrical, and biochemical changes, allow brain anatomical and physiological monitoring-guided therapy, and have improved patient survival rates. The purpose of this review is to discuss the multimodality methods available for monitoring patients with FHF in the neurocritical care setting. PMID:27574545

Electronic decision support for diagnostic imaging in a primary care setting

PubMed Central

Reed, Martin H

2011-01-01

Methods Clinical guideline adherence for diagnostic imaging (DI) and acceptance of electronic decision support in a rural community family practice clinic was assessed over 36 weeks. Physicians wrote 904 DI orders, 58% of which were addressed by the Canadian Association of Radiologists guidelines. Results Of those orders with guidelines, 76% were ordered correctly; 24% were inappropriate or unnecessary resulting in a prompt from clinical decision support. Physicians followed suggestions from decision support to improve their DI order on 25% of the initially inappropriate orders. The use of decision support was not mandatory, and there were significant variations in use rate. Initially, 40% reported decision support disruptive in their work flow, which dropped to 16% as physicians gained experience with the software. Conclusions Physicians supported the concept of clinical decision support but were reluctant to change clinical habits to incorporate decision support into routine work flow. PMID:21486884

Rational risk-based decision support for drinking water well managers by optimized monitoring designs

NASA Astrophysics Data System (ADS)

Enzenhöfer, R.; Geiges, A.; Nowak, W.

2011-12-01

Advection-based well-head protection zones are commonly used to manage the contamination risk of drinking water wells. Considering the insufficient knowledge about hazards and transport properties within the catchment, current Water Safety Plans recommend that catchment managers and stakeholders know, control and monitor all possible hazards within the catchments and perform rational risk-based decisions. Our goal is to supply catchment managers with the required probabilistic risk information, and to generate tools that allow for optimal and rational allocation of resources between improved monitoring versus extended safety margins and risk mitigation measures. To support risk managers with the indispensable information, we address the epistemic uncertainty of advective-dispersive solute transport and well vulnerability (Enzenhoefer et al., 2011) within a stochastic simulation framework. Our framework can separate between uncertainty of contaminant location and actual dilution of peak concentrations by resolving heterogeneity with high-resolution Monte-Carlo simulation. To keep computational costs low, we solve the reverse temporal moment transport equation. Only in post-processing, we recover the time-dependent solute breakthrough curves and the deduced well vulnerability criteria from temporal moments by non-linear optimization. Our first step towards optimal risk management is optimal positioning of sampling locations and optimal choice of data types to reduce best the epistemic prediction uncertainty for well-head delineation, using the cross-bred Likelihood Uncertainty Estimator (CLUE, Leube et al., 2011) for optimal sampling design. Better monitoring leads to more reliable and realistic protection zones and thus helps catchment managers to better justify smaller, yet conservative safety margins. In order to allow an optimal choice in sampling strategies, we compare the trade-off in monitoring versus the delineation costs by accounting for ill-delineated fractions of protection zones. Within an illustrative simplified 2D synthetic test case, we demonstrate our concept, involving synthetic transmissivity and head measurements for conditioning. We demonstrate the worth of optimally collected data in the context of protection zone delineation by assessing the reduced areal demand of delineated area at user-specified risk acceptance level. Results indicate that, thanks to optimally collected data, risk-aware delineation can be made at low to moderate additional costs compared to conventional delineation strategies.

The Lower Sevier River Basin Crop Monitor and Forecast Decision Support System: Exploiting Landsat Imagery to Provide Continuous Information to Farmers and Water Managers

NASA Astrophysics Data System (ADS)

Torres-Rua, A. F.; Walker, W. R.; McKee, M.

2013-12-01

The last century has seen a large number of innovations in agriculture such as better policies for water control and management, upgraded water conveyance, irrigation, distribution, and monitoring systems, and better weather forecasting products. In spite of this, irrigation management and irrigation water deliveries by farmers/water managers is still based on factors like water share amounts, tradition, and past experience on irrigation. These factors are not necessarily related to the actual crop water use; they are followed because of the absence of related information provided in a timely manner at an affordable cost. Thus, it is necessary to develop means to deliver continuous and personalized information about crop water requirements to water users/managers at the field and irrigation system levels so managers at these levels can better quantify the required versus available water for irrigation during the irrigation season. This study presents a new decision support system (DSS) platform that addresses the absence of information on actual crop water requirements and crop performance by providing continuous updated farm-based crop water use along with other farm performance indicators such as crop yield and farm management to irrigators and water managers. This DSS exploits the periodicity of the Landsat Satellite Mission (8 to 16 days, depending on the period of interest) to provide remote monitoring at the individual field and irrigation system levels. The Landsat satellite images are converted into information about crop water use, yield performance and field management through application of state-of-the-art semi-physical and statistical algorithms that provide this information at a pixel basis that are ultimately aggregated to field and irrigation system levels. A version of the DSS has been implemented for the agricultural lands in the Lower Sevier River, Utah, and has been operational since the beginning of the 2013 irrigation season. The main goal of this DSS implementation is to provide continuous and personalized information to farmers and water managers regarding crops in fields and the irrigation delivery system throughout the irrigation season so that decisions related to agricultural water use can result in water savings while not diminishing crop yields.

Supporting end of life decision making: Case studies of relational closeness in supported decision making for people with severe or profound intellectual disability.

PubMed

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-11-01

The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions. Five people with severe or profound intellectual disability's experiences of supported decision making were examined. This article is particularly focused on one participant's experiences at the end of his life. All five case studies identified that supporters were most effective in providing decision-making support for participants when they were relationally close to the person and had knowledge of the person's life story, particularly in relation to events that demonstrated preference. Findings from this study provide new understandings of supported decision making for people with severe or profound intellectual disability and have particular relevance for supporting decision making at the end of life. © 2017 John Wiley & Sons Ltd.

A Framework for Achieving Situational Awareness during Crisis based on Twitter Analysis

NASA Astrophysics Data System (ADS)

Zielinski, Andrea; Tokarchuk, Laurissa; Middleton, Stuart; Chaves, Fernando

2013-04-01

Decision Support Systems for Natural Crisis Management increasingly employ Web 2.0 and 3.0 technologies for future collaborative decision making, including the use of social networks like Twitter. However, human sensor data is not readily accessible and interpretable, since the texts are unstructured, noisy and available in various languages. The present work focusses on the detection of crisis events in a multilingual setting as part of the FP7-funded EU project TRIDEC and is motivated by the goal to establish a Tsunami warning system for the Mediterranean. It is integrated into a dynamic spatial-temporal decision making component with a command and control unit's graphical user interface that presents all relevant information to the human operator to support critical decision-support. To this end, a tool for the interactive visualization of geospatial data is implemented: All tweets with an exact timestamp or geo-location are monitored on the map in real-time so that the operator on duty can get an overall picture of the situation. Apart from the human sensor data, the seismic sensor data will appear also on the same screen. Signs of abnormal activity from twitter usage in social networks as well as in sensor networks devices can then be used to trigger official warning alerts according to the CAP message standard. Whenever a certain threshold of relevant tweets in a HASC region (Hierarchical Administrative Subdivision Code) is exceeded, the twitter activity in this administrative region will be shown on a map. We believe that the following functionalities are crucial for monitoring crisis, making use of text mining and network analysis techniques: Focussed crawling, trustworthyness analysis geo-parsing, and multilingual tweet classification. In the first step, the Twitter Streaming API accesses the social data, using an adaptive keyword list (focussed crawling). Then, tweets are filtered and aggregated to form counts for a certain time-span (e.g., an interval of 1-2 minutes). Particularly, we investigate the following novel techniques that help to fulfill this task: trustworthyness analysis (linkage analysis and user network analysis), geo-parsing (locating the event in space), and multilingual tweet classification (filtering out of noisy tweets for various Mediterranean languages). Lastly, an aberration algorithm looks for spikes in the temporal stream of twitter data.

Deterministic Wave Predictions from the WaMoS II

DTIC Science & Technology

2014-10-23

Monitoring System WaMoS II as input to a wave pre- diction system . The utility of wave prediction is primarily ves- sel motion prediction. Specific...successful prediction. The envisioned prediction system may provide graphical output in the form of a decision support system (Fig. 1). Predictions are...quality and accuracy of WaMoS as input to a deterministic wave prediction system . In the context of this paper, the Time Now Forecast H e a v e Hindcast

Effects of Simulated Pathophysiology on the Performance of a Decision Support Medical Monitoring System for Early Detection of Hemodynamic Decompensation in Humans

DTIC Science & Technology

2014-10-01

pulse oximeter (Cardiocap/5; Datex-Ohmeda, Louisville, CO). The EKG and pulse oximeter tracings were interfaced with a personal computer for con- tinuous...responses to reduced central venous pressure (CVP) and pulse pressure (PP) elicited during graded lower body negative pressure (LBNP) to those observed...Johnson BD, Curry TB, Convertino VA, & Joyner MJ. The association between pulse pressure and stroke volume during lower body negative pressure and

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

Sanfilippo, Antonio P.; Chikkagoudar, Satish

We describe an approach to analyzing trade data which uses clustering to detect similarities across shipping manifest records, classification to evaluate clustering results and categorize new unseen shipping data records, and visual analytics to provide to support situation awareness in dynamic decision making to monitor and warn against the movement of radiological threat materials through search, analysis and forecasting capabilities. The evaluation of clustering results through classification and systematic inspection of the clusters show the clusters have strong semantic cohesion and offer novel ways to detect transactions related to nuclear smuggling.

Multimedia-based decision support system for hazards recognition and abatement

DOEpatents

Czachowski, John B.; Zoldak, John T.

1998-01-01

A system for monitoring a site includes a portable data collection module used in the field to collect site specific data, and a processor module located at a central location. The data collection module displays choices of categories of findings, and then specific findings within each category. A selected specific finding is then displayed in report form with a citation to the specific code or statutory requirement, as well as a recommended course of action and an abatement date.

Systems identification and the adaptive management of waterfowl in the United States

USGS Publications Warehouse

Williams, B.K.; Nichols, J.D.

2001-01-01

Waterfowl management in the United States is one of the more visible conservation success stories in the United States. It is authorized and supported by appropriate legislative authorities, based on large-scale monitoring programs, and widely accepted by the public. The process is one of only a limited number of large-scale examples of effective collaboration between research and management, integrating scientific information with management in a coherent framework for regulatory decision-making. However, harvest management continues to face some serious technical problems, many of which focus on sequential identification of the resource system in a context of optimal decision-making. The objective of this paper is to provide a theoretical foundation of adaptive harvest management, the approach currently in use in the United States for regulatory decision-making. We lay out the legal and institutional framework for adaptive harvest management and provide a formal description of regulatory decision-making in terms of adaptive optimization. We discuss some technical and institutional challenges in applying adaptive harvest management and focus specifically on methods of estimating resource states for linear resource systems.

Applicability of aquifer impact models to support decisions at CO 2 sequestration sites

DOE PAGES

Keating, Elizabeth; Bacon, Diana; Carroll, Susan; ...

2016-07-25

The National Risk Assessment Partnership has developed a suite of tools to assess and manage risk at CO 2 sequestration sites. This capability includes polynomial or look-up table based reduced-order models (ROMs) that predict the impact of CO 2 and brine leaks on overlying aquifers. The development of these computationally-efficient models and the underlying reactive transport simulations they emulate has been documented elsewhere (Carroll et al., 2014a; Carroll et al., 2014b; Dai et al., 2014 ; Keating et al., 2016). Here in this paper, we seek to demonstrate applicability of ROM-based analysis by considering what types of decisions and aquifermore » types would benefit from the ROM analysis. We present four hypothetical examples where applying ROMs, in ensemble mode, could support decisions during a geologic CO 2 sequestration project. These decisions pertain to site selection, site characterization, monitoring network evaluation, and health impacts. In all cases, we consider potential brine/CO 2 leak rates at the base of the aquifer to be uncertain. We show that derived probabilities provide information relevant to the decision at hand. Although the ROMs were developed using site-specific data from two aquifers (High Plains and Edwards), the models accept aquifer characteristics as variable inputs and so they may have more broad applicability. We conclude that pH and TDS predictions are the most transferable to other aquifers based on the analysis of the nine water quality metrics (pH, TDS, 4 trace metals, 3 organic compounds). Guidelines are presented for determining the aquifer types for which the ROMs should be applicable.« less

Towards Developing a Regional Drought Information System for Lower Mekong

NASA Astrophysics Data System (ADS)

Dutta, R.; Jayasinghe, S.; Basnayake, S. B.; Apirumanekul, C.; Pudashine, J.; Granger, S. L.; Andreadis, K.; Das, N. N.

2016-12-01

With the climate and weather patterns changing over the years, the Lower Mekong Basin have been experiencing frequent and prolonged droughts resulting in severe damage to the agricultural sector affecting food security and livelihoods of the farming community. However, the Regional Drought Information System (RDIS) for Lower Mekong countries would help prepare vulnerable communities from frequent and severe droughts through monitoring, assessing and forecasting of drought conditions and allowing decision makers to take effective decisions in terms of providing early warning, incentives to farmers, and adjustments to cropping calendars and so on. The RDIS is an integrated system that is being designed for drought monitoring, analysis and forecasting based on the need to meet the growing demand of an effective monitoring system for drought by the lower Mekong countries. The RDIS is being built on four major components that includes earth observation component, meteorological data component, database storage and Regional Hydrologic Extreme Assessment System (RHEAS) framework while the outputs from the system will be made open access to the public through a web-based user interface. The system will run on the RHEAS framework that allows both nowcasting and forecasting using hydrological and crop simulation models such as the Variable Infiltration Capacity (VIC) model and the Decision Support System for Agro-Technology Transfer (DSSAT) model respectively. The RHEAS allows for a tightly constrained observation based drought and crop yield information system that can provide customized outputs on drought that includes root zone soil moisture, Standard Precipitation Index (SPI), Standard Runoff Index (SRI), Palmer Drought Severity Index (PDSI) and Crop Yield and can integrate remote sensing products, along with evapotranspiration and soil moisture data. The anticipated outcomes from the RDIS is to improve the operational, technological and institutional capabilities of lower Mekong countries to prepare for and respond towards drought situations and providing policy makers with current and forecast drought indices for decision making on adjusting cropping calendars as well as planning short and long term mitigation measures.

Workflow management in large distributed systems

NASA Astrophysics Data System (ADS)

Legrand, I.; Newman, H.; Voicu, R.; Dobre, C.; Grigoras, C.

2011-12-01

The MonALISA (Monitoring Agents using a Large Integrated Services Architecture) framework provides a distributed service system capable of controlling and optimizing large-scale, data-intensive applications. An essential part of managing large-scale, distributed data-processing facilities is a monitoring system for computing facilities, storage, networks, and the very large number of applications running on these systems in near realtime. All this monitoring information gathered for all the subsystems is essential for developing the required higher-level services—the components that provide decision support and some degree of automated decisions—and for maintaining and optimizing workflow in large-scale distributed systems. These management and global optimization functions are performed by higher-level agent-based services. We present several applications of MonALISA's higher-level services including optimized dynamic routing, control, data-transfer scheduling, distributed job scheduling, dynamic allocation of storage resource to running jobs and automated management of remote services among a large set of grid facilities.

Monitoring of European corn borer with pheromone-baited traps: review of trapping system basics and remaining problems.

PubMed

Laurent, Pélozuelo; Frérot, Brigitte

2007-12-01

Since the identification of female European corn borer, Ostrinia nubilalis (Hübner) pheromone, pheromone-baited traps have been regarded as a promising tool to monitor populations of this pest. This article reviews the literature produced on this topic since the 1970s. Its aim is to provide extension entomologists and other researchers with all the necessary information to establish an efficient trapping procedure for this moth. The different pheromone races of the European corn borer are described, and research results relating to the optimization of pheromone blend, pheromone bait, trap design, and trap placement are summarized followed by a state-of-the-art summary of data comparing blacklight trap and pheromone-baited trap techniques to monitor European corn borer flight. Finally, we identify the information required to definitively validate/invalidate the pheromone-baited traps as an efficient decision support tool in European corn borer control.

Chemically dependent physicians and informed consent disclosure.

PubMed

Ackerman, T F

1996-01-01

Developments in law, professional guidelines, and public attitudes support informed consent disclosure by physicians who have been treated for chemical dependency. This view is built on the apparent materiality of the risk of relapse to informed treatment decisions by patients. Several considerations undercut this position. The probability is remote that a patient will be injured by a recovering physician who suffers an undetected relapse while being properly monitored. Monitoring by impaired physicians programs provides a more sensitive and specific mechanism for detecting relapsed physicians. Moreover, compromise of the privacy and employment rights of recovering physicians by consent disclosure is not justified if programs provide rigorous monitoring that protects the welfare of patients. Finally, required consent disclosure will reduce referrals of chemically dependent physicians to impaired physicians programs, thereby increasing the danger to patients. Limiting demands for required consent disclosure necessitates effective operation of impaired physicians programs.

Hanford Site Raptor Nest Monitoring Report for Calendar Year 2013

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

Nugent, John J.; Lindsey, Cole T.; Wilde, Justin W.

2014-02-13

The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE activities. Ecological monitoring data provide baseline information about the plants, animals, and habitat under DOE-RL stewardship at Hanford required for decision-making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). The Hanford Site Comprehensive Land Use Plan (CLUP, DOE/EIS-0222-F) which is the Environmental Impact Statement for Hanford Site activities, helps ensure that DOE-RL, its contractors, and othermore » entities conducting activities on the Hanford Site are in compliance with NEPA. The Hanford Site supports a large and diverse community of raptorial birds (Fitzner et al. 1981), with 26 species of raptors observed on the Hanford Site.« less

Integrating molecular diagnostic and flow cytometric reporting for improved longitudinal monitoring of HIV patients.

PubMed Central

Asare, A. L.; Huda, H.; Klimczak, J. C.; Caldwell, C. W.

1998-01-01

Studies have shown that monitoring HIV-infected patients undergoing antiretroviral therapy is best represented by combined measurement of plasma HIV-1 RNA and CD4+ T-lymphocytes [1]. This pilot study at the University of Missouri-Columbia integrates molecular diagnostic and flow cytometric data reporting to provide current and historical HIV-1 RNA levels and CD4+ T-cell counts. The development of a single database for storage and retrieval of these values facilitates composite report generation that includes longitudinal HIV-1 RNA levels and CD4+ T-cell counts for all patients. Results are displayed in tables and plotted graphically within a web browser. This method of data presentation converts individual data points to more useful medical information and could provide clinicians with decision support for improved monitoring of HIV patients undergoing antiretroviral therapy. Images Figure 2 Figure 3 Figure 4 PMID:9929359

EMF Monitoring—Concepts, Activities, Gaps and Options

PubMed Central

Dürrenberger, Gregor; Fröhlich, Jürg; Röösli, Martin; Mattsson, Mats-Olof

2014-01-01

Exposure to electromagnetic fields (EMF) is a cause of concern for many people. The topic will likely remain for the foreseeable future on the scientific and political agenda, since emissions continue to change in characteristics and levels due to new infrastructure deployments, smart environments and novel wireless devices. Until now, systematic and coordinated efforts to monitor EMF exposure are rare. Furthermore, virtually nothing is known about personal exposure levels. This lack of knowledge is detrimental for any evidence-based risk, exposure and health policy, management and communication. The main objective of the paper is to review the current state of EMF exposure monitoring activities in Europe, to comment on the scientific challenges and deficiencies, and to describe appropriate strategies and tools for EMF exposure assessment and monitoring to be used to support epidemiological health research and to help policy makers, administrators, industry and consumer representatives to base their decisions and communication activities on facts and data. PMID:25216256

Analysis of post-tensioned girders structural behaviour using continuous temperature and strain monitoring

NASA Astrophysics Data System (ADS)

Bednarski, Ł.; Sieńko, R.; Howiacki, T.

2017-10-01

This article presents the possibility of using structural health monitoring system data for the analysis of structure’s operation during its life cycle. Within the specific case study it was proved, that continuous, automatic and long term monitoring of selected physical quantities such as strains and temperatures, can significantly improve the assessment of technical condition by identifying hazardous phenomena. In this work the analysis of structural behaviour of post-tensioned girders within the roofing of sport halls in Cracow, Poland, was performed based on measurement results and verified by numerical model carried out in SOFiSTiK software. Thanks to the possibility of performing calculations in real time and informing the manager of the object about abnormalities it is possible to manage the structure in effective way by, inter alia, planning the renovations or supporting decisions about snow removal.

Application of GNSS-RTK derived topographical maps for rapid environmental monitoring: a case study of Jack Finnery Lake (Perth, Australia).

PubMed

Schloderer, Glen; Bingham, Matthew; Awange, Joseph L; Fleming, Kevin M

2011-09-01

In environmental monitoring, environmental impact assessments and environmental audits, topographical maps play an essential role in providing a means by which the locations of sampling sites may be selected, in assisting with the interpretation of physical features, and in indicating the impact or potential impact on an area due to changes in the system being monitored (e.g., spatially changing features such as wetlands). Global Navigation Satellite Systems (GNSS) are hereby presented as a rapid method for monitoring spatial changes to support environmental monitoring decisions and policies. To validate the GNSS-based method, a comparison is made of results from a small-scale topographic survey using radio-based real-time kinematic GNSS (GNSS-RTK) and total station survey methods at Jack Finnery Lake, Perth, Australia. The accuracies achieved by the total station in this study were 2 cm horizontally and 6 cm vertically, while the GNSS-RTK also achieved an accuracy of 2 cm horizontally, but only 28 cm vertically. While the GNSS-RTK measurements were less accurate in the height component compared to those from the total station method, it is still capable of achieving accuracies sufficient for a topographic map at a scale of 1:1,750 that could support environmental monitoring tasks such as identifying spatial changes in small water bodies or wetlands. The time taken to perform the survey using GNSS-RTK, however, was much shorter compared to the total station method, thereby making it quite suitable for monitoring spatial changes within an environmental context, e.g., dynamic mining activities that require rapid surveys and the updating of the monitored data at regular intervals.

Case Study on the Maintenance of a Construction Monitoring Using USN-Based Data Acquisition

PubMed Central

Kim, Sangyong; Shin, Yoonseok; Kim, Gwang-Hee

2014-01-01

In recent years, there has been an increasing interest in the adoption of emerging ubiquitous sensor network (USN) technologies for instrumentation within a variety of sustainability systems. USN is emerging as a sensing paradigm that is being newly considered by the sustainability management field as an alternative to traditional tethered monitoring systems. Researchers have been discovering that USN is an exciting technology that should not be viewed simply as a substitute for traditional tethered monitoring systems. In this study, we investigate how a movement monitoring measurement system of a complex building is developed as a research environment for USN and related decision-supportive technologies. To address the apparent danger of building movement, agent-mediated communication concepts have been designed to autonomously manage large volumes of exchanged information. In this study, we additionally detail the design of the proposed system, including its principles, data processing algorithms, system architecture, and user interface specifics. Results of the test and case study demonstrate the effectiveness of the USN-based data acquisition system for real-time monitoring of movement operations. PMID:25097890

MS-BWME: A Wireless Real-Time Monitoring System for Brine Well Mining Equipment

PubMed Central

Xiao, Xinqing; Zhu, Tianyu; Qi, Lin; Moga, Liliana Mihaela; Zhang, Xiaoshuan

2014-01-01

This paper describes a wireless real-time monitoring system (MS-BWME) to monitor the running state of pumps equipment in brine well mining and prevent potential failures that may produce unexpected interruptions with severe consequences. MS-BWME consists of two units: the ZigBee Wireless Sensors Network (WSN) unit and the real-time remote monitoring unit. MS-BWME was implemented and tested in sampled brine wells mining in Qinghai Province and four kinds of indicators were selected to evaluate the performance of the MS-BWME, i.e., sensor calibration, the system's real-time data reception, Received Signal Strength Indicator (RSSI) and sensor node lifetime. The results show that MS-BWME can accurately judge the running state of the pump equipment by acquiring and transmitting the real-time voltage and electric current data of the equipment from the spot and provide real-time decision support aid to help workers overhaul the equipment in a timely manner and resolve failures that might produce unexpected production down-time. The MS-BWME can also be extended to a wide range of equipment monitoring applications. PMID:25340455

Case study on the maintenance of a construction monitoring using USN-based data acquisition.

PubMed

Kim, Sangyong; Shin, Yoonseok; Kim, Gwang-Hee

2014-01-01

In recent years, there has been an increasing interest in the adoption of emerging ubiquitous sensor network (USN) technologies for instrumentation within a variety of sustainability systems. USN is emerging as a sensing paradigm that is being newly considered by the sustainability management field as an alternative to traditional tethered monitoring systems. Researchers have been discovering that USN is an exciting technology that should not be viewed simply as a substitute for traditional tethered monitoring systems. In this study, we investigate how a movement monitoring measurement system of a complex building is developed as a research environment for USN and related decision-supportive technologies. To address the apparent danger of building movement, agent-mediated communication concepts have been designed to autonomously manage large volumes of exchanged information. In this study, we additionally detail the design of the proposed system, including its principles, data processing algorithms, system architecture, and user interface specifics. Results of the test and case study demonstrate the effectiveness of the USN-based data acquisition system for real-time monitoring of movement operations.

Real-time Web GIS to monitor marine water quality using wave glider

NASA Astrophysics Data System (ADS)

Maneesa Amiruddin, Siti

2016-06-01

In the past decade, Malaysia has experienced unprecedented economic development and associated socioeconomic changes. As environmentalists anticipate these changes could have negative impacts on the marine and coastal environment, a comprehensive, continuous and long term marine water quality monitoring programme needs to be strengthened to reflect the government's aggressive mind-set of enhancing its authority in protection, preservation, management and enrichment of vast resources of the ocean. Wave Glider, an autonomous, unmanned marine vehicle provides continuous ocean monitoring at all times and is durable in any weather condition. Geographic Information System (GIS) technology is ideally suited as a tool for the presentation of data derived from continuous monitoring of locations, and used to support and deliver information to environmental managers and the public. Combined with GeoEvent Processor, an extension from ArcGIS for Server, it extends the Web GIS capabilities in providing real-time data from the monitoring activities. Therefore, there is a growing need of Web GIS for easy and fast dissemination, sharing, displaying and processing of spatial information which in turn helps in decision making for various natural resources based applications.

Ubiquitous computing in shared-care environments.

PubMed

Koch, S

2006-07-01

In light of future challenges, such as growing numbers of elderly, increase in chronic diseases, insufficient health care budgets and problems with staff recruitment for the health-care sector, information and communication technology (ICT) becomes a possible means to meet these challenges. Organizational changes such as the decentralization of the health-care system lead to a shift from in-hospital to both advanced and basic home health care. Advanced medical technologies provide solutions for distant home care in form of specialist consultations and home monitoring. Furthermore, the shift towards home health care will increase mobile work and the establishment of shared care teams which require ICT-based solutions that support ubiquitous information access and cooperative work. Clinical documentation and decision support systems are the main ICT-based solutions of interest in the context of ubiquitous computing for shared care environments. This paper therefore describes the prerequisites for clinical documentation and decision support at the point of care, the impact of mobility on the documentation process, and how the introduction of ICT-based solutions will influence organizations and people. Furthermore, the role of dentistry in shared-care environments is discussed and illustrated in the form of a future scenario.

Monitoring and sustainable management of oil polluting wrecks and chemical munitions dump sites in the Baltic Sea

NASA Astrophysics Data System (ADS)

Hassellöv, Ida-Maja; Tengberg, Anders

2017-04-01

The Baltic Sea region contains a dark legacy of about 100 000 tons of dumped chemical warfare agents. As time passes the gun shells corrode and the risks of release of contaminants increase. A major goal of the EU-flagship project Daimon is to support governmental organisations with case-to-case adapted methods for sustainable management of dumped toxic munitions. At the Chalmers University of Technology, a partner of Daimon, a unique ISO 31000 adapted method was developed to provide decision support regarding potentially oilpolluting shipwrecks. The method is called VRAKA and is based on probability calculations. It includes site-specific information as well as expert knowledge. VRAKA is now being adapted to dumped chemical munitions. To estimate corrosion potential of gun shells and ship wrecks along with sediment re-suspension and transport multiparameter instruments are deployed at dump sites. Parameters measured include Currents, Salinity, Temperature, Oxygen, Depth, Waves and Suspended particles. These measurements have revealed how trawling at dump sites seems to have large implications in spreading toxic substances (Arsenic) over larger areas. This presentation will shortly describe the decision support model, the used instrumentation and discuss some of the obtain results.

Drought Monitoring with VegDRI

USGS Publications Warehouse

Brown, Jesslyn F.

2010-01-01

Drought strikes somewhere in the United States every year, turning green landscapes brown as precipitation falls below normal levels and water supplies dwindle. Drought is typically a temporary climatic aberration, but it is also an insidious natural hazard. It might last for weeks, months, or years and may have many negative effects. Drought can threaten crops, livestock, and livelihoods, stress wildlife and habitats, and increase wildfire risks and threats to human health. Drought conditions can vary tremendously from place to place and week to week. Accurate drought monitoring is essential to understand a drought's progression and potential effects, and to provide information necessary to support drought mitigation decisions. It is also crucial in light of climate change where droughts could become more frequent, severe, and persistent.

Optical sensors for water quality

USGS Publications Warehouse

Pellerin, Brian A.; Bergamaschi, Brian A.

2014-01-01

Recent advancements in commercially available in situ sensors, data platforms, and new techniques for data analysis provide an opportunity to monitor water quality in rivers, lakes, and estuaries on the time scales in which changes occur. For example, measurements that capture the variability in freshwater systems over time help to assess how shifts in seasonal runoff, changes in precipitation intensity, and increased frequencies of disturbances (such as fire and insect outbreaks) affect the storage, production, and transport of carbon and nitrogen in watersheds. Transmitting these data in real-time also provides information that can be used for early trend detection, help identify monitoring gaps, and provide sciencebased decision support across a range of issues related to water quality, freshwater ecosystems, and human health.

On-Line Modal State Monitoring of Slowly Time-Varying Structures

NASA Technical Reports Server (NTRS)

Johnson, Erik A.; Bergman, Lawrence A.; Voulgaris, Petros G.

1997-01-01

Monitoring the dynamic response of structures is often performed for a variety of reasons. These reasons include condition-based maintenance, health monitoring, performance improvements, and control. In many cases the data analysis that is performed is part of a repetitive decision-making process, and in these cases the development of effective on-line monitoring schemes help to speed the decision-making process and reduce the risk of erroneous decisions. This report investigates the use of spatial modal filters for tracking the dynamics of slowly time-varying linear structures. The report includes an overview of modal filter theory followed by an overview of several structural system identification methods. Included in this discussion and comparison are H-infinity, eigensystem realization, and several time-domain least squares approaches. Finally, a two-stage adaptive on-line monitoring scheme is developed and evaluated.

A model of human decision making in multiple process monitoring situations

NASA Technical Reports Server (NTRS)

Greenstein, J. S.; Rouse, W. B.

1982-01-01

Human decision making in multiple process monitoring situations is considered. It is proposed that human decision making in many multiple process monitoring situations can be modeled in terms of the human's detection of process related events and his allocation of attention among processes once he feels event have occurred. A mathematical model of human event detection and attention allocation performance in multiple process monitoring situations is developed. An assumption made in developing the model is that, in attempting to detect events, the human generates estimates of the probabilities that events have occurred. An elementary pattern recognition technique, discriminant analysis, is used to model the human's generation of these probability estimates. The performance of the model is compared to that of four subjects in a multiple process monitoring situation requiring allocation of attention among processes.

PREFER: a European service providing forest fire management support products

NASA Astrophysics Data System (ADS)

Eftychidis, George; Laneve, Giovanni; Ferrucci, Fabrizio; Sebastian Lopez, Ana; Lourenco, Louciano; Clandillon, Stephen; Tampellini, Lucia; Hirn, Barbara; Diagourtas, Dimitris; Leventakis, George

2015-06-01

PREFER is a Copernicus project of the EC-FP7 program which aims developing spatial information products that may support fire prevention and burned areas restoration decisions and establish a relevant web-based regional service for making these products available to fire management stakeholders. The service focuses to the Mediterranean region, where fire risk is high and damages from wildfires are quite important, and develop its products for pilot areas located in Spain, Portugal, Italy, France and Greece. PREFER aims to allow fire managers to have access to online resources, which shall facilitate fire prevention measures, fire hazard and risk assessment, estimation of fire impact and damages caused by wildfire as well as support monitoring of post-fire regeneration and vegetation recovery. It makes use of a variety of products delivered by space borne sensors and develop seasonal and daily products using multi-payload, multi-scale and multi-temporal analysis of EO data. The PREFER Service portfolio consists of two main suite of products. The first refers to mapping products for supporting decisions concerning the Preparedness/Prevention Phase (ISP Service). The service delivers Fuel, Hazard and Fire risk maps for this purpose. Furthermore the PREFER portfolio includes Post-fire vegetation recovery, burn scar maps, damage severity and 3D fire damage assessment products in order to support relative assessments required in context of the Recovery/Reconstruction Phase (ISR Service) of fire management.

Building a Shared Understanding of Phenology

NASA Astrophysics Data System (ADS)

Rosemartin, A.; Posthumus, E.; Gerst, K.

2017-12-01

The USA National Phenology Network (USA-NPN) seeks to advance the science of phenology and support the use of phenology information in decision-making. We envision that natural resource, human health, recreation and land-use decisions, in the context of a variable and changing climate, will be supported by USA-NPN products and tools. To achieve this vision we developed a logic model, breaking down the necessary inputs (e.g., IT infrastructure), participants, activities and the short- to long-term goals (e.g., use of phenological information in adaptive management). Here we compare the ongoing activities and outcomes of three recent collaborations to our logic model, in order to improve the model and inform future collaborations. At Midway Atoll National Wildlife Refuge, resource managers use the USA-NPN's phenology monitoring program to pinpoint the minimum number of days between initial growth and seed set in an invasive species. The data output and calendar visualizations that USA-NPN provides are sufficient to identify the appropriate treatment window. In contrast to a direct relationship with a natural resource manager using USA-NPN tools and products, some collaborations require substantive iterative work between partners. USA-NPN and National Park Service staff, along with academic researchers, assessed advancement in the timing of spring, and delivered the work in a format appropriate for park managers. Lastly, collaborations with indigenous communities reveal a requirement to reconsider the relationship between Western science and indigenous knowledge systems, as well as address ethical considerations and develop trust, before Western science can be meaningfully incorporated into decision-making. While the USA-NPN is a boundary organization, working in between federal agencies, states and universities, and is mandated to support decision-making, we still face challenges in generating usable science. We share lessons learned based on our experience with diverse and evolving partnerships.

Decision Support System For Management Of Low-Level Radioactive Waste Disposal At The Nevada Test Site

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

Shott, G.; Yucel, V.; Desotell, L.

2006-07-01

The long-term safety of U.S. Department of Energy (DOE) low-level radioactive disposal facilities is assessed by conducting a performance assessment -- a systematic analysis that compares estimated risks to the public and the environment with performance objectives contained in DOE Manual 435.1-1, Radioactive Waste Management Manual. Before site operations, facilities design features such as final inventory, waste form characteristics, and closure cover design may be uncertain. Site operators need a modeling tool that can be used throughout the operational life of the disposal site to guide decisions regarding the acceptance of problematic waste streams, new disposal cell design, environmental monitoringmore » program design, and final site closure. In response to these needs the National Nuclear Security Administration Nevada Site Office (NNSA/NSO) has developed a decision support system for the Area 5 Radioactive Waste Management Site in Frenchman Flat on the Nevada Test Site. The core of the system is a probabilistic inventory and performance assessment model implemented in the GoldSim{sup R} simulation platform. The modeling platform supports multiple graphic capabilities that allow clear documentation of the model data sources, conceptual model, mathematical implementation, and results. The combined models have the capability to estimate disposal site inventory, contaminant concentrations in environmental media, and radiological doses to members of the public engaged in various activities at multiple locations. The model allows rapid assessment and documentation of the consequences of waste management decisions using the most current site characterization information, radionuclide inventory, and conceptual model. The model is routinely used to provide annual updates of site performance, evaluate the consequences of disposal of new waste streams, develop waste concentration limits, optimize the design of new disposal cells, and assess the adequacy of environmental monitoring programs. (authors)« less

Measuring, managing and maximizing performance of mineral processing plants

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

Bascur, O.A.; Kennedy, J.P.

1995-12-31

The implementation of continuous quality improvement is the confluence of Total Quality Management, People Empowerment, Performance Indicators and Information Engineering. The supporting information technologies allow a mineral processor to narrow the gap between management business objectives and the process control level. One of the most important contributors is the user friendliness and flexibility of the personal computer in a client/server environment. This synergistic combination when used for real time performance monitoring translates into production cost savings, improved communications and enhanced decision support. Other savings come from reduced time to collect data and perform tedious calculations, act quickly with fresh newmore » data, generate and validate data to be used by others. This paper presents an integrated view of plant management. The selection of the proper tools for continuous quality improvement are described. The process of selecting critical performance monitoring indices for improved plant performance are discussed. The importance of a well balanced technological improvement, personnel empowerment, total quality management and organizational assets are stressed.« less

Towards a Global Wetland Observation System: The Geo-Wetlands Initiative

NASA Astrophysics Data System (ADS)

Strauch, Adrian; Geller, Gary; Grobicki, Ania; Hilarides, Lammert; Muro, Javier; Paganini, Marc; Weise, Kathrin

2016-08-01

Wetlands are hot spots of biodiversity and provide a wide range of valuable ecosystem services, but at the same time they globally are one of the fastest declining and most endangered ecosystems. The development of a Global Wetland Observation System (GWOS) that is supported by the Ramsar Convention on Wetlands since 2007 is seen as a step towards improved capabilities for global mapping, monitoring and assessment of wetland ecosystems and their services, status and trends. A newly proposed GEO-Wetlands initiative is taking up this effort and developing the necessary governance and management structures, a community of practice and the necessary scientific and technical outputs to set up this system and maintain it over the long term. This effort is aiming at directly supporting the needs of global conventions and monitoring frameworks as well as users of wetland information on all levels (local to global) to build a platform that provides a knowledge-hub as a baseline for informed ecosystem management and decision-making.

Influence of encoding focus and stereotypes on source monitoring event-related-potentials.

PubMed

Leynes, P Andrew; Nagovsky, Irina

2016-01-01

Source memory, memory for the origin of a memory, can be influenced by stereotypes and the information of focus during encoding processes. Participants studied words from two different speakers (male or female) using self-focus or other-focus encoding. Source judgments for the speaker׳s voice and Event-Related Potentials (ERPs) were recorded during test. Self-focus encoding increased dependence on stereotype information and the Late Posterior Negativity (LPN). The results link the LPN with an increase in systematic decision processes such as consulting prior knowledge to support an episodic memory judgment. In addition, other-focus encoding increased conditional source judgments and resulted in weaker old/new recognition relative to the self-focus encoding. The putative correlate of recollection (LPC) was absent during this condition and this was taken as evidence that recollection of partial information supported source judgments. Collectively, the results suggest that other-focus encoding changes source monitoring processing by altering the weight of specific memory features. Copyright © 2015 Elsevier B.V. All rights reserved.

Combined monitoring, decision and control model for the human operator in a command and control desk

NASA Technical Reports Server (NTRS)

Muralidharan, R.; Baron, S.

1978-01-01

A report is given on the ongoing efforts to mode the human operator in the context of the task during the enroute/return phases in the ground based control of multiple flights of remotely piloted vehicles (RPV). The approach employed here uses models that have their analytical bases in control theory and in statistical estimation and decision theory. In particular, it draws heavily on the modes and the concepts of the optimal control model (OCM) of the human operator. The OCM is being extended into a combined monitoring, decision, and control model (DEMON) of the human operator by infusing decision theoretic notions that make it suitable for application to problems in which human control actions are infrequent and in which monitoring and decision-making are the operator's main activities. Some results obtained with a specialized version of DEMON for the RPV control problem are included.

National ecosystem assessments supported by scientific and local knowledge

USGS Publications Warehouse

Herrick, Jeffrey E.; Lessard, Veronica C.; Spaeth, Kenneth E.; Shaver, Patrick L.; Dayton, Robert S.; Pyke, David A.; Jolley, Leonard; Goebel, J. Jeffery

2010-01-01

An understanding of the extent of land degradation and recovery is necessary to guide land-use policy and management, yet currently available land-quality assessments are widely known to be inadequate. Here, we present the results of the first statistically based application of a new approach to national assessments that integrates scientific and local knowledge. Qualitative observations completed at over 10 000 plots in the United States showed that while soil degradation remains an issue, loss of biotic integrity is more widespread. Quantitative soil and vegetation data collected at the same locations support the assessments and serve as a baseline for monitoring the effectiveness of policy and management initiatives, including responses to climate change. These results provide the information necessary to support strategic decisions by land managers and policy makers.

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

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

Information systems for health sector monitoring in Papua New Guinea.

PubMed Central

Cibulskis, R. E.; Hiawalyer, G.

2002-01-01

This paper describes (i). how a national health information System was designed, tested and implemented in Papua New Guinea, (ii). how the system was integrated with other management information systems, and (iii). how information has been used to support decision-making. It concludes that central coordination of systems design is essential to make sure that information systems are aligned with government priorities and can deliver the information required by managers. While there is often scope for improving the performance of existing information systems, too much emphasis can be placed on revising data collection procedures and creating the perfect information system. Data analysis, even from imperfect systems, can stimulate greater interest in information, which can improve the quality and completeness of reporting and encourage a more methodical approach to planning and monitoring services. Our experience suggests that senior decision-makers and political leaders can play an important role in creating a culture of information use. By demanding health information, using it to formulate policy, and disseminating it through the channels open to them, they can exert greater influence in negotiations with donors and other government departments, encourage a more rational approach to decision-making that will improve the operation of health services, and stimulate greater use of information at lower levels of the health system. The ability of information systems to deliver these benefits is critical to their sustainability. PMID:12378295

The Regional Land Cover Monitoring System: Building regional capacity through innovative land cover mapping approaches

NASA Astrophysics Data System (ADS)

Saah, D.; Tenneson, K.; Hanh, Q. N.; Aekakkararungroj, A.; Aung, K. S.; Goldstein, J.; Cutter, P. G.; Maus, P.; Markert, K. N.; Anderson, E.; Ellenburg, W. L.; Ate, P.; Flores Cordova, A. I.; Vadrevu, K.; Potapov, P.; Phongsapan, K.; Chishtie, F.; Clinton, N.; Ganz, D.

2017-12-01

Earth observation and Geographic Information System (GIS) tools, products, and services are vital to support the environmental decision making by governmental institutions, non-governmental agencies, and the general public. At the heart of environmental decision making is the monitoring land cover and land use change (LCLUC) for land resource planning and for ecosystem services, including biodiversity conservation and resilience to climate change. A major challenge for monitoring LCLUC in developing regions, such as Southeast Asia, is inconsistent data products at inconsistent intervals that have different typologies across the region and are typically made in without stakeholder engagement or input. Here we present the Regional Land Cover Monitoring System (RLCMS), a novel land cover mapping effort for Southeast Asia, implemented by SERVIR-Mekong, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries. The RLCMS focuses on mapping biophysical variables (e.g. canopy cover, tree height, or percent surface water) at an annual interval and in turn using those biophysical variables to develop land cover maps based on stakeholder definitions of land cover classes. This allows for flexible and consistent land cover classifications that can meet the needs of different institutions across the region. Another component of the RLCMS production is the stake-holder engagement through co-development. Institutions that directly benefit from this system have helped drive the development for regional needs leading to services for their specific uses. Examples of services for regional stakeholders include using the RLCMS to develop maps using the IPCC classification scheme for GHG emission reporting and developing custom annual maps as an input to hydrologic modeling/flood forecasting systems. In addition to the implementation of this system and the service stemming from the RLCMS in Southeast Asia, it is planned to replicate the methods presented at the SERVIR-Hindu Kush Himalaya hub serving South Asia. Enhancements to the system will include change detection methods, enhanced biophysical models, and delivery systems.

Localizing drought monitoring products to support agricultural climate service advisories in South Asia

NASA Astrophysics Data System (ADS)

Qamer, F. M.; Matin, M. A.; Yadav, N. K.; Bajracharya, B.; Zaitchik, B. F.; Ellenburg, W. L.; Krupnik, T. J.; Hussain, G.

2017-12-01

The Fifth Assessment Report of the Intergovernmental Panel on Climate Change identifies drought as one of the major climate risks in South Asia. During past two decades, a large amount of climate data have been made available by the scientific community, but the deployment of climate information for local level and agricultural decision making remains less than optimal. The provisioning of locally calibrated, easily accessible, decision-relevant and user-oriented information, in the form of drought advisory service could help to prepare communities to reduce climate vulnerability and increase resilience. A collaborative effort is now underway to strengthen existing and/or establish new drought monitoring and early warning systems in Afghanistan, Bangladesh, Nepal and Pakistan by incorporating standard ground-based observations, earth observation datasets, and numerical forecast models. ICT-based agriculture drought monitoring platforms, hosted at national agricultural and meteorological institutions, are being developed and coupled with communications and information deployment strategies to enable the rapid and efficient deployment of information that farmers can understand, interpret, and act on to adapt to anticipated droughts. Particular emphasis is being placed on the calibration and validation of data products through retrospective analysis of time series data, in addition to the installation of automatic weather station networks. In order to contextualize monitoring products to that they may be relevant for farmers' primary cropping systems, district level farming practices calendars are being compiled and validated through focus groups and surveys to identify the most important times and situations during which farmers can adapt to drought. High-resolution satellite crop distribution maps are under development and validation to add value to these efforts. This programme also aims to enhance capacity of agricultural extension staff to better understand climate information, probabilistic forecasts, related technologies, and adaptation strategies, in addition to equipping them with increased capacity to convey drought risks to farmers and improve climate related decision making.

Efforts Toward an Early Warning Crop Monitor for Countries at Risk

NASA Astrophysics Data System (ADS)

Budde, M. E.; Verdin, J. P.; Barker, B.; Humber, M. L.; Becker-Reshef, I.; Justice, C. O.; Magadzire, T.; Galu, G.; Rodriguez, M.; Jayanthi, H.

2015-12-01

Assessing crop growing conditions is a crucial aspect of monitoring food security in the developing world. One of the core components of the Group on Earth Observations - Global Agricultural Monitoring (GEOGLAM) targets monitoring Countries at Risk (component 3). The Famine Early Warning Systems Network (FEWS NET) has a long history of utilizing remote sensing and crop modeling to address food security threats in the form of drought, floods, pest infestation, and climate change in some of the world's most at risk countries. FEWS NET scientists at the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center and the University of Maryland Department of Geography have undertaken efforts to address component 3, by promoting the development of a collaborative Early Warning Crop Monitor (EWCM) that would specifically address Countries at Risk. A number of organizations utilize combinations of satellite earth observations, field campaigns, network partner inputs, and crop modeling techniques to monitor crop conditions throughout the world. Agencies such as the Food and Agriculture Organization of the United Nations (FAO), United Nations World Food Programme (WFP), and the European Commission's Joint Research Centre (JRC) provide agricultural monitoring information and reporting across a broad number of areas at risk and in many cases, organizations routinely report on the same countries. The latter offers an opportunity for collaboration on crop growing conditions among agencies. The reduction of uncertainty and achievement of consensus will help strengthen confidence in decisions to commit resources for mitigation of acute food insecurity and support for resilience and development programs. In addition, the development of a collaborative global EWCM will provide each of the partner agencies with the ability to quickly gather crop condition information for areas where they may not typically work or have access to local networks. Using a framework developed by GEOGLAM for monitoring crop conditions in support of the Agricultural Market Information System, we developed an EWCM system for countries at risk. We present the current status of that implementation and highlight achievements to date along with future plans to support the needs of the global agricultural monitoring community.

Development of the Supported Decision Making Inventory System.

PubMed

Shogren, Karrie A; Wehmeyer, Michael L; Uyanik, Hatice; Heidrich, Megan

2017-12-01

Supported decision making has received increased attention as an alternative to guardianship and a means to enable people with intellectual and developmental disabilities to exercise their right to legal capacity. Assessments are needed that can used by people with disabilities and their systems of supports to identify and plan for needed supports to enable decision making. This article describes the steps taken to develop such an assessment tool, the Supported Decision Making Inventory System (SDMIS), and initial feedback received from self-advocates with intellectual disability. The three sections of the SDMIS (Supported Decision Making Personal Factors Inventory, Supported Decision Making Environmental Demands Inventory, and Decision Making Autonomy Inventory) are described and implications for future research, policy, and practice are discussed.

Towards an internal model in pilot training.

PubMed

Braune, R J; Trollip, S R

1982-10-01

Optimal decision making requires an information seeking behavior which reflects the comprehension of the overall system dynamics. Research in the area of human monitors in man-machine systems supports the notion of an internal model with built-in expectancies. It is doubtful that the current approach to pilot training helps develop this internal model in the most efficient way. But this is crucial since the role of the pilot is changing to a systems' manager and decision maker. An extension of the behavioral framework of pilot training might help to prepare the pilot better for the increasingly complex flight environment. This extension is based on the theoretical model of schema theory, which evolved out of psychological research. The technological advances in aircraft simulators and in-flight performance measurement devices allow investigation of the still-unresolved issues.

Using Bayesian networks to support decision-focused information retrieval

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

Lehner, P.; Elsaesser, C.; Seligman, L.

This paper has described an approach to controlling the process of pulling data/information from distributed data bases in a way that is specific to a persons specific decision making context. Our prototype implementation of this approach uses a knowledge-based planner to generate a plan, an automatically constructed Bayesian network to evaluate the plan, specialized processing of the network to derive key information items that would substantially impact the evaluation of the plan (e.g., determine that replanning is needed), automated construction of Standing Requests for Information (SRIs) which are automated functions that monitor changes and trends in distributed data base thatmore » are relevant to the key information items. This emphasis of this paper is on how Bayesian networks are used.« less

Development and implementation of sepsis alert systems

PubMed Central

Harrison, Andrew M.; Gajic, Ognjen; Pickering, Brian W.; Herasevich, Vitaly

2016-01-01

Synopsis/Summary Development and implementation of sepsis alert systems is challenging, particularly outside the monitored intensive care unit (ICU) setting. Important barriers to wider use of sepsis alerts include evolving clinical definitions of sepsis, information overload & alert fatigue, due to suboptimal alert performance. Outside the ICU, additional barriers include differences in health care delivery models, charting behaviors, and availability of electronic data. Currently available evidence does not support routine use of sepsis alert systems in clinical practice. However, continuous improvement in both the afferent (data availability and accuracy of detection algorithms) and efferent (evidence-based decision support and smoother integration into clinical workflow) limbs of sepsis alert systems will help translate theoretical advantages into measurable patient benefit. PMID:27229639

Useful Life Prediction for Payload Carrier Hardware

NASA Technical Reports Server (NTRS)

Ben-Arieh, David

2002-01-01

The Space Shuttle has been identified for use through 2020. Payload carrier systems will be needed to support missions through the same time frame. To support the future decision making process with reliable systems, it is necessary to analyze design integrity, identify possible sources of undesirable risk and recognize required upgrades for carrier systems. This project analyzed the information available regarding the carriers and developed the probability of becoming obsolete under different scenarios. In addition, this project resulted in a plan for an improved information system that will improve monitoring and control of the various carriers. The information collected throughout this project is presented in this report as process flow, historical records, and statistical analysis.

Comparison of Computer-based Clinical Decision Support Systems and Content for Diabetes Mellitus.

PubMed

Kantor, M; Wright, A; Burton, M; Fraser, G; Krall, M; Maviglia, S; Mohammed-Rajput, N; Simonaitis, L; Sonnenberg, F; Middleton, B

2011-01-01

Computer-based clinical decision support (CDS) systems have been shown to improve quality of care and workflow efficiency, and health care reform legislation relies on electronic health records and CDS systems to improve the cost and quality of health care in the United States; however, the heterogeneity of CDS content and infrastructure of CDS systems across sites is not well known. We aimed to determine the scope of CDS content in diabetes care at six sites, assess the capabilities of CDS in use at these sites, characterize the scope of CDS infrastructure at these sites, and determine how the sites use CDS beyond individual patient care in order to identify characteristics of CDS systems and content that have been successfully implemented in diabetes care. We compared CDS systems in six collaborating sites of the Clinical Decision Support Consortium. We gathered CDS content on care for patients with diabetes mellitus and surveyed institutions on characteristics of their site, the infrastructure of CDS at these sites, and the capabilities of CDS at these sites. The approach to CDS and the characteristics of CDS content varied among sites. Some commonalities included providing customizability by role or user, applying sophisticated exclusion criteria, and using CDS automatically at the time of decision-making. Many messages were actionable recommendations. Most sites had monitoring rules (e.g. assessing hemoglobin A1c), but few had rules to diagnose diabetes or suggest specific treatments. All sites had numerous prevention rules including reminders for providing eye examinations, influenza vaccines, lipid screenings, nephropathy screenings, and pneumococcal vaccines. Computer-based CDS systems vary widely across sites in content and scope, but both institution-created and purchased systems had many similar features and functionality, such as integration of alerts and reminders into the decision-making workflow of the provider and providing messages that are actionable recommendations.