Science.gov

Sample records for allocation decisions based

  1. Administrators' Decisions about Resource Allocation

    ERIC Educational Resources Information Center

    Knight, William E.; Folkins, John W.; Hakel, Milton D.; Kennell, Richard P.

    2011-01-01

    Do academic administrators make decisions about resource allocation differently depending on the discipline receiving the funding? Does an administrator's academic identity influence these decisions? This study explored those questions with a sample of 1,690 academic administrators at doctoral-research universities. Participants used fictional…

  2. Performance Ratio Based Resource Allocation Decision-Making in Genomic Medicine.

    PubMed

    Fragoulakis, Vasilios; Mitropoulou, Christina; Katelidou, Daphne; van Schaik, Ron H; Maniadakis, Nikolaos; Patrinos, George P

    2017-02-01

    In modern healthcare systems, the available resources may influence the morbidity, mortality, and-consequently-the level of healthcare provided in every country. This is of particular interest in developing countries where the resources are limited and must be spent wisely to address social justice and the right for equal access in healthcare services by all the citizens in economically viable terms. In this light, the current allocation is, in practice, inefficient and rests mostly on each country's individual political and historical context and, thus, does not always incorporate decision-making enabled by economic models. In this study, we present a new economic model, specifically for resource allocation for genomic medicine, based on performance ratio, with potential applications in diverse healthcare sectors, which are particularly appealing for developing countries and low-resource environments. The model proposes a new method for resource allocation taking into account (1) the size of innovation of a new technology, (2) the relative effectiveness in comparison with social preferences, and (3) the cost of the technology, which permits the measurement of effectiveness to be determined differently in the context of a specific disease and then to be expressed in a relative form using a common performance ratio. The present work expands on previous work for innovation in economic models pertaining to genomic medicine and supports translational science.

  3. A Web-based graphical user interface for evidence-based decision making for health care allocations in rural areas

    PubMed Central

    Schuurman, Nadine; Leight, Margo; Berube, Myriam

    2008-01-01

    Background The creation of successful health policy and location of resources increasingly relies on evidence-based decision-making. The development of intuitive, accessible tools to analyse, display and disseminate spatial data potentially provides the basis for sound policy and resource allocation decisions. As health services are rationalized, the development of tools such graphical user interfaces (GUIs) is especially valuable at they assist decision makers in allocating resources such that the maximum number of people are served. GIS can used to develop GUIs that enable spatial decision making. Results We have created a Web-based GUI (wGUI) to assist health policy makers and administrators in the Canadian province of British Columbia make well-informed decisions about the location and allocation of time-sensitive service capacities in rural regions of the province. This tool integrates datasets for existing hospitals and services, regional populations and road networks to allow users to ascertain the percentage of population in any given service catchment who are served by a specific health service, or baskets of linked services. The wGUI allows policy makers to map trauma and obstetric services against rural populations within pre-specified travel distances, illustrating service capacity by region. Conclusion The wGUI can be used by health policy makers and administrators with little or no formal GIS training to visualize multiple health resource allocation scenarios. The GUI is poised to become a critical decision-making tool especially as evidence is increasingly required for distribution of health services. PMID:18793428

  4. Irrational time allocation in decision-making

    PubMed Central

    Oud, Bastiaan; Krajbich, Ian; Miller, Kevin; Cheong, Jin Hyun; Botvinick, Matthew; Fehr, Ernst

    2016-01-01

    Time is an extremely valuable resource but little is known about the efficiency of time allocation in decision-making. Empirical evidence suggests that in many ecologically relevant situations, decision difficulty and the relative reward from making a correct choice, compared to an incorrect one, are inversely linked, implying that it is optimal to use relatively less time for difficult choice problems. This applies, in particular, to value-based choices, in which the relative reward from choosing the higher valued item shrinks as the values of the other options get closer to the best option and are thus more difficult to discriminate. Here, we experimentally show that people behave sub-optimally in such contexts. They do not respond to incentives that favour the allocation of time to choice problems in which the relative reward for choosing the best option is high; instead they spend too much time on problems in which the reward difference between the options is low. We demonstrate this by showing that it is possible to improve subjects' time allocation with a simple intervention that cuts them off when their decisions take too long. Thus, we provide a novel form of evidence that organisms systematically spend their valuable time in an inefficient way, and simultaneously offer a potential solution to the problem. PMID:26763695

  5. Machine learning-based coding unit depth decisions for flexible complexity allocation in high efficiency video coding.

    PubMed

    Zhang, Yun; Kwong, Sam; Wang, Xu; Yuan, Hui; Pan, Zhaoqing; Xu, Long

    2015-07-01

    In this paper, we propose a machine learning-based fast coding unit (CU) depth decision method for High Efficiency Video Coding (HEVC), which optimizes the complexity allocation at CU level with given rate-distortion (RD) cost constraints. First, we analyze quad-tree CU depth decision process in HEVC and model it as a three-level of hierarchical binary decision problem. Second, a flexible CU depth decision structure is presented, which allows the performances of each CU depth decision be smoothly transferred between the coding complexity and RD performance. Then, a three-output joint classifier consists of multiple binary classifiers with different parameters is designed to control the risk of false prediction. Finally, a sophisticated RD-complexity model is derived to determine the optimal parameters for the joint classifier, which is capable of minimizing the complexity in each CU depth at given RD degradation constraints. Comparative experiments over various sequences show that the proposed CU depth decision algorithm can reduce the computational complexity from 28.82% to 70.93%, and 51.45% on average when compared with the original HEVC test model. The Bjøntegaard delta peak signal-to-noise ratio and Bjøntegaard delta bit rate are -0.061 dB and 1.98% on average, which is negligible. The overall performance of the proposed algorithm outperforms those of the state-of-the-art schemes.

  6. Healthcare resource allocation decisions affecting uninsured services

    PubMed Central

    Harrison, Krista Lyn; Taylor, Holly A.

    2017-01-01

    Purpose Using the example of community access programs (CAPs), the purpose of this paper is to describe resource allocation and policy decisions related to providing health services for the uninsured in the USA and the organizational values affecting these decisions. Design/methodology/approach The study used comparative case study methodology at two geographically diverse sites. Researchers collected data from program documents, meeting observations, and interviews with program stakeholders. Findings Five resource allocation or policy decisions relevant to providing healthcare services were described at each site across three categories: designing the health plan, reacting to funding changes, and revising policies. Organizational values of access to care and stewardship most frequently affected resource allocation and policy decisions, while economic and political pressures affect the relative prioritization of values. Research limitations/implications Small sample size, the potential for social desirability or recall bias, and the exclusion of provider, member or community perspectives beyond those represented among participating board members. Practical implications Program directors or researchers can use this study to assess the extent to which resource allocation and policy decisions align with organizational values and mission statements. Social implications The description of how healthcare decisions are actually made can be matched with literature that describes how healthcare resource decisions ought to be made, in order to provide a normative grounding for future decisions. Originality/value This study addresses a gap in literature regarding how CAPs actually make resource allocation decisions that affect access to healthcare services. PMID:27934550

  7. Funding Based on Needs? A Study on the Use of Needs Assessment Data by a Major Humanitarian Health Assistance Donor in its Decisions to Allocate Funds

    PubMed Central

    Olin, Emma; von Schreeb, Johan

    2014-01-01

    Background: International humanitarian assistance is essential for disaster-affected populations, particularly in resource scarce settings. To target such assistance, needs assessments are required. According to internationally endorsed principles, donor governments should provide funding for humanitarian assistance based on need. Aim: The aim of this study is to explore a major donor’s use of needs assessment data in decision-making for allocations of funds for health-related humanitarian assistance contributions. Setting: This is a case study of the Swedish International Development Cooperation Agency (Sida), a major and respected international donor of humanitarian assistance. Methods: To explore Sida’s use of needs assessment data in practice for needs-based allocations, we reviewed all decision documents and assessment memoranda for humanitarian assistance contributions for 2012 using content analysis; this was followed by interviews with key personnel at Sida. Results: Our document analysis found that needs assessment data was not systematically included in Sida’s assessment memoranda and decision documents. In the interviews, we observed various descriptions of the concept of needs assessments, the importance of contextual influences as well as previous collaborations with implementing humanitarian assistance organizations. Our findings indicate that policies guiding funding decisions on humanitarian assistance need to be matched with available needs assessment data and that terminologies and concepts have to be clearly defined. Conclusion: Based on the document analysis and the interviews, it is unclear how well Sida used needs assessment data for decisions to allocate funds. However, although our observations show that needs assessments are seldom used in decision making, Sida’s use of needs assessments has improved compared to a previous study. To improve project funds allocations based on needs assessment data, it will be critical to develop

  8. Risk-based decision making for staggered bioterrorist attacks : resource allocation and risk reduction in "reload" scenarios.

    SciTech Connect

    Lemaster, Michelle Nicole; Gay, David M.; Ehlen, Mark Andrew; Boggs, Paul T.; Ray, Jaideep

    2009-10-01

    Staggered bioterrorist attacks with aerosolized pathogens on population centers present a formidable challenge to resource allocation and response planning. The response and planning will commence immediately after the detection of the first attack and with no or little information of the second attack. In this report, we outline a method by which resource allocation may be performed. It involves probabilistic reconstruction of the bioterrorist attack from partial observations of the outbreak, followed by an optimization-under-uncertainty approach to perform resource allocations. We consider both single-site and time-staggered multi-site attacks (i.e., a reload scenario) under conditions when resources (personnel and equipment which are difficult to gather and transport) are insufficient. Both communicable (plague) and non-communicable diseases (anthrax) are addressed, and we also consider cases when the data, the time-series of people reporting with symptoms, are confounded with a reporting delay. We demonstrate how our approach develops allocations profiles that have the potential to reduce the probability of an extremely adverse outcome in exchange for a more certain, but less adverse outcome. We explore the effect of placing limits on daily allocations. Further, since our method is data-driven, the resource allocation progressively improves as more data becomes available.

  9. The Role of Research and Analysis in Resource Allocation Decisions

    ERIC Educational Resources Information Center

    Lea, Dennis; Polster, Patty Poppe

    2011-01-01

    In a time of diminishing resources and increased accountability, it is important for school leaders to make the most of every dollar they spend. One approach to ensuring responsible resource allocation is to closely examine the organizational culture surrounding decision making and provide a structure and process to incorporate research and data…

  10. Valuing certainty in a consensus-based water allocation mechanism

    NASA Astrophysics Data System (ADS)

    Pande, Saket; McKee, Mac

    2007-02-01

    We present an interdisciplinary approach to attach economic value to model certainty. The central theme of this paper concerns valuing certainty in water resource management, specifically resource allocation. A conceptual framework is developed to study (1) a hypothetical scenario of three water users attempting to mutually agree on allocation of some fixed amount of water amongst themselves and (2) California water policy negotiations along the lines of Adams et al. (1996). We attempt to answer how uncertainty in a policy variable affects the "allocation solution" in such consensus-based decision-making processes. This study finally evolves into economic valuation of uncertainty reduction and willingness to pay for the same.

  11. [Strategic decisions in public psychiatric institutions: a proposed method for resource analysis and allocation].

    PubMed

    Micheletti, Pierre; Chierici, Piero; Durang, Xavier; Salvador, Nathalie; Lopez, Nathalie

    2011-01-01

    Because of its sector-based organization and extra-hospital care, public psychiatry has a unique position in healthcare. This paper describes the tools and procedures used to analyze and allocate the resources of the "Centre Hospitalier Alpes-Isère", a hospital serving a catchment population of 530,000 adults. A consensus-based approach was used to validate the selected indicators and included the participation of a geographer. Five levels of resource allocation were identified and classified using a decision tree. At each level, the relevant authorities and criteria were identified as key components of the decision-making process. This paper describes the first three levels of care provision. Focusing on adult care, a comparative assessment of the resources allocated to general psychiatric care and specialist care was conducted, in addition to a comparative assessment of the resources allocated to each of the hospital's four local centers. Geographical accessibility to extramural facilities was also assessed. A study of the characteristics of each general psychiatry clinic revealed significant disparities. The paper highlights several issues: the poor knowledge of psychiatric epidemiological data relating to the population within the catchment area, the difficulty of assessing non-consolidated data or indicators from multiple sources, and the limited and partial nature of geographical data for characterizing and evaluating health care in the hospital's peripheral clinics. Several studies are currently underway to assess the operational effectiveness of the tools and procedures used to analyze and allocate resources.

  12. Soldier Decision-Making for Allocation of Intelligence, Surveillance, and Reconnaissance Assets

    DTIC Science & Technology

    2014-06-01

    decisions by assigning ISR platform sensors to simplified target detection and identification tasks. The objective, or algorithmic accuracy of the decisions...allocation tasks. Soldiers made decisions by assigning ISR platform sensors to simplified target detection and identification tasks. The objective...ISR allocation, which is the assignment of assets to target detection and identification tasks, for physical sensors on aerial platforms. Military

  13. 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

  14. Adaptive Allocation of Decision Making Responsibility Between Human and Computer in Multi-Task Situations. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Chu, Y. Y.

    1978-01-01

    A unified formulation of computer-aided, multi-task, decision making is presented. Strategy for the allocation of decision making responsibility between human and computer is developed. The plans of a flight management systems are studied. A model based on the queueing theory was implemented.

  15. Impact of one or two visits strategy on hypertension burden estimation in HYDY, a population-based cross-sectional study: implications for healthcare resource allocation decision making

    PubMed Central

    Modesti, Pietro Amedeo; Rapi, Stefano; Bamoshmoosh, Mohamed; Baldereschi, Marzia; Massetti, Luciano; Padeletti, Luigi; Gensini, Gian Franco; Zhao, Dong; Al-Hidabi, Dawood; Al Goshae, Husni

    2012-01-01

    Context The prevalence of hypertension in developing countries is coming closer to values found in developed countries. However, surveys usually rely on readings taken at a single visit, the option to implement the diagnosis on readings taken at multiple visits, being limited by costs. Objective To estimate more accurately the magnitude and extent of the resource that should be allocated to the prevention of hypertension. Design Population-based cross-sectional survey with triplicate blood pressure (BP) readings taken on two separate home-visits. Setting Rural and urban locations in three areas of Yemen (capital, inland and coast). Participants A nationally representative sample of the Yemen population aged 15–69 years (5063 men and 5179 women), with an overall response rate of 92% in urban and 94% in rural locations. Main outcome measure Hypertension diagnosed as systolic BP ≥140 mm Hg and/or diastolic BP ≥90 mm Hg and/or self-reported use of antihypertensive drugs. Results Hypertension prevalence (age-standardised to the WHO world population 2001) based on fulfilling the same criteria on both visits (11.3%; 95% Cl 10.7% to 11.9%), was 35% lower than estimation based on the first visit (17.3%; 16.5% to 18.0%). Advanced age, blood glucose ≥7 mmol/l or proteinuria ≥1+ at dipstick test at visit one were significant predictors of confirmation at visit 2. The 959 participants found to be hypertensive at visit 1 or at visit 2 only and thus excluded from the final diagnosis had a rate of proteinuria (5.0%; 3.8% to 6.5%) comparable to rates of the general population (6.1%; 5.6% to 6.6%), and of subjects normotensive at both visits (5.6%; 5.1% to 6.2%). Only 1.9% of Yemen population classified at high or very high cardiovascular (CV) risk at visit 1 moved to average, low or moderate CV risk categories after two visits. Conclusions Hypertension prevalence based on readings obtained after two visits is 35% lower than estimation based on the first visit

  16. A spatial decision support tool for estimating population catchments to aid rural and remote health service allocation planning.

    PubMed

    Schuurman, Nadine; Randall, Ellen; Berube, Myriam

    2011-12-01

    There is mounting pressure on healthcare planners to manage and contain costs. In rural regions, there is a particular need to rationalize health service allocation to ensure the best possible coverage for a dispersed population. Rural health administrators need to be able to quantify the population affected by their allocation decisions and, therefore, need the capacity to incorporate spatial analyses into their decision-making process. Spatial decision support systems (SDSS) can provide this capability. In this article, we combine geographical information systems (GIS) with a web-based graphical user interface (webGUI) in a SDSS tool that enables rural decision-makers charged with service allocation, to estimate population catchments around specific health services in rural and remote areas. Using this tool, health-care planners can model multiple scenarios to determine the optimal location for health services, as well as the number of people served in each instance.

  17. An Optimization Model for the Allocation of University Based Merit Aid

    ERIC Educational Resources Information Center

    Sugrue, Paul K.

    2010-01-01

    The allocation of merit-based financial aid during the college admissions process presents postsecondary institutions with complex and financially expensive decisions. This article describes the application of linear programming as a decision tool in merit based financial aid decisions at a medium size private university. The objective defined for…

  18. An Analysis of Shelf Space Allocation at the Wright-Patterson Air Force Base Commissary.

    DTIC Science & Technology

    1987-09-01

    techniques, the allocation of shelf space decisions differ. Management can get many different allocations, depending on the way the data are defined and tne...oe associated witn change in facings made during the reallocation. Population Tne population under study is defined as t.le daily sales of products in...the available space will be allocated equally among the products based on turnover ratio. Turnover is defined as product sold divided by product

  19. [Allocating resources for cancer control--resolving multicriteria decision-making using the analytic hierarchy process].

    PubMed

    Gróf, Agnes

    2007-01-01

    When competing programs ought to be financed simultaneously for the same purpose, an allocation problem occurs due to scarce resources, and different perspectives and preferences. Facing the problem needs determining criteria which the decision might be based on. Those criteria form the objectives (the scope) of the different participants, and are relevant for the achievement of the goal, providing a comprehensive resource allocation that bridges and integrates the different perspectives. In case of cancer control primary prevention, secondary prevention, therapy and tertiary prevention, education, basic sciences, and clinical trials form the alternatives. An analytic hierarchy process (AHP) is used for supporting decision-making in the resource allocation problem. AHP is a method for setting priorities, but can only work out the implications of what was declared through the pairwise-ranking process, namely the relative preferences, weighing the criteria and rating the alternatives two by two. In the first analysis the relative weights to criteria were 0.099 for 'distributive justice'; 0.120 for constitutional and human rights; 0.251 for lay opinion; 0.393 for EBM; 0.137 for cost-effectiveness. Ranking the alternatives using 'judgements' resulted in relative preference of 0.238 for therapy, 0.204 for primary prevention, 0.201 for secondary prevention, 0.135 for clinical trials, 0.111 for tertiary prevention, 0.066 for basic sciences and 0.045 for education. In the second analysis the relative importance of "cost-effectiveness" was doubled, thus resulting in 0.234 for therapy, 0.216 for secondary prevention, 0.183 for primary prevention, 0.145 for clinical trials, 0.113 for tertiary prevention, 0.063 for basic sciences and 0.046 for education. Sensitivity analysis has shown that increasing the relative weight of cost-effectiveness up to approximately 0.4 changes the rank of alternatives, and above 0.4 this criterion gives secondary prevention preferences. According

  20. 47 CFR 69.502 - Base factor allocation.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 47 Telecommunication 3 2014-10-01 2014-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that...

  1. 47 CFR 69.502 - Base factor allocation.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 3 2010-10-01 2010-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that...

  2. 47 CFR 69.502 - Base factor allocation.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 47 Telecommunication 3 2013-10-01 2013-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that...

  3. 47 CFR 69.502 - Base factor allocation.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 3 2012-10-01 2012-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that...

  4. 47 CFR 69.502 - Base factor allocation.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 3 2011-10-01 2011-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that...

  5. How SmithKline Beecham makes better resource-allocation decisions.

    PubMed

    Sharpe, P; Keelin, T

    1998-01-01

    Major resource-allocation decisions are never easy. For a pharmaceuticals company like SmithKline Beecham, the problem is this: How do you make good decisions in a high-risk, technically complex business when the information you need to make those decisions comes largely from the project champions who are competing against one another for resources? In 1993, the company experimented with ways of depoliticizing the process and improving the quality of decision making. In most resource-allocation processes, project advocates develop a single plan of action and present it as the only viable approach. In SB's new process, the company found an effective way to get around the all-or-nothing thinking that only reinforces the project-champion culture. Project teams were required--and helped--to create meaningful alternatives to current development plans. What would they do with more money? With less? With none at all? In another important departure from common practice, SB separated the discussion of project alternatives from their financial evaluations. In doing so, SB was able to avoid the premature evaluations that kill both creativity and the opportunity to improve decision making. The new process at SB has allowed the organization to spend less time arguing about how to value its R&D projects and more time figuring out how to make them more valuable. In the end, the company learned that by tackling the soft issues around resource allocation--such as information quality, credibility, and trust--it had also addressed the hard ones: how much to invest and where to invest it.

  6. 78 FR 19518 - Notice of Availability of Approved Land Use Plan Amendments/Record of Decision for Allocation of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-01

    ... for Allocation of Oil Shale and Tar Sands Resources on Lands Administered by the Bureau of Land... Use Plan Amendments/Record of Decision (ROD) for Allocation of Oil Shale and Tar Sands Resources on... plan in the Final Oil Shale and Tar Sands Programmatic Environmental Impact Statement (EIS), as...

  7. Sustainability Based Decision Making

    EPA Science Inventory

    With sustainability as the “true north” for EPA research, a premium is placed on the ability to make decisions under highly complex and uncertain conditions. The primary challenge is reconciling disparate criteria toward credible and defensible decisions. Making decisions on on...

  8. Allocating resources and building confidence in public-safety decisions for nuclear waste sites

    SciTech Connect

    Lew, K L; Wilder, D G

    1999-05-21

    There are three basic ways to protect the public from the hazards of exposure to radionuclides in nuclear waste: completely contain the waste; limit the rate at which radionuclides are released; and, once radionuclides are released, minimize their impact by reducing concentrations and retarding transport. A geologic repository system that implements all three provides maximum protection for the public: if one element fails, the others serve to protect. This is ''defense-in-depth.'' Demonstrating confidence in the ability of a designed system to provide the requisite safety to the public must rely on a combination of the following aspects relating to engineered and natural system components: 1 Knowledge or understanding of properties and processes 2 Uniformity of (or ability to understand or control) the range of variability associated with each component 3 Experience over time This paper proposes a tool based on defining a ''confidence region'' determined by these three essential aspects of confidence. The defense-in-depth decision-making tool described identifies the portion of the ultimate confidence region that is not well demonstrated and indicates where there is potential for changing a specific component's confidence region, therefore providing in-formation for decisions on emphasis--either for demonstrating performance or for focusing on further studies. The US Yucca Mountain Site Characterization Project (YMP), wherein Yucca Mountain is being investigated as a potential site for a nuclear waste repository, and the Swedish geologic repository studies are used as examples of this tool. of protective or operating components such that failure of a single component does not by itself lead to system failure. The greater the exposure to loss, the greater the requirements for design margins (the margin of conservatism associated with the fabrication and operation of important components in complex engineering projects) or for compensation by defense-in-depth. Thus

  9. Two-stage seasonal streamflow forecasts to guide water resources decisions and water rights allocation

    NASA Astrophysics Data System (ADS)

    Block, P. J.; Gonzalez, E.; Bonnafous, L.

    2011-12-01

    Decision-making in water resources is inherently uncertain producing copious risks, ranging from operational (present) to planning (season-ahead) to design/adaptation (decadal) time-scales. These risks include human activity and climate variability/change. As the risks in designing and operating water systems and allocating available supplies vary systematically in time, prospects for predicting and managing such risks become increasingly attractive. Considerable effort has been undertaken to improve seasonal forecast skill and advocate for integration to reduce risk, however only minimal adoption is evident. Impediments are well defined, yet tailoring forecast products and allowing for flexible adoption assist in overcoming some obstacles. The semi-arid Elqui River basin in Chile is contending with increasing levels of water stress and demand coupled with insufficient investment in infrastructure, taxing its ability to meet agriculture, hydropower, and environmental requirements. The basin is fed from a retreating glacier, with allocation principles founded on a system of water rights and markets. A two-stage seasonal streamflow forecast at leads of one and two seasons prescribes the probability of reductions in the value of each water right, allowing water managers to inform their constituents in advance. A tool linking the streamflow forecast to a simple reservoir decision model also allows water managers to select a level of confidence in the forecast information.

  10. Evidence-based medicine: a new tool for resource allocation?

    PubMed

    Nunes, Rui

    2003-01-01

    Evidence-Based Medicine (EBM) is defined as the conscious, and judicious use of current best evidence in making decisions about the care of individual patients. The greater the level of evidence the greater the grade of recommendation. This pioneering explicit concept of EBM is embedded in a particular view of medical practice namely the singular nature of the patient-physician relation and the commitment of the latter towards a specific goal: the treatment and the well being of his or her client. Nevertheless, in many European countries as well as in the United States, this "integration of the best evidence from systematic research with clinical expertise and patient values" appears to be re-interpreted in light of the scarcity of healthcare resources. The purpose of this paper is double. First, to claim that from an ethical perspective EBM should be a guideline to clinical practice; and second, that in specific circumstances EBM might be a useful tool in macro-allocation of healthcare resources. Methodologically the author follows Norman Daniels' theory of "democratic accountability" to justify this assumption. That is, choices in healthcare must be accountable by democratic procedures. This perspective of distributive justice is responsible for the scope and limits of healthcare services. It follows that particular entitlements to healthcare--namely expensive innovative treatments and medicines--may be fairly restricted as long as this decision is socially and democratically accountable and imposed by financial restrictions of the system. In conclusion, the implementation of EBM, as long as it limits the access to drugs and treatments of unproven scientific results is in accordance with this perspective. The use of EBM is regarded as an instrument to facilitate the access of all citizens to a reasonable level of healthcare and to promote the efficiency of the system.

  11. Decisions Based on Science.

    ERIC Educational Resources Information Center

    Campbell, Vincent; Lofstrom, Jocelyn; Jerome, Brian

    This guide makes the case for a decision-making focus in the science curriculum as a response to concern over preparing scientifically literate students. The student activities are organized by guided activities and independent exercises. Themes of the guided activities include xenotransplants, immunizations, household cleaning products, ozone,…

  12. The use of the Dutch Self-Sufficiency Matrix (SSM-D) to inform allocation decisions to public mental health care for homeless people.

    PubMed

    Lauriks, Steve; de Wit, Matty A S; Buster, Marcel C A; Fassaert, Thijs J L; van Wifferen, Ron; Klazinga, Niek S

    2014-10-01

    The current study set out to develop a decision support tool based on the Self-Sufficiency Matrix (Dutch version; SSM-D) for the clinical decision to allocate homeless people to the public mental health care system at the central access point of public mental health care in Amsterdam, The Netherlands. Logistic regression and receiver operating characteristic-curve analyses were used to model professional decisions and establish four decision categories based on SSM-D scores from half of the research population (Total n = 612). The model and decision categories were found to be accurate and reliable in predicting professional decisions in the second half of the population. Results indicate that the decision support tool based on the SSM-D is useful and feasible. The method to develop the SSM-D as a decision support tool could be applied to decision-making processes in other systems and services where the SSM-D has been implemented, to further increase the utility of the instrument.

  13. Improving resource allocation decisions for health and HIV programmes in South Africa: Bioethical, cost-effectiveness and health diplomacy considerations.

    PubMed

    Kevany, Sebastian; Benatar, Solomon R; Fleischer, Theodore

    2013-01-01

    The escalating expenditure on patients with HIV/AIDS within an inadequately funded public health system is tending towards crowding out care for patients with non-HIV illnesses. Priority-setting decisions are thus required and should increasingly be based on an explicit, transparent and accountable process to facilitate sustainability. South Africa's public health system is eroding, even though the government has received extensive donor financing for specific conditions, such as HIV/AIDS. The South African government's 2007 HIV plan anticipated costs exceeding 20% of the annual health budget with a strong focus on treatment interventions, while the recently announced 2012-2016 National Strategic HIV plan could cost up to US$16 billion. Conversely, the total non-HIV health budget has remained static in recent years, effectively reducing the supply of health care for other diseases. While the South African government cannot meet all demands for health care simultaneously, health funders should attempt to allocate health resources in a fair, efficient, transparent and accountable manner, in order to ensure that publicly funded health care is delivered in a reasonable and non-discriminatory fashion. We recommend a process for resource allocation that includes ethical, economic, legal and policy considerations. This process, adapted for use by South Africa's policy-makers, could bring health, political, economic and ethical gains, whilst allaying a social crisis as mounting treatment commitments generated by HIV have the potential to overwhelm the health system.

  14. Auction-based resource allocation game under a hierarchical structure

    NASA Astrophysics Data System (ADS)

    Cui, Yingying; Zou, Suli; Ma, Zhongjing

    2016-01-01

    This paper studies a class of auction-based resource allocation games under a hierarchical structure, such that each supplier is assigned a certain amount of resource from a single provider and allocates it to its buyers with auction mechanisms. To implement the efficient allocations for the underlying hierarchical system, we first design an auction mechanism, for each local system composed of a supplier and its buyers, which inherits the advantages of the progressive second price mechanism. By employing a dynamic algorithm, each local system converges to its own efficient Nash equilibrium, at which the efficient resource allocation is achieved and the bidding prices of all the buyers in this local system are identical with each other. After the local systems reach their own equilibria respectively, the resources assigned to suppliers are readjusted via a dynamic hierarchical algorithm with respect to the bidding prices associated with the implemented equilibria of local systems. By applying the proposed hierarchical process, the formulated hierarchical system can converge to the efficient allocation under certain mild conditions. The developed results in this work are demonstrated with simulations.

  15. Allocating Great Lakes forage bases in response to multiple demand

    USGS Publications Warehouse

    Brown, Edward H.; Busiahn, Thomas R.; Jones, Michael L.; Argyle, Ray L.; Taylor, William W.; Ferreri, C. Paola

    1999-01-01

    Forage base allocation, which has become an important issue because of major changes in the fish communities and fisheries of the Great Lakes since the 1950s is examined and documented in this chapter. Management initiatives that were used to address the issue, and supporting research and development that provided new or improved methods of field sampling and analysis are also highlighted.

  16. Data-driven decision-making tools to improve public resource allocation for care and prevention of HIV/AIDS.

    PubMed

    Ryan, Gery W; Bloom, Evan W; Lowsky, David J; Linthicum, Mark T; Juday, Timothy; Rosenblatt, Lisa; Kulkarni, Sonali; Goldman, Dana P; Sayles, Jennifer N

    2014-03-01

    Public health agencies face difficult decisions when allocating scarce resources to control the spread of HIV/AIDS. Decisions are often made with few local empirical data. We demonstrated the use of the robust decision making approach in Los Angeles County, an approach that is data driven and allows decision makers to compare the performance of various intervention strategies across thousands of simulated future scenarios. We found that the prevailing strategy of emphasizing behavioral risk reduction interventions was unlikely to achieve the policy goals of the national HIV/AIDS strategy. Of the alternative strategies we examined, those that invested most heavily in interventions to initiate antiretroviral treatment and support treatment adherence were the most likely to achieve policy objectives. By employing similar methods, other public health agencies can identify robust strategies and invest in interventions more likely to achieve HIV/AIDS policy goals.

  17. [Optimal allocation of irrigation water resources based on systematical strategy].

    PubMed

    Cheng, Shuai; Zhang, Shu-qing

    2015-01-01

    With the development of the society and economy, as well as the rapid increase of population, more and more water is needed by human, which intensified the shortage of water resources. The scarcity of water resources and growing competition of water in different water use sectors reduce water availability for irrigation, so it is significant to plan and manage irrigation water resources scientifically and reasonably for improving water use efficiency (WUE) and ensuring food security. Many investigations indicate that WUE can be increased by optimization of water use. However, present studies focused primarily on a particular aspect or scale, which lack systematic analysis on the problem of irrigation water allocation. By summarizing previous related studies, especially those based on intelligent algorithms, this article proposed a multi-level, multi-scale framework for allocating irrigation water, and illustrated the basic theory of each component of the framework. Systematical strategy of optimal irrigation water allocation can not only control the total volume of irrigation water on the time scale, but also reduce water loss on the spatial scale. It could provide scientific basis and technical support for improving the irrigation water management level and ensuring the food security.

  18. Cognitive radio based optimal channel sensing and resources allocation

    NASA Astrophysics Data System (ADS)

    Vijayasarveswari, V.; Khatun, S.; Fakir, M. M.; Nayeem, M. N.; Kamarudin, L. M.; Jakaria, A.

    2017-03-01

    Cognitive radio (CR) is the latest type of wireless technoloy that is proposed to mitigate spectrum saturation problem. İn cognitve radio, secondary user will use primary user's spectrum during primary user's absence without interupting primary user's transmission. This paper focuses on practical cognitive radio network development process using Android based smart phone for the data transmission. Energy detector based sensing method was proposed and used here because it doesnot require primary user's information. Bluetooth and Wi-fi are the two available types of spectrum that was sensed for CR detection. Simulation showed cognitive radio network can be developed using Android based smart phones. So, a complete application was developed using Java based Android Eclipse program. Finally, the application was uploaded and run on Android based smart phone to form and verify CR network for channel sensing and resource allocation. The observed efficiency of the application was around 81%.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  20. Decision Allocation of C2 System Based on ULMADM

    DTIC Science & Technology

    2014-06-01

    term. The expanded scale still meets the upper conditions (1) and (2). Definition 1 Assuming ],[ ~ ba ss , Sss ba , . as and bs are the lower...variables. The algorithms of uncertain linguistic variable can be seen in reference [13]. Definition 2[13] Assuming ],[ ~ ba ss , Sss dc...2322031432032  sssssssssssssR ]),[], 200 sss , ,[],,[],,[],,[],,[],,[],,([ ~ 1434232104220 sssssssssssssQ ]),[], 133  sss

  1. Stochastic multi-objective auto-optimization for resource allocation decision-making in fixed-input health systems.

    PubMed

    Bastian, Nathaniel D; Ekin, Tahir; Kang, Hyojung; Griffin, Paul M; Fulton, Lawrence V; Grannan, Benjamin C

    2016-01-07

    The management of hospitals within fixed-input health systems such as the U.S. Military Health System (MHS) can be challenging due to the large number of hospitals, as well as the uncertainty in input resources and achievable outputs. This paper introduces a stochastic multi-objective auto-optimization model (SMAOM) for resource allocation decision-making in fixed-input health systems. The model can automatically identify where to re-allocate system input resources at the hospital level in order to optimize overall system performance, while considering uncertainty in the model parameters. The model is applied to 128 hospitals in the three services (Air Force, Army, and Navy) in the MHS using hospital-level data from 2009 - 2013. The results are compared to the traditional input-oriented variable returns-to-scale Data Envelopment Analysis (DEA) model. The application of SMAOM to the MHS increases the expected system-wide technical efficiency by 18 % over the DEA model while also accounting for uncertainty of health system inputs and outputs. The developed method is useful for decision-makers in the Defense Health Agency (DHA), who have a strategic level objective of integrating clinical and business processes through better sharing of resources across the MHS and through system-wide standardization across the services. It is also less sensitive to data outliers or sampling errors than traditional DEA methods.

  2. Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation.

    PubMed

    Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu

    2016-09-20

    In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate and fast retrieval method for breast histopathological image. Specifically, the method presents local statistical feature of nuclei for morphology and distribution of nuclei, and employs Gabor feature to describe texture information. Latent Dirichlet Allocation model is utilized for high-level semantic mining. Locality- Sensitive Hashing is used to speed up the search. Experiments on a WSI database with over 8000 images from 15 types of breast histopathology demonstrate that our method achieves about 0.9 retrieval precision as well as promising efficiency. Based on the proposed framework, we are developing a search engine for an online digital slide browsing and retrieval platform, which can be applied in computer-aided diagnosis, pathology education, WSI archiving and management.

  3. Rate Distortion Analysis and Bit Allocation Scheme for Wavelet Lifting-Based Multiview Image Coding

    NASA Astrophysics Data System (ADS)

    Lasang, Pongsak; Kumwilaisak, Wuttipong

    2009-12-01

    This paper studies the distortion and the model-based bit allocation scheme of wavelet lifting-based multiview image coding. Redundancies among image views are removed by disparity-compensated wavelet lifting (DCWL). The distortion prediction of the low-pass and high-pass subbands of each image view from the DCWL process is analyzed. The derived distortion is used with different rate distortion models in the bit allocation of multiview images. Rate distortion models including power model, exponential model, and the proposed combining the power and exponential models are studied. The proposed rate distortion model exploits the accuracy of both power and exponential models in a wide range of target bit rates. Then, low-pass and high-pass subbands are compressed by SPIHT (Set Partitioning in Hierarchical Trees) with a bit allocation solution. We verify the derived distortion and the bit allocation with several sets of multiview images. The results show that the bit allocation solution based on the derived distortion and our bit allocation scheme provide closer results to those of the exhaustive search method in both allocated bits and peak-signal-to-noise ratio (PSNR). It also outperforms the uniform bit allocation and uniform bit allocation with normalized energy in the order of 1.7-2 and 0.3-1.4 dB, respectively.

  4. Random property allocation: A novel geographic imputation procedure based on a complete geocoded address file.

    PubMed

    Walter, Scott R; Rose, Nectarios

    2013-09-01

    Allocating an incomplete address to randomly selected property coordinates within a locality, known as random property allocation, has many advantages over other geoimputation techniques. We compared the performance of random property allocation to four other methods under various conditions using a simulation approach. All methods performed well for large spatial units, but random property allocation was the least prone to bias and error under volatile scenarios with small units and low prevalence. Both its coordinate based approach as well as the random process of assignment contribute to its increased accuracy and reduced bias in many scenarios. Hence it is preferable to fixed or areal geoimputation for many epidemiological and surveillance applications.

  5. Utility-based uplink joint power and subcarrier allocation in SC-FDMA wireless networks

    NASA Astrophysics Data System (ADS)

    Eleni Tsiropoulou, Eirini; Papavassiliou, Symeon

    2011-11-01

    In this letter, the problem of optimal joint uplink power and subcarrier allocation in single-carrier frequency-division multiple access wireless networks with real-time services is addressed, via the introduction and adoption of a utility-based framework. A joint optimisation power and subcarrier allocation problem is formulated and the optimal power allocation is determined, while an iterative algorithm to realise the joint allocation is presented. Finally, numerical results are provided that demonstrate the effectiveness of the proposed approach in terms of power savings and user satisfaction.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  7. Agent-based evacuation simulation for spatial allocation assessment of urban shelters

    NASA Astrophysics Data System (ADS)

    Yu, Jia; Wen, Jiahong; Jiang, Yong

    2015-12-01

    The construction of urban shelters is one of the most important work in urban planning and disaster prevention. The spatial allocation assessment is a fundamental pre-step for spatial location-allocation of urban shelters. This paper introduces a new method which makes use of agent-based technology to implement evacuation simulation so as to conduct dynamic spatial allocation assessment of urban shelters. The method can not only accomplish traditional geospatial evaluation for urban shelters, but also simulate the evacuation process of the residents to shelters. The advantage of utilizing this method lies into three aspects: (1) the evacuation time of each citizen from a residential building to the shelter can be estimated more reasonably; (2) the total evacuation time of all the residents in a region is able to be obtained; (3) the road congestions in evacuation in sheltering can be detected so as to take precautionary measures to prevent potential risks. In this study, three types of agents are designed: shelter agents, government agents and resident agents. Shelter agents select specified land uses as shelter candidates for different disasters. Government agents delimitate the service area of each shelter, in other words, regulate which shelter a person should take, in accordance with the administrative boundaries and road distance between the person's position and the location of the shelter. Resident agents have a series of attributes, such as ages, positions, walking speeds, and so on. They also have several behaviors, such as reducing speed when walking in the crowd, helping old people and children, and so on. Integrating these three types of agents which are correlated with each other, evacuation procedures can be simulated and dynamic allocation assessment of shelters will be achieved. A case study in Jing'an District, Shanghai, China, was conducted to demonstrate the feasibility of the method. A scenario of earthquake disaster which occurs in nighttime

  8. Classification Based on Tree-Structured Allocation Rules

    ERIC Educational Resources Information Center

    Vaughn, Brandon K.; Wang, Qui

    2008-01-01

    The authors consider the problem of classifying an unknown observation into 1 of several populations by using tree-structured allocation rules. Although many parametric classification procedures are robust to certain assumption violations, there is need for classification procedures that can be used regardless of the group-conditional…

  9. Staged decision making based on probabilistic forecasting

    NASA Astrophysics Data System (ADS)

    Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

    2016-04-01

    Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in

  10. Impact-Based Area Allocation for Yield Optimization in Integrated Circuits

    NASA Astrophysics Data System (ADS)

    Abraham, Billion; Widodo, Arif; Chen, Poki

    2016-06-01

    In analog integrated circuit (IC) layout, area allocation is a very important issue for achieving good mismatch cancellation. However, most IC layout papers focus only on layout strategy to reduce systematic mismatch. In 2006, an outstanding paper presenting area allocation strategy was published to introduce technique for random mismatch reduction. Instead of using general theoretical study to prove the strategy, this research presented close-to-optimum simulations only on case-bycase basis. The impact-based area allocation for yield optimization in integrated circuits is proposed in this chapter. To demonstrate the corresponding strategy, not only a theoretical analysis but also an integral nonlinearity-based yield simulation will be given to derive optimum area allocation for binary weighted current steering digital-to-analog converter (DAC). The result will be concluded to convince IC designers how to allocate area for critical devices in an optimum way.

  11. Rate Adaptive Based Resource Allocation with Proportional Fairness Constraints in OFDMA Systems.

    PubMed

    Yin, Zhendong; Zhuang, Shufeng; Wu, Zhilu; Ma, Bo

    2015-09-25

    Orthogonal frequency division multiple access (OFDMA), which is widely used in the wireless sensor networks, allows different users to obtain different subcarriers according to their subchannel gains. Therefore, how to assign subcarriers and power to different users to achieve a high system sum rate is an important research area in OFDMA systems. In this paper, the focus of study is on the rate adaptive (RA) based resource allocation with proportional fairness constraints. Since the resource allocation is a NP-hard and non-convex optimization problem, a new efficient resource allocation algorithm ACO-SPA is proposed, which combines ant colony optimization (ACO) and suboptimal power allocation (SPA). To reduce the computational complexity, the optimization problem of resource allocation in OFDMA systems is separated into two steps. For the first one, the ant colony optimization algorithm is performed to solve the subcarrier allocation. Then, the suboptimal power allocation algorithm is developed with strict proportional fairness, and the algorithm is based on the principle that the sums of power and the reciprocal of channel-to-noise ratio for each user in different subchannels are equal. To support it, plenty of simulation results are presented. In contrast with root-finding and linear methods, the proposed method provides better performance in solving the proportional resource allocation problem in OFDMA systems.

  12. Rate Adaptive Based Resource Allocation with Proportional Fairness Constraints in OFDMA Systems

    PubMed Central

    Yin, Zhendong; Zhuang, Shufeng; Wu, Zhilu; Ma, Bo

    2015-01-01

    Orthogonal frequency division multiple access (OFDMA), which is widely used in the wireless sensor networks, allows different users to obtain different subcarriers according to their subchannel gains. Therefore, how to assign subcarriers and power to different users to achieve a high system sum rate is an important research area in OFDMA systems. In this paper, the focus of study is on the rate adaptive (RA) based resource allocation with proportional fairness constraints. Since the resource allocation is a NP-hard and non-convex optimization problem, a new efficient resource allocation algorithm ACO-SPA is proposed, which combines ant colony optimization (ACO) and suboptimal power allocation (SPA). To reduce the computational complexity, the optimization problem of resource allocation in OFDMA systems is separated into two steps. For the first one, the ant colony optimization algorithm is performed to solve the subcarrier allocation. Then, the suboptimal power allocation algorithm is developed with strict proportional fairness, and the algorithm is based on the principle that the sums of power and the reciprocal of channel-to-noise ratio for each user in different subchannels are equal. To support it, plenty of simulation results are presented. In contrast with root-finding and linear methods, the proposed method provides better performance in solving the proportional resource allocation problem in OFDMA systems. PMID:26426016

  13. On System Engineering a Barter-Based Re-allocation of Space System Key Development Resources

    NASA Astrophysics Data System (ADS)

    Kosmann, William J.

    NASA has had a decades-long problem with cost growth during the development of space science missions. Numerous agency-sponsored studies have produced average mission level development cost growths ranging from 23 to 77%. A new study of 26 historical NASA science instrument set developments using expert judgment to re-allocate key development resources has an average cost growth of 73.77%. Twice in history, during the Cassini and EOS-Terra science instrument developments, a barter-based mechanism has been used to re-allocate key development resources. The mean instrument set development cost growth was -1.55%. Performing a bivariate inference on the means of these two distributions, there is statistical evidence to support the claim that using a barter-based mechanism to re-allocate key instrument development resources will result in a lower expected cost growth than using the expert judgment approach. Agent-based discrete event simulation is the natural way to model a trade environment. A NetLogo agent-based barter-based simulation of science instrument development was created. The agent-based model was validated against the Cassini historical example, as the starting and ending instrument development conditions are available. The resulting validated agent-based barter-based science instrument resource re-allocation simulation was used to perform 300 instrument development simulations, using barter to re-allocate development resources. The mean cost growth was -3.365%. A bivariate inference on the means was performed to determine that additional significant statistical evidence exists to support a claim that using barter-based resource re-allocation will result in lower expected cost growth, with respect to the historical expert judgment approach. Barter-based key development resource re-allocation should work on science spacecraft development as well as it has worked on science instrument development. A new study of 28 historical NASA science spacecraft

  14. Measuring health indicators and allocating health resources: a DEA-based approach.

    PubMed

    Yang, Chih-Ching

    2016-02-03

    This paper suggests new empirical DEA models for the measurement of health indicators and the allocation of health resources. The proposed models were developed by first suggesting a population-based health indicator. By introducing the suggested indicator into DEA models, a new approach that solves the problem of health resource allocation has been developed. The proposed models are applied to an empirical study of Taiwan's health system. Empirical findings show that the suggested indicator can successfully accommodate the differences in health resource demands between populations, providing more reliable performance information than traditional indicators such as physician density. Using our models and a commonly used allocation mechanism, capitation, to allocate medical expenditures, it is found that the proposed model always obtains higher performance than those derived from capitation, and the superiority increases as allocated expenditures rise.

  15. Cost Accounting for Decision Makers.

    ERIC Educational Resources Information Center

    Kaneklides, Ann L.

    1985-01-01

    Underscores the importance of informed decision making through accurate anticipation of cost incurrence in light of changing economic and environmental conditions. Explains the concepts of cost accounting, full allocation of costs, the selection of an allocation base, the allocation of indirect costs, depreciation, and implications for community…

  16. Neural Network Based Modeling and Analysis of LP Control Surface Allocation

    NASA Technical Reports Server (NTRS)

    Langari, Reza; Krishnakumar, Kalmanje; Gundy-Burlet, Karen

    2003-01-01

    This paper presents an approach to interpretive modeling of LP based control allocation in intelligent flight control. The emphasis is placed on a nonlinear interpretation of the LP allocation process as a static map to support analytical study of the resulting closed loop system, albeit in approximate form. The approach makes use of a bi-layer neural network to capture the essential functioning of the LP allocation process. It is further shown via Lyapunov based analysis that under certain relatively mild conditions the resulting closed loop system is stable. Some preliminary conclusions from a study at Ames are stated and directions for further research are given at the conclusion of the paper.

  17. Selecting a risk-based tool to aid in decision making

    SciTech Connect

    Bendure, A.O.

    1995-03-01

    Selecting a risk-based tool to aid in decision making is as much of a challenge as properly using the tool once it has been selected. Failure to consider customer and stakeholder requirements and the technical bases and differences in risk-based decision making tools will produce confounding and/or politically unacceptable results when the tool is used. Selecting a risk-based decisionmaking tool must therefore be undertaken with the same, if not greater, rigor than the use of the tool once it is selected. This paper presents a process for selecting a risk-based tool appropriate to a set of prioritization or resource allocation tasks, discusses the results of applying the process to four risk-based decision-making tools, and identifies the ``musts`` for successful selection and implementation of a risk-based tool to aid in decision making.

  18. Dynamic Channel Allocation

    DTIC Science & Technology

    2003-09-01

    7 1 . Fixed Channel Allocation (FCA) ........................................................7 2. Dynamic Channel ...19 7. CSMA/CD-Based Multiple Network Lines .....................................20 8. Hybrid Channel Allocation in Wireless Networks...28 1 . Channel Allocation

  19. Web based tool for resource allocation in multiple mass casualty incidents.

    PubMed

    Inampudi, Venkata S; Ganz, Aura

    2009-01-01

    In this paper we introduce a web based real time resource allocation tool that can assist the incident commanders and resource managers in the complex task of resource allocation and transportation for multiple simultaneous incidents that occur in close geographical proximity. The tool takes real time inputs like the location of emergency sites and damaged routes from Google Maps, generates an optimal transportation plan so that emergency sites with highest priorities for a resource are assigned the resources in the least amount of time. The optimal solution is presented graphically using Google Maps. Our solution can be used for emergency resource allocation at both the initial response stage and later stages.

  20. Hybrid Resource Allocation Scheme with Proportional Fairness in OFDMA-Based Cognitive Radio Systems

    NASA Astrophysics Data System (ADS)

    Li, Li; Xu, Changqing; Fan, Pingzhi; He, Jian

    In this paper, the resource allocation problem for proportional fairness in hybrid Cognitive Radio (CR) systems is studied. In OFDMA-based CR systems, traditional resource allocation algorithms can not guarantee proportional rates among CR users (CRU) in each OFDM symbol because the number of available subchannels might be smaller than that of CRUs in some OFDM symbols. To deal with this time-varying nature of available spectrum resource, a hybrid CR scheme in which CRUs are allowed to use subchannels in both spectrum holes and primary users (PU) bands is adopted and a resource allocation algorithm is proposed to guarantee proportional rates among CRUs with no undue interference to PUs.

  1. Resource Allocation for the New Defense Strategy The DynaRank Decision-Support System

    DTIC Science & Technology

    1998-01-01

    tutorial. DynaRank is a Microsoft ® Excel workbook available for the Macintosh and an IBM-compatible computer. The research reported here was...in the routine operations of the depart- ment. DynaRank, which is based on a hierarchical "scorecard" framework in Microsoft ® Excel for the...user modification. The Clear option removes the information from a template. Templates can be removed from the worksheet by using the Excel submenu

  2. MDP-based resource allocation for triple-play transmission on xDSL systems

    NASA Astrophysics Data System (ADS)

    de Souza, Lamartine V.; de Carvalho, Glaucio H. S.; Cardoso, Diego L.; de Carvalho, Solon V.; Frances, Carlos R. L.; Costa, João C. W. A.; Riu, Jaume Rius i.

    2007-09-01

    Many broadband services are based on multimedia applications, such as voice over internet protocol (VoIP), video conferencing, video on demand (VoD), and internet protocol television (IPTV). The combination "triple-play" is often used with IPTV. It simply means offering voice, video and data. IPTV and others services uses digital broadband networks such as ADSL2+ (Asymmetric Digital Subscriber Line) and VDSL (Very High Rate DSL) to transmit the data. We have formulated a MDP (Markov Decision Process) for a triple-play transmission on DSL environment. In this paper, we establish the relationship between DSL transmission characteristics and its finite-state Markov model for a triple-play transmission system. This relationship can be used for a resource management for multimedia applications delivered through a broadband infrastructure. The solution to our optimization problem can be found using dynamic programming (DP) techniques, such as value iteration and its variants. Our study results in a transmission strategy that chooses the optimal resource allocation according the triple-play traffic requirements, defined in technical report TR-126 (Triple-Play Services Quality of Experience Requirements) from DSL Forum, minimizing quality of service (QoS) violations with respect to bandwidth. Three traffic classes (video, audio, and best effort internet data) are defined and analyzed. Our simulation results show parameters like as blocking probability for each class, link utilization and optimal control policies. The MDP-based approach provides a satisfactory way of resource management for a DSL system.

  3. FOR Allocation to Distribution Systems based on Credible Improvement Potential (CIP)

    NASA Astrophysics Data System (ADS)

    Tiwary, Aditya; Arya, L. D.; Arya, Rajesh; Choube, S. C.

    2017-02-01

    This paper describes an algorithm for forced outage rate (FOR) allocation to each section of an electrical distribution system subject to satisfaction of reliability constraints at each load point. These constraints include threshold values of basic reliability indices, for example, failure rate, interruption duration and interruption duration per year at load points. Component improvement potential measure has been used for FOR allocation. Component with greatest magnitude of credible improvement potential (CIP) measure is selected for improving reliability performance. The approach adopted is a monovariable method where one component is selected for FOR allocation and in the next iteration another component is selected for FOR allocation based on the magnitude of CIP. The developed algorithm is implemented on sample radial distribution system.

  4. Data-Based Decision Making in Education: Challenges and Opportunities

    ERIC Educational Resources Information Center

    Schildkamp, Kim, Ed.; Lai, Mei Kuin, Ed.; Earl, Lorna, Ed.

    2013-01-01

    In a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of…

  5. Feature Extraction Based on Decision Boundaries

    NASA Technical Reports Server (NTRS)

    Lee, Chulhee; Landgrebe, David A.

    1993-01-01

    In this paper, a novel approach to feature extraction for classification is proposed based directly on the decision boundaries. We note that feature extraction is equivalent to retaining informative features or eliminating redundant features; thus, the terms 'discriminantly information feature' and 'discriminantly redundant feature' are first defined relative to feature extraction for classification. Next, it is shown how discriminantly redundant features and discriminantly informative features are related to decision boundaries. A novel characteristic of the proposed method arises by noting that usually only a portion of the decision boundary is effective in discriminating between classes, and the concept of the effective decision boundary is therefore introduced. Next, a procedure to extract discriminantly informative features based on a decision boundary is proposed. The proposed feature extraction algorithm has several desirable properties: (1) It predicts the minimum number of features necessary to achieve the same classification accuracy as in the original space for a given pattern recognition problem; and (2) it finds the necessary feature vectors. The proposed algorithm does not deteriorate under the circumstances of equal class means or equal class covariances as some previous algorithms do. Experiments show that the performance of the proposed algorithm compares favorably with those of previous algorithms.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  8. Performance Improvement of Proportional Fairness-Based Resource Allocation in OFDMA Downlink Systems

    NASA Astrophysics Data System (ADS)

    Ruangchaijatupon, Nararat; Ji, Yusheng

    We have developed a novel downlink packet scheduling scheme for a multiuser OFDMA system in which a subchannel can be time-multiplexed among multiple users. This scheme which is called Matrixed-based Proportional Fairness can provide a high system throughput while ensuring fairness. The scheme is based on a Proportional Fairness (PF) utility function and can be applied to any of the PF-based schedulers. Our scheduler explores multichannel multiuser diversity by using a two-dimensional matrix combining user selection, subchannel assignment, and time slot allocation. Furthermore, unlike other PF-based schemes, our scheme considers finitely backlogged queues during the time slot allocation. By doing so, it can exploit multichannel multiuser diversity to utilize bandwidth efficiently and with throughput fairness. Additionally, fairness in the time domain is enhanced by limiting the number of allocated time slots. Intensive simulations considering finitely backlogged queues and user mobility prove the scheme's effectiveness.

  9. A trust-based sensor allocation algorithm in cooperative space search problems

    NASA Astrophysics Data System (ADS)

    Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik

    2011-06-01

    Sensor allocation is an important and challenging problem within the field of multi-agent systems. The sensor allocation problem involves deciding how to assign a number of targets or cells to a set of agents according to some allocation protocol. Generally, in order to make efficient allocations, we need to design mechanisms that consider both the task performers' costs for the service and the associated probability of success (POS). In our problem, the costs are the used sensor resource, and the POS is the target tracking performance. Usually, POS may be perceived differently by different agents because they typically have different standards or means of evaluating the performance of their counterparts (other sensors in the search and tracking problem). Given this, we turn to the notion of trust to capture such subjective perceptions. In our approach, we develop a trust model to construct a novel mechanism that motivates sensor agents to limit their greediness or selfishness. Then we model the sensor allocation optimization problem with trust-in-loop negotiation game and solve it using a sub-game perfect equilibrium. Numerical simulations are performed to demonstrate the trust-based sensor allocation algorithm in cooperative space situation awareness (SSA) search problems.

  10. Computer Based Decision Support in Dentistry.

    ERIC Educational Resources Information Center

    Wagner, Ina-Veronika; Schneider, Werner

    1991-01-01

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

  11. Estimating Decision Indices Based on Composite Scores

    ERIC Educational Resources Information Center

    Knupp, Tawnya Lee

    2009-01-01

    The purpose of this study was to develop an IRT model that would enable the estimation of decision indices based on composite scores. The composite scores, defined as a combination of unidimensional test scores, were either a total raw score or an average scale score. Additionally, estimation methods for the normal and compound multinomial models…

  12. Decision Analysis in the U.S. Army’s Capabilties Needs Analysis: Applications of Decision Analysis Methods to Capabilities Resource Allocation and Capabilities Development Decisions

    DTIC Science & Technology

    2015-10-01

    value functions and their scales; the use of a modified Delphi method to refine the analysis results; and the implementation of an open architecture web ...analysis results; and the implementation of an open architecture web -based tool to collect and analyze data and socialize results. Finally, the...greatly from an application of web -based assessment tools to collect data from a diverse and geographically dispersed community of practice, assess

  13. Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation

    PubMed Central

    Gui, Zhipeng; Yu, Manzhu; Yang, Chaowei; Jiang, Yunfeng; Chen, Songqing; Xia, Jizhe; Huang, Qunying; Liu, Kai; Li, Zhenlong; Hassan, Mohammed Anowarul; Jin, Baoxuan

    2016-01-01

    Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical

  14. Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation.

    PubMed

    Gui, Zhipeng; Yu, Manzhu; Yang, Chaowei; Jiang, Yunfeng; Chen, Songqing; Xia, Jizhe; Huang, Qunying; Liu, Kai; Li, Zhenlong; Hassan, Mohammed Anowarul; Jin, Baoxuan

    2016-01-01

    Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical

  15. Multi-robot task allocation based on two dimensional artificial fish swarm algorithm

    NASA Astrophysics Data System (ADS)

    Zheng, Taixiong; Li, Xueqin; Yang, Liangyi

    2007-12-01

    The problem of task allocation for multiple robots is to allocate more relative-tasks to less relative-robots so as to minimize the processing time of these tasks. In order to get optimal multi-robot task allocation scheme, a twodimensional artificial swarm algorithm based approach is proposed in this paper. In this approach, the normal artificial fish is extended to be two dimension artificial fish. In the two dimension artificial fish, each vector of primary artificial fish is extended to be an m-dimensional vector. Thus, each vector can express a group of tasks. By redefining the distance between artificial fish and the center of artificial fish, the behavior of two dimension fish is designed and the task allocation algorithm based on two dimension artificial swarm algorithm is put forward. At last, the proposed algorithm is applied to the problem of multi-robot task allocation and comparer with GA and SA based algorithm is done. Simulation and compare result shows the proposed algorithm is effective.

  16. What Does it Really Cost? Allocating Indirect Costs.

    ERIC Educational Resources Information Center

    Snyder, Herbert; Davenport, Elisabeth

    1997-01-01

    Better managerial control in terms of decision making and understanding the costs of a system/service result from allocating indirect costs. Allocation requires a three-step process: selecting cost objectives, pooling related overhead costs, and selecting costs bases to connect the objectives to the pooled costs. Argues that activity-based costing…

  17. Word Learning and Attention Allocation Based on Word Class and Category Knowledge

    ERIC Educational Resources Information Center

    Hupp, Julie M.

    2015-01-01

    Attention allocation in word learning may vary developmentally based on the novelty of the object. It has been suggested that children differentially learn verbs based on the novelty of the agent, but adults do not because they automatically infer the object's category and thus treat it like a familiar object. The current research examined…

  18. Research on multirobot pursuit task allocation algorithm based on emotional cooperation factor.

    PubMed

    Fang, Baofu; Chen, Lu; Wang, Hao; Dai, Shuanglu; Zhong, Qiubo

    2014-01-01

    Multirobot task allocation is a hot issue in the field of robot research. A new emotional model is used with the self-interested robot, which gives a new way to measure self-interested robots' individual cooperative willingness in the problem of multirobot task allocation. Emotional cooperation factor is introduced into self-interested robot; it is updated based on emotional attenuation and external stimuli. Then a multirobot pursuit task allocation algorithm is proposed, which is based on emotional cooperation factor. Combined with the two-step auction algorithm recruiting team leaders and team collaborators, set up pursuit teams, and finally use certain strategies to complete the pursuit task. In order to verify the effectiveness of this algorithm, some comparing experiments have been done with the instantaneous greedy optimal auction algorithm; the results of experiments show that the total pursuit time and total team revenue can be optimized by using this algorithm.

  19. Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

    PubMed

    Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

    2015-09-01

    This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach.

  20. Automated Vectorization of Decision-Based Algorithms

    NASA Technical Reports Server (NTRS)

    James, Mark

    2006-01-01

    Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.

  1. Block-layer bit allocation for quality constrained video encoding based on constant perceptual quality

    NASA Astrophysics Data System (ADS)

    Wang, Chao; Mou, Xuanqin; Hong, Wei; Zhang, Lei

    2013-02-01

    In lossy image/video encoding, there is a compromise between the number of bits (rate) and the extent of distortion. Bits need to be properly allocated to different sources, such as frames and macro blocks (MBs). Since the human eyes are more sensitive to the difference than the absolute value of signals, the MINMAX criterion suggests to minimizing the maximum distortion of the sources to limit quality fluctuation. There are many works aimed to such constant quality encoding, however, almost all of them focus on the frame layer bit allocation, and use PSNR as the quality index. We suggest that the bit allocation for MBs should also be constrained in the constant quality, and furthermore, perceptual quality indices should be used instead of PSNR. Based on this idea, we propose a multi-pass block-layer bit allocation scheme for quality constrained encoding. The experimental results show that the proposed method can achieve much better encoding performance. Keywords: Bit allocation, block-layer, perceptual quality, constant quality, quality constrained

  2. Stereoscopic Visual Attention-Based Regional Bit Allocation Optimization for Multiview Video Coding

    NASA Astrophysics Data System (ADS)

    Zhang, Yun; Jiang, Gangyi; Yu, Mei; Chen, Ken; Dai, Qionghai

    2010-12-01

    We propose a Stereoscopic Visual Attention- (SVA-) based regional bit allocation optimization for Multiview Video Coding (MVC) by the exploiting visual redundancies from human perceptions. We propose a novel SVA model, where multiple perceptual stimuli including depth, motion, intensity, color, and orientation contrast are utilized, to simulate the visual attention mechanisms of human visual system with stereoscopic perception. Then, a semantic region-of-interest (ROI) is extracted based on the saliency maps of SVA. Both objective and subjective evaluations of extracted ROIs indicated that the proposed SVA model based on ROI extraction scheme outperforms the schemes only using spatial or/and temporal visual attention clues. Finally, by using the extracted SVA-based ROIs, a regional bit allocation optimization scheme is presented to allocate more bits on SVA-based ROIs for high image quality and fewer bits on background regions for efficient compression purpose. Experimental results on MVC show that the proposed regional bit allocation algorithm can achieve over [InlineEquation not available: see fulltext.]% bit-rate saving while maintaining the subjective image quality. Meanwhile, the image quality of ROIs is improved by [InlineEquation not available: see fulltext.] dB at the cost of insensitive image quality degradation of the background image.

  3. Link prediction in complex networks based on an information allocation index

    NASA Astrophysics Data System (ADS)

    Pei, Panpan; Liu, Bo; Jiao, Licheng

    2017-03-01

    An important issue in link prediction of complex networks is to make full use of different kinds of available information simultaneously. To tackle this issue, recently, an information-theoretic model has been proposed and a novel Neighbor Set Information Index (NSI) has been designed. Motivated by this work, we proposed a more general information-theoretic model by further distinguishing the contributions from different variables of the available features. Then, by introducing the resource allocation process into the model, we designed a new index based on neighbor sets with a virtual information allocation process: Neighbor Set Information Allocation Index(NSIA). Experimental studies on real world networks from disparate fields indicate that NSIA performs well compared with NSI as well as other typical proximity indices.

  4. Allocating Information Costs in a Negotiated Information Order: Interorganizational Constraints on Decision Making in Norwegian Oil Insurance.

    ERIC Educational Resources Information Center

    Heimer, Carol A.

    1985-01-01

    This paper analyzes two types of decisions for insuring mobile oil rigs and fixed installations in the Norwegian North Sea: (1) decisions about information for ratemaking and underwriting, and (2) decisions about the conditions of insurance. Appended are 46 references. (MLF)

  5. Intra-District Resource Allocation and Criteria Used for Student Based Funding in Urban School Districts

    ERIC Educational Resources Information Center

    Aloo, Peter Mangla

    2011-01-01

    Resource allocation to school sites in public school districts is inequitable. While Student Based Funding (SBF) has been implemented in several major urban school districts, there are few empirical studies about how SBF policies are derived and implemented. Current efforts to align resources with student need are hindered by a lack of systematic,…

  6. A global trait-based approach to estimate leaf nitrogen functional allocation from observations.

    PubMed

    Ghimire, Bardan; Riley, William J; Koven, Charles D; Kattge, Jens; Rogers, Alistair; Reich, Peter B; Wright, Ian J

    2017-03-28

    Nitrogen is one of the most important nutrients for plant growth and a major constituent of proteins that regulate photosynthetic and respiratory processes. However, a comprehensive global analysis of nitrogen allocation in leaves for major processes with respect to different plant functional types is currently lacking. This study integrated observations from global databases with photosynthesis and respiration models to determine plant-functional-type-specific allocation patterns of leaf nitrogen for photosynthesis (Rubisco, electron transport, light absorption) and respiration (growth and maintenance), and by difference from observed total leaf nitrogen, an unexplained "residual" nitrogen pool. Based on our analysis, crops partition the largest fraction of nitrogen to photosynthesis (57%) and respiration (5%) followed by herbaceous plants (44% and 4%). Tropical broadleaf evergreen trees partition the least to photosynthesis (25%) and respiration (2%) followed by needle-leaved evergreen trees (28% and 3%). In trees (especially needle-leaved evergreen and tropical broadleaf evergreen trees) a large fraction (70% and 73% respectively) of nitrogen was not explained by photosynthetic or respiratory functions. Compared to crops and herbaceous plants, this large residual pool is hypothesized to emerge from larger investments in cell wall proteins, lipids, amino acids, nucleic acid, CO2 fixation proteins (other than Rubisco), secondary compounds, and other proteins. Our estimates are different from previous studies due to differences in methodology and assumptions used in deriving nitrogen allocation estimates. Unlike previous studies, we integrate and infer nitrogen allocation estimates across multiple plant functional types, and report substantial differences in nitrogen allocation across different plant functional types. The resulting pattern of nitrogen allocation provides insights on mechanisms that operate at a cellular scale within leaves, and can be integrated

  7. A global trait-based approach to estimate leaf nitrogen functional allocation from observations

    DOE PAGES

    Ghimire, Bardan; Riley, William J.; Koven, Charles D.; ...

    2017-03-28

    Nitrogen is one of the most important nutrients for plant growth and a major constituent of proteins that regulate photosynthetic and respiratory processes. However, a comprehensive global analysis of nitrogen allocation in leaves for major processes with respect to different plant functional types is currently lacking. This study integrated observations from global databases with photosynthesis and respiration models to determine plant-functional-type-specific allocation patterns of leaf nitrogen for photosynthesis (Rubisco, electron transport, light absorption) and respiration (growth and maintenance), and by difference from observed total leaf nitrogen, an unexplained “residual” nitrogen pool. Based on our analysis, crops partition the largest fractionmore » of nitrogen to photosynthesis (57%) and respiration (5%) followed by herbaceous plants (44% and 4%). Tropical broadleaf evergreen trees partition the least to photosynthesis (25%) and respiration (2%) followed by needle-leaved evergreen trees (28% and 3%). In trees (especially needle-leaved evergreen and tropical broadleaf evergreen trees) a large fraction (70% and 73% respectively) of nitrogen was not explained by photosynthetic or respiratory functions. Compared to crops and herbaceous plants, this large residual pool is hypothesized to emerge from larger investments in cell wall proteins, lipids, amino acids, nucleic acid, CO2 fixation proteins (other than Rubisco), secondary compounds, and other proteins. Our estimates are different from previous studies due to differences in methodology and assumptions used in deriving nitrogen allocation estimates. Unlike previous studies, we integrate and infer nitrogen allocation estimates across multiple plant functional types, and report substantial differences in nitrogen allocation across different plant functional types. Furthermore, the resulting pattern of nitrogen allocation provides insights on mechanisms that operate at a cellular scale within leaves

  8. Individual Schooling Decisions and Labor Market Allocation: Vertical and Horizontal Sorting. IFG Program Report No. 84-B8.

    ERIC Educational Resources Information Center

    Hartog, Joop

    If labor market phenomena are interpreted from an allocational point of view, where individuals differing in levels of various capabilities have to be matched with jobs differing in job requirements, education can be seen as an intermediary institution affecting the capability endowment of individuals upon entering the labor market. Vertical…

  9. Multi-Agent Based Simulation of Optimal Urban Land Use Allocation in the Middle Reaches of the Yangtze River, China

    NASA Astrophysics Data System (ADS)

    Zeng, Y.; Huang, W.; Jin, W.; Li, S.

    2016-06-01

    The optimization of land-use allocation is one of important approaches to achieve regional sustainable development. This study selects Chang-Zhu-Tan agglomeration as study area and proposed a new land use optimization allocation model. Using multi-agent based simulation model, the future urban land use optimization allocation was simulated in 2020 and 2030 under three different scenarios. This kind of quantitative information about urban land use optimization allocation and urban expansions in future would be of great interest to urban planning, water and land resource management, and climate change research.

  10. Water consumption and allocation strategies along the river oases of Tarim River based on large-scale hydrological modelling

    NASA Astrophysics Data System (ADS)

    Yu, Yang; Disse, Markus; Yu, Ruide

    2016-04-01

    With the mainstream of 1,321km and located in an arid area in northwest China, the Tarim River is China's longest inland river. The Tarim basin on the northern edge of the Taklamakan desert is an extremely arid region. In this region, agricultural water consumption and allocation management are crucial to address the conflicts among irrigation water users from upstream to downstream. Since 2011, the German Ministry of Science and Education BMBF established the Sino-German SuMaRiO project, for the sustainable management of river oases along the Tarim River. The project aims to contribute to a sustainable land management which explicitly takes into account ecosystem functions and ecosystem services. SuMaRiO will identify realizable management strategies, considering social, economic and ecological criteria. This will have positive effects for nearly 10 million inhabitants of different ethnic groups. The modelling of water consumption and allocation strategies is a core block in the SuMaRiO cluster. A large-scale hydrological model (MIKE HYDRO Basin) was established for the purpose of sustainable agricultural water management in the main stem Tarim River. MIKE HYDRO Basin is an integrated, multipurpose, map-based decision support tool for river basin analysis, planning and management. It provides detailed simulation results concerning water resources and land use in the catchment areas of the river. Calibration data and future predictions based on large amount of data was acquired. The results of model calibration indicated a close correlation between simulated and observed values. Scenarios with the change on irrigation strategies and land use distributions were investigated. Irrigation scenarios revealed that the available irrigation water has significant and varying effects on the yields of different crops. Irrigation water saving could reach up to 40% in the water-saving irrigation scenario. Land use scenarios illustrated that an increase of farmland area in the

  11. Comprehensive reliability allocation method for CNC lathes based on cubic transformed functions of failure mode and effects analysis

    NASA Astrophysics Data System (ADS)

    Yang, Zhou; Zhu, Yunpeng; Ren, Hongrui; Zhang, Yimin

    2015-03-01

    Reliability allocation of computerized numerical controlled(CNC) lathes is very important in industry. Traditional allocation methods only focus on high-failure rate components rather than moderate failure rate components, which is not applicable in some conditions. Aiming at solving the problem of CNC lathes reliability allocating, a comprehensive reliability allocation method based on cubic transformed functions of failure modes and effects analysis(FMEA) is presented. Firstly, conventional reliability allocation methods are introduced. Then the limitations of direct combination of comprehensive allocation method with the exponential transformed FMEA method are investigated. Subsequently, a cubic transformed function is established in order to overcome these limitations. Properties of the new transformed functions are discussed by considering the failure severity and the failure occurrence. Designers can choose appropriate transform amplitudes according to their requirements. Finally, a CNC lathe and a spindle system are used as an example to verify the new allocation method. Seven criteria are considered to compare the results of the new method with traditional methods. The allocation results indicate that the new method is more flexible than traditional methods. By employing the new cubic transformed function, the method covers a wider range of problems in CNC reliability allocation without losing the advantages of traditional methods.

  12. Knowledge-based load leveling and task allocation in human-machine systems

    NASA Technical Reports Server (NTRS)

    Chignell, M. H.; Hancock, P. A.

    1986-01-01

    Conventional human-machine systems use task allocation policies which are based on the premise of a flexible human operator. This individual is most often required to compensate for and augment the capabilities of the machine. The development of artificial intelligence and improved technologies have allowed for a wider range of task allocation strategies. In response to these issues a Knowledge Based Adaptive Mechanism (KBAM) is proposed for assigning tasks to human and machine in real time, using a load leveling policy. This mechanism employs an online workload assessment and compensation system which is responsive to variations in load through an intelligent interface. This interface consists of a loading strategy reasoner which has access to information about the current status of the human-machine system as well as a database of admissible human/machine loading strategies. Difficulties standing in the way of successful implementation of the load leveling strategy are examined.

  13. A Bayesian formulation for auction-based task allocation in heterogeneous multi-agent teams

    NASA Astrophysics Data System (ADS)

    Pippin, Charles E.; Christensen, Henrik

    2011-06-01

    In distributed, heterogeneous, multi-agent teams, agents may have different capabilities and types of sensors. Agents in dynamic environments will need to cooperate in real-time to perform tasks with minimal costs. Some example scenarios include dynamic allocation of UAV and UGV robot teams to possible hurricane survivor locations, search and rescue and target detection. Auction based algorithms scale well because agents generally only need to communicate bid information. In addition, the agents are able to perform their computations in parallel and can operate on local information. Furthermore, it is easy to integrate humans and other vehicle types and sensor combinations into an auction framework. However, standard auction mechanisms do not explicitly consider sensors with varying reliability. The agents sensor qualities should be explicitly accounted. Consider a scenario with multiple agents, each carrying a single sensor. The tasks in this case are to simply visit a location and detect a target. The sensors are of varying quality, with some having a higher probability of target detection. The agents themselves may have different capabilities, as well. The agents use knowledge of their environment to submit cost-based bids for performing each task and an auction is used to perform the task allocation. This paper discusses techniques for including a Bayesian formulation of target detection likelihood into this auction based framework for performing task allocation across multi-agent heterogeneous teams. Analysis and results of experiments with multiple air systems performing distributed target detection are also included.

  14. Optimality versus stability in water resource allocation.

    PubMed

    Read, Laura; Madani, Kaveh; Inanloo, Bahareh

    2014-01-15

    Water allocation is a growing concern in a developing world where limited resources like fresh water are in greater demand by more parties. Negotiations over allocations often involve multiple groups with disparate social, economic, and political status and needs, who are seeking a management solution for a wide range of demands. Optimization techniques for identifying the Pareto-optimal (social planner solution) to multi-criteria multi-participant problems are commonly implemented, although often reaching agreement for this solution is difficult. In negotiations with multiple-decision makers, parties who base decisions on individual rationality may find the social planner solution to be unfair, thus creating a need to evaluate the willingness to cooperate and practicality of a cooperative allocation solution, i.e., the solution's stability. This paper suggests seeking solutions for multi-participant resource allocation problems through an economics-based power index allocation method. This method can inform on allocation schemes that quantify a party's willingness to participate in a negotiation rather than opt for no agreement. Through comparison of the suggested method with a range of distance-based multi-criteria decision making rules, namely, least squares, MAXIMIN, MINIMAX, and compromise programming, this paper shows that optimality and stability can produce different allocation solutions. The mismatch between the socially-optimal alternative and the most stable alternative can potentially result in parties leaving the negotiation as they may be too dissatisfied with their resource share. This finding has important policy implications as it justifies why stakeholders may not accept the socially optimal solution in practice, and underlies the necessity of considering stability where it may be more appropriate to give up an unstable Pareto-optimal solution for an inferior stable one. Authors suggest assessing the stability of an allocation solution as an

  15. A perceptual-based approach to bit allocation for H.264 encoder

    NASA Astrophysics Data System (ADS)

    Ou, Tao-Sheng; Huang, Yi-Hsin; Chen, Homer H.

    2010-07-01

    Since the ultimate receivers of encoded video are human eyes, the characteristics of human visual system should be taken into consideration in the design of bit allocation to improve the perceptual video quality. In this paper, we incorporate the structural similarity index as a distortion metric and propose a novel rate-distortion model to characterize the relationship between rate and the structural similarity index. Based on the model, we develop an optimum bit allocation and rate control scheme for H.264 encoders. Experimental results show that up to 25% bitrate reduction over the JM reference software can be achieved. Subjective evaluation further confirms that the proposed scheme preserves more structural information and improves the perceptual quality of the encoded video.

  16. Adjacency Matrix-Based Transmit Power Allocation Strategies in Wireless Sensor Networks

    PubMed Central

    Consolini, Luca; Medagliani, Paolo; Ferrari, Gianluigi

    2009-01-01

    In this paper, we present an innovative transmit power control scheme, based on optimization theory, for wireless sensor networks (WSNs) which use carrier sense multiple access (CSMA) with collision avoidance (CA) as medium access control (MAC) protocol. In particular, we focus on schemes where several remote nodes send data directly to a common access point (AP). Under the assumption of finite overall network transmit power and low traffic load, we derive the optimal transmit power allocation strategy that minimizes the packet error rate (PER) at the AP. This approach is based on modeling the CSMA/CA MAC protocol through a finite state machine and takes into account the network adjacency matrix, depending on the transmit power distribution and determining the network connectivity. It will be then shown that the transmit power allocation problem reduces to a convex constrained minimization problem. Our results show that, under the assumption of low traffic load, the power allocation strategy, which guarantees minimal delay, requires the maximization of network connectivity, which can be equivalently interpreted as the maximization of the number of non-zero entries of the adjacency matrix. The obtained theoretical results are confirmed by simulations for unslotted Zigbee WSNs. PMID:22346705

  17. Adjacency matrix-based transmit power allocation strategies in wireless sensor networks.

    PubMed

    Consolini, Luca; Medagliani, Paolo; Ferrari, Gianluigi

    2009-01-01

    In this paper, we present an innovative transmit power control scheme, based on optimization theory, for wireless sensor networks (WSNs) which use carrier sense multiple access (CSMA) with collision avoidance (CA) as medium access control (MAC) protocol. In particular, we focus on schemes where several remote nodes send data directly to a common access point (AP). Under the assumption of finite overall network transmit power and low traffic load, we derive the optimal transmit power allocation strategy that minimizes the packet error rate (PER) at the AP. This approach is based on modeling the CSMA/CA MAC protocol through a finite state machine and takes into account the network adjacency matrix, depending on the transmit power distribution and determining the network connectivity. It will be then shown that the transmit power allocation problem reduces to a convex constrained minimization problem. Our results show that, under the assumption of low traffic load, the power allocation strategy, which guarantees minimal delay, requires the maximization of network connectivity, which can be equivalently interpreted as the maximization of the number of non-zero entries of the adjacency matrix. The obtained theoretical results are confirmed by simulations for unslotted Zigbee WSNs.

  18. S-EMG signal compression based on domain transformation and spectral shape dynamic bit allocation

    PubMed Central

    2014-01-01

    Background Surface electromyographic (S-EMG) signal processing has been emerging in the past few years due to its non-invasive assessment of muscle function and structure and because of the fast growing rate of digital technology which brings about new solutions and applications. Factors such as sampling rate, quantization word length, number of channels and experiment duration can lead to a potentially large volume of data. Efficient transmission and/or storage of S-EMG signals are actually a research issue. That is the aim of this work. Methods This paper presents an algorithm for the data compression of surface electromyographic (S-EMG) signals recorded during isometric contractions protocol and during dynamic experimental protocols such as the cycling activity. The proposed algorithm is based on discrete wavelet transform to proceed spectral decomposition and de-correlation, on a dynamic bit allocation procedure to code the wavelets transformed coefficients, and on an entropy coding to minimize the remaining redundancy and to pack all data. The bit allocation scheme is based on mathematical decreasing spectral shape models, which indicates a shorter digital word length to code high frequency wavelets transformed coefficients. Four bit allocation spectral shape methods were implemented and compared: decreasing exponential spectral shape, decreasing linear spectral shape, decreasing square-root spectral shape and rotated hyperbolic tangent spectral shape. Results The proposed method is demonstrated and evaluated for an isometric protocol and for a dynamic protocol using a real S-EMG signal data bank. Objective performance evaluations metrics are presented. In addition, comparisons with other encoders proposed in scientific literature are shown. Conclusions The decreasing bit allocation shape applied to the quantized wavelet coefficients combined with arithmetic coding results is an efficient procedure. The performance comparisons of the proposed S-EMG data

  19. Opportunistic Capacity-Based Resource Allocation for Chunk-Based Multi-Carrier Cognitive Radio Sensor Networks

    PubMed Central

    Huang, Jie; Zeng, Xiaoping; Jian, Xin; Tan, Xiaoheng; Zhang, Qi

    2017-01-01

    The spectrum allocation for cognitive radio sensor networks (CRSNs) has received considerable research attention under the assumption that the spectrum environment is static. However, in practice, the spectrum environment varies over time due to primary user/secondary user (PU/SU) activity and mobility, resulting in time-varied spectrum resources. This paper studies resource allocation for chunk-based multi-carrier CRSNs with time-varied spectrum resources. We present a novel opportunistic capacity model through a continuous time semi-Markov chain (CTSMC) to describe the time-varied spectrum resources of chunks and, based on this, a joint power and chunk allocation model by considering the opportunistically available capacity of chunks is proposed. To reduce the computational complexity, we split this model into two sub-problems and solve them via the Lagrangian dual method. Simulation results illustrate that the proposed opportunistic capacity-based resource allocation algorithm can achieve better performance compared with traditional algorithms when the spectrum environment is time-varied. PMID:28106803

  20. Comparing administered and market-based water allocation systems through a consistent agent-based modeling framework.

    PubMed

    Zhao, Jianshi; Cai, Ximing; Wang, Zhongjing

    2013-07-15

    Water allocation can be undertaken through administered systems (AS), market-based systems (MS), or a combination of the two. The debate on the performance of the two systems has lasted for decades but still calls for attention in both research and practice. This paper compares water users' behavior under AS and MS through a consistent agent-based modeling framework for water allocation analysis that incorporates variables particular to both MS (e.g., water trade and trading prices) and AS (water use violations and penalties/subsidies). Analogous to the economic theory of water markets under MS, the theory of rational violation justifies the exchange of entitled water under AS through the use of cross-subsidies. Under water stress conditions, a unique water allocation equilibrium can be achieved by following a simple bargaining rule that does not depend upon initial market prices under MS, or initial economic incentives under AS. The modeling analysis shows that the behavior of water users (agents) depends on transaction, or administrative, costs, as well as their autonomy. Reducing transaction costs under MS or administrative costs under AS will mitigate the effect that equity constraints (originating with primary water allocation) have on the system's total net economic benefits. Moreover, hydrologic uncertainty is shown to increase market prices under MS and penalties/subsidies under AS and, in most cases, also increases transaction, or administrative, costs.

  1. An In-Depth Analysis of Decisions Made by Kentucky's School Based Decision-Making Councils.

    ERIC Educational Resources Information Center

    Klecker, Beverly M.; Austin, Jerry L.; Burns, Leonard T.

    This report describes the implementation of School-Based Decision-Making (SBDM) Councils. The research drew on a stratified random sample of high schools, middle and junior high schools, and elementary schools geographically distributed throughout the eight service regions of Kentucky. The paper also details the types of decisions being made by…

  2. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets

    PubMed Central

    Doubravsky, Karel; Dohnal, Mirko

    2015-01-01

    Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details. PMID:26158662

  3. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

    PubMed

    Doubravsky, Karel; Dohnal, Mirko

    2015-01-01

    Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

  4. The Implementation of Kentucky's School-Based Decision Making Program.

    ERIC Educational Resources Information Center

    Kentucky Univ., Lexington. Inst. on Education Reform.

    This report describes what schools and educators across Kentucky are doing to implement school reform in school-based decision-making based on the Kentucky Education Reform Act of 1990 (KERA). The School-Based Decision Making (SBDM) component of KERA is a decentralized governance structure that vests great authority in SBDM councils operating at…

  5. Deriving effective vaccine allocation strategies for pandemic influenza: Comparison of an agent-based simulation and a compartmental model

    PubMed Central

    Dalgıç, Özden O.; Özaltın, Osman Y.; Ciccotelli, William A.; Erenay, Fatih S.

    2017-01-01

    Individuals are prioritized based on their risk profiles when allocating limited vaccine stocks during an influenza pandemic. Computationally expensive but realistic agent-based simulations and fast but stylized compartmental models are typically used to derive effective vaccine allocation strategies. A detailed comparison of these two approaches, however, is often omitted. We derive age-specific vaccine allocation strategies to mitigate a pandemic influenza outbreak in Seattle by applying derivative-free optimization to an agent-based simulation and also to a compartmental model. We compare the strategies derived by these two approaches under various infection aggressiveness and vaccine coverage scenarios. We observe that both approaches primarily vaccinate school children, however they may allocate the remaining vaccines in different ways. The vaccine allocation strategies derived by using the agent-based simulation are associated with up to 70% decrease in total cost and 34% reduction in the number of infections compared to the strategies derived by using the compartmental model. Nevertheless, the latter approach may still be competitive for very low and/or very high infection aggressiveness. Our results provide insights about potential differences between the vaccine allocation strategies derived by using agent-based simulations and those derived by using compartmental models. PMID:28222123

  6. Allocation Games: Addressing the Ill-Posed Nature of Allocation in Life-Cycle Inventories.

    PubMed

    Hanes, Rebecca J; Cruze, Nathan B; Goel, Prem K; Bakshi, Bhavik R

    2015-07-07

    Allocation is required when a life cycle contains multi-functional processes. One approach to allocation is to partition the embodied resources in proportion to a criterion, such as product mass or cost. Many practitioners apply multiple partitioning criteria to avoid choosing one arbitrarily. However, life cycle results from different allocation methods frequently contradict each other, making it difficult or impossible for the practitioner to draw any meaningful conclusions from the study. Using the matrix notation for life-cycle inventory data, we show that an inventory that requires allocation leads to an ill-posed problem: an inventory based on allocation is one of an infinite number of inventories that are highly dependent upon allocation methods. This insight is applied to comparative life-cycle assessment (LCA), in which products with the same function but different life cycles are compared. Recently, there have been several studies that applied multiple allocation methods and found that different products were preferred under different methods. We develop the Comprehensive Allocation Investigation Strategy (CAIS) to examine any given inventory under all possible allocation decisions, enabling us to detect comparisons that are not robust to allocation, even when the comparison appears robust under conventional partitioning methods. While CAIS does not solve the ill-posed problem, it provides a systematic way to parametrize and examine the effects of partitioning allocation. The practical usefulness of this approach is demonstrated with two case studies. The first compares ethanol produced from corn stover hydrolysis, corn stover gasification, and corn grain fermentation. This comparison was not robust to allocation. The second case study compares 1,3-propanediol (PDO) produced from fossil fuels and from biomass, which was found to be a robust comparison.

  7. Integer programming-based approach to allocation of reporter genes for cell array analysis.

    PubMed

    Hayashida, Morihiro; Sun, Fuyan; Aburatani, Sachiyo; Horimoto, Katsuhisa; Akutsu, Tatsuya

    2008-01-01

    In this paper, we consider the problem of selecting the most effective set of reporter genes for analysis of biological networks using cell microarrays. We propose two graph theoretic formulations of the reporter gene allocation problem, and show that both problems are hard to approximate. We propose integer programming-based methods for solving practical instances of these problems optimally. We apply them to apoptosis pathway maps, and discuss the biological significance of the result. We also apply them to artificial networks, the result of which shows that optimal solutions can be obtained within several seconds for networks with 10,000 nodes.

  8. Analysis and simulation of the dynamic spectrum allocation based on parallel immune optimization in cognitive wireless networks.

    PubMed

    Huixin, Wu; Duo, Mo; He, Li

    2014-01-01

    Spectrum allocation is one of the key issues to improve spectrum efficiency and has become the hot topic in the research of cognitive wireless network. This paper discusses the real-time feature and efficiency of dynamic spectrum allocation and presents a new spectrum allocation algorithm based on the master-slave parallel immune optimization model. The algorithm designs a new encoding scheme for the antibody based on the demand for convergence rate and population diversity. For improving the calculating efficiency, the antibody affinity in the population is calculated in multiple computing nodes at the same time. Simulation results show that the algorithm reduces the total spectrum allocation time and can achieve higher network profits. Compared with traditional serial algorithms, the algorithm proposed in this paper has better speedup ratio and parallel efficiency.

  9. Allocation of Periodic Tasks with Precedences on Transputer-Based Systems

    DTIC Science & Technology

    1992-09-01

    MARSH2.OCC .......... ................. 78 C. OCCAM HARNESSES ON PROCESSOR PLUTO .. ...... 78 1. PLUTOH.OCC ............ ................. 78 2...ALLOCATION OF CHANNELS ON PLUTO ......... .. 11 Table III: ALLOCATION OF CHANNELS ON SATURN ...... .. 12 Table IV: ALLOCATION OF CHANNELS ON VENUS...HARNESSES ON PROCESSOR PLUTO ..... .. 14 Table VIII: OCCAM HARNESSES ON PROCESSOR SATURN . . .. 15 Table IX: OCCAM HARNESSES ON PROCESSOR VENUS ..... 15

  10. Functional Allocation for Ground-Based Automated Separation Assurance in NextGen

    NASA Technical Reports Server (NTRS)

    Prevot, Thomas; Mercer, Joey; Martin, Lynne; Homola, Jeffrey; Cabrall, Christopher; Brasil, Connie

    2010-01-01

    As part of an ongoing research effort into functional allocation in a NextGen environment, a controller-in-the-loop study on ground-based automated separation assurance was conducted at NASA Ames' Airspace Operations Laboratory in February 2010. Participants included six FAA front line managers, who are currently certified professional controllers and four recently retired controllers. Traffic scenarios were 15 and 30 minutes long where controllers interacted with advanced technologies for ground-based separation assurance, weather avoidance, and arrival metering. The automation managed the separation by resolving conflicts automatically and involved controllers only by exception, e.g., when the automated resolution would have been outside preset limits. Results from data analyses show that workload was low despite high levels of traffic, Operational Errors did occur but were closely tied to local complexity, and safety acceptability ratings varied with traffic levels. Positive feedback was elicited for the overall concept with discussion on the proper allocation of functions and trust in automation.

  11. K-Shortest-Path-Based Evacuation Routing with Police Resource Allocation in City Transportation Networks.

    PubMed

    He, Yunyue; Liu, Zhong; Shi, Jianmai; Wang, Yishan; Zhang, Jiaming; Liu, Jinyuan

    2015-01-01

    Emergency evacuation aims to transport people from dangerous places to safe shelters as quickly as possible. Police play an important role in the evacuation process, as they can handle traffic accidents immediately and help people move smoothly on roads. This paper investigates an evacuation routing problem that involves police resource allocation. We propose a novel k-th-shortest-path-based technique that uses explicit congestion control to optimize evacuation routing and police resource allocation. A nonlinear mixed-integer programming model is presented to formulate the problem. The model's objective is to minimize the overall evacuation clearance time. Two algorithms are given to solve the problem. The first one linearizes the original model and solves the linearized problem with CPLEX. The second one is a heuristic algorithm that uses a police resource utilization efficiency index to directly solve the original model. This police resource utilization efficiency index significantly aids in the evaluation of road links from an evacuation throughput perspective. The proposed algorithms are tested with a number of examples based on real data from cities of different sizes. The computational results show that the police resource utilization efficiency index is very helpful in finding near-optimal solutions. Additionally, comparing the performance of the heuristic algorithm and the linearization method by using randomly generated examples indicates that the efficiency of the heuristic algorithm is superior.

  12. K-Shortest-Path-Based Evacuation Routing with Police Resource Allocation in City Transportation Networks

    PubMed Central

    He, Yunyue; Liu, Zhong; Shi, Jianmai; Wang, Yishan; Zhang, Jiaming; Liu, Jinyuan

    2015-01-01

    Emergency evacuation aims to transport people from dangerous places to safe shelters as quickly as possible. Police play an important role in the evacuation process, as they can handle traffic accidents immediately and help people move smoothly on roads. This paper investigates an evacuation routing problem that involves police resource allocation. We propose a novel k-th-shortest-path-based technique that uses explicit congestion control to optimize evacuation routing and police resource allocation. A nonlinear mixed-integer programming model is presented to formulate the problem. The model’s objective is to minimize the overall evacuation clearance time. Two algorithms are given to solve the problem. The first one linearizes the original model and solves the linearized problem with CPLEX. The second one is a heuristic algorithm that uses a police resource utilization efficiency index to directly solve the original model. This police resource utilization efficiency index significantly aids in the evaluation of road links from an evacuation throughput perspective. The proposed algorithms are tested with a number of examples based on real data from cities of different sizes. The computational results show that the police resource utilization efficiency index is very helpful in finding near-optimal solutions. Additionally, comparing the performance of the heuristic algorithm and the linearization method by using randomly generated examples indicates that the efficiency of the heuristic algorithm is superior. PMID:26226109

  13. Computationally Efficient Power Allocation Algorithm in Multicarrier-Based Cognitive Radio Networks: OFDM and FBMC Systems

    NASA Astrophysics Data System (ADS)

    Shaat, Musbah; Bader, Faouzi

    2010-12-01

    Cognitive Radio (CR) systems have been proposed to increase the spectrum utilization by opportunistically access the unused spectrum. Multicarrier communication systems are promising candidates for CR systems. Due to its high spectral efficiency, filter bank multicarrier (FBMC) can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM) for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier-based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs) constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The proposed algorithm utilizes the spectrum holes in PUs bands as well as active PU bands. The performance of the proposed algorithm is investigated for OFDM and FBMC based CR systems. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and proves the efficiency of using FBMC in CR context.

  14. CUDT: a CUDA based decision tree algorithm.

    PubMed

    Lo, Win-Tsung; Chang, Yue-Shan; Sheu, Ruey-Kai; Chiu, Chun-Chieh; Yuan, Shyan-Ming

    2014-01-01

    Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in the era without new technology help. In order to improve data processing latency in huge data mining, in this paper, we design and implement a new parallelized decision tree algorithm on a CUDA (compute unified device architecture), which is a GPGPU solution provided by NVIDIA. In the proposed system, CPU is responsible for flow control while the GPU is responsible for computation. We have conducted many experiments to evaluate system performance of CUDT and made a comparison with traditional CPU version. The results show that CUDT is 5 ∼ 55 times faster than Weka-j48 and is 18 times speedup than SPRINT for large data set.

  15. A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems.

    PubMed

    Wang, Lujia; Liu, Ming; Meng, Max Q-H

    2017-02-01

    Cloud computing enables users to share computing resources on-demand. The cloud computing framework cannot be directly mapped to cloud robotic systems with ad hoc networks since cloud robotic systems have additional constraints such as limited bandwidth and dynamic structure. However, most multirobotic applications with cooperative control adopt this decentralized approach to avoid a single point of failure. Robots need to continuously update intensive data to execute tasks in a coordinated manner, which implies real-time requirements. Thus, a resource allocation strategy is required, especially in such resource-constrained environments. This paper proposes a hierarchical auction-based mechanism, namely link quality matrix (LQM) auction, which is suitable for ad hoc networks by introducing a link quality indicator. The proposed algorithm produces a fast and robust method that is accurate and scalable. It reduces both global communication and unnecessary repeated computation. The proposed method is designed for firm real-time resource retrieval for physical multirobot systems. A joint surveillance scenario empirically validates the proposed mechanism by assessing several practical metrics. The results show that the proposed LQM auction outperforms state-of-the-art algorithms for resource allocation.

  16. A swarm intelligence based memetic algorithm for task allocation in distributed systems

    NASA Astrophysics Data System (ADS)

    Sarvizadeh, Raheleh; Haghi Kashani, Mostafa

    2012-01-01

    This paper proposes a Swarm Intelligence based Memetic algorithm for Task Allocation and scheduling in distributed systems. The tasks scheduling in distributed systems is known as an NP-complete problem. Hence, many genetic algorithms have been proposed for searching optimal solutions from entire solution space. However, these existing approaches are going to scan the entire solution space without considering the techniques that can reduce the complexity of the optimization. Spending too much time for doing scheduling is considered the main shortcoming of these approaches. Therefore, in this paper memetic algorithm has been used to cope with this shortcoming. With regard to load balancing efficiently, Bee Colony Optimization (BCO) has been applied as local search in the proposed memetic algorithm. Extended experimental results demonstrated that the proposed method outperformed the existing GA-based method in terms of CPU utilization.

  17. A swarm intelligence based memetic algorithm for task allocation in distributed systems

    NASA Astrophysics Data System (ADS)

    Sarvizadeh, Raheleh; Haghi Kashani, Mostafa

    2011-12-01

    This paper proposes a Swarm Intelligence based Memetic algorithm for Task Allocation and scheduling in distributed systems. The tasks scheduling in distributed systems is known as an NP-complete problem. Hence, many genetic algorithms have been proposed for searching optimal solutions from entire solution space. However, these existing approaches are going to scan the entire solution space without considering the techniques that can reduce the complexity of the optimization. Spending too much time for doing scheduling is considered the main shortcoming of these approaches. Therefore, in this paper memetic algorithm has been used to cope with this shortcoming. With regard to load balancing efficiently, Bee Colony Optimization (BCO) has been applied as local search in the proposed memetic algorithm. Extended experimental results demonstrated that the proposed method outperformed the existing GA-based method in terms of CPU utilization.

  18. Challenges in defining an optimal approach to formula-based allocations of public health funds in the United States

    PubMed Central

    Buehler, James W; Holtgrave, David R

    2007-01-01

    Background Controversy and debate can arise whenever public health agencies determine how program funds should be allocated among constituent jurisdictions. Two common strategies for making such allocations are expert review of competitive applications and the use of funding formulas. Despite widespread use of funding formulas by public health agencies in the United States, formula allocation strategies in public health have been subject to relatively little formal scrutiny, with the notable exception of the attention focused on formula funding of HIV care programs. To inform debates and deliberations in the selection of a formula-based approach, we summarize key challenges to formula-based funding, based on prior reviews of federal programs in the United States. Discussion The primary challenge lies in identifying data sources and formula calculation methods that both reflect and serve program objectives, with or without adjustments for variations in the cost of delivering services, the availability of local resources, capacity, or performance. Simplicity and transparency are major advantages of formula-based allocations, but these advantages can be offset if formula-based allocations are perceived to under- or over-fund some jurisdictions, which may result from how guaranteed minimum funding levels are set or from "hold-harmless" provisions intended to blunt the effects of changes in formula design or random variations in source data. While fairness is considered an advantage of formula-based allocations, the design of a formula may implicitly reflect unquestioned values concerning equity versus equivalence in setting funding policies. Whether or how past or projected trends are taken into account can also have substantial impacts on allocations. Summary Insufficient attention has been focused on how the approach to designing funding formulas in public health should differ for treatment or service versus prevention programs. Further evaluations of formula-based

  19. Organizing for Evidence-Based Decision Making and Improvement

    ERIC Educational Resources Information Center

    Leimer, Christina

    2012-01-01

    In today's accountability climate, regional accrediting bodies are requiring colleges and universities to develop and sustain a culture of evidence-based decision making and improvement. But two-thirds of college presidents in a 2011 "Inside Higher Ed" survey said their institutions are not particularly strong at using data for making decisions.…

  20. CUDT: A CUDA Based Decision Tree Algorithm

    PubMed Central

    Sheu, Ruey-Kai; Chiu, Chun-Chieh

    2014-01-01

    Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in the era without new technology help. In order to improve data processing latency in huge data mining, in this paper, we design and implement a new parallelized decision tree algorithm on a CUDA (compute unified device architecture), which is a GPGPU solution provided by NVIDIA. In the proposed system, CPU is responsible for flow control while the GPU is responsible for computation. We have conducted many experiments to evaluate system performance of CUDT and made a comparison with traditional CPU version. The results show that CUDT is 5∼55 times faster than Weka-j48 and is 18 times speedup than SPRINT for large data set. PMID:25140346

  1. Extracting clinical information to support medical decision based on standards.

    PubMed

    Gomoi, Valentin; Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Stoicu-Tivadar, Vasile

    2011-01-01

    The paper presents a method connecting medical databases to a medical decision system, and describes a service created to extract the necessary information that is transferred based on standards. The medical decision can be improved based on many inputs from different medical locations. The developed solution is described for a concrete case concerning the management for chronic pelvic pain, based on the information retrieved from diverse healthcare databases.

  2. On-Line Allocation Of Robot Resources To Task Plans

    NASA Astrophysics Data System (ADS)

    Lyons, Damian M.

    1989-02-01

    In this paper, I present an approach to representing plans that make on-line decisions about resource allocation. An on-line decision is the evaluation of a conditional expression involving sensory information as the plan is being executed. I use a plan representation called 7ZS10'1 1,12that has been especially designed for the domain of robot programming, and in particular, for the problem of on-line decisions. The resource allocation example is based on the robot assembly cell architecture outlined by Venkataraman and Lyons16. I begin by setting forth a definition of on-line decision making and some arguments as to why this form of decision making is important and useful. To set the context for the resource allocation example, I take some care in categorizing the types of on-line decision making and the approaches adopted by other workers so far. In particular, I justify a plan-based approach to the study of on-line decision making. From that, the focus shifts to one type of decision making: on-line allocation of robot resources to task plans. Robot resources are the physical manipulators (grippers, wrists, arms, feeders, etc) that are available to carry out the task. I formulate the assembly cell architecture of Venkataraman and Lyons16 as an R.S plan schema, and show how the on-line allocation specified in that architecture can be implemented. Finally, I show how considering the on-line allocation of logical resources, that is a physical resource plus some model information, can be used as a non-traditional approach to some problems in robot task planning.

  3. Using bi-directional communications in a market-based resource allocation system

    DOEpatents

    Chassin, David P; Pratt, Robert G

    2015-05-05

    Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.

  4. Using bi-directional communications in a market-based resource allocation system

    DOEpatents

    Chassin, David P.; Pratt, Robert G.

    2015-09-08

    Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.

  5. Using bi-directional communications in a market-based resource allocation system

    DOEpatents

    Chassin, David P; Pratt, Robert G

    2014-04-01

    Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.

  6. Electric power grid control using a market-based resource allocation system

    DOEpatents

    Chassin, David P

    2014-01-28

    Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.

  7. Electric power grid control using a market-based resource allocation system

    DOEpatents

    Chassin, David P.

    2015-07-21

    Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.

  8. Using one-way communications in a market-based resource allocation system

    DOEpatents

    Chassin, David P.; Pratt, Robert G.

    2014-07-22

    Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.

  9. Geographic Resource Allocation Based on Cost Effectiveness: An Application to Malaria Policy.

    PubMed

    Drake, Tom L; Lubell, Yoel; Kyaw, Shwe Sin; Devine, Angela; Kyaw, Myat Phone; Day, Nicholas P J; Smithuis, Frank M; White, Lisa J

    2017-02-10

    Healthcare services are often provided to a country as a whole, though in many cases the available resources can be more effectively targeted to specific geographically defined populations. In the case of malaria, risk is highly geographically heterogeneous, and many interventions, such as insecticide-treated bed nets and malaria community health workers, can be targeted to populations in a way that maximises impact for the resources available. This paper describes a framework for geographically targeted budget allocation based on the principles of cost-effectiveness analysis and applied to priority setting in malaria control and elimination. The approach can be used with any underlying model able to estimate intervention costs and effects given relevant local data. Efficient geographic targeting of core malaria interventions could significantly increase the impact of the resources available, accelerating progress towards elimination. These methods may also be applicable to priority setting in other disease areas.

  10. Task allocation in a distributed computing system

    NASA Technical Reports Server (NTRS)

    Seward, Walter D.

    1987-01-01

    A conceptual framework is examined for task allocation in distributed systems. Application and computing system parameters critical to task allocation decision processes are discussed. Task allocation techniques are addressed which focus on achieving a balance in the load distribution among the system's processors. Equalization of computing load among the processing elements is the goal. Examples of system performance are presented for specific applications. Both static and dynamic allocation of tasks are considered and system performance is evaluated using different task allocation methodologies.

  11. Resource Allocation Within Universities. Occasional Paper 3. SDU Staff Development in Universities Programme.

    ERIC Educational Resources Information Center

    Orton, F. J.

    Resource allocation in universities is analyzed based on economic theory and a theory of organizational behavior in universities. Basic methods of reaching decisions regarding allocation are intuition and numbers and combinations of the two. The intuitive method assumes a university committee can judge its needs. The numerical method employs a…

  12. Development of a Decision Support Tool to Inform Resource Allocation for Critical Infrastructure Protection in Homeland Security

    DTIC Science & Technology

    2008-06-01

    would have a debilitating impact on security, national economic security, national public health or safety, or any combination of those matters.” – The... health , emergency services, defense industrial base, banking and finance, chemicals and hazardous materials, and postal and shipping. A network is...links might represent water pipes or aqueducts . Figure 1 An example network 4 Threat, t, is the probability that an attack will be attempted

  13. Multi-Objective, Auto-Optimization Modeling for Resource Allocation Decision Making in the Military Health System

    DTIC Science & Technology

    2014-01-22

    1992) and MINOS (Murtagh & Saunders, 1983) non-linear programming ( NLP ) solvers, a simple, hospital-based textbook problem (Anderson et al., 2012...example, using the CONOPT NLP solver in GAMS resulted in an alternate (but similar) solution set. Detailing multiple solution sets that result in...changing funding (COST) and FTEs as shown in Table 4 (CONOPT) and in Table 5 (MINOS). Both NLP solvers executed this analysis (see the Appendix for the

  14. SADA: Ecological Risk Based Decision Support System for Selective Remediation

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

  15. Microcomputer-Based Expert System for Clinical Decision-Making

    PubMed Central

    Hudson, Donna L.; Estrin, Thelma

    1981-01-01

    A computerized rule-based expert system for chest pain analysis in the emergency room has been developed as a medical decision-making tool. The rules are based on a previously established criteria mapping procedure developed for evaluating emergency room decisions. The system is implemented in PASCAL, a standardized language, and hence is machine-independent, and also has modest memory requirements. The overall design permits usage by those unfamiliar with computers.

  16. Probabilistic resource allocation system with self-adaptive capability

    NASA Technical Reports Server (NTRS)

    Yufik, Yan M. (Inventor)

    1998-01-01

    A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and weighted links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Weights are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

  17. Probabilistic resource allocation system with self-adaptive capability

    NASA Technical Reports Server (NTRS)

    Yufik, Yan M. (Inventor)

    1996-01-01

    A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and directed links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Reliability values are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

  18. The Use of Different Rules to Allocate Reward and Punishment.

    ERIC Educational Resources Information Center

    Mueller, Charles W.

    Much research has been conducted about how and when individuals allocate rewards, yet little research exists concerning the allocation of punishment. The process of allocating negative outcomes may be different from the decision making process for positive outcomes. To examine the decision making process for allocating rewards and punishment,…

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

    NASA Astrophysics Data System (ADS)

    Vasilecas, Olegas; Smaizys, Aidas; Brazinskas, Ramunas

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

  20. Channel Allocation Options.

    ERIC Educational Resources Information Center

    Powers, Robert S.

    The Frequency Allocation Subcommittee of the Coordinating Committee for Cable Communication Systems, Institute of Electrical and Electronic Engineers, was formed to produce a background report on the general problems of frequency allocation and assignments in cable television. The present paper, based on the subcommittee's interim report,…

  1. Optimal Power Allocation for CC-HARQ-based Cognitive Radio with Statistical CSI in Nakagami Slow Fading Channels

    NASA Astrophysics Data System (ADS)

    Xu, Ding; Li, Qun

    2017-01-01

    This paper addresses the power allocation problem for cognitive radio (CR) based on hybrid-automatic-repeat-request (HARQ) with chase combining (CC) in Nakagamimslow fading channels. We assume that, instead of the perfect instantaneous channel state information (CSI), only the statistical CSI is available at the secondary user (SU) transmitter. The aim is to minimize the SU outage probability under the primary user (PU) interference outage constraint. Using the Lagrange multiplier method, an iterative and recursive algorithm is derived to obtain the optimal power allocation for each transmission round. Extensive numerical results are presented to illustrate the performance of the proposed algorithm.

  2. Task allocation among multiple intelligent robots

    NASA Technical Reports Server (NTRS)

    Gasser, L.; Bekey, G.

    1987-01-01

    Researchers describe the design of a decentralized mechanism for allocating assembly tasks in a multiple robot assembly workstation. Currently, the approach focuses on distributed allocation to explore its feasibility and its potential for adaptability to changing circumstances, rather than for optimizing throughput. Individual greedy robots make their own local allocation decisions using both dynamic allocation policies which propagate through a network of allocation goals, and local static and dynamic constraints describing which robots are elibible for which assembly tasks. Global coherence is achieved by proper weighting of allocation pressures propagating through the assembly plan. Deadlock avoidance and synchronization is achieved using periodic reassessments of local allocation decisions, ageing of allocation goals, and short-term allocation locks on goals.

  3. Decision Making Under Uncertainty: A Neural Model Based on Partially Observable Markov Decision Processes

    PubMed Central

    Rao, Rajesh P. N.

    2010-01-01

    A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs). Actions are selected based not on a single “optimal” estimate of state but on the posterior distribution over states (the “belief” state). We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD) learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize

  4. Perception-based Co-evolutionary Reinforcement Learning for UAV Sensor Allocation

    DTIC Science & Technology

    2003-02-01

    reinforcement learning was developed for jointly addressing sensor allocation on each individual UAV and allocation of a team of UAVs in the geographical search space. An elaborate problem setup was simulated and experimented with, for testing and analysis of this framework using the Player-Stage multi-agent simulator. This simulator was developed jointly at the USC Robotics Research Lab and HRL Labs.The experimental results demonstrated a very strong performance of our methodology for UAV sensor allocation problem domains. Our results indicate that not only it is feasible

  5. Knowledge-Based Decision Support in Department of Defense Acquisitions

    DTIC Science & Technology

    2010-09-01

    2005) reviewed and analyzed the National Aeronautics and Space Administration ( NASA ) project management policies and compared them to the GAO’s best...practices on knowledge-based decision making. The study was primarily focused on the Goddard Space Flight Center, the Jet Propulsion Lab, Johnson ...Space Center, and Marshall Space Flight Center. During its investigation, the GAO found NASA deficient in key criteria and decision reviews to fully

  6. Network Allocation Vector (NAV) Optimization for Underwater Handshaking-Based Protocols

    PubMed Central

    Cho, Junho; Shitiri, Ethungshan; Cho, Ho-Shin

    2016-01-01

    In this paper, we obtained the optimized network allocation vector (NAV) for underwater handshaking-based protocols, as inefficient determination of the NAV leads to unnecessarily long silent periods. We propose a scheme which determines the NAV by taking into account all possible propagation delays: propagation delay between a source and a destination; propagation delay between a source and the neighbors; and propagation delay between a destination and the neighbors. Such an approach effectively allows the NAV to be determined precisely equal to duration of a busy channel, and the silent period can be set commensurate to that duration. This allows for improvements in the performance of handshaking-based protocols, such as the carrier sense multiple access/collision avoidance (CSMA/CA) protocol, in terms of throughput and fairness. To evaluate the performance of the proposed scheme, performance comparisons were carried out through simulations with prior NAV setting methods. The simulation results show that the proposed scheme outperforms the other schemes in terms of throughput and fairness. PMID:28029122

  7. Network Allocation Vector (NAV) Optimization for Underwater Handshaking-Based Protocols.

    PubMed

    Cho, Junho; Shitiri, Ethungshan; Cho, Ho-Shin

    2016-12-24

    In this paper, we obtained the optimized network allocation vector (NAV) for underwater handshaking-based protocols, as inefficient determination of the NAV leads to unnecessarily long silent periods. We propose a scheme which determines the NAV by taking into account all possible propagation delays: propagation delay between a source and a destination; propagation delay between a source and the neighbors; and propagation delay between a destination and the neighbors. Such an approach effectively allows the NAV to be determined precisely equal to duration of a busy channel, and the silent period can be set commensurate to that duration. This allows for improvements in the performance of handshaking-based protocols, such as the carrier sense multiple access/collision avoidance (CSMA/CA) protocol, in terms of throughput and fairness. To evaluate the performance of the proposed scheme, performance comparisons were carried out through simulations with prior NAV setting methods. The simulation results show that the proposed scheme outperforms the other schemes in terms of throughput and fairness.

  8. Application-oriented region of interest based image compression using bit-allocation optimization

    NASA Astrophysics Data System (ADS)

    Zhu, Yuanping

    2015-01-01

    Region of interest (ROI) based image compression can offer a high image-compression ratio along with high quality in the important regions of the image. For many applications, stable compression quality is required for both the ROIs and the images. However, image compression does not consider information specific to the application and cannot meet this requirement well. This paper proposes an application-oriented ROI-based image-compression method using bit-allocation optimization. Unlike typical methods that define bit-rate parameters empirically, the proposed method adjusts the bit-rate parameters adaptively to both images and ROIs. First, an application-dependent optimization model is constructed. The relationship between the compression parameters and the image content is learned from a training image set. Image redundancy is used to measure the compression capability of image content. Then, during compression, the global bit rate and the ROI bit rate are adjusted in the images and ROIs, respectively-supported by the application-dependent information in the optimization model. As a result, stable compression quality is assured in the applications. Experiments with two different applications showed that quality deviation in the reconstructed images decreased, verifying the effectiveness of the proposed method.

  9. Reduced model-based decision-making in schizophrenia.

    PubMed

    Culbreth, Adam J; Westbrook, Andrew; Daw, Nathaniel D; Botvinick, Matthew; Barch, Deanna M

    2016-08-01

    Individuals with schizophrenia have a diminished ability to use reward history to adaptively guide behavior. However, tasks traditionally used to assess such deficits often rely on multiple cognitive and neural processes, leaving etiology unresolved. In the current study, we adopted recent computational formalisms of reinforcement learning to distinguish between model-based and model-free decision-making in hopes of specifying mechanisms associated with reinforcement-learning dysfunction in schizophrenia. Under this framework, decision-making is model-free to the extent that it relies solely on prior reward history, and model-based if it relies on prospective information such as motivational state, future consequences, and the likelihood of obtaining various outcomes. Model-based and model-free decision-making was assessed in 33 schizophrenia patients and 30 controls using a 2-stage 2-alternative forced choice task previously demonstrated to discern individual differences in reliance on the 2 forms of reinforcement-learning. We show that, compared with controls, schizophrenia patients demonstrate decreased reliance on model-based decision-making. Further, parameter estimates of model-based behavior correlate positively with IQ and working memory measures, suggesting that model-based deficits seen in schizophrenia may be partially explained by higher-order cognitive deficits. These findings demonstrate specific reinforcement-learning and decision-making deficits and thereby provide valuable insights for understanding disordered behavior in schizophrenia. (PsycINFO Database Record

  10. Allocating physicians' overhead costs to services: an econometric/accounting-activity based-approach.

    PubMed

    Peden, Al; Baker, Judith J

    2002-01-01

    Using the optimizing properties of econometric analysis, this study analyzes how physician overhead costs (OC) can be allocated to multiple activities to maximize precision in reimbursing the costs of services. Drawing on work by Leibenstein and Friedman, the analysis also shows that allocating OC to multiple activities unbiased by revenue requires controlling for revenue when making the estimates. Further econometric analysis shows that it is possible to save about 10 percent of OC by paying only for those that are necessary.

  11. Improvements to Air Force Strategic Basing Decisions

    DTIC Science & Technology

    2016-01-01

    MOB main operating base NEPA National Environmental Policy Act NSC-68 National Security Council Report 68 OCONUS outside of the continental United...6.3 !  GS Locality – 2.7 Criteria to Base Active Duty-Led 36-PAA KC-46A Classic Association ( MOB 1) (SecAF Approved 27 Apr 12) 6 10 survey...eliminate static formations in Europe and Asia by moving away from large main operating bases ( MOBs ) in favor of access to cold and warm facilities that

  12. Episodic memories predict adaptive value-based decision-making.

    PubMed

    Murty, Vishnu P; FeldmanHall, Oriel; Hunter, Lindsay E; Phelps, Elizabeth A; Davachi, Lila

    2016-05-01

    Prior research illustrates that memory can guide value-based decision-making. For example, previous work has implicated both working memory and procedural memory (i.e., reinforcement learning) in guiding choice. However, other types of memories, such as episodic memory, may also influence decision-making. Here we test the role for episodic memory-specifically item versus associative memory-in supporting value-based choice. Participants completed a task where they first learned the value associated with trial unique lotteries. After a short delay, they completed a decision-making task where they could choose to reengage with previously encountered lotteries, or new never before seen lotteries. Finally, participants completed a surprise memory test for the lotteries and their associated values. Results indicate that participants chose to reengage more often with lotteries that resulted in high versus low rewards. Critically, participants not only formed detailed, associative memories for the reward values coupled with individual lotteries, but also exhibited adaptive decision-making only when they had intact associative memory. We further found that the relationship between adaptive choice and associative memory generalized to more complex, ecologically valid choice behavior, such as social decision-making. However, individuals more strongly encode experiences of social violations-such as being treated unfairly, suggesting a bias for how individuals form associative memories within social contexts. Together, these findings provide an important integration of episodic memory and decision-making literatures to better understand key mechanisms supporting adaptive behavior.

  13. A Subcarrier-Pair Based Resource Allocation Scheme Using Proportional Fairness for Cooperative OFDM-Based Cognitive Radio Networks

    PubMed Central

    Ma, Yongtao; Zhou, Liuji; Liu, Kaihua

    2013-01-01

    The paper presents a joint subcarrier-pair based resource allocation algorithm in order to improve the efficiency and fairness of cooperative multiuser orthogonal frequency division multiplexing (MU-OFDM) cognitive radio (CR) systems. A communication model where one source node communicates with one destination node assisted by one half-duplex decode-and-forward (DF) relay is considered in the paper. An interference-limited environment is considered, with the constraint of transmitted sum-power over all channels and aggregate average interference towards multiple primary users (PUs). The proposed resource allocation algorithm is capable of maximizing both the system transmission efficiency and fairness among secondary users (SUs). Besides, the proposed algorithm can also keep the interference introduced to the PU bands below a threshold. A proportional fairness constraint is used to assure that each SU can achieve a required data rate, with quality of service guarantees. Moreover, we extend the analysis to the scenario where each cooperative SU has no channel state information (CSI) about non-adjacent links. We analyzed the throughput and fairness tradeoff in CR system. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results. PMID:23939586

  14. Integrated visual vocabulary in latent Dirichlet allocation-based scene classification for IKONOS image

    NASA Astrophysics Data System (ADS)

    Kusumaningrum, Retno; Wei, Hong; Manurung, Ruli; Murni, Aniati

    2014-01-01

    Scene classification based on latent Dirichlet allocation (LDA) is a more general modeling method known as a bag of visual words, in which the construction of a visual vocabulary is a crucial quantization process to ensure success of the classification. A framework is developed using the following new aspects: Gaussian mixture clustering for the quantization process, the use of an integrated visual vocabulary (IVV), which is built as the union of all centroids obtained from the separate quantization process of each class, and the usage of some features, including edge orientation histogram, CIELab color moments, and gray-level co-occurrence matrix (GLCM). The experiments are conducted on IKONOS images with six semantic classes (tree, grassland, residential, commercial/industrial, road, and water). The results show that the use of an IVV increases the overall accuracy (OA) by 11 to 12% and 6% when it is implemented on the selected and all features, respectively. The selected features of CIELab color moments and GLCM provide a better OA than the implementation over CIELab color moment or GLCM as individuals. The latter increases the OA by only ˜2 to 3%. Moreover, the results show that the OA of LDA outperforms the OA of C4.5 and naive Bayes tree by ˜20%.

  15. Task Allocation of Wasps Governed by Common Stomach: A Model Based on Electric Circuits

    PubMed Central

    2016-01-01

    Simple regulatory mechanisms based on the idea of the saturable ‘common stomach’ can control the regulation of construction behavior and colony-level responses to environmental perturbations in Metapolybia wasp societies. We mapped the different task groups to mutual inductance electrical circuits and used Kirchoff’s basic voltage laws to build a model that uses master equations from physics, yet is able to provide strong predictions for this complex biological phenomenon. Similar to real colonies, independently of the initial conditions, the system shortly sets into an equilibrium, which provides optimal task allocation for a steady construction, depending on the influx of accessible water. The system is very flexible and in the case of perturbations, it reallocates its workforce and adapts to the new situation with different equilibrium levels. Similar to the finding of field studies, decreasing any task groups caused decrease of construction; increasing or decreasing water inflow stimulated or reduced the work of other task groups while triggering compensatory behavior in water foragers. We also showed that only well connected circuits are able to produce adequate construction and this agrees with the finding that this type of task partitioning only exists in larger colonies. Studying the buffer properties of the common stomach and its effect on the foragers revealed that it provides stronger negative feedback to the water foragers, while the connection between the pulp foragers and the common stomach has a strong fixed-point attractor, as evidenced by the dissipative trajectory. PMID:27861633

  16. Performance-based workload assessment: Allocation strategy and added task sensitivity

    NASA Technical Reports Server (NTRS)

    Vidulich, Michael A.

    1990-01-01

    The preliminary results of a research program investigating the use of added tasks to evaluate mental workload are reviewed. The focus of the first studies was a reappraisal of the traditional secondary task logic that encouraged the use of low-priority instructions for the added task. It was believed that such low-priority tasks would encourage subjects to split their available resources among the two tasks. The primary task would be assigned all the resources it needed, and any remaining reserve capacity would be assigned to the secondary task. If the model were correct, this approach was expected to combine sensitivity to primary task difficulty with unintrusiveness to primary task performance. The first studies of the current project demonstrated that a high-priority added task, although intrusive, could be more sensitive than the traditional low-priority secondary task. These results suggested that a more appropriate model of the attentional effects associated with added task performance might be based on capacity switching, rather than the traditional optimal allocation model.

  17. Task Allocation of Wasps Governed by Common Stomach: A Model Based on Electric Circuits.

    PubMed

    Hilbun, Allison; Karsai, Istvan

    2016-01-01

    Simple regulatory mechanisms based on the idea of the saturable 'common stomach' can control the regulation of construction behavior and colony-level responses to environmental perturbations in Metapolybia wasp societies. We mapped the different task groups to mutual inductance electrical circuits and used Kirchoff's basic voltage laws to build a model that uses master equations from physics, yet is able to provide strong predictions for this complex biological phenomenon. Similar to real colonies, independently of the initial conditions, the system shortly sets into an equilibrium, which provides optimal task allocation for a steady construction, depending on the influx of accessible water. The system is very flexible and in the case of perturbations, it reallocates its workforce and adapts to the new situation with different equilibrium levels. Similar to the finding of field studies, decreasing any task groups caused decrease of construction; increasing or decreasing water inflow stimulated or reduced the work of other task groups while triggering compensatory behavior in water foragers. We also showed that only well connected circuits are able to produce adequate construction and this agrees with the finding that this type of task partitioning only exists in larger colonies. Studying the buffer properties of the common stomach and its effect on the foragers revealed that it provides stronger negative feedback to the water foragers, while the connection between the pulp foragers and the common stomach has a strong fixed-point attractor, as evidenced by the dissipative trajectory.

  18. Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction.

    PubMed

    Nezarat, Amin; Dastghaibifard, G H

    2015-01-01

    One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer's utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider.

  19. Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction

    PubMed Central

    Nezarat, Amin; Dastghaibifard, GH

    2015-01-01

    One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer’s utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider. PMID:26431035

  20. Microeconomics-based resource allocation in overlay networks by using non-strategic behavior modeling

    NASA Astrophysics Data System (ADS)

    Analoui, Morteza; Rezvani, Mohammad Hossein

    2011-01-01

    Behavior modeling has recently been investigated for designing self-organizing mechanisms in the context of communication networks in order to exploit the natural selfishness of the users with the goal of maximizing the overall utility. In strategic behavior modeling, the users of the network are assumed to be game players who seek to maximize their utility with taking into account the decisions that the other players might make. The essential difference between the aforementioned researches and this work is that it incorporates the non-strategic decisions in order to design the mechanism for the overlay network. In this solution concept, the decisions that a peer might make does not affect the actions of the other peers at all. The theory of consumer-firm developed in microeconomics is a model of the non-strategic behavior that we have adopted in our research. Based on it, we have presented distributed algorithms for peers' "joining" and "leaving" operations. We have modeled the overlay network as a competitive economy in which the content provided by an origin server can be viewed as commodity and the origin server and the peers who multicast the content to their downside are considered as the firms. On the other hand, due to the dual role of the peers in the overlay network, they can be considered as the consumers as well. On joining to the overlay economy, each peer is provided with an income and tries to get hold of the service regardless to the behavior of the other peers. We have designed the scalable algorithms in such a way that the existence of equilibrium price (known as Walrasian equilibrium price) is guaranteed.

  1. Modulation of Saccade Vigor during Value-Based Decision Making

    PubMed Central

    Lempert, Karolina M.; Glimcher, Paul W.; Shadmehr, Reza

    2015-01-01

    During value-based decision-making, individuals consider the various options and select the one that provides the maximum subjective value. Although the brain integrates abstract information to compute and compare these values, the only behavioral outcome is often the decision itself. However, if the options are visual stimuli, during deliberation the brain moves the eyes from one stimulus to the other. Previous work suggests that saccade vigor, i.e., peak velocity as a function of amplitude, is greater if reward is associated with the visual stimulus. This raises the possibility that vigor during the free viewing of options may be influenced by the valuation of each option. Here, humans chose between a small, immediate monetary reward and a larger but delayed reward. As the deliberation began, vigor was similar for the saccades made to the two options but diverged 0.5 s before decision time, becoming greater for the preferred option. This difference in vigor increased as a function of the difference in the subjective values that the participant assigned to the delayed and immediate options. After the decision was made, participants continued to gaze at the options, but with reduced vigor, making it possible to infer timing of the decision from the sudden drop in vigor. Therefore, the subjective value that the brain assigned to a stimulus during decision-making affected the motor system via the vigor with which the eyes moved toward that stimulus. SIGNIFICANCE STATEMENT We find that, as individuals deliberate between two rewarding options and arrive at a decision, the vigor with which they make saccades to each option reflects a real-time evaluation of that option. With deliberation, saccade vigor diverges between the two options, becoming greater for the option that the individual will eventually choose. The results suggest a shared element between the network that assigns value to a stimulus during the process of decision-making and the network that controls

  2. Stackelberg Game Based Power Allocation for Physical Layer Security of Device-to-device Communication Underlaying Cellular Networks

    NASA Astrophysics Data System (ADS)

    Qu, Junyue; Cai, Yueming; Wu, Dan; Chen, Hualiang

    2014-05-01

    The problem of power allocation for device-to-device (D2D) underlay communication to improve physical layer security is addressed. Specifically, to improve the secure communication of the cellular users, we introduce a Stackelberg game for allocating the power of the D2D link under a total power constraint and a rate constraint at the D2D pair. In the introduced Stackelberg game the D2D pair works as a seller and the cellular UEs work as buyers. Firstly, because the interference signals from D2D pair are unknown to both the legitimate receiver and the illegitimate eavesdropper, it is possible that a cellular UE decline to participate in the introduced Stackelberg game. So the condition under which a legitimate user will participate in the introduced Stackelberg game is discussed. Then, based on the Stackelberg game, we propose a semi-distributed power allocation algorithm, which is proved to conclude after finite-time iterations. In the end, some simulations are presented to verify the performance improvement in the physical layer security of cellular UEs using the proposed power allocation algorithm. We can determine that with the proposed algorithm, while the D2D pair's communication demand is met, the physical layer security of cellular UEs can be improved.

  3. Influence of branding on preference-based decision making.

    PubMed

    Philiastides, Marios G; Ratcliff, Roger

    2013-07-01

    Branding has become one of the most important determinants of consumer choices. Intriguingly, the psychological mechanisms of how branding influences decision making remain elusive. In the research reported here, we used a preference-based decision-making task and computational modeling to identify which internal components of processing are affected by branding. We found that a process of noisy temporal integration of subjective value information can model preference-based choices reliably and that branding biases are explained by changes in the rate of the integration process itself. This result suggests that branding information and subjective preference are integrated into a single source of evidence in the decision-making process, thereby altering choice behavior.

  4. Road-network-Based spatial allocation of on-road mobile source emissions in the Pearl River Delta region, China, and comparisons with population-based approach.

    PubMed

    Zheng, Junyu; Che, Wenwei; Wang, Xuemei; Louie, Peter; Zhong, Liuju

    2009-12-01

    Gridded air pollutant emission inventories are prerequisites for using air quality models to assess air pollution control strategies and predict air quality. A precise gridded emission inventory will help improve the accuracy of air quality simulation. Mobile source emissions are one of the major contributors to volatile organic compound (VOC) and nitrogen oxide (NOx) pollutants, the precursors of ozone formation. However, because of the complexity of road networks and variations in traffic flows at different road types and locations, spatial allocation of emissions from mobile sources into grid cells is challenging. This paper proposes a new methodological framework, named as "the road-network-based approach," for spatially allocating regional mobile source emission inventories. The new approach utilizes the Geographic Information System (GIS)-based road network information and road-types-based traffic flow data to provide spatial surrogates for allocating Pearl River Delta (PRD) regional mobile source emission inventories. The results show that the new approach provides reasonable spatial distributions of mobile source emissions, and the distributions are in good agreement with PRD regional on-road emission line sources. Comparisons between using the population-based and the new road-network-based approaches are made. The air quality modeling results indicate that the new approach can obviously improve model predictions with increasing accuracy in mobile source emission allocations. Means of choosing appropriate approaches for spatially allocating regional mobile source emissions are discussed.

  5. Dynamic bandwidth allocation algorithms for local storage based VoD delivery: Comparison between single and dual receiver configurations

    NASA Astrophysics Data System (ADS)

    Abeywickrama, Sandu; Wong, Elaine

    2015-02-01

    The benefits of using distributed caching servers to optimize the traditional video-on-demand delivery have been extensively discussed in literature. In our previous work, we introduced a dual-receiver based dynamic bandwidth allocation algorithm to improve video-on-demand services using a local storage placed within the access network. The main drawback of this algorithm lies in the additional power consumption at the optical network unit that arises from using two receivers. In this paper, we present two novel single-receiver based dynamic bandwidth allocation algorithms to further optimize local storage aided video-on-demand over passive optical networks. The quality-of-service and power performances of the algorithms are critically analyzed using packet level simulations and formulation of power consumption models. We show that the energy-efficiency of a local storage based video-on-demand scheme can be increased without compromising the quality-of-service by the use of single receiver algorithms. Further, we compare the two newly introduced algorithms against dual-receiver based and without local storage schemes to find the most appropriate bandwidth allocation algorithm for local storage based video-on-demand delivery over passive optical networks.

  6. Decision making in flood risk based storm sewer network design.

    PubMed

    Sun, S A; Djordjević, S; Khu, S T

    2011-01-01

    It is widely recognised that flood risk needs to be taken into account when designing a storm sewer network. Flood risk is generally a combination of flood consequences and flood probabilities. This paper aims to explore the decision making in flood risk based storm sewer network design. A multiobjective optimization is proposed to find the Pareto front of optimal designs in terms of low construction cost and low flood risk. The decision making process then follows this multi-objective optimization to select a best design from the Pareto front. The traditional way of designing a storm sewer system based on a predefined design storm is used as one of the decision making criteria. Additionally, three commonly used risk based criteria, i.e., the expected flood risk based criterion, the Hurwicz criterion and the stochastic dominance based criterion, are investigated and applied in this paper. Different decisions are made according to different criteria as a result of different concerns represented by the criteria. The proposed procedure is applied to a simple storm sewer network design to demonstrate its effectiveness and the different criteria are compared.

  7. Demystifying the Data-Based Decision-Making Process

    ERIC Educational Resources Information Center

    Cramer, Elizabeth D.; Little, Mary E.; McHatton, Patricia Alvarez

    2014-01-01

    Across the United States, teachers and teacher educators are facing increased accountability for improved student achievement. Using assessment results to inform instruction provides a catalyst to improve student outcomes and is a key skill for preservice teacher candidates. The process of data-based decision making is integral to performance…

  8. Data-Based Decision Making in Teams: Enablers and Barriers

    ERIC Educational Resources Information Center

    Bolhuis, Erik; Schildkamp, Kim; Voogt, Joke

    2016-01-01

    Data use is becoming more important in higher education. In this case study, a team of teachers from a teacher education college was supported in data-based decision making by means of the data team procedure. This data team studied the reasons why students drop out. A team's success depends in part on whether the team is able to develop and apply…

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

    NASA Technical Reports Server (NTRS)

    Tyagi, Rajesh; Tseng, Fan T.

    1988-01-01

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

  10. The online community based decision making support system for mitigating biased decision making

    NASA Astrophysics Data System (ADS)

    Kang, Sunghyun; Seo, Jiwan; Choi, Seungjin; Kim, Junho; Han, Sangyong

    2016-10-01

    As the Internet technology and social media advance, various information and opinions are shared and distributed through the online communities. However, the existence of implicit and explicit bias of opinions may have a potential influence on the outcomes. Compared to the importance of mitigating biased information, the study in this field is relatively young and does not address many important issues. In this paper we propose the noble approach to mitigate the biased opinions using conventional machine learning methods. The proposed method extracts the useful features such as inclination and sentiment of the community members. They are classified based on their previous behavior, and the propensity of the members is understood. This information on each community and its members is very useful and improve the ability to make an unbiased decision. The proposed method presented in this paper is shown to have the ability to assist optimal, fair and good decision making while also reducing the influence of implicit bias.

  11. Predicting Preference for Items during Periods of Extended Access Based on Early Response Allocation

    ERIC Educational Resources Information Center

    Rapp, John T.; Rojas, Nairim C.; Colby-Dirksen, Amanda M.; Swanson, Greg J.; Marvin, Kendra L.

    2010-01-01

    Top-ranked items were identified during 30-min free-operant preference assessments for 9 individuals. Data from each session were analyzed to identify the item (a) that was engaged with first in each session and (b) to which the most responding was allocated after 5 min, 10 min, 15 min, 20 min, and 25 min had elapsed in each session. The results…

  12. A Web-Based Tool to Support Data-Based Early Intervention Decision Making

    ERIC Educational Resources Information Center

    Buzhardt, Jay; Greenwood, Charles; Walker, Dale; Carta, Judith; Terry, Barbara; Garrett, Matthew

    2010-01-01

    Progress monitoring and data-based intervention decision making have become key components of providing evidence-based early childhood special education services. Unfortunately, there is a lack of tools to support early childhood service providers' decision-making efforts. The authors describe a Web-based system that guides service providers…

  13. H.264 SVC Complexity Reduction Based on Likelihood Mode Decision

    PubMed Central

    Balaji, L.; Thyagharajan, K. K.

    2015-01-01

    H.264 Advanced Video Coding (AVC) was prolonged to Scalable Video Coding (SVC). SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD) is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method. PMID:26221623

  14. H.264 SVC Complexity Reduction Based on Likelihood Mode Decision.

    PubMed

    Balaji, L; Thyagharajan, K K

    2015-01-01

    H.264 Advanced Video Coding (AVC) was prolonged to Scalable Video Coding (SVC). SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD) is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method.

  15. Evidence-based decision-making: an argumentative approach.

    PubMed

    Dickinson, H D

    1998-01-01

    A practical theory of argumentation is outlined and applied to a hypothetical clinical scenario to elucidate the use of research evidence in individual treatment decisions. The primary role of research evidence is to establish warrants as opposed to warrant using. Warrants are defined as the rules, principles or interpretive rationales used to justify an inference from observed data to conclusion, or clinical claim. Clarity on the appropriate use of research evidence in clinical decision-making can help resolve current debates over the nature and consequences of evidence-based medicine. The theory of argumentation has potential to inform both the design of decision support tools and to provide criteria for assessing decisional performance.

  16. A safety-based decision making architecture for autonomous systems

    NASA Technical Reports Server (NTRS)

    Musto, Joseph C.; Lauderbaugh, L. K.

    1991-01-01

    Engineering systems designed specifically for space applications often exhibit a high level of autonomy in the control and decision-making architecture. As the level of autonomy increases, more emphasis must be placed on assimilating the safety functions normally executed at the hardware level or by human supervisors into the control architecture of the system. The development of a decision-making structure which utilizes information on system safety is detailed. A quantitative measure of system safety, called the safety self-information, is defined. This measure is analogous to the reliability self-information defined by McInroy and Saridis, but includes weighting of task constraints to provide a measure of both reliability and cost. An example is presented in which the safety self-information is used as a decision criterion in a mobile robot controller. The safety self-information is shown to be consistent with the entropy-based Theory of Intelligent Machines defined by Saridis.

  17. Evidence to inform resource allocation for tuberculosis control in Myanmar: a systematic review based on the SYSRA framework.

    PubMed

    Khan, Mishal S; Schwanke Khilji, Sara U; Saw, Saw; Coker, Richard J

    2017-02-01

    Myanmar represents an extreme example of the difficulties in optimally allocating resources for maximum public health benefit, on the basis of limited information. At the recent Myanmar Health Forum 'Investing in Health' much of the discussion revolved around what to invest in, how health systems could be strengthened, and what research and capacity building areas the international donor community should prioritise for support. Funding for infectious disease control, particularly HIV and tuberculosis, is being channelled to the country at an unprecedented rate, but very little research has been conducted in recent years, and existing information has not yet been synthesised. This paper presents findings of the first systematic literature review on tuberculosis control and the health system in Myanmar, with the aim of informing the development of optimal research priorities and strategies. Medline and grey literature were searched for relevant papers. Inclusion criteria and analyses were structured to capture data on the Myanmar health system, healthcare delivery, financing, tuberculosis control indicators and information systems. A total of 77 papers were included in the analysis. The results indicate that there has been a large increase in the number of peer-reviewed articles published on tuberculosis in Myanmar over the past decade, although the absolute number of studies remains small. We identified several areas in which evidence to inform policy and resource allocation decisions is lacking, including research focused on rural and/or vulnerable populations, analyses of risk factors for TB and drug resistance that can inform prevention strategies and economic analyses for optimising resource allocation. The gaps in research to inform policy identified through this study may be relevant to other low resource settings with extremely limited research capacity.

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

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

  19. Make or buy analysis model based on tolerance allocation to minimize manufacturing cost and fuzzy quality loss

    NASA Astrophysics Data System (ADS)

    Rosyidi, C. N.; Puspitoingrum, W.; Jauhari, W. A.; Suhardi, B.; Hamada, K.

    2016-02-01

    The specification of tolerances has a significant impact on the quality of product and final production cost. The company should carefully pay attention to the component or product tolerance so they can produce a good quality product at the lowest cost. Tolerance allocation has been widely used to solve problem in selecting particular process or supplier. But before merely getting into the selection process, the company must first make a plan to analyse whether the component must be made in house (make), to be purchased from a supplier (buy), or used the combination of both. This paper discusses an optimization model of process and supplier selection in order to minimize the manufacturing costs and the fuzzy quality loss. This model can also be used to determine the allocation of components to the selected processes or suppliers. Tolerance, process capability and production capacity are three important constraints that affect the decision. Fuzzy quality loss function is used in this paper to describe the semantic of the quality, in which the product quality level is divided into several grades. The implementation of the proposed model has been demonstrated by solving a numerical example problem that used a simple assembly product which consists of three components. The metaheuristic approach were implemented to OptQuest software from Oracle Crystal Ball in order to obtain the optimal solution of the numerical example.

  20. Modelling decision-making by pilots

    NASA Technical Reports Server (NTRS)

    Patrick, Nicholas J. M.

    1993-01-01

    Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).

  1. A QoS aware resource allocation strategy for 3D A/V streaming in OFDMA based wireless systems.

    PubMed

    Chung, Young-Uk; Choi, Yong-Hoon; Park, Suwon; Lee, Hyukjoon

    2014-01-01

    Three-dimensional (3D) video is expected to be a "killer app" for OFDMA-based broadband wireless systems. The main limitation of 3D video streaming over a wireless system is the shortage of radio resources due to the large size of the 3D traffic. This paper presents a novel resource allocation strategy to address this problem. In the paper, the video-plus-depth 3D traffic type is considered. The proposed resource allocation strategy focuses on the relationship between 2D video and the depth map, handling them with different priorities. It is formulated as an optimization problem and is solved using a suboptimal heuristic algorithm. Numerical results show that the proposed scheme provides a better quality of service compared to conventional schemes.

  2. Capacity allocation mechanism based on differentiated QoS in 60 GHz radio-over-fiber local access network

    NASA Astrophysics Data System (ADS)

    Kou, Yanbin; Liu, Siming; Zhang, Weiheng; Shen, Guansheng; Tian, Huiping

    2017-03-01

    We present a dynamic capacity allocation mechanism based on the Quality of Service (QoS) for different mobile users (MU) in 60 GHz radio-over-fiber (RoF) local access networks. The proposed mechanism is capable for collecting the request information of MUs to build a full list of MU capacity demands and service types at the Central Office (CO). A hybrid algorithm is introduced to implement the capacity allocation which can satisfy the requirements of different MUs at different network traffic loads. Compared with the weight dynamic frames assignment (WDFA) scheme, the Hybrid scheme can keep high priority MUs in low delay and maintain the packet loss rate less than 1% simultaneously. At the same time, low priority MUs have a relatively better performance.

  3. A vertical handoff decision algorithm based on ARMA prediction model

    NASA Astrophysics Data System (ADS)

    Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan

    2011-12-01

    With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.

  4. A vertical handoff decision algorithm based on ARMA prediction model

    NASA Astrophysics Data System (ADS)

    Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan

    2012-01-01

    With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.

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

    PubMed

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

    2014-06-23

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

  6. Optimal power allocation based on sum-throughput maximization for energy harvesting cognitive radio networks

    NASA Astrophysics Data System (ADS)

    Xie, Zhenwei; Zhu, Qi

    2017-01-01

    In this study, an optimal power allocation algorithm by maximizing the sum-throughput in energy harvesting cognitive radio networks is proposed. Under the causality constraints of the harvested energy by solar radiation, electromagnetic waves and so on in the two secondary users (SUs), and the interference constraint in the primary user (PU), the sum-throughput maximization problem is formulated. The algorithm decomposes the interference threshold constraint to the power upper bounds of the two SUs. Then, the power allocation problems of the two SUs can be solved by a directional water-filling algorithm (DWA) with the power upper bounds, respectively. The paper gives the algorithm steps and simulation results, and the simulation results verify that the proposed algorithm has obvious advantages over the other two algorithms.

  7. A New Subcarrier Allocation Strategy for MIMO-OFDMA Multicellular Networks Based on Cooperative Interference Mitigation

    PubMed Central

    Gkonis, Panagiotis K.; Seimeni, Maria A.; Asimakis, Nikolaos P.; Kaklamani, Dimitra I.; Venieris, Iakovos S.

    2014-01-01

    The goal of the study presented in this paper is to investigate the performance of a new subcarrier allocation strategy for Orthogonal Frequency Division Multiple Access (OFDMA) multicellular networks which employ Multiple Input Multiple Output (MIMO) architecture. For this reason, a hybrid system-link level simulator has been developed executing independent Monte Carlo (MC) simulations in parallel. Up to two tiers of cells around the central cell are taken into consideration and increased loading per cell. The derived results indicate that this strategy can provide up to 12% capacity gain for 16-QAM modulation and two tiers of cells around the central cell in a symmetric 2 × 2 MIMO configuration. This gain is derived when comparing the proposed strategy to the traditional approach of allocating subcarriers that maximize only the desired user's signal. PMID:24683351

  8. Optimal allocation of bulk water supplies to competing use sectors based on economic criterion - An application to the Chao Phraya River Basin, Thailand

    NASA Astrophysics Data System (ADS)

    Divakar, L.; Babel, M. S.; Perret, S. R.; Gupta, A. Das

    2011-04-01

    SummaryThe study develops a model for optimal bulk allocations of limited available water based on an economic criterion to competing use sectors such as agriculture, domestic, industry and hydropower. The model comprises a reservoir operation module (ROM) and a water allocation module (WAM). ROM determines the amount of water available for allocation, which is used as an input to WAM with an objective function to maximize the net economic benefits of bulk allocations to different use sectors. The total net benefit functions for agriculture and hydropower sectors and the marginal net benefit from domestic and industrial sectors are established and are categorically taken as fixed in the present study. The developed model is applied to the Chao Phraya basin in Thailand. The case study results indicate that the WAM can improve net economic returns compared to the current water allocation practices.

  9. A dynamic programming approach to water allocation for seasonally dry area, based on stochastic soil moisture

    NASA Astrophysics Data System (ADS)

    Lu, Z.; Porporato, A. M.

    2012-12-01

    seasonally dry areas, which are widely distributed in the world, are usually facing an intensive disparity between the lack of natural resource and the great demand of social development. In dry seasons of such areas, the distribution/allocation of water resource is an extremely critical and sensitive issue, and conflicts often occur due to lack of appropriate water allocation scheme. Among the many uses of water, the need of agricultural irrigation water is highly elastic, but this factor has not yet been made full use to free up water from agriculture use. The primary goal of this work is to design an optimal distribution scheme of water resource for dry seasons to maximize benefits from precious water resources, considering the high elasticity of agriculture water demand due to the dynamic of soil moisture affected by the uncertainty of precipitation and other factors like canopy interception. A dynamic programming model will be used to figure out an appropriate allocation of water resources among agricultural irrigation and other purposes like drinking water, industry, and hydropower, etc. In this dynamic programming model, we analytically quantify the dynamic of soil moisture in the agricultural fields by describing the interception with marked Poisson process and describing the rainfall depth with exponential distribution. Then, we figure out a water-saving irrigation scheme, which regulates the timetable and volumes of water in irrigation, in order to minimize irrigation water requirement under the premise of necessary crop yield (as a constraint condition). And then, in turn, we provide a scheme of water resource distribution/allocation among agriculture and other purposes, taking aim at maximizing benefits from precious water resources, or in other words, make best use of limited water resource.

  10. Resource allocation of in vitro fertilization: a nationwide register-based cohort study

    PubMed Central

    Klemetti, Reija; Gissler, Mika; Sevón, Tiina; Hemminki, Elina

    2007-01-01

    Background Infertility is common and in vitro fertilization (IVF) is a widely used treatment. In IVF the need increases and the effectiveness and appropriateness decrease by age. The purpose of this study was to describe allocation of resources for IVF by women's age, socioeconomic position, area of residence and treatment sector (public vs. private) and to discuss how fairly the IVF resources are allocated in Finland. Methods Women who received IVF between 1996 and 1998 (N = 9175) were identified from the reimbursement records of the Social Insurance Institution (SII). Information on IVF women's background characteristics came from the Central Population Register and the SII, on treatment costs from IVF clinics and the SII, and on births from the Medical Birth Register. The main outcome measures were success of IVF by number of cycles and treated women, expenditures per IVF cycles, per women, per live-birth, and per treatment sector, and private and public expenditures. Expenditures were estimated from health care visits and costs. Results During a mean period of 1.5 years, older women (women aged 40 or older) received 1.4 times more IVF treatment cycles than younger women (women aged below 30). The success rate decreased by age: from 22 live births per 100 cycles among younger women to 6 per 100 among older women. The mean cost of a live birth increased by age: compared to younger women, costs per born live birth of older women were 3-fold. Calculated by population, public expenditure was allocated most to young women and women from the highest socioeconomic position. Regional differences were not remarkable. Conclusion Children of older infertile women involve more expense due to the lower success rates of IVF. Socioeconomic differences suggest unfair resource allocation in Finland. PMID:18154645

  11. Resource allocation using risk analysis

    SciTech Connect

    Bott, T. F.; Eisenhawer, S. W.

    2003-01-01

    Allocating limited resources among competing priorities is an important problem in management. In this paper we describe an approach to resource allocation using risk as a metric. We call this approach the Logic-Evolved Decision (LED) approach because we use logic-models to generate an exhaustive set of competing options and to describe the often highly complex model used for evaluating the risk reduction achieved by different resource allocations among these options. The risk evaluation then proceeds using probabilistic or linguistic input data.

  12. Risk-based decision making for terrorism applications.

    PubMed

    Dillon, Robin L; Liebe, Robert M; Bestafka, Thomas

    2009-03-01

    This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.

  13. Optimization model for the allocation of water resources based on the maximization of employment in the agriculture and industry sectors

    NASA Astrophysics Data System (ADS)

    Habibi Davijani, M.; Banihabib, M. E.; Nadjafzadeh Anvar, A.; Hashemi, S. R.

    2016-02-01

    In many discussions, work force is mentioned as the most important factor of production. Principally, work force is a factor which can compensate for the physical and material limitations and shortcomings of other factors to a large extent which can help increase the production level. On the other hand, employment is considered as an effective factor in social issues. The goal of the present research is the allocation of water resources so as to maximize the number of jobs created in the industry and agriculture sectors. An objective that has attracted the attention of policy makers involved in water supply and distribution is the maximization of the interests of beneficiaries and consumers in case of certain policies adopted. The present model applies the particle swarm optimization (PSO) algorithm in order to determine the optimum amount of water allocated to each water-demanding sector, area under cultivation, agricultural production, employment in the agriculture sector, industrial production and employment in the industry sector. Based on the results obtained from this research, by optimally allocating water resources in the central desert region of Iran, 1096 jobs can be created in the industry and agriculture sectors, which constitutes an improvement of about 13% relative to the previous situation (non-optimal water utilization). It is also worth mentioning that by optimizing the employment factor as a social parameter, the other areas such as the economic sector are influenced as well. For example, in this investigation, the resulting economic benefits (incomes) have improved from 73 billion Rials at baseline employment figures to 112 billion Rials in the case of optimized employment condition. Therefore, it is necessary to change the inter-sector and intra-sector water allocation models in this region, because this change not only leads to more jobs in this area, but also causes an improvement in the region's economic conditions.

  14. The ethical dilemma of population-based medical decision making.

    PubMed

    Kirsner, R S; Federman, D G

    1998-11-01

    Over the past several years, there has been a growing interest in population-based medicine. Some elements in healthcare have used population-based medicine as a technique to decrease healthcare expenditures. However, in their daily practice of medicine, physicians must grapple with the question of whether they incorporate population-based medicine when making decisions for an individual patient. They therefore may encounter an ethical dilemma. Physicians must remember that the physician-patient relationship is of paramount importance and that even well-conducted research may not be applicable to an individual patient.

  15. Clinical data warehousing for evidence based decision making.

    PubMed

    Narra, Lekha; Sahama, Tony; Stapleton, Peta

    2015-01-01

    Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

  16. An Innovative Time-Cost-Quality Tradeoff Modeling of Building Construction Project Based on Resource Allocation

    PubMed Central

    2014-01-01

    The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated. PMID:24672351

  17. An innovative time-cost-quality tradeoff modeling of building construction project based on resource allocation.

    PubMed

    Hu, Wenfa; He, Xinhua

    2014-01-01

    The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated.

  18. Systematic Task Allocation Evaluation in Distributed Software Development

    NASA Astrophysics Data System (ADS)

    Münch, Jürgen; Lamersdorf, Ansgar

    Systematic task allocation to different development sites in global software development projects can open business and engineering perspectives and help to reduce risks and problems inherent in distributed development. Relying only on a single evaluation criterion such as development cost when distributing tasks to development sites has shown to be very risky and often does not lead to successful solutions in the long run. Task allocation in global software projects is challenging due to a multitude of impact factors and constraints. Systematic allocation decisions require the ability to evaluate and compare task allocation alternatives and to effectively establish customized task allocation practices in an organization. In this article, we present a customizable process for task allocation evaluation that is based on results from a systematic interview study with practitioners. In this process, the relevant criteria for evaluating task allocation alternatives are derived by applying principles from goal-oriented measurement. In addition, the customization of the process is demonstrated, related work and limitations are sketched, and an outlook on future work is given.

  19. An algorithm for calculating exam quality as a basis for performance-based allocation of funds at medical schools

    PubMed Central

    Kirschstein, Timo; Wolters, Alexander; Lenz, Jan-Hendrik; Fröhlich, Susanne; Hakenberg, Oliver; Kundt, Günther; Darmüntzel, Martin; Hecker, Michael; Altiner, Attila; Müller-Hilke, Brigitte

    2016-01-01

    Objective: The amendment of the Medical Licensing Act (ÄAppO) in Germany in 2002 led to the introduction of graded assessments in the clinical part of medical studies. This, in turn, lent new weight to the importance of written tests, even though the minimum requirements for exam quality are sometimes difficult to reach. Introducing exam quality as a criterion for the award of performance-based allocation of funds is expected to steer the attention of faculty members towards more quality and perpetuate higher standards. However, at present there is a lack of suitable algorithms for calculating exam quality. Methods: In the spring of 2014, the students‘ dean commissioned the „core group“ for curricular improvement at the University Medical Center in Rostock to revise the criteria for the allocation of performance-based funds for teaching. In a first approach, we developed an algorithm that was based on the results of the most common type of exam in medical education, multiple choice tests. It included item difficulty and discrimination, reliability as well as the distribution of grades achieved. Results: This algorithm quantitatively describes exam quality of multiple choice exams. However, it can also be applied to exams involving short assay questions and the OSCE. It thus allows for the quantitation of exam quality in the various subjects and – in analogy to impact factors and third party grants – a ranking among faculty. Conclusion: Our algorithm can be applied to all test formats in which item difficulty, the discriminatory power of the individual items, reliability of the exam and the distribution of grades are measured. Even though the content validity of an exam is not considered here, we believe that our algorithm is suitable as a general basis for performance-based allocation of funds. PMID:27275509

  20. Joint Resource Allocation of Spectrum Sensing and Energy Harvesting in an Energy-Harvesting-Based Cognitive Sensor Network.

    PubMed

    Liu, Xin; Lu, Weidang; Ye, Liang; Li, Feng; Zou, Deyue

    2017-03-16

    The cognitive sensor (CS) can transmit data to the control center in the same spectrum that is licensed to the primary user (PU) when the absence of the PU is detected by spectrum sensing. However, the battery energy of the CS is limited due to its small size, deployment in atrocious environments and long-term working. In this paper, an energy-harvesting-based CS is described, which senses the PU together with collecting the radio frequency energy to supply data transmission. In order to improve the transmission performance of the CS, we have proposed the joint resource allocation of spectrum sensing and energy harvesting in the cases of a single energy-harvesting-based CS and an energy-harvesting-based cognitive sensor network (CSN), respectively. Based on the proposed frame structure, we have formulated the resource allocation as a class of joint optimization problems, which seek to maximize the transmission rate of the CS by jointly optimizing sensing time, harvesting time and the numbers of sensing nodes and harvesting nodes. Using the half searching method and the alternating direction optimization, we have achieved the sub-optimal solution by converting the joint optimization problem into several convex sub-optimization problems. The simulation results have indicated the predominance of the proposed energy-harvesting-based CS and CSN models.

  1. Joint Resource Allocation of Spectrum Sensing and Energy Harvesting in an Energy-Harvesting-Based Cognitive Sensor Network

    PubMed Central

    Liu, Xin; Lu, Weidang; Ye, Liang; Li, Feng; Zou, Deyue

    2017-01-01

    The cognitive sensor (CS) can transmit data to the control center in the same spectrum that is licensed to the primary user (PU) when the absence of the PU is detected by spectrum sensing. However, the battery energy of the CS is limited due to its small size, deployment in atrocious environments and long-term working. In this paper, an energy-harvesting-based CS is described, which senses the PU together with collecting the radio frequency energy to supply data transmission. In order to improve the transmission performance of the CS, we have proposed the joint resource allocation of spectrum sensing and energy harvesting in the cases of a single energy-harvesting-based CS and an energy-harvesting-based cognitive sensor network (CSN), respectively. Based on the proposed frame structure, we have formulated the resource allocation as a class of joint optimization problems, which seek to maximize the transmission rate of the CS by jointly optimizing sensing time, harvesting time and the numbers of sensing nodes and harvesting nodes. Using the half searching method and the alternating direction optimization, we have achieved the sub-optimal solution by converting the joint optimization problem into several convex sub-optimization problems. The simulation results have indicated the predominance of the proposed energy-harvesting-based CS and CSN models. PMID:28300763

  2. Decision-directed entropy-based adaptive filtering

    NASA Astrophysics Data System (ADS)

    Myler, Harley R.; Weeks, Arthur R.; Van Dyke-Lewis, Michelle

    1991-12-01

    A recurring problem in adaptive filtering is selection of control measures for parameter modification. A number of methods reported thus far have used localized order statistics to adaptively adjust filter parameters. The most effective techniques are based on edge detection as a decision mechanism to allow the preservation of edge information while noise is filtered. In general, decision-directed adaptive filters operate on a localized area within an image by using statistics of the area as a discrimination parameter. Typically, adaptive filters are based on pixel to pixel variations within a localized area that are due to either edges or additive noise. In homogeneous areas within the image where variances are due to additive noise, the filter should operate to reduce the noise. Using an edge detection technique, a decision directed adaptive filter can vary the filtering proportional to the amount of edge information detected. We show an approach using an entropy measure on edges to differentiate between variations in the image due to edge information as compared against noise. The method uses entropy calculated against the spatial contour variations of edges in the window.

  3. Basing perceptual decisions on the most informative sensory neurons.

    PubMed

    Scolari, Miranda; Serences, John T

    2010-10-01

    Single unit recording studies show that perceptual decisions are often based on the output of sensory neurons that are maximally responsive (or "tuned") to relevant stimulus features. However, when performing a difficult discrimination between two highly similar stimuli, perceptual decisions should instead be based on the activity of neurons tuned away from the relevant feature (off-channel neurons) as these neurons undergo a larger firing rate change and are thus more informative. To test this hypothesis, we measured feature-selective responses in human primary visual cortex (V1) using functional magnetic resonance imaging and show that the degree of off-channel activation predicts performance on a difficult visual discrimination task. Moreover, this predictive relationship between off-channel activation and perceptual acuity is not simply the result of extensive practice with a specific stimulus feature (as in studies of perceptual learning). Instead, relying on the output of the most informative sensory neurons may represent a general, and optimal, strategy for efficiently computing perceptual decisions.

  4. Iterative resource allocation based on propagation feature of node for identifying the influential nodes

    NASA Astrophysics Data System (ADS)

    Zhong, Lin-Feng; Liu, Jian-Guo; Shang, Ming-Sheng

    2015-10-01

    The identification of the influential nodes in networks is one of the most promising domains. In this paper, we present an improved iterative resource allocation (IIRA) method by considering the centrality information of neighbors and the influence of spreading rate for a target node. Comparing with the results of the Susceptible Infected Recovered (SIR) model for four real networks, the IIRA method could identify influential nodes more accurately than the tradition IRA method. Specially, in the Erdös network, Kendall's tau could be enhanced 23% when the spreading rate is 0.12. In the Protein network, Kendall's tau could be enhanced 24% when the spreading rate is 0.08.

  5. Probabilistic confidence for decisions based on uncertain reliability estimates

    NASA Astrophysics Data System (ADS)

    Reid, Stuart G.

    2013-05-01

    Reliability assessments are commonly carried out to provide a rational basis for risk-informed decisions concerning the design or maintenance of engineering systems and structures. However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities. For uncertain probabilities of failure, a measure of 'probabilistic confidence' has been proposed to reflect the concern that uncertainty about the true probability of failure could result in a system or structure that is unsafe and could subsequently fail. The paper describes how the concept of probabilistic confidence can be applied to evaluate and appropriately limit the probabilities of failure attributable to particular uncertainties such as design errors that may critically affect the dependability of risk-acceptance decisions. This approach is illustrated with regard to the dependability of structural design processes based on prototype testing with uncertainties attributable to sampling variability.

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

    PubMed

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

    2012-01-01

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

  7. Comparison of new conditional value-at-risk-based management models for optimal allocation of uncertain water supplies

    NASA Astrophysics Data System (ADS)

    Yamout, Ghina M.; Hatfield, Kirk; Romeijn, H. Edwin

    2007-07-01

    The paper studies the effect of incorporating the conditional value-at-risk (CVaRα) in analyzing a water allocation problem versus using the frequently used expected value, two-stage modeling, scenario analysis, and linear optimization tools. Five models are developed to examine water resource allocation when available supplies are uncertain: (1) a deterministic expected value model, (2) a scenario analysis model, (3) a two-stage stochastic model with recourse, (4) a CVaRα objective function model, and (5) a CVaRα constraint model. The models are applied over a region of east central Florida. Results show the deterministic expected value model underestimates system costs and water shortage. Furthermore, the expected value model produces identical cost estimates for different standard deviations distributions of water supplies with identical mean. From the scenario analysis model it is again demonstrated that the expected value of results taken from many scenarios underestimates costs and water shortages. Using a two-stage stochastic mixed integer formulation with recourse permits an improved representation of uncertainties and real-life decision making which in turn predicts higher costs. The inclusion of CVaRα objective function in the latter provides for the optimization and control of high-risk events. Minimizing CVaRα does not, however, permit control of lower-risk events. Constraining CVaRα while minimizing cost, on the other hand, allows for the control of high-risk events while minimizing the costs of all events. Results show CVaRα exhibits continuous and consistent behavior with respect to the confidence level α, when compared to value-at-risk (VaRα).

  8. Decision support system based on DPSIR framework for a low flow Mediterranean river basin

    NASA Astrophysics Data System (ADS)

    Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

    2013-04-01

    The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river

  9. Analysis of QoS-Based Band Power Allocation for Broadband Multi-Cell Forward Link Environments

    NASA Astrophysics Data System (ADS)

    Son, Hyukmin; Lee, Sanghoon

    ICI (Inter-Cell Interference) mitigation schemes at the cell border are frequently dealt with as a special issue in 3GPP LTE (Long Term Evolution). However, few papers have analyzed the outage performance for the ICI mitigation schemes. In this paper, we propose a generalized cell planning scheme termed QBPA (Quality of Service based Band Power Allocation). Utilizing the QBPA scheme, we measure how much increase in channel capacity can be obtained through the flexible control of bandwidth and power in multi-cell forward-link environments. In addition, the feasible performance of the conventional schemes can be evaluated as long as those schemes are specific forms of the QBPA.

  10. An Analysis of Naval Personnel Resource Allocations to Logistics. Volume I. Navy Sea-Based Personnel Resource Allocations to Logistics Functions.

    DTIC Science & Technology

    1982-08-01

    Personnel Resource Allocations to May 1982 Logistics Functions 6. PERFORMING ORG . REPORT NUMBER 7AUTHOR(s) ____________________ 8. CONTRACT OR GRANT NUMBER...6 I 114,8 1 54,7 1 I (.Cc J0 1 45.4 1 514,3 1 M059 I 956,0 1 57.4 z I IArA 1 1 218.0 1 963.9 1 620.7 1 2022.0 1 57.6 1 I ISA 11 1 36.9 1 299,6

  11. Memory-Based Decision-Making with Heuristics: Evidence for a Controlled Activation of Memory Representations

    ERIC Educational Resources Information Center

    Khader, Patrick H.; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rosler, Frank

    2011-01-01

    Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by…

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

    PubMed Central

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

    2002-01-01

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

  13. Decomposition-Based Decision Making for Aerospace Vehicle Design

    NASA Technical Reports Server (NTRS)

    Borer, Nicholas K.; Mavris, DImitri N.

    2005-01-01

    reader to observe how this technique can be applied to aerospace systems design and compare the results of this so-called Decomposition-Based Decision Making to more traditional design approaches.

  14. An Optimization-based Multi-level Asset Allocation Model for Collaborative Planning

    DTIC Science & Technology

    2011-06-01

    Collaborative Planning” Modeling and Simulation Experimentation, Metrics, and Analysis Collaboration, Shared Awareness, and Decision Making...modules that focused on the Future Operations (FOPS) cell’s planning activities and Current Operations’ (COPS) Risk Analysis . The FOPS Planning Module...planners would indeed be achievable to a specified degree of accuracy. Current Operations (COPS) Risk Analysis module was also implemented to assist COPS

  15. Risk-Based Prioritization of Research for Aviation Security Using Logic-Evolved Decision Analysis

    NASA Technical Reports Server (NTRS)

    Eisenhawer, S. W.; Bott, T. F.; Sorokach, M. R.; Jones, F. P.; Foggia, J. R.

    2004-01-01

    The National Aeronautics and Space Administration is developing advanced technologies to reduce terrorist risk for the air transportation system. Decision support tools are needed to help allocate assets to the most promising research. An approach to rank ordering technologies (using logic-evolved decision analysis), with risk reduction as the metric, is presented. The development of a spanning set of scenarios using a logic-gate tree is described. Baseline risk for these scenarios is evaluated with an approximate reasoning model. Illustrative risk and risk reduction results are presented.

  16. Statistical mechanics of competitive resource allocation using agent-based models

    NASA Astrophysics Data System (ADS)

    Chakraborti, Anirban; Challet, Damien; Chatterjee, Arnab; Marsili, Matteo; Zhang, Yi-Cheng; Chakrabarti, Bikas K.

    2015-01-01

    Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.

  17. PIYAS-Proceeding to Intelligent Service Oriented Memory Allocation for Flash Based Data Centric Sensor Devices in Wireless Sensor Networks

    PubMed Central

    Rizvi, Sanam Shahla; Chung, Tae-Sun

    2010-01-01

    Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks. PMID:22315541

  18. PIYAS-proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks.

    PubMed

    Rizvi, Sanam Shahla; Chung, Tae-Sun

    2010-01-01

    Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.

  19. Optimizing insecticide allocation strategies based on houses and livestock shelters for visceral leishmaniasis control in Bihar, India.

    PubMed

    Gorahava, Kaushik K; Rosenberger, Jay M; Mubayi, Anuj

    2015-07-01

    Visceral leishmaniasis (VL) is the most deadly form of the leishmaniasis family of diseases, which affects numerous developing countries. The Indian state of Bihar has the highest prevalence and mortality rate of VL in the world. Insecticide spraying is believed to be an effective vector control program for controlling the spread of VL in Bihar; however, it is expensive and less effective if not implemented systematically. This study develops and analyzes a novel optimization model for VL control in Bihar that identifies an optimal (best possible) allocation of chosen insecticide (dichlorodiphenyltrichloroethane [DDT] or deltamethrin) based on the sizes of human and cattle populations in the region. The model maximizes the insecticide-induced sandfly death rate in human and cattle dwellings while staying within the current state budget for VL vector control efforts. The model results suggest that deltamethrin might not be a good replacement for DDT because the insecticide-induced sandfly deaths are 3.72 times more in case of DDT even after 90 days post spray. Different insecticide allocation strategies between the two types of sites (houses and cattle sheds) are suggested based on the state VL-control budget and have a direct implication on VL elimination efforts in a resource-limited region.

  20. A group-based tasks allocation algorithm for the optimization of long leave opportunities in academic departments

    NASA Astrophysics Data System (ADS)

    Eyono Obono, S. D.; Basak, Sujit Kumar

    2011-12-01

    The general formulation of the assignment problem consists in the optimal allocation of a given set of tasks to a workforce. This problem is covered by existing literature for different domains such as distributed databases, distributed systems, transportation, packets radio networks, IT outsourcing, and teaching allocation. This paper presents a new version of the assignment problem for the allocation of academic tasks to staff members in departments with long leave opportunities. It presents the description of a workload allocation scheme and its algorithm, for the allocation of an equitable number of tasks in academic departments where long leaves are necessary.

  1. Informing the gestalt: an ethical framework for allocating scarce federal public health and medical resources to states during disasters.

    PubMed

    Knebel, Ann R; Sharpe, Virginia A; Danis, Marion; Toomey, Lauren M; Knickerbocker, Deborah K

    2014-02-01

    During catastrophic disasters, government leaders must decide how to efficiently and effectively allocate scarce public health and medical resources. The literature about triage decision making at the individual patient level is substantial, and the National Response Framework provides guidance about the distribution of responsibilities between federal and state governments. However, little has been written about the decision-making process of federal leaders in disaster situations when resources are not sufficient to meet the needs of several states simultaneously. We offer an ethical framework and logic model for decision making in such circumstances. We adapted medical triage and the federalism principle to the decision-making process for allocating scarce federal public health and medical resources. We believe that the logic model provides a values-based framework that can inform the gestalt during the iterative decision process used by federal leaders as they allocate scarce resources to states during catastrophic disasters.

  2. Climate policy decisions require policy-based lifecycle analysis.

    PubMed

    Bento, Antonio M; Klotz, Richard

    2014-05-20

    Lifecycle analysis (LCA) metrics of greenhouse gas emissions are increasingly being used to select technologies supported by climate policy. However, LCAs typically evaluate the emissions associated with a technology or product, not the impacts of policies. Here, we show that policies supporting the same technology can lead to dramatically different emissions impacts per unit of technology added, due to multimarket responses to the policy. Using a policy-based consequential LCA, we find that the lifecycle emissions impacts of four US biofuel policies range from a reduction of 16.1 gCO2e to an increase of 24.0 gCO2e per MJ corn ethanol added by the policy. The differences between these results and representative technology-based LCA measures, which do not account for the policy instrument driving the expansion in the technology, illustrate the need for policy-based LCA measures when informing policy decision making.

  3. Artificial intelligence based decision support for trumpeter swan management

    USGS Publications Warehouse

    Sojda, Richard S.

    2002-01-01

    The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

  4. High performance in healthcare priority setting and resource allocation: A literature- and case study-based framework in the Canadian context.

    PubMed

    Smith, Neale; Mitton, Craig; Hall, William; Bryan, Stirling; Donaldson, Cam; Peacock, Stuart; Gibson, Jennifer L; Urquhart, Bonnie

    2016-08-01

    Priority setting and resource allocation, or PSRA, are key functions of executive teams in healthcare organizations. Yet decision-makers often base their choices on historical patterns of resource distribution or political pressures. Our aim was to provide leaders with guidance on how to improve PSRA practice, by creating organizational contexts which enable high performance. We carried out in-depth case studies of six Canadian healthcare organizations to obtain from healthcare leaders their understanding of the concept of high performance in PSRA and the factors which contribute to its achievement. Individual and group interviews were carried out (n = 62) with senior managers, middle managers and Board members. Site observations and document review were used to assist researchers in interpreting the interview data. Qualitative data were analyzed iteratively with the literature on empirical examples of PSRA practice, in order to develop a framework of high performance in PSRA. The framework consists of four domains - structures, processes, attitudes and behaviours, and outcomes - within which are 19 specific elements. The emergent themes derive from case studies in different kinds of health organizations (urban/rural, small/large) across Canada. The elements can serve as a checklist for 'high performance' in PSRA. This framework provides a means by which decision-makers in healthcare might assess their practice and identify key areas for improvement. The findings are likely generalizable, certainly within Canada but also across countries. This work constitutes, to our knowledge, the first attempt to present a full package of elements comprising high performance in health care PSRA.

  5. Web based collaborative decision making in flood risk management

    NASA Astrophysics Data System (ADS)

    Evers, Mariele; Almoradie, Adrian; Jonoski, Andreja

    2014-05-01

    Stakeholder participation in the development of flood risk management (FRM) plans is essential since stakeholders often have a better understanding or knowledge of the potentials and limitation of their local area. Moreover, a participatory approach also creates trust amongst stakeholders, leading to a successful implementation of measures. Stakeholder participation however has its challenges and potential pitfalls that could lead to its premature termination. Such challenges and pitfalls are the limitation of financial resources, stakeholders' spatial distribution and their interest to participate. Different type of participation in FRM may encounter diverse challenges. These types of participation in FRM can be classified into (1) Information and knowledge sharing (IKS), (2) Consultative participation (CP) or (3) Collaborative decision making (CDM)- the most challenging type of participation. An innovative approach to address these challenges and potential pitfalls is a web-based mobile or computer-aided environment for stakeholder participation. This enhances the remote interaction between participating entities such as stakeholders. This paper presents a developed framework and an implementation of CDM web based environment for the Alster catchment (Hamburg, Germany) and Cranbrook catchment (London, UK). The CDM framework consists of two main stages: (1) Collaborative modelling and (2) Participatory decision making. This paper also highlights the stakeholder analyses, modelling approach and application of General Public License (GPL) technologies in developing the web-based environments. Actual test and evaluation of the environments was through series of stakeholders workshops. The overall results based from stakeholders' evaluation shows that web-based environments can address the challenges and potential pitfalls in stakeholder participation and it enhances participation in flood risk management. The web-based environment was developed within the DIANE

  6. Constant time worker thread allocation via configuration caching

    DOEpatents

    Eichenberger, Alexandre E; O'Brien, John K. P.

    2014-11-04

    Mechanisms are provided for allocating threads for execution of a parallel region of code. A request for allocation of worker threads to execute the parallel region of code is received from a master thread. Cached thread allocation information identifying prior thread allocations that have been performed for the master thread are accessed. Worker threads are allocated to the master thread based on the cached thread allocation information. The parallel region of code is executed using the allocated worker threads.

  7. Ignorance- versus Evidence-Based Decision Making: A Decision Time Analysis of the Recognition Heuristic

    ERIC Educational Resources Information Center

    Hilbig, Benjamin E.; Pohl, Rudiger F.

    2009-01-01

    According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments--and its duration--is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of…

  8. Preventing conflicts among bid curves used with transactive controllers in a market-based resource allocation system

    DOEpatents

    Fuller, Jason C.; Chassin, David P.; Pratt, Robert G.; Hauer, Matthew; Tuffner, Francis K.

    2017-03-07

    Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. One of the disclosed embodiments is a method for operating a transactive thermostatic controller configured to submit bids to a market-based resource allocation system. According to the exemplary method, a first bid curve is determined, the first bid curve indicating a first set of bid prices for corresponding temperatures and being associated with a cooling mode of operation for a heating and cooling system. A second bid curve is also determined, the second bid curve indicating a second set of bid prices for corresponding temperatures and being associated with a heating mode of operation for a heating and cooling system. In this embodiment, the first bid curve, the second bid curve, or both the first bid curve and the second bid curve are modified to prevent overlap of any portion of the first bid curve and the second bid curve.

  9. Performance impact of mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems.

    PubMed

    Liu, Chun; Kroll, Andreas

    2016-01-01

    Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems.

  10. Grey situation group decision-making method based on prospect theory.

    PubMed

    Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

    2014-01-01

    This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example.

  11. A review of alternative approaches to healthcare resource allocation.

    PubMed

    Petrou, S; Wolstenholme, J

    2000-07-01

    The resources available for healthcare are limited compared with demand, if not need, and all healthcare systems, regardless of their financing and organisation, employ mechanisms to ration or prioritise finite healthcare resources. This paper reviews alternative approaches that can be used to allocate healthcare resources. It discusses the problems encountered when allocating healthcare resources according to free market principles. It then proceeds to discuss the advantages and disadvantages of alternative resource allocation approaches that can be applied to public health systems. These include: (i) approaches based on the concept of meeting the needs of the population to maximising its capacity to benefit from interventions; (ii) economic approaches that identify the most efficient allocation of resources with the view of maximising health benefits or other measures of social welfare; (iii) approaches that seek to ration healthcare by age; and (iv) approaches that resolve resource allocation disputes through debate and bargaining. At present, there appears to be no consensus about the relative importance of the potentially conflicting principles that can be used to guide resource allocation decisions. It is concluded that whatever shape tomorrow's health service takes, the requirement to make equitable and efficient use of finite healthcare resources will remain.

  12. Data-Based Decision-Making: Developing a Method for Capturing Teachers' Understanding of CBM Graphs

    ERIC Educational Resources Information Center

    Espin, Christine A.; Wayman, Miya Miura; Deno, Stanley L.; McMaster, Kristen L.; de Rooij, Mark

    2017-01-01

    In this special issue, we explore the decision-making aspect of "data-based decision-making". The articles in the issue address a wide range of research questions, designs, methods, and analyses, but all focus on data-based decision-making for students with learning difficulties. In this first article, we introduce the topic of…

  13. The past, present and future of HIV, AIDS and resource allocation

    PubMed Central

    2009-01-01

    Background How should HIV and AIDS resources be allocated to achieve the greatest possible impact? This paper begins with a theoretical discussion of this issue, describing the key elements of an "evidence-based allocation strategy". While it is noted that the quality of epidemiological and economic data remains inadequate to define such an optimal strategy, there do exist tools and research which can lead countries in a way that they can make allocation decisions. Furthermore, there are clear indications that most countries are not allocating their HIV and AIDS resources in a way which is likely to achieve the greatest possible impact. For example, it is noted that neighboring countries, even when they have a similar prevalence of HIV, nonetheless often allocate their resources in radically different ways. These differing allocation patterns appear to be attributable to a number of different issues, including a lack of data, contradictory results in existing data, a need for overemphasizing a multisectoral response, a lack of political will, a general inefficiency in the use of resources when they do get allocated, poor planning and a lack of control over the way resources get allocated. Methods There are a number of tools currently available which can improve the resource-allocation process. Tools such as the Resource Needs Model (RNM) can provide policymakers with a clearer idea of resource requirements, whereas other tools such as Goals and the Allocation by Cost-Effectiveness (ABCE) models can provide countries with a clearer vision of how they might reallocate funds. Results Examples from nine different countries provide information about how policymakers are trying to make their resource-allocation strategies more "evidence based". By identifying the challenges and successes of these nine countries in making more informed allocation decisions, it is hoped that future resource-allocation decisions for all countries can be improved. Conclusion We discuss the

  14. Application of portfolio theory to risk-based allocation of surveillance resources in animal populations.

    PubMed

    Prattley, D J; Morris, R S; Stevenson, M A; Thornton, R

    2007-09-14

    Distribution of finite levels of resources between multiple competing tasks can be a challenging problem. Resources need to be distributed across time periods and geographic locations to increase the probability of detection of a disease incursion or significant change in disease pattern. Efforts should focus primarily on areas and populations where risk factors for a given disease reach relatively high levels. In order to target resources into these areas, the overall risk level can be evaluated periodically across locations to create a dynamic national risk landscape. Methods are described to integrate the levels of various risk factors into an overall risk score for each area, to account for the certainty or variability around those measures and then to allocate surveillance resources across this risk landscape. In addition to targeting resources into high risk areas, surveillance continues in lower risk areas where there is a small yet positive chance of disease occurrence. In this paper we describe the application of portfolio theory concepts, routinely used in finance, to design surveillance portfolios for a series of examples. The appropriate level of resource investment is chosen for each disease or geographical area and time period given the degree of disease risk and uncertainty present.

  15. Monitoring of posture allocations and activities by a shoe-based wearable sensor.

    PubMed

    Sazonov, Edward S; Fulk, George; Hill, James; Schutz, Yves; Browning, Raymond

    2011-04-01

    Monitoring of posture allocations and activities enables accurate estimation of energy expenditure and may aid in obesity prevention and treatment. At present, accurate devices rely on multiple sensors distributed on the body and thus may be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable of very accurate recognition of common postures and activities. The patterns of heel acceleration and plantar pressure uniquely characterize postures and typical activities while requiring minimal preprocessing and no feature extraction. The shoe sensor was tested in nine adults performing sitting and standing postures and while walking, running, stair ascent/descent and cycling. Support vector machines (SVMs) were used for classification. A fourfold validation of a six-class subject-independent group model showed 95.2% average accuracy of posture/activity classification on full sensor set and over 98% on optimized sensor set. Using a combination of acceleration/pressure also enabled a pronounced reduction of the sampling frequency (25 to 1 Hz) without significant loss of accuracy (98% versus 93%). Subjects had shoe sizes (US) M9.5-11 and W7-9 and body mass index from 18.1 to 39.4 kg/m2 and thus suggesting that the device can be used by individuals with varying anthropometric characteristics.

  16. DESPOT, a process-based tree growth model that allocates carbon to maximize carbon gain.

    PubMed

    Buckley, Thomas N; Roberts, David W

    2006-02-01

    We present a new model of tree growth, DESPOT (Deducing Emergent Structure and Physiology Of Trees), in which carbon (C) allocation is adjusted in each time step to maximize whole-tree net C gain in the next time step. Carbon gain, respiration and the acquisition and transport of substitutable photosynthetic resources (nitrogen, water and light) are modeled on a process basis. The current form of DESPOT simulates a uniform, monospecific, self-thinning stand. This paper describes DESPOT and its general behavior in comparison to published data, and presents an evaluation of the sensitivity of its qualitative predictions by Monte Carlo parameter sensitivity analysis. DESPOT predicts determinate height growth and steady stand-level net primary productivity (NPP), but slow declines in aboveground NPP and leaf area index. Monte Carlo analysis, wherein the model was run repeatedly with randomly different parameter sets, revealed that many parameter sets do not lead to sustainable NPP. Of those that do lead to sustainable growth, the ratios at maturity of net to gross primary productivity and of leaf area to sapwood area are highly conserved.

  17. Energy-efficient orthogonal frequency division multiplexing-based passive optical network based on adaptive sleep-mode control and dynamic bandwidth allocation

    NASA Astrophysics Data System (ADS)

    Zhang, Chongfu; Xiao, Nengwu; Chen, Chen; Yuan, Weicheng; Qiu, Kun

    2016-02-01

    We propose an energy-efficient orthogonal frequency division multiplexing-based passive optical network (OFDM-PON) using adaptive sleep-mode control and dynamic bandwidth allocation. In this scheme, a bidirectional-centralized algorithm named the receiver and transmitter accurate sleep control and dynamic bandwidth allocation (RTASC-DBA), which has an overall bandwidth scheduling policy, is employed to enhance the energy efficiency of the OFDM-PON. The RTASC-DBA algorithm is used in an optical line terminal (OLT) to control the sleep mode of an optical network unit (ONU) sleep and guarantee the quality of service of different services of the OFDM-PON. The obtained results show that, by using the proposed scheme, the average power consumption of the ONU is reduced by ˜40% when the normalized ONU load is less than 80%, compared with the average power consumption without using the proposed scheme.

  18. Decision Manifold Approximation for Physics-Based Simulations

    NASA Technical Reports Server (NTRS)

    Wong, Jay Ming; Samareh, Jamshid A.

    2016-01-01

    With the recent surge of success in big-data driven deep learning problems, many of these frameworks focus on the notion of architecture design and utilizing massive databases. However, in some scenarios massive sets of data may be difficult, and in some cases infeasible, to acquire. In this paper we discuss a trajectory-based framework that quickly learns the underlying decision manifold of binary simulation classifications while judiciously selecting exploratory target states to minimize the number of required simulations. Furthermore, we draw particular attention to the simulation prediction application idealized to the case where failures in simulations can be predicted and avoided, providing machine intelligence to novice analysts. We demonstrate this framework in various forms of simulations and discuss its efficacy.

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

    PubMed Central

    2010-01-01

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

  20. System and method for integrating hazard-based decision making tools and processes

    DOEpatents

    Hodgin, C Reed [Westminster, CO

    2012-03-20

    A system and method for inputting, analyzing, and disseminating information necessary for identified decision-makers to respond to emergency situations. This system and method provides consistency and integration among multiple groups, and may be used for both initial consequence-based decisions and follow-on consequence-based decisions. The system and method in a preferred embodiment also provides tools for accessing and manipulating information that are appropriate for each decision-maker, in order to achieve more reasoned and timely consequence-based decisions. The invention includes processes for designing and implementing a system or method for responding to emergency situations.

  1. A Decision Analytic Approach to Exposure-Based Chemical ...

    EPA Pesticide Factsheets

    The manufacture of novel synthetic chemicals has increased in volume and variety, but often the environmental and health risks are not fully understood in terms of toxicity and, in particular, exposure. While efforts to assess risks have generally been effective when sufficient data are available, the hazard and exposure data necessary to assess risks adequately are unavailable for the vast majority of chemicals in commerce. The US Environmental Protection Agency has initiated the ExpoCast Program to develop tools for rapid chemical evaluation based on potential for exposure. In this context, a model is presented in which chemicals are evaluated based on inherent chemical properties and behaviorally-based usage characteristics over the chemical’s life cycle. These criteria are assessed and integrated within a decision analytic framework, facilitating rapid assessment and prioritization for future targeted testing and systems modeling. A case study outlines the prioritization process using 51 chemicals. The results show a preliminary relative ranking of chemicals based on exposure potential. The strength of this approach is the ability to integrate relevant statistical and mechanistic data with expert judgment, allowing for an initial tier assessment that can further inform targeted testing and risk management strategies. The National Exposure Research Laboratory′s (NERL′s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in suppor

  2. A Decision Analytic Approach to Exposure-Based Chemical Prioritization

    PubMed Central

    Mitchell, Jade; Pabon, Nicolas; Collier, Zachary A.; Egeghy, Peter P.; Cohen-Hubal, Elaine; Linkov, Igor; Vallero, Daniel A.

    2013-01-01

    The manufacture of novel synthetic chemicals has increased in volume and variety, but often the environmental and health risks are not fully understood in terms of toxicity and, in particular, exposure. While efforts to assess risks have generally been effective when sufficient data are available, the hazard and exposure data necessary to assess risks adequately are unavailable for the vast majority of chemicals in commerce. The US Environmental Protection Agency has initiated the ExpoCast Program to develop tools for rapid chemical evaluation based on potential for exposure. In this context, a model is presented in which chemicals are evaluated based on inherent chemical properties and behaviorally-based usage characteristics over the chemical’s life cycle. These criteria are assessed and integrated within a decision analytic framework, facilitating rapid assessment and prioritization for future targeted testing and systems modeling. A case study outlines the prioritization process using 51 chemicals. The results show a preliminary relative ranking of chemicals based on exposure potential. The strength of this approach is the ability to integrate relevant statistical and mechanistic data with expert judgment, allowing for an initial tier assessment that can further inform targeted testing and risk management strategies. PMID:23940664

  3. Following Human Footsteps: Proposal of a Decision Theory Based on Human Behavior

    NASA Technical Reports Server (NTRS)

    Mahmud, Faisal

    2011-01-01

    Human behavior is a complex nature which depends on circumstances and decisions varying from time to time as well as place to place. The way a decision is made either directly or indirectly related to the availability of the options. These options though appear at random nature, have a solid directional way for decision making. In this paper, a decision theory is proposed which is based on human behavior. The theory is structured with model sets that will show the all possible combinations for making a decision, A virtual and simulated environment is considered to show the results of the proposed decision theory

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

    NASA Astrophysics Data System (ADS)

    Huo, Hanqiang

    2010-07-01

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

  5. Six Heads Are Better than One? School-Based Decision Making in Rural Kentucky.

    ERIC Educational Resources Information Center

    Kannapel, Patricia J.; And Others

    1995-01-01

    A 3-year examination of school-based decision-making (SBDM) councils in four rural Kentucky school districts revealed that, similar to findings in urban and suburban settings, SBDM councils in rural schools experienced difficulties in achieving true shared decision making. Decisions regarding hiring and budget management were most likely to lead…

  6. Development of an Optimal Water Allocation Decision Tool for the Major Crops During the Water Deficit Period in the Southeast U.S.

    NASA Technical Reports Server (NTRS)

    Paudel, Krishna P.; Limaye, Ashutosh; Hatch, Upton; Cruise, James; Musleh, Fuad

    2005-01-01

    We developed a dynamic model to optimize irrigation application in three major crops (corn, cotton and peanuts) grown in the Southeast USA. Water supply amount is generated from an engineering model which is then combined with economic models to find the optimal amount of irrigation water to apply on each crop field during the six critical water deficit weeks in summer. Results indicate that water is applied on the crop with the highest marginal value product of irrigation. Decision making tool such as the one developed here would help farmers and policy makers to find the maximum profitable solution when water shortage is a serious concern.

  7. In-person and video-based post-traumatic stress disorder treatment for veterans: a location-allocation model.

    PubMed

    Musdal, Hande; Shiner, Brian; Chen, Techieh; Ceyhan, Mehmet E; Watts, Bradley V; Benneyan, James

    2014-02-01

    Post-traumatic stress disorder (PTSD) is associated with poor health but there is a gap between need and receipt of care. It is useful to understand where to optimally locate in-person care and where video-based PTSD care would be most useful to minimize access to care barriers, care outside the Veterans Affairs system, and total costs. We developed a service location systems engineering model based on 2010 to 2020 projected care needs for veterans across New England to help determine where to best locate and use in-person and video-based care. This analysis determined specific locations and capacities of each type of PTSD care relative to patient home locations to help inform allocation of mental health resources. Not surprisingly Massachusetts, Connecticut, and Rhode Island are well suited for in-person care, whereas some rural areas of Maine, Vermont, and New Hampshire where in-patient services are infeasible could be better served by video-based care than external care, if the latter is even available. Results in New England alone suggest a potential $3,655,387 reduction in average annual total costs by shifting 9.73% of care to video-based treatment, with an average 12.6 miles travel distance for the remaining in-person care.

  8. Does improved decision-making ability reduce the physiological demands of game-based activities in field sport athletes?

    PubMed

    Gabbett, Tim J; Carius, Josh; Mulvey, Mike

    2008-11-01

    This study investigated the effects of video-based perceptual training on pattern recognition and pattern prediction ability in elite field sport athletes and determined whether enhanced perceptual skills influenced the physiological demands of game-based activities. Sixteen elite women soccer players (mean +/- SD age, 18.3 +/- 2.8 years) were allocated to either a video-based perceptual training group (N = 8) or a control group (N = 8). The video-based perceptual training group watched video footage of international women's soccer matches. Twelve training sessions, each 15 minutes in duration, were conducted during a 4-week period. Players performed assessments of speed (5-, 10-, and 20-m sprint), repeated-sprint ability (6 x 20-m sprints, with active recovery on a 15-second cycle), estimated maximal aerobic power (V O2 max, multistage fitness test), and a game-specific video-based perceptual test of pattern recognition and pattern prediction before and after the 4 weeks of video-based perceptual training. The on-field assessments included time-motion analysis completed on all players during a standardized 45-minute small-sided training game, and assessments of passing, shooting, and dribbling decision-making ability. No significant changes were detected in speed, repeated-sprint ability, or estimated V O2 max during the training period. However, video-based perceptual training improved decision accuracy and reduced the number of recall errors, indicating improved game awareness and decision-making ability. Importantly, the improvements in pattern recognition and prediction ability transferred to on-field improvements in passing, shooting, and dribbling decision-making skills. No differences were detected between groups for the time spent standing, walking, jogging, striding, and sprinting during the small-sided training game. These findings demonstrate that video-based perceptual training can be used effectively to enhance the decision-making ability of field

  9. Decision Maker based on Nanoscale Photo-excitation Transfer

    NASA Astrophysics Data System (ADS)

    Kim, Song-Ju; Naruse, Makoto; Aono, Masashi; Ohtsu, Motoichi; Hara, Masahiko

    2013-08-01

    Decision-making is one of the most important intellectual abilities of the human brain. Here we propose an efficient decision-making system which uses optical energy transfer between quantum dots (QDs) mediated by optical near-field interactions occurring at scales far below the wavelength of light. The simulation results indicate that our system outperforms the softmax rule, which is known as the best-fitting algorithm for human decision-making behaviour. This suggests that we can produce a nano-system which makes decisions efficiently and adaptively by exploiting the intrinsic spatiotemporal dynamics involving QDs mediated by optical near-field interactions.

  10. Decision Maker based on Nanoscale Photo-excitation Transfer

    PubMed Central

    Kim, Song-Ju; Naruse, Makoto; Aono, Masashi; Ohtsu, Motoichi; Hara, Masahiko

    2013-01-01

    Decision-making is one of the most important intellectual abilities of the human brain. Here we propose an efficient decision-making system which uses optical energy transfer between quantum dots (QDs) mediated by optical near-field interactions occurring at scales far below the wavelength of light. The simulation results indicate that our system outperforms the softmax rule, which is known as the best-fitting algorithm for human decision-making behaviour. This suggests that we can produce a nano-system which makes decisions efficiently and adaptively by exploiting the intrinsic spatiotemporal dynamics involving QDs mediated by optical near-field interactions. PMID:23928655

  11. Statistical analysis of blocking probability and fragmentation based on Markov modeling of elastic spectrum allocation on fiber link

    NASA Astrophysics Data System (ADS)

    Rosa, A. N. F.; Wiatr, P.; Cavdar, C.; Carvalho, S. V.; Costa, J. C. W. A.; Wosinska, L.

    2015-11-01

    In Elastic Optical Network (EON), spectrum fragmentation refers to the existence of non-aligned, small-sized blocks of free subcarrier slots in the optical spectrum. Several metrics have been proposed in order to quantify a level of spectrum fragmentation. Approximation methods might be used for estimating average blocking probability and some fragmentation measures, but are so far unable to accurately evaluate the influence of different sizes of connection requests and do not allow in-depth investigation of blocking events and their relation to fragmentation. The analytical study of the effect of fragmentation on requests' blocking probability is still under-explored. In this work, we introduce new definitions for blocking that differentiate between the reasons for the blocking events. We developed a framework based on Markov modeling to calculate steady-state probabilities for the different blocking events and to analyze fragmentation related problems in elastic optical links under dynamic traffic conditions. This framework can also be used for evaluation of different definitions of fragmentation in terms of their relation to the blocking probability. We investigate how different allocation request sizes contribute to fragmentation and blocking probability. Moreover, we show to which extend blocking events, due to insufficient amount of available resources, become inevitable and, compared to the amount of blocking events due to fragmented spectrum, we draw conclusions on the possible gains one can achieve by system defragmentation. We also show how efficient spectrum allocation policies really are in reducing the part of fragmentation that in particular leads to actual blocking events. Simulation experiments are carried out showing good match with our analytical results for blocking probability in a small scale scenario. Simulated blocking probabilities for the different blocking events are provided for a larger scale elastic optical link.

  12. Designing a robust feature extraction method based on optimum allocation and principal component analysis for epileptic EEG signal classification.

    PubMed

    Siuly, Siuly; Li, Yan

    2015-04-01

    The aim of this study is to design a robust feature extraction method for the classification of multiclass EEG signals to determine valuable features from original epileptic EEG data and to discover an efficient classifier for the features. An optimum allocation based principal component analysis method named as OA_PCA is developed for the feature extraction from epileptic EEG data. As EEG data from different channels are correlated and huge in number, the optimum allocation (OA) scheme is used to discover the most favorable representatives with minimal variability from a large number of EEG data. The principal component analysis (PCA) is applied to construct uncorrelated components and also to reduce the dimensionality of the OA samples for an enhanced recognition. In order to choose a suitable classifier for the OA_PCA feature set, four popular classifiers: least square support vector machine (LS-SVM), naive bayes classifier (NB), k-nearest neighbor algorithm (KNN), and linear discriminant analysis (LDA) are applied and tested. Furthermore, our approaches are also compared with some recent research work. The experimental results show that the LS-SVM_1v1 approach yields 100% of the overall classification accuracy (OCA), improving up to 7.10% over the existing algorithms for the epileptic EEG data. The major finding of this research is that the LS-SVM with the 1v1 system is the best technique for the OA_PCA features in the epileptic EEG signal classification that outperforms all the recent reported existing methods in the literature.

  13. Activity-based analyses lead to better decision making.

    PubMed

    Player, S

    1998-08-01

    Activity-based costing (ABC) and activity-based management (ABM) are cost-management tools that are relatively new to the healthcare industry. ABC is used for strategic decision making. It assesses the costs associated with specific activities and resources and links those costs to specific internal and external customers of the healthcare enterprise (e.g., patients, service lines, and physician groups) to determine the costs associated with each customer. This cost information then can be adjusted to account for anticipated changes and to predict future costs. ABM, on the other hand, supports operations by focusing on the causes of costs and how costs can be reduced. It assesses cost drivers that directly affect the cost of a product or service, and uses performance measures to evaluate the financial or nonfinancial benefit an activity provides. By identifying each cost driver and assessing the value the element adds to the healthcare enterprise, ABM provides a basis for selecting areas that can be changed to reduce costs.

  14. Recollection- and Familiarity-Based Decisions Reflect Memory Strength

    PubMed Central

    Wiesmann, Martin; Ishai, Alumit

    2008-01-01

    We used event-related fMRI to investigate whether recollection- and familiarity-based memory judgments are modulated by the degree of visual similarity between old and new art paintings. Subjects performed a flower detection task, followed by a Remember/Know/New surprise memory test. The old paintings were randomly presented with new paintings, which were either visually similar or visually different. Consistent with our prediction, subjects were significantly faster and more accurate to reject new, visually different paintings than new, visually similar ones. The proportion of false alarms, namely remember and know responses to new paintings, was significantly reduced with decreased visual similarity. The retrieval task evoked activation in multiple visual, parietal and prefrontal regions, within which remember judgments elicited stronger activation than know judgments. New, visually different paintings evoked weaker activation than new, visually similar items in the intraparietal sulcus. Contrasting recollection with familiarity revealed activation predominantly within the precuneus, where the BOLD response elicited by recollection peaked significantly earlier than the BOLD response evoked by familiarity judgments. These findings suggest that successful memory retrieval of pictures is mediated by activation in a distributed cortical network, where memory strength is manifested by differential hemodynamic profiles. Recollection- and familiarity-based memory decisions may therefore reflect strong memories and weak memories, respectively. PMID:18958245

  15. An Analysis and Allocation System for Library Collections Budgets: The Comprehensive Allocation Process (CAP)

    ERIC Educational Resources Information Center

    Lyons, Lucy Eleonore; Blosser, John

    2012-01-01

    The "Comprehensive Allocation Process" (CAP) is a reproducible decision-making structure for the allocation of new collections funds, for the reallocation of funds within stagnant budgets, and for budget cuts in the face of reduced funding levels. This system was designed to overcome common shortcomings of current methods. Its philosophical…

  16. 77 FR 64890 - Transmission Planning and Cost Allocation by Transmission Owning and Operating Public Utilities

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-24

    .... Consideration of Transmission Needs Driven by 28 Public Policy Requirements B. Nonincumbent Transmission... followed or if a cost allocation method was not followed or produced unjust and unreasonable results for a.... 1000 compliance filings process and make a decision based on the record before us. 3. Consideration...

  17. District Allocation of Human Resources Utilizing the Evidence Based Model: A Study of One High Achieving School District in Southern California

    ERIC Educational Resources Information Center

    Lane, Amber Marie

    2013-01-01

    This study applies the Gap Analysis Framework to understand the gaps that exist in human resource allocation of one Southern California school district. Once identified, gaps are closed with the reallocation of human resources, according to the Evidenced Based Model, requiring the re-purposing of core classroom teachers, specialists, special…

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

    PubMed Central

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

    2001-01-01

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

  19. Creating a GIS-Based Decision-Support System

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  20. Evidence-Based Decision-Making as a Practice-Based Learning Skill: A Pilot Study

    ERIC Educational Resources Information Center

    Falzer, Paul R.; Garman, Melissa

    2012-01-01

    Objectives: As physicians are being trained to adapt their practices to the needs and experience of patients, initiatives to standardize care have been gaining momentum. The resulting conflict can be addressed through a practice-based learning and improvement (PBL) program that develops competency in using treatment guidelines as decision aids and…

  1. Visual Attention Allocation Between Robotic Arm and Environmental Process Control: Validating the STOM Task Switching Model

    NASA Technical Reports Server (NTRS)

    Wickens, Christopher; Vieanne, Alex; Clegg, Benjamin; Sebok, Angelia; Janes, Jessica

    2015-01-01

    Fifty six participants time shared a spacecraft environmental control system task with a realistic space robotic arm control task in either a manual or highly automated version. The former could suffer minor failures, whose diagnosis and repair were supported by a decision aid. At the end of the experiment this decision aid unexpectedly failed. We measured visual attention allocation and switching between the two tasks, in each of the eight conditions formed by manual-automated arm X expected-unexpected failure X monitoring- failure management. We also used our multi-attribute task switching model, based on task attributes of priority interest, difficulty and salience that were self-rated by participants, to predict allocation. An un-weighted model based on attributes of difficulty, interest and salience accounted for 96 percent of the task allocation variance across the 8 different conditions. Task difficulty served as an attractor, with more difficult tasks increasing the tendency to stay on task.

  2. Stakeholders' views on the routine use of n-of-1 trials to improve clinical care and to make resource allocation decisions for drug use.

    PubMed

    Nikles, Jane; Mitchell, Geoffrey K; Clavarino, Alexandra; Yelland, Michael J; Del Mar, Christopher B

    2010-03-01

    N-of-1 trials are empirical formal tests using a within-patient randomised, double-blind, cross-over comparison of drug and placebo (or another drug), which we adapted to study individual patients' responses as a clinical tool to guide clinical management. We administered semi-structured interviews to gauge stakeholder perspectives on the possibility of using routine n-of-1 trials for this purpose. Stakeholders included government and non-government health care sector, and patient, clinician and consumer, organisations. Stakeholders supported more widespread implementation of n-of-1 trials, in a targeted fashion, with some caveats. Barriers to their widespread implementation included constraints on doctors' time, doctors' acceptance, drug company acceptance, patient willingness, and cost. Strategies for overcoming barriers included conditional Pharmaceutical Benefits Scheme listing if cost-effective. There was little consensus on which model of n-of-1 trial implementation would be most effective. We discuss different approaches to addressing the several concerns raised to enable widespread introduction of n-of-1 trials into routine clinical practice as a decision tool.

  3. Age Differences in Road Crossing Decisions Based on Gap Judgements

    PubMed Central

    Oxley, J. A.; Fildes, B. N.; Ihsen, E.; Charlton, J. L.; Day, R. H.

    1999-01-01

    Older pedestrians are over-involved in serious injury and fatal crashes compared to younger adults. This may be due, in part, to diminished perceptual, cognitive and motor skills which act to reduce the older person’s ability to sense danger and take measures to avoid hazards. Two experiments are described in this paper which examine age differences in gap selection decisions in a simulated road crossing environment. The results demonstrated age differences in the decision-making process, particularly a difficulty in estimating appropriate time-of-arrival of oncoming traffic along with an inability to allow for slower decision times and walking speeds. A two-phase model of road crossing decisions is discussed within a limited information processing approach and it is suggested that older adults experience problems in quickly and instantaneously calculating distance and velocity information in order to select safe margins in which to cross the road.

  4. GUIDED TOUR OF A WEB-BASED ENVIRONMENTAL DECISION TOOLKIT

    EPA Science Inventory

    Decision-making regarding the targeting of vulnerable resources and prioritization of actions requires synthesis of data on condition, vulnerability, and feasibility of risk management alternatives. EP A's Regional Vulnerability Assessment (ReV A) Program has evaluated existing a...

  5. Collective credit allocation in science.

    PubMed

    Shen, Hua-Wei; Barabási, Albert-László

    2014-08-26

    Collaboration among researchers is an essential component of the modern scientific enterprise, playing a particularly important role in multidisciplinary research. However, we continue to wrestle with allocating credit to the coauthors of publications with multiple authors, because the relative contribution of each author is difficult to determine. At the same time, the scientific community runs an informal field-dependent credit allocation process that assigns credit in a collective fashion to each work. Here we develop a credit allocation algorithm that captures the coauthors' contribution to a publication as perceived by the scientific community, reproducing the informal collective credit allocation of science. We validate the method by identifying the authors of Nobel-winning papers that are credited for the discovery, independent of their positions in the author list. The method can also compare the relative impact of researchers working in the same field, even if they did not publish together. The ability to accurately measure the relative credit of researchers could affect many aspects of credit allocation in science, potentially impacting hiring, funding, and promotion decisions.

  6. Collective credit allocation in science

    PubMed Central

    Shen, Hua-Wei; Barabási, Albert-László

    2014-01-01

    Collaboration among researchers is an essential component of the modern scientific enterprise, playing a particularly important role in multidisciplinary research. However, we continue to wrestle with allocating credit to the coauthors of publications with multiple authors, because the relative contribution of each author is difficult to determine. At the same time, the scientific community runs an informal field-dependent credit allocation process that assigns credit in a collective fashion to each work. Here we develop a credit allocation algorithm that captures the coauthors’ contribution to a publication as perceived by the scientific community, reproducing the informal collective credit allocation of science. We validate the method by identifying the authors of Nobel-winning papers that are credited for the discovery, independent of their positions in the author list. The method can also compare the relative impact of researchers working in the same field, even if they did not publish together. The ability to accurately measure the relative credit of researchers could affect many aspects of credit allocation in science, potentially impacting hiring, funding, and promotion decisions. PMID:25114238

  7. Motion-Based Piloted Simulation Evaluation of a Control Allocation Technique to Recover from Pilot Induced Oscillations

    NASA Technical Reports Server (NTRS)

    Craun, Robert W.; Acosta, Diana M.; Beard, Steven D.; Leonard, Michael W.; Hardy, Gordon H.; Weinstein, Michael; Yildiz, Yildiray

    2013-01-01

    This paper describes the maturation of a control allocation technique designed to assist pilots in the recovery from pilot induced oscillations (PIOs). The Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) is designed to enable next generation high efficiency aircraft designs. Energy efficient next generation aircraft require feedback control strategies that will enable lowering the actuator rate limit requirements for optimal airframe design. One of the common issues flying with actuator rate limits is PIOs caused by the phase lag between the pilot inputs and control surface response. CAPIO utilizes real-time optimization for control allocation to eliminate phase lag in the system caused by control surface rate limiting. System impacts of the control allocator were assessed through a piloted simulation evaluation of a non-linear aircraft simulation in the NASA Ames Vertical Motion Simulator. Results indicate that CAPIO helps reduce oscillatory behavior, including the severity and duration of PIOs, introduced by control surface rate limiting.

  8. 77 FR 43184 - Allocation of Capacity on New Merchant Transmission Projects and New Cost-Based, Participant...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-24

    ... customers, and (2) file a report with the Commission describing the solicitation, selection and negotiation... report to the Commission describing the solicitation, selection and negotiation process. The Commission... allocate 100 percent of their projects' capacity through bilateral negotiations with identified...

  9. Developing an Agent-based Model for the Depot-based Water Allocation System in the Bakken Field in Western North Dakota

    NASA Astrophysics Data System (ADS)

    Lin, T.; Lin, Z.; Lim, S.; Borders, M.

    2015-12-01

    The oil production at the Bakken Shale increased more than ten times from 2008 to 2013 due to technological advancement in hydraulic fracturing and North Dakota has become the second largest oil producing state in the U.S. behind only Texas since 2012. On average it requires about 2-4 million gallons of freshwater to complete one oil well in the Bakken field and the number of oil well completions (i.e., hydraulic fracturing) in the Bakken field increased from 500 in 2008 to 2085 in 2013. A large quantity of freshwater used for hydraulic fracturing renders a significant impact on water resource management in the semi-arid region. A novel water allocation system - water depots - was spontaneously created to distribute surface and ground water for industrial uses. A GIS-based multi-agent model is developed to simulate the emergent patterns and dynamics of the water depot-based water allocation system and to explore its economic and environmental consequences. Four different types of water depot are defined as agents and water price, climate condition, water source, geology, and other physical and economic constraints are considered in the model. Decentralized optimization algorithm will be used to determine the agents' behaviors. The agent-based model for water depots will be coupled with hydrological models to improve the region's water resources management.

  10. Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

    PubMed Central

    Dolan, James G.

    2010-01-01

    Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

  11. Agent based model of effects of task allocation strategies in flat organizations

    NASA Astrophysics Data System (ADS)

    Sobkowicz, Pawel

    2016-09-01

    A common practice in many organizations is to pile the work on the best performers. It is easy to implement by the management and, despite the apparent injustice, appears to be working in many situations. In our work we present a simple agent based model, constructed to simulate this practice and to analyze conditions under which the overall efficiency of the organization (for example measured by the backlog of unresolved issues) breaks down, due to the cumulative effect of the individual overloads. The model confirms that the strategy mentioned above is, indeed, rational: it leads to better global results than an alternative one, using equal workload distribution among all workers. The presented analyses focus on the behavior of the organizations close to the limit of the maximum total throughput and provide results for the growth of the unprocessed backlog in several situations, as well as suggestions related to avoiding such buildup.

  12. CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

    PubMed Central

    Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

    2015-01-01

    Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options

  13. The Relative Success of Recognition-Based Inference in Multichoice Decisions

    ERIC Educational Resources Information Center

    McCloy, Rachel; Beaman, C. Philip; Smith, Philip T.

    2008-01-01

    The utility of an "ecologically rational" recognition-based decision rule in multichoice decision problems is analyzed, varying the type of judgment required (greater or lesser). The maximum size and range of a counterintuitive advantage associated with recognition-based judgment (the "less-is-more effect") is identified for a range of cue…

  14. Data-Based Decisions Guidelines for Teachers of Students with Severe Intellectual and Developmental Disabilities

    ERIC Educational Resources Information Center

    Jimenez, Bree A.; Mims, Pamela J.; Browder, Diane M.

    2012-01-01

    Effective practices in student data collection and implementation of data-based instructional decisions are needed for all educators, but are especially important when students have severe intellectual and developmental disabilities. Although research in the area of data-based instructional decisions for students with severe disabilities shows…

  15. Asymmetric programming: a highly reliable metadata allocation strategy for MLC NAND flash memory-based sensor systems.

    PubMed

    Huang, Min; Liu, Zhaoqing; Qiao, Liyan

    2014-10-10

    While the NAND flash memory is widely used as the storage medium in modern sensor systems, the aggressive shrinking of process geometry and an increase in the number of bits stored in each memory cell will inevitably degrade the reliability of NAND flash memory. In particular, it's critical to enhance metadata reliability, which occupies only a small portion of the storage space, but maintains the critical information of the file system and the address translations of the storage system. Metadata damage will cause the system to crash or a large amount of data to be lost. This paper presents Asymmetric Programming, a highly reliable metadata allocation strategy for MLC NAND flash memory storage systems. Our technique exploits for the first time the property of the multi-page architecture of MLC NAND flash memory to improve the reliability of metadata. The basic idea is to keep metadata in most significant bit (MSB) pages which are more reliable than least significant bit (LSB) pages. Thus, we can achieve relatively low bit error rates for metadata. Based on this idea, we propose two strategies to optimize address mapping and garbage collection. We have implemented Asymmetric Programming on a real hardware platform. The experimental results show that Asymmetric Programming can achieve a reduction in the number of page errors of up to 99.05% with the baseline error correction scheme.

  16. Asymmetric Programming: A Highly Reliable Metadata Allocation Strategy for MLC NAND Flash Memory-Based Sensor Systems

    PubMed Central

    Huang, Min; Liu, Zhaoqing; Qiao, Liyan

    2014-01-01

    While the NAND flash memory is widely used as the storage medium in modern sensor systems, the aggressive shrinking of process geometry and an increase in the number of bits stored in each memory cell will inevitably degrade the reliability of NAND flash memory. In particular, it's critical to enhance metadata reliability, which occupies only a small portion of the storage space, but maintains the critical information of the file system and the address translations of the storage system. Metadata damage will cause the system to crash or a large amount of data to be lost. This paper presents Asymmetric Programming, a highly reliable metadata allocation strategy for MLC NAND flash memory storage systems. Our technique exploits for the first time the property of the multi-page architecture of MLC NAND flash memory to improve the reliability of metadata. The basic idea is to keep metadata in most significant bit (MSB) pages which are more reliable than least significant bit (LSB) pages. Thus, we can achieve relatively low bit error rates for metadata. Based on this idea, we propose two strategies to optimize address mapping and garbage collection. We have implemented Asymmetric Programming on a real hardware platform. The experimental results show that Asymmetric Programming can achieve a reduction in the number of page errors of up to 99.05% with the baseline error correction scheme. PMID:25310473

  17. Dynamic resource allocation engine for cloud-based real-time video transcoding in mobile cloud computing environments

    NASA Astrophysics Data System (ADS)

    Adedayo, Bada; Wang, Qi; Alcaraz Calero, Jose M.; Grecos, Christos

    2015-02-01

    The recent explosion in video-related Internet traffic has been driven by the widespread use of smart mobile devices, particularly smartphones with advanced cameras that are able to record high-quality videos. Although many of these devices offer the facility to record videos at different spatial and temporal resolutions, primarily with local storage considerations in mind, most users only ever use the highest quality settings. The vast majority of these devices are optimised for compressing the acquired video using a single built-in codec and have neither the computational resources nor battery reserves to transcode the video to alternative formats. This paper proposes a new low-complexity dynamic resource allocation engine for cloud-based video transcoding services that are both scalable and capable of being delivered in real-time. Firstly, through extensive experimentation, we establish resource requirement benchmarks for a wide range of transcoding tasks. The set of tasks investigated covers the most widely used input formats (encoder type, resolution, amount of motion and frame rate) associated with mobile devices and the most popular output formats derived from a comprehensive set of use cases, e.g. a mobile news reporter directly transmitting videos to the TV audience of various video format requirements, with minimal usage of resources both at the reporter's end and at the cloud infrastructure end for transcoding services.

  18. A Consensus-Based Grouping Algorithm for Multi-agent Cooperative Task Allocation with Complex Requirements.

    PubMed

    Hunt, Simon; Meng, Qinggang; Hinde, Chris; Huang, Tingwen

    2014-01-01

    This paper looks at consensus algorithms for agent cooperation with unmanned aerial vehicles. The foundation is the consensus-based bundle algorithm, which is extended to allow multi-agent tasks requiring agents to cooperate in completing individual tasks. Inspiration is taken from the cognitive behaviours of eusocial animals for cooperation and improved assignments. Using the behaviours observed in bees and ants inspires decentralised algorithms for groups of agents to adapt to changing task demand. Further extensions are provided to improve task complexity handling by the agents with added equipment requirements and task dependencies. We address the problems of handling these challenges and improve the efficiency of the algorithm for these requirements, whilst decreasing the communication cost with a new data structure. The proposed algorithm converges to a conflict-free, feasible solution of which previous algorithms are unable to account for. Furthermore, the algorithm takes into account heterogeneous agents, deadlocking and a method to store assignments for a dynamical environment. Simulation results demonstrate reduced data usage and communication time to come to a consensus on multi-agent tasks.

  19. Finding shared decisions in stakeholder networks: An agent-based approach

    NASA Astrophysics Data System (ADS)

    Le Pira, Michela; Inturri, Giuseppe; Ignaccolo, Matteo; Pluchino, Alessandro; Rapisarda, Andrea

    2017-01-01

    We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations' results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.

  20. Aeromedical decision-making: an evidence-based risk management paradigm.

    PubMed

    Watson, Dougal B

    2005-01-01

    Aeromedical decisions take many forms and are made by different groups and individuals. Because of the ubiquity of aviation in the world today, it is important that aeromedical decisions are of the highest quality that can be reasonably achieved. A paradigm of evidence-based aeromedical risk management is reported on here. It combines the concept of evidence-based medicine with structured risk management methodologies to produce a methodology capable of delivering the highest quality of aeromedical decisions. While neither of these concepts is new, practitioners do need to ensure that they have the skills and knowledge to maximize the quality of their aeromedical decisions.

  1. The case-based decision support system in the field of IT-consulting

    NASA Astrophysics Data System (ADS)

    Avdeenko, T. V.; Makarova, E. S.

    2017-01-01

    In the present paper, we propose an approach to facilitation of decision-making in the field of IT-consulting. The approach is based on knowledge representation in the form of cases containing past history about decision making. We also proposed an ontology to store the cases as instances of classes. Classification of cases in the ontology is executed by means of fuzzy inference. The method of classification is based on the original algorithm of transformation of cases (precedents) sample to the set of linguistic rules allowing one to make relevant decisions. Research of the method has shown good accuracy of the decisions classification according to test data.

  2. Decision-fusion-based automated drill bit toolmark correlator

    NASA Astrophysics Data System (ADS)

    Jones, Brett C.; Press, Michael J.; Guerci, Joseph R.

    1999-02-01

    This paper describes a recent study conducted to investigate the reproducibility of toolmarks left by drill bits. This paper focuses on the automated analysis aspect of the study, and particularly the advantages of using decision fusion methods in the comparisons. To enable the study to encompass a large number of samples, existing technology was adapted to the task of automatically comparing the test impressions. Advanced forensic pattern recognition algorithms that had been developed for the comparison of ballistic evidence in the DRUGFIRETM system were modified for use in this test. The results of the decision fusion architecture closely matched those obtained by expert visual examination. The study, aided by the improved pattern recognition algorithm, showed that drill bit impressions do contain reproducible marks. In a blind test, the DRUGFIRE pattern recognition algorithm, enhanced with the decision fusion architecture, consistently identified the correct bit as the source of the test impressions.

  3. Estradiol modulates effort-based decision making in female rats.

    PubMed

    Uban, Kristina A; Rummel, Julia; Floresco, Stan B; Galea, Liisa A M

    2012-01-01

    Disorders of the dopamine system, such as schizophrenia or stimulant addiction, are associated with impairments in different forms of cost/benefit decision making. The neural circuitry (ie amygdala, prefrontal cortex, nucleus accumbens) underlying these functions receives dopamine input, which is thought to have a central role in mediating cost/benefit decisions. Estradiol modulates dopamine activity, and estrogen receptors (ERs) are found within this neurocircuitry, suggesting that decision making may be influenced by estradiol. The present study examined the contribution of estradiol and selective ERα and β agonists on cost/benefit decision making in adult female Long-Evans rats. An effort-discounting task was utilized, where rats could either emit a single response on a low-reward lever to receive two pellets, or make 2, 5, 10, or 20 responses on a high-reward lever to obtain four pellets. Ovariectomy increased the choice on the high-reward lever, whereas replacement with high (10 μg), but not low (0.3 μg), levels of estradiol benzoate reduced the choice on the high-reward lever. Interestingly, both an ERα agonist (propyl-pyrazole triol (PPT)) and an ERβ agonist (diarylpropionitrile (DPN)) increased choice on the high-reward lever when administered independently, but when these two agonists were combined, a decrease in choice for the high-reward lever was observed. The effects of estradiol, PPT, and DPN were more pronounced 24 h post-administration, suggesting that these effects may be genomic in nature. Together, these results demonstrate that estradiol modulates cost/benefit decision making in females, whereby concomitant activation of ERα and β receptors shifts the decision criteria and reduces preference for larger, yet more costly rewards.

  4. Understanding the impacts of allocation approaches during process-based life cycle assessment of water treatment chemicals.

    PubMed

    Alvarez-Gaitan, Juan P; Peters, Gregory M; Short, Michael D; Schulz, Matthias; Moore, Stephen

    2014-01-01

    Chemicals are an important component of advanced water treatment operations not only in terms of economics but also from an environmental standpoint. Tools such as life cycle assessment (LCA) are useful for estimating the environmental impacts of water treatment operations. At the same time, LCA analysts must manage several fundamental and as yet unresolved methodological challenges, one of which is the question of how best to "allocate" environmental burdens in multifunctional processes. Using water treatment chemicals as a case study example, this article aims to quantify the variability in greenhouse gas emissions estimates stemming from methodological choices made in respect of allocation during LCA. The chemicals investigated and reported here are those most important to coagulation and disinfection processes, and the outcomes are illustrated on the basis of treating 1000 ML of noncoagulated and nondisinfected water. Recent process and economic data for the production of these chemicals is used and methodological alternatives for solving the multifunctionality problem, including system expansion and mass, exergy, and economic allocation, are applied to data from chlor-alkali plants. In addition, Monte Carlo simulation is included to provide a comprehensive picture of the robustness of economic allocation results to changes in the market price of these industrial commodities. For disinfection, results demonstrate that chlorine gas has a lower global warming potential (GWP) than sodium hypochlorite regardless of the technique used to solve allocation issues. For coagulation, when mass or economic allocation is used to solve the multifunctionality problem in the chlor-alkali facility, ferric chloride was found to have a higher GWP than aluminum sulfate and a slightly lower burden where system expansion or exergy allocation are applied instead. Monte Carlo results demonstrate that when economic allocation is used, GWP results were relatively robust and resilient

  5. Developing Evidence-Based Care Standards and a Decision-Making Support System for Pain Management.

    PubMed

    Feng, Rung-Chuang; Chang, Polun

    2016-01-01

    Pain is a crucial sign and symptom in hospitalised patients. This paper describes how a medical centre created a knowledge-based, computerised pain management decision-making process to support nurses in personalising preventive interventions based on patient requirements.

  6. An Advance Reservation-Based Co-allocation Algorithm for Distributed Computers and Network Bandwidth on QoS-Guaranteed Grids

    NASA Astrophysics Data System (ADS)

    Takefusa, Atsuko; Nakada, Hidemoto; Kudoh, Tomohiro; Tanaka, Yoshio

    Co-allocation of performance-guaranteed computing and network resources provided by several administrative domains is one of the key issues for constructing a QoS-guaranteed Grid. We propose an advance reservation-based co-allocation algorithm for both computing and network resources on a QoS-guaranteed Grid, modeled as an integer programming (IP) problem. The goal of our algorithm is to create reservation plans satisfying user resource requirements as an on-line service. Also the algorithm takes co-allocation options for user and resource administrator issues into consideration. We evaluate the proposed algorithm with extensive simulation, in terms of both functionality and practicality. The results show: The algorithm enables efficient co-allocation of both computing and network resources provided by multiple domains, and can reflect reservation options for resource administrators issues as a first step. The calculation times needed for selecting resources using an IP solver are acceptable for an on-line service.

  7. Implementation of a National Priority Allocation System for Hypersensitized Patients in Spain, Based on Virtual Crossmatch: Initial Results.

    PubMed

    Valentin, M O; Ruiz, J C; Vega, R; Martín, C; Matesanz, R

    2016-11-01

    Access to kidney transplantation for patients with high levels of antibodies against HLA is a major challenge. This issue makes it difficult to detect compatible donors for those patients in a certain geographical area. Consequently, hypersensitized patients remain on the waiting list for long periods and their quality of life deteriorates. Our purpose was to increase access to transplantation for highly sensitized patients by developing a national priority allocation system based on virtual crossmatch. Between June 15, 2015, and May 15, 2016, 675 patients on the kidney transplant waiting list with calculated panel-reactive antibodies ≥98% and undergoing dialysis for at least 12 months were included in the study; 86.1% of the patients had previously received at least one transplant. Solid-phase immunoassays were used to identify class I and II HLA antibodies in all patients. Participating hospitals assigned to the program one of the kidneys of every identified brain-dead real donor between 18 and 70 years old. Survival data were collected for the recipients transplanted between June 15, 2015, and December 31, 2015. In all, 475 (290 male and 185 female) brain-dead donors were assigned to the program. Virtual crossmatch was negative for 191 (41%) donors, 149 offers were accepted, and 102 (21.8%) kidneys were transplanted. At the end of the study, patient and graft survival were both 93.4%. The implementation of a national prioritization system based on virtual crossmatch increased access to transplantation for highly sensitized patients, with excellent results in terms of patient and graft survival.

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

    ERIC Educational Resources Information Center

    Greenes, Robert A.

    2009-01-01

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

  9. Decision Support for Patient Preference-based Care Planning

    PubMed Central

    Ruland, Cornelia M.

    1999-01-01

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

  10. [Evidence-based decision-making: when it is worthwhile].

    PubMed

    Neumann, Ignacio; Rada, Gabriel

    2014-06-11

    Every day health professionals have to make dozens of decisions regarding patient care and management. It is not easy to integrate scientific evidence in this process. The primary ability we need in order to achieve successful results is learning how to recognize the circumstances in which evidence arising from results of scientific trials may help.

  11. A Core Journal Decision Model Based on Weighted Page Rank

    ERIC Educational Resources Information Center

    Wang, Hei-Chia; Chou, Ya-lin; Guo, Jiunn-Liang

    2011-01-01

    Purpose: The paper's aim is to propose a core journal decision method, called the local impact factor (LIF), which can evaluate the requirements of the local user community by combining both the access rate and the weighted impact factor, and by tracking citation information on the local users' articles. Design/methodology/approach: Many…

  12. Modelling C allocation in response to nutrient availability

    NASA Astrophysics Data System (ADS)

    Stocker, Benjamin; Prentice, Colin

    2015-04-01

    Carbon (C) allocation in ecosystems is a key variable of the global terrestrial C cycle. While photosynthesis governs the amount of C that enters ecosystems, its subsequent allocation to compartments with different life times determines its over-all residence time and variations in allocation patterns drive changes in ecosystem C balance and its response to environmental change. A better understanding of the controls on allocation is thus key to improving global vegetation models that commonly rely on using fixed partitioning factors. Observational data suggests variations of ecosystem structure and functioning along large-scale gradients of resource availability. Below-ground C allocation, inferred as gross primary production minus above-ground biomass production increases along gradients of decreasing nutrient availability. This is not only due to more root growth, but also due to enhanced production of exudates and stimulation of root symbionts and has been interpreted to reflect optimal plant allocation decisions under a varying soil fertility status. Here, we propose a model that accounts for trade-offs between (i) growth in above-ground and (ii) below-ground plant compartments, (iii) exudation to the rhizosphere and root symbionts and (iv) temporary storage in non-structural pools. By postulating the maximization of long-term growth under a given (seasonal regime) of soil nitrogen (N) availability, we attempt to reproduce observed large-scale gradients. The model is formulated based on a C cost for different N uptake decisions, where the cost is a function of N availability, root mass, and soil temperature (for biological N fixation). On a daily time scale, ecosystem N uptake may be realized by C exudation to the rhizosphere and/or symbiotic fixation of atmospheric N2. On an annual time scale, allocation to roots versus leaves is adjusted to soil inorganic N availability and modeled to yield maximum total growth. Exudation versus temporary storage of C is

  13. Classic EEG motor potentials track the emergence of value-based decisions.

    PubMed

    Gluth, Sebastian; Rieskamp, Jörg; Büchel, Christian

    2013-10-01

    Making a value-based decision is a cognitively complex phenomenon and divisible into several sub-processes, such as the perception, evaluation, and final selection of choice options. Although previous research has attempted to dissociate these processes in the brain, there is emerging evidence that late action selection mechanisms are influenced continuously throughout the entire decision act. We used electroencephalography (EEG) and an established sequential decision making paradigm to investigate the extent to which the readiness potential (RP) and the lateralized readiness potential (LRP), two classic preparatory EEG motor components, reflect the ongoing evaluation process in value-based choices. During the task, human participants sequentially sampled probabilistic information to buy or reject offers of unknown value (using both hands) and were allowed to respond at any time. The pressure to respond was manipulated by charging low or high costs for collecting information. We modeled how and when decisions were made and found that participants adaptively lowered their threshold for required evidence with information costs and elapsed time. These shifts were accompanied by an increased RP-like signal during the decision process. The RP was further influenced by the amount of accumulated evidence. In addition, an LRP could be measured from the start of the decision process, well in advance and independent of the final decision. Our results are consistent with a continuous involvement of the brain's motor system in emerging value-based decisions and advocate using classic EEG motor potentials for studying neurocognitive theories of decision making.

  14. A Cercla-Based Decision Support System for Environmental Remediation Strategy Selection.

    DTIC Science & Technology

    1997-03-01

    A CERCLA -BASED DECISION SUPPORT SYSTEM FOR ENVIRONMENTAL REMEDIATION STRATEGY SELECTION 2Lt Brian J. Grelk AFIT/GORI97M- 10 DEPARTMENT OF THE AIR...FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio vimC ’QEjA BP3f AFIT/GOR/ENS/97M- 10 A CERCLA -BASED DECISION...unlimited MC QULM TnpEOM1 AFIT/GOR/ENS/97M- 10 A CERCLA -BASED DECISION SUPPORT SYSTEM FOR ENVIRONMENTAL REMEDIATION STRATEGY SELECTION THESIS Presented to

  15. 24 CFR 982.101 - Allocation of funding.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 24 Housing and Urban Development 4 2013-04-01 2013-04-01 false Allocation of funding. 982.101... DEVELOPMENT SECTION 8 TENANT-BASED ASSISTANCE: HOUSING CHOICE VOUCHER PROGRAM Funding and PHA Application for Funding § 982.101 Allocation of funding. (a) Allocation of funding. HUD allocates available...

  16. 24 CFR 982.101 - Allocation of funding.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 24 Housing and Urban Development 4 2012-04-01 2012-04-01 false Allocation of funding. 982.101... DEVELOPMENT SECTION 8 TENANT BASED ASSISTANCE: HOUSING CHOICE VOUCHER PROGRAM Funding and PHA Application for Funding § 982.101 Allocation of funding. (a) Allocation of funding. HUD allocates available...

  17. Competitive allocation of resources on a network: an agent-based model of air companies competing for the best routes

    NASA Astrophysics Data System (ADS)

    Gurtner, Gérald; Valori, Luca; Lillo, Fabrizio

    2015-05-01

    We present a stylized model of the allocation of resources on a network. By considering as a concrete example the network of sectors of the airspace, where each node is a sector characterized by a maximal number of simultaneously present aircraft, we consider the problem of air companies competing for the allocation of the airspace. Each company is characterized by a cost function, weighting differently punctuality and length of the flight. We consider the model in the presence of pure and mixed populations of types of airline companies and we study how the equilibria depends on the characteristics of the network.

  18. Age Estimation Based on Children's Voice: A Fuzzy-Based Decision Fusion Strategy

    PubMed Central

    Ting, Hua-Nong

    2014-01-01

    Automatic estimation of a speaker's age is a challenging research topic in the area of speech analysis. In this paper, a novel approach to estimate a speaker's age is presented. The method features a “divide and conquer” strategy wherein the speech data are divided into six groups based on the vowel classes. There are two reasons behind this strategy. First, reduction in the complicated distribution of the processing data improves the classifier's learning performance. Second, different vowel classes contain complementary information for age estimation. Mel-frequency cepstral coefficients are computed for each group and single layer feed-forward neural networks based on self-adaptive extreme learning machine are applied to the features to make a primary decision. Subsequently, fuzzy data fusion is employed to provide an overall decision by aggregating the classifier's outputs. The results are then compared with a number of state-of-the-art age estimation methods. Experiments conducted based on six age groups including children aged between 7 and 12 years revealed that fuzzy fusion of the classifier's outputs resulted in considerable improvement of up to 53.33% in age estimation accuracy. Moreover, the fuzzy fusion of decisions aggregated the complementary information of a speaker's age from various speech sources. PMID:25006595

  19. Development of a web GIS application for emissions inventory spatial allocation based on open source software tools

    NASA Astrophysics Data System (ADS)

    Gkatzoflias, Dimitrios; Mellios, Giorgos; Samaras, Zissis

    2013-03-01

    Combining emission inventory methods and geographic information systems (GIS) remains a key issue for environmental modelling and management purposes. This paper examines the development of a web GIS application as part of an emission inventory system that produces maps and files with spatial allocated emissions in a grid format. The study is not confined in the maps produced but also presents the features and capabilities of a web application that can be used by every user even without any prior knowledge of the GIS field. The development of the application was based on open source software tools such as MapServer for the GIS functions, PostgreSQL and PostGIS for the data management and HTML, PHP and JavaScript as programming languages. In addition, background processes are used in an innovative manner to handle the time consuming and computational costly procedures of the application. Furthermore, a web map service was created to provide maps to other clients such as the Google Maps API v3 that is used as part of the user interface. The output of the application includes maps in vector and raster format, maps with temporal resolution on daily and hourly basis, grid files that can be used by air quality management systems and grid files consistent with the European Monitoring and Evaluation Programme Grid. Although the system was developed and validated for the Republic of Cyprus covering a remarkable wide range of pollutant and emissions sources, it can be easily customized for use in other countries or smaller areas, as long as geospatial and activity data are available.

  20. A new web-based framework development for fuzzy multi-criteria group decision-making.

    PubMed

    Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

    2016-01-01

    Fuzzy multi-criteria group decision making (FMCGDM) process is usually used when a group of decision-makers faces imprecise data or linguistic variables to solve the problems. However, this process contains many methods that require many time-consuming calculations depending on the number of criteria, alternatives and decision-makers in order to reach the optimal solution. In this study, a web-based FMCGDM framework that offers decision-makers a fast and reliable response service is proposed. The proposed framework includes commonly used tools for multi-criteria decision-making problems such as fuzzy Delphi, fuzzy AHP and fuzzy TOPSIS methods. The integration of these methods enables taking advantages of the strengths and complements each method's weakness. Finally, a case study of location selection for landfill waste in Morocco is performed to demonstrate how this framework can facilitate decision-making process. The results demonstrate that the proposed framework can successfully accomplish the goal of this study.

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

    EPA Science Inventory

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

  2. Overview of Results from 1994 & 1995 School-Based Decision Making Surveys.

    ERIC Educational Resources Information Center

    Lindle, Jane Clark; Gale, Bruce S.; Curry-White, Brenda

    The 1994 and 1995 School-Based Decision Making (SBDM) Surveys were conducted in the fall of each of those years for the Study of Education Policy. This report compares the 1994 and 1995 responses to three questions: (1) What do people think of the effectiveness of SBDM? (2) Who is involved in the SBDM decisions? and (3) What are councils doing?…

  3. Distance-Based and Distributed Learning: A Decision Tool for Education Leaders.

    ERIC Educational Resources Information Center

    McGraw, Tammy M.; Ross, John D.

    This decision tool presents a progression of data collection and decision-making strategies that can increase the effectiveness of distance-based or distributed learning instruction. A narrative and flow chart cover the following steps: (1) basic assumptions, including purpose of instruction, market scan, and financial resources; (2) needs…

  4. Integration or Fragmentation: The Impact of Site-Based Decision-Making.

    ERIC Educational Resources Information Center

    Avila, Linda, Ed.

    Early efforts at site-based decision making in Texas created many diverse questions about how to proceed. In some school districts, the change to a new decision-making balance centered around the district office. In others, strong campus control was established and effective self-governance plans were created. This monograph presents the…

  5. School-Based Management: An Approach to Decision-Making Quality in Egyptian General Secondary Schools

    ERIC Educational Resources Information Center

    Elmelegy, Reda Ibrahim

    2015-01-01

    The current research aims at clarifying how school-based management (SBM) can contribute to achieve the decision-making quality in Egyptian general secondary schools and determine the requirements of quality decision-making. It depends on the descriptive method in order to acknowledge the basics of the SBM and its relationship with the quality of…

  6. Error rate information in attention allocation pilot models

    NASA Technical Reports Server (NTRS)

    Faulkner, W. H.; Onstott, E. D.

    1977-01-01

    The Northrop urgency decision pilot model was used in a command tracking task to compare the optimized performance of multiaxis attention allocation pilot models whose urgency functions were (1) based on tracking error alone, and (2) based on both tracking error and error rate. A matrix of system dynamics and command inputs was employed, to create both symmetric and asymmetric two axis compensatory tracking tasks. All tasks were single loop on each axis. Analysis showed that a model that allocates control attention through nonlinear urgency functions using only error information could not achieve performance of the full model whose attention shifting algorithm included both error and error rate terms. Subsequent to this analysis, tracking performance predictions for the full model were verified by piloted flight simulation. Complete model and simulation data are presented.

  7. Bandwidth-allocated algorithm modeled with matrix theory for traffic-orientated multisubsystem-based virtual passive optical network in metro-access optical network

    NASA Astrophysics Data System (ADS)

    Xia, Weidong; Gan, Chaoqin; Chen, Bingqin; Xie, Weilun; Zhang, YuChao; Gou, Kaiyu

    2016-09-01

    In a metro-access optical network, a bandwidth-allocated algorithm is proposed for traffic-orientated multisubsystem-based virtual passive optical network (MS-VPON) that can implement the syncretism of multiple systems such as time division multiplexing-PON (TDM-PON), wavelength division multiplexing-PON (WDM-PON), and orthogonal frequency division multiplexing-PON (OFDM-PON). VPONs are constructed based on traffic and different VPONs are separated by different types of traffic. The bandwidth-allocated algorithm is modeled with a matrix theory to determine which VPON can be admitted and then a bandwidth is assigned to these VPONs. With the algorithm, the network value can be maximized. Two cases are investigated to demonstrate the effectiveness of the proposed algorithm in the bandwidth-utilized ratio and VPONs' admission probability.

  8. Design and implementation of priority and time-window based traffic scheduling and routing-spectrum allocation mechanism in elastic optical networks

    NASA Astrophysics Data System (ADS)

    Wang, Honghuan; Xing, Fangyuan; Yin, Hongxi; Zhao, Nan; Lian, Bizhan

    2016-02-01

    With the explosive growth of network services, the reasonable traffic scheduling and efficient configuration of network resources have an important significance to increase the efficiency of the network. In this paper, an adaptive traffic scheduling policy based on the priority and time window is proposed and the performance of this algorithm is evaluated in terms of scheduling ratio. The routing and spectrum allocation are achieved by using the Floyd shortest path algorithm and establishing a node spectrum resource allocation model based on greedy algorithm, which is proposed by us. The fairness index is introduced to improve the capability of spectrum configuration. The results show that the designed traffic scheduling strategy can be applied to networks with multicast and broadcast functionalities, and makes them get real-time and efficient response. The scheme of node spectrum configuration improves the frequency resource utilization and gives play to the efficiency of the network.

  9. A Dynamic Interval Decision-Making Method Based on GRA

    NASA Astrophysics Data System (ADS)

    Xue-jun, Tang; Jia, Chen

    According to the basic theory of grey relational analysis, this paper constructs a three-dimensional grey interval relation degree model for the three dimensions of time, index and scheme. On its basis, it sets up and solves a single-targeted optimization model, and obtains each scheme's affiliate degree for the positive/negative ideal scheme and also arranges the schemes in sequence. The result shows that the three-dimensional grey relation degree simplifies the traditional dynamic multi-attribute decision-making method and can better resolve the dynamic multi-attribute decision-making method of interval numbers. Finally, this paper proves the practicality and efficiency of the model through a case study.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  11. The neural bases underlying social risk perception in purchase decisions.

    PubMed

    Yokoyama, Ryoichi; Nozawa, Takayuki; Sugiura, Motoaki; Yomogida, Yukihito; Takeuchi, Hikaru; Akimoto, Yoritaka; Shibuya, Satoru; Kawashima, Ryuta

    2014-05-01

    Social considerations significantly influence daily purchase decisions, and the perception of social risk (i.e., the anticipated disapproval of others) is crucial in dissuading consumers from making purchases. However, the neural basis for consumers' perception of social risk remains undiscovered, and this novel study clarifies the relevant neural processes. A total of 26 volunteers were scanned while they evaluated purchase intention of products (purchase intention task) and their anticipation of others' disapproval for possessing a product (social risk task), using functional magnetic resonance imaging (fMRI). The fMRI data from the purchase intention task was used to identify the brain region associated with perception of social risk during purchase decision making by using subjective social risk ratings for a parametric modulation analysis. Furthermore, we aimed to explore if there was a difference between participants' purchase decisions and their explicit evaluations of social risk, with reference to the neural activity associated with social risk perception. For this, subjective social risk ratings were used for a parametric modulation analysis on fMRI data from the social risk task. Analysis of the purchase intention task revealed a significant positive correlation between ratings of social risk and activity in the anterior insula, an area of the brain that is known as part of the emotion-related network. Analysis of the social risk task revealed a significant positive correlation between ratings of social risk and activity in the temporal parietal junction and the medial prefrontal cortex, which are known as theory-of-mind regions. Our results suggest that the anterior insula processes consumers' social risk implicitly to prompt consumers not to buy socially unacceptable products, whereas ToM-related regions process such risk explicitly in considering the anticipated disapproval of others. These findings may prove helpful in understanding the mental

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

    PubMed Central

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

    2016-01-01

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

  13. 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

  14. Evidence-Based Medicine in judicial decisions concerning right to healthcare

    PubMed Central

    Dias, Eduardo Rocha; da Silva, Geraldo Bezerra

    2016-01-01

    ABSTRACT Objective To analyze, from the examination of decisions issued by Brazilian courts, how Evidence-Based Medicine was applied and if it led to well-founded decisions, searching the best scientific knowledge. Methods The decisions made by the Federal Courts were searched, with no time limits, at the website of the Federal Court Council, using the expression “Evidence-Based Medicine”. With regard to decisions issued by the court of the State of São Paulo, the search was done at the webpage and applying the same terms and criterion as to time. Next, a qualitative analysis of the decisions was conducted for each action, to verify if the patient/plaintiff’s situation, as well as the efficacy or inefficacy of treatments or drugs addressed in existing protocols were considered before the court granted the provision claimed by the plaintiff. Results In less than one-third of the decisions there was an appropriate discussion about efficacy of the procedure sought in court, in comparison to other procedures available in clinical guidelines adopted by the Brazilian Unified Health System (Sistema Único de Saúde) or by private health insurance plans, considering the individual situation. The majority of the decisions involved private health insurance plans (n=13, 68%). Conclusion The number of decisions that did consider scientific evidence and the peculiarities of each patient was a concern. Further discussion on Evidence-Based Medicine in judgments involving public healthcare are required. PMID:27074226

  15. The Interplay of Hippocampus and Ventromedial Prefrontal Cortex in Memory-Based Decision Making

    PubMed Central

    Weilbächer, Regina A.; Gluth, Sebastian

    2016-01-01

    Episodic memory and value-based decision making are two central and intensively studied research domains in cognitive neuroscience, but we are just beginning to understand how they interact to enable memory-based decisions. The two brain regions that have been associated with episodic memory and value-based decision making are the hippocampus and the ventromedial prefrontal cortex, respectively. In this review article, we first give an overview of these brain–behavior associations and then focus on the mechanisms of potential interactions between the hippocampus and ventromedial prefrontal cortex that have been proposed and tested in recent neuroimaging studies. Based on those possible interactions, we discuss several directions for future research on the neural and cognitive foundations of memory-based decision making. PMID:28036071

  16. Decision Support System for Resource Allocation Model

    DTIC Science & Technology

    1989-04-01

    by Presutti and Trepp in their paper "Much Ado about EOQ." [2) The constraints used in the stock fund model are total stock fund dollars and limits on...Jersey, 1963. 2. Presutti, Victor J., Jr. and Trepp , Richard C., More Ado About Economic Order Ouantities (EOO), Operations Analysis Office

  17. Recruiting Resource and Goal Allocation Decision Model.

    DTIC Science & Technology

    1980-01-01

    Number of High Schools AHSS Average High School Size a These variables are available only by flight (i.e., data are not available at the office level...649, 1.96(HSM) . 3 , (INT). I 4 ( AHSS ) - . 9 , (LEAD). 0 4 , (ACO’ 6 9 , (EXP). I I + 5.85(AFB) + 21.8 (3) Where: I. The constant term value 21.8

  18. Hesitant Fuzzy Thermodynamic Method for Emergency Decision Making Based on Prospect Theory.

    PubMed

    Ren, Peijia; Xu, Zeshui; Hao, Zhinan

    2016-12-30

    Due to the timeliness of emergency response and much unknown information in emergency situations, this paper proposes a method to deal with the emergency decision making, which can comprehensively reflect the emergency decision making process. By utilizing the hesitant fuzzy elements to represent the fuzziness of the objects and the hesitant thought of the experts, this paper introduces the negative exponential function into the prospect theory so as to portray the psychological behaviors of the experts, which transforms the hesitant fuzzy decision matrix into the hesitant fuzzy prospect decision matrix (HFPDM) according to the expectation-levels. Then, this paper applies the energy and the entropy in thermodynamics to take the quantity and the quality of the decision values into account, and defines the thermodynamic decision making parameters based on the HFPDM. Accordingly, a whole procedure for emergency decision making is conducted. What is more, some experiments are designed to demonstrate and improve the validation of the emergency decision making procedure. Last but not the least, this paper makes a case study about the emergency decision making in the firing and exploding at Port Group in Tianjin Binhai New Area, which manifests the effectiveness and practicability of the proposed method.

  19. Learning to maximize reward rate: a model based on semi-Markov decision processes

    PubMed Central

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R.

    2014-01-01

    When animals have to make a number of decisions during a limited time interval, they face a fundamental problem: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible “conditions.” A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each “condition” being a “state” and the value of decision thresholds being the “actions” taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values. PMID:24904252

  20. Learning to maximize reward rate: a model based on semi-Markov decision processes.

    PubMed

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

    2014-01-01

    WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

  1. Partially observable Markov decision processes for risk-based screening

    NASA Astrophysics Data System (ADS)

    Mrozack, Alex; Liao, Xuejun; Skatter, Sondre; Carin, Lawrence

    2016-05-01

    A long-term goal for checked baggage screening in airports has been to include passenger information, or at least a predetermined passenger risk level, in the screening process. One method for including that information could be treating the checked baggage screening process as a system-of-systems. This would allow for an optimized policy builder, such as one trained using the methodology of partially observable Markov decision processes (POMDP), to navigate the different sensors available for screening. In this paper we describe the necessary steps to tailor a POMDP for baggage screening, as well as results of simulations for specific screening scenarios.

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

    NASA Astrophysics Data System (ADS)

    Rehr, Amanda P.; Small, Mitchell J.; Bradley, Patricia; Fisher, William S.; Vega, Ann; Black, Kelly; Stockton, Tom

    2012-12-01

    We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers-Pressures-States-Impacts-Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.

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

    EPA Science Inventory

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

  4. Measuring Land Uses Accessibility by Using Fuzzy Majority Gis-Based Multicriteria Decision Analysis Case Study: Malayer City

    NASA Astrophysics Data System (ADS)

    Taravat, A.; Yari, A.; Rajaei, M.; Mousavian, R.

    2014-10-01

    Public spaces accessibility has become one of the important factors in urban planning. Therefore, considerable attention has been given to measure accessibility to public spaces on the UK, US and Canada, but there are few studies outside the anglophone world especially in developing countries such as Iran. In this study an attempt has been made to measure objective accessibility to public spaces (parks, school, library and administrative) using fuzzy majority GIS-based multicriteria decision analysis. This method is for defining the priority for distribution of urban facilities and utilities as the first step towards elimination of social justice. In order to test and demonstrate the presented model, the comprehensive plan of Malayer city has been considered for ranking in three objectives and properties in view of index per capital (Green space, sport facilities and major cultural centers like library and access index). The results can be used to inform the local planning process and the GIS approach can be expanded into other local authority domains. The results shows that the distribution of facilities in Malayer city has followed on the base of cost benefit law and the human aspect of resource allocation programming of facilities (from centre to suburbs of the city).

  5. Holistic risk-based environmental decision making: a Native perspective.

    PubMed Central

    Arquette, Mary; Cole, Maxine; Cook, Katsi; LaFrance, Brenda; Peters, Margaret; Ransom, James; Sargent, Elvera; Smoke, Vivian; Stairs, Arlene

    2002-01-01

    Native American Nations have become increasingly concerned about the impacts of toxic substances. Although risk assessment and risk management processes have been used by government agencies to help estimate and manage risks associated with exposure to toxicants, these tools have many inadequacies and as a result have not served Native people well. In addition, resources have not always been adequate to address the concerns of Native Nations, and involvement of Native decision makers on a government-to-government basis in discussions regarding risk has only recently become common. Finally, because the definitions of health used by Native people are strikingly different from that of risk assessors, there is also a need to expand current definitions and incorporate traditional knowledge into decision making. Examples are discussed from the First Environment Restoration Initiative, a project that is working to address toxicant issues facing the Mohawk territory of Akwesasne. This project is developing a community-defined model in which health is protected at the same time that traditional cultural practices, which have long been the key to individual and community health, are maintained and restored. PMID:11929736

  6. An evidence-based shared decision making programme on the prevention of myocardial infarction in type 2 diabetes: protocol of a randomised-controlled trial

    PubMed Central

    2013-01-01

    Background Lack of patient involvement in decision making has been suggested as one reason for limited treatment success. Concepts such as shared decision making may contribute to high quality healthcare by supporting patients to make informed decisions together with their physicians. A multi-component shared decision making programme on the prevention of heart attack in type 2 diabetes has been developed. It aims at improving the quality of decision-making by providing evidence-based patient information, enhancing patients’ knowledge, and supporting them to actively participate in decision-making. In this study the efficacy of the programme is evaluated in the setting of a diabetes clinic. Methods/Design A single blinded randomised-controlled trial is conducted to compare the shared decision making programme with a control-intervention. The intervention consists of an evidence-based patient decision aid on the prevention of myocardial infarction and a corresponding counselling module provided by diabetes educators. Similar in duration and structure, the control-intervention targets nutrition, sports, and stress coping. A total of 154 patients between 40 and 69 years of age with type 2 diabetes and no previous diagnosis of ischaemic heart disease or stroke are enrolled and allocated either to the intervention or the control-intervention. Primary outcome measure is the patients’ knowledge on benefits and harms of heart attack prevention captured by a standardised knowledge test. Key secondary outcome measure is the achievement of treatment goals prioritised by the individual patient. Treatment goals refer to statin taking, HbA1c-, blood pressure levels and smoking status. Outcomes are assessed directly after the counselling and at 6 months follow-up. Analyses will be carried out on intention-to-treat basis. Concurrent qualitative methods are used to explore intervention fidelity and to gain insight into implementation processes. Discussion Interventions to

  7. Neural oscillations and synchronization differentially support evidence accumulation in perceptual and value-based decision making.

    PubMed

    Polanía, Rafael; Krajbich, Ian; Grueschow, Marcus; Ruff, Christian C

    2014-05-07

    Organisms make two types of decisions on a regular basis. Perceptual decisions are determined by objective states of the world (e.g., melons are bigger than apples), whereas value-based decisions are determined by subjective preferences (e.g., I prefer apples to melons). Theoretical accounts suggest that both types of choice involve neural computations accumulating evidence for the choice alternatives; however, little is known about the overlap or differences in the processes underlying perceptual versus value-based decisions. We analyzed EEG recordings during a paradigm where perceptual- and value-based choices were based on identical stimuli. For both types of choice, evidence accumulation was evident in parietal gamma-frequency oscillations, whereas a similar frontal signal was unique for value-based decisions. Fronto-parietal synchronization of these signals predicted value-based choice accuracy. These findings uncover how decisions emerge from topographic- and frequency-specific oscillations that accumulate distinct aspects of evidence, with large-scale synchronization as a mechanism integrating these spatially distributed signals.

  8. Learning automata-based solutions to the nonlinear fractional knapsack problem with applications to optimal resource allocation.

    PubMed

    Granmo, Ole-Christoffer; Oommen, B John; Myrer, Svein Arild; Olsen, Morten Goodwin

    2007-02-01

    This paper considers the nonlinear fractional knapsack problem and demonstrates how its solution can be effectively applied to two resource allocation problems dealing with the World Wide Web. The novel solution involves a "team" of deterministic learning automata (LA). The first real-life problem relates to resource allocation in web monitoring so as to "optimize" information discovery when the polling capacity is constrained. The disadvantages of the currently reported solutions are explained in this paper. The second problem concerns allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. This is the scenario encountered when the user has to evaluate multiple web sites by accessing a limited number of web pages, and the proportions of interest are the fraction of each web site that is successfully validated by an HTML validator. Using the general LA paradigm to tackle both of the real-life problems, the proposed scheme improves a current solution in an online manner through a series of informed guesses that move toward the optimal solution. At the heart of the scheme, a team of deterministic LA performs a controlled random walk on a discretized solution space. Comprehensive experimental results demonstrate that the discretization resolution determines the precision of the scheme, and that for a given precision, the current solution (to both problems) is consistently improved until a nearly optimal solution is found--even for switching environments. Thus, the scheme, while being novel to the entire field of LA, also efficiently handles a class of resource allocation problems previously not addressed in the literature.

  9. Network coding based joint signaling and dynamic bandwidth allocation scheme for inter optical network unit communication in passive optical networks

    NASA Astrophysics Data System (ADS)

    Wei, Pei; Gu, Rentao; Ji, Yuefeng

    2014-06-01

    As an innovative and promising technology, network coding has been introduced to passive optical networks (PON) in recent years to support inter optical network unit (ONU) communication, yet the signaling process and dynamic bandwidth allocation (DBA) in PON with network coding (NC-PON) still need further study. Thus, we propose a joint signaling and DBA scheme for efficiently supporting differentiated services of inter ONU communication in NC-PON. In the proposed joint scheme, the signaling process lays the foundation to fulfill network coding in PON, and it can not only avoid the potential threat to downstream security in previous schemes but also be suitable for the proposed hybrid dynamic bandwidth allocation (HDBA) scheme. In HDBA, a DBA cycle is divided into two sub-cycles for applying different coding, scheduling and bandwidth allocation strategies to differentiated classes of services. Besides, as network traffic load varies, the entire upstream transmission window for all REPORT messages slides accordingly, leaving the transmission time of one or two sub-cycles to overlap with the bandwidth allocation calculation time at the optical line terminal (the OLT), so that the upstream idle time can be efficiently eliminated. Performance evaluation results validate that compared with the existing two DBA algorithms deployed in NC-PON, HDBA demonstrates the best quality of service (QoS) support in terms of delay for all classes of services, especially guarantees the end-to-end delay bound of high class services. Specifically, HDBA can eliminate queuing delay and scheduling delay of high class services, reduce those of lower class services by at least 20%, and reduce the average end-to-end delay of all services over 50%. Moreover, HDBA also achieves the maximum delay fairness between coded and uncoded lower class services, and medium delay fairness for high class services.

  10. A Model of Reward- and Effort-Based Optimal Decision Making and Motor Control

    PubMed Central

    Rigoux, Lionel; Guigon, Emmanuel

    2012-01-01

    Costs (e.g. energetic expenditure) and benefits (e.g. food) are central determinants of behavior. In ecology and economics, they are combined to form a utility function which is maximized to guide choices. This principle is widely used in neuroscience as a normative model of decision and action, but current versions of this model fail to consider how decisions are actually converted into actions (i.e. the formation of trajectories). Here, we describe an approach where decision making and motor control are optimal, iterative processes derived from the maximization of the discounted, weighted difference between expected rewards and foreseeable motor efforts. The model accounts for decision making in cost/benefit situations, and detailed characteristics of control and goal tracking in realistic motor tasks. As a normative construction, the model is relevant to address the neural bases and pathological aspects of decision making and motor control. PMID:23055916

  11. On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

    NASA Technical Reports Server (NTRS)

    Tunstel, Edward; Jamshidi, Mo

    1997-01-01

    Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

  12. Orbitofrontal Cortex Is Required for Optimal Waiting Based on Decision Confidence

    PubMed Central

    Lak, Armin; Costa, Gil M.; Romberg, Erin; Koulakov, Alexei A.; Mainen, Zachary F.; Kepecs, Adam

    2015-01-01

    SUMMARY Confidence judgments are a central example of metacognition—knowledge about one’s own cognitive processes. According to this metacognitive view, confidence reports are generated by a second-order monitoring process based on the quality of internal representations about beliefs. Although neural correlates of decision confidence have been recently identified in humans and other animals, it is not well understood whether there are brain areas specifically important for confidence monitoring. To address this issue, we designed a postdecision temporal wagering task in which rats expressed choice confidence by the amount of time they were willing to wait for reward. We found that orbitofrontal cortex inactivation disrupts waiting-based confidence reports without affecting decision accuracy. Furthermore, we show that a normative model can quantitatively account for waiting times based on the computation of decision confidence. These results establish an anatomical locus for a metacognitive report, confidence judgment, distinct from the processes required for perceptual decisions. PMID:25242219

  13. A decision surface-based taxonomy of detection statistics

    NASA Astrophysics Data System (ADS)

    Bouffard, François

    2012-09-01

    Current and past literature on the topic of detection statistics - in particular those used in hyperspectral target detection - can be intimidating for newcomers, especially given the huge number of detection tests described in the literature. Detection tests for hyperspectral measurements, such as those generated by dispersive or Fourier transform spectrometers used in remote sensing of atmospheric contaminants, are of paramount importance if any level of analysis automation is to be achieved. The detection statistics used in hyperspectral target detection are generally borrowed and adapted from other fields such as radar signal processing or acoustics. Consequently, although remarkable efforts have been made to clarify and categorize the vast number of available detection tests, understanding their differences, similarities, limits and other intricacies is still an exacting journey. Reasons for this state of affairs include heterogeneous nomenclature and mathematical notation, probably due to the multiple origins of hyperspectral target detection formalisms. Attempts at sorting out detection statistics using ambiguously defined properties may also cause more harm than good. Ultimately, a detection statistic is entirely characterized by its decision boundary. Thus, we propose to catalogue detection statistics according to the shape of their decision surfaces, which greatly simplifies this taxonomy exercise. We make a distinction between the topology resulting from the mathematical formulation of the statistic and mere parameters that adjust the boundary's precise shape, position and orientation. Using this simple approach, similarities between various common detection statistics are found, limit cases are reduced to simpler statistics, and a general understanding of the available detection tests and their properties becomes much easier to achieve.

  14. 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

  15. Evaluating a Web-Based MMR Decision Aid to Support Informed Decision-Making by UK Parents: A Before-and-After Feasibility Study

    ERIC Educational Resources Information Center

    Jackson, Cath; Cheater, Francine M.; Peacock, Rose; Leask, Julie; Trevena, Lyndal

    2010-01-01

    Objective: The objective of this feasibility study was to evaluate the acceptability and potential effectiveness of a web-based MMR decision aid in supporting informed decision-making for the MMR vaccine. Design: This was a prospective before-and-after evaluation. Setting: Thirty parents of children eligible for MMR vaccination were recruited from…

  16. The Effect of Conflict Theory Based Decision-Making Skill Training Psycho-Educational Group Experience on Decision Making Styles of Adolescents

    ERIC Educational Resources Information Center

    Colakkadioglu, Oguzhan; Gucray, S. Sonay

    2012-01-01

    In this study, the effect of conflict theory based decision making skill training group applications on decision making styles of adolescents was investigated. A total of 36 students, including 18 students in experimental group and 18 students in control group, participated in the research. When assigning students to experimental group or control…

  17. RECOVER: An Automated, Cloud-Based Decision Support System for Post-Fire Rehabilitation Planning

    NASA Astrophysics Data System (ADS)

    Schnase, J. L.; Carroll, M. L.; Weber, K. T.; Brown, M. E.; Gill, R. L.; Wooten, M.; May, J.; Serr, K.; Smith, E.; Goldsby, R.; Newtoff, K.; Bradford, K.; Doyle, C.; Volker, E.; Weber, S.

    2014-11-01

    RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

  18. RECOVER: An Automated Cloud-Based Decision Support System for Post-fire Rehabilitation Planning

    NASA Technical Reports Server (NTRS)

    Schnase, John L.; Carroll, Mark; Weber, K. T.; Brown, Molly E.; Gill, Roger L.; Wooten, Margaret; May J.; Serr, K.; Smith, E.; Goldsby, R.; Newtoff, Kiersten; Bradford, Kathryn; Doyle Colin S.; Volker, Emily; Weber, Samuel J.

    2014-01-01

    RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

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

    NASA Astrophysics Data System (ADS)

    Li, Yongchang

    of an appropriate decision making method. Furthermore, some DMs may be exclusively using one or two specific methods which they are familiar with or trust and not realizing that they may be inappropriate to handle certain classes of the problems, thus yielding erroneous results. These issues reveal that in order to ensure a good decision a suitable decision method should be chosen before the decision making process proceeds. The first part of this dissertation proposes an MCDM process supported by an intelligent, knowledge-based advisor system referred to as Multi-Criteria Interactive Decision-Making Advisor and Synthesis process (MIDAS), which is able to facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. The second part of this dissertation presents an autonomous decision making advisor which is capable of dealing with ever-evolving real time information and making autonomous decisions under uncertain conditions. The advisor encompasses a Markov Decision Process (MDP) formulation which takes uncertainty into account when determines the best action for each system state. (Abstract shortened by UMI.)

  20. Research-based-decision-making in Canadian health organizations: a behavioural approach.

    PubMed

    Jbilou, Jalila; Amara, Nabil; Landry, Réjean

    2007-06-01

    Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment... These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build

  1. Resource allocation for efficient environmental management.

    PubMed

    McCarthy, Michael A; Thompson, Colin J; Hauser, Cindy; Burgman, Mark A; Possingham, Hugh P; Moir, Melinda L; Tiensin, Thanawat; Gilbert, Marius

    2010-10-01

    Environmental managers must decide how to invest available resources. Researchers have previously determined how to allocate conservation resources among regions, design nature reserves, allocate funding to species conservation programs, design biodiversity surveys and monitoring programs, manage species and invest in greenhouse gas mitigation schemes. However, these issues have not been addressed with a unified theory. Furthermore, uncertainty is prevalent in environmental management, and needs to be considered to manage risks. We present a theory for optimal environmental management, synthesizing previous approaches to the topic and incorporating uncertainty. We show that the theory solves a diverse range of important problems of resource allocation, including distributing conservation resources among the world's biodiversity hotspots; surveillance to detect the highly pathogenic avian influenza H5N1 virus in Thailand; and choosing survey methods for the insect order Hemiptera. Environmental management decisions are similar to decisions about financial investments, with trade-offs between risk and reward.

  2. Evaluation of a rule base for decision making in general practice.

    PubMed Central

    Essex, B; Healy, M

    1994-01-01

    BACKGROUND. Decision making in general practice relies heavily on judgmental expertise. It should be possible to codify this expertise into rules and principles. AIM. A study was undertaken to evaluate the effectiveness, of rules from a rule base designed to improve students' and trainees' management decisions relating to patients seen in general practice. METHOD. The rule base was developed after studying decisions about and management of thousands of patients seen in one general practice over an eight year period. Vignettes were presented to 93 fourth year medical students and 179 general practitioner trainees. They recorded their perception and management of each case before and after being presented with a selection of relevant rules. Participants also commented on their level of agreement with each of the rules provided with the vignettes. A panel of five independent assessors then rated as good, acceptable or poor, the participants' perception and management of each case before and after seeing the rules. RESULTS. Exposure to a few selected rules of thumb improved the problem perception and management decisions of both undergraduates and trainees. The degree of improvement was not related to previous experience or to the stated level of agreement with the proposed rules. The assessors identified difficulties students and trainees experienced in changing their perceptions and management decisions when the rules suggested options they had not considered. CONCLUSION. The rules developed to improve decision making skills in general practice are effective when used with vignettes. The next phase is to transform the rule base into an expert system to train students and doctors to acquire decision making skills. It could also be used to provide decision support when confronted with difficult management decisions in general practice. PMID:8204334

  3. Electrophysiological correlates reflect the integration of model-based and model-free decision information.

    PubMed

    Eppinger, Ben; Walter, Maik; Li, Shu-Chen

    2017-01-03

    In this study, we investigated the interplay of habitual (model-free) and goal-directed (model-based) decision processes by using a two-stage Markov decision task in combination with event-related potentials (ERPs) and computational modeling. To manipulate the demands on model-based decision making, we applied two experimental conditions with different probabilities of transitioning from the first to the second stage of the task. As we expected, when the stage transitions were more predictable, participants showed greater model-based (planning) behavior. Consistent with this result, we found that stimulus-evoked parietal (P300) activity at the second stage of the task increased with the predictability of the state transitions. However, the parietal activity also reflected model-free information about the expected values of the stimuli, indicating that at this stage of the task both types of information are integrated to guide decision making. Outcome-related ERP components only reflected reward-related processes: Specifically, a medial prefrontal ERP component (the feedback-related negativity) was sensitive to negative outcomes, whereas a component that is elicited by reward (the feedback-related positivity) increased as a function of positive prediction errors. Taken together, our data indicate that stimulus-locked parietal activity reflects the integration of model-based and model-free information during decision making, whereas feedback-related medial prefrontal signals primarily reflect reward-related decision processes.

  4. Team-based learning instruction for responsible conduct of research positively impacts ethical decision-making.

    PubMed

    McCormack, Wayne T; Garvan, Cynthia W

    2014-01-01

    Common practices for responsible conduct of research (RCR) instruction have recently been shown to have no positive impact on and possibly to undermine ethical decision-making (EDM). We show that a team-based learning (TBL) RCR curriculum results in some gains in decision ethicality, the use of more helpful metacognitive reasoning strategies in decision-making, and elimination of most negative effects of other forms of RCR instruction on social-behavioral responses. TBL supports the reasoning strategies and social mechanisms that underlie EDM and ethics instruction, and may provide a more effective method for RCR instruction than lectures and small group discussion.

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

    PubMed

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

    2014-01-01

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

  6. Fuzzy rule-based models for decision support in ecosystem management.

    PubMed

    Adriaenssens, Veronique; De Baets, Bernard; Goethals, Peter L M; De Pauw, Niels

    2004-02-05

    To facilitate decision support in the ecosystem management, ecological expertise and site-specific data need to be integrated. Fuzzy logic can deal with highly variable, linguistic, vague and uncertain data or knowledge and, therefore, has the ability to allow for a logical, reliable and transparent information stream from data collection down to data usage in decision-making. Several environmental applications already implicate the use of fuzzy logic. Most of these applications have been set up by trial and error and are mainly limited to the domain of environmental assessment. In this article, applications of fuzzy logic for decision support in ecosystem management are reviewed and assessed, with an emphasis on rule-based models. In particular, the identification, optimisation, validation, the interpretability and uncertainty aspects of fuzzy rule-based models for decision support in ecosystem management are discussed.

  7. A decision model for cost effective design of biomass based green energy supply chains.

    PubMed

    Yılmaz Balaman, Şebnem; Selim, Hasan

    2015-09-01

    The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures.

  8. Eielson Air Force Base operable unit 2 and other areas record of decision

    SciTech Connect

    Lewis, R.E.; Smith, R.M.

    1994-10-01

    This decision document presents the selected remedial actions and no action decisions for Operable Unit 2 (OU2) at Eielson Air Force Base (AFB), Alaska, chosen in accordance with state and federal regulations. This document also presents the decision that no further action is required for 21 other source areas at Eielson AFB. This decision is based on the administrative record file for this site. OU2 addresses sites contaminated by leaks and spills of fuels. Soils contaminated with petroleum products occur at or near the source of contamination. Contaminated subsurface soil and groundwater occur in plumes on the top of a shallow groundwater table that fluctuates seasonally. These sites pose a risk to human health and the environment because of ingestion, inhalation, and dermal contact with contaminated groundwater. The purpose of this response is to prevent current or future exposure to the contaminated groundwater, to reduce further contaminant migration into the groundwater, and to remediate groundwater.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  10. Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration

    NASA Astrophysics Data System (ADS)

    Altaleb, Hesham

    With the introduction of power energy markets deregulation, innovations have transformed once a static network into a more flexible grid. Microgrids have also been deployed to serve various purposes (e.g., reliability, sustainability, etc.). With the rapid deployment of smart grid technologies, it has become possible to measure and record both, the quantity and time of the consumption of electrical power. In addition, capabilities for controlling distributed supply and demand have resulted in complex systems where inefficiencies are possible and where improvements can be made. Electric power like other volatile resources cannot be stored efficiently, therefore, managing such resource requires considerable attention. Such complex systems present a need for decisions that can streamline consumption, delay infrastructure investments, and reduce costs. When renewable power resources and the need for limiting harmful emissions are added to the equation, the search space for decisions becomes increasingly complex. As a result, the need for a comprehensive decision guidance system for electrical power resources consumption and productions becomes evident. In this dissertation, I formulate and implement a comprehensive framework that addresses different aspect of the electrical power generation and consumption using optimization models and utilizing collaboration concepts. Our solution presents a two-prong approach: managing interaction in real-time for the short-term immediate consumption of already allocated resources; and managing the operational planning for the long-run consumption. More specifically, in real-time, we present and implement a model of how to organize a secondary market for peak-demand allocation and describe the properties of the market that guarantees efficient execution and a method for the fair distribution of collaboration gains. We also propose and implement a primary market for peak demand bounds determination problem with the assumption that

  11. 10 CFR 490.503 - Credit allocation.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 3 2010-01-01 2010-01-01 false Credit allocation. 490.503 Section 490.503 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ALTERNATIVE FUEL TRANSPORTATION PROGRAM Alternative Fueled Vehicle Credit Program § 490.503 Credit allocation. (a) Based on annual credit activity report information,...

  12. 23 CFR 1240.15 - Allocations.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 23 Highways 1 2010-04-01 2010-04-01 false Allocations. 1240.15 Section 1240.15 Highways NATIONAL HIGHWAY TRAFFIC SAFETY ADMINISTRATION AND FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION GUIDELINES SAFETY INCENTIVE GRANTS FOR USE OF SEAT BELTS-ALLOCATIONS BASED ON SEAT BELT USE...

  13. 23 CFR 1240.15 - Allocations.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 23 Highways 1 2011-04-01 2011-04-01 false Allocations. 1240.15 Section 1240.15 Highways NATIONAL HIGHWAY TRAFFIC SAFETY ADMINISTRATION AND FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION GUIDELINES SAFETY INCENTIVE GRANTS FOR USE OF SEAT BELTS-ALLOCATIONS BASED ON SEAT BELT USE...

  14. Genetic-program-based data mining for hybrid decision-theoretic algorithms and theories

    NASA Astrophysics Data System (ADS)

    Smith, James F., III

    2005-03-01

    A genetic program (GP) based data mining (DM) procedure has been developed that automatically creates decision theoretic algorithms. A GP is an algorithm that uses the theory of evolution to automatically evolve other computer programs or mathematical expressions. The output of the GP is a computer program or mathematical expression that is optimal in the sense that it maximizes a fitness function. The decision theoretic algorithms created by the DM algorithm are typically designed for making real-time decisions about the behavior of systems. The database that is mined by the DM typically consists of many scenarios characterized by sensor output and labeled by experts as to the status of the scenario. The DM procedure will call a GP as a data mining function. The GP incorporates the database and expert"s rules into its fitness function to evolve an optimal decision theoretic algorithm. A decision theoretic algorithm created through this process will be discussed as well as validation efforts showing the utility of the decision theoretic algorithm created by the DM process. GP based data mining to determine equations related to scientific theories and automatic simplification methods based on computer algebra will also be discussed.

  15. Protecting resources for primary health care under fiscal federalism: options for resource allocation.

    PubMed

    Okorafor, Okore A; Thomas, Stephen

    2007-11-01

    The introduction of fiscal federalism or decentralization of functions to lower levels of government is a reform not done primarily with health sector concerns. A major concern for the health sector is that devolution of expenditure responsibilities to sub-national levels of government can adversely affect the equitable distribution of financial resources across local jurisdictions. Since the adoption of fiscal federalism in South Africa, progress towards achieving a more equitable distribution of public sector health resources (financial) has slowed down considerably. This study attempts to identify appropriate resource allocation mechanisms under the current South African fiscal federal system that could be employed to promote equity in primary health care (PHC) allocations across provinces and districts. The study uses data from interviews with government officials involved in the budgeting and resource allocation process for PHC, literature on fiscal federalism and literature on international experience to inform analysis and recommendations. The results from the study identify historical incremental budgeting, weak managerial capacity at lower levels of government, poor accounting of PHC expenditure, and lack of protection for PHC funds as constraints to the realization of a more equitable distribution of PHC allocations. Based on interview data, no one resource allocation mechanism received unanimous support from stakeholders. However, the study highlights the particularly high level of autonomy enjoyed by provincial governments with regards to decision making for allocations to health and PHC services as the major constraint to achieving a more equitable distribution of PHC resources. The national government needs to have more involvement in decision making for resource allocation to PHC services if significant progress towards equity is to be achieved.

  16. Evidence-Based Practice: A Framework for Making Effective Decisions

    ERIC Educational Resources Information Center

    Spencer, Trina D.; Detrich, Ronnie; Slocum, Timothy A.

    2012-01-01

    The research to practice gap in education has been a long-standing concern. The enactment of No Child Left Behind brought increased emphasis on the value of using scientifically based instructional practices to improve educational outcomes. It also brought education into the broader evidence-based practice movement that started in medicine and has…

  17. Graph-based Models for Data and Decision Making

    DTIC Science & Technology

    2014-01-01

    signed// DR. LESLIE M. BLAHA JEFFREY L. CRAIG, Chief Work Unit Manager Battlespace Visualization Branch Battlespace Visualization...Performance Wing Human Effectiveness Directorate Crew Systems Interface Division Battlespace Visualization Branch Wright-Patterson Air Force Base...information transmission through a network. Additionally, new visual tools for pattern discovery and visual analytics are proposed based on topological data

  18. [Value-based cancer care. From traditional evidence-based decision making to balanced decision making within frameworks of shared values].

    PubMed

    Palazzo, Salvatore; Filice, Aldo; Mastroianni, Candida; Biamonte, Rosalbino; Conforti, Serafino; Liguori, Virginia; Turano, Salvatore; De Simone, Rosanna; Rovito, Antonio; Manfredi, Caterina; Minardi, Stefano; Vilardo, Emmanuelle; Loizzo, Monica; Oriolo, Carmela

    2016-04-01

    Clinical decision making in oncology is based so far on the evidence of efficacy from high-quality clinical research. Data collection and analysis from experimental studies provide valuable insight into response rates and progression-free or overall survival. Data processing generates valuable information for medical professionals involved in cancer patient care, enabling them to make objective and unbiased choices. The increased attention of many scientific associations toward a more rational resource consumption in clinical decision making is mirrored in the Choosing Wisely campaign against the overuse or misuse of exams and procedures of little or no benefit for the patient. This cultural movement has been actively promoting care solutions based on the concept of "value". As a result, the value-based decision-making process for cancer care should not be dissociated from economic sustainability and from ethics of the affordability, also given the growing average cost of the most recent cancer drugs. In support of this orientation, the National Comprehensive Cancer Network (NCCN) has developed innovative and "complex" guidelines based on values, defined as "evidence blocks", with the aim of assisting the medical community in making overall sustainable choices.

  19. General Formalism of Decision Making Based on Theory of Open Quantum Systems

    NASA Astrophysics Data System (ADS)

    Asano, M.; Ohya, M.; Basieva, I.; Khrennikov, A.

    2013-01-01

    We present the general formalism of decision making which is based on the theory of open quantum systems. A person (decision maker), say Alice, is considered as a quantum-like system, i.e., a system which information processing follows the laws of quantum information theory. To make decision, Alice interacts with a huge mental bath. Depending on context of decision making this bath can include her social environment, mass media (TV, newspapers, INTERNET), and memory. Dynamics of an ensemble of such Alices is described by Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) equation. We speculate that in the processes of evolution biosystems (especially human beings) designed such "mental Hamiltonians" and GKSL-operators that any solution of the corresponding GKSL-equation stabilizes to a diagonal density operator (In the basis of decision making.) This limiting density operator describes population in which all superpositions of possible decisions has already been resolved. In principle, this approach can be used for the prediction of the distribution of possible decisions in human populations.

  20. Reward-Based Decision Signals in Parietal Cortex Are Partially Embodied

    PubMed Central

    Snyder, Lawrence H.

    2015-01-01

    Recordings in the lateral intraparietal area (LIP) reveal that parietal cortex encodes variables related to spatial decision-making, the selection of desirable targets in space. It has been unclear whether parietal cortex is involved in spatial decision-making in general, or whether specific parietal compartments subserve decisions made using specific actions. To test this, we engaged monkeys (Macaca mulatta) in a reward-based decision task in which they selected a target based on its desirability. The animals' choice behavior in this task followed the molar matching law, and in each trial was governed by the desirability of the choice targets. Critically, animals were instructed to make the choice using one of two actions: eye movements (saccades) and arm movements (reaches). We recorded the discharge activity of neurons in area LIP and the parietal reach region (PRR) of the parietal cortex. In line with previous studies, we found that both LIP and PRR encode a reward-based decision variable, the target desirability. Crucially, the target desirability was encoded in LIP at least twice as strongly when choices were made using saccades compared with reaches. In contrast, PRR encoded target desirability only for reaches and not for saccades. These data suggest that decisions can evolve in dedicated parietal circuits in the context of specific actions. This finding supports the hypothesis of an intentional representation of developing decisions in parietal cortex. Furthermore, the close link between the cognitive (decision-related) and bodily (action-related) processes presents a neural contribution to the theories of embodied cognition. PMID:25810518

  1. Documenting the decision structure in software development

    NASA Technical Reports Server (NTRS)

    Wild, J. Christian; Maly, Kurt; Shen, Stewart N.

    1990-01-01

    Current software development paradigms focus on the products of the development process. Much of the decision making process which produces these products is outside the scope of these paradigms. The Decision-Based Software Development (DBSD) paradigm views the design process as a series of interrelated decisions which involve the identification and articulation of problems, alternates, solutions and justifications. Decisions made by programmers and analysts are recorded in a project data base. Unresolved problems are also recorded and resources for their resolution are allocated by management according to the overall development strategy. This decision structure is linked to the products affected by the relevant decision and provides a process oriented view of the resulted system. Software maintenance uses this decision view of the system to understand the rationale behind the decisions affecting the part of the system to be modified. D-HyperCase, a prototype Decision-Based Hypermedia System is described and results of applying the DBSD approach during its development are presented.

  2. Orbitofrontal contributions to value-based decision making: evidence from humans with frontal lobe damage.

    PubMed

    Fellows, Lesley K

    2011-12-01

    The work described here aims to isolate the component processes of decision making that rely critically on particular subregions of the human prefrontal cortex, with a particular focus on the orbitofrontal cortex. Here, experiments isolating specific aspects of decision making, using very simple preference judgment and reinforcement learning paradigms, were carried out in patients with focal frontal damage. The orbitofrontal cortex and the adjacent ventromedial prefrontal cortex play a critical role in decisions based on subjective value, across many categories of stimuli, and in learning to choose between stimuli based on value feedback. However, these regions are not required for learning to choose between actions based on feedback, which instead seems to rely critically on the dorsomedial prefrontal cortex. These results point to a potentially common role for the orbitofrontal cortex in representing the context-sensitive, subjective value of stimuli to allow consistent choices between them. They also argue for multiple, parallel, value-based processes that influence behavior through dissociable mechanisms.

  3. The NATO SOF Air Wing: A Basing Decision

    DTIC Science & Technology

    2012-12-01

    59 2. Medical and Dental Analysis...33. Alternative’s Current Base Medical and Dental Capacity ...............................60 Table 34. Pairwise Comparison of Alternatives on the...Medical and Dental Sub- criterion ............................................................................................................61 Table

  4. [Postmastectomy pain syndrome evidence based guidelines and decision trees].

    PubMed

    Labrèze, Laurent; Dixmérias-Iskandar, Florence; Monnin, Dominique; Bussières, Emmanuel; Delahaye, Evelyne; Bernard, Dominique; Lakdja, Fabrice

    2007-03-01

    A multidisciplinary expert group had reviewed all scientific data available of post mastectomy pain syndrome. Seventy six publications were retained and thirty evidence based diagnosis, treatment and follow-up recommendations are listed. Few of theses recommendations are classed level A. Datas analysis make possible to propose a strategy based on systematic association of drugs, kinesitherapy and psychological support. Evaluation and closer follow-up are necessary. Several decisional trees are proposed.

  5. A Cross-Layer User Centric Vertical Handover Decision Approach Based on MIH Local Triggers

    NASA Astrophysics Data System (ADS)

    Rehan, Maaz; Yousaf, Muhammad; Qayyum, Amir; Malik, Shahzad

    Vertical handover decision algorithm that is based on user preferences and coupled with Media Independent Handover (MIH) local triggers have not been explored much in the literature. We have developed a comprehensive cross-layer solution, called Vertical Handover Decision (VHOD) approach, which consists of three parts viz. mechanism for collecting and storing user preferences, Vertical Handover Decision (VHOD) algorithm and the MIH Function (MIHF). MIHF triggers the VHOD algorithm which operates on user preferences to issue handover commands to mobility management protocol. VHOD algorithm is an MIH User and therefore needs to subscribe events and configure thresholds for receiving triggers from MIHF. In this regard, we have performed experiments in WLAN to suggest thresholds for Link Going Down trigger. We have also critically evaluated the handover decision process, proposed Just-in-time interface activation technique, compared our proposed approach with prominent user centric approaches and analyzed our approach from different aspects.

  6. Picture Exchange Communication System (PECS) or Sign Language: An Evidence-Based Decision-Making Example

    ERIC Educational Resources Information Center

    Spencer, Trina D.; Petersen, Douglas B.; Gillam, Sandra L.

    2008-01-01

    Evidence-based practice (EBP) refers to clinical decisions as a result of the careful integration of research evidence and student needs. Legal mandates such as No Child Left Behind require teachers to employ evidence-based practices in their classrooms, yet teachers receive little guidance regarding how to determine which practices are…

  7. Examining Preservice Teachers' Classroom Management Decisions in Three Case-Based Teaching Approaches

    ERIC Educational Resources Information Center

    Demiraslan-Çevik, Yasemin; Andre, Thomas

    2013-01-01

    This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…

  8. Diverter AI based decision aid, phases 1 and 2

    NASA Technical Reports Server (NTRS)

    Sexton, George A.; Bayles, Scott J.; Patterson, Robert W.; Schulke, Duane A.; Williams, Deborah C.

    1989-01-01

    It was determined that a system to incorporate artificial intelligence (AI) into airborne flight management computers is feasible. The AI functions that would be most useful to the pilot are to perform situational assessment, evaluate outside influences on the contemplated rerouting, perform flight planning/replanning, and perform maneuver planning. A study of the software architecture and software tools capable of demonstrating Diverter was also made. A skeletal planner known as the Knowledge Acquisition Development Tool (KADET), which is a combination script-based and rule-based system, was used to implement the system. A prototype system was developed which demonstrates advanced in-flight planning/replanning capabilities.

  9. A web-based decision support system for slopeland hazard warning.

    PubMed

    Yu, Fan-Chieh; Chen, Chien-Yuan; Lin, Sheng-Chi; Lin, Yu-Ching; Wu, Shang-Yu; Cheung, Kei-Wai

    2007-04-01

    A WebGIS decision support system for slopeland hazard warning based on real-time monitored rainfall is introduced herein. This paper presents its framework, database, processes of setting up the threshold line for debris flow triggering and the calculation algorithm implemented in the system. The web-based GIS via the Microsoft Internet Explorer is designed for analysis of areas prone to debris flows outburst and landslides during torrential rain. Its function is to provide suggestions to commander for immediate response to the possibility of slopeland hazards, and determine if pre-evacuation is necessary. The defining characteristics of the internet-based decision support system is not to automatically show the dangerous areas but acts as part of the decision process via information collection to help experts judge the prone debris flow creeks and the tendency of landslides initiation. The combination with real-time rainfall estimation by the QPESUMS radar system is suggested for further enhancement.

  10. CODE: Coherence Based Decision Boundaries for Feature Correspondence.

    PubMed

    Lin, Wen-Yan; Wang, Fan; Cheng, Ming-Ming; Yeung, Sai-Kit; Torr, Philip H S; Do, Minh N; Lu, Jiangbo

    2017-01-16

    A key challenge in feature correspondence is the difficulty in differentiating true and false matches at a local descriptor level. This forces adoption of strict similarity thresholds that discard many true matches. However, if analyzed at a global level, false matches are usually randomly scattered while true matches tend to be coherent (clustered around a few dominant motions), thus creating a coherence based separability constraint. This paper proposes a non-linear regression technique that can discover such a coherence based separability constraint from highly noisy matches and embed it into a correspondence likelihood model. Once computed, the model can filter the entire set of nearest neighbor matches (which typically contains over 90% false matches) for true matches. We integrate our technique into a full feature correspondence system which reliably generates large numbers of good quality correspondences over wide baselines where previous techniques provide few or no matches.

  11. Energy-efficient optical line terminal for WDM-OFDM-PON based on two-dimensional subcarrier and layer allocation.

    PubMed

    Hu, Xiaofeng; Cao, Pan; Zhuang, Zhiming; Zhang, Liang; Yang, Qi; Su, Yikai

    2012-11-05

    We propose and experimentally demonstrate a scheme to reduce the energy consumption of optical line terminal (OLT) in wavelength division multiplexing - orthogonal frequency division multiplexing - passive optical networks (WDM-OFDM-PONs). In our scheme, a wireless communication technique, termed layered modulation, is introduced to maximize the transmission capacity of OFDM modulation module in the OLT by multiplexing data from different ONU groups with signal-to-noise ratio (SNR) margins onto the same subcarriers. With adaptive and dynamic subcarrier and layer allocation, several ONU groups with low traffic demands can share one OFDM modulation module to deliver their data during non-peak hours of a day, thus greatly reducing the number of running devices and minimizing the energy consumption of the OLT. Numerical calculation shows that an energy efficiency improvement of 28.3% in the OLT can be achieved by using proposed scheme compared to the conventional WDM-OFDM-PON.

  12. Core domains of shared decision-making during psychiatric visits: Scientific and preference-based discussions

    PubMed Central

    Fukui, Sadaaki; Matthias, Marianne S.; Salyers, Michelle P.

    2014-01-01

    Shared decision-making (SDM) is imperative to person-centered care, yet little is known about what aspects of SDM are targeted during psychiatric visits. This secondary data analysis (191 psychiatric visits with 11 providers, coded with a validated SDM coding system) revealed two factors (scientific and preference-based discussions) underlying SDM communication. Preference-based discussion occurred less. Both provider and consumer initiation of SDM elements and decision complexity were associated with greater discussions in both factors, but were more strongly associated with scientific discussion. Longer visit length correlated with only scientific discussion. Providers’ understanding of core domains could facilitate engaging consumers in SDM. PMID:24500023

  13. CEOS Contributions to Informing Energy Management and Policy Decision Making Using Space-Based Earth Observations

    NASA Technical Reports Server (NTRS)

    Eckman, Richard S.

    2009-01-01

    Earth observations are playing an increasingly significant role in informing decision making in the energy sector. In renewable energy applications, space-based observations now routinely augment sparse ground-based observations used as input for renewable energy resource assessment applications. As one of the nine Group on Earth Observations (GEO) societal benefit areas, the enhancement of management and policy decision making in the energy sector is receiving attention in activities conducted by the Committee on Earth Observation Satellites (CEOS). CEOS has become the "space arm" for the implementation of the Global Earth Observation System of Systems (GEOSS) vision. It is directly supporting the space-based, near-term tasks articulated in the GEO three-year work plan. This paper describes a coordinated program of demonstration projects conducted by CEOS member agencies and partners to utilize Earth observations to enhance energy management end-user decision support systems. I discuss the importance of engagement with stakeholders and understanding their decision support needs in successfully increasing the uptake of Earth observation products for societal benefit. Several case studies are presented, demonstrating the importance of providing data sets in formats and units familiar and immediately usable by decision makers. These projects show the utility of Earth observations to enhance renewable energy resource assessment in the developing world, forecast space-weather impacts on the power grid, and improve energy efficiency in the built environment.

  14. Semisupervised classification for hyperspectral image based on multi-decision labeling and deep feature learning

    NASA Astrophysics Data System (ADS)

    Ma, Xiaorui; Wang, Hongyu; Wang, Jie

    2016-10-01

    Semisupervised learning is widely used in hyperspectral image classification to deal with the limited training samples, however, some more information of hyperspectral image should be further explored. In this paper, a novel semisupervised classification based on multi-decision labeling and deep feature learning is presented to exploit and utilize as much information as possible to realize the classification task. First, the proposed method takes two decisions to pre-label each unlabeled sample: local decision based on weighted neighborhood information is made by the surrounding samples, and global decision based on deep learning is performed by the most similar training samples. Then, some unlabeled ones with high confidence are selected to extent the training set. Finally, self decision, which depends on the self features exploited by deep learning, is employed on the updated training set to extract spectral-spatial features and produce classification map. Experimental results with real data indicate that it is an effective and promising semisupervised classification method for hyperspectral image.

  15. [Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

    PubMed

    Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

    2012-02-01

    In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

  16. Reactivation of Reward-Related Patterns from Single Past Episodes Supports Memory-Based Decision Making.

    PubMed

    Wimmer, G Elliott; Büchel, Christian

    2016-03-09

    Rewarding experiences exert a strong influence on later decision making. While decades of neuroscience research have shown how reinforcement gradually shapes preferences, decisions are often influenced by single past experiences. Surprisingly, relatively little is known about the influence of single learning episodes. Although recent work has proposed a role for episodes in decision making, it is largely unknown whether and how episodic experiences contribute to value-based decision making and how the values of single episodes are represented in the brain. In multiple behavioral experiments and an fMRI experiment, we tested whether and how rewarding episodes could support later decision making. Participants experienced episodes of high reward or low reward in conjunction with incidental, trial-unique neutral pictures. In a surprise test phase, we found that participants could indeed remember the associated level of reward, as evidenced by accurate source memory for value and preferences to re-engage with rewarded objects. Further, in a separate experiment, we found that high-reward objects shown as primes before a gambling task increased financial risk taking. Neurally, re-exposure to objects in the test phase led to significant reactivation of reward-related patterns. Importantly, individual variability in the strength of reactivation predicted value memory performance. Our results provide a novel demonstration that affect-related neural patterns are reactivated during later experience. Reactivation of value information represents a mechanism by which memory can guide decision making.

  17. Elderly Care and Intrafamily Resource Allocation when Children Migrate *

    PubMed Central

    Antman, Francisca M.

    2012-01-01

    This paper considers the intrafamily allocation of elderly care in the context of international migration where migrant children may be able to provide financial assistance to their parents, but are unable to offer physical care. To investigate the interaction between siblings, I take a non-cooperative view of family decision-making and estimate best response functions for individual physical and financial contributions as a function of siblings’ contributions. I address the endogeneity of siblings’ contributions and individual migration decisions by using siblings’ characteristics as instrumental variables as well as models including family fixed effects. For both migrants and non-migrants, I find evidence that financial contributions function as strategic complements while siblings’ time contributions operate as strategic substitutes. This suggests that children’s contributions toward elderly care may be based on both strategic bequest and public good motivations. PMID:22518064

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

    SciTech Connect

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

    1992-11-01

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

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

    SciTech Connect

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

    1992-11-01

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

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

    PubMed

    Yu, Peter Paul

    2015-03-01

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

  1. Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

    NASA Astrophysics Data System (ADS)

    Ben Rabah, N.; Saddem, R.; Ben Hmida, F.; Carre-Menetrier, V.; Tagina, M.

    2017-01-01

    Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.

  2. Neurocognitive mechanisms underlying value-based decision-making: from core values to economic value

    PubMed Central

    Brosch, Tobias; Sander, David

    2013-01-01

    Value plays a central role in practically every aspect of human life that requires a decision: whether we choose between different consumer goods, whether we decide which person we marry or which political candidate gets our vote, we choose the option that has more value to us. Over the last decade, neuroeconomic research has mapped the neural substrates of economic value, revealing that activation in brain regions such as ventromedial prefrontal cortex (VMPFC), ventral striatum or posterior cingulate cortex reflects how much an individual values an option and which of several options he/she will choose. However, while great progress has been made exploring the mechanisms underlying concrete decisions, neuroeconomic research has been less concerned with the questions of why people value what they value, and why different people value different things. Social psychologists and sociologists have long been interested in core values, motivational constructs that are intrinsically linked to the self-schema and are used to guide actions and decisions across different situations and different time points. Core value may thus be an important determinant of individual differences in economic value computation and decision-making. Based on a review of recent neuroimaging studies investigating the neural representation of core values and their interactions with neural systems representing economic value, we outline a common framework that integrates the core value concept and neuroeconomic research on value-based decision-making. PMID:23898252

  3. Clinical-decision support based on medical literature: A complex network approach

    NASA Astrophysics Data System (ADS)

    Jiang, Jingchi; Zheng, Jichuan; Zhao, Chao; Su, Jia; Guan, Yi; Yu, Qiubin

    2016-10-01

    In making clinical decisions, clinicians often review medical literature to ensure the reliability of diagnosis, test, and treatment because the medical literature can answer clinical questions and assist clinicians making clinical decisions. Therefore, finding the appropriate literature is a critical problem for clinical-decision support (CDS). First, the present study employs search engines to retrieve relevant literature about patient records. However, the result of the traditional method is usually unsatisfactory. To improve the relevance of the retrieval result, a medical literature network (MLN) based on these retrieved papers is constructed. Then, we show that this MLN has small-world and scale-free properties of a complex network. According to the structural characteristics of the MLN, we adopt two methods to further identify the potential relevant literature in addition to the retrieved literature. By integrating these potential papers into the MLN, a more comprehensive MLN is built to answer the question of actual patient records. Furthermore, we propose a re-ranking model to sort all papers by relevance. We experimentally find that the re-ranking model can improve the normalized discounted cumulative gain of the results. As participants of the Text Retrieval Conference 2015, our clinical-decision method based on the MLN also yields higher scores than the medians in most topics and achieves the best scores for topics: #11 and #12. These research results indicate that our study can be used to effectively assist clinicians in making clinical decisions, and the MLN can facilitate the investigation of CDS.

  4. Context-Driven Decision Making in Network-Centric Operations: Agent-Based Intelligent Support

    DTIC Science & Technology

    2006-01-01

    SPIIRAS CKM Workshop (MIT, Cambridge, MA; January 24, 2006 Context-Driven Decision Making in Network-Centric Operations: Agent- Based Intelligent...Operations: Agent- Based Intelligent Support 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK...Enterprise and Multi-Agent Systems (Engineering and Physical Sciences Research Council, UK, 2003-2005) Ontology- Based New Order Code Generation for

  5. Social Area Indicators of Educational Need. A Study of the Use of Census Descriptions of School Neighbourhoods in Guiding Decisions Concerning the Allocation of Resources to Educationally Disadvantaged Schools in Australia. ACER Research Monograph No. 20.

    ERIC Educational Resources Information Center

    Ross, Kenneth N.

    The purpose of this study was to develop, validate, and describe indicators of educational disadvantage to be used in Australia to identify schools and students most in need of assistance from the Disadvantaged Schools Program. Initially, a detailed review was prepared of the resource allocation responses which have been made in Australia to the…

  6. Reward Allocation and Academic versus Social Orientation toward School.

    ERIC Educational Resources Information Center

    Peterson, Candida C.; Peterson, James L.

    1978-01-01

    Correlates 138 elementary school children's views about the purposes of school to their styles of reward allocation: academically motivated students allocated rewards equally to two hypothetical performers who had unequally helped a teacher perform a manual chore, while socially motivated children allocated rewards in an equity (performance-based)…

  7. Comparison of Ground-Based and Airborne Function Allocation Concepts for NextGen Using Human-In-The-Loop Simulations

    NASA Technical Reports Server (NTRS)

    Wing, David J.; Prevot, Thomas; Murdoch, Jennifer L.; Cabrall, Christopher D.; Homola, Jeffrey R.; Martin, Lynne H.; Mercer, Joey S.; Hoadley, Sherwood T.; Wilson, Sara R.; Hubbs, Clay E.; Chamberlain, James P.; Chartrand, Ryan C.; Consiglio, Maria C.; Palmer, Michael T.

    2010-01-01

    Investigation of function allocation for the Next Generation Air Transportation System is being conducted by the National Aeronautics and Space Administration (NASA). To provide insight on comparability of different function allocations for separation assurance, two human-in-the-loop simulation experiments were conducted on homogeneous airborne and ground-based approaches to four-dimensional trajectory-based operations, one referred to as ground-based automated separation assurance (groundbased) and the other as airborne trajectory management with self-separation (airborne). In the coordinated simulations at NASA s Ames and Langley Research Centers, controllers for the ground-based concept at Ames and pilots for the airborne concept at Langley managed the same traffic scenarios using the two different concepts. The common scenarios represented a significant increase in airspace demand over current operations. Using common independent variables, the simulations varied traffic density, scheduling constraints, and the timing of trajectory change events. Common metrics were collected to enable a comparison of relevant results. Where comparisons were possible, no substantial differences in performance or operator acceptability were observed. Mean schedule conformance and flight path deviation were considered adequate for both approaches. Conflict detection warning times and resolution times were mostly adequate, but certain conflict situations were detected too late to be resolved in a timely manner. This led to some situations in which safety was compromised and/or workload was rated as being unacceptable in both experiments. Operators acknowledged these issues in their responses and ratings but gave generally positive assessments of the respective concept and operations they experienced. Future studies will evaluate technical improvements and procedural enhancements to achieve the required level of safety and acceptability and will investigate the integration of

  8. Using decision aids in community-based primary care: A theory-driven evaluation with ethnically diverse patients

    PubMed Central

    Frosch, Dominick L.; Légaré, France; Mangione, Carol M.

    2010-01-01

    Objective To assess the effects of informational brochures and video decision aids about cancer screening on patient intention to engage in shared decision making and its predictors in a racially diverse sample. Methods Participants were recruited from 13 community-based primary care practices serving racially and ethnically diverse patients in predominately economically disadvantaged neighborhoods. Participants completed theory-based measures assessing attitudes, perceived social norms, self-efficacy and intentions for working with their physician to make a cancer screening decision after reviewing a brochure or video decision aid, but before seeing the physician. A post-questionnaire assessed screening decisions and participant knowledge. Results Participants who reviewed a video decision aid had higher knowledge and were more likely to want to be the primary decision-maker. They reported lower perceived social norms, self-efficacy and intentions to work with their physicians than participants who reviewed a brochure. Participants who decided against cancer screening reported lower intentions to work with their physician in making a decision and were less likely to report having spoken with their physician about screening. Conclusion Participants who opted against cancer screening after reviewing a brochure or decision aid were less likely to discuss their decision with their physician. The tendency toward autonomous decision-making was stronger among participants who reviewed a video decision aid. PMID:18771875

  9. Knowledge-based reasoning in the Paladin tactical decision generation system

    NASA Technical Reports Server (NTRS)

    Chappell, Alan R.

    1993-01-01

    A real-time tactical decision generation system for air combat engagements, Paladin, has been developed. A pilot's job in air combat includes tasks that are largely symbolic. These symbolic tasks are generally performed through the application of experience and training (i.e. knowledge) gathered over years of flying a fighter aircraft. Two such tasks, situation assessment and throttle control, are identified and broken out in Paladin to be handled by specialized knowledge based systems. Knowledge pertaining to these tasks is encoded into rule-bases to provide the foundation for decisions. Paladin uses a custom built inference engine and a partitioned rule-base structure to give these symbolic results in real-time. This paper provides an overview of knowledge-based reasoning systems as a subset of rule-based systems. The knowledge used by Paladin in generating results as well as the system design for real-time execution is discussed.

  10. Improving Child Outcomes with Data-Based Decision Making: Collecting Data

    ERIC Educational Resources Information Center

    Hojnoski, Robin L.; Gischlar, Karen L.; Missall, Kristen N.

    2009-01-01

    Collecting and graphing performance data are important parts of the educational process. Such procedures help educators, caregivers, and other important stakeholders make data-based decisions to accelerate child progress. With school-age children, collecting and graphing data have been associated with more frequent instructional changes to better…

  11. Effort-Based Decision Making: A Novel Approach for Assessing Motivation in Schizophrenia

    PubMed Central

    Green, Michael F.; Horan, William P.; Barch, Deanna M.; Gold, James M.

    2015-01-01

    Because negative symptoms, including motivational deficits, are a critical unmet need in schizophrenia, there are many ongoing efforts to develop new pharmacological and psychosocial interventions for these impairments. A common challenge of these studies involves how to evaluate and select optimal endpoints. Currently, all studies of negative symptoms in schizophrenia depend on ratings from clinician-conducted interviews. Effort-based decision-making tasks may provide a more objective, and perhaps more sensitive, endpoint for trials of motivational negative symptoms. These tasks assess how much effort a person is willing to exert for a given level of reward. This area has been well-studied with animal models of effort and motivation, and effort-based decision-making tasks have been adapted for use in humans. Very recently, several studies have examined physical and cognitive types of effort-based decision-making tasks in cross-sectional studies of schizophrenia, providing evidence for effort-related impairment in this illness. This article covers the theoretical background on effort-based decision-making tasks to provide a context for the subsequent articles in this theme section. In addition, we review the existing literature of studies using these tasks in schizophrenia, consider some practical challenges in adapting them for use in clinical trials in schizophrenia, and discuss interpretive challenges that are central to these types of tasks. PMID:26089350

  12. CaseNET: Teaching Decisions via a Web-Based Learning Environment.

    ERIC Educational Resources Information Center

    Bronack, Stephen C.; Kilbane, Clare R.

    CaseNET is a Web-based learning environment where teachers utilize the latest technologies to form communities of professionals who hone their decision making skills via "slice-of-life" cases. Students involved with CaseNET physically meet during regularly scheduled times at a designated site. Each site is staffed with an instructor, or team of…

  13. The Impact of School-Based Decision Making: A Case Study.

    ERIC Educational Resources Information Center

    Etheridge, Carol Plata; Hall, Mary Lee

    As a last resort to catalyze change in its innercity schools, Memphis City School District (Tennessee) designated seven schools as school-based decision-making (SBDM) sites in April 1989. In the same month, Memphis State University researchers were appointed official observers/researchers of SBDM implementation. Not to be confused with…

  14. Effort-Based Decision Making: A Novel Approach for Assessing Motivation in Schizophrenia.

    PubMed

    Green, Michael F; Horan, William P; Barch, Deanna M; Gold, James M

    2015-09-01

    Because negative symptoms, including motivational deficits, are a critical unmet need in schizophrenia, there are many ongoing efforts to develop new pharmacological and psychosocial interventions for these impairments. A common challenge of these studies involves how to evaluate and select optimal endpoints. Currently, all studies of negative symptoms in schizophrenia depend on ratings from clinician-conducted interviews. Effort-based decision-making tasks may provide a more objective, and perhaps more sensitive, endpoint for trials of motivational negative symptoms. These tasks assess how much effort a person is willing to exert for a given level of reward. This area has been well-studied with animal models of effort and motivation, and effort-based decision-making tasks have been adapted for use in humans. Very recently, several studies have examined physical and cognitive types of effort-based decision-making tasks in cross-sectional studies of schizophrenia, providing evidence for effort-related impairment in this illness. This article covers the theoretical background on effort-based decision-making tasks to provide a context for the subsequent articles in this theme section. In addition, we review the existing literature of studies using these tasks in schizophrenia, consider some practical challenges in adapting them for use in clinical trials in schizophrenia, and discuss interpretive challenges that are central to these types of tasks.

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

    DTIC Science & Technology

    2014-09-01

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

  16. Effects of an Intensive Data-Based Decision Making Intervention on Teacher Efficacy

    ERIC Educational Resources Information Center

    van der Scheer, Emmelien A.; Visscher, Adrie J.

    2016-01-01

    Despite the emphasis on data-based decision making (DBDM) in educational policy in several countries, evidence regarding the intended effect of improved student achievement is still scarce. The purpose of this study is to examine the effects of a DBDM intervention on teacher efficacy. This study incorporates an experimental longitudinal research…

  17. 40 CFR 761.298 - Decisions based on PCB concentration measurements resulting from sampling.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ..., PROCESSING, DISTRIBUTION IN COMMERCE, AND USE PROHIBITIONS Sampling To Verify Completion of Self-Implementing... measurements resulting from sampling. 761.298 Section 761.298 Protection of Environment ENVIRONMENTAL....61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a)...

  18. Scenario-based modeling for multiple allocation hub location problem under disruption risk: multiple cuts Benders decomposition approach

    NASA Astrophysics Data System (ADS)

    Yahyaei, Mohsen; Bashiri, Mahdi

    2017-03-01

    The hub location problem arises in a variety of domains such as transportation and telecommunication systems. In many real-world situations, hub facilities are subject to disruption. This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. In the proposed model, the number of scenarios grows exponentially with the number of facilities. To alleviate this issue, two approaches are applied simultaneously. The first approach is to apply sample average approximation to approximate the two stochastic problem via sampling. Then, by applying the multiple cuts Benders decomposition approach, computational performance is enhanced. Numerical studies show the effective performance of the SAA in terms of optimality gap for small problem instances with numerous scenarios. Moreover, performance of multi-cut Benders decomposition is assessed through comparison with the classic version and the computational results reveal the superiority of the multi-cut approach regarding the computational time and number of iterations.

  19. Community-Based Decision Making and Priority Setting Using the R Software: The Community Priority Index

    PubMed Central

    Salihu, Hamisu M.; Salinas-Miranda, Abraham A.; Paothong, Arnut; Wang, Wei; King, Lindsey M.

    2015-01-01

    This paper outlines how to compute community priority indices in the context of multicriteria decision making in community settings. A simple R function was developed and validated with community needs assessment data. Particularly, the first part of this paper briefly overviews the existing methods for priority setting and reviews the utility of a multicriteria decision-making approach for community-based prioritization. The second part illustrates how community priority indices can be calculated using the freely available R program to handle community data by showing the computational and mathematical steps of CPI (Community Priority Index) with bootstrapped 95% confidence intervals. PMID:25815045

  20. Analyses of S-Box in Image Encryption Applications Based on Fuzzy Decision Making Criterion

    NASA Astrophysics Data System (ADS)

    Rehman, Inayatur; Shah, Tariq; Hussain, Iqtadar

    2014-06-01

    In this manuscript, we put forward a standard based on fuzzy decision making criterion to examine the current substitution boxes and study their strengths and weaknesses in order to decide their appropriateness in image encryption applications. The proposed standard utilizes the results of correlation analysis, entropy analysis, contrast analysis, homogeneity analysis, energy analysis, and mean of absolute deviation analysis. These analyses are applied to well-known substitution boxes. The outcome of these analyses are additional observed and a fuzzy soft set decision making criterion is used to decide the suitability of an S-box to image encryption applications.

  1. Effect of Social Influence on Effort-Allocation for Monetary Rewards

    PubMed Central

    Gilman, Jodi M.; Treadway, Michael T.; Curran, Max T.; Calderon, Vanessa; Evins, A. Eden

    2015-01-01

    Though decades of research have shown that people are highly influenced by peers, few studies have directly assessed how the value of social conformity is weighed against other types of costs and benefits. Using an effort-based decision-making paradigm with a novel social influence manipulation, we measured how social influence affected individuals’ decisions to allocate effort for monetary rewards during trials with either high or low probability of receiving a reward. We found that information about the effort-allocation of peers modulated participant choices, specifically during conditions of low probability of obtaining a reward. This suggests that peer influence affects effort-based choices to obtain rewards especially under conditions of risk. This study provides evidence that people value social conformity in addition to other costs and benefits when allocating effort, and suggests that neuroeconomic studies that assess trade-offs between effort and reward should consider social environment as a factor that can influence decision-making. PMID:25961725

  2. How do people learn to allocate resources? Comparing two learning theories.

    PubMed

    Rieskamp, Jörg; Busemeyer, Jerome R; Laine, Tei

    2003-11-01

    How do people learn to allocate resources? To answer this question, 2 major learning models are compared, each incorporating different learning principles. One is a global search model, which assumes that allocations are made probabilistically on the basis of expectations formed through the entire history of past decisions. The 2nd is a local adaptation model, which assumes that allocations are made by comparing the present decision with the most successful decision up to that point, ignoring all other past decisions. In 2 studies, participants repeatedly allocated a capital resource to 3 financial assets. Substantial learning effects occurred, although the optimal allocation was often not found. From the calibrated models of Study 1, a priori predictions were derived and tested in Study 2. This generalization test shows that the local adaptation model provides a better account of learning in resource allocations than the global search model.

  3. Timed colored Petri nets and fuzzy-set-based model for decision making

    NASA Astrophysics Data System (ADS)

    Scopel Simoes, Marcos A.; Barretto, Marcos R. P.

    2000-10-01

    This work proposes the use of Timed Colored Petri nets as a formal base to a decision making tool for applications in industrial productive processes planning and programming. The Timed Colored Petri net is responsible for the transition of states in the decision process, establishing in time the use of resources and of heuristics that correspond to the more important managerial and operational actions for the planning activities and programming of the productive processes of an industrial plant. To negotiate with the uncertainties involved in a decision process, that in general takes care of the responsible specialist's knowledge for the routines involved in the productive system, we make use of the theory of fuzzy sets to suggest decisions logically consistent that obtain a viable solution just leading the viable states of the decision tree, that, in this case, is confused with the occurrence graph of the Petri net. As application example to the proposed model, we used a production system characterized by a port plant, whose model and simulation results are described at the end of this work.

  4. Algorithms for optimal redundancy allocation

    SciTech Connect

    Vandenkieboom, J.; Youngblood, R.

    1993-01-01

    Heuristic and exact methods for solving the redundancy allocation problem are compared to an approach based on genetic algorithms. The various methods are applied to the bridge problem, which has been used as a benchmark in earlier work on optimization methods. Comparisons are presented in terms of the best configuration found by each method, and the computation effort which was necessary in order to find it.

  5. Intelligent decision making in disassembly process based on fuzzy reasoning petri nets.

    PubMed

    Gao, Meimei; Zhou, MengChu; Tang, Ying

    2004-10-01

    Practical disassembly process planning is extremely important for efficient material recycling and components reuse. The research work for the process planning in literature focuses on the generation of optimal sequences based on the predictive information of products. The used products, unfortunately, exhibit high uncertainty since products may experience very different conditions during their use stage. The indeterminate characteristics associated to used products often makes the predetermined plan unrealistic. Their disassembly process has to be decided dynamically adaptive to the products' specific status. To be able to deal with uncertainty in a dynamic decision making process, this paper presents a fuzzy reasoning Petri net (FRPN) model to represent related decision making rules in disassembly process. Using the proposed fuzzy reasoning algorithm based on the FRPN model, the multicriterion disassembly rules can be considered in the parallel way to make the decision automatically and quickly. Instead of producing the disassembly sequences before disassembling a whole product, the proposed method makes intelligent decisions based on dynamically updated status of components in the product at each disassembly step. Therefore, it is adaptive to the changes that arise during the process. Finally, an example is used to illustrate the application of the proposed methodology.

  6. An Approach for Web Service Selection Based on Confidence Level of Decision Maker

    PubMed Central

    Khezrian, Mojtaba; Jahan, Ali; Wan Kadir, Wan Mohd Nasir; Ibrahim, Suhaimi

    2014-01-01

    Web services today are among the most widely used groups for Service Oriented Architecture (SOA). Service selection is one of the most significant current discussions in SOA, which evaluates discovered services and chooses the best candidate from them. Although a majority of service selection techniques apply Quality of Service (QoS), the behaviour of QoS-based service selection leads to service selection problems in Multi-Criteria Decision Making (MCDM). In the existing works, the confidence level of decision makers is neglected and does not consider their expertise in assessing Web services. In this paper, we employ the VIKOR (VIšekriterijumskoKOmpromisnoRangiranje) method, which is absent in the literature for service selection, but is well-known in other research. We propose a QoS-based approach that deals with service selection by applying VIKOR with improvement of features. This research determines the weights of criteria based on user preference and accounts for the confidence level of decision makers. The proposed approach is illustrated by an example in order to demonstrate and validate the model. The results of this research may facilitate service consumers to attain a more efficient decision when selecting the appropriate service. PMID:24897426

  7. Application of a web-based Decision Support System in risk management

    NASA Astrophysics Data System (ADS)

    Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

    2013-04-01

    Increasingly, risk information is widely available with the help of advanced technologies such as earth observation satellites, global positioning technologies, coupled with hazard modeling and analysis, and geographical information systems (GIS). Even though it exists, no effort will be put into action if it is not properly presented to the decision makers. These information need to be communicated clearly and show its usefulness so that people can make better informed decision. Therefore, communicating available risk information has become an important challenge and decision support systems have been one of the significant approaches which can help not only in presenting risk information to the decision makers but also in making efficient decisions while reducing human resources and time needed. In this study, the conceptual framework of an internet-based decision support system is presented to highlight its importance role in risk management framework and how it can be applied in case study areas chosen. The main purpose of the proposed system is to facilitate the available risk information in risk reduction by taking into account of the changes in climate, land use and socio-economic along with the risk scenarios. It allows the users to formulate, compare and select risk reduction scenarios (mainly for floods and landslides) through an enhanced participatory platform with diverse stakeholders' involvement in the decision making process. It is based on the three-tier (client-server) architecture which integrates web-GIS plus DSS functionalities together with cost benefit analysis and other supporting tools. Embedding web-GIS provides its end users to make better planning and informed decisions referenced to a geographical location, which is the one of the essential factors in disaster risk reduction programs. Different risk reduction measures of a specific area (local scale) will be evaluated using this web-GIS tool, available risk scenarios obtained from

  8. Towards case-based medical learning in radiological decision making using content-based image retrieval

    PubMed Central

    2011-01-01

    Background Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. Methods We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. Results We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. Conclusions The IBCR-RE paradigm incorporates a

  9. Improving Hospital-Wide Early Resource Allocation through Machine Learning.

    PubMed

    Gartner, Daniel; Padman, Rema

    2015-01-01

    The objective of this paper is to evaluate the extent to which early determination of diagnosis-related groups (DRGs) can be used for better allocation of scarce hospital resources. When elective patients seek admission, the true DRG, currently determined only at discharge, is unknown. We approach the problem of early DRG determination in three stages: (1) test how much a Naïve Bayes classifier can improve classification accuracy as compared to a hospital's current approach; (2) develop a statistical program that makes admission and scheduling decisions based on the patients' clincial pathways and scarce hospital resources; and (3) feed the DRG as classified by the Naïve Bayes classifier and the hospitals' baseline approach into the model (which we evaluate in simulation). Our results reveal that the DRG grouper performs poorly in classifying the DRG correctly before admission while the Naïve Bayes approach substantially improves the classification task. The results from the connection of the classification method with the mathematical program also reveal that resource allocation decisions can be more effective and efficient with the hybrid approach.

  10. Patient preferences, knowledge and beliefs about kidney allocation: qualitative findings from the UK-wide ATTOM programme

    PubMed Central

    Cinnirella, Marco; Bayfield, Janet; Wu, Diana; Draper, Heather; Johnson, Rachel J; Tomson, Charles R V; Forsythe, John L R; Metcalfe, Wendy; Fogarty, Damian; Roderick, Paul; Ravanan, Rommel; Oniscu, Gabriel C; Watson, Christopher J E; Bradley, J Andrew; Bradley, Clare

    2017-01-01

    Objective To explore how patients who are wait-listed for or who have received a kidney transplant understand the current UK kidney allocation system, and their views on ways to allocate kidneys in the future. Design Qualitative study using semistructured interviews and thematic analysis based on a pragmatic approach. Participants 10 deceased-donor kidney transplant recipients, 10 live-donor kidney transplant recipients, 12 participants currently wait-listed for a kidney transplant and 4 participants whose kidney transplant failed. Setting Semistructured telephone interviews conducted with participants in their own homes across the UK. Results Three main themes were identified: uncertainty of knowledge of the allocation scheme; evaluation of the system and participant suggestions for future allocation schemes. Most participants identified human leucocyte anitgen matching as a factor in determining kidney allocation, but were often uncertain of the accuracy of their knowledge. In the absence of information that would allow a full assessment, the majority of participants consider that the current system is effective. A minority of participants were concerned about the perceived lack of transparency of the general decision-making processes within the scheme. Most participants felt that people who are younger and those better matched to the donor kidney should be prioritised for kidney allocation, but in contrast to the current scheme, less priority was considered appropriate for longer waiting patients. Some non-medical themes were also discussed, such as whether parents of dependent children should be prioritised for allocation, and whether patients with substance abuse problems be deprioritised. Conclusions Our participants held differing views about the most important factors for kidney allocation, some of which were in contrast to the current scheme. Patient participation in reviewing future allocation policies will provide insight as to what is considered

  11. Overhead-Aware-Best-Fit (OABF) Resource Allocation Algorithm for Minimizing VM Launching Overhead

    SciTech Connect

    Wu, Hao; Garzoglio, Gabriele; Ren, Shangping; Timm, Steven; Noh, Seo Young

    2014-11-11

    FermiCloud is a private cloud developed in Fermi National Accelerator Laboratory to provide elastic and on-demand resources for different scientific research experiments. The design goal of the FermiCloud is to automatically allocate resources for different scientific applications so that the QoS required by these applications is met and the operational cost of the FermiCloud is minimized. Our earlier research shows that VM launching overhead has large variations. If such variations are not taken into consideration when making resource allocation decisions, it may lead to poor performance and resource waste. In this paper, we show how we may use an VM launching overhead reference model to minimize VM launching overhead. In particular, we first present a training algorithm that automatically tunes a given refer- ence model to accurately reflect FermiCloud environment. Based on the tuned reference model for virtual machine launching overhead, we develop an overhead-aware-best-fit resource allocation algorithm that decides where and when to allocate resources so that the average virtual machine launching overhead is minimized. The experimental results indicate that the developed overhead-aware-best-fit resource allocation algorithm can significantly improved the VM launching time when large number of VMs are simultaneously launched.

  12. A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks

    PubMed Central

    Zhang, Shukui; Chen, Hao; Zhu, Qiaoming

    2014-01-01

    The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic. PMID:25136690

  13. Devaluation and sequential decisions: linking goal-directed and model-based behavior.

    PubMed

    Friedel, Eva; Koch, Stefan P; Wendt, Jean; Heinz, Andreas; Deserno, Lorenz; Schlagenhauf, Florian

    2014-01-01

    In experimental psychology different experiments have been developed to assess goal-directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans.

  14. Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges

    NASA Astrophysics Data System (ADS)

    Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu

    2016-09-01

    In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.

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

    NASA Technical Reports Server (NTRS)

    Lewis, Kemper; Mistree, Farrokh

    1995-01-01

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

  16. Rural tourism spatial distribution based on multi-criteria decision analysis and GIS

    NASA Astrophysics Data System (ADS)

    Zhang, Hongxian; Yang, Qingsheng

    2008-10-01

    To study spatial distribution of rural tourism can provide scientific decision basis for developing rural economics. Traditional ways of tourism spatial distribution have some limitations in quantifying priority locations of tourism development on small units. They can only produce the overall tourism distribution locations and whether locations are suitable to tourism development simply while the tourism develop ranking with different decision objectives should be considered. This paper presents a way to find ranking of location of rural tourism development in spatial by integrating multi-criteria decision analysis (MCDA) and geography information system (GIS). In order to develop country economics with inconvenient transportation, undeveloped economy and better tourism resource, these locations should be firstly develop rural tourism. Based on this objective, the tourism develop priority utility of each town is calculated with MCDA and GIS. Towns which should be first develop rural tourism can be selected with higher tourism develop priority utility. The method is used to find ranking of location of rural tourism in Ningbo City successfully. The result shows that MCDA is an effective way for distribution rural tourism in spatial based on special decision objectives and rural tourism can promote economic development.

  17. Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks

    PubMed Central

    Zhang, Wenyu; Zhang, Zhenjiang

    2015-01-01

    Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399

  18. A Cumulative Energy Demand indicator (CED), life cycle based, for industrial waste management decision making

    SciTech Connect

    Puig, Rita; Fullana-i-Palmer, Pere; Bala, Alba

    2013-12-15

    Highlights: • We developed a methodology useful to environmentally compare industrial waste management options. • The methodology uses a Net Energy Demand indicator which is life cycle based. • The method was simplified to be widely used, thus avoiding cost driven decisions. • This methodology is useful for governments to promote the best environmental options. • This methodology can be widely used by other countries or regions around the world. - Abstract: Life cycle thinking is a good approach to be used for environmental decision-support, although the complexity of the Life Cycle Assessment (LCA) studies sometimes prevents their wide use. The purpose of this paper is to show how LCA methodology can be simplified to be more useful for certain applications. In order to improve waste management in Catalonia (Spain), a Cumulative Energy Demand indicator (LCA-based) has been used to obtain four mathematical models to help the government in the decision of preventing or allowing a specific waste from going out of the borders. The conceptual equations and all the subsequent developments and assumptions made to obtain the simplified models are presented. One of the four models is discussed in detail, presenting the final simplified equation to be subsequently used by the government in decision making. The resulting model has been found to be scientifically robust, simple to implement and, above all, fulfilling its purpose: the limitation of waste transport out of Catalonia unless the waste recovery operations are significantly better and justify this transport.

  19. Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks.

    PubMed

    Zhang, Wenyu; Zhang, Zhenjiang

    2015-08-19

    Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier's training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster's combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule.

  20. An Agent-Based Model of Farmer Decision Making in Jordan

    NASA Astrophysics Data System (ADS)

    Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

    2016-04-01

    We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

  1. A Preliminary Study in Applying the Function-Based Intervention Decision Model in Consultation to Increase Treatment Integrity

    ERIC Educational Resources Information Center

    Gann, Candace J.; Kunnavatana, S. Shanun

    2016-01-01

    This preliminary study investigated the use of the Function-Based Intervention Decision Model (Decision Model; Umbreit, Ferro, Liaupsin, & Lane, 2007) to improve teacher treatment integrity for a function-based classroom management plan. The participants were a special education teacher and three elementary-age students receiving special…

  2. Parameter uncertainty-based pattern identification and optimization for robust decision making on watershed load reduction

    NASA Astrophysics Data System (ADS)

    Jiang, Qingsong; Su, Han; Liu, Yong; Zou, Rui; Ye, Rui; Guo, Huaicheng

    2017-04-01

    Nutrients loading reduction in watershed is essential for lake restoration from eutrophication. The efficient and optimal decision-making on loading reduction is generally based on water quality modeling and the quantitative identification of nutrient sources at the watershed scale. The modeling process is influenced inevitably by inherent uncertainties, especially by uncertain parameters due to equifinality. Therefore, the emerging question is: if there is parameter uncertainty, how to ensure the robustness of the optimal decisions? Based on simulation-optimization models, an integrated approach of pattern identification and analysis of robustness was proposed in this study that focuses on the impact of parameter uncertainty in water quality modeling. Here the pattern represents the discernable regularity of solutions for load reduction under multiple parameter sets. Pattern identification is achieved by using a hybrid clustering analysis (i.e., Ward-Hierarchical and K-means), which was flexible and efficient in analyzing Lake Bali near the Yangtze River in China. The results demonstrated that urban domestic nutrient load is the most potential source that should be reduced, and there are two patterns for Total Nitrogen (TN) reduction and three patterns for Total Phosphorus (TP) reduction. The patterns indicated different total reduction of nutrient loads, which reflect diverse decision preferences. The robust solution was identified by the highest accomplishment with the water quality at monitoring stations that were improved uniformly with this solution. We conducted a process analysis of robust decision-making that was based on pattern identification and uncertainty, which provides effective support for decision-making with preference under uncertainty.

  3. Effectiveness of a Theoretically-Based Judgment and Decision Making Intervention for Adolescents

    PubMed Central

    Knight, Danica K.; Dansereau, Donald F.; Becan, Jennifer E.; Rowan, Grace A.; Flynn, Patrick M.

    2014-01-01

    Although adolescents demonstrate capacity for rational decision making, their tendency to be impulsive, place emphasis on peers, and ignore potential consequences of their actions often translates into higher risk-taking including drug use, illegal activity, and physical harm. Problems with judgment and decision making contribute to risky behavior and are core issues for youth in treatment. Based on theoretical and empirical advances in cognitive science, the Treatment Readiness and Induction Program (TRIP) represents a curriculum-based decision making intervention that can be easily inserted into a variety of content-oriented modalities as well as administered as a separate therapeutic course. The current study examined the effectiveness of TRIP for promoting better judgment among 519 adolescents (37% female; primarily Hispanic and Caucasian) in residential substance abuse treatment. Change over time in decision making and premeditation (i.e., thinking before acting) was compared among youth receiving standard operating practice (n = 281) versus those receiving standard practice plus TRIP (n = 238). Change in TRIP-specific content knowledge was examined among clients receiving TRIP. Premeditation improved among youth in both groups; TRIP clients showed greater improvement in decision making. TRIP clients also reported significant increases over time in self-awareness, positive-focused thinking (e.g., positive self-talk, goal setting), and recognition of the negative effects of drug use. While both genders showed significant improvement, males showed greater gains in metacognitive strategies (i.e., awareness of one’s own cognitive process) and recognition of the negative effects of drug use. These results suggest that efforts to teach core thinking strategies and apply/practice them through independent intervention modules may benefit adolescents when used in conjunction with content-based programs designed to change problematic behaviors. PMID:24760288

  4. Effectiveness of a theoretically-based judgment and decision making intervention for adolescents.

    PubMed

    Knight, Danica K; Dansereau, Donald F; Becan, Jennifer E; Rowan, Grace A; Flynn, Patrick M

    2015-05-01

    Although adolescents demonstrate capacity for rational decision making, their tendency to be impulsive, place emphasis on peers, and ignore potential consequences of their actions often translates into higher risk-taking including drug use, illegal activity, and physical harm. Problems with judgment and decision making contribute to risky behavior and are core issues for youth in treatment. Based on theoretical and empirical advances in cognitive science, the Treatment Readiness and Induction Program (TRIP) represents a curriculum-based decision making intervention that can be easily inserted into a variety of content-oriented modalities as well as administered as a separate therapeutic course. The current study examined the effectiveness of TRIP for promoting better judgment among 519 adolescents (37 % female; primarily Hispanic and Caucasian) in residential substance abuse treatment. Change over time in decision making and premeditation (i.e., thinking before acting) was compared among youth receiving standard operating practice (n = 281) versus those receiving standard practice plus TRIP (n = 238). Change in TRIP-specific content knowledge was examined among clients receiving TRIP. Premeditation improved among youth in both groups; TRIP clients showed greater improvement in decision making. TRIP clients also reported significant increases over time in self-awareness, positive-focused thinking (e.g., positive self-talk, goal setting), and recognition of the negative effects of drug use. While both genders showed significant improvement, males showed greater gains in metacognitive strategies (i.e., awareness of one's own cognitive process) and recognition of the negative effects of drug use. These results suggest that efforts to teach core thinking strategies and apply/practice them through independent intervention modules may benefit adolescents when used in conjunction with content-based programs designed to change problematic behaviors.

  5. Enhancing the credibility of decisions based on scientific conclusions: transparency is imperative.

    PubMed

    Schreider, Jay; Barrow, Craig; Birchfield, Norman; Dearfield, Kerry; Devlin, Dennis; Henry, Sara; Kramer, Melissa; Schappelle, Seema; Solomon, Keith; Weed, Douglas L; Embry, Michelle R

    2010-07-01

    Transparency and documentation of the decision process are at the core of a credible risk assessment and, in addition, are essential in the presentation of a weight of evidence (WoE)-based approach. Lack of confidence in the risk assessment process (as the basis for a risk management decision), beginning with evaluation of raw data and continuing through the risk decision process, is largely because of issues surrounding transparency. There is a critical need to implement greater transparency throughout the risk assessment process, and although doing so will not guarantee the correctness of the risk assessment or that all risk assessors come up with the same conclusions, it will provide essential information on how a particular conclusion or decision was made, thereby increasing confidence in the conclusions. Recognizing this issue, the International Life Sciences Institute Health and Environmental Sciences Institute convened a multisector committee tasked with discussing this issue and examining existing guidance and recommendations related to transparency in risk assessment. The committee concluded that transparency is inextricably linked to credibility: credibility of the data, credibility of the risk assessment process, and credibility of the resulting decision making. To increase this credibility, existing guidance concerning criteria elements of transparency related to the risk assessment process must be more widely disseminated and applied, and raw data for studies used in human health and environmental risk assessment must be more widely available. Finally, the decision-making process in risk management must be better documented and a guidance framework established for both the process itself and its communication to the public.

  6. Data-based Decision-making: Teachers' Comprehension of Curriculum-based Measurement Progress-monitoring Graphs

    ERIC Educational Resources Information Center

    van den Bosch, Roxette M.; Espin, Christine A.; Chung, Siuman; Saab, Nadira

    2017-01-01

    Teachers have difficulty using data from Curriculum-based Measurement (CBM) progress graphs of students with learning difficulties for instructional decision-making. As a first step in unraveling those difficulties, we studied teachers' comprehension of CBM graphs. Using think-aloud methodology, we examined 23 teachers' ability to…

  7. Ag2S atomic switch-based `tug of war' for decision making

    NASA Astrophysics Data System (ADS)

    Lutz, C.; Hasegawa, T.; Chikyow, T.

    2016-07-01

    For a computing process such as making a decision, a software controlled chip of several transistors is necessary. Inspired by how a single cell amoeba decides its movements, the theoretical `tug of war' computing model was proposed but not yet implemented in an analogue device suitable for integrated circuits. Based on this model, we now developed a new electronic element for decision making processes, which will have no need for prior programming. The devices are based on the growth and shrinkage of Ag filaments in α-Ag2+δS gap-type atomic switches. Here we present the adapted device design and the new materials. We demonstrate the basic `tug of war' operation by IV-measurements and Scanning Electron Microscopy (SEM) observation. These devices could be the base for a CMOS-free new computer architecture.For a computing process such as making a decision, a software controlled chip of several transistors is necessary. Inspired by how a single cell amoeba decides its movements, the theoretical `tug of war' computing model was proposed but not yet implemented in an analogue device suitable for integrated circuits. Based on this model, we now developed a new electronic element for decision making processes, which will have no need for prior programming. The devices are based on the growth and shrinkage of Ag filaments in α-Ag2+δS gap-type atomic switches. Here we present the adapted device design and the new materials. We demonstrate the basic `tug of war' operation by IV-measurements and Scanning Electron Microscopy (SEM) observation. These devices could be the base for a CMOS-free new computer architecture. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00690f

  8. Comparison of Airborne and Ground-Based Function Allocation Concepts for NextGen Using Human-In-The-Loop Simulations

    NASA Technical Reports Server (NTRS)

    Wing, David J.; Prevot, Thomas; Murdoch, Jennifer L.; Cabrall, Christopher D.; Homola, Jeffrey R.; Martin, Lynne H.; Mercer, Joey S.; Hoadley, Sherwood T.; Wilson, Sara R.; Hubbs, Clay E.; Chamberlain, James P.; Chartrand, Ryan C.; Consiglio, Maria C.; Palmer, Michael T.

    2010-01-01

    This paper presents an air/ground functional allocation experiment conducted by the National Aeronautics and Space Administration (NASA) using two human-in-the-Loop simulations to compare airborne and ground-based approaches to NextGen separation assurance. The approaches under investigation are two trajectory-based four-dimensional (4D) concepts; one referred to as "airborne trajectory management with self-separation" (airborne) the other as "ground-based automated separation assurance" (ground-based). In coordinated simulations at NASA's Ames and Langley Research Centers, the primary operational participants -controllers for the ground-based concept and pilots for the airborne concept - manage the same traffic scenario using the two different 4D concepts. The common scenarios are anchored in traffic problems that require a significant increase in airspace capacity - on average, double, and in some local areas, close to 250% over current day levels - in order to enable aircraft to safely and efficiently traverse the test airspace. The simulations vary common independent variables such as traffic density, sequencing and scheduling constraints, and timing of trajectory change events. A set of common metrics is collected to enable a direct comparison of relevant results. The simulations will be conducted in spring 2010. If accepted, this paper will be the first publication of the experimental approach and early results. An initial comparison of safety and efficiency as well as operator acceptability under the two concepts is expected.

  9. Value-based attentional capture influences context-dependent decision-making.

    PubMed

    Itthipuripat, Sirawaj; Cha, Kexin; Rangsipat, Napat; Serences, John T

    2015-07-01

    Normative theories posit that value-based decision-making is context independent. However, decisions between two high-value options can be suboptimally biased by the introduction of a third low-value option. This context-dependent modulation is consistent with the divisive normalization of the value of each stimulus by the total value of all stimuli. In addition, an independent line of research demonstrates that pairing a stimulus with a high-value outcome can lead to attentional capture that can mediate the efficiency of visual information processing. Here we tested the hypothesis that value-based attentional capture interacts with value-based normalization to influence the optimality of decision-making. We used a binary-choice paradigm in which observers selected between two targets and the color of each target indicated the magnitude of their reward potential. Observers also had to simultaneously ignore a task-irrelevant distractor rendered in a color that was previously associated with a specific reward magnitude. When the color of the task-irrelevant distractor was previously associated with a high reward, observers responded more slowly and less optimally. Moreover, as the learned value of the distractor increased, electrophysiological data revealed an attenuation of the lateralized N1 and N2Pc responses evoked by the relevant choice stimuli and an attenuation of the late positive deflection (LPD). Collectively, these behavioral and electrophysiological data suggest that value-based attentional capture and value-based normalization jointly mediate the influence of context on free-choice decision-making.

  10. Value-based attentional capture influences context-dependent decision-making

    PubMed Central

    Cha, Kexin; Rangsipat, Napat; Serences, John T.

    2015-01-01

    Normative theories posit that value-based decision-making is context independent. However, decisions between two high-value options can be suboptimally biased by the introduction of a third low-value option. This context-dependent modulation is consistent with the divisive normalization of the value of each stimulus by the total value of all stimuli. In addition, an independent line of research demonstrates that pairing a stimulus with a high-value outcome can lead to attentional capture that can mediate the efficiency of visual information processing. Here we tested the hypothesis that value-based attentional capture interacts with value-based normalization to influence the optimality of decision-making. We used a binary-choice paradigm in which observers selected between two targets and the color of each target indicated the magnitude of their reward potential. Observers also had to simultaneously ignore a task-irrelevant distractor rendered in a color that was previously associated with a specific reward magnitude. When the color of the task-irrelevant distractor was previously associated with a high reward, observers responded more slowly and less optimally. Moreover, as the learned value of the distractor increased, electrophysiological data revealed an attenuation of the lateralized N1 and N2Pc responses evoked by the relevant choice stimuli and an attenuation of the late positive deflection (LPD). Collectively, these behavioral and electrophysiological data suggest that value-based attentional capture and value-based normalization jointly mediate the influence of context on free-choice decision-making. PMID:25995350

  11. Primary motor cortex contributes to the implementation of implicit value-based rules during motor decisions.

    PubMed

    Derosiere, Gerard; Zénon, Alexandre; Alamia, Andrea; Duque, Julie

    2017-02-01

    In the present study, we investigated the functional contribution of the human primary motor cortex (M1) to motor decisions. Continuous theta burst stimulation (cTBS) was used to alter M1 activity while participants performed a decision-making task in which the reward associated with the subjects' responses (right hand finger movements) depended on explicit and implicit value-based rules. Subjects performed the task over two consecutive days and cTBS occurred in the middle of Day 2, once the subjects were just about to implement implicit rules, in addition to the explicit instructions, to choose their responses, as evident in the control group (cTBS over the right somatosensory cortex). Interestingly, cTBS over the left M1 prevented subjects from implementing the implicit value-based rule while its implementation was enhanced in the group receiving cTBS over the right M1. Hence, cTBS had opposite effects depending on whether it was applied on the contralateral or ipsilateral M1. The use of the explicit value-based rule was unaffected by cTBS in the three groups of subject. Overall, the present study provides evidence for a functional contribution of M1 to the implementation of freshly acquired implicit rules, possibly through its involvement in a cortico-subcortical network controlling value-based motor decisions.

  12. Collaborative Resource Allocation

    NASA Technical Reports Server (NTRS)

    Wang, Yeou-Fang; Wax, Allan; Lam, Raymond; Baldwin, John; Borden, Chester

    2007-01-01

    Collaborative Resource Allocation Networking Environment (CRANE) Version 0.5 is a prototype created to prove the newest concept of using a distributed environment to schedule Deep Space Network (DSN) antenna times in a collaborative fashion. This program is for all space-flight and terrestrial science project users and DSN schedulers to perform scheduling activities and conflict resolution, both synchronously and asynchronously. Project schedulers can, for the first time, participate directly in scheduling their tracking times into the official DSN schedule, and negotiate directly with other projects in an integrated scheduling system. A master schedule covers long-range, mid-range, near-real-time, and real-time scheduling time frames all in one, rather than the current method of separate functions that are supported by different processes and tools. CRANE also provides private workspaces (both dynamic and static), data sharing, scenario management, user control, rapid messaging (based on Java Message Service), data/time synchronization, workflow management, notification (including emails), conflict checking, and a linkage to a schedule generation engine. The data structure with corresponding database design combines object trees with multiple associated mortal instances and relational database to provide unprecedented traceability and simplify the existing DSN XML schedule representation. These technologies are used to provide traceability, schedule negotiation, conflict resolution, and load forecasting from real-time operations to long-range loading analysis up to 20 years in the future. CRANE includes a database, a stored procedure layer, an agent-based middle tier, a Web service wrapper, a Windows Integrated Analysis Environment (IAE), a Java application, and a Web page interface.

  13. Interpatch foraging in honeybees-rational decision making at secondary hubs based upon time and motivation.

    PubMed

    Najera, Daniel A; McCullough, Erin L; Jander, Rudolf

    2012-11-01

    For honeybees, Apis mellifera, the hive has been well known to function as a primary decision-making hub, a place from which foragers decide among various directions, distances, and times of day to forage efficiently. Whether foraging honeybees can make similarly complex navigational decisions from locations away from the hive is unknown. To examine whether or not such secondary decision-making hubs exist, we trained bees to forage at four different locations. Specifically, we trained honeybees to first forage to a distal site "CT" 100 m away from the hive; if food was present, they fed and then chose to go home. If food was not present, the honeybees were trained to forage to three auxiliary sites, each at a different time of the day: A in the morning, B at noon, and C in the afternoon. The foragers learned to check site CT for food first and then efficiently depart to the correct location based upon the time of day if there was no food at site CT. Thus, the honeybees were able to cognitively map motivation, time, and five different locations (Hive, CT, A, B, and C) in two spatial dimensions; these are the contents of the cognitive map used by the honeybees here. While at site CT, we verified that the honeybees could choose between 4 different directions (to A, B, C, and the Hive) and thus label it as a secondary decision-making hub. The observed decision making uncovered here is inferred to constitute genuine logical operations, involving a branched structure, based upon the premises of motivational state, and spatiotemporal knowledge.

  14. Location-allocation models and new solution methodologies in telecommunication networks

    NASA Astrophysics Data System (ADS)

    Dinu, S.; Ciucur, V.

    2016-08-01

    When designing a telecommunications network topology, three types of interdependent decisions are combined: location, allocation and routing, which are expressed by the following design considerations: how many interconnection devices - consolidation points/concentrators should be used and where should they be located; how to allocate terminal nodes to concentrators; how should the voice, video or data traffic be routed and what transmission links (capacitated or not) should be built into the network. Including these three components of the decision into a single model generates a problem whose complexity makes it difficult to solve. A first method to address the overall problem is the sequential one, whereby the first step deals with the location-allocation problem and based on this solution the subsequent sub-problem (routing the network traffic) shall be solved. The issue of location and allocation in a telecommunications network, called "The capacitated concentrator location- allocation - CCLA problem" is based on one of the general location models on a network in which clients/demand nodes are the terminals and facilities are the concentrators. Like in a location model, each client node has a demand traffic, which must be served, and the facilities can serve these demands within their capacity limit. In this study, the CCLA problem is modeled as a single-source capacitated location-allocation model whose optimization objective is to determine the minimum network cost consisting of fixed costs for establishing the locations of concentrators, costs for operating concentrators and costs for allocating terminals to concentrators. The problem is known as a difficult combinatorial optimization problem for which powerful algorithms are required. Our approach proposes a Fuzzy Genetic Algorithm combined with a local search procedure to calculate the optimal values of the location and allocation variables. To confirm the efficiency of the proposed algorithm with respect

  15. Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback

    PubMed Central

    Whitney, Paul; Hinson, John M.; Jackson, Melinda L.; Van Dongen, Hans P.A.

    2015-01-01

    Study Objectives: To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Design: Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Setting: Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Subjects: Twenty-six subjects (22–40 y of age; 10 women). Interventions: Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Results: Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Conclusions: Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback

  16. Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data.

    PubMed

    Metting, Esther I; In 't Veen, Johannes C C M; Dekhuijzen, P N Richard; van Heijst, Ellen; Kocks, Janwillem W H; Muilwijk-Kroes, Jacqueline B; Chavannes, Niels H; van der Molen, Thys

    2016-01-01

    The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years) with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD) service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215). Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma-COPD overlap syndrome (ACOS) patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%). Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool.

  17. A Z-number-based decision making procedure with ranking fuzzy numbers method

    NASA Astrophysics Data System (ADS)

    Mohamad, Daud; Shaharani, Saidatull Akma; Kamis, Nor Hanimah

    2014-12-01

    The theory of fuzzy set has been in the limelight of various applications in decision making problems due to its usefulness in portraying human perception and subjectivity. Generally, the evaluation in the decision making process is represented in the form of linguistic terms and the calculation is performed using fuzzy numbers. In 2011, Zadeh has extended this concept by presenting the idea of Z-number, a 2-tuple fuzzy numbers that describes the restriction and the reliability of the evaluation. The element of reliability in the evaluation is essential as it will affect the final result. Since this concept can still be considered as new, available methods that incorporate reliability for solving decision making problems is still scarce. In this paper, a decision making procedure based on Z-numbers is proposed. Due to the limitation of its basic properties, Z-numbers will be first transformed to fuzzy numbers for simpler calculations. A method of ranking fuzzy number is later used to prioritize the alternatives. A risk analysis problem is presented to illustrate the effectiveness of this proposed procedure.

  18. Selecting discrete and continuous features based on neighborhood decision error minimization.

    PubMed

    Hu, Qinghua; Pedrycz, Witold; Yu, Daren; Lang, Jun

    2010-02-01

    Feature selection plays an important role in pattern recognition and machine learning. Feature evaluation and classification complexity estimation arise as key issues in the construction of selection algorithms. To estimate classification complexity in different feature subspaces, a novel feature evaluation measure, called the neighborhood decision error rate (NDER), is proposed, which is applicable to both categorical and numerical features. We first introduce a neighborhood rough-set model to divide the sample set into decision positive regions and decision boundary regions. Then, the samples that fall within decision boundary regions are further grouped into recognizable and misclassified subsets based on class probabilities that occur in neighborhoods. The percentage of misclassified samples is viewed as the estimate of classification complexity of the corresponding feature subspaces. We present a forward greedy strategy for searching the feature subset, which minimizes the NDER and, correspondingly, minimizes the classification complexity of the selected feature subset. Both theoretical and experimental comparison with other feature selection algorithms shows that the proposed algorithm is effective for discrete and continuous features, as well as their mixture.

  19. Interactive Decision-Support Tool for Risk-Based Radiation Therapy Plan Comparison for Hodgkin Lymphoma

    SciTech Connect

    Brodin, N. Patrik; Maraldo, Maja V.; Aznar, Marianne C.; Vogelius, Ivan R.; Petersen, Peter M.; Bentzen, Søren M.; Specht, Lena

    2014-02-01

    Purpose: To present a novel tool that allows quantitative estimation and visualization of the risk of various relevant normal tissue endpoints to aid in treatment plan comparison and clinical decision making in radiation therapy (RT) planning for Hodgkin lymphoma (HL). Methods and Materials: A decision-support tool for risk-based, individualized treatment plan comparison is presented. The tool displays dose–response relationships, derived from published clinical data, for a number of relevant side effects and thereby provides direct visualization of the trade-off between these endpoints. The Quantitative Analyses of Normal Tissue Effects in the Clinic reports were applied, complemented with newer data where available. A “relevance score” was assigned to each data source, reflecting how relevant the input data are to current RT for HL. Results: The tool is applied to visualize the local steepness of dose–response curves to drive the reoptimization of a volumetric modulated arc therapy treatment plan for an HL patient with head-and-neck involvement. We also use this decision-support tool to visualize and quantitatively evaluate the trade-off between a 3-dimensional conformal RT plan and a volumetric modulated arc therapy plan for a patient with mediastinal HL. Conclusion: This multiple-endpoint decision-support tool provides quantitative risk estimates to supplement the clinical judgment of the radiation oncologist when comparing different RT options.

  20. A Novel Group Decision-Making Method Based on Sensor Data and Fuzzy Information

    PubMed Central

    Bai, Yu-Ting; Zhang, Bai-Hai; Wang, Xiao-Yi; Jin, Xue-Bo; Xu, Ji-Ping; Su, Ting-Li; Wang, Zhao-Yang

    2016-01-01

    Algal bloom is a typical phenomenon of the eutrophication of rivers and lakes and makes the water dirty and smelly. It is a serious threat to water security and public health. Most scholars studying solutions for this pollution have studied the principles of remediation approaches, but few have studied the decision-making and selection of the approaches. Existing research uses simplex decision-making information which is highly subjective and uses little of the data from water quality sensors. To utilize these data and solve the rational decision-making problem, a novel group decision-making method is proposed using the sensor data with fuzzy evaluation information. Firstly, the optimal similarity aggregation model of group opinions is built based on the modified similarity measurement of Vague values. Secondly, the approaches’ ability to improve the water quality indexes is expressed using Vague evaluation methods. Thirdly, the water quality sensor data are analyzed to match the features of the alternative approaches with grey relational degrees. This allows the best remediation approach to be selected to meet the current water status. Finally, the selection model is applied to the remediation of algal bloom in lakes. The results show this method’s rationality and feasibility when using different data from different sources. PMID:27801827

  1. Optimal Breast Biopsy Decision-Making Based on Mammographic Features and Demographic Factors.

    PubMed

    Chhatwal, Jagpreet; Alagoz, Oguzhan; Burnside, Elizabeth S

    2010-11-01

    Breast cancer is the most common non-skin cancer affecting women in the United States, where every year more than 20 million mammograms are performed. Breast biopsy is commonly performed on the suspicious findings on mammograms to confirm the presence of cancer. Currently, 700,000 biopsies are performed annually in the U.S.; 55%-85% of these biopsies ultimately are found to be benign breast lesions, resulting in unnecessary treatments, patient anxiety, and expenditures. This paper addresses the decision problem faced by radiologists: When should a woman be sent for biopsy based on her mammographic features and demographic factors? This problem is formulated as a finite-horizon discrete-time Markov decision process. The optimal policy of our model shows that the decision to biopsy should take the age of patient into account; particularly, an older patient's risk threshold for biopsy should be higher than that of a younger patient. When applied to the clinical data, our model outperforms radiologists in the biopsy decision-making problem. This study also derives structural properties of the model, including sufficiency conditions that ensure the existence of a control-limit type policy and nondecreasing control-limits with age.

  2. Integrating patient values into evidence-based practice: effective communication for shared decision-making.

    PubMed

    Vranceanu, Ana-Maria; Cooper, Cynthia; Ring, David

    2009-02-01

    Increasing data suggest that the traditional clinician-centered or disease-focused, biomedical approach to illness is less effective than a biopsychosocial, evidence-based, patient-centered approach to illness, particularly for chronic pain conditions. This article distinguishes patient-centered care from more traditional and outdated biomedical decision-making models; illustrates the complexity of illness behavior with a patient example; delves into the communication issues raised by this complexity, thereby demonstrating how best evidence can sometimes run counter to biases and intuition; provides a summary of evidence that patient-centered care positively affects outcomes; and explores how the shared decision-making approach along with cultivation of good communication skills can facilitate evidence-based practice.

  3. Some Results of Weak Anticipative Concept Applied in Simulation Based Decision Support in Enterprise

    NASA Astrophysics Data System (ADS)

    Kljajić, Miroljub; Kofjač, Davorin; Kljajić Borštnar, Mirjana; Škraba, Andrej

    2010-11-01

    The simulation models are used as for decision support and learning in enterprises and in schools. Tree cases of successful applications demonstrate usefulness of weak anticipative information. Job shop scheduling production with makespan criterion presents a real case customized flexible furniture production optimization. The genetic algorithm for job shop scheduling optimization is presented. Simulation based inventory control for products with stochastic lead time and demand describes inventory optimization for products with stochastic lead time and demand. Dynamic programming and fuzzy control algorithms reduce the total cost without producing stock-outs in most cases. Values of decision making information based on simulation were discussed too. All two cases will be discussed from optimization, modeling and learning point of view.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-11-19

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

  6. A Web-Based GIS for Health Care Decision-Support

    PubMed Central

    Richard, Jean-Baptiste; Toubiana, Laurent; Le Mignot, Loïc; Ben Said, Mohamed; Mugnier, Claude; Le Bihan–Benjamin, Christine; Jaïs, Jean Philippe; Landais, Paul

    2005-01-01

    This Web-based application allows access to the epidemiology of the demand and the supply of care concerning End-Stage Renal Disease (ESRD). It is a Web-based Geographic Information System (Web-GIS), the SIGNe (Système d’Information Géographique pour la Néphrologie), designed for the Renal Epidemiology and Information Network (REIN) dedicated to ESRD. It is a visualisation and decision-support tool. This Web-GIS was coupled to a data warehouse and embedded in a n-tier architecture designed as the Multi-Source Information System (MSIS). It provides maps matching the offer of care to the demand. It is presented with insights on the design and underlying technologies. It is dedicated to professionals and to public health care decision-makers. PMID:16779063

  7. A Web-based GIS for health care decision-support.

    PubMed

    Jean-Baptiste, Richard; Toubiana, Laurent; Le Mignot, Loïc; Ben Said, Mohamed; Mugnier, Claude; Le Bihan-Benjamin, Christine; Jaïs, Jean Philippe; Landais, Paul

    2005-01-01

    This Web-based application allows to access views of End-Stage Renal Disease (ESRD) concerning the epidemiology of the demand and the supply of care. It is a Web-based Geographic Information System (Web-GIS), the SIGNe (Système d'Information Géographique pour la Néphrologie), designed for the Renal Epidemiology and Information Network (REIN) dedicated to ESRD. It is a visualisation and decision-support tool. This Web-GIS was coupled to a data warehouse and embedded in an n-tier architecture designed as the Multi-Source Information System (MSIS). It provides maps matching the offer of care to the demand. It is presented with insights on the design and underlying technologies. It is dedicated to professionals and to public health care decision-makers.

  8. Risk-based decision-making framework for the selection of sediment dredging option.

    PubMed

    Manap, Norpadzlihatun; Voulvoulis, Nikolaos

    2014-10-15

    The aim of this study was to develop a risk-based decision-making framework for the selection of sediment dredging option. Descriptions using case studies of the newly integrated, holistic and staged framework were followed. The first stage utilized the historical dredging monitoring data and the contamination level in media data into Ecological Risk Assessment phases, which have been altered for benefits in cost, time and simplicity. How Multi-Criteria Decision Analysis (MCDA) can be used to analyze and prioritize dredging areas based on environmental, socio-economic and managerial criteria was described for the next stage. The results from MCDA will be integrated into Ecological Risk Assessment to characterize the degree of contamination in the prioritized areas. The last stage was later described using these findings and analyzed using MCDA, in order to identify the best sediment dredging option, accounting for the economic, environmental and technical aspects of dredging, which is beneficial for dredging and sediment management industries.

  9. A fuzzy knowledge-based decision support system for groundwater pollution risk evaluation.

    PubMed

    Uricchio, Vito F; Giordano, Raffaele; Lopez, Nicola

    2004-11-01

    In this paper we propose a decision support system that can provide information on the environmental impact of anthropic activities by examining their effects on groundwater quality. We use the combined value of both intrinsic vulnerability of a specific local aquifer, obtained by implementing a parametric managerial model (SINTACS), and a degree of hazard value, which takes into account specific human activities. Incomplete information is notoriously common in environmental planning. To overcome this deficiency we apply an algorithmic and a qualitative approach, based on expert judgment incorporated into the system's knowledge base. The decision support system takes into account the uncertainty of the environmental domain by using fuzzy logic and evaluates the reliability of the results according to information availability.

  10. Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy

    PubMed Central

    Barrett, Jeffrey S; Mondick, John T; Narayan, Mahesh; Vijayakumar, Kalpana; Vijayakumar, Sundararajan

    2008-01-01

    Background Decision analysis in hospital-based settings is becoming more common place. The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics. With respect to clinical decision making at the level of the patient, modeling and simulation approaches have been used to study and forecast treatment options, examine and rate caregiver performance and assign resources (staffing, beds, patient throughput). There us a great need to facilitate pharmacotherapeutic decision making in pediatrics given the often limited data available to guide dosing and manage patient response. We have employed nonlinear mixed effect models and Bayesian forecasting algorithms coupled with data summary and visualization tools to create drug-specific decision support systems that utilize individualized patient data from our electronic medical records systems. Methods Pharmacokinetic and pharmacodynamic nonlinear mixed-effect models of specific drugs are generated based on historical data in relevant pediatric populations or from adults when no pediatric data is available. These models are re-executed with individual patient data allowing for patient-specific guidance via a Bayesian forecasting approach. The models are called and executed in an interactive manner through our web-based dashboard environment which interfaces to the hospital's electronic medical records system. Results The methotrexate dashboard utilizes a two-compartment, population-based, PK mixed-effect model to project patient response to specific dosing events. Projected plasma concentrations are viewable against protocol-specific nomograms to provide dosing guidance for potential rescue therapy with leucovorin. These data are also viewable against common biomarkers used to assess patient safety (e.g., vital signs and plasma creatinine levels). As additional data become available via therapeutic drug monitoring, the model is re-executed and projections are

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

    PubMed

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

    1999-01-01

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

  12. INEEL Subsurface Disposal Area CERCLA-based Decision Analysis for Technology Screening and Remedial Alternative Evaluation

    SciTech Connect

    Parnell, G. S.; Kloeber, Jr. J.; Westphal, D; Fung, V.; Richardson, John Grant

    2000-03-01

    A CERCLA-based decision analysis methodology for alternative evaluation and technology screening has been developed for application at the Idaho National Engineering and Environmental Laboratory WAG 7 OU13/14 Subsurface Disposal Area (SDA). Quantitative value functions derived from CERCLA balancing criteria in cooperation with State and Federal regulators are presented. A weighted criteria hierarchy is also summarized that relates individual value function numerical values to an overall score for a specific technology alternative.

  13. A Strategic Decision Matrix for Analyzing Food Service Operations at Air Force Bases

    DTIC Science & Technology

    2006-12-01

    comment addressing this area on the returned questionnaire stated “Since our wartime mission is food and we earn a large portion of our go-to-war...looking to satisfy a craving for fast food . The menu also changes from day to day to add additional variety. But, their strategy is not based solely on...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA MBA PROFESSIONAL REPORT A Strategic Decision Matrix for Analyzing Food Service

  14. 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

  15. Implementing Genomic Clinical Decision Support for Drug‐Based Precision Medicine

    PubMed Central

    Formea, CM; Hoffman, JM; Matey, E; Peterson, JF; Boyce, RD

    2017-01-01

    The explosive growth of patient‐specific genomic information relevant to drug therapy will continue to be a defining characteristic of biomedical research. To implement drug‐based personalized medicine (PM) for patients, clinicians need actionable information incorporated into electronic health records (EHRs). New clinical decision support (CDS) methods and informatics infrastructure are required in order to comprehensively integrate, interpret, deliver, and apply the full range of genomic data for each patient.1 PMID:28109071

  16. Temporal dynamics of prediction error processing during reward-based decision making.

    PubMed

    Philiastides, Marios G; Biele, Guido; Vavatzanidis, Niki; Kazzer, Philipp; Heekeren, Hauke R

    2010-10-15

    Adaptive decision making depends on the accurate representation of rewards associated with potential choices. These representations can be acquired with reinforcement learning (RL) mechanisms, which use the prediction error (PE, the difference between expected and received rewards) as a learning signal to update reward expectations. While EEG experiments have highlighted the role of feedback-related potentials during performance monitoring, important questions about the temporal sequence of feedback processing and the specific function of feedback-related potentials during reward-based decision making remain. Here, we hypothesized that feedback processing starts with a qualitative evaluation of outcome-valence, which is subsequently complemented by a quantitative representation of PE magnitude. Results of a model-based single-trial analysis of EEG data collected during a reversal learning task showed that around 220ms after feedback outcomes are initially evaluated categorically with respect to their valence (positive vs. negative). Around 300ms, and parallel to the maintained valence-evaluation, the brain also represents quantitative information about PE magnitude, thus providing the complete information needed to update reward expectations and to guide adaptive decision making. Importantly, our single-trial EEG analysis based on PEs from an RL model showed that the feedback-related potentials do not merely reflect error awareness, but rather quantitative information crucial for learning reward contingencies.

  17. 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.

  18. Allocating funds for HIV/AIDS: a descriptive study of KwaDukuza, South Africa

    PubMed Central

    Lasry, Arielle; Carter, Michael W; Zaric, Gregory S

    2011-01-01

    Objective Through a descriptive study, we determined the factors that influence the decision-making process for allocating funds to HIV/AIDS prevention and treatment programmes, and the extent to which formal decision tools are used in the municipality of KwaDukuza, South Africa. Methods We conducted 35 key informant interviews in KwaDukuza. The interview questions addressed specific resource allocation issues while allowing respondents to speak openly about the complexities of the HIV/AIDS resource allocation process. Results Donors have a large influence on the decision-making process for HIV/AIDS resource allocation. However, advocacy groups, governmental bodies and local communities also play an important role. Political power, culture and ethics are among a set of intangible factors that have a strong influence on HIV/AIDS resource allocation. Formal methods, including needs assessment, best practice approaches, epidemiologic modelling and cost-effectiveness analysis are sometimes used to support the HIV/AIDS resource allocation process. Historical spending patterns are an important consideration in future HIV/AIDS allocation strategies. Conclusions Several factors and groups influence resource allocation in KwaDukuza. Although formal economic and epidemiologic information is sometimes used, in most cases other factors are more important for resource allocation decision-making. These other factors should be considered in any attempts to improve the resource allocation processes. PMID:20551138

  19. Cognitive cost as dynamic allocation of energetic resources

    PubMed Central

    Christie, S. Thomas; Schrater, Paul

    2015-01-01

    While it is widely recognized that thinking is somehow costly, involving cognitive effort and producing mental fatigue, these costs have alternatively been assumed to exist, treated as the brain's assessment of lost opportunities, or suggested to be metabolic but with implausible biological bases. We present a model of cognitive cost based on the novel idea that the brain senses and plans for longer-term allocation of metabolic resources by purposively conserving brain activity. We identify several distinct ways the brain might control its metabolic output, and show how a control-theoretic model that models decision-making with an energy budget can explain cognitive effort avoidance in terms of an optimal allocation of limited energetic resources. The model accounts for both subject responsiveness to reward and the detrimental effects of hypoglycemia on cognitive function. A critical component of the model is using astrocytic glycogen as a plausible basis for limited energetic reserves. Glycogen acts as an energy buffer that can temporarily support high neural activity beyond the rate supported by blood glucose supply. The published dynamics of glycogen depletion and repletion are consonant with a broad array of phenomena associated with cognitive cost. Our model thus subsumes both the “cost/benefit” and “limited resource” models of cognitive cost while retaining valuable contributions of each. We discuss how the rational control of metabolic resources could underpin the control of attention, working memory, cognitive look ahead, and model-free vs. model-based policy learning. PMID:26379482

  20. Advances in liver transplantation allocation systems.

    PubMed

    Schilsky, Michael L; Moini, Maryam

    2016-03-14

    With the growing number of patients in need of liver transplantation, there is a need for adopting new and modifying existing allocation policies that prioritize patients for liver transplantation. Policy should ensure fair allocation that is reproducible and strongly predictive of best pre and post transplant outcomes while taking into account the natural history of the potential recipients liver disease and its complications. There is wide acceptance for allocation policies based on urgency in which the sickest patients on the waiting list with the highest risk of mortality receive priority. Model for end-stage liver disease and Child-Turcotte-Pugh scoring system, the two most universally applicable systems are used in urgency-based prioritization. However, other factors must be considered to achieve optimal allocation. Factors affecting pre-transplant patient survival and the quality of the donor organ also affect outcome. The optimal system should have allocation prioritization that accounts for both urgency and transplant outcome. We reviewed past and current liver allocation systems with the aim of generating further discussion about improvement of current policies.

  1. Advances in liver transplantation allocation systems

    PubMed Central

    Schilsky, Michael L; Moini, Maryam

    2016-01-01

    With the growing number of patients in need of liver transplantation, there is a need for adopting new and modifying existing allocation policies that prioritize patients for liver transplantation. Policy should ensure fair allocation that is reproducible and strongly predictive of best pre and post transplant outcomes while taking into account the natural history of the potential recipients liver disease and its complications. There is wide acceptance for allocation policies based on urgency in which the sickest patients on the waiting list with the highest risk of mortality receive priority. Model for end-stage liver disease and Child-Turcotte-Pugh scoring system, the two most universally applicable systems are used in urgency-based prioritization. However, other factors must be considered to achieve optimal allocation. Factors affecting pre-transplant patient survival and the quality of the donor organ also affect outcome. The optimal system should have allocation prioritization that accounts for both urgency and transplant outcome. We reviewed past and current liver allocation systems with the aim of generating further discussion about improvement of current policies. PMID:26973389

  2. Decision Making and Environmental Problems

    ERIC Educational Resources Information Center

    Thompson, Bertha Boya

    1977-01-01

    Suggests a decision-making model that can be applied by high school students to a variety of environmental problems, and illustrates how the model can be used to make decisions concerning future energy shortages. Provides criteria for judging allocation priorities of limited resources and stimulates awareness of alternative solutions to energy…

  3. Bases for Curriculum Decisions for Development of Curriculum for Minorities in Small Business Ownership and Management, Post-Secondary Level.

    ERIC Educational Resources Information Center

    Green (Del) Associates, Foster City, CA.

    This document presents in three parts the bases for curriculum decisions in the development of a post-secondary curriculum for minorities in small business ownership and management. Part 1 covers the general curriculum decisions, including the following items: selection of curriculum testing site; academic credits; class scheduling; student…

  4. Design and Implementation of a Web-Based Collaborative Spatial Decision Support System: Organizational and Managerial Implications.

    ERIC Educational Resources Information Center

    Sikder, Iftikhar U.; Gangopadhyay, Aryya

    2002-01-01

    Discusses the development of collaborative spatial support systems and identifies research issues on the design and implementation of a Web-based collaborative spatial decision-making system, in the specific context of distributed environmental planning. Demonstrates the use of GEO-ELCA for decision-making tasks by urban or municipal planning…

  5. Approaches to Resource Allocation

    ERIC Educational Resources Information Center

    Dressel, Paul; Simon, Lou Anna Kimsey

    1976-01-01

    Various budgeting patterns and strategies are currently in use, each with its own particular strengths and weaknesses. Neither cost-benefit analysis nor cost-effectiveness analysis offers any better solution to the allocation problem than do the unsupported contentions of departments or the historical unit costs. An operable model that performs…

  6. Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations

    PubMed Central

    Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W.

    2016-01-01

    Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty’s 1–9 scale, this paper proposes a cross-ratio-based bipolar 0.1–0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness. PMID:27618082

  7. A collaborative teaching strategy for enhancing learning of evidence-based clinical decision-making.

    PubMed

    Scott, P J; Altenburger, P A; Kean, J

    2011-01-01

    The educational literature cites a lack of student motivation to learn how to use research evidence in clinical decision-making because the students do not observe clinicians using evidence. This lack of motivation presents a challenge to educators as they seek to instill the value of evidence-based clinical decision-making (EBCD) in students. One problem is that students in entry-level programs do not have the experience needed to know what to look for, and secondly, clinical decision-making is contextually based in a patient problem. Our approach offers one solution to bridging the gap between classroom teaching and real-world implementation of EBCD through a three-phase collaborative approach. Occupational and physical therapy students are partnered with clinicians to find and appraise evidence to answer the real-world questions posed by these therapists. This paper describes the implementation of the partnership, teaching/learning outcomes, logistics, and implications for clinicians. We found this approach increased student motivation and greatly enhanced the learning experience. Future directions include implementing a framework which allows for the assessment of the strategy on the facility and creates opportunities to integrate the use of EBCD in all aspects of facility practice.

  8. Negotiation Support Agent Based on Fuzzy Decision Making by Genetic Programming with the Coupled Chaos System

    NASA Astrophysics Data System (ADS)

    Matsumura, Koki; Goto, Michihiko; Hamamatsu, Yoshio

    This paper describes a negotiation agent system based on the fuzzy decision making. The method of seeking appropriate membership functions and a reasonable agreement point was examined by means of the genetic programming technique with the coupled chaos system, which is an intelligent principle. The negotiation rule is based on the negotiation model expressed by the utility theory in the process of decision making. And the concession process was modified with the opponent’s movement and the persistence of each negotiator. In order to search for a membership function more efficiently, the dynamic state of symbiosis between individuals, which was caused by the coupled chaos system, was taken advantage of. Then the effectiveness of the technique was examined by applying it to a practical negotiation case which needs cooperative decision making. As a result, the following findings were obtained. This technique helps discover practicable membership functions in a vast search area, and achieve the solution search with high efficiency. This technique is also considered to be applied to the negotiation support easily.

  9. Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations.

    PubMed

    Qian, Wuyong; Wang, Zhou-Jing; Li, Kevin W

    2016-09-09

    Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness.

  10. Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

    PubMed Central

    Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng

    2015-01-01

    In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597

  11. Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees.

    PubMed

    Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng

    2015-09-18

    In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods.

  12. Understanding Student-Weighted Allocation as a Means to Greater School Resource Equity

    ERIC Educational Resources Information Center

    Miles, Karen Hawley; Roza, Marguerite

    2006-01-01

    As attention shifts to how districts allocate resources to schools, student weighted allocation has emerged as an alternative to traditional staff-based allocation policies. Student-weighted allocation uses student need, rather than staff placement, as the building block of school budgeting. This article examines how the shift to student-weighted…

  13. Decision-making method for railway emergency based on combination weighting and cloud model

    NASA Astrophysics Data System (ADS)

    Liu, Xiaoqin; Wang, Fuzhang; Wang, Pu

    2017-01-01

    Aiming at the problems of randomness and fuzziness of railway emergency, this paper introduces a decision-making method of railway emergency based on combination weighting and cloud model. Firstly, In order to enhance the subjective and objective consistency of combined weights, the adjustment equations of weight coefficient are established with the Euclidean distance, then combined weights are calculated by means of improved analytic hierarchy process(IAHP) and entropy weight method. Secondly, the decision-making information of experts is converted into the cloud parameters of indexes with cloud model, and the cloud parameters of alternatives are obtained by integrating the combined weights and cloud parameters of indexes. Thirdly, the best alternative is obtained by analyzing and comparing the cloud parameters or cloud images of alternatives. Finally, the effectiveness and feasibility of the method are verified by a case.

  14. The Neural Representation of Unexpected Uncertainty During Value-Based Decision Making

    PubMed Central

    Payzan-LeNestour, Elise; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P.

    2016-01-01

    Summary Uncertainty is an inherent property of the environment and a central feature of models of decision-making and learning. Theoretical propositions suggest that one form, unexpected uncertainty, may be used to rapidly adapt to changes in the environment, while being influenced by two other forms: risk and estimation uncertainty. While previous studies have reported neural representations of estimation uncertainty and risk, relatively little is known about unexpected uncertainty. Here, participants performed a decision-making task while undergoing functional magnetic resonance imaging (fMRI), which, in combination with a Bayesian model-based analysis, enabled each form of uncertainty to be separately measured. We found representations of unexpected uncertainty in multiple cortical areas, as well as the noradrenergic brainstem nucleus locus coeruleus. Other unique cortical regions were found to encode risk, estimation uncertainty and learning rate. Collectively, these findings support theoretical models in which several formally separable uncertainty computations determine the speed of learning. PMID:23849203

  15. 'These sorts of people don't do very well': race and allocation of health care resources.

    PubMed Central

    Lowe, M; Kerridge, I H; Mitchell, K R

    1995-01-01

    Recent literature has highlighted issues of racial discrimination in medicine. In order to explore the sometimes subtle influence of racial determinants in decisions about resource allocation, we present the case of a 53-year-old Australian Aboriginal woman with end-stage renal failure. The epidemiology of renal failure in the Australian Aboriginal population and amongst other indigenous peoples is discussed. We show that the use of utilitarian outcome criteria for resource allocation may embody subtle racial discrimination where consideration is not given to issues of justice, race, culture and gender. It is only where the processes by which resources are allocated are transparent, clearly defined and based upon consultation with individual patients that issues and justice are likely to be adequately addressed. PMID:8778460

  16. [Contribution of mathematical modeling to vaccination decision making. Examples from varicella, rotavirus and papillomavirus vaccinations].

    PubMed

    Lévy-Bruhl, Daniel

    2010-11-01

    The decision to add a new vaccine to the immunization schedule is a complex and multidisciplinary process based on the risk-benefit balance and, increasingly, on the cost- effectiveness ratio. Such decisions now use mathematical models that can predict the indirect, and potentially detrimental, effects of mass vaccination on the epidemiology of the target disease. The adjunction of an economic component to the modeling process ensures that vaccination represents an efficient allocation of available financial resources in an increasingly constrained environment.

  17. Routing and wavelength allocation algorithm based on the weighted attack probability in software-defined optical networks

    NASA Astrophysics Data System (ADS)

    Zhao, Yongli; Zhang, Jie

    2017-02-01

    A routing and wavelength assignment (RWA) algorithm against high-power jamming based on software-defined optical networks (SDONs) is proposed. The SDON architecture is designed with power monitors at each node, which can collect the abnormal power information from each port and wavelength. Based on the abnormal power information, a metric, the weighted attack probability (WAP), can be calculated. A WAP-based RWA algorithm (WAP-RWA) is proposed considering the WAP values of each link and node along the selected lightpath. Numerical results show that the WAP-RWA algorithm can achieve a better performance in terms of blocking probability and resource utilization compared with the attack-aware dedicated path protection (AA-DPP) RWA (AA-DPP-RWA) algorithm, while providing a protection comparable with the AA-DPP-RWA algorithm.

  18. Patient choice and evidence based decisions: The case of complementary therapies

    PubMed Central

    Wye, Lesley; Shaw, Alison; Sharp, Debbie

    2009-01-01

    Abstract Objective  Current government policies simultaneously pursue the development of ‘patient‐led’ and ‘evidence‐based’ approaches to healthcare. The objective of this study was to explore how primary care clinicians and Primary Care Trust (PCT) managers balance these potentially competing tensions when considering popular, controversial treatments, like complementary therapies, in consultations (clinicians) or funding decisions (PCT managers). Setting and participants  We selected two case sites where complementary therapies were offered on NHS premises in England. We interviewed 18 PCT managers and clinicians, conducted an observation of a PCT meeting on complementary therapies and collected documentary data from referral databases and service funding bids. All interviews were taped, transcribed and analysed thematically. Interview, observation and documentary data were used to compare reported beliefs and behaviour to observed and documented behaviour. Results  The majority of clinicians and PCT managers claimed that research evidence guided their decisions; those who did not felt increasingly marginalized. However, discrepancies between reported and observed behaviour suggest that perceptions of research evidence, rather than fact based knowledge, predominated when considering complementary therapies. Conclusion  In the case of NHS complementary therapy service provision, patient preference may be largely insignificant in clinician and PCT managerial decisions, with decisions based mainly on ‘evidence rhetoric’ devised from collectively agreed, unchallenged, tacit perceptions of research literature. If a patient‐led NHS is to become a reality, NHS professionals need to cede the power that they wield with evidence rhetoric and acknowledge the legitimacy of patient preferences, views and alternative sources of evidence. PMID:19656225

  19. Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to AIG Prognostication in Terminally Ill Patients

    DTIC Science & Technology

    2016-03-01

    1 Award Number: W81-XWH-09-2-0175 TITLE: Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to AIG Prognostication in...From - To) 25Sep2009 - 31Dec2015 4. TITLE AND SUBTITLE Development of EBM-CDSS (Evidence-Based Clinical Decision Support System) to AIG Prognostication...health.usf.edu 4 14. ABSTRACT Goal of the project is to develop an Evidence-based Clinical Decision Support (CDSS-EBM) system and make it available at the point

  20. Real-Time Adaptive Control Allocation Applied to a High Performance Aircraft

    NASA Technical Reports Server (NTRS)

    Davidson, John B.; Lallman, Frederick J.; Bundick, W. Thomas

    2001-01-01

    Abstract This paper presents the development and application of one approach to the control of aircraft with large numbers of control effectors. This approach, referred to as real-time adaptive control allocation, combines a nonlinear method for control allocation with actuator failure detection and isolation. The control allocator maps moment (or angular acceleration) commands into physical control effector commands as functions of individual control effectiveness and availability. The actuator failure detection and isolation algorithm is a model-based approach that uses models of the actuators to predict actuator behavior and an adaptive decision threshold to achieve acceptable false alarm/missed detection rates. This integrated approach provides control reconfiguration when an aircraft is subjected to actuator failure, thereby improving maneuverability and survivability of the degraded aircraft. This method is demonstrated on a next generation military aircraft Lockheed-Martin Innovative Control Effector) simulation that has been modified to include a novel nonlinear fluid flow control control effector based on passive porosity. Desktop and real-time piloted simulation results demonstrate the performance of this integrated adaptive control allocation approach.

  1. Monetary-based consequences for drug abstinence: Methods of implementation and some considerations about the allocation of finances in substance abusers

    PubMed Central

    Dallery, Jesse; Raiff, Bethany

    2012-01-01

    Conceptualizing drug abuse within the framework of behavioral theories of choice highlights the relevance of environmental variables in shifting behavior away from drug-related purchases. Choosing to use drugs results in immediate, certain consequences (e.g., drug high and relief from withdrawal), whereas choosing abstinence typically results in delayed, and often uncertain, consequences (e.g., improved health, interpersonal relationships, money). Contingency management (CM) increases choice for drug abstinence via the availability of immediate, financial-based gains, contingent on objective evidence of abstinence. In this selective review of the literature, we highlight a variety of methods to deliver CM in practical, effective, and sustainable ways. We consider a number of parameters that are critical to the success of monetary-based CM, and the role of the context in influencing CM’s effects. To illustrate the broad range of applications of CM, we also review different methods for arranging contingencies to promote abstinence and other relevant behavior. Finally, we discuss some considerations about how drug-dependent individuals allocate their finances in the context of CM interventions. PMID:22149758

  2. 78 FR 5268 - Allocation of Capacity on New Merchant Transmission Projects and New Cost-Based, Participant...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-25

    ... satisfied the solicitation, selection and negotiation process criteria set forth herein. The Commission is... negotiation process criteria set forth herein. The Commission is making these clarifications and refinements... negotiations with identified customers.\\14\\ Based on these comments, the Commission held a follow up...

  3. Confidentiality Protection of User Data and Adaptive Resource Allocation for Managing Multiple Workflow Performance in Service-Based Systems

    ERIC Educational Resources Information Center

    An, Ho

    2012-01-01

    In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in…

  4. Reference allocations and use of a disparity measure to inform the design of allocation funding formulas in public health programs.

    PubMed

    Buehler, James W; Bernet, Patrick M; Ogden, Lydia L

    2012-01-01

    Funding formulas are commonly used by federal agencies to allocate program funds to states. As one approach to evaluating differences in allocations resulting from alternative formula calculations, we propose the use of a measure derived from the Gini index to summarize differences in allocations relative to 2 referent allocations: one based on equal per-capita funding across states and another based on equal funding per person living in poverty, which we define as the "proportionality of allocation" (PA). These referents reflect underlying values that often shape formula-based allocations for public health programs. The size of state populations serves as a general proxy for the amount of funding needed to support programs across states. While the size of state populations living in poverty is correlated with overall population size, allocations based on states' shares of the national population living in poverty reflect variations in funding need shaped by the association between poverty and multiple adverse health outcomes. The PA measure is a summary of the degree of dispersion in state-specific allocations relative to the referent allocations and provides a quick assessment of the impact of selecting alternative funding formula designs. We illustrate the PA values by adjusting a sample allocation, using various measures of the salary costs and in-state wealth, which might modulate states' needs for federal funding.

  5. Effect of individual thinking styles on item selection during study time allocation.

    PubMed

    Jia, Xiaoyu; Li, Weijian; Cao, Liren; Li, Ping; Shi, Meiling; Wang, Jingjing; Cao, Wei; Li, Xinyu

    2016-03-14

    The influence of individual differences on learners' study time allocation has been emphasised in recent studies; however, little is known about the role of individual thinking styles (analytical versus intuitive). In the present study, we explored the influence of individual thinking styles on learners' application of agenda-based and habitual processes when selecting the first item during a study-time allocation task. A 3-item cognitive reflection test (CRT) was used to determine individuals' degree of cognitive reliance on intuitive versus analytical cognitive processing. Significant correlations between CRT scores and the choices of first item selection were observed in both Experiment 1a (study time was 5 seconds per triplet) and Experiment 1b (study time was 20 seconds per triplet). Furthermore, analytical decision makers constructed a value-based agenda (prioritised high-reward items), whereas intuitive decision makers relied more upon habitual responding (selected items from the leftmost of the array). The findings of Experiment 1a were replicated in Experiment 2 notwithstanding ruling out the possible effects from individual intelligence and working memory capacity. Overall, the individual thinking style plays an important role on learners' study time allocation and the predictive ability of CRT is reliable in learners' item selection strategy.

  6. An image feature-based approach to automatically find images for application to clinical decision support.

    PubMed

    Stanley, R Joe; De, Soumya; Demner-Fushman, Dina; Antani, Sameer; Thoma, George R

    2011-07-01

    The illustrations in biomedical publications often provide useful information in aiding clinicians' decisions when full text searching is performed to find evidence in support of a clinical decision. In this research, image analysis and classification techniques are explored to automatically extract information for differentiating specific modalities to characterize illustrations in biomedical publications, which may assist in the evidence finding process. Global, histogram-based, and texture image illustration features were compared to basis function luminance histogram correlation features for modality-based discrimination over a set of 742 manually annotated images by modality (radiological, photo, etc.) selected from the 2004-2005 issues of the British Journal of Oral and Maxillofacial Surgery. Using a mean shifting supervised clustering technique, automatic modality-based discrimination results as high as 95.57% were obtained using the basis function features. These results compared favorably to other feature categories examined. The experimental results show that image-based features, particularly correlation-based features, can provide useful modality discrimination information.

  7. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems

    PubMed Central

    Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

    2015-01-01

    A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What’s more, the improved algorithm can enhance the accuracy of blind recognition obviously. PMID:26154439

  8. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

    PubMed

    Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

    2015-01-01

    A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

  9. Resource allocation for mitigating regional air pollution–related mortality: A summertime case study for five cities in the United States

    PubMed Central

    Liao, Kuo-Jen; Hou, Xiangting; Strickland, Matthew J.

    2016-01-01

    ABSTRACT An important issue of regional air quality management is to allocate air quality management funds to maximize environmental and human health benefits. In this study, we use an innovative approach to tackle this air quality management issue. We develop an innovative resource allocation model that allows identification of air pollutant emission control strategies that maximize mortality avoidances subject to a resource constraint. We first present the development of the resource allocation model and then a case study to show how the model can be used to identify resource allocation strategies that maximize mortality avoidances for top five Metropolitan Statistical Areas (MSAs) (i.e., New York, Los Angeles, Chicago, Dallas-Fort Worth, and Philadelphia) in the continental United States collectively. Given budget constraints in the U.S. Environmental Protection Agency’s (EPA) Clean Air Act assessment, the results of the case study suggest that controls of sulfur dioxide (SO2) and primary carbon (PC) emissions from EPA Regions 2, 3, 5, 6, and 9 would have significant health benefits for the five selected cities collectively. Around 30,800 air pollution–related mortalities could be avoided during the selected 2-week summertime episode for the five cities collectively if the budget could be allocated based on the results of the resource allocation model. Although only five U.S. cities during a 2-week episode are considered in the case study, the resource allocation model can be used by decision-makers to plan air pollution mitigation strategies to achieve the most significant health benefits for other seasons and more cities over a region or the continental U.S.Implications: Effective allocations of air quality management resources are challenging and complicated, and it is desired to have a tool that can help decision-makers better allocate the funds to maximize health benefits of air pollution mitigation. An innovative resource allocation model developed in

  10. Establishing Total Maximum Daily Load (TMDL) Wasteload Allocations (WLAs) for Storm Water Sources and NPDES Permit Requirements Based on Those WLAs

    EPA Pesticide Factsheets

    The memoranda clarify existing EPA regulatory requirements for, and provide guidance on, establishing wasteload allocations (WLAs) for storm water discharges in total maximum daily loads (TMDLs) approved or established by EPA.

  11. Visualization-based decision support for value-driven system design

    NASA Astrophysics Data System (ADS)

    Tibor, Elliott

    with a Value-Driven Design formulation. The visualization methods are also used to assist in the decomposition of a value function, by representing attribute sensitivities to aid with trade-off studies. Lastly, visualization is used to enable greater understanding of the subsystem relationships, by displaying derivative-based couplings, and the design uncertainties, through implementation of utility theory. The use of these visualization methods is shown to enhance the decision-making capabilities of the designer by granting them a more holistic view of the complex design space.

  12. A multicriteria decision making approach based on fuzzy theory and credibility mechanism for logistics center location selection.

    PubMed

    Wang, Bowen; Xiong, Haitao; Jiang, Chengrui

    2014-01-01

    As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.

  13. Implementation and evaluation of an Asbru-based decision support system for adjuvant treatment in breast cancer.

    PubMed

    Eccher, Claudio; Seyfang, Andreas; Ferro, Antonella

    2014-11-01

    The domain of cancer treatment is a promising field for the implementation and evaluation of a protocol-based clinical decision support system, because of the algorithmic nature of treatment recommendations. However, many factors can limit such systems' potential to support the decision of clinicians: technical challenges related to the interoperability with existing electronic patient records and clinical challenges related to the inherent complexity of the decisions, often collectively taken by panels of different specialists. In this paper, we evaluate the performances of an Asbru-based decision support system implementing treatment protocols for breast cancer, which accesses data from an oncological electronic patient record. Focusing on the decision on the adjuvant pharmaceutical treatment for patients affected by early invasive breast cancer, we evaluate the matching of the system's recommendations with those issued by the multidisciplinary panel held weekly in a hospital.

  14. Measuring the Return on Information Technology: A Knowledge-Based Approach for Revenue Allocation at the Process and Firm Level

    DTIC Science & Technology

    2005-07-01

    option = value Predicting the future value of an IT investment No surrogate for revenue at sub- corporate level Family of Measures...various contributions of inputs to the firm’s output. Hitt and Brynjolfsson (1996) asessed the value of IT in terms of productivity, profitability, and...the process level, approaches to determining the impact of IT can be classified as: (a) family of measures, (b) cost-based, and (c) knowledge value

  15. Modelling a decision-support system for oncology using rule-based and case-based reasoning methodologies.

    PubMed

    Rossille, Delphine; Laurent, Jean-François; Burgun, Anita

    2005-03-01

    In most hospital medical units, multidisciplinary committees meet weekly to discuss their patients' cases. The medical experts base their decisions on three sources of information. First, they check if their patient complies with existing guidelines. Failing these, the medical experts will base their therapeutic decisions on the cases of similar patients that they have treated in the past. We propose a multi-modal reasoning decision-support system based on both guideline and case series, which will automatically compare the patient's case to the corresponding guideline, then to other cases, and retrieve similar cases. The general structure of the system is presented here, the domain of application being oncology. As the patients' records are not currently stored in a database in a format which is directly accessible, an object-oriented model is proposed, which includes prognosis factors currently tested in clinical trials, well-established ones, and a description of the illness episodes. The system is designed to be a data warehouse. Such a system does not exist in the literature. Future work will be needed to define the similarity measures, and to connect the system to the current database.

  16. Mice plan decision strategies based on previously learned time intervals, locations, and probabilities.

    PubMed

    Tosun, Tuğçe; Gür, Ezgi; Balcı, Fuat

    2016-01-19

    Animals can shape their timed behaviors based on experienced probabilistic relations in a nearly optimal fashion. On the other hand, it is not clear if they adopt these timed decisions by making computations based on previously learnt task parameters (time intervals, locations, and probabilities) or if they gradually develop their decisions based on trial and error. To address this question, we tested mice in the timed-switching task, which required them to anticipate when (after a short or long delay) and at which of the two delay locations a reward would be presented. The probability of short trials differed between test groups in two experiments. Critically, we first trained mice on relevant task parameters by signaling the active trial with a discriminative stimulus and delivered the corresponding reward after the associated delay without any response requirement (without inducing switching behavior). During the test phase, both options were presented simultaneously to characterize the emergence and temporal characteristics of the switching behavior. Mice exhibited timed-switching behavior starting from the first few test trials, and their performance remained stable throughout testing in the majority of the conditions. Furthermore, as the probability of the short trial increased, mice waited longer before switching from the short to long location (experiment 1). These behavioral adjustments were in directions predicted by reward maximization. These results suggest that rather than gradually adjusting their time-dependent choice behavior, mice abruptly adopted temporal decision strategies by directly integrating their previous knowledge of task parameters into their timed behavior, supporting the model-based representational account of temporal risk assessment.

  17. An improved poly(A) motifs recognition method based on decision level fusion.

    PubMed

    Zhang, Shanxin; Han, Jiuqiang; Liu, Jun; Zheng, Jiguang; Liu, Ruiling

    2015-02-01

    Polyadenylation is the process of addition of poly(A) tail to mRNA 3' ends. Identification of motifs controlling polyadenylation plays an essential role in improving genome annotation accuracy and better understanding of the mechanisms governing gene regulation. The bioinformatics methods used for poly(A) motifs recognition have demonstrated that information extracted from sequences surrounding the candidate motifs can differentiate true motifs from the false ones greatly. However, these methods depend on either domain features or string kernels. To date, methods combining information from different sources have not been found yet. Here, we proposed an improved poly(A) motifs recognition method by combing different sources based on decision level fusion. First of all, two novel prediction methods was proposed based on support vector machine (SVM): one method is achieved by using the domain-specific features and principle component analysis (PCA) method to eliminate the redundancy (PCA-SVM); the other method is based on Oligo string kernel (Oligo-SVM). Then we proposed a novel machine-learning method for poly(A) motif prediction by marrying four poly(A) motifs recognition methods, including two state-of-the-art methods (Random Forest (RF) and HMM-SVM), and two novel proposed methods (PCA-SVM and Oligo-SVM). A decision level information fusion method was employed to combine the decision values of different classifiers by applying the DS evidence theory. We evaluated our method on a comprehensive poly(A) dataset that consists of 14,740 samples on 12 variants of poly(A) motifs and 2750 samples containing none of these motifs. Our method has achieved accuracy up to 86.13%. Compared with the four classifiers, our evidence theory based method reduces the average error rate by about 30%, 27%, 26% and 16%, respectively. The experimental results suggest that the proposed method is more effective for poly(A) motif recognition.

  18. Mice plan decision strategies based on previously learned time intervals, locations, and probabilities

    PubMed Central

    Tosun, Tuğçe; Gür, Ezgi; Balcı, Fuat

    2016-01-01

    Animals can shape their timed behaviors based on experienced probabilistic relations in a nearly optimal fashion. On the other hand, it is not clear if they adopt these timed decisions by making computations based on previously learnt task parameters (time intervals, locations, and probabilities) or if they gradually develop their decisions based on trial and error. To address this question, we tested mice in the timed-switching task, which required them to anticipate when (after a short or long delay) and at which of the two delay locations a reward would be presented. The probability of short trials differed between test groups in two experiments. Critically, we first trained mice on relevant task parameters by signaling the active trial with a discriminative stimulus and delivered the corresponding reward after the associated delay without any response requirement (without inducing switching behavior). During the test phase, both options were presented simultaneously to characterize the emergence and temporal characteristics of the switching behavior. Mice exhibited timed-switching behavior starting from the first few test trials, and their performance remained stable throughout testing in the majority of the conditions. Furthermore, as the probability of the short trial increased, mice waited longer before switching from the short to long location (experiment 1). These behavioral adjustments were in directions predicted by reward maximization. These results suggest that rather than gradually adjusting their time-dependent choice behavior, mice abruptly adopted temporal decision strategies by directly integrating their previous knowledge of task parameters into their timed behavior, supporting the model-based representational account of temporal risk assessment. PMID:26733674

  19. Health economics and outcomes methods in risk-based decision-making for blood safety.

    PubMed

    Custer, Brian; Janssen, Mart P

    2015-08-01

    Analytical methods appropriate for health economic assessments of transfusion safety interventions have not previously been described in ways that facilitate their use. Within the context of risk-based decision-making (RBDM), health economics can be important for optimizing decisions among competing interventions. The objective of this review is to address key considerations and limitations of current methods as they apply to blood safety. Because a voluntary blood supply is an example of a public good, analyses should be conducted from the societal perspective when possible. Two primary study designs are recommended for most blood safety intervention assessments: budget impact analysis (BIA), which measures the cost to implement an intervention both to the blood operator but also in a broader context, and cost-utility analysis (CUA), which measures the ratio between costs and health gain achieved, in terms of reduced morbidity and mortality, by use of an intervention. These analyses often have important limitations because data that reflect specific aspects, for example, blood recipient population characteristics or complication rates, are not available. Sensitivity analyses play an important role. The impact of various uncertain factors can be studied conjointly in probabilistic sensitivity analyses. The use of BIA and CUA together provides a comprehensive assessment of the costs and benefits from implementing (or not) specific interventions. RBDM is multifaceted and impacts a broad spectrum of stakeholders. Gathering and analyzing health economic evidence as part of the RBDM process enhances the quality, completeness, and transparency of decision-making.

  20. Challenges of Interpreting Frontal Neurons during Value-Based Decision-Making

    PubMed Central

    Wallis, Jonathan D.; Rich, Erin L.

    2011-01-01

    The frontal cortex is crucial to sound decision-making, and the activity of frontal neurons correlates with many aspects of a choice, including the reward value of options and outcomes. However, rewards are of high motivational significance and have widespread effects on neural activity. As such, many neural signals not directly involved in the decision process can correlate with reward value. With correlative techniques such as electrophysiological recording or functional neuroimaging, it can be challenging to distinguish neural signals underlying value-based decision-making from other perceptual, cognitive, and motor processes. In the first part of the paper, we examine how different value-related computations can potentially be confused. In particular, error-related signals in the anterior cingulate cortex, generated when one discovers the consequences of an action, might actually represent violations of outcome expectation, rather than errors per se. Also, signals generated at the time of choice are typically interpreted as reflecting predictions regarding the outcomes associated with the different choice alternatives. However, these signals could instead reflect comparisons between the presented choice options and previously presented choice alternatives. In the second part of the paper, we examine how value signals have been successfully dissociated from saliency-related signals, such as attention, arousal, and motor preparation in studies employing outcomes with both positive and negative valence. We hope that highlighting these issues will prove useful for future studies aimed at disambiguating the contribution of different neuronal populations to choice behavior. PMID:22125508