Treatment decision-making by men with localized prostate cancer: the influence of personal factors.

Science.gov (United States)

Berry, Donna L; Ellis, William J; Woods, Nancy Fugate; Schwien, Christina; Mullen, Kristin H; Yang, Claire

2003-01-01

For many men with localized prostate cancer, there is no definite answer or unequivocal choice regarding treatment modality. This high-stakes treatment decision is made in the context of great uncertainty. The purpose of this study is to systematically document meaningful and relevant aspects of treatment decision-making reported by men with localized prostate cancer. Focus groups and individual interviews were conducted with 44 men who were within 6 months of a diagnosis of localized prostate cancer. Using content analysis and grounded theory analytic techniques, major aspects and processes of men's treatment decision making are identified and described. The participants reported their experiences beginning with influential personal history factors, followed by detailed descriptions of information gathering and the important influence of expected treatment outcomes and other individuals' cancer histories and/or shared opinions. Twenty of the 44 (45%) participants relied heavily on the influence of another's opinion or history to finalize a decision, yet only 10 of the 44 (22.7%) reported this individual to be their physician. A common process, "making the best choice for me" was explicated. Clinicians assume that men are making rational treatment decisions based on reliable information, yet this study documents a different reality. Patient education about medical therapies and the patients' own medical factors is not enough. A clinic visit dialogue that brings personal factors to the conversation along with medical factors can guide a man to making his "best choice" for localized prostate cancer.

Measuring agreement between decision support reminders: the cloud vs. the local expert

OpenAIRE

Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M; Wright, Adam; Middleton, Blackford

2014-01-01

Background: A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods: Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web ser...

Mathematical programming solver based on local search

CERN Document Server

Gardi, Frédéric; Darlay, Julien; Estellon, Bertrand; Megel, Romain

2014-01-01

This book covers local search for combinatorial optimization and its extension to mixed-variable optimization. Although not yet understood from the theoretical point of view, local search is the paradigm of choice for tackling large-scale real-life optimization problems. Today's end-users demand interactivity with decision support systems. For optimization software, this means obtaining good-quality solutions quickly. Fast iterative improvement methods, like local search, are suited to satisfying such needs. Here the authors show local search in a new light, in particular presenting a new kind of mathematical programming solver, namely LocalSolver, based on neighborhood search. First, an iconoclast methodology is presented to design and engineer local search algorithms. The authors' concern about industrializing local search approaches is of particular interest for practitioners. This methodology is applied to solve two industrial problems with high economic stakes. Software based on local search induces ex...

The Influence Of Planning Decisions Regarding Land Evaluation Based On A Selected Local Real Estate Market

Directory of Open Access Journals (Sweden)

Foryś Iwona

2015-12-01

Full Text Available The article analyzes the influence of planning decisions on changes taking place on the local real estate market. Three stages of the planning process are studied in particular, i.e.: the passing of the study of conditions and directions of spatial development, the Commune Council Resolution on initiating the formulation of a local spatial development plan, and finally the Resolution on accepting the local plan, as well as the effects of these activities on the land value in a given real estate market in Stargard Szczeciński, in the West-Pomeranian (Zachodniopomorskie Province of Poland. The object of the research is to identify the indicated relationships on a given real estate market, on which respective spatial planning stages can be distinguished, as well as the strength and course of the analyzed relationships. The study will verify the research hypothesis regarding the strength and directions of the effects of planning decisions as the direct and indirect reasons behind price changes on the real estate market. The analysis uses data from the Price Register and the District Starosty Values, along with statistical and public information data and the authors' own studies.

Proposal of a Holistic Model to Support Local-Level Evidence-Based Practice

Directory of Open Access Journals (Sweden)

Said Shahtahmasebi

2010-01-01

Full Text Available In response to a central drive for evidence-based practice, there have been many research support schemes, setups, and other practices concentrating on facilitating access to external research, such as the Centre for Evidence Based Healthcare Aotearoa, the Cochrane Collaboration, and the York Centre for Reviews and Dissemination. Very little attention has been paid to supporting internal research in terms of local evidence and internal research capabilities. The whole evidence-based practice movement has alienated internal decision makers and, thus, very little progress has been made in the context of evidence informing local policy formation. Health and social policies are made centrally based on dubious claims and often evidence is sought after implementation. For example, on record, most health care practitioners appear to agree with the causal link between depression and mental illness (sometimes qualified with other social factors with suicide; off the record, even some psychiatrists doubt that such a link is applicable to the population as a whole. Therefore, be it through misplaced loyalty or a lack of support for internal researchers/decision makers, local evidence informing local decision making may have been ignored in favour of external evidence. In this paper, we present a practical holistic model to support local evidence-based decision making. This approach is more relevant in light of a new approach to primary health care of “local knowledge” complementing external evidence. One possible outcome would be to network with other regional programmes around the world to share information and identify “best” practices, such as the “Stop Youth Suicide Campaign”(www.stopyouthsuicide.com.

New Methods for Crafting Locally Decision-Relevant Scenarios

Science.gov (United States)

Lempert, R. J.

2015-12-01

Scenarios can play an important role in helping decision makers to imagine future worlds, both good and bad, different than the one with which we are familiar and to take concrete steps now to address the risks generated by climate change. At their best, scenarios can effectively represent deep uncertainty; integrate over multiple domains; and enable parties with different expectation and values to expand the range of futures they consider, to see the world from different points of view, and to grapple seriously with the potential implications of surprising or inconvenient futures. These attributes of scenario processes can prove crucial in helping craft effective responses to climate change. But traditional scenario methods can also fail to overcome difficulties related to choosing, communicating, and using scenarios to identify, evaluate, and reach consensus on appropriate policies. Such challenges can limit scenario's impact in broad public discourse. This talk will demonstrate how new decision support approaches can employ new quantitative tools that allow scenarios to emerge from a process of deliberation with analysis among stakeholders, rather than serve as inputs to it, thereby increasing the impacts of scenarios on decision making. This talk will demonstrate these methods in the design of a decision support tool to help residents of low lying coastal cities grapple with the long-term risks of sea level rise. In particular, this talk will show how information from the IPCC SSP's can be combined with local information to provide a rich set of locally decision-relevant information.

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

Science.gov (United States)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

Enhancing guideline-based decision support with distributed computation through local mobile application

NARCIS (Netherlands)

Shalom, Erez; Shahar, Yuval; Goldstein, Ayelet; Ariel, Elior; Quaglini, Silvana; Sacchi, Lucia; Fung, L.S.N.; Jones, Valerie M.; Broens, T.H.F.; García-Sáez, Gema; Hernando, Elena

2014-01-01

We introduce the need for a distributed guideline-based decision support (DSS) process, describe its characteristics, and explain how we implemented this process within the European Union’s MobiGuide project. In particular, we have developed a mechanism of sequential, piecemeal projection, i.e.,

Introduction of new technologies and decision making processes: a framework to adapt a Local Health Technology Decision Support Program for other local settings.

Science.gov (United States)

Poulin, Paule; Austen, Lea; Scott, Catherine M; Poulin, Michelle; Gall, Nadine; Seidel, Judy; Lafrenière, René

2013-01-01

Introducing new health technologies, including medical devices, into a local setting in a safe, effective, and transparent manner is a complex process, involving many disciplines and players within an organization. Decision making should be systematic, consistent, and transparent. It should involve translating and integrating scientific evidence, such as health technology assessment (HTA) reports, with context-sensitive evidence to develop recommendations on whether and under what conditions a new technology will be introduced. However, the development of a program to support such decision making can require considerable time and resources. An alternative is to adapt a preexisting program to the new setting. We describe a framework for adapting the Local HTA Decision Support Program, originally developed by the Department of Surgery and Surgical Services (Calgary, AB, Canada), for use by other departments. The framework consists of six steps: 1) development of a program review and adaptation manual, 2) education and readiness assessment of interested departments, 3) evaluation of the program by individual departments, 4) joint evaluation via retreats, 5) synthesis of feedback and program revision, and 6) evaluation of the adaptation process. Nine departments revised the Local HTA Decision Support Program and expressed strong satisfaction with the adaptation process. Key elements for success were identified. Adaptation of a preexisting program may reduce duplication of effort, save resources, raise the health care providers' awareness of HTA, and foster constructive stakeholder engagement, which enhances the legitimacy of evidence-informed recommendations for introducing new health technologies. We encourage others to use this framework for program adaptation and to report their experiences.

The construction of a decision tool to analyse local demand and local supply for GP care using a synthetic estimation model.

Science.gov (United States)

de Graaf-Ruizendaal, Willemijn A; de Bakker, Dinny H

2013-10-27

This study addresses the growing academic and policy interest in the appropriate provision of local healthcare services to the healthcare needs of local populations to increase health status and decrease healthcare costs. However, for most local areas information on the demand for primary care and supply is missing. The research goal is to examine the construction of a decision tool which enables healthcare planners to analyse local supply and demand in order to arrive at a better match. National sample-based medical record data of general practitioners (GPs) were used to predict the local demand for GP care based on local populations using a synthetic estimation technique. Next, the surplus or deficit in local GP supply were calculated using the national GP registry. Subsequently, a dynamic internet tool was built to present demand, supply and the confrontation between supply and demand regarding GP care for local areas and their surroundings in the Netherlands. Regression analysis showed a significant relationship between sociodemographic predictors of postcode areas and GP consultation time (F [14, 269,467] = 2,852.24; P 1,000 inhabitants in the Netherlands covering 97% of the total population. Confronting these estimated demand figures with the actual GP supply resulted in the average GP workload and the number of full-time equivalent (FTE) GP too much/too few for local areas to cover the demand for GP care. An estimated shortage of one FTE GP or more was prevalent in about 19% of the postcode areas with >1,000 inhabitants if the surrounding postcode areas were taken into consideration. Underserved areas were mainly found in rural regions. The constructed decision tool is freely accessible on the Internet and can be used as a starting point in the discussion on primary care service provision in local communities and it can make a considerable contribution to a primary care system which provides care when and where people need it.

Rule-based decision making model

International Nuclear Information System (INIS)

Sirola, Miki

1998-01-01

A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

LOCAL BINARIZATION FOR DOCUMENT IMAGES CAPTURED BY CAMERAS WITH DECISION TREE

Directory of Open Access Journals (Sweden)

Naser Jawas

2012-07-01

Full Text Available Character recognition in a document image captured by a digital camera requires a good binary image as the input for the separation the text from the background. Global binarization method does not provide such good separation because of the problem of uneven levels of lighting in images captured by cameras. Local binarization method overcomes the problem but requires a method to partition the large image into local windows properly. In this paper, we propose a local binariation method with dynamic image partitioning using integral image and decision tree for the binarization decision. The integral image is used to estimate the number of line in the document image. The number of line in the document image is used to devide the document into local windows. The decision tree makes a decision for threshold in every local window. The result shows that the proposed method can separate the text from the background better than using global thresholding with the best OCR result of the binarized image is 99.4%. Pengenalan karakter pada sebuah dokumen citra yang diambil menggunakan kamera digital membutuhkan citra yang terbinerisasi dengan baik untuk memisahkan antara teks dengan background. Metode binarisasi global tidak memberikan hasil pemisahan yang bagus karena permasalahan tingkat pencahayaan yang tidak seimbang pada citra hasil kamera digital. Metode binarisasi lokal dapat mengatasi permasalahan tersebut namun metode tersebut membutuhkan metode untuk membagi citra ke dalam bagian-bagian window lokal. Pada paper ini diusulkan sebuah metode binarisasi lokal dengan pembagian citra secara dinamis menggunakan integral image dan decision tree untuk keputusan binarisasi lokalnya. Integral image digunakan untuk mengestimasi jumlah baris teks dalam dokumen citra. Jumlah baris tersebut kemudian digunakan untuk membagi citra dokumen ke dalam window lokal. Keputusan nilai threshold untuk setiap window lokal ditentukan dengan decisiontree. Hasilnya menunjukkan

Local Orientation and the Evolution of Foraging: Changes in Decision Making Can Eliminate Evolutionary Trade-offs

Science.gov (United States)

van der Post, Daniel J.; Semmann, Dirk

2011-01-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape. PMID:21998571

Treatment decision-making strategies and influences in patients with localized prostate carcinoma.

Science.gov (United States)

Gwede, Clement K; Pow-Sang, Julio; Seigne, John; Heysek, Randy; Helal, Mohamed; Shade, Kristin; Cantor, Alan; Jacobsen, Paul B

2005-10-01

Patients diagnosed with localized prostate carcinoma need to interpret complicated medical information to make an informed treatment selection from among treatments that have comparable efficacy but differing side effects. The authors reported initial results for treatment decision-making strategies among men receiving definitive treatment for localized prostate carcinoma. One hundred nineteen men treated with radical prostatectomy (44%) or brachytherapy (56%) consented to participate. Guided by a cognitive-affective theoretic framework, the authors assessed differences in decision-making strategies, and treatment and disease-relevant beliefs and affects, in addition to demographic and clinical variables. Approximately half of patients reported difficulty (49%) and distress (45%) while making treatment decisions, but no regrets (74%) regarding the treatment choice they made. Patients who underwent prostatectomy were younger, were more likely to be employed, had worse tumor grade, and had a shorter time since diagnosis (P Decision-making aids or other interventions to reduce decisional difficulty and emotional distress during decision making were indicated.

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

Science.gov (United States)

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

2016-12-01

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

What is a “good” treatment decision?: Decisional control, knowledge, treatment decision-making, and quality of life in men with clinically localized prostate cancer

Science.gov (United States)

Orom, Heather; Biddle, Caitlin; Underwood, Willie; Nelson, Christian J.; Homish, D. Lynn

2016-01-01

Objective We explored whether active patient involvement in decision making and greater patient knowledge are associated with better treatment decision making experiences and better quality of life (QOL) among men with clinically localized prostate cancer. Localized prostate cancer treatment decision-making is an advantageous model for studying patient treatment decision-making dynamics as there are multiple treatment options and a lack of empirical evidence to recommend one over the other; consequently, it is recommended that patients be fully involved in making the decision. Methods Men with newly diagnosed clinically localized prostate cancer (N=1529) completed measures of decisional control, prostate cancer knowledge, and their decision-making experience (decisional conflict, and decision-making satisfaction and difficulty) shortly after they made their treatment decision. Prostate cancer-specific QOL was assessed 6-months after treatment. Results More active involvement in decision making and greater knowledge were associated with lower decisional conflict and higher decision-making satisfaction, but greater decision-making difficulty. An interaction between decisional control and knowledge revealed that greater knowledge was only associated with greater difficulty for men actively involved in making the decision (67% of sample). Greater knowledge, but not decisional control predicted better QOL 6-months post-treatment. Conclusion Although men who are actively involved in decision making and more knowledgeable may make more informed decisions, they could benefit from decisional support (e.g., decision-making aids, emotional support from providers, strategies for reducing emotional distress) to make the process easier. Men who were more knowledgeable about prostate cancer and treatment side effects at the time they made their treatment decision may have appraised their QOL as higher because they had realistic expectations about side effects. PMID:26957566

Applications of decision theory to test-based decision making

NARCIS (Netherlands)

van der Linden, Willem J.

1987-01-01

The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Four basic decision problems are distinguished: (1) selection; (2) mastery; (3) placement; and (4) classification, the situation where each treatment has its own criterion. Each type of decision can be

Does consideration of GHG reductions change local decision making? A Case Study in Chile

Science.gov (United States)

Cifuentes, L. A.; Blumel, G.

2003-12-01

While local air pollution has been a public concern in developing countries for some time, climate change is looked upon as a non-urgent, developed world problem. In this work we present a case study of the interaction of measures to abate air pollution and measures to mitigate GHG emissions in Santiago, Chile, with the purpose of determining if the consideration of reductions in GHG affects the decisions taken to mitigate local air pollution. The emissions reductions of both GHG and local air pollutants were estimated from emission factors (some derived locally) and changes in activity levels. Health benefits due to air pollution abatement were computed using figures derived previously for the cost benefit analysis of Santiago's Decontamination Plan, transferred to the different cities taking into consideration local demographic and income data. The Santiago estimates were obtained using the damage function approach, based on some local epidemiological studies, and on local health and demographic data. Unit social values for the effects were estimated locally (for cost of treatment and lost productivity values) or extrapolated from US values (mainly for WTP values) using the ratio of per-capita income and an income elasticity of 1. The average benefits of emission abatement (in 1997 US\\ per ton) are 1,800 (1,200-2300) for NOx, 3,000 (2,100-3900) for SO2, 31,900 (21,900 - 41,900) for PM, and 630 (430 - 830) for resuspended dust. Economic benefits due to carbon reduction were considered at 3.5, 10 and 20 UStCO2. Marginal abatement cost curves were constructed considering private and net costs (private less the potential sales of carbon credits) Due to the bottom-up approach to constructing the marginal cost curve, many abatement measures (like congestion tolls and CNG instead of diesel buses) amounting to 8% reduction of PM2.5 concentration, exhibit a negative private cost. If the health benefits are considered for the decision, a maximum reduction of 22% in PM2

Measuring agreement between decision support reminders: the cloud vs. the local expert.

Science.gov (United States)

Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M; Wright, Adam; Middleton, Blackford

2014-04-10

A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web service and local CDSS. The clinical reminders returned by both services were captured for analysis. Cohen's Kappa coefficient was calculated to compare the two sets of reminders. Kappa statistics were further adjusted for prevalence and bias due to the potential effects of bias in the CDS logic and prevalence in the relative small sample of patients. The cloud-based CDSS generated 965 clinical reminders for 405 patient visits over 3 months. The local CDSS returned 889 reminders for the same patient visit data. When adjusted for prevalence and bias, observed agreement varied by reminder from 0.33 (95% CI 0.24 - 0.42) to 0.99 (95% CI 0.97 - 1.00) and demonstrated almost perfect agreement for 7 of the 11 reminders. Preventive care reminders delivered by two disparate CDS systems show substantial agreement. Subtle differences in rule logic and terminology mapping appear to account for much of the discordance. Cloud-based CDSS therefore show promise, opening the door for future development and implementation in support of health care providers with limited resources for knowledge management of complex logic and rules.

Assessing the acceptability and usability of an interactive serious game in aiding treatment decisions for patients with localized prostate cancer.

Science.gov (United States)

Reichlin, Lindsey; Mani, Nithya; McArthur, Kara; Harris, Amy M; Rajan, Nithin; Dacso, Clifford C

2011-01-12

Men diagnosed with localized prostate cancer face a potentially life-altering treatment decision that can be overwhelming. Enhancing patient knowledge through education can significantly reduce feelings of uncertainty while simultaneously increasing confidence in decision making. Serious games have been shown in other populations to increase health knowledge and assist with the health decision-making process. We developed an interactive serious game, Time After Time, which translates evidence-based treatment outcome data into an accessible and understandable format that men can utilize in their prostate cancer treatment decision-making process. The game specifically aims to raise men's awareness and understanding of the impact of health-related quality of life issues associated with the major treatment options and to enrich their conversations with their health care providers. This study determined the acceptability and usability of the alpha version of Time After Time, an interactive decision aid for men diagnosed with localized prostate cancer, in order to inform future iterations of the serious game. The study employed a mixed methods approach to assess the acceptability and usability of the Time After Time serious game using qualitative focus groups and a quantitative Likert scale survey. A total of 13 men who had already completed treatment for localized prostate cancer completed the survey and participated in focus group meetings. The majority of the study participants rated Time After Time as an appropriate decision tool for localized prostate cancer and verified that it meets its goals of increasing focus on side effects and generating questions for the patient's health care team. However, participants also expressed concerns about game usability and the diversity of information covered regarding treatment options and potential treatment outcomes. Serious games are a promising approach to health education and decision support for older men. Participants

Networking CD-ROMs: The Decision Maker's Guide to Local Area Network Solutions.

Science.gov (United States)

Elshami, Ahmed M.

In an era when patrons want access to CD-ROM resources but few libraries can afford to buy multiple copies, CD-ROM local area networks (LANs) are emerging as a cost-effective way to provide shared access. To help librarians make informed decisions, this manual offers information on: (1) the basics of LANs, a "local area network primer";…

Science-based decision making in a high-risk energy production environment

Science.gov (United States)

Weiser, D. A.

2016-12-01

Energy production practices that may induce earthquakes require decisions about acceptable risk before projects begin. How much ground shaking, structural damage, infrastructure damage, or delay of geothermal power and other operations is tolerable? I review a few mitigation strategies as well as existing protocol in several U.S. states. Timely and accurate scientific information can assist in determining the costs and benefits of altering production parameters. These issues can also be addressed with probability estimates of adverse effects ("costs"), frequency of earthquakes of different sizes, and associated impacts of different magnitude earthquakes. When risk management decisions based on robust science are well-communicated to stakeholders, mitigation efforts benefit. Effective communications elements include a) the risks and benefits of different actions (e.g. using a traffic light protocol); b) the factors to consider when determining acceptable risk; and c) the probability of different magnitude events. I present a case example for The Geysers geothermal field in California, to discuss locally "acceptable" and "unacceptable" earthquakes and share nearby communities' responses to smaller and larger magnitude earthquakes. I use the USGS's "Did You Feel It?" data archive to sample how often felt events occur, and how many of those are above acceptable magnitudes (to both local residents and operators). Using this information, I develop a science-based decision-making framework, in the case of potentially risky earthquakes, for lessening seismic risk and other negative consequences. This includes assessing future earthquake probabilities based on past earthquake records. One of my goals is to help characterize uncertainties in a way that they can be managed; to this end, I present simple and accessible approaches that can be used in the decision making process.

Exchanging environmental information and decision making: developing the local Pilot Environmental Virtual Observatory with stakeholder communities

Science.gov (United States)

Mackay, E.; Beven, K.; Brewer, P.; M, Haygarth, P.; Macklin, M.; Marshall, K.; Quinn, P.; Stutter, M.; Thomas, N.; Wilkinson, M.

2012-04-01

Public participation in the development of flood risk management and river basin management plans are explicit components of both the Water Framework and Floods Directives. At the local level, involving communities in land and water management has been found to (i) aid better environmental decision making, (ii) enhance social, economic and environmental benefits, and (iii) increase a sense of ownership. Facilitating the access and exchange of information on the local environment is an important part of this new approach to the land and water management process, which also includes local community stakeholders in decisions about the design and content of the information provided. As part of the Natural Environment Research Council's pilot Environment Virtual Observatory (EVO), the Local Level group are engaging with local community stakeholders in three different catchments in the UK (the rivers Eden, Tarland and Dyfi) to start the process of developing prototype visualisation tools to address the specific land and water management issues identified in each area. Through this local collaboration, we will provide novel visualisation tools through which to communicate complex catchment science outcomes and bring together different sources of environmental data in ways that better meet end-user needs as well as facilitate a far broader participatory approach in environmental decision making. The Local Landscape Visualisation Tools are being evolved iteratively during the project to reflect the needs, interests and capabilities of a wide range of stakeholders. The tools will use the latest concepts and technologies to communicate with and provide opportunities for the provision and exchange of information between the public, government agencies and scientists. This local toolkit will reside within a wider EVO platform that will include national datasets, models and state of the art cloud computer systems. As such, local stakeholder groups are assisting the EVO

Local School Board Members Need Quality Public Information That Informs Decisions, Empowers Action. Don't Make Decisions in the Dark

Science.gov (United States)

Data Quality Campaign, 2014

2014-01-01

Local school board members need to be able to access and use high-quality data to make good decisions. Often this data is collected and stored locally, but information that is publicly reported by the state can provide additional value. Most state public reporting is designed to serve information needs, and are geared toward compliance with state…

ICT-based reforms in local government decision-making in the gram panchayats of Kerala

Directory of Open Access Journals (Sweden)

Alex K Thottunkel

2015-06-01

Full Text Available The beneficial impact of computerisation can be felt in all elements that contribute to decision-making in panchayats in the state of Kerala. However, even though computerisation is bringing about immense improvements compared to traditional administrative practices, but scope still remains for further improvement. Instead of the 'as it is' computerisation that is mostly carried out a process based approach is needed.

Advances in the application of decision theory to test-based decision making

NARCIS (Netherlands)

van der Linden, Willem J.

This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical

Effect of Wind Farm Noise on Local Residents' Decision to Adopt Mitigation Measures.

Science.gov (United States)

Botelho, Anabela; Arezes, Pedro; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M Costa

2017-07-11

Wind turbines' noise is frequently pointed out as the reason for local communities' objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes' noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people's decision to adopt mitigating measures, independently of the reported annoyance.

Effect of Wind Farm Noise on Local Residents’ Decision to Adopt Mitigation Measures

Science.gov (United States)

Botelho, Anabela; Bernardo, Carlos; Dias, Hernâni; Pinto, Lígia M. Costa

2017-01-01

Wind turbines’ noise is frequently pointed out as the reason for local communities’ objection to the installation of wind farms. The literature suggests that local residents feel annoyed by such noise and that, in many instances, this is significant enough to make them adopt noise-abatement interventions on their homes. Aiming at characterizing the relationship between wind turbine noise, annoyance, and mitigating actions, we propose a novel conceptual framework. The proposed framework posits that actual sound pressure levels of wind turbines determine individual homes’ noise-abatement decisions; in addition, the framework analyzes the role that self-reported annoyance, and perception of noise levels, plays on the relationship between actual noise pressure levels and those decisions. The application of this framework to a particular case study shows that noise perception and annoyance constitutes a link between the two. Importantly, however, noise also directly affects people’s decision to adopt mitigating measures, independently of the reported annoyance. PMID:28696404

Global analysis of dynamical decision-making models through local computation around the hidden saddle.

Directory of Open Access Journals (Sweden)

Laura Trotta

Full Text Available Bistable dynamical switches are frequently encountered in mathematical modeling of biological systems because binary decisions are at the core of many cellular processes. Bistable switches present two stable steady-states, each of them corresponding to a distinct decision. In response to a transient signal, the system can flip back and forth between these two stable steady-states, switching between both decisions. Understanding which parameters and states affect this switch between stable states may shed light on the mechanisms underlying the decision-making process. Yet, answering such a question involves analyzing the global dynamical (i.e., transient behavior of a nonlinear, possibly high dimensional model. In this paper, we show how a local analysis at a particular equilibrium point of bistable systems is highly relevant to understand the global properties of the switching system. The local analysis is performed at the saddle point, an often disregarded equilibrium point of bistable models but which is shown to be a key ruler of the decision-making process. Results are illustrated on three previously published models of biological switches: two models of apoptosis, the programmed cell death and one model of long-term potentiation, a phenomenon underlying synaptic plasticity.

Staged decision making based on probabilistic forecasting

Science.gov (United States)

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

Non-clinical influences on clinical decision-making: a major challenge to evidence-based practice.

Science.gov (United States)

Hajjaj, F M; Salek, M S; Basra, M K A; Finlay, A Y

2010-05-01

This article reviews an aspect of daily clinical practice which is of critical importance in virtually every clinical consultation, but which is seldom formally considered. Non-clinical influences on clinical decision-making profoundly affect medical decisions. These influences include patient-related factors such as socioeconomic status, quality of life and patient's expectations and wishes, physician-related factors such as personal characteristics and interaction with their professional community, and features of clinical practice such as private versus public practice as well as local management policies. This review brings together the different strands of knowledge concerning non-clinical influences on clinical decision-making. This aspect of decision-making may be the biggest obstacle to the reality of practising evidence-based medicine. It needs to be understood in order to develop clinical strategies that will facilitate the practice of evidence-based medicine.

Learning environment simulator: a tool for local decision makers and first responders

Energy Technology Data Exchange (ETDEWEB)

Leclaire, Rene J [Los Alamos National Laboratory; Hirsch, Gary B [CLE, INCORPORATED

2009-01-01

The National Infrastructure Simulation and Analysis Center (NISAC) has developed a prototype learning environment simulator (LES) based on the Critical Infrastructure Protection Decision Support System (CIPDSS) infrastructure and scenario models. The LES is designed to engage decision makers at the grass-roots level (local/city/state) to deepen their understanding of an evolving crisis, enhance their intuition and allow them to test their own strategies for events before they occur. An initial version is being developed, centered on a pandemic influenza outbreak and has been successfully tested with a group of hospital administrators and first responders. LES is not a predictive tool but rather a simulated environment allowing the user to experience the complexities of a crisis before it happens. Users can contrast various approaches to the crisis, competing with alternative strategies of their own or other participants. LES is designed to assist decision makers in making informed choices by functionally representing relevant scenarios before they occur, including impacts to critical infrastructures with their interdependencies, and estimating human health & safety and economic impacts. In this paper a brief overview of the underlying models are given followed by a description of the LES, its interface and usage and an overview of the experience testing LES with a group of hospital administrators and first responders. The paper concludes with a brief discussion of the work remaining to make LES operational.

Influence of Men’s Personality and Social Support on Treatment Decision-Making for Localized Prostate Cancer

Directory of Open Access Journals (Sweden)

Elyse Reamer

2017-01-01

Full Text Available Background. Optimal treatment for localized prostate cancer (LPC is controversial. We assessed the effects of personality, specialists seen, and involvement of spouse, family, or friends on treatment decision/decision-making qualities. Methods. We surveyed a population-based sample of men ≤ 75 years with newly diagnosed LPC about treatment choice, reasons for the choice, decision-making difficulty, satisfaction, and regret. Results. Of 160 men (71 black, 89 white, with a mean age of 61 (±7.3 years, 59% chose surgery, 31% chose radiation, and 10% chose active surveillance (AS/watchful waiting (WW. Adjusting for age, race, comorbidity, tumor risk level, and treatment status, men who consulted friends during decision-making were more likely to choose curative treatment (radiation or surgery than WW/AS (OR = 11.1, p<0.01; 8.7, p<0.01. Men who saw a radiation oncologist in addition to a urologist were more likely to choose radiation than surgery (OR = 6.0, p=0.04. Men who consulted family or friends (OR = 2.6, p<0.01; 3.7, p<0.01 experienced greater decision-making difficulty. No personality traits (pessimism, optimism, or faith were associated with treatment choice/decision-making quality measures. Conclusions. In addition to specialist seen, consulting friends increased men’s likelihood of choosing curative treatment. Consulting family or friends increased decision-making difficulty.

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

Science.gov (United States)

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

Choosing to Work? Mothers Return-to-Work Decisions, Social Class, and the Local Labor Market

Directory of Open Access Journals (Sweden)

Tiina Sihto

2015-10-01

Full Text Available The aim of this study is to examine the ways in which social class shapes the return-to-work decisions of Finnish working-class and middle-class mothers, and how these decisions are structured by the constraints and opportunities mothers face in the local labor market. The focus of the study is in the local labor market of the city of Jyväskylä. The data consist of two semi-structured focus group interviews of 14 employed mothers of below school-age children. Using the framework of “gendered moral rationalities,” the study shows that there are similarities in mothers’ experiences, while the structural constraints mothers faced when deciding about the timing of returning back to work differ. The analysis highlights that the differences were not only dependent on social class but also on the situation in the local labor market. For working-class mothers, the most crucial issue was the financial strain that their staying at home caused to their families. For middle-class mothers, finding employment opportunities that would match their educational qualifications in the local labor market had been challenging, which affected their timing of returning back to work. The paper concludes that local labor market plays an important role in mother’s return-to-work decisions and should be explored further in differing geographical contexts.

Bringing the Consumer Back in—The Motives, Perceptions, and Values behind Consumers and Rural Tourists’ Decision to Buy Local and Localized Artisan Food—A Swedish Example

Directory of Open Access Journals (Sweden)

Paulina Rytkönen

2018-04-01

Full Text Available This article highlights the motivational factors behind consumers’ and tourists’ decisions to buy local artisan cheese in Jämtland (Sweden. Empirically, the case itself diverts from the typical Franco-Mediterranean case in which both the actions of producers and consumers are embedded in historical, long-term culinary traditions and territorial features, nor is it the typical farmers’ market or another market-driven direct produce system. The main purpose is to shed light on the motivational factors behind the purchasing decision of consumers and tourists by studying the attributes that consumers embody in the products. The article is based on two consumer surveys/short interviews, the first conducted in June 2012 and the second in February 2017. The results were tested against/related to the wider local food discussion conceptualized through four types of attributes. Namely, intrinsic and extrinsic attributes; post-modernity and environmental attributes; geographical and territorial attributes; and local and rural development attributes. The results in this article clearly show that consumers value a combination of different attributes from both market-driven direct produce systems and close typicity systems. Therefore, the construction of proximity from the point of view of the consumer can be derived from a complex set of attributes and motivational factors not normally highlighted in the localized food discussion.

Optimal policy for value-based decision-making.

Science.gov (United States)

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-08-18

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

Science.gov (United States)

Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C

2014-01-01

Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.

Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

Directory of Open Access Journals (Sweden)

Nicholas R Magliocca

Full Text Available Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model

Decision-Making Based on Emotional Images

OpenAIRE

Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

2011-01-01

The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward...

Decision making based on emotional images

OpenAIRE

Kentaro eKatahira; Kentaro eKatahira; Kentaro eKatahira; Tomomi eFujimura; Tomomi eFujimura; Kazuo eOkanoya; Kazuo eOkanoya; Kazuo eOkanoya; Masato eOkada; Masato eOkada; Masato eOkada

2011-01-01

The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward...

An exploratory study identifying where local government public health decision makers source their evidence for policy.

Science.gov (United States)

Stoneham, Melissa; Dodds, James

2014-08-01

The Western Australian (WA) Public Health Bill will replace the antiquated Health Act 1911. One of the proposed clauses of the Bill requires all WA local governments to develop a Public Health Plan. The Bill states that Public Health Plans should be based on evidence from all levels, including national and statewide priorities, community needs, local statistical evidence, and stakeholder data. This exploratory study, which targeted 533 WA local government officers, aimed to identify the sources of evidence used to generate the list of public health risks to be included in local government Public Health Plans. The top four sources identified for informing local policy were: observation of the consequences of the risks in the local community (24.5%), statewide evidence (17.6%), local evidence (17.6%) and coverage in local media (16.2%). This study confirms that both hard and soft data are used to inform policy decisions at the local level. Therefore, the challenge that this study has highlighted is in the definition or constitution of evidence. SO WHAT? Evidence is critical to the process of sound policy development. This study highlights issues associated with what actually constitutes evidence in the policy development process at the local government level. With the exception of those who work in an extremely narrow field, it is difficult for local government officers, whose role includes policymaking, to read the vast amount of information that has been published in their area of expertise. For those who are committed to the notion of evidence-based policymaking, as advocated within the WA Public Health Bill, this presents a considerable challenge.

Risk-based emergency decision support

International Nuclear Information System (INIS)

Koerte, Jens

2003-01-01

In the present paper we discuss how to assist critical decisions taken under complex, contingent circumstances, with a high degree of uncertainty and short time frames. In such sharp-end decision regimes, standard rule-based decision support systems do not capture the complexity of the situation. At the same time, traditional risk analysis is of little use due to variability in the specific circumstances. How then, can an organisation provide assistance to, e.g. pilots in dealing with such emergencies? A method called 'contingent risk and decision analysis' is presented, to provide decision support for decisions under variable circumstances and short available time scales. The method consists of nine steps of definition, modelling, analysis and criteria definition to be performed 'off-line' by analysts, and procedure generation to transform the analysis result into an operational decision aid. Examples of pilots' decisions in response to sudden vibration in offshore helicopter transport method are used to illustrate the approach

Implementation of a web-based national child health-care programme in a local context: A complex facilitator role.

Science.gov (United States)

Tell, Johanna; Olander, Ewy; Anderberg, Peter; Berglund, Johan Sanmartin

2018-02-01

The aim of this study was to investigate child health-care coordinators' experiences of being a facilitator for the implementation of a new national child health-care programme in the form of a web-based national guide. The study was based on eight remote, online focus groups, using Skype for Business. A qualitative content analysis was performed. The analysis generated three categories: adapt to a local context, transition challenges and led by strong incentives. There were eight subcategories. In the latent analysis, the theme 'Being a facilitator: a complex role' was formed to express the child health-care coordinators' experiences. Facilitating a national guideline or decision support in a local context is a complex task that requires an advocating and mediating role. For successful implementation, guidelines and decision support, such as a web-based guide and the new child health-care programme, must match professional consensus and needs and be seen as relevant by all. Participation in the development and a strong bottom-up approach was important, making the web-based guide and the programme relevant to whom it is intended to serve, and for successful implementation. The study contributes valuable knowledge when planning to implement a national web-based decision support and policy programme in a local health-care context.

Reasoning in explanation-based decision making.

Science.gov (United States)

Pennington, N; Hastie, R

1993-01-01

A general theory of explanation-based decision making is outlined and the multiple roles of inference processes in the theory are indicated. A typology of formal and informal inference forms, originally proposed by Collins (1978a, 1978b), is introduced as an appropriate framework to represent inferences that occur in the overarching explanation-based process. Results from the analysis of verbal reports of decision processes are presented to demonstrate the centrality and systematic character of reasoning in a representative legal decision-making task.

A cloud based tool for knowledge exchange on local scale flood risk.

Science.gov (United States)

Wilkinson, M E; Mackay, E; Quinn, P F; Stutter, M; Beven, K J; MacLeod, C J A; Macklin, M G; Elkhatib, Y; Percy, B; Vitolo, C; Haygarth, P M

2015-09-15

There is an emerging and urgent need for new approaches for the management of environmental challenges such as flood hazard in the broad context of sustainability. This requires a new way of working which bridges disciplines and organisations, and that breaks down science-culture boundaries. With this, there is growing recognition that the appropriate involvement of local communities in catchment management decisions can result in multiple benefits. However, new tools are required to connect organisations and communities. The growth of cloud based technologies offers a novel way to facilitate this process of exchange of information in environmental science and management; however, stakeholders need to be engaged with as part of the development process from the beginning rather than being presented with a final product at the end. Here we present the development of a pilot Local Environmental Virtual Observatory Flooding Tool. The aim was to develop a cloud based learning platform for stakeholders, bringing together fragmented data, models and visualisation tools that will enable these stakeholders to make scientifically informed environmental management decisions at the local scale. It has been developed by engaging with different stakeholder groups in three catchment case studies in the UK and a panel of national experts in relevant topic areas. However, these case study catchments are typical of many northern latitude catchments. The tool was designed to communicate flood risk in locally impacted communities whilst engaging with landowners/farmers about the risk of runoff from the farmed landscape. It has been developed iteratively to reflect the needs, interests and capabilities of a wide range of stakeholders. The pilot tool combines cloud based services, local catchment datasets, a hydrological model and bespoke visualisation tools to explore real time hydrometric data and the impact of flood risk caused by future land use changes. The novel aspects of the

How normative interpretations of climate risk assessment affect local decision-making: an exploratory study at the city scale in Cork, Ireland

Science.gov (United States)

McDermott, T. K. J.; Surminski, S.

2018-06-01

Urban areas already suffer substantial losses in both economic and human terms from climate-related disasters. These losses are anticipated to grow substantially, in part as a result of the impacts of climate change. In this paper, we investigate the process of translating climate risk data into action for the city level. We apply a commonly used decision-framework as our backdrop and explore where in this process climate risk assessment and normative political judgements intersect. We use the case of flood risk management in Cork city in Ireland to investigate what is needed for translating risk assessment into action at the local city level. Evidence presented is based on focus group discussions at two stakeholder workshops, and a series of individual meetings and phone-discussions with stakeholders involved in local decision-making related to flood risk management and adaptation to climate change, in Ireland. Respondents were chosen on the basis of their expertise or involvement in the decision-making processes locally and nationally. Representatives of groups affected by flood risk and flood risk management and climate adaptation efforts were also included. The Cork example highlights that, despite ever more accurate data and an increasing range of theoretical approaches available to local decision-makers, it is the normative interpretation of this information that determines what action is taken. The use of risk assessments for decision-making is a process that requires normative decisions, such as setting `acceptable risk levels' and identifying `adequate' protection levels, which will not succeed without broader buy-in and stakeholder participation. Identifying and embracing those normative views up-front could strengthen the urban adaptation process-this may, in fact, turn out to be the biggest advantage of climate risk assessment: it offers an opportunity to create a shared understanding of the problem and enables an informed evaluation and discussion of

How normative interpretations of climate risk assessment affect local decision-making: an exploratory study at the city scale in Cork, Ireland.

Science.gov (United States)

McDermott, T K J; Surminski, S

2018-06-13

Urban areas already suffer substantial losses in both economic and human terms from climate-related disasters. These losses are anticipated to grow substantially, in part as a result of the impacts of climate change. In this paper, we investigate the process of translating climate risk data into action for the city level. We apply a commonly used decision-framework as our backdrop and explore where in this process climate risk assessment and normative political judgements intersect. We use the case of flood risk management in Cork city in Ireland to investigate what is needed for translating risk assessment into action at the local city level. Evidence presented is based on focus group discussions at two stakeholder workshops, and a series of individual meetings and phone-discussions with stakeholders involved in local decision-making related to flood risk management and adaptation to climate change, in Ireland. Respondents were chosen on the basis of their expertise or involvement in the decision-making processes locally and nationally. Representatives of groups affected by flood risk and flood risk management and climate adaptation efforts were also included. The Cork example highlights that, despite ever more accurate data and an increasing range of theoretical approaches available to local decision-makers, it is the normative interpretation of this information that determines what action is taken. The use of risk assessments for decision-making is a process that requires normative decisions, such as setting 'acceptable risk levels' and identifying 'adequate' protection levels, which will not succeed without broader buy-in and stakeholder participation. Identifying and embracing those normative views up-front could strengthen the urban adaptation process-this may, in fact, turn out to be the biggest advantage of climate risk assessment: it offers an opportunity to create a shared understanding of the problem and enables an informed evaluation and discussion of

Decision-making based on emotional images.

Science.gov (United States)

Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

2011-01-01

The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants' choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the "reward value" of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants' choice data, we used reinforcement learning models that have successfully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures) was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

Decision making based on emotional images

Directory of Open Access Journals (Sweden)

Kentaro eKatahira

2011-10-01

Full Text Available The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the reward value of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants’ choice data, we used reinforcement learning models that have success- fully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

Iowa pavement asset management decision-making framework.

Science.gov (United States)

2015-10-01

Most local agencies in Iowa currently make their pavement treatment decisions based on their limited experience due primarily to : lack of a systematic decision-making framework and a decision-aid tool. The lack of objective condition assessment data...

Health decision making: lynchpin of evidence-based practice.

Science.gov (United States)

Spring, Bonnie

2008-01-01

Health decision making is both the lynchpin and the least developed aspect of evidence-based practice. The evidence-based practice process requires integrating the evidence with consideration of practical resources and patient preferences and doing so via a process that is genuinely collaborative. Yet, the literature is largely silent about how to accomplish integrative, shared decision making. for evidence-based practice are discussed for 2 theories of clinician decision making (expected utility and fuzzy trace) and 2 theories of patient health decision making (transtheoretical model and reasoned action). Three suggestions are offered. First, it would be advantageous to have theory-based algorithms that weight and integrate the 3 data strands (evidence, resources, preferences) in different decisional contexts. Second, patients, not providers, make the decisions of greatest impact on public health, and those decisions are behavioral. Consequently, theory explicating how provider-patient collaboration can influence patient lifestyle decisions made miles from the provider's office is greatly needed. Third, although the preponderance of data on complex decisions supports a computational approach, such an approach to evidence-based practice is too impractical to be widely applied at present. More troublesomely, until patients come to trust decisions made computationally more than they trust their providers' intuitions, patient adherence will remain problematic. A good theory of integrative, collaborative health decision making remains needed.

Parallel constraint satisfaction in memory-based decisions.

Science.gov (United States)

Glöckner, Andreas; Hodges, Sara D

2011-01-01

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Effort-Based Decision-Making in Schizophrenia.

Science.gov (United States)

Culbreth, Adam J; Moran, Erin K; Barch, Deanna M

2018-08-01

Motivational impairment has long been associated with schizophrenia but the underlying mechanisms are not clearly understood. Recently, a small but growing literature has suggested that aberrant effort-based decision-making may be a potential contributory mechanism for motivational impairments in psychosis. Specifically, multiple reports have consistently demonstrated that individuals with schizophrenia are less willing than healthy controls to expend effort to obtain rewards. Further, this effort-based decision-making deficit has been shown to correlate with severity of negative symptoms and level of functioning, in many but not all studies. In the current review, we summarize this literature and discuss several factors that may underlie aberrant effort-based decision-making in schizophrenia.

Optimization of decision rules based on dynamic programming approach

KAUST Repository

Zielosko, Beata

2014-01-14

This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.

Validating evidence based decision making in health care

DEFF Research Database (Denmark)

Nüssler, Emil Karl; Eskildsen, Jacob Kjær; Håkonsson, Dorthe Døjbak

Surgeons who perform prolapse surgeries face the dilemma of choosing to use mesh, with its assumed benefits, and the risks associated with mesh. In this paper, we examine whether decisions to use mesh is evidence based. Based on data of 30,398 patients from the Swedish National Quality Register o...... are highly influenced by the geographical placement of surgeons. Therfore, decisions to use mesh are boundedly rationality, rather than rational.......Surgeons who perform prolapse surgeries face the dilemma of choosing to use mesh, with its assumed benefits, and the risks associated with mesh. In this paper, we examine whether decisions to use mesh is evidence based. Based on data of 30,398 patients from the Swedish National Quality Register...... of Gynecological Surgery we examine factors related to decisions to use mesh. Our results indicate that decisions to use mesh are not evidence based, and cannot be explained neither by FDA safety communications, nor by medical conditions usually assumed to predict its usage. Instead, decisions to use mesh...

FlooDSuM - a decision support methodology for assisting local authorities in flood situations

Science.gov (United States)

Schwanbeck, Jan; Weingartner, Rolf

2014-05-01

Decision making in flood situations is a difficult task, especially in small to medium-sized mountain catchments (30 - 500 km2) which are usually characterized by complex topography, high drainage density and quick runoff response to rainfall events. Operating hydrological models driven by numerical weather prediction systems, which have a lead-time of several hours up to few even days, would be beneficial in this case as time for prevention could be gained. However, the spatial and quantitative accuracy of such meteorological forecasts usually decrease with increasing lead-time. In addition, the sensitivity of rainfall-runoff models to inaccuracies in estimations of areal rainfall increases with decreasing catchment size. Accordingly, decisions on flood alerts should ideally be based on areal rainfall from high resolution and short-term numerical weather prediction, nowcasts or even real-time measurements, which is transformed into runoff by a hydrological model. In order to benefit from the best possible rainfall data while retaining enough time for alerting and for prevention, the hydrological model should be fast and easily applicable by decision makers within local authorities themselves. The proposed decision support methodology FlooDSuM (Flood Decision Support Methodology) aims to meet those requirements. Applying FlooDSuM, a few successive binary decisions of increasing complexity have to be processed following a flow-chart-like structure. Prepared data and straightforwardly applicable tools are provided for each of these decisions. Maps showing the current flood disposition are used for the first step. While danger of flooding cannot be excluded more and more complex and time consuming methods will be applied. For the final decision, a set of scatter-plots relating areal precipitation to peak flow is provided. These plots take also further decisive parameters into account such as storm duration, distribution of rainfall intensity in time as well as the

Risk-based decision analysis for groundwater operable units

International Nuclear Information System (INIS)

Chiaramonte, G.R.

1995-01-01

This document proposes a streamlined approach and methodology for performing risk assessment in support of interim remedial measure (IRM) decisions involving the remediation of contaminated groundwater on the Hanford Site. This methodology, referred to as ''risk-based decision analysis,'' also supports the specification of target cleanup volumes and provides a basis for design and operation of the groundwater remedies. The risk-based decision analysis can be completed within a short time frame and concisely documented. The risk-based decision analysis is more versatile than the qualitative risk assessment (QRA), because it not only supports the need for IRMs, but also provides criteria for defining the success of the IRMs and provides the risk-basis for decisions on final remedies. For these reasons, it is proposed that, for groundwater operable units, the risk-based decision analysis should replace the more elaborate, costly, and time-consuming QRA

Barriers to and Facilitators of Evidence-Based Decision Making at the Point of Care

Directory of Open Access Journals (Sweden)

Ann S. O’Malley MD, MPH

2016-07-01

Full Text Available Introduction: Physicians vary widely in how they treat some health conditions, despite strong evidence favoring certain treatments over others. We examined physicians’ perspectives on factors that support or hinder evidence-based decisions and the implications for delivery systems, payers, and policymakers. Methods: We used Choosing Wisely ® recommendations to create four clinical vignettes for common types of decisions. We conducted semi-structured interviews with 36 specialists to identify factors that support or hinder evidence-based decisions. We examined these factors using a conceptual framework that includes six levels: patients, physicians, practice sites, organizations, networks and hospital affiliations, and the local market. In this model, population characteristics and payer and regulatory factors interact to influence decisions. Results: Patient openness to behavior modification and expectations, facilitated and hindered physicians in making evidence-based recommendations. Physicians’ communication skills were the most commonly mentioned facilitator. Practice site, organization, and hospital system barriers included measures of emergency department throughput, the order in which test options are listed in electronic health records (EHR, lack of relevant decision support in EHRs, and payment incentives that maximize billing and encourage procedures rather than medical management or counseling patients on behavior change. Factors from different levels interacted to undermine evidence-based care. Most physicians received billing feedback, but quality metrics on evidence-based service use were nonexistent for the four decisions in this study. Conclusions and Implications: Additional research and quality improvement may help to modify delivery systems to overcome barriers at multiple levels. Enhancing provider communication skills, improving decision support in EHRs, modifying workflows, and refining the design and interpretation of

Protocol-based care: the standardisation of decision-making?

Science.gov (United States)

Rycroft-Malone, Jo; Fontenla, Marina; Seers, Kate; Bick, Debra

2009-05-01

To explore how protocol-based care affects clinical decision-making. In the context of evidence-based practice, protocol-based care is a mechanism for facilitating the standardisation of care and streamlining decision-making through rationalising the information with which to make judgements and ultimately decisions. However, whether protocol-based care does, in the reality of practice, standardise decision-making is unknown. This paper reports on a study that explored the impact of protocol-based care on nurses' decision-making. Theoretically informed by realistic evaluation and the promoting action on research implementation in health services framework, a case study design using ethnographic methods was used. Two sites were purposively sampled; a diabetic and endocrine unit and a cardiac medical unit. Within each site, data collection included observation, postobservation semi-structured interviews with staff and patients, field notes, feedback sessions and document review. Data were inductively and thematically analysed. Decisions made by nurses in both sites were varied according to many different and interacting factors. While several standardised care approaches were available for use, in reality, a variety of information sources informed decision-making. The primary approach to knowledge exchange and acquisition was person-to-person; decision-making was a social activity. Rarely were standardised care approaches obviously referred to; nurses described following a mental flowchart, not necessarily linked to a particular guideline or protocol. When standardised care approaches were used, it was reported that they were used flexibly and particularised. While the logic of protocol-based care is algorithmic, in the reality of clinical practice, other sources of information supported nurses' decision-making process. This has significant implications for the political goal of standardisation. The successful implementation and judicious use of tools such as

Evidence-based surgery: Dissemination, communication, decision aids

NARCIS (Netherlands)

Knops, A.M.

2013-01-01

Surgeons are expected to make treatment decisions that are based on the best available evidence. Moreover, they are called to recognise that important decisions should also be shared with patients. While dissemination of evidence-based surgery and communication of evidence to patients have been

Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform.

Science.gov (United States)

Hoffman, Aubri S; Llewellyn-Thomas, Hilary A; Tosteson, Anna N A; O'Connor, Annette M; Volk, Robert J; Tomek, Ivan M; Andrews, Steven B; Bartels, Stephen J

2014-12-12

Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web-based

The administrative protection of local planning authorities against decisions on a higher level

International Nuclear Information System (INIS)

Steinberg, R.

1982-01-01

The author discusses governmental planning that influences local planning's scope of organization and limits local sovereinty which is established as a guarantee for local self-government. Those conflicts occurr in the case of country planning, various specific plans (such as road construction an tower and country planning, nature conservation and landscape planning), and planning permits (decisions to establish new plans according to civil air regulations and permits according to atomic law). Then the author describes the possibilities of legal protection in the case of an action for avoidance which he illustrates with some conflicting cases, laying special emphasis on the right of action of a community, and on the justification of the action for avoidance. (HSCH) [de

Local Choices: Rationality and the Contextuality of Decision-Making

Science.gov (United States)

Vlaev, Ivo

2018-01-01

Rational explanation is ubiquitous in psychology and social sciences, ranging from rational analysis, expectancy-value theories, ideal observer models, mental logic to probabilistic frameworks, rational choice theory, and informal “folk psychological” explanation. However, rational explanation appears to be challenged by apparently systematic irrationality observed in psychological experiments, especially in the field of judgement and decision-making (JDM). Here, it is proposed that the experimental results require not that rational explanation should be rejected, but that rational explanation is local, i.e., within a context. Thus, rational models need to be supplemented with a theory of contextual shifts. We review evidence in JDM that patterns of choices are often consistent within contexts, but unstable between contexts. We also demonstrate that for a limited, though reasonably broad, class of decision-making domains, recent theoretical models can be viewed as providing theories of contextual shifts. It is argued that one particular significant source of global inconsistency arises from a cognitive inability to represent absolute magnitudes, whether for perceptual variables, utilities, payoffs, or probabilities. This overall argument provides a fresh perspective on the scope and limits of human rationality. PMID:29301289

Local Choices: Rationality and the Contextuality of Decision-Making.

Science.gov (United States)

Vlaev, Ivo

2018-01-02

Rational explanation is ubiquitous in psychology and social sciences, ranging from rational analysis, expectancy-value theories, ideal observer models, mental logic to probabilistic frameworks, rational choice theory, and informal "folk psychological" explanation. However, rational explanation appears to be challenged by apparently systematic irrationality observed in psychological experiments, especially in the field of judgement and decision-making (JDM). Here, it is proposed that the experimental results require not that rational explanation should be rejected, but that rational explanation is local , i.e., within a context. Thus, rational models need to be supplemented with a theory of contextual shifts. We review evidence in JDM that patterns of choices are often consistent within contexts, but unstable between contexts. We also demonstrate that for a limited, though reasonably broad, class of decision-making domains, recent theoretical models can be viewed as providing theories of contextual shifts. It is argued that one particular significant source of global inconsistency arises from a cognitive inability to represent absolute magnitudes, whether for perceptual variables, utilities, payoffs, or probabilities. This overall argument provides a fresh perspective on the scope and limits of human rationality.

A user-friendly mathematical modelling web interface to assist local decision making in the fight against drug-resistant tuberculosis.

Science.gov (United States)

Ragonnet, Romain; Trauer, James M; Denholm, Justin T; Marais, Ben J; McBryde, Emma S

2017-05-30

Multidrug-resistant and rifampicin-resistant tuberculosis (MDR/RR-TB) represent an important challenge for global tuberculosis (TB) control. The high rates of MDR/RR-TB observed among re-treatment cases can arise from diverse pathways: de novo amplification during initial treatment, inappropriate treatment of undiagnosed MDR/RR-TB, relapse despite appropriate treatment, or reinfection with MDR/RR-TB. Mathematical modelling allows quantification of the contribution made by these pathways in different settings. This information provides valuable insights for TB policy-makers, allowing better contextualised solutions. However, mathematical modelling outputs need to consider local data and be easily accessible to decision makers in order to improve their usefulness. We present a user-friendly web-based modelling interface, which can be used by people without technical knowledge. Users can input their own parameter values and produce estimates for their specific setting. This innovative tool provides easy access to mathematical modelling outputs that are highly relevant to national TB control programs. In future, the same approach could be applied to a variety of modelling applications, enhancing local decision making.

Integration of Local Ecological Knowledge and Conventional Science: a Study of Seven Community-Based Forestry Organizations in the USA

Directory of Open Access Journals (Sweden)

Heidi L. Ballard

2008-12-01

Full Text Available Natural resource management decisions can be based on incomplete knowledge when they lack scientific research, monitoring, and assessment and/or simultaneously fail to draw on local ecological knowledge. Many community-based forestry organizations in the United States attempt to address these knowledge gaps with an integrated ecological stewardship approach that balances ecological, social, and economic goals. This paper examines the use and integration of local knowledge and conventional science in ecological stewardship and monitoring by seven community-based forestry demonstration projects. Through document reviews and interviews with both participants and partners of all of these community-based organizations, we found that all the community-based forestry groups incorporated local ecological knowledge into many aspects of their management or monitoring activities, such as collaboratively designing monitoring programs with local ranchers, forest workers, and residents; involving local people in collecting data and interpreting results; and documenting the local ecological knowledge of private forest landowners, long-time residents, and harvesters of nontimber forest products. We found that all the groups also used conventional science to design or conduct ecological assessments, monitoring, or research. We also found evidence, in the form of changes in attitudes on the part of local people and conventional scientists and jointly produced reports, that the two types of knowledge were integrated by all groups. These findings imply that community-based forestry groups are redistributing the power of conventional science through the use of diverse knowledge sources. Still, several obstacles prevented some local, traditionally under-represented groups from being significantly involved in monitoring and management decisions, and their knowledge has not yet been consistently incorporated.

Navigating the boundary of science for decision making at the state and local level

Science.gov (United States)

Gonzales, L. M.; Wood, C.; Boland, M. A.; Rose, C. A.

2015-12-01

Scientific information should play a vital role in many decision making processes, yet issues incorporating geoscience information often arise due to inherent differences between how scientists and decision makers operate. Decision makers and scientists have different priorities, produce work at different rates, and often lack an understanding of each others' institutional constraints. Boundary organizations, entities that facilitate collaboration and information flow across traditional boundaries such as that between scientists and decision makers, are in a unique position to improve the dialogue between disparate groups. The American Geosciences Institute (AGI), a nonprofit federation of 50 geoscience societies and organizations, is linking the geoscience and decision-making communities through its Critical Issues Program. AGI's Critical Issues program has first-hand experience in improving the transfer of information across the science-decision making boundary, particularly in areas pertaining to water resources and hazards. This presentation will focus on how, by collaborating with organizations representing the decision making and geoscience communities to inform our program development, we have created our three main content types - website, webinar series, and research database - to better meet the needs of the decision-making process. The program presents existing geoscience information in a way that makes the interconnected nature of geoscience topics more easily understood, encourages discussion between the scientific and decision-making communities, and has established a trusted source of impartial geoscience information. These efforts have focused on state and local decision makers—groups that increasingly influence climate and risk-related decisions, yet often lack the resources to access and understand geoscience information.

Exploring the science–policy interface on climate change: The role of the IPCC in informing local decision-making in the UK

OpenAIRE

Candice Howarth; James Painter

2016-01-01

Building on the Intergovernmental Panel on Climate Change’s (IPCC) review of\\ud how to make its Assessment Reports (ARs) more accessible in the future, the research\\ud reported here assesses the extent to which the ARs are a useful tool through which scientific\\ud advice informs local decision-making on climate change in the United Kingdom. Results from\\ud interviews with local policy representatives and three workshops with UK academics, practitioners\\ud and local decision makers are present...

San Jose, California: Evaluating Local Solar Energy Generation Potential (City Energy: From Data to Decisions)

Energy Technology Data Exchange (ETDEWEB)

Office of Strategic Programs, Strategic Priorities and Impact Analysis Team

2017-09-29

This fact sheet "San Jose, California: Evaluating Local Solar Energy Generation Potential" explains how the City of San Jose used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

Decision and Inhibitory Rule Optimization for Decision Tables with Many-valued Decisions

KAUST Repository

Alsolami, Fawaz

2016-04-25

‘If-then’ rule sets are one of the most expressive and human-readable knowledge representations. This thesis deals with optimization and analysis of decision and inhibitory rules for decision tables with many-valued decisions. The most important areas of applications are knowledge extraction and representation. The benefit of considering inhibitory rules is connected with the fact that in some situations they can describe more knowledge than the decision ones. Decision tables with many-valued decisions arise in combinatorial optimization, computational geometry, fault diagnosis, and especially under the processing of data sets. In this thesis, various examples of real-life problems are considered which help to understand the motivation of the investigation. We extend relatively simple results obtained earlier for decision rules over decision tables with many-valued decisions to the case of inhibitory rules. The behavior of Shannon functions (which characterize complexity of rule systems) is studied for finite and infinite information systems, for global and local approaches, and for decision and inhibitory rules. The extensions of dynamic programming for the study of decision rules over decision tables with single-valued decisions are generalized to the case of decision tables with many-valued decisions. These results are also extended to the case of inhibitory rules. As a result, we have algorithms (i) for multi-stage optimization of rules relative to such criteria as length or coverage, (ii) for counting the number of optimal rules, (iii) for construction of Pareto optimal points for bi-criteria optimization problems, (iv) for construction of graphs describing relationships between two cost functions, and (v) for construction of graphs describing relationships between cost and accuracy of rules. The applications of created tools include comparison (based on information about Pareto optimal points) of greedy heuristics for bi-criteria optimization of rules

Model-based synthesis of locally contingent responses to global market signals

Science.gov (United States)

Magliocca, N. R.

2015-12-01

Rural livelihoods and the land systems on which they depend are increasingly influenced by distant markets through economic globalization. Place-based analyses of land and livelihood system sustainability must then consider both proximate and distant influences on local decision-making. Thus, advancing land change theory in the context of economic globalization calls for a systematic understanding of the general processes as well as local contingencies shaping local responses to global signals. Synthesis of insights from place-based case studies of land and livelihood change is a path forward for developing such systematic knowledge. This paper introduces a model-based synthesis approach to investigating the influence of local socio-environmental and agent-level factors in mediating land-use and livelihood responses to changing global market signals. A generalized agent-based modeling framework is applied to six case-study sites that differ in environmental conditions, market access and influence, and livelihood settings. The largest modeled land conversions and livelihood transitions to market-oriented production occurred in sties with relatively productive agricultural land and/or with limited livelihood options. Experimental shifts in the distributions of agents' risk tolerances generally acted to attenuate or amplify responses to changes in global market signals. Importantly, however, responses of agents at different points in the risk tolerance distribution varied widely, with the wealth gap growing wider between agents with higher or lower risk tolerance. These results demonstrate model-based synthesis is a promising approach to overcome many of the challenges of current synthesis methods in land change science, and to identify generalized as well as locally contingent responses to global market signals.

Risk-Based Decision Making for Deterioration Processes Using POMDP

DEFF Research Database (Denmark)

Nielsen, Jannie Sønderkær; Sørensen, John Dalsgaard

2015-01-01

This paper proposes a method for risk-based decision making for maintenance of deteriorating components, based on the partially observable Markov decision process (POMDP). Unlike most methods, the decision polices do not need to be stationary and can vary according to seasons and near the end...

Information integration in perceptual and value-based decisions

OpenAIRE

Tsetsos, K.

2012-01-01

Research on the psychology and neuroscience of simple, evidence-based choices has led to an impressive progress in capturing the underlying mental processes as optimal mechanisms that make the fastest decision for a specified accuracy. The idea that decision-making is an optimal process stands in contrast with findings in more complex, motivation-based decisions, focussed on multiple goals with trade-offs. Here, a number of paradoxical and puzzling choice behaviours have been r...

Frame-based safety analysis approach for decision-based errors

International Nuclear Information System (INIS)

Fan, Chin-Feng; Yihb, Swu

1997-01-01

A frame-based approach is proposed to analyze decision-based errors made by automatic controllers or human operators due to erroneous reference frames. An integrated framework, Two Frame Model (TFM), is first proposed to model the dynamic interaction between the physical process and the decision-making process. Two important issues, consistency and competing processes, are raised. Consistency between the physical and logic frames makes a TFM-based system work properly. Loss of consistency refers to the failure mode that the logic frame does not accurately reflect the state of the controlled processes. Once such failure occurs, hazards may arise. Among potential hazards, the competing effect between the controller and the controlled process is the most severe one, which may jeopardize a defense-in-depth design. When the logic and physical frames are inconsistent, conventional safety analysis techniques are inadequate. We propose Frame-based Fault Tree; Analysis (FFTA) and Frame-based Event Tree Analysis (FETA) under TFM to deduce the context for decision errors and to separately generate the evolution of the logical frame as opposed to that of the physical frame. This multi-dimensional analysis approach, different from the conventional correctness-centred approach, provides a panoramic view in scenario generation. Case studies using the proposed techniques are also given to demonstrate their usage and feasibility

Integrating Indigenous Traditional, Local and Scientific Knowledge for Improved Management, Policy and Decision-Making in Reindeer Husbandry in the Russian Arctic

Science.gov (United States)

Maynard, Nancy G.; Yurchak, Boris; Turi, Johan Mathis; Mathiesen, Svein D.; Aissi-Wespi, Rita L.

2004-01-01

As scientists and policy-makers from both indigenous and non-indigenous communities begin to build closer partnerships to address common sustainability issues such as the health impacts of climate change and anthropogenic activities, it becomes increasingly important to create shared information management systems which integrate all relevant factors for optimal information sharing and decision-making. This paper describes a new GIs-based system being designed to bring local and indigenous traditional knowledge together with scientific data and information, remote sensing, and information technologies to address health-related environment, weather, climate, pollution and land use change issues for improved decision/policy-making for reindeer husbandry. The system is building an easily-accessible archive of relevant current and historical, traditional, local and remotely-sensed and other data and observations for shared analysis, measuring, and monitoring parameters of interest. Protection of indigenous culturally sensitive information will be respected through appropriate data protocols. A mechanism which enables easy information sharing among all participants, which is real time and geo-referenced and which allows interconnectivity with remote sites is also being designed into the system for maximum communication among partners. A preliminary version of our system will be described for a Russian reindeer test site, which will include a combination of indigenous knowledge about local conditions and issues, remote sensing and ground-based data on such parameters as the vegetation state and distribution, snow cover, temperature, ice condition, and infrastructure.

Treatment Decision Regret Among Long-Term Survivors of Localized Prostate Cancer: Results From the Prostate Cancer Outcomes Study.

Science.gov (United States)

Hoffman, Richard M; Lo, Mary; Clark, Jack A; Albertsen, Peter C; Barry, Michael J; Goodman, Michael; Penson, David F; Stanford, Janet L; Stroup, Antoinette M; Hamilton, Ann S

2017-07-10

Purpose To determine the demographic, clinical, decision-making, and quality-of-life factors that are associated with treatment decision regret among long-term survivors of localized prostate cancer. Patients and Methods We evaluated men who were age ≤ 75 years when diagnosed with localized prostate cancer between October 1994 and October 1995 in one of six SEER tumor registries and who completed a 15-year follow-up survey. The survey obtained demographic, socioeconomic, and clinical data and measured treatment decision regret, informed decision making, general- and disease-specific quality of life, health worry, prostate-specific antigen (PSA) concern, and outlook on life. We used multivariable logistic regression analyses to identify factors associated with regret. Results We surveyed 934 participants, 69.3% of known survivors. Among the cohort, 59.1% had low-risk tumor characteristics (PSA decision regret: 8.2% of those whose disease was managed conservatively, 15.0% of those who received surgery, and 16.6% of those who underwent radiotherapy. Factors associated with regret on multivariable analysis included reporting moderate or big sexual function bother (reported by 39.0%; OR, 2.77; 95% CI, 1.51 to 5.0), moderate or big bowel function bother (reported by 7.7%; OR, 2.32; 95% CI, 1.04 to 5.15), and PSA concern (mean score 52.8; OR, 1.01 per point change; 95% CI, 1.00 to 1.02). Increasing age at diagnosis and report of having made an informed treatment decision were inversely associated with regret. Conclusion Regret was a relatively infrequently reported outcome among long-term survivors of localized prostate cancer; however, our results suggest that better informing men about treatment options, in particular, conservative treatment, might help mitigate long-term regret. These findings are timely for men with low-risk cancers who are being encouraged to consider active surveillance.

Seminal Quality Prediction Using Clustering-Based Decision Forests

Directory of Open Access Journals (Sweden)

Hong Wang

2014-08-01

Full Text Available Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.

MMPI-based employment decisions for high-risk positions in nuclear power settings

Energy Technology Data Exchange (ETDEWEB)

Wilikofsky, A.S.

1986-01-01

To asses the feasibility of using the Minnesota Multiphasic Personality Inventory (MMPI) as a personnel screening device for high-risk occupations, the test protocols of 735 applicants to and employees of the nuclear facilities owned by a southeastern utility were obtained. Institutional information on initial screening, hiring, and follow-up status was provided. MMPI data were processed to yield pass-and-fail screening decisions using a commercially available computer-based test interpretation system and a locally developed (NC) clerical interpretive system. The latter method was applied both with and without K corrections to component scores. The clerical system using K-corrected scores produced the largest number of true and false positives. The same rules, using uncorrected scores, produced the greatest number of false negatives. The computer-based system produced the most-acceptable set of decisions overall, striking a balance between these two kinds of errors. It was concluded that, when assessed against the available criterion information, the MMPI could not be recommended as a screening device. However, due to serious limitations inherent in these data, further study is needed.

MMPI-based employment decisions for high-risk positions in nuclear power settings

International Nuclear Information System (INIS)

Wilikofsky, A.S.

1986-01-01

To asses the feasibility of using the Minnesota Multiphasic Personality Inventory (MMPI) as a personnel screening device for high-risk occupations, the test protocols of 735 applicants to and employees of the nuclear facilities owned by a southeastern utility were obtained. Institutional information on initial screening, hiring, and follow-up status was provided. MMPI data were processed to yield pass-and-fail screening decisions using a commercially available computer-based test interpretation system and a locally developed (NC) clerical interpretive system. The latter method was applied both with and without K corrections to component scores. The clerical system using K-corrected scores produced the largest number of true and false positives. The same rules, using uncorrected scores, produced the greatest number of false negatives. The computer-based system produced the most-acceptable set of decisions overall, striking a balance between these two kinds of errors. It was concluded that, when assessed against the available criterion information, the MMPI could not be recommended as a screening device. However, due to serious limitations inherent in these data, further study is needed

EEG feature selection method based on decision tree.

Science.gov (United States)

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

2015-01-01

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

eHealth Literacy and Partner Involvement in Treatment Decision Making for Men With Newly Diagnosed Localized Prostate Cancer.

Science.gov (United States)

Song, Lixin; Tatum, Kimberly; Greene, Giselle; Chen, Ronald C

2017-03-01

To examine how the eHealth literacy of partners of patients with newly diagnosed prostate cancer affects their involvement in decision making, and to identify the factors that influence their eHealth literacy.
. Cross-sectional exploratory study.
. North Carolina.
. 142 partners of men with newly diagnosed localized prostate cancer. 
. A telephone survey and descriptive and multiple linear regression analyses were used.
. The partners' eHealth literacy, involvement in treatment decision making, and demographics, and the health statuses of the patients and their partners. 
. Higher levels of eHealth literacy among partners were significantly associated with their involvement in getting a second opinion, their awareness of treatment options, and the size of the social network they relied on for additional information and support for treatment decision making for prostate cancer. The factor influencing eHealth literacy was the partners' access to the Internet for personal use, which explained some of the variance in eHealth literacy.
. This study described how partners' eHealth literacy influenced their involvement in treatment decision making for prostate cancer and highlighted the influencing factors (i.e., partners' access to the Internet for personal use).
. When helping men with prostate cancer and their partners with treatment decision making, nurses need to assess eHealth literacy levels to determine whether nonelectronically based education materials are needed and to provide clear instructions on how to use eHealth resources.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Karel Doubravsky

Full Text Available 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 (rechecked 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.

An Intuitionistic Fuzzy Stochastic Decision-Making Method Based on Case-Based Reasoning and Prospect Theory

Directory of Open Access Journals (Sweden)

Peng Li

2017-01-01

Full Text Available According to the case-based reasoning method and prospect theory, this paper mainly focuses on finding a way to obtain decision-makers’ preferences and the criterion weights for stochastic multicriteria decision-making problems and classify alternatives. Firstly, we construct a new score function for an intuitionistic fuzzy number (IFN considering the decision-making environment. Then, we aggregate the decision-making information in different natural states according to the prospect theory and test decision-making matrices. A mathematical programming model based on a case-based reasoning method is presented to obtain the criterion weights. Moreover, in the original decision-making problem, we integrate all the intuitionistic fuzzy decision-making matrices into an expectation matrix using the expected utility theory and classify or rank the alternatives by the case-based reasoning method. Finally, two illustrative examples are provided to illustrate the implementation process and applicability of the developed method.

Seeing white elephants? The production and communication of information in a locally-based monitoring system in Tanzania

Directory of Open Access Journals (Sweden)

Martin Reinhardt Nielsen

2012-01-01

Full Text Available The literature on locally-based monitoring in the context of conservation displays a great deal of optimism about the prospects of involving local people in the systematic gathering of information about the condition and use of natural resources and conservation areas to inform management decisions from local to national levels. This study challenges this notion based on a case study of a collaborative forest management and locally-based monitoring project that has been considered a successful showcase example in Tanzania. It does so by comparing information from locally-based monitoring of forest condition and financial transactions, as presented by community management institutions to higher authorities, with forest transect surveys and an audit of financial accounts. The results reveal that the information produced and communicated under the locally-based monitoring system contradicts trends in wildlife densities and human disturbance observed in the forest and under-represents actual financial flows. Interviews and observations further indicate that communication of this information takes place under conditions of ongoing power struggles over access to benefits of collaborative forest management. This study serves to caution that the information produced and communicated under the locally-based monitoring system may be shaped by the incentives and power struggles surrounding the particular context within which the system is based and therefore cannot be taken at face value.

A distributed clinical decision support system architecture

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Shaker H. El-Sappagh

2014-01-01

Full Text Available This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR, data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibility, interoperability and scalability objectives of an EHR. The system will also have a set of distributed knowledge bases. Each knowledge base will be specialized in a specific domain (i.e., heart disease, and the model achieves cooperation, integration and interoperability between these knowledge bases. Moreover, the model ensures that all knowledge bases are up-to-date by connecting data mining engines to each local knowledge base. These data mining engines continuously mine EHR databases to extract the most recent knowledge, to standardize it and to add it to the knowledge bases. This framework is expected to improve the quality of healthcare, reducing medical errors and guaranteeing the safety of patients by helping clinicians to make correct, accurate, knowledgeable and timely decisions.

Accrual based accounting implementation: An approach for modelling major decisions

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Ratno Agriyanto

2016-12-01

Full Text Available Over the last three decades the main issues of implementation of accrual based accounting government institutions in Indonesia. Implementation of accrual based accounting in government institutions amid debate about the usefulness of accounting information for decision-making. Empirical study shows that the accrual based of accounting information on a government institution is not used for decision making. The research objective was to determine the impact of the implementation of the accrual based accounting to the accrual basis of accounting information use for decision-making basis. We used the survey questionnaires. The data were processed by SEM using statistical software WarpPLS. The results showed that the implementation of the accrual based accounting in City Government Semarang has significantly positively associated with decision-making. Another important finding is the City Government officials of Semarang have personality, low tolerance of ambiguity is a negative effect on the relationship between the implementation of the accrual based accounting for decision making

School-Based Decision-Making: The Canadian Perspective.

Science.gov (United States)

Peters, Frank

1997-01-01

In Canada, school-based decision making is a political expedient to co-opt public support for public education at the same time as financial resources to schools are being curtailed. School councils are advisory in nature and have no statutory position in either school or school-system decisions. (17 references) (MLF)

Multi-robot Cooperation Behavior Decision Based on Psychological Values

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Jian JIANG

2014-01-01

Full Text Available The method based on psychology concept has been proved to be a successful tool used for human-robot interaction. But its related research in multi-robot cooperation has remained scarce until recent studies. To solve the problem, a decision-making mechanism based on psychological values is presented to be regarded as the basis of the multi-robot cooperation. Robots give birth to psychological values based on the estimations of environment, teammates and themselves. The mapping relationship between psychological values and cooperation tendency threshold values is set up with artificial neural network. Robots can make decision on the bases of these threshold values in cooperation scenes. Experiments show that the multi-robot cooperation method presented in the paper not only can ensure the rationality of robots’ decision-making, but also can ensure the speediness of robots’ decision-making.

Rough set and rule-based multicriteria decision aiding

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Roman Slowinski

2012-08-01

Full Text Available The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA. DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems.

Modalities of self-managing teams - The "must", "may", "can" and "will" of local decision making

NARCIS (Netherlands)

Molleman, E

2000-01-01

This paper deals with the leeway organizations have to develop and design self-managing teams by using a model containing four model verbs: must, may, can and will. ''Must'' refers to the need for local decision making and is considered to be the result of diversity in enviromental demand and

Anytime decision making based on unconstrained influence diagrams

DEFF Research Database (Denmark)

Luque, Manuel; Nielsen, Thomas Dyhre; Jensen, Finn Verner

2016-01-01

. This paper addresses this problem by proposing an anytime algorithm that at any time provides a qualified recommendation for the first decisions of the problem. The algorithm performs a heuristic-based search in a decision tree representation of the problem. We provide a framework for analyzing......Unconstrained influence diagrams extend the language of influence diagrams to cope with decision problems in which the order of the decisions is unspecified. Thus, when solving an unconstrained influence diagram we not only look for an optimal policy for each decision, but also for a so-called step......-policy specifying the next decision given the observations made so far. However, due to the complexity of the problem, temporal constraints can force the decision maker to act before the solution algorithm has finished, and, in particular, before an optimal policy for the first decision has been computed...

Selecting a risk-based tool to aid in decision making

Energy Technology Data Exchange (ETDEWEB)

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.

Science-based natural resource management decisions: what are they?

Science.gov (United States)

T.J. Mills; T.M. Quigley; F.J. Everest

2001-01-01

While many people interested in natural resources management propose science-based decisions, it is not clear what “science-based” means. Science-based decisions are those that result from the full and complete consideration of the relevant science information. We offer five guidelines to focus the scientist’s contributions to science-based decisionmaking and use the...

Dopamine and Effort-Based Decision Making

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Irma Triasih Kurniawan

2011-06-01

Full Text Available Motivational theories of choice focus on the influence of goal values and strength of reinforcement to explain behavior. By contrast relatively little is known concerning how the cost of an action, such as effort expended, contributes to a decision to act. Effort-based decision making addresses how we make an action choice based on an integration of action and goal values. Here we review behavioral and neurobiological data regarding the representation of effort as action cost, and how this impacts on decision making. Although organisms expend effort to obtain a desired reward there is a striking sensitivity to the amount of effort required, such that the net preference for an action decreases as effort cost increases. We discuss the contribution of the neurotransmitter dopamine (DA towards overcoming response costs and in enhancing an animal’s motivation towards effortful actions. We also consider the contribution of brain structures, including the basal ganglia (BG and anterior cingulate cortex (ACC, in the internal generation of action involving a translation of reward expectation into effortful action.

The Environmental Virtual Observatory (EVO) local exemplar: A cloud based local landscape learning visualisation tool for communicating flood risk to catchment stakeholders

Science.gov (United States)

Wilkinson, Mark; Beven, Keith; Brewer, Paul; El-khatib, Yehia; Gemmell, Alastair; Haygarth, Phil; Mackay, Ellie; Macklin, Mark; Marshall, Keith; Quinn, Paul; Stutter, Marc; Thomas, Nicola; Vitolo, Claudia

2013-04-01

Today's world is dominated by a wide range of informatics tools that are readily available to a wide range of stakeholders. There is growing recognition that the appropriate involvement of local communities in land and water management decisions can result in multiple environmental, economic and social benefits. Therefore, local stakeholder groups are increasingly being asked to participate in decision making alongside policy makers, government agencies and scientists. As such, addressing flooding issues requires new ways of engaging with the catchment and its inhabitants at a local level. To support this, new tools and approaches are required. The growth of cloud based technologies offers new novel ways to facilitate this process of exchange of information in earth sciences. The Environmental Virtual Observatory Pilot project (EVOp) is a new initiative from the UK Natural Environment Research Council (NERC) designed to deliver proof of concept for new tools and approaches to support the challenges as outlined above (http://www.evo-uk.org/). The long term vision of the Environmental Virtual Observatory is to: • Make environmental data more visible and accessible to a wide range of potential users including public good applications; • Provide tools to facilitate the integrated analysis of data, greater access to added knowledge and expert analysis and visualisation of the results; • Develop new, added-value knowledge from public and private sector data assets to help tackle environmental challenges. As part of the EVO pilot, an interactive cloud based tool has been developed with local stakeholders. The Local Landscape Visualisation Tool attempts to communicate flood risk in local impacted communities. The tool has been developed iteratively to reflect the needs, interests and capabilities of a wide range of stakeholders. This tool (assessable via a web portal) combines numerous cloud based tools and services, local catchment datasets, hydrological models and

A heuristic framework for understanding the role of participatory decision making in community-based non-profits.

Science.gov (United States)

Bess, Kimberly D; Perkins, Douglas D; Cooper, Daniel G; Jones, Diana L

2011-06-01

This paper explores the role of member participation in decision-making (PDM) from an organizational learning (OL) perspective. Community-based organizations (CBOs) serve as mediators between the individual and the local community, often providing the means for community member participation and benefiting organizationally from members' input. Community psychologists have recognized these benefits; however, the field has paid less attention to the role participation plays in increasing CBOs' capacity to meet community needs. We present a framework for exploring how CBO contextual factors influence the use of participatory decision-making structures and practices, and how these affect OL. We then use the framework to examine PDM in qualitative case study analysis of four CBOs: a youth development organization, a faith-based social action coalition, a low-income neighborhood organization, and a large human service agency. We found that organizational form, energy, and culture each had a differential impact on participation in decision making within CBOs. We highlight how OL is constrained in CBOs and document how civic aims and voluntary membership enhanced participation and learning.

A Game-Chain-Based Approach for Decision Making

OpenAIRE

An, Tingyu; Watanabe, tsunami

2009-01-01

Nowadays, with the rapid development of information society, decision-making problems become more and more complicated especially in large scale systems such as infrastructure, environmental and industrial fields, which are usually accompanied by psychological competition between involved parties in a complicated, uncertain and dynamic situation. From a holistic perspective of system, a specific decision-making method which is described as game-chain-based decision making has been proposed in...

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

OpenAIRE

Bo Sun; Qiang Feng; Songjie Li

2012-01-01

According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

[Value-based cancer care. From traditional evidence-based decision making to balanced decision making within frameworks of shared values].

Science.gov (United States)

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.

Decision-Based Design Integrating Consumer Preferences into Engineering Design

CERN Document Server

Chen, Wei; Wassenaar, Henk Jan

2013-01-01

Building upon the fundamental principles of decision theory, Decision-Based Design: Integrating Consumer Preferences into Engineering Design presents an analytical approach to enterprise-driven Decision-Based Design (DBD) as a rigorous framework for decision making in engineering design.  Once the related fundamentals of decision theory, economic analysis, and econometrics modelling are established, the remaining chapters describe the entire process, the associated analytical techniques, and the design case studies for integrating consumer preference modeling into the enterprise-driven DBD framework. Methods for identifying key attributes, optimal design of human appraisal experiments, data collection, data analysis, and demand model estimation are presented and illustrated using engineering design case studies. The scope of the chapters also provides: •A rigorous framework of integrating the interests from both producer and consumers in engineering design, •Analytical techniques of consumer choice model...

Influence of branding on preference-based decision making.

Science.gov (United States)

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.

Evidence-based decision making in health care settings: from theory to practice.

Science.gov (United States)

Kohn, Melanie Kazman; Berta, Whitney; Langley, Ann; Davis, David

2011-01-01

The relatively recent attention that evidence-based decision making has received in health care management has been at least in part due to the profound influence of evidence-based medicine. The result has been several comparisons in the literature between the use of evidence in health care management decisions and the use of evidence in medical decision making. Direct comparison, however, may be problematic, given the differences between medicine and management as they relate to (1) the nature of evidence that is brought to bear on decision making; (2) the maturity of empirical research in each field (in particular, studies that have substantiated whether or not and how evidence-based decision making is enacted); and (3) the context within which evidence-based decisions are made. By simultaneously reviewing evidence-based medicine and management, this chapter aims to inform future theorizing and empirical research on evidence-based decision making in health care settings.

Validating the predictions of case-based decision theory

OpenAIRE

Radoc, Benjamin

2015-01-01

Real-life decision-makers typically do not know all possible outcomes arising from alternative courses of action. Instead, when people face a problem, they may rely on the recollection of their past personal experience: the situation, the action taken, and the accompanying consequence. In addition, the applicability of a past experience in decision-making may depend on how similar the current problem is to situations encountered previously. Case-based decision theory (CBDT), proposed by Itzha...

Overview of EPA tools for supporting local- and regional-scale decision makers addressing energy and environmental issues

Science.gov (United States)

EPA’s Office of Research and Development (ORD) has been developing tools and illustrative case studies for decision makers in local and regional authorities who are facing challenges of establishing resilience to extreme weather events, aging built environment and infrastru...

Agent-Based Modeling of Consumer Decision making Process Based on Power Distance and Personality

NARCIS (Netherlands)

Roozmand, O.; Ghasem-Aghaee, N.; Hofstede, G.J.; Nematbakhsh, M.A.; Baraani, A.; Verwaart, T.

2011-01-01

Simulating consumer decision making processes involves different disciplines such as: sociology, social psychology, marketing, and computer science. In this paper, we propose an agent-based conceptual and computational model of consumer decision-making based on culture, personality and human needs.

Decision aid use during post-biopsy consultations for localized prostate cancer.

Science.gov (United States)

Holmes-Rovner, Margaret; Srikanth, Akshay; Henry, Stephen G; Langford, Aisha; Rovner, David R; Fagerlin, Angela

2018-02-01

Decision Aids (DAs) effectively translate medical evidence for patients but are not routinely used in clinical practice. Little is known about how DAs are used during patient-clinician encounters. To characterize the content and communicative function of high-quality DAs during diagnostic clinic visits for prostate cancer. 252 men newly diagnosed with localized prostate cancer who had received a DA, 45 treating physicians at 4 US Veterans Administration urology clinics. Qualitative analysis of transcribed audio recordings was used to inductively develop categories capturing content and function of all direct references to DAs (booklet talk). The presence or absence of any booklet talk per transcript was also calculated. Booklet talk occurred in 55% of transcripts. Content focused on surgical procedures (36%); treatment choice (22%); and clarifying risk classification (17%). The most common function of booklet talk was patient corroboration of physicians' explanations (42%), followed by either physician or patient acknowledgement that the patient had the booklet. Codes reflected the absence of DA use for shared decision-making. In regression analysis, predictors of booklet talk were fewer years of patient education (P = .027) and more time in the encounter (P = .027). Patient race, DA type, time reading the DA, physician informing quality and physician age did not predict booklet talk. Results show that good decision aids, systematically provided to patients, appeared to function not to open up deliberations about how to balance benefits and harms of competing treatments, but rather to allow patients to ask narrow technical questions about recommended treatments. © 2017 The Authors Health Expectations Published by John Wiley & Sons Ltd.

Local/regional policies: Acting globally by thinking locally

International Nuclear Information System (INIS)

Hillsman, E.L.

1991-01-01

Policies to reduce greenhouse gas emissions from present levels will require changes in local and regional decision making as well as decisions made at national and multinational scales. A number of cities and states have taken action to reduce emissions either directly or as a byproduct of solving local problems such as air quality. These initiatives represent a potential resource to be mobilized in national policy. A series of case studies is under way to understand the decision making involved and its implications, and to identify ways that national policy might support and benefit from local efforts. Preliminary results from the first of these case studies indicate that reductions in greenhouse gas emissions may be greater when set as a direct target than when resulting as a byproduct of other local problem solving

Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes

Directory of Open Access Journals (Sweden)

Rajesh P N Rao

2010-11-01

Full Text Available 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

Applying the balanced scorecard to local public health performance measurement: deliberations and decisions

Directory of Open Access Journals (Sweden)

Kurji Karim

2009-05-01

Full Text Available Abstract Background All aspects of the heath care sector are being asked to account for their performance. This poses unique challenges for local public health units with their traditional focus on population health and their emphasis on disease prevention, health promotion and protection. Reliance on measures of health status provides an imprecise and partial picture of the performance of a health unit. In 2004 the provincial Institute for Clinical Evaluative Sciences based in Ontario, Canada introduced a public-health specific balanced scorecard framework. We present the conceptual deliberations and decisions undertaken by a health unit while adopting the framework. Discussion Posing, pondering and answering key questions assisted in applying the framework and developing indicators. Questions such as: Who should be involved in developing performance indicators? What level of performance should be measured? Who is the primary intended audience? Where and how do we begin? What types of indicators should populate the health status and determinants quadrant? What types of indicators should populate the resources and services quadrant? What type of indicators should populate the community engagement quadrant? What types of indicators should populate the integration and responsiveness quadrants? Should we try to link the quadrants? What comparators do we use? How do we move from a baseline report card to a continuous quality improvement management tool? Summary An inclusive, participatory process was chosen for defining and creating indicators to populate the four quadrants. Examples of indicators that populate the four quadrants of the scorecard are presented and key decisions are highlighted that facilitated the process.

Applying the balanced scorecard to local public health performance measurement: deliberations and decisions.

Science.gov (United States)

Weir, Erica; d'Entremont, Nadine; Stalker, Shelley; Kurji, Karim; Robinson, Victoria

2009-05-08

All aspects of the heath care sector are being asked to account for their performance. This poses unique challenges for local public health units with their traditional focus on population health and their emphasis on disease prevention, health promotion and protection. Reliance on measures of health status provides an imprecise and partial picture of the performance of a health unit. In 2004 the provincial Institute for Clinical Evaluative Sciences based in Ontario, Canada introduced a public-health specific balanced scorecard framework. We present the conceptual deliberations and decisions undertaken by a health unit while adopting the framework. Posing, pondering and answering key questions assisted in applying the framework and developing indicators. Questions such as: Who should be involved in developing performance indicators? What level of performance should be measured? Who is the primary intended audience? Where and how do we begin? What types of indicators should populate the health status and determinants quadrant? What types of indicators should populate the resources and services quadrant? What type of indicators should populate the community engagement quadrant? What types of indicators should populate the integration and responsiveness quadrants? Should we try to link the quadrants? What comparators do we use? How do we move from a baseline report card to a continuous quality improvement management tool? An inclusive, participatory process was chosen for defining and creating indicators to populate the four quadrants. Examples of indicators that populate the four quadrants of the scorecard are presented and key decisions are highlighted that facilitated the process.

Facial expression recognition under partial occlusion based on fusion of global and local features

Science.gov (United States)

Wang, Xiaohua; Xia, Chen; Hu, Min; Ren, Fuji

2018-04-01

Facial expression recognition under partial occlusion is a challenging research. This paper proposes a novel framework for facial expression recognition under occlusion by fusing the global and local features. In global aspect, first, information entropy are employed to locate the occluded region. Second, principal Component Analysis (PCA) method is adopted to reconstruct the occlusion region of image. After that, a replace strategy is applied to reconstruct image by replacing the occluded region with the corresponding region of the best matched image in training set, Pyramid Weber Local Descriptor (PWLD) feature is then extracted. At last, the outputs of SVM are fitted to the probabilities of the target class by using sigmoid function. For the local aspect, an overlapping block-based method is adopted to extract WLD features, and each block is weighted adaptively by information entropy, Chi-square distance and similar block summation methods are then applied to obtain the probabilities which emotion belongs to. Finally, fusion at the decision level is employed for the data fusion of the global and local features based on Dempster-Shafer theory of evidence. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the effectiveness and fault tolerance of this method.

Fundamentals of the fuzzy logic-based generalized theory of decisions

CERN Document Server

Aliev, Rafik Aziz

2013-01-01

Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision making has a long history and arose also in Keynes’s analysis of uncertainty. There is a need for further generalization – a move to decision theories with perception-based imperfect information described in NL. The languages of new decision models for human-centric systems should be not languages based on binary logic but human-centric computational schemes able to operate on NL-described information. Development of new theories is now possible due to an increased computational power of information processing systems which allows for computations with imperfect information, particularly, imprecise and partially true information, which are much more complex than comput...

Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

KAUST Repository

Delimata, Paweł

2010-01-01

We discuss two, in a sense extreme, kinds of nondeterministic rules in decision tables. The first kind of rules, called as inhibitory rules, are blocking only one decision value (i.e., they have all but one decisions from all possible decisions on their right hand sides). Contrary to this, any rule of the second kind, called as a bounded nondeterministic rule, can have on the right hand side only a few decisions. We show that both kinds of rules can be used for improving the quality of classification. In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules. We also present an application of bounded nondeterministic rules in construction of rule based classifiers. We include the results of experiments showing that by combining rule based classifiers based on minimal decision rules with bounded nondeterministic rules having confidence close to 1 and sufficiently large support, it is possible to improve the classification quality. © 2010 Springer-Verlag.

A comparison of web-based versus print-based decision AIDS for prostate cancer screening: participants' evaluation and utilization.

Science.gov (United States)

Tomko, Catherine; Davis, Kimberly M; Luta, George; Krist, Alexander H; Woolf, Steven H; Taylor, Kathryn L

2015-01-01

Patient decision aids facilitate informed decision making for medical tests and procedures that have uncertain benefits. To describe participants' evaluation and utilization of print-based and web-based prostate cancer screening decision aids that were found to improve decisional outcomes in a prior randomized controlled trial. Men completed brief telephone interviews at baseline, one month, and 13 months post-randomization. Participants were primary care patients, 45-70 years old, who received the print-based (N = 628) or web-based decision aid (N = 625) and completed the follow-up assessments. We assessed men's baseline preference for web-based or print-based materials, time spent using the decision aids, comprehension of the overall message, and ratings of the content. Decision aid use was self-reported by 64.3 % (web) and 81.8 % (print) of participants. Significant predictors of decision aid use were race (white vs. non-white, OR = 2.43, 95 % CI: 1.77, 3.35), higher education (OR = 1.68, 95 % CI: 1.06, 2.70) and trial arm (print vs. web, OR = 2.78, 95 % CI: 2.03, 3.83). Multivariable analyses indicated that web-arm participants were more likely to use the website when they preferred web-based materials (OR: 1.91, CI: 1.17, 3.12), whereas use of the print materials was not significantly impacted by a preference for print-based materials (OR: 0.69, CI: 0.38, 1.25). Comprehension of the decision aid message (i.e., screening is an individual decision) did not significantly differ between arms in adjusted analyses (print: 61.9 % and web: 68.2 %, p = 0.42). Decision aid use was independently influenced by race, education, and the decision aid medium, findings consistent with the 'digital divide.' These results suggest that when it is not possible to provide this age cohort with their preferred decision aid medium, print materials will be more highly used than web-based materials. Although there are many advantages to web-based decision aids, providing an option for

On developing a prospecting tool for wind industry and policy decision support

International Nuclear Information System (INIS)

McKeown, Charles; Adelaja, Adesoji; Calnin, Benjamin

2011-01-01

This paper presents the rudiments of a Wind Prospecting Tool designed to inform private and public decision makers involved in wind industry development in reducing transaction costs associated with identifying areas of mutual focus within a state. The multiple layer decision support framework has proven to be valuable to industry, state government and local decision makers. Information on wind resources, land availability, potential land costs, potential NIMBYism concerns and economic development potential were integrated to develop a framework for decision support. The paper also highlights implications for decision support research and the role of higher education in providing anticipatory science to enhance private and public choices in economic development. - Research Highlights: →In this paper we explore the building and value of a wind industry location decision support tool. →We examine the development process from the industry perspective. →We discuss the creation of a decision support tool that was designed for industry, state policy makers and local decision makers. →We build a model framework for wind prospecting decision support. →Finally we discuss the impact on local and state decision making as a result of being informed by science based decision support.

Vicarious Effort-Based Decision-Making in Autism Spectrum Disorders.

Science.gov (United States)

Mosner, Maya G; Kinard, Jessica L; McWeeny, Sean; Shah, Jasmine S; Markiewitz, Nathan D; Damiano-Goodwin, Cara R; Burchinal, Margaret R; Rutherford, Helena J V; Greene, Rachel K; Treadway, Michael T; Dichter, Gabriel S

2017-10-01

This study investigated vicarious effort-based decision-making in 50 adolescents with autism spectrum disorders (ASD) compared to 32 controls using the Effort Expenditure for Rewards Task. Participants made choices to win money for themselves or for another person. When choosing for themselves, the ASD group exhibited relatively similar patterns of effort-based decision-making across reward parameters. However, when choosing for another person, the ASD group demonstrated relatively decreased sensitivity to reward magnitude, particularly in the high magnitude condition. Finally, patterns of responding in the ASD group were related to individual differences in consummatory pleasure capacity. These findings indicate atypical vicarious effort-based decision-making in ASD and more broadly add to the growing body of literature addressing social reward processing deficits in ASD.

Application of a web-based Decision Support System in risk management

Science.gov (United States)

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

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

Science.gov (United States)

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.

Simulation-based decision support for evaluating operational plans

Directory of Open Access Journals (Sweden)

Johan Schubert

2015-12-01

Full Text Available In this article, we describe simulation-based decision support techniques for evaluation of operational plans within effects-based planning. Using a decision support tool, developers of operational plans are able to evaluate thousands of alternative plans against possible courses of events and decide which of these plans are capable of achieving a desired end state. The objective of this study is to examine the potential of a decision support system that helps operational analysts understand the consequences of numerous alternative plans through simulation and evaluation. Operational plans are described in the effects-based approach to operations concept as a set of actions and effects. For each action, we examine several different alternative ways to perform the action. We use a representation where a plan consists of several actions that should be performed. Each action may be performed in one of several different alternative ways. Together these action alternatives make up all possible plan instances, which are represented as a tree of action alternatives that may be searched for the most effective sequence of alternative actions. As a test case, we use an expeditionary operation with a plan of 43 actions and several alternatives for these actions, as well as a scenario of 40 group actors. Decision support for planners is provided by several methods that analyze the impact of a plan on the 40 actors, e.g., by visualizing time series of plan performance. Detailed decision support for finding the most influential actions of a plan is presented by using sensitivity analysis and regression tree analysis. Finally, a decision maker may use the tool to determine the boundaries of an operation that it must not move beyond without risk of drastic failure. The significant contribution of this study is the presentation of an integrated approach for evaluation of operational plans.

Probabilistic Decision Based Block Partitioning for Future Video Coding

KAUST Repository

Wang, Zhao; Wang, Shiqi; Zhang, Jian; Wang, Shanshe; Ma, Siwei

2017-01-01

, the mode decision problem is casted into a probabilistic framework to select the final partition based on the confidence interval decision strategy. Experimental results show that the proposed CIET algorithm can speed up QTBT block partitioning structure

Towards Strengths-Based Planning Strategies for Rural Localities in Finland

Directory of Open Access Journals (Sweden)

Rönkkö Emilia

2017-09-01

Full Text Available In this article, we will introduce the topic of strengths-based planning strategies for rural localities in Finland. The strengths-based approach focuses on capacity building and competence enhancement with the local people, encouraging communities to valorise, identify and mobilise existing but often unrecognised assets. Setting focus only on the deficiencies and problems easily inflicts a ‘surrender mentality‘ in places outside of the urbanisation impact, creating a narrative that both decision-makers and community members start to believe. Hence, the role and potential of smaller rural localities is easily forgotten by planners, politicians and the public at large. Addressing the scale of rural localities in spatial planning, we will first reflect upon the main findings from our earlier research project “Finnish rural localities in the 2010`s” conducted by Lahti University of Applied Sciences, the University of Oulu and Aalto University in 2013-2015. Findings from the research project affirmed the unfortunate consequences of rapid urbanisation, rational blueprint planning and overoptimistic expectations of growth in the 1960s and 70s, which have resulted in the state of permanent incompleteness in rural localities today. However, these localities possess many under-utilised strengths, and we consider it essential for the future development of rural localities to make the most of this potential, and not only tackle the downwards spiral. This requires the ability to engage local stakeholders around a common vision for the future, and strategic approach based on endogenous strengths. We will discuss these possibilities via two theoretically informed case studies. The first one, Vieremä, is situated in the region of Northern Savo, and the other one, Vääksy, is the main centre in the municipality of Asikkala, situated in the region of Päijät-Häme in Southern Finland. Our study design can be characterised as qualitative research

Modular Architecture for Integrated Model-Based Decision Support.

Science.gov (United States)

Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

2018-01-01

Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

A local authority view of the Sizewell B decision and the role of the public enquiry

International Nuclear Information System (INIS)

Ayre, D.

1987-01-01

The background to the Sizewell-B public inquiry is presented. The local authorities are important in this as it was they who first received the Central Electricity Generating Board's request to build Sizewell-B and who triggered the need for a Public Inquiry. The local authorities did not object in principle to the use of the Sizewell site for additional nuclear power generation provided the Government was satisfied that there was a national need for the extra capacity. In future inquiries there might not be acceptance in principle which would change the nature of the Inquiry. The local authority involvement in the public inquiry is discussed under the headings: need and economics, safety and local environment issues. The relevant parts of the Sizewell-B report are considered. The Secretary of State's decision, which follows the Inspector's report, justifies the confidence put in the inquiry process by the local authorities. Concern is expressed, however, that extra financial help is needed to pay for the local authorities expenditure on the Inquiry and also for the consequences of the Sizewell-B project itself. (U.K.)

Episodic memories predict adaptive value-based decision-making

Science.gov (United States)

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

2016-01-01

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 re-engage 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 re-engage 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. PMID:26999046

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

Science.gov (United States)

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.

Evidence-Based Medicine in judicial decisions concerning right to healthcare

Science.gov (United States)

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

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

Science.gov (United States)

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.

Automated Vectorization of Decision-Based Algorithms

Science.gov (United States)

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.

Cognitive schema and naturalistic decision making in evidence-based practices.

Science.gov (United States)

Falzer, Paul R

2004-04-01

A recent article in this journal proposed a naturalistic approach to decision making that overcomes problems intrinsic to classical decision theory. The approach emphasizes cognitive and multi-level processes, the development of expert reasoning, and the role of decision support in individual and organizational decision making. The current paper builds on this effort by suggesting a naturalistic, multi-level, theory that can facilitate the dissemination of evidence-based practices (EBPs). The paper presents "Image Theory," a theory that has been extensively investigated in other disciplines, but has yet to be utilized in medical decision research. It is suggested that its rich, empirically tested, distinctions among kinds of cognitive and organizational processes and types of decisions and tasks make Image Theory especially valuable in describing impediments to implementing EBPs. The paper discusses how naturalistic theory can assist clinicians, administrators, researchers, and policy makers in achieving a balance between evidence-based medicine and patient-centered practice.

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

Science.gov (United States)

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

Proposal optimization in nuclear accident emergency decision based on IAHP

International Nuclear Information System (INIS)

Xin Jing

2007-01-01

On the basis of establishing the multi-layer structure of nuclear accident emergency decision, several decision objectives are synthetically analyzed, and an optimization model of decision proposals for nuclear accident emergency based on interval analytic hierarchy process is proposed in the paper. The model makes comparisons among several emergency decision proposals quantified, and the optimum proposal is selected out, which solved the uncertain and fuzzy decision problem of judgments by experts' experiences in nuclear accidents emergency decision. Case study shows that the optimization result is much more reasonable, objective and reliable than subjective judgments, and it could be decision references for nuclear accident emergency. (authors)

Bayesian risk-based decision method for model validation under uncertainty

International Nuclear Information System (INIS)

Jiang Xiaomo; Mahadevan, Sankaran

2007-01-01

This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model. A Bayesian decision theory-based method is developed for this purpose, using a likelihood ratio as the validation metric for model assessment. An expected risk or cost function is defined as a function of the decision costs, and the likelihood and prior of each hypothesis. The risk is minimized through correctly assigning experimental data to two decision regions based on the comparison of the likelihood ratio with a decision threshold. A Bayesian validation metric is derived based on the risk minimization criterion. Two types of validation tests are considered: pass/fail tests and system response value measurement tests. The methodology is illustrated for the validation of reliability prediction models in a tension bar and an engine blade subjected to high cycle fatigue. The proposed method can effectively integrate optimal experimental design into model validation to simultaneously reduce the cost and improve the accuracy of reliability model assessment

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

Science.gov (United States)

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).

The Relative Success of Recognition-Based Inference in Multichoice Decisions

Science.gov (United States)

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…

Trust Index Based Fault Tolerant Multiple Event Localization Algorithm for WSNs

Science.gov (United States)

Xu, Xianghua; Gao, Xueyong; Wan, Jian; Xiong, Naixue

2011-01-01

This paper investigates the use of wireless sensor networks for multiple event source localization using binary information from the sensor nodes. The events could continually emit signals whose strength is attenuated inversely proportional to the distance from the source. In this context, faults occur due to various reasons and are manifested when a node reports a wrong decision. In order to reduce the impact of node faults on the accuracy of multiple event localization, we introduce a trust index model to evaluate the fidelity of information which the nodes report and use in the event detection process, and propose the Trust Index based Subtract on Negative Add on Positive (TISNAP) localization algorithm, which reduces the impact of faulty nodes on the event localization by decreasing their trust index, to improve the accuracy of event localization and performance of fault tolerance for multiple event source localization. The algorithm includes three phases: first, the sink identifies the cluster nodes to determine the number of events occurred in the entire region by analyzing the binary data reported by all nodes; then, it constructs the likelihood matrix related to the cluster nodes and estimates the location of all events according to the alarmed status and trust index of the nodes around the cluster nodes. Finally, the sink updates the trust index of all nodes according to the fidelity of their information in the previous reporting cycle. The algorithm improves the accuracy of localization and performance of fault tolerance in multiple event source localization. The experiment results show that when the probability of node fault is close to 50%, the algorithm can still accurately determine the number of the events and have better accuracy of localization compared with other algorithms. PMID:22163972

Trust Index Based Fault Tolerant Multiple Event Localization Algorithm for WSNs

Directory of Open Access Journals (Sweden)

Jian Wan

2011-06-01

Full Text Available This paper investigates the use of wireless sensor networks for multiple event source localization using binary information from the sensor nodes. The events could continually emit signals whose strength is attenuated inversely proportional to the distance from the source. In this context, faults occur due to various reasons and are manifested when a node reports a wrong decision. In order to reduce the impact of node faults on the accuracy of multiple event localization, we introduce a trust index model to evaluate the fidelity of information which the nodes report and use in the event detection process, and propose the Trust Index based Subtract on Negative Add on Positive (TISNAP localization algorithm, which reduces the impact of faulty nodes on the event localization by decreasing their trust index, to improve the accuracy of event localization and performance of fault tolerance for multiple event source localization. The algorithm includes three phases: first, the sink identifies the cluster nodes to determine the number of events occurred in the entire region by analyzing the binary data reported by all nodes; then, it constructs the likelihood matrix related to the cluster nodes and estimates the location of all events according to the alarmed status and trust index of the nodes around the cluster nodes. Finally, the sink updates the trust index of all nodes according to the fidelity of their information in the previous reporting cycle. The algorithm improves the accuracy of localization and performance of fault tolerance in multiple event source localization. The experiment results show that when the probability of node fault is close to 50%, the algorithm can still accurately determine the number of the events and have better accuracy of localization compared with other algorithms.

Monitoring, accounting and automated decision support for the ALICE experiment based on the MonALISA framework

CERN Document Server

Cirstoiu, C; Betev, L; Saiz, P; Peters, A J; Muraru, A; Voicu, R; Legrand, I

2007-01-01

We are developing a general purpose monitoring system for the ALICE experiment, based on the MonALISA framework. MonALISA (Monitoring Agents using a Large Integrated Services Architecture) is a fully distributed system with no single point of failure that is able to collect, store monitoring information and present it as significant perspectives and synthetic views on the status and the trends of the entire system. Furthermore, agents can use it for taking automated operational decisions. Monitoring information is gathered locally from all the components running in each site. The entire flow of information is aggregated on site level by a MonALISA service and then collected and presented in various forms by a central MonALISA Repository. Based on this information, other services take operational decisions such as alerts, triggers, service restarts and automatic production job or transfer submissions. The system monitors all the components: computer clusters (all major parameters of each computing node), jobs ...

Energy-Based Acoustic Source Localization Methods: A Survey

Directory of Open Access Journals (Sweden)

Wei Meng

2017-02-01

Full Text Available Energy-based source localization is an important problem in wireless sensor networks (WSNs, which has been studied actively in the literature. Numerous localization algorithms, e.g., maximum likelihood estimation (MLE and nonlinear-least-squares (NLS methods, have been reported. In the literature, there are relevant review papers for localization in WSNs, e.g., for distance-based localization. However, not much work related to energy-based source localization is covered in the existing review papers. Energy-based methods are proposed and specially designed for a WSN due to its limited sensor capabilities. This paper aims to give a comprehensive review of these different algorithms for energy-based single and multiple source localization problems, their merits and demerits and to point out possible future research directions.

Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data.

Science.gov (United States)

Dexter, Franklin; Wachtel, Ruth E; Epstein, Richard H

2011-01-07

No systematic process has previously been described for a needs assessment that identifies the operating room (OR) management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1). Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS) data for most scenarios (43 of 45). Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of individualized assessments. Our technical advance is the

Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data

Directory of Open Access Journals (Sweden)

Epstein Richard H

2011-01-01

Full Text Available Abstract Background No systematic process has previously been described for a needs assessment that identifies the operating room (OR management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. Methods A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1. Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS data for most scenarios (43 of 45. Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Results Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of

An Isometric Mapping Based Co-Location Decision Tree Algorithm

Science.gov (United States)

Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.

2018-05-01

Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

AN ISOMETRIC MAPPING BASED CO-LOCATION DECISION TREE ALGORITHM

Directory of Open Access Journals (Sweden)

G. Zhou

2018-05-01

Full Text Available Decision tree (DT induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT, which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1 The extraction method of exposed carbonate rocks is of high accuracy. (2 The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

Science.gov (United States)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in

DXplain: a Web-based diagnostic decision support system for medical students.

Science.gov (United States)

London, S

1998-01-01

DXplain is a diagnostic decision support program, with a new World Wide Web interface, designed to help medical students and physicians formulate differential diagnoses based on clinical findings. It covers over 2000 diseases and 5000 clinical manifestations. DXplain suggests possible diagnoses, and provides brief descriptions of every disease in the database. Not all diseases are included, nor does DXplain take into account preexisting conditions or the chronological sequence of clinical manifestations. Despite these limitations, it is a useful educational tool, particularly for problem-based learning (PBL) cases and for students in clinical rotations, as it fills a niche not adequately covered by MEDLINE or medical texts. The system is relatively self-explanatory, requiring little or no end-user training. Medical libraries offering, or planning to offer, their users access to Web-based materials and resources may find this system a valuable addition to their electronic collections. Should it prove popular with the local users, provision of access may also establish or enhance the library's image as a partner in medical education.

Feasibility of web-based decision aids in neurological patients

NARCIS (Netherlands)

van Til, Janine Astrid; Drossaert, Constance H.C.; Renzenbrink, Gerbert J.; Snoek, Govert J.; Dijkstra, Evelien; Stiggelbout, Anne M.; IJzerman, Maarten Joost

2010-01-01

Decision aids (DAs) may be helpful in improving patients' participation in medical decision-making. We investigated the potential for web-based DAs in a rehabilitation population. Two self-administered DAs focused on the treatment of acquired ankle-foot impairment in stroke and the treatment of

Improving the Slum Planning Through Geospatial Decision Support System

Science.gov (United States)

Shekhar, S.

2014-11-01

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

Local and global trust based on the concept of promises

NARCIS (Netherlands)

Bergstra, J.; Burgess, M.

2009-01-01

We use the notion of a promise to define local trust between agents possessing autonomous decision-making. An agent is trustworthy if it is expected that it will keep a promise. This definition satisfies most commonplace meanings of trust. Reputation is then an estimation of this expectation value

Accrual based accounting implementation: An approach for modelling major decisions

OpenAIRE

Ratno Agriyanto; Abdul Rohman; Dwi Ratmono; Imam Ghozali

2016-01-01

Over the last three decades the main issues of implementation of accrual based accounting government institutions in Indonesia. Implementation of accrual based accounting in government institutions amid debate about the usefulness of accounting information for decision-making. Empirical study shows that the accrual based of accounting information on a government institution is not used for decision making. The research objective was to determine the impact of the implementation of the accrual...

Factors influencing the surgical decision for the treatment of degenerative lumbar stenosis in a preference-based shared decision-making process.

Science.gov (United States)

Kim, Ho-Joong; Park, Jae-Young; Kang, Kyoung-Tak; Chang, Bong-Soon; Lee, Choon-Ki; Yeom, Jin S

2015-02-01

In a preference-based shared decision-making system, several subjective and/or objective factors such as pain severity, degree of disability, and the radiological severity of canal stenosis may influence the final surgical decision for the treatment of lumbar spinal stenosis (LSS). However, our understanding of the shared decision-making process and the significance of each factor remain primitive. In the present study, we aimed to investigate which factors influence the surgical decision for the treatment of LSS when using a preference-based, shared decision-making process. We included 555 patients, aged 45-80 years, who used a preference-based shared decision-making process and were treated conservatively or surgically for chronic leg and/or back pain caused by LSS from April 2012 to December 2012. Univariate and multivariable-adjusted logistic regression analyses were used to assess the association of surgical decision making with age, sex, body mass index, symptom duration, radiologic stenotic grade, Oswestry Disability Index (ODI), visual analog scale (VAS) scores for back and leg pain, Short Form-36 (SF-36) subscales, and motor weakness. In univariate analysis, the following variables were associated with a higher odds of a surgical decision for LSS: male sex; the VAS score for leg pain; ODI; morphological stenotic grades B, C, and D; motor weakness; and the physical function, physical role, bodily pain, social function, and emotional role of the SF-36 subscales. Multivariate analysis revealed that male sex, ODI, morphological stenotic grades C and D, and motor weakness were significantly associated with a higher possibility of a surgical decision. Motor weakness, male sex, morphological stenotic grade, and the amount of disability are critical factors leading to a surgical decision for LSS when using a preference-based shared decision-making process.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

2016-01-26

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. 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. 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. 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, some features performed better than

To Share or Not to Share: Malaysian Healthcare Professionals' Views on Localized Prostate Cancer Treatment Decision Making Roles.

Directory of Open Access Journals (Sweden)

Yew Kong Lee

Full Text Available To explore the views of Malaysian healthcare professionals (HCPs on stakeholders' decision making roles in localized prostate cancer (PCa treatment.Qualitative interviews and focus groups were conducted with HCPs treating PCa. Data was analysed using a thematic approach. Four in-depth interviews and three focus group discussions were conducted between December 2012 and March 2013 using a topic guide. Interviews were audio-recorded, transcribed verbatim, and analysed thematically.The participants comprised private urologists (n = 4, government urologists (n = 6, urology trainees (n = 6, government policy maker (n = 1 and oncologists (n = 3. HCP perceptions of the roles of the three parties involved (HCPs, patients, family included: HCP as the main decision maker, HCP as a guide to patients' decision making, HCP as a facilitator to family involvement, patients as main decision maker and patient prefers HCP to decide. HCPs preferred to share the decision with patients due to equipoise between prostate treatment options. Family culture was important as family members often decided on the patient's treatment due to Malaysia's close-knit family culture.A range of decision making roles were reported by HCPs. It is thus important that stakeholder roles are clarified during PCa treatment decisions. HCPs need to cultivate an awareness of sociocultural norms and family dynamics when supporting non-Western patients in making decisions about PCa.

To Share or Not to Share: Malaysian Healthcare Professionals' Views on Localized Prostate Cancer Treatment Decision Making Roles.

Science.gov (United States)

Lee, Yew Kong; Lee, Ping Yein; Cheong, Ai Theng; Ng, Chirk Jenn; Abdullah, Khatijah Lim; Ong, Teng Aik; Razack, Azad Hassan Abdul

2015-01-01

To explore the views of Malaysian healthcare professionals (HCPs) on stakeholders' decision making roles in localized prostate cancer (PCa) treatment. Qualitative interviews and focus groups were conducted with HCPs treating PCa. Data was analysed using a thematic approach. Four in-depth interviews and three focus group discussions were conducted between December 2012 and March 2013 using a topic guide. Interviews were audio-recorded, transcribed verbatim, and analysed thematically. The participants comprised private urologists (n = 4), government urologists (n = 6), urology trainees (n = 6), government policy maker (n = 1) and oncologists (n = 3). HCP perceptions of the roles of the three parties involved (HCPs, patients, family) included: HCP as the main decision maker, HCP as a guide to patients' decision making, HCP as a facilitator to family involvement, patients as main decision maker and patient prefers HCP to decide. HCPs preferred to share the decision with patients due to equipoise between prostate treatment options. Family culture was important as family members often decided on the patient's treatment due to Malaysia's close-knit family culture. A range of decision making roles were reported by HCPs. It is thus important that stakeholder roles are clarified during PCa treatment decisions. HCPs need to cultivate an awareness of sociocultural norms and family dynamics when supporting non-Western patients in making decisions about PCa.

An Automated System for Generating Situation-Specific Decision Support in Clinical Order Entry from Local Empirical Data

Science.gov (United States)

Klann, Jeffrey G.

2011-01-01

Clinical Decision Support is one of the only aspects of health information technology that has demonstrated decreased costs and increased quality in healthcare delivery, yet it is extremely expensive and time-consuming to create, maintain, and localize. Consequently, a majority of health care systems do not utilize it, and even when it is…

Development, implementation and evaluation of an evidence-based program for introduction of new health technologies and clinical practices in a local healthcare setting.

Science.gov (United States)

Harris, Claire; Garrubba, Marie; Allen, Kelly; King, Richard; Kelly, Cate; Thiagarajan, Malar; Castleman, Beverley; Ramsey, Wayne; Farjou, Dina

2015-12-28

This paper reports the process of establishing a transparent, accountable, evidence-based program for introduction of new technologies and clinical practices (TCPs) in a large Australian healthcare network. Many countries have robust evidence-based processes for assessment of new TCPs at national level. However many decisions are made by local health services where the resources and expertise to undertake health technology assessment (HTA) are limited and a lack of structure, process and transparency has been reported. An evidence-based model for process change was used to establish the program. Evidence from research and local data, experience of health service staff and consumer perspectives were incorporated at each of four steps: identifying the need for change, developing a proposal, implementation and evaluation. Checklists assessing characteristics of success, factors for sustainability and barriers and enablers were applied and implementation strategies were based on these findings. Quantitative and qualitative methods were used for process and outcome evaluation. An action research approach underpinned ongoing refinement to systems, processes and resources. A Best Practice Guide developed from the literature and stakeholder consultation identified seven program components: Governance, Decision-Making, Application Process, Monitoring and Reporting, Resources, Administration, and Evaluation and Quality Improvement. The aims of transparency and accountability were achieved. The processes are explicit, decisions published, outcomes recorded and activities reported. The aim of ascertaining rigorous evidence-based information for decision-making was not achieved in all cases. Applicants proposing new TCPs provided the evidence from research literature and local data however the information was often incorrect or inadequate, overestimating benefits and underestimating costs. Due to these limitations the initial application process was replaced by an Expression of

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

Directory of Open Access Journals (Sweden)

Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier.

Science.gov (United States)

Mao, Keming; Deng, Zhuofu

2016-01-01

This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP) is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

Directory of Open Access Journals (Sweden)

Keming Mao

2016-01-01

Full Text Available This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

Modelling and simulation-based acquisition decision support: present & future

CSIR Research Space (South Africa)

Naidoo, S

2009-10-01

Full Text Available stream_source_info Naidoo1_2009.pdf.txt stream_content_type text/plain stream_size 24551 Content-Encoding UTF-8 stream_name Naidoo1_2009.pdf.txt Content-Type text/plain; charset=UTF-8 1 Modelling & Simulation...-Based Acquisition Decision Support: Present & Future Shahen Naidoo Abstract The Ground Based Air Defence System (GBADS) Programme, of the South African Army has been applying modelling and simulation (M&S) to provide acquisition decision and doctrine...

Promotion of technical harmonisation on risk-based decision making

International Nuclear Information System (INIS)

Kirchsteiger, Christian; Cojazzi, Giacomo

2000-01-01

The EC-JRC International Workshop on Promotion of Technical Harmonisation on Risk-Based Decision Making, held at Stresa and Ispra, Italy, 22-25 May 2000, was an experts meeting to discuss the possible need of developing an internationally accepted generic 'standard' for risk-based decision making.This paper briefly describes the workshop background, its organisation and summarises its main results and conclusions; it reflects the personal opinions of the authors and in no way commits the European Commission. (author)

Value-based attentional capture influences context-dependent decision-making

Science.gov (United States)

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

Testing interventions to influence women's dietary decisions in ...

International Development Research Centre (IDRC) Digital Library (Canada)

... that responds to national priorities for establishing an evidence-based culture for ... It will host a workshop with researchers, local nutrition specialists and social ... of dietary behaviour and practical solutions to improve nutrition decisions.

Securing Localization With Hidden and Mobile Base Stations

DEFF Research Database (Denmark)

Capkun, Srdjan; Srivastava, Mani; Cagalj, Mario

2006-01-01

localization based on hidden and mobile base stations. Our approach enables secure localization with a broad spectrum of localization techniques: ultrasonic or radio, based on received signal strength or signal time of flight. Through several examples we show how this approach can be used to secure nodecentric...

Risk-based decision making for terrorism applications.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2015-07-01

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

Framing the decision to contract out elderly care and primary health care services - perspectives of local level politicians and civil servants in Finland.

Science.gov (United States)

Tynkkynen, Liina-Kaisa; Lehto, Juhani; Miettinen, Sari

2012-07-17

In the literature there are only few empirical studies that analyse the decision makers' reasoning to contract out health care and social services to private sector. However, the decisions on the delivery patterns of health care and social services are considered to be of great importance as they have a potential to influence citizens' access to services and even affect their health. This study contributes to filling this cap by exploring the frames used by Finnish local authorities as they talk about contracting out of primary health care and elderly care services. Contracting with the private sector has gained increasing popularity, in Finland, during the past decade, as a practise of organising health care and social services. Interview data drawn from six municipalities through thematic group interviews were used. The data were analysed applying frame analysis in order to reveal the underlying reasoning for the decisions. Five argumentation frames were found: Rational reasoning; Pragmatic realism; Promoting diversity among providers; Good for the municipality; Good for the local people. The interviewees saw contracting with the private sector mostly as a means to improve the performance of public providers, to improve service quality and efficiency and to boost the local economy. The decisions to contract out were mainly argued through the good for the municipal administration, political and ideological commitments, available resources and existing institutions. This study suggests that the policy makers use a number of grounds to justify their decisions on contracting out. Most of the arguments were related to the benefits of the municipality rather than on what is best for the local people. The citizens were offered the role of active consumers who are willing to purchase services also out-of-pocket. This development has a potential to endanger the affordability of the services and lead to undermining some of the traditional principles of the Nordic welfare

Supporting decision-making processes for evidence-based mental health promotion.

Science.gov (United States)

Jané-Llopis, Eva; Katschnig, Heinz; McDaid, David; Wahlbeck, Kristian

2011-12-01

The use of evidence is critical in guiding decision-making, but evidence from effect studies will be only one of a number of factors that will need to be taken into account in the decision-making processes. Equally important for policymakers will be the use of different types of evidence including implementation essentials and other decision-making principles such as social justice, political, ethical, equity issues, reflecting public attitudes and the level of resources available, rather than be based on health outcomes alone. This paper, aimed to support decision-makers, highlights the importance of commissioning high-quality evaluations, the key aspects to assess levels of evidence, the importance of supporting evidence-based implementation and what to look out for before, during and after implementation of mental health promotion and mental disorder prevention programmes.

Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

Science.gov (United States)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

Science.gov (United States)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

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

Science.gov (United States)

McCaughey, Deirdre; Bruning, Nealia S

2010-05-26

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. 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. 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 EBDM/EBPM process can be

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

Directory of Open Access Journals (Sweden)

Bruning Nealia S

2010-05-01

Full Text Available Abstract 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

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

Science.gov (United States)

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

Evidence-based decision-making 7: Knowledge translation.

Science.gov (United States)

Manns, Braden J

2015-01-01

There is a significant gap between what is known and what is implemented by key stakeholders in practice (the evidence to practice gap). The primary purpose of knowledge translation is to address this gap, bridging evidence to clinical practice. The knowledge to action cycle is one framework for knowledge translation that integrates policy-makers throughout the research cycle. The knowledge to action cycle begins with the identification of a problem (usually a gap in care provision). After identification of the problem, knowledge creation is undertaken, depicted at the center of the cycle as a funnel. Knowledge inquiry is at the wide end of the funnel, and moving down the funnel, the primary data is synthesized into knowledge products in the form of educational materials, guidelines, decision aids, or clinical pathways. The remaining components of the knowledge to action cycle refer to the action of applying the knowledge that has been created. This includes adapting knowledge to local context, assessing barriers to knowledge use, selecting, tailoring implementing interventions, monitoring knowledge use, evaluating outcomes, and sustaining knowledge use. Each of these steps is connected by bidirectional arrows and ideally involves healthcare decision-makers and key stakeholders at each transition.

All hazardous waste politics is local: Grass-roots advocacy and public participation in siting and cleanup decisions

Energy Technology Data Exchange (ETDEWEB)

Lowry, R.C.

1998-12-31

The combined effects of federalism and interest group pluralism pose particularly difficult problems for hazardous waste siting and cleanup decisions. Most national environmental groups have only limited involvement in local hazardous waste politics, while local grass-roots advocates have very different interests and sometimes are pitted against one another. Both the Environmental protection Agency and the Department of energy recently have begun to use site-specific citizen advisory boards at cleanup sites. This approach appears to improve communications at some sites, but does not address the issues of ``not in my back yard`` politics and alleged inequitable exposure to hazardous wastes.

Decision making in matters of pollution in France

International Nuclear Information System (INIS)

Galle, Marion

1989-01-01

Decision making in matters of pollution, although taking place in a hierarchically determined institutional setting, can be interpreted as the result of a conflictual process between the different groups involved. 1. The statutory setting: coherence of laws and adaptability of norms; a hierarchical, pyramidal, formal structure; relative autonomy and flexibility of local decision making: possibility of developing local organizations for the control of pollution. 2. The conflictual process: Within the institutional setting, decision making is the result of interaction between: the state and the authorities, who make the rules and possess the formal power; industry, which has the economic power and is the arbiter of technical feasibility; the public, who are guardians of social values and judges of the acceptability of final decisions; the experts, who possess the scientific knowledge on which decisions are based. The relative weights of these different interests in decision making are linked with the existence of today's society of communication which increases the importance of communicators and especially the media. Conclusion: decision making in questions of environmental risk and pollution necessarily consists in taking into account all the interests involved in order to arrive at a solution acceptable to the public. The interests of society are not necessarily compatible with technical or scientific logic. (author)

Value-based attentional capture influences context-dependent decision-making.

Science.gov (United States)

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. Copyright © 2015 the American Physiological Society.

onlineDeCISion.org: a web-based decision aid for DCIS treatment.

Science.gov (United States)

Ozanne, Elissa M; Schneider, Katharine H; Soeteman, Djøra; Stout, Natasha; Schrag, Deborah; Fordis, Michael; Punglia, Rinaa S

2015-11-01

Women diagnosed with DCIS face complex treatment decisions and often do so with inaccurate and incomplete understanding of the risks and benefits involved. Our objective was to create a tool to guide these decisions for both providers and patients. We developed a web-based decision aid designed to provide clinicians with tailored information about a patient’s recurrence risks and survival outcomes following different treatment strategies for DCIS. A theoretical framework, microsimulation model (Soeteman et al., J Natl Cancer 105:774–781, 2013) and best practices for web-based decision tools guided the development of the decision aid. The development process used semi-structured interviews and usability testing with key stakeholders, including a diverse group of multidisciplinary clinicians and a patient advocate. We developed onlineDeCISion.​org to include the following features that were rated as important by the stakeholders: (1) descriptions of each of the standard treatment options available; (2) visual projections of the likelihood of time-specific (10-year and lifetime) breast-preservation, recurrence, and survival outcomes; and (3) side-by-side comparisons of down-stream effects of each treatment choice. All clinicians reviewing the decision aid in usability testing were interested in using it in their clinical practice. The decision aid is available in a web-based format and is planned to be publicly available. To improve treatment decision making in patients with DCIS, we have developed a web-based decision aid onlineDeCISion.​org that conforms to best practices and that clinicians are interested in using in their clinics with patients to better inform treatment decisions.

Coastal Adaptation Planning for Sea Level Rise and Extremes: A Global Model for Adaptation Decision-making at the Local Level Given Uncertain Climate Projections

Science.gov (United States)

Turner, D.

2014-12-01

Understanding the potential economic and physical impacts of climate change on coastal resources involves evaluating a number of distinct adaptive responses. This paper presents a tool for such analysis, a spatially-disaggregated optimization model for adaptation to sea level rise (SLR) and storm surge, the Coastal Impact and Adaptation Model (CIAM). This decision-making framework fills a gap between very detailed studies of specific locations and overly aggregate global analyses. While CIAM is global in scope, the optimal adaptation strategy is determined at the local level, evaluating over 12,000 coastal segments as described in the DIVA database (Vafeidis et al. 2006). The decision to pursue a given adaptation measure depends on local socioeconomic factors like income, population, and land values and how they develop over time, relative to the magnitude of potential coastal impacts, based on geophysical attributes like inundation zones and storm surge. For example, the model's decision to protect or retreat considers the costs of constructing and maintaining coastal defenses versus those of relocating people and capital to minimize damages from land inundation and coastal storms. Uncertain storm surge events are modeled with a generalized extreme value distribution calibrated to data on local surge extremes. Adaptation is optimized for the near-term outlook, in an "act then learn then act" framework that is repeated over the model time horizon. This framework allows the adaptation strategy to be flexibly updated, reflecting the process of iterative risk management. CIAM provides new estimates of the economic costs of SLR; moreover, these detailed results can be compactly represented in a set of adaptation and damage functions for use in integrated assessment models. Alongside the optimal result, CIAM evaluates suboptimal cases and finds that global costs could increase by an order of magnitude, illustrating the importance of adaptive capacity and coastal policy.

The Environmental Advisory Service (EASe): a decision support system for comprehensive screening of local land-use development proposals and comparative evaluation of proposed land-use plans

OpenAIRE

K P White; A P Sage; F A Rodammer; C T Peters

1985-01-01

The Environmental Advisory Service (EASe) is a decision support system which can provide assistance to local planning agencies in selecting land-development alternatives or in formulating land-use plans. EASe offers a comprehensive and consistent procedure for rating either a development proposal or a proposed plan. This procedure is based upon qualitative assessments of the impact of developments or plans on the natural environment, zoning and land use. public and private services, transport...

Applications of decision theory to computer-based adaptive instructional systems

NARCIS (Netherlands)

Vos, Hendrik J.

1988-01-01

This paper considers applications of decision theory to the problem of instructional decision-making in computer-based adaptive instructional systems, using the Minnesota Adaptive Instructional System (MAIS) as an example. The first section indicates how the problem of selecting the appropriate

Tactical decision games - developing scenario-based training for decision-making in distributed teams

NARCIS (Netherlands)

Lauche, K.; Crichton, M.; Bayerl, P.S.

2009-01-01

Team training should reflect the increasing complexity of decision-making environments. Guidelines for scenario-based training were adopted for a distributed setting and tested in a pilot training session with a distributed team in the offshore oil industry. Participants valued the scenario as

Cost-Based Vertical Handover Decision Algorithm for WWAN/WLAN Integrated Networks

Directory of Open Access Journals (Sweden)

Kim LaeYoung

2009-01-01

Full Text Available Abstract Next generation wireless communications are expected to rely on integrated networks consisting of multiple wireless technologies. Heterogeneous networks based on Wireless Local Area Networks (WLANs and Wireless Wide Area Networks (WWANs can combine their respective advantages on coverage and data rates, offering a high Quality of Service (QoS to mobile users. In such environment, multi-interface terminals should seamlessly switch from one network to another in order to obtain improved performance or at least to maintain a continuous wireless connection. Therefore, network selection algorithm is important in providing better performance to the multi-interface terminals in the integrated networks. In this paper, we propose a cost-based vertical handover decision algorithm that triggers the Vertical Handover (VHO based on a cost function for WWAN/WLAN integrated networks. For the cost function, we focus on developing an analytical model of the expected cost of WLAN for the mobile users that enter the double-coverage area while having a connection in the WWAN. Our simulation results show that the proposed scheme achieves better performance in terms of power consumption and throughput than typical approach where WLANs are always preferred whenever the WLAN access is available.

Range-Based Localization in Mobile Sensor Networks

NARCIS (Netherlands)

Dil, B.J.; Dil, B.; Dulman, S.O.; Havinga, Paul J.M.; Romer, K.; Karl, H.; Mattern, F.

2006-01-01

Localization schemes for wireless sensor networks can be classified as range-based or range-free. They differ in the information used for localization. Range-based methods use range measurements, while range-free techniques only use the content of the messages. None of the existing algorithms

The role local initiatives in community based disaster risk management in Kemijen, Semarang City

Science.gov (United States)

Fauzie, W. Z.; Sariffudin, S.

2017-06-01

Community-based disaster risk reduction is one of the homegrown initiatives efforts and community empowerment oriented in disaster management. This approach is very important because no one can understand the conditions in a region better than the local communities. Therefore, the implementation of CBDRM always emphasize local initiatives in decision making. The existence of local initiative is necessary specially to anticipate the impact of climate change which is increasingly affecting towns in coastal areas, including settlements in Semarang. Kemijen Urban Village is one of the informal settlements in Semarang, which has the highest intensity of flood that is 12 times during 5 years (2011-2015). The research question is how the level of local initiatives in flood disaster management in Kemijen, Semarang? This study aims to assess the level of local initiatives in Kemijen as the community adaptive capacity of flood prevention in pre-disaster, emergency response, and post-disaster. Local initiatives assessed on water supply, sanitation, food, shelter, health, drainage maintenance and waste management. This study shows the level of local initiatives in pre-disaster and post-disaster is almost same and bigger than the response phase. Scoring results showed that pre-disaster is 35.002, 27.9577 for emergency response, and post-disaster is 34.9862 with each category that is independent, empowered, and independent. This study also shows that local initiatives in Kemijen largely formed by individual initiative and only a few were formed by a collective initiative.

Analysis of Local Financial Management Transparency Based on Websites on Local Government in Java

Directory of Open Access Journals (Sweden)

Anissa Adriana

2018-03-01

Full Text Available The aim of this research is to analyze financial management transparency of local governments in Java using scoring and rating. The financial management transparency of the local governments is scored based on presentation of local financial information uploaded on each local government’s official website in Jawa in the fiscal years 2016.This research is a qualitative research with the object of research is all local government in Java. Data analysis in two levels, namely the transparency of local government financial management and identification of local government characteristics based on transparency of financial management. Data analysis in two levels, namely the transparency of local government financial management and identification of local government characteristics based on transparency of financial management. The results show that the Special Capital Region of Jakarta obtained the highest transparency index, at 58, 02% whereas Madiun Regency received the lowest transparency index, at 3, 40%. The average transparency index in Jawa for the fiscal years 2016 was still low, at only 19, 59%.The conclusion of this research is that Java regional governments consider the transparency of local financial management using less important websites because it is considered as a better thing not delivered to the public.

Asymmetric Localization of Cdx2 mRNA during the First Cell-Fate Decision in Early Mouse Development

Directory of Open Access Journals (Sweden)

Maria Skamagki

2013-02-01

Full Text Available A longstanding question in mammalian development is whether the divisions that segregate pluripotent progenitor cells for the future embryo from cells that differentiate into extraembryonic structures are asymmetric in cell-fate instructions. The transcription factor Cdx2 plays a key role in the first cell-fate decision. Here, using live-embryo imaging, we show that localization of Cdx2 transcripts becomes asymmetric during development, preceding cell lineage segregation. Cdx2 transcripts preferentially localize apically at the late eight-cell stage and become inherited asymmetrically during divisions that set apart pluripotent and differentiating cells. Asymmetric localization depends on a cis element within the coding region of Cdx2 and requires cell polarization as well as intact microtubule and actin cytoskeletons. Failure to enrich Cdx2 transcripts apically results in a significant decrease in the number of pluripotent cells. We discuss how the asymmetric localization and segregation of Cdx2 transcripts could contribute to multiple mechanisms that establish different cell fates in the mouse embryo.

Ignorance- versus evidence-based decision making: a decision time analysis of the recognition heuristic.

Science.gov (United States)

Hilbig, Benjamin E; Pohl, Rüdiger F

2009-09-01

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 evidence speaking for each of the objects and that decision times thus depend on the evidential difference between objects, or the degree of conflict between options. This article presents 3 experiments that tested predictions derived from the RH against those from alternative models. All experiments used naturally recognized objects without teaching participants any information and thus provided optimal conditions for application of the RH. However, results supported the alternative, evidence-based models and often conflicted with the RH. Recognition was not the key determinant of decision times, whereas differences between objects with respect to (both positive and negative) evidence predicted effects well. In sum, alternative models that allow for the integration of different pieces of information may well provide a better account of comparative judgments. (c) 2009 APA, all rights reserved.

Multiobjective memetic estimation of distribution algorithm based on an incremental tournament local searcher.

Science.gov (United States)

Yang, Kaifeng; Mu, Li; Yang, Dongdong; Zou, Feng; Wang, Lei; Jiang, Qiaoyong

2014-01-01

A novel hybrid multiobjective algorithm is presented in this paper, which combines a new multiobjective estimation of distribution algorithm, an efficient local searcher and ε-dominance. Besides, two multiobjective problems with variable linkages strictly based on manifold distribution are proposed. The Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise low-dimensional continuous manifold. The regularity by the manifold features just build probability distribution model by globally statistical information from the population, yet, the efficiency of promising individuals is not well exploited, which is not beneficial to search and optimization process. Hereby, an incremental tournament local searcher is designed to exploit local information efficiently and accelerate convergence to the true Pareto-optimal front. Besides, since ε-dominance is a strategy that can make multiobjective algorithm gain well distributed solutions and has low computational complexity, ε-dominance and the incremental tournament local searcher are combined here. The novel memetic multiobjective estimation of distribution algorithm, MMEDA, was proposed accordingly. The algorithm is validated by experiment on twenty-two test problems with and without variable linkages of diverse complexities. Compared with three state-of-the-art multiobjective optimization algorithms, our algorithm achieves comparable results in terms of convergence and diversity metrics.

Multiobjective Memetic Estimation of Distribution Algorithm Based on an Incremental Tournament Local Searcher

Directory of Open Access Journals (Sweden)

Kaifeng Yang

2014-01-01

Full Text Available A novel hybrid multiobjective algorithm is presented in this paper, which combines a new multiobjective estimation of distribution algorithm, an efficient local searcher and ε-dominance. Besides, two multiobjective problems with variable linkages strictly based on manifold distribution are proposed. The Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise low-dimensional continuous manifold. The regularity by the manifold features just build probability distribution model by globally statistical information from the population, yet, the efficiency of promising individuals is not well exploited, which is not beneficial to search and optimization process. Hereby, an incremental tournament local searcher is designed to exploit local information efficiently and accelerate convergence to the true Pareto-optimal front. Besides, since ε-dominance is a strategy that can make multiobjective algorithm gain well distributed solutions and has low computational complexity, ε-dominance and the incremental tournament local searcher are combined here. The novel memetic multiobjective estimation of distribution algorithm, MMEDA, was proposed accordingly. The algorithm is validated by experiment on twenty-two test problems with and without variable linkages of diverse complexities. Compared with three state-of-the-art multiobjective optimization algorithms, our algorithm achieves comparable results in terms of convergence and diversity metrics.

Opioid Modulation of Value-Based Decision-Making in Healthy Humans.

Science.gov (United States)

Eikemo, Marie; Biele, Guido; Willoch, Frode; Thomsen, Lotte; Leknes, Siri

2017-08-01

Modifying behavior to maximize reward is integral to adaptive decision-making. In rodents, the μ-opioid receptor (MOR) system encodes motivation and preference for high-value rewards. Yet it remains unclear whether and how human MORs contribute to value-based decision-making. We reasoned that if the human MOR system modulates value-based choice, this would be reflected by opposite effects of agonist and antagonist drugs. In a double-blind pharmacological cross-over study, 30 healthy men received morphine (10 mg), placebo, and the opioid antagonist naltrexone (50 mg). They completed a two-alternative decision-making task known to induce a considerable bias towards the most frequently rewarded response option. To quantify MOR involvement in this bias, we fitted accuracy and reaction time data with the drift-diffusion model (DDM) of decision-making. The DDM analysis revealed the expected bidirectional drug effects for two decision subprocesses. MOR stimulation with morphine increased the preference for the stimulus with high-reward probability (shift in starting point). Compared to placebo, morphine also increased, and naltrexone reduced, the efficiency of evidence accumulation. Since neither drug affected motor-coordination, speed-accuracy trade-off, or subjective state (indeed participants were still blinded after the third session), we interpret the MOR effects on evidence accumulation efficiency as a consequence of changes in effort exerted in the task. Together, these findings support a role for the human MOR system in value-based choice by tuning decision-making towards high-value rewards across stimulus domains.

Goal-Directed Decision Making with Spiking Neurons.

Science.gov (United States)

Friedrich, Johannes; Lengyel, Máté

2016-02-03

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules

Cluster-based global firms' use of local capabilities

DEFF Research Database (Denmark)

Andersen, Poul Houman; Bøllingtoft, Anne

2011-01-01

Purpose – Despite growing interest in clusters role for the global competitiveness of firms, there has been little research into how globalization affects cluster-based firms’ (CBFs) use of local knowledge resources and the combination of local and global knowledge used. Using the cluster......’s knowledge base as a mediating variable, the purpose of this paper is to examine how globalization affected the studied firms’ use of local cluster-based knowledge, integration of local and global knowledge, and networking capabilities. Design/methodology/approach – Qualitative case studies of nine firms...... in three clusters strongly affected by increasing global division of labour. Findings – The paper suggests that globalization has affected how firms use local resources and combine local and global knowledge. Unexpectedly, clustered firms with explicit procedures and established global fora for exchanging...

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

Directory of Open Access Journals (Sweden)

Regina A. Weilbächer

2016-12-01

Full Text Available 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.

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha

2013-11-25

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Analytical evaluation of computer-based decision aids

International Nuclear Information System (INIS)

Kisner, R.A.

1985-01-01

This paper introduces a method for evaluating decision aids for nuclear power plant operators. The method involves a two-stage process of classification and analytical evaluation of display form and content. The classification scheme relates each specific aid to one or more general decision-making tasks. Evaluation then proceeds using a normative top-down design process based on the classification scheme by determining or deducing how various design issues associated with this process were resolved by the designer. The result is an assessment of the ''understandability'' of the aid as well as identification of the training and display features necessary to ensure understandability. 7 refs., 4 figs., 1 tab

GSNL 2.0: leveraging on Open Science to promote science-based decision making in Disaster Risk Reduction

Science.gov (United States)

Salvi, Stefano; Rubbia, Giuliana; Abruzzese, Luigi

2017-04-01

In 2010 the GEO Geohazard Supersites and Natural Laboratories initiative (GSNL) launched the concept of a global partnership among the geophysical scientific community and the satellite and in situ data providers, aiming to promote scientific advancements in the knowledge of seismic and volcanic phenomena. The initial goal was successfully achieved, and many more new scientific results were obtained than it could have been possible if the Supersites had not existed (http://www.earthobservations.org/gsnl.php). At the same time the Supersites have demonstrated to be able to effectively support the rapid transfer of useful scientific information to the risk managers, exploiting the existing institutional relationships between the Supersite coordinators and the local decision makers. However, a more demanding call for action is given by the Sendai Framework 2015-2030 (outcome of the 2015 UN World Conference on Disaster Risk Reduction), where for the first time the knowledge of the risk components and the science based decision-making process are defined as top priorities for an effective DRR. There are evident possible synergies between the Sendai framework, GEO, the CEOS (Committee on Earth Observation Satellites), and GSNL, but for maximum benefit and effectiveness the latter needs to progress at a faster pace towards a full implementation of the Open Science approach to geohazard science. In the above global framework the Supersites can represent local test beds where to experiment coordination, collaboration and communication approaches and technological solutions tailored to the local situation, to ensure that the scientific community can contribute the information needed for the best possible decision making. This vision and the new developments of GSNL 2.0 have been approved by the GEO Program Board, and a clear roadmap has been set for the period 2017-2019. We will present the approach and the implementation plan at the conference.

Perceptual decision neurosciences: a model-based review

NARCIS (Netherlands)

Mulder, M.J.; van Maanen, L.; Forstmann, B.U.

2014-01-01

In this review we summarize findings published over the past 10 years focusing on the neural correlates of perceptual decision-making. Importantly, this review highlights only studies that employ a model-based approach, i.e., they use quantitative cognitive models in combination with neuroscientific

Development of hybrid artificial intelligent based handover decision algorithm

Directory of Open Access Journals (Sweden)

A.M. Aibinu

2017-04-01

Full Text Available The possibility of seamless handover remains a mirage despite the plethora of existing handover algorithms. The underlying factor responsible for this has been traced to the Handover decision module in the Handover process. Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. The developed model is made up of hybrid of Artificial Neural Network (ANN based prediction model and Fuzzy Logic. On accessing the network, the Received Signal Strength (RSS was acquired over a period of time to form a time series data. The data was then fed to the newly proposed k-step ahead ANN-based RSS prediction system for estimation of prediction model coefficients. The synaptic weights and adaptive coefficients of the trained ANN was then used to compute the k-step ahead ANN based RSS prediction model coefficients. The predicted RSS value was later codified as Fuzzy sets and in conjunction with other measured network parameters were fed into the Fuzzy logic controller in order to finalize handover decision process. The performance of the newly developed k-step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. Results obtained in both cases shows that the proposed algorithm is capable of predicting ahead the RSS value to about ±0.0002 dB. Also, the cascaded effect of the complete handover decision module was also evaluated. Results obtained show that the newly proposed hybrid approach was able to reduce ping-pong effect associated with other handover techniques.

Expected Utility Based Decision Making under Z-Information and Its Application.

Science.gov (United States)

Aliev, Rashad R; Mraiziq, Derar Atallah Talal; Huseynov, Oleg H

2015-01-01

Real-world decision relevant information is often partially reliable. The reasons are partial reliability of the source of information, misperceptions, psychological biases, incompetence, and so forth. Z-numbers based formalization of information (Z-information) represents a natural language (NL) based value of a variable of interest in line with the related NL based reliability. What is important is that Z-information not only is the most general representation of real-world imperfect information but also has the highest descriptive power from human perception point of view as compared to fuzzy number. In this study, we present an approach to decision making under Z-information based on direct computation over Z-numbers. This approach utilizes expected utility paradigm and is applied to a benchmark decision problem in the field of economics.

Landmark based localization in urban environment

Science.gov (United States)

Qu, Xiaozhi; Soheilian, Bahman; Paparoditis, Nicolas

2018-06-01

A landmark based localization with uncertainty analysis based on cameras and geo-referenced landmarks is presented in this paper. The system is developed to adapt different camera configurations for six degree-of-freedom pose estimation. Local bundle adjustment is applied for optimization and the geo-referenced landmarks are integrated to reduce the drift. In particular, the uncertainty analysis is taken into account. On the one hand, we estimate the uncertainties of poses to predict the precision of localization. On the other hand, uncertainty propagation is considered for matching, tracking and landmark registering. The proposed method is evaluated on both KITTI benchmark and the data acquired by a mobile mapping system. In our experiments, decimeter level accuracy can be reached.

A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

Directory of Open Access Journals (Sweden)

Burhanuddin M. A.

2011-01-01

Full Text Available Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for

Exploring decision-making for environmental health services: perspectives from four cities.

Science.gov (United States)

Hunt, C; Lewin, S

2000-01-01

Increasing resources are being allocated to environmental health monitoring, especially for developing methods and collecting data to construct environmental health indicators (EHIs). Yet, little research has focused on understanding how communities and service providers make decisions with regard to environmental health priorities and the role of indicators in this process. This paper presents insights regarding local decision-making that arose from a project to test the feasibility of using community-based EHIs to facilitate communication between the providers and the recipients of environmental services in four developing-country cities. The results of the study indicate that decision-making for environmental health services is complex and iterative rather than rational and linear. Contextual and process factors play an important role. These factors include the morale of service providers, the extent of collaboration between service agencies, the priorities of different community groups and relations between service providers and communities. Scientific information, in the form of EHIs, did not appear to be a key element of decision-making in the settings studied. As tools, EHIs are unlikely to become part of the decision-making process unless they are integrated with local agendas and backed by strong local representation.

Intensity-modulated radiation therapy (IMRT) for locally advanced paranasal sinus tumors: incorporating clinical decisions in the optimization process

International Nuclear Information System (INIS)

Tsien, Christina; Eisbruch, Avraham; McShan, Daniel; Kessler, Marc; Marsh, Robin C.; Fraass, Benedick

2003-01-01

Purpose: Intensity-modulated radiotherapy (IMRT) plans require decisions about priorities and tradeoffs among competing goals. This study evaluates the incorporation of various clinical decisions into the optimization system, using locally advanced paranasal sinus tumors as a model. Methods and Materials: Thirteen patients with locally advanced paranasal sinus tumors were retrospectively replanned using inverse planning. Two clinical decisions were assumed: (1) Spare both optic pathways (OP), or (2) Spare only the contralateral OP. In each case, adequate tumor coverage (treated to 70 Gy in 35 fractions) was required. Two beamlet IMRT plans were thus developed for each patient using a class solution cost function. By altering one key variable at a time, different levels of risk of OP toxicity and planning target volume (PTV) compromise were compared in a systematic manner. The resulting clinical tradeoffs were analyzed using dosimetric criteria, tumor control probability (TCP), equivalent uniform dose (EUD), and normal tissue complication probability. Results: Plan comparisons representing the two clinical decisions (sparing both OP and sparing only the contralateral OP), with respect to minimum dose, TCP, V 95 , and EUD, demonstrated small, yet statistically significant, differences. However, when individual cases were analyzed further, significant PTV underdosage (>5%) was present in most cases for plans sparing both OP. In 6/13 cases (46%), PTV underdosage was between 5% and 15%, and in 3 cases (23%) was greater than 15%. By comparison, adequate PTV coverage was present in 8/13 cases (62%) for plans sparing only the contralateral OP. Mean target EUD comparisons between the two plans (including 9 cases where a clinical tradeoff between PTV coverage and OP sparing was required) were similar: 68.6 Gy and 69.1 Gy, respectively (p=0.02). Mean TCP values for those 9 cases were 56.5 vs. 61.7, respectively (p=0.006). Conclusions: In IMRT plans for paranasal sinus tumors

Risk Decision Making Based on Decision-theoretic Rough Set: A Three-way View Decision Model

OpenAIRE

Huaxiong Li; Xianzhong Zhou

2011-01-01

Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers. A simplex decision model can not provide a full description on such diverse decisions. In this article, a review of Pawlak rough set models and probabilistic rough set models is presented, and a ...

A basic design of microcontroller based data processor and local display for digital logarithmic power channel

International Nuclear Information System (INIS)

Nur Khasan; Syahrudin Yusuf

2009-01-01

A data processor and its local display for a digital logarithmic power channel, which will be used as a complement and diversification of nuclear reactor instrument, has been designed using micro controller base circuit. This power channel has been designed using TTL device and microcontroller. The roll of the microcontroller will be as data acquisition, data processing for the measurement of percentage reactor power, period and the trip decision. In this design has beer; created display of numerical value will be display on the local display in on-line mode for 1 nV to 10 10 nV neutron flux measurement range. This logarithmic power channel is expected to support the existing instrument which uses analog system in Instrumentation and Control System of nuclear reactor. (author)

Bases for Decisions on Final Disposal in Finland

International Nuclear Information System (INIS)

Avolahti, Jaana

2001-01-01

The disposal of the spent nuclear fuel is approaching one of the significant milestones in Finland. Social debate on the nuclear waste management is going on aiming at a decision of principle on future directions of spent fuel management. The research so far has required no political decision. This current situation is preceded by preparations for two decades carried out by Posiva Oy who took over the programme managed earlier by Teollisuuden Voinia Oy, one of the country's nuclear power companies. The preparations comprise site investigations, technical concept development, research into long-term safety and an environmental impact assessment. The work carried out by Posiva is under regular assessment by the authorities. Research programmes are drawn up every year and reports are published for open review. The preparations in the next years to come aim at starting the construction of the repository in 2010 and the disposal operations are planned to be started in 2020. Various stakeholders in Finland are involved in the decision-making process on the disposal of spent nuclear fuel. The process started when Posiva as an implementer applied for the Government's Decision in Principle in 1999. The Government made a favourable decision in December 2000 on the basis of different considerations. Among the important bases were the preceding favourable decisions made by the proposed siting municipality and the regulatory authority for radiation safety. At the moment the members of the Parliament are discussing the principles of the disposal in order to be able to vote on the Government's decision in the springtime. This paper discusses similarities and differences between the decisions made so far as regards the deep repository. The objective is to present the significance of the decisions from the point of view of an implementer of the repository. The Decision in Principle does not give any consent to start constructing the repository. Licenses for construction and

Decision rules for decision tables with many-valued decisions

KAUST Repository

Chikalov, Igor

2011-01-01

In the paper, authors presents a greedy algorithm for construction of exact and partial decision rules for decision tables with many-valued decisions. Exact decision rules can be \\'over-fitted\\', so instead of exact decision rules with many attributes, it is more appropriate to work with partial decision rules with smaller number of attributes. Based on results for set cover problem authors study bounds on accuracy of greedy algorithm for exact and partial decision rule construction, and complexity of the problem of minimization of decision rule length. © 2011 Springer-Verlag.

Multiple Attribute Decision Making Based on Cross-Evaluation with Uncertain Decision Parameters

Directory of Open Access Journals (Sweden)

Tao Ding

2016-01-01

Full Text Available Multiple attribute decision making (MADM problem is one of the most common and popular research fields in the theory of decision science. A variety of methods have been proposed to deal with such problems. Nevertheless, many of them assumed that attribute weights are determined by different types of additional preference information which will result in subjective decision making. In order to solve such problems, in this paper, we propose a novel MADM approach based on cross-evaluation with uncertain parameters. Specifically, the proposed approach assumes that all attribute weights are uncertain. It can overcome the drawback in prior research that the alternatives’ ranking may be determined by a single attribute with an overestimated weight. In addition, the proposed method can also balance the mean and deviation of each alternative’s cross-evaluation score to guarantee the stability of evaluation. Then, this method is extended to a more generalized situation where the attribute values are also uncertain. Finally, we illustrate the applicability of the proposed method by revisiting two reported studies and by a case study on the selection of community service companies in the city of Hefei in China.

Increased Reliance on Value-based Decision Processes Following Motor Cortex Disruption.

Science.gov (United States)

Zénon, Alexandre; Klein, Pierre-Alexandre; Alamia, Andrea; Boursoit, François; Wilhelm, Emmanuelle; Duque, Julie

2015-01-01

During motor decision making, the neural activity in primary motor cortex (M1) encodes dynamically the competition occurring between potential action plans. A common view is that M1 represents the unfolding of the outcome of a decision process taking place upstream. Yet, M1 could also be directly involved in the decision process. Here we tested this hypothesis by assessing the effect of M1 disruption on a motor decision-making task. We applied continuous theta burst stimulation (cTBS) to inhibit either left or right M1 in different groups of subjects and included a third control group with no stimulation. Following cTBS, participants performed a task that required them to choose between two finger key-presses with the right hand according to both perceptual and value-based information. Effects were assessed by means of generalized linear mixed models and computational simulations. In all three groups, subjects relied both on perceptual (P < 0.0001) and value-based information (P = 0.003) to reach a decision. Yet, left M1 disruption led to an increased reliance on value-based information (P = 0.03). This result was confirmed by a computational model showing an increased weight of the valued-based process on the right hand finger choices following left M1 cTBS (P < 0.01). These results indicate that M1 is involved in motor decision making, possibly by weighting the final integration of multiple sources of evidence driving motor behaviors. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrating Design Decision Management with Model-based Software Development

DEFF Research Database (Denmark)

Könemann, Patrick

Design decisions are continuously made during the development of software systems and are important artifacts for design documentation. Dedicated decision management systems are often used to capture such design knowledge. Most such systems are, however, separated from the design artifacts...... of the system. In model-based software development, where design models are used to develop a software system, outcomes of many design decisions have big impact on design models. The realization of design decisions is often manual and tedious work on design models. Moreover, keeping design models consistent......, or by ignoring the causes. This substitutes manual reviews to some extent. The concepts, implemented in a tool, have been validated with design patterns, refactorings, and domain level tests that comprise a replay of a real project. This proves the applicability of the solution to realistic examples...

Use of GIS-Based Sampling to Inform Food Security Assessments and Decision Making in Kenya

Science.gov (United States)

Wahome, A.; Ndubi, A. O.; Ndungu, L. W.; Mugo, R. M.; Flores Cordova, A. I.

2017-12-01

Kenya relies on agricultural production for supporting local consumption and other processing value chains. With changing climate in a rain-fed dependent agricultural production system, cropping zones are shifting and proper decision making will require updated data. Where up-to-date data is not available it is important that it is generated and passed over to relevant stakeholders to inform their decision making. The process of generating this data should be cost effective and less time consuming. The Kenyan State Department of Agriculture (SDA) runs an insurance programme for maize farmers in a number of counties in Kenya. Previously, SDA was using a list of farmers to identify the crop fields for this insurance programme. However, the process of listing of all farmers in each Unit Area of Insurance (UAI) proved to be tedious and very costly, hence need for an alternative approach, but acceptable sampling methodology. Building on the existing cropland maps, SERVIR, a joint NASA-USAID initiative that brings Earth observations (EO) for improved environmental decision making in developing countries, specifically its hub in Eastern and Soutehrn Africa developed a High Resolution Map based on 10m Sentinel satellite images from which a GIS based sampling frame for identifying maize fields was developed. Sampling points were randomly generated in each UAI and navigated to using hand-held GPS units for identification of maize farmers. In the GIS-based identification of farmers SDA uses 1 day to cover an area covered in 1 week by list identification of farmers. Similarly, SDA spends approximately 3,000 USD per sub-county to locate maize fields using GIS-based sampling as compared 10,000 USD they used to spend before. This has resulted in 70% cost reduction.

Distributed, signal strength-based indoor localization algorithm for use in healthcare environments.

Science.gov (United States)

Wyffels, Jeroen; De Brabanter, Jos; Crombez, Pieter; Verhoeve, Piet; Nauwelaers, Bart; De Strycker, Lieven

2014-11-01

In current healthcare environments, a trend toward mobile and personalized interactions between people and nurse call systems is strongly noticeable. Therefore, it should be possible to locate patients at all times and in all places throughout the care facility. This paper aims at describing a method by which a mobile node can locate itself indoors, based on signal strength measurements and a minimal amount of yes/no decisions. The algorithm has been developed specifically for use in a healthcare environment. With extensive testing and statistical support, we prove that our algorithm can be used in a healthcare setting with an envisioned level of localization accuracy up to room revel (or region level in a corridor), while avoiding heavy investments since the hardware of an existing nurse call network can be reused. The approach opted for leads to very high scalability, since thousands of mobile nodes can locate themselves. Network timing issues and localization update delays are avoided, which ensures that a patient can receive the needed care in a time and resources efficient way.

The usefulness of financial reporting for internal decision-making in portuguese municipalities

OpenAIRE

Nogueira, Sónia P.; Jorge, Susana M.; Cervera Oliver, Mercedes

2013-01-01

The purpose of this paper is to analyse the perception of internal users regarding the usefulness of municipal financial reporting in the context of decision-making in Portuguese Local Administration. This research is quantitative and positive, based on a cross-section analysis through online application of a questionnaire to decision-makers (politicians and technicians) of the 308 Portuguese municipalities. The approach is based on the information usefulness paradigm. Results indicate a...

Dual entanglement measures based on no local cloning and no local deleting

International Nuclear Information System (INIS)

Horodecki, Michal; Sen, Aditi; Sen, Ujjwal

2004-01-01

The impossibility of cloning and deleting of unknown states constitute important restrictions on processing of information in the quantum world. On the other hand, a known quantum state can always be cloned or deleted. However, if we restrict the class of allowed operations, there will arise restrictions on the ability of cloning and deleting machines. We have shown that cloning and deleting of known states is in general not possible by local operations. This impossibility hints at quantum correlation in the state. We propose dual measures of quantum correlation based on the dual restrictions of no local cloning and no local deleting. The measures are relative entropy distances of the desired states in a (generally impossible) perfect local cloning or local deleting process from the best approximate state that is actually obtained by imperfect local cloning or deleting machines. Just like the dual measures of entanglement cost and distillable entanglement, the proposed measures are based on important processes in quantum information. We discuss their properties. For the case of pure states, estimations of these two measures are also provided. Interestingly, the entanglement of cloning for a maximally entangled state of two two-level systems is not unity

MRI-based decision tree model for diagnosis of biliary atresia.

Science.gov (United States)

Kim, Yong Hee; Kim, Myung-Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, Mi-Jung

2018-02-23

To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

Financial Management and Control for Decision Making in Urban Local Bodies in India Using Statistical Techniques

Science.gov (United States)

Bhattacharyya, Sidhakam; Bandyopadhyay, Gautam

2010-10-01

The council of most of the Urban Local Bodies (ULBs) has a limited scope for decision making in the absence of appropriate financial control mechanism. The information about expected amount of own fund during a particular period is of great importance for decision making. Therefore, in this paper, efforts are being made to present set of findings and to establish a model of estimating receipts of own sources and payments thereof using multiple regression analysis. Data for sixty months from a reputed ULB in West Bengal have been considered for ascertaining the regression models. This can be used as a part of financial management and control procedure by the council to estimate the effect on own fund. In our study we have considered two models using multiple regression analysis. "Model I" comprises of total adjusted receipt as the dependent variable and selected individual receipts as the independent variables. Similarly "Model II" consists of total adjusted payments as the dependent variable and selected individual payments as independent variables. The resultant of Model I and Model II is the surplus or deficit effecting own fund. This may be applied for decision making purpose by the council.

Economic Learning Media Development Based on Local Locality

Science.gov (United States)

Hadi, Rizali; Supriyanto; Hasanah, Mahmudah

2017-01-01

This study aims to describe the learning medium of economic education at senior High School in Banjarmasin with media based on local wisdom. This research uses qualitative method as developed by Miles & Huberman, starting from data collection, data reduction data display, and then made conclusion. Data were collected in the order of Basic…

Robust 3D face landmark localization based on local coordinate coding.

Science.gov (United States)

Song, Mingli; Tao, Dacheng; Sun, Shengpeng; Chen, Chun; Maybank, Stephen J

2014-12-01

In the 3D facial animation and synthesis community, input faces are usually required to be labeled by a set of landmarks for parameterization. Because of the variations in pose, expression and resolution, automatic 3D face landmark localization remains a challenge. In this paper, a novel landmark localization approach is presented. The approach is based on local coordinate coding (LCC) and consists of two stages. In the first stage, we perform nose detection, relying on the fact that the nose shape is usually invariant under the variations in the pose, expression, and resolution. Then, we use the iterative closest points algorithm to find a 3D affine transformation that aligns the input face to a reference face. In the second stage, we perform resampling to build correspondences between the input 3D face and the training faces. Then, an LCC-based localization algorithm is proposed to obtain the positions of the landmarks in the input face. Experimental results show that the proposed method is comparable to state of the art methods in terms of its robustness, flexibility, and accuracy.

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

Science.gov (United States)

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

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. 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. 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. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratiodecisions 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. 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.

Explanatory factors for the use of the financial report in decision-making: Evidence from Local Government in Portugal

Directory of Open Access Journals (Sweden)

Sónia Paula S. Nogueira

2016-07-01

Two important implications of this study are the following: first, professional bodies and the financial situation in the country; while stimulating informational needs by internal users in the public sector they determine the usefulness they offer to financial reporting for decision-making. Second, the lack of knowledge of the accounting information system, especially by local politicians, is a hindering factor of the usefulness given to financial reporting for internal decision-making. Nowadays, when many countries are considering reforms of public sector accounting in line with the International Public Sector Accounting Standards (IPSAS, supposedly increasing the sophistication, the level of information and usefulness of financial reporting, such factors must be taken into account.

Development of a greenhouse gas accounting GIS-based tool to support local policy making—application to an Italian municipality

International Nuclear Information System (INIS)

Asdrubali, F.; Presciutti, A.; Scrucca, F.

2013-01-01

Climate change is the issue of the century and, according to Agenda 21, local actions are essential to impact global mitigation of greenhouse gases (GHG) emissions (“think globally, act locally”). However, in order to plan and implement effective, sustainable actions, local authorities need detailed information on their GHG emissions and their sources. This paper presents the work that led to the development of a GIS-based tool for local GHG accounting, which provides data for local decision-makers in an innovative manner different from traditional GHG inventories. The original aspects of the study are the geo-referencing of all results and the possibility of calculating all emissions (carbon sources) and removals (carbon sinks) with input data of different accuracy. - Highlights: • We developed a GIS-based tool for local (municipal) GHG accounting. • All emissions (carbon sources) and removals (carbon sinks) are geo-referenced. • The tool can be used with different levels of input data (less or more accurate). • The town of Spoleto (Italy) was chosen to apply and validate both methodologies. • The tool is effective to monitor the energy and environmental policies of the municipality

Using interactive modeling tools to engage with, inform and empower decision making in local communities of landscape managers

DEFF Research Database (Denmark)

Christensen, Andreas Aagaard

During the last decade digital modelling tools for environmental impact assessment have become increasingly interactive, agile and user-oriented. This has made it possible to implement models in situ, using them in live scenario situations with local stakeholders. As a result modelling tools......- and long term environmental impact of landscape management. This opens up a number of questions regarding the status and consequence of scientific data and modelled impact estimates as compared to locally held knowledge and expertise. It also opens up questions regarding how the injection of modelling...... for modelling the effect of agricultural land use decisions on nitrogen emission to the environment at landscape scales. Recently Danish authorities proposed to shift the scale of regulation from national regulatory instruments to a more local level to better fit relevant socio-political and agro-environmental...

Arriba-lib: association of an evidence-based electronic library of decision aids with communication and decision-making in patients and primary care physicians.

Science.gov (United States)

Hirsch, Oliver; Keller, Heidemarie; Krones, Tanja; Donner-Banzhoff, Norbert

2012-03-01

In shared decision-making, patients are empowered to actively ask questions and participate in decisions about their healthcare based on their preferences and values. Decision aids should help patients make informed choices among diagnostic or treatment options by delivering evidence-based information on options and outcomes; however, they have rarely been field tested, especially in the primary care context. We therefore evaluated associations between the use of an interactive, transactional and evidence-based library of decision aids (arriba-lib) and communication and decision-making in patients and physicians in the primary care context. Our electronic library of decision aids ('arriba-lib') includes evidence-based modules for cardiovascular prevention, diabetes, coronary heart disease, atrial fibrillation and depression. Twenty-nine primary care physicians recruited 192 patients. We used questionnaires to ask patients and physicians about their experiences with and attitudes towards the programme. Patients were interviewed via telephone 2 months after the consultation. Data were analysed by general estimation equations, cross tab analyses and by using effect sizes. Only a minority (8.9%) of the consultations were felt to be too long because physicians said consultations were unacceptably extended by arriba-lib. We found a negative association between the detailedness of the discussion of the clinical problem's definition and the age of the patients. Physicians discuss therapeutic options in less detail with patients who have a formal education of less than 8 years. Patients who were counselled by a physician with no experience in using a decision aid more often reported that they do not remember being counselled with the help of a decision aid or do not wish to be counselled again with a decision aid. Arriba-lib has positive associations to the decision-making process in patients and physicians. It can also be used with older age groups and patients with less

Maintenance planning support method for nuclear power plants based on collective decision making

International Nuclear Information System (INIS)

Shimizu, Shunichi; Sakurai, Shoji; Takaoka, Kazushi; Kanemoto, Shigeru; Fukutomi, Shigeki

1992-01-01

Inspection and maintenance planning in nuclear power plants is conducted by decision making based on experts' collective consensus. However, since a great deal of time and effort is required to reach a consensus among expert judgments, the establishment of effective decision making methods is necessary. Therefore, the authors developed a method for supporting collective decision making, based on a combination of three types of decision making methods; the Characteristic Diagram method, Interpretative Structural Modeling method, and the Analytic Hierarchy Process method. The proposed method enables us to determine the evaluation criteria systematically for collective decision making, and also allows extracting collective decisions using simplified questionnaires. The proposed method can support reaching a consensus of groups effectively through the evaluation of collective decision structural models and their characteristics. In this paper, the effectiveness of the proposed method was demonstrated through its application to the decision making problem concerning whether or not the improved ultrasonic testing equipment should be adopted at nuclear power plants. (author)

Framing water and forests as global or local? Transnational community-based networks transforming common-pool resources essence and scales

OpenAIRE

Dupuits, Emilie; Pflieger, Géraldine

2017-01-01

The current era of globalization and commodification has had a substantial impact on common-pool resources governance. In direct response to this, community-based organizations managing water and forests at the local level began to create their own transnational networks. Primarily, these organizations aim to achieve direct representation in international decision-making arenas in order to promote their model of collective governance. By reframing the representations of common-pool resources ...

Building organizational knowledge and value: informed decision making in Kansas children's community-based mental health services.

Science.gov (United States)

Stipp, Karen Flint; Kapp, Stephen A

2012-02-01

Knowledge is managers' principal asset and knowledge building is managers' primary work. This qualitative study explores knowledge building by directors of children's community-based mental health services in Kansas. Of the state's 27 directors, 25 completed a survey about knowledge building, in their preference of online or telephone format. Fourteen participants took part either in preliminary interviews for study development, or in follow-up interviews for further detail and member checking. Study findings indicate that with requisite resources, directors inform their decision making with streams of information, which they manage and generate to build organizational knowledge and value for local practice effectiveness.

Teaching advance care planning to medical students with a computer-based decision aid.

Science.gov (United States)

Green, Michael J; Levi, Benjamin H

2011-03-01

Discussing end-of-life decisions with cancer patients is a crucial skill for physicians. This article reports findings from a pilot study evaluating the effectiveness of a computer-based decision aid for teaching medical students about advance care planning. Second-year medical students at a single medical school were randomized to use a standard advance directive or a computer-based decision aid to help patients with advance care planning. Students' knowledge, skills, and satisfaction were measured by self-report; their performance was rated by patients. 121/133 (91%) of students participated. The Decision-Aid Group (n = 60) outperformed the Standard Group (n = 61) in terms of students' knowledge (p satisfaction with their learning experience (p student performance. Use of a computer-based decision aid may be an effective way to teach medical students how to discuss advance care planning with cancer patients.

Approach of simultaneous localization and mapping based on local maps for robot

Institute of Scientific and Technical Information of China (English)

CHEN Bai-fan; CAI Zi-xing; HU De-wen

2006-01-01

An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps.A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.

Local Decisions and Global Networks

Science.gov (United States)

King, David C.; Long, Cathryn J.

1976-01-01

Impact of economic and urban planning on the natural environment can be studied through local situations: California conservation students realized the detrimental effects of a seemingly beneficial dam project. Students were inspired to initiate community-state action to correct damage to wildlife, sanitation, and farming. (AV)

Knowledge-Based Information Management in Decision Support for Ecosystem Management

Science.gov (United States)

Keith Reynolds; Micahel Saunders; Richard Olson; Daniel Schmoldt; Michael Foster; Donald Latham; Bruce Miller; John Steffenson; Lawrence Bednar; Patrick Cunningham

1995-01-01

The Pacific Northwest Research Station (USDA Forest Service) is developing a knowledge-based information management system to provide decision support for watershed analysis in the Pacific Northwest region of the U.S. The decision support system includes: (1) a GIS interface that allows users to graphically navigate to specific provinces and watersheds and display a...

Nicotine replacement therapy decision based on fuzzy multi-criteria analysis

Science.gov (United States)

Tarmudi, Zamali; Matmali, Norfazillah; Abdullah, Mohd Lazim

2017-08-01

It has been observed that Nicotine Replacement Therapy (NRT) is one of the alternatives to control and reduce smoking addiction among smokers. Since the decision to choose the best NRT alternative involves uncertainty, ambiguity factors and diverse input datasets, thus, this paper proposes a fuzzy multi-criteria analysis (FMA) to overcome these issues. It focuses on how the fuzzy approach can unify the diversity of datasets based on NRT's decision-making problem. The analysis done employed the advantage of the cost-benefit criterion to unify the mixture of dataset input. The performance matrix was utilised to derive the performance scores. An empirical example regarding the NRT's decision-making problem was employed to illustrate the proposed approach. Based on the calculations, this analytical approach was found to be highly beneficial in terms of usability. It was also very applicable and efficient in dealing with the mixture of input datasets. Hence, the decision-making process can easily be used by experts and patients who are interested to join the therapy/cessation program.

Finger Vein Recognition Based on Local Directional Code

Science.gov (United States)

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger Vein Recognition Based on Local Directional Code

Directory of Open Access Journals (Sweden)

Rongyang Xiao

2012-11-01

Full Text Available Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP, Local Derivative Pattern (LDP and Local Line Binary Pattern (LLBP. However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD, this paper represents a new direction based local descriptor called Local Directional Code (LDC and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

Permutation based decision making under fuzzy environment using Tabu search

Directory of Open Access Journals (Sweden)

Mahdi Bashiri

2012-04-01

Full Text Available One of the techniques, which are used for Multiple Criteria Decision Making (MCDM is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method.

Examining Preservice Teachers' Decision Behaviors and Individual Differences in Three Online Case-Based Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

International Nuclear Information System (INIS)

Luo, Y; McShan, D; Schipper, M; Matuszak, M; Ten Haken, R; Kong, F

2014-01-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for

Factors influencing the clinical decision-making of midwives: a qualitative study.

Science.gov (United States)

Daemers, Darie O A; van Limbeek, Evelien B M; Wijnen, Hennie A A; Nieuwenhuijze, Marianne J; de Vries, Raymond G

2017-10-06

Although midwives make clinical decisions that have an impact on the health and well-being of mothers and babies, little is known about how they make those decisions. Wide variation in intrapartum decisions to refer women to obstetrician-led care suggests that midwives' decisions are based on more than the evidence based medicine (EBM) model - i.e. clinical evidence, midwife's expertise, and woman's values - alone. With this study we aimed to explore the factors that influence clinical decision-making of midwives who work independently. We used a qualitative approach, conducting in-depth interviews with a purposive sample of 11 Dutch primary care midwives. Data collection took place between May and September 2015. The interviews were semi-structured, using written vignettes to solicit midwives' clinical decision-making processes (Think Aloud method). We performed thematic analysis on the transcripts. We identified five themes that influenced clinical decision-making: the pregnant woman as a whole person, sources of knowledge, the midwife as a whole person, the collaboration between maternity care professionals, and the organisation of care. Regarding the midwife, her decisions were shaped not only by her experience, intuition, and personal circumstances, but also by her attitudes about physiology, woman-centredness, shared decision-making, and collaboration with other professionals. The nature of the local collaboration between maternity care professionals and locally-developed protocols dominated midwives' clinical decision-making. When midwives and obstetricians had different philosophies of care and different practice styles, their collaborative efforts were challenged. Midwives' clinical decision-making is a more varied and complex process than the EBM framework suggests. If midwives are to succeed in their role as promoters and protectors of physiological pregnancy and birth, they need to understand how clinical decisions in a multidisciplinary context are

Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

International Nuclear Information System (INIS)

Ohdaira, Tetsushi

2014-01-01

Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision. (paper)

Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

Science.gov (United States)

Ohdaira, Tetsushi

2014-07-01

Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision.

Support System Model for Value based Group Decision on Roof System Selection

Directory of Open Access Journals (Sweden)

Christiono Utomo

2011-02-01

Full Text Available A group decision support system is required on a value-based decision because there are different concern caused by differing preferences, experiences, and background. It is to enable each decision-maker to evaluate and rank the solution alternatives before engaging into negotiation with other decision-makers. Stakeholder of multi-criteria decision making problems usually evaluates the alternative solution from different perspective, making it possible to have a dominant solution among the alternatives. Each stakeholder needs to identify the goals that can be optimized and those that can be compromised in order to reach an agreement with other stakeholders. This paper presents group decision model involving three decision-makers on the selection of suitable system for a building’s roof. The objective of the research is to find an agreement options model and coalition algorithms for multi person decision with two main preferences of value which are function and cost. The methodology combines value analysis method using Function Analysis System Technique (FAST; Life Cycle Cost analysis, group decision analysis method based on Analytical Hierarchy Process (AHP in a satisfying options, and Game theory-based agent system to develop agreement option and coalition formation for the support system. The support system bridges theoretical gap between automated design in construction domain and automated negotiation in information technology domain by providing a structured methodology which can lead to systematic support system and automated negotiation. It will contribute to value management body of knowledge as an advanced method for creativity and analysis phase, since the practice of this knowledge is teamwork based. In the case of roof system selection, it reveals the start of the first negotiation round. Some of the solutions are not an option because no individual stakeholder or coalition of stakeholders desires to select it. The result indicates

Framing the decision to contract out elderly care and primary health care services – perspectives of local level politicians and civil servants in Finland

Directory of Open Access Journals (Sweden)

Tynkkynen Liina-Kaisa

2012-07-01

Full Text Available Abstract Background In the literature there are only few empirical studies that analyse the decision makers’ reasoning to contract out health care and social services to private sector. However, the decisions on the delivery patterns of health care and social services are considered to be of great importance as they have a potential to influence citizens’ access to services and even affect their health. This study contributes to filling this cap by exploring the frames used by Finnish local authorities as they talk about contracting out of primary health care and elderly care services. Contracting with the private sector has gained increasing popularity, in Finland, during the past decade, as a practise of organising health care and social services. Methods Interview data drawn from six municipalities through thematic group interviews were used. The data were analysed applying frame analysis in order to reveal the underlying reasoning for the decisions. Results Five argumentation frames were found: Rational reasoning; Pragmatic realism; Promoting diversity among providers; Good for the municipality; Good for the local people. The interviewees saw contracting with the private sector mostly as a means to improve the performance of public providers, to improve service quality and efficiency and to boost the local economy. The decisions to contract out were mainly argued through the good for the municipal administration, political and ideological commitments, available resources and existing institutions. Conclusions This study suggests that the policy makers use a number of grounds to justify their decisions on contracting out. Most of the arguments were related to the benefits of the municipality rather than on what is best for the local people. The citizens were offered the role of active consumers who are willing to purchase services also out-of-pocket. This development has a potential to endanger the affordability of the services and lead

CONTEXT-CAPTURE MULTI-VALUED DECISION FUSION WITH FAULT TOLERANT CAPABILITY FOR WIRELESS SENSOR NETWORKS

OpenAIRE

Jun Wu; Shigeru Shimamoto

2011-01-01

Wireless sensor networks (WSNs) are usually utilized to perform decision fusion of event detection. Current decision fusion schemes are based on binary valued decision and do not consider bursty contextcapture. However, bursty context and multi-valued data are important characteristics of WSNs. One on hand, the local decisions from sensors usually have bursty and contextual characteristics. Fusion center must capture the bursty context information from the sensors. On the other hand, in pract...

Interval-Valued Intuitionistic Fuzzy Multicriteria Group Decision Making Based on VIKOR and Choquet Integral

Directory of Open Access Journals (Sweden)

Chunqiao Tan

2013-01-01

Full Text Available An effective decision making approach based on VIKOR and Choquet integral is developed to solve multicriteria group decision making problem with conflicting criteria and interdependent subjective preference of decision makers in a fuzzy environment where preferences of decision makers with respect to criteria are represented by interval-valued intuitionistic fuzzy sets. First, an interval-valued intuitionistic fuzzy Choquet integral operator is given. Some of its properties are investigated in detail. The extended VIKOR decision procedure based on the proposed operator is developed for solving the multicriteria group decision making problem where the interactive criteria weight is measured by Shapley value. An illustrative example is given for demonstrating the applicability of the proposed decision procedure for solving the multi-criteria group decision making problem in interval-valued intuitionistic fuzzy environment.

Multi-objective decision-making model based on CBM for an aircraft fleet

Science.gov (United States)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

Agent-based Decision Support System for the Third Generation Distributed Dynamic Decision-making (DDD-III) Simulator

National Research Council Canada - National Science Library

Meirina, Candra; Ruan, Sui; Yu, Feili; Zhu, Liang; Pattipati, Krishna R; Kleinman, David L

2004-01-01

...) based on the third-generation distributed dynamic decision-making (DDD-III) simulator and contingency theory to increase the organizational cognitive capacity and to facilitate the processes of adaptation...

Using structured decision making to manage disease risk for Montana wildlife

Science.gov (United States)

Mitchell, Michael S.; Gude, Justin A.; Anderson, Neil J.; Ramsey, Jennifer M.; Thompson, Michael J.; Sullivan, Mark G.; Edwards, Victoria L.; Gower, Claire N.; Cochrane, Jean Fitts; Irwin, Elise R.; Walshe, Terry

2013-01-01

We used structured decision-making to develop a 2-part framework to assist managers in the proactive management of disease outbreaks in Montana, USA. The first part of the framework is a model to estimate the probability of disease outbreak given field observations available to managers. The second part of the framework is decision analysis that evaluates likely outcomes of management alternatives based on the estimated probability of disease outbreak, and applies managers' values for different objectives to indicate a preferred management strategy. We used pneumonia in bighorn sheep (Ovis canadensis) as a case study for our approach, applying it to 2 populations in Montana that differed in their likelihood of a pneumonia outbreak. The framework provided credible predictions of both probability of disease outbreaks, as well as biological and monetary consequences of management actions. The structured decision-making approach to this problem was valuable for defining the challenges of disease management in a decentralized agency where decisions are generally made at the local level in cooperation with stakeholders. Our approach provides local managers with the ability to tailor management planning for disease outbreaks to local conditions. Further work is needed to refine our disease risk models and decision analysis, including robust prediction of disease outbreaks and improved assessment of management alternatives.

Beyond Bioethics: A Child Rights-Based Approach to Complex Medical Decision-Making.

Science.gov (United States)

Wade, Katherine; Melamed, Irene; Goldhagen, Jeffrey

2016-01-01

This analysis adopts a child rights approach-based on the principles, standards, and norms of child rights and the U.N. Convention on the Rights of the Child (CRC)-to explore how decisions could be made with regard to treatment of a severely impaired infant (Baby G). While a child rights approach does not provide neat answers to ethically complex issues, it does provide a framework for decision-making in which the infant is viewed as an independent rights-holder. The state has obligations to develop the capacity of those who make decisions for infants in such situations to meet their obligations to respect, protect, and fulfill their rights as delineated in the CRC. Furthermore, a child rights approach requires procedural clarity and transparency in decision-making processes. As all rights in the CRC are interdependent and indivisible, all must be considered in the process of ethical decision-making, and the reasons for decisions must be delineated by reference to how these rights were considered. It is also important that decisions that are made in this context be monitored and reviewed to ensure consistency. A rights-based framework ensures decision-making is child-centered and that there are transparent criteria and legitimate procedures for making decisions regarding the child's most basic human right: the right to life, survival, and development.

Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks

International Nuclear Information System (INIS)

Busch, Jonathan; Roelich, Katy; Bale, Catherine S.E.; Knoeri, Christof

2017-01-01

The potential contribution of local energy infrastructure – such as heat networks – to the transition to a low carbon economy is increasingly recognised in international, national and municipal policy. Creating the policy environment to foster the scaling up of local energy infrastructure is, however, still challenging; despite national policy action and local authority interest the growth of heat networks in UK cities remains slow. Techno-economic energy system models commonly used to inform policy are not designed to address institutional and governance barriers. We present an agent-based model of heat network development in UK cities in which policy interventions aimed at the institutional and governance barriers faced by diverse actors can be explored. Three types of project instigators are included – municipal, commercial and community – which have distinct decision heuristics and capabilities and follow a multi-stage development process. Scenarios of policy interventions developed in a companion modelling approach indicate that the effect of interventions differs between actors depending on their capabilities. Successful interventions account for the specific motivations and capabilities of different actors, provide a portfolio of support along the development process and recognise the important strategic role of local authorities in supporting low carbon energy infrastructure. - Highlights: • Energy policy should account for diverse actor motivations and capabilities. • Project development is a multi-stage process, not a one-off event. • Participatory agent-based modelling can inform policy that accounts for complexity. • Policy should take a portfolio approach to providing support. • Local authorities have an important strategic role in local infrastructure.

Decision Making Based On Management Information System and Decision Support System

Directory of Open Access Journals (Sweden)

Şükrü Ada

2015-04-01

Full Text Available Information hasbecome an essentialresource for managing modern organizations. This is so because today’sbusiness environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete,timely and economical information needed to drive the decision-making process in order to accentuate organizational abilities to manage opportunities and threat. MIS work on online mode with an average processing speed. Generally, it is used by low level management. Decision support system are powerful tool that assist corporate executives, administrators and other senior officials in making decision regarding the problem. Management Information Systems is a useful tool that provided organized and summarized information in a proper time to decision makers and enable making accurate decision for managers in organizations. This paper will discuss the concept, characteristics, types of MIS, the MIS model, and in particular it will highlight the impact and role of MIS on decision making.

Managing wildfire events: risk-based decision making among a group of federal fire managers

Science.gov (United States)

Robyn S. Wilson; Patricia L. Winter; Lynn A. Maguire; Timothy. Ascher

2011-01-01

Managing wildfire events to achieve multiple management objectives involves a high degree of decision complexity and uncertainty, increasing the likelihood that decisions will be informed by experience-based heuristics triggered by available cues at the time of the decision. The research reported here tests the prevalence of three risk-based biases among 206...

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

Science.gov (United States)

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…

Optimization-based decision support systems for planning problems in processing industries

OpenAIRE

Claassen, G.D.H.

2014-01-01

Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. T...

Optimization-based decision support systems for planning problems in processing industries

NARCIS (Netherlands)

Claassen, G.D.H.

2014-01-01

Summary

Optimization-based decision support systems for planning problems in processing industries

Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in

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

Science.gov (United States)

Jones, M.; Pitts, R.

2017-12-01

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

A Multiple Criteria Decision Making Method Based on Relative Value Distances

Directory of Open Access Journals (Sweden)

Shyur Huan-jyh

2015-12-01

Full Text Available This paper proposes a new multiple criteria decision-making method called ERVD (election based on relative value distances. The s-shape value function is adopted to replace the expected utility function to describe the risk-averse and risk-seeking behavior of decision makers. Comparisons and experiments contrasting with the TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution method are carried out to verify the feasibility of using the proposed method to represent the decision makers’ preference in the decision making process. Our experimental results show that the proposed approach is an appropriate and effective MCDM method.

Multiattribute Decision Making Based on Entropy under Interval-Valued Intuitionistic Fuzzy Environment

Directory of Open Access Journals (Sweden)

Yingjun Zhang

2013-01-01

Full Text Available Multiattribute decision making (MADM is one of the central problems in artificial intelligence, specifically in management fields. In most cases, this problem arises from uncertainty both in the data derived from the decision maker and the actions performed in the environment. Fuzzy set and high-order fuzzy sets were proven to be effective approaches in solving decision-making problems with uncertainty. Therefore, in this paper, we investigate the MADM problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy (IVIF set (IVIFS. We first propose a new definition of IVIF entropy and some calculation methods for IVIF entropy. Furthermore, we propose an entropy-based decision-making method to solve IVIF MADM problems with completely unknown attribute weights. Particular emphasis is put on assessing the attribute weights based on IVIF entropy. Instead of the traditional methods, which use divergence among attributes or the probabilistic discrimination of attributes to obtain attribute weights, we utilize the IVIF entropy to assess the attribute weights based on the credibility of the decision-making matrix for solving the problem. Finally, a supplier selection example is given to demonstrate the feasibility and validity of the proposed MADM method.

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

Science.gov (United States)

Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

2017-01-01

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

A GIS-based decision support system for regional eco-security assessment and its application on the Tibetan Plateau.

Science.gov (United States)

Xiaodan, Wang; Xianghao, Zhong; Pan, Gao

2010-10-01

Regional eco-security assessment is an intricate, challenging task. In previous studies, the integration of eco-environmental models and geographical information systems (GIS) usually takes two approaches: loose coupling and tight coupling. However, the present study used a full coupling approach to develop a GIS-based regional eco-security assessment decision support system (ESDSS). This was achieved by merging the pressure-state-response (PSR) model and the analytic hierarchy process (AHP) into ArcGIS 9 as a dynamic link library (DLL) using ArcObjects in ArcGIS and Visual Basic for Applications. Such an approach makes it easy to capitalize on the GIS visualization and spatial analysis functions, thereby significantly supporting the dynamic estimation of regional eco-security. A case study is presented for the Tibetan Plateau, known as the world's "third pole" after the Arctic and Antarctic. Results verified the usefulness and feasibility of the developed method. As a useful tool, the ESDSS can also help local managers to make scientifically-based and effective decisions about Tibetan eco-environmental protection and land use. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

[Evidence-based Risk and Benefit Communication for Shared Decision Making].

Science.gov (United States)

Nakayama, Takeo

2018-01-01

　Evidence-based medicine (EBM) can be defined as "the integration of the best research evidence with clinical expertise and a patient's unique values and circumstances". However, even with the best research evidence, many uncertainties can make clinical decisions difficult. As the social requirement of respecting patient values and preferences has been increasingly recognized, shared decision making (SDM) and consensus development between patients and clinicians have attracted attention. SDM is a process by which patients and clinicians make decisions and arrive at a consensus through interactive conversations and communications. During the process of SDM, patients and clinicians share information with each other on the goals they hope to achieve and responsibilities in meeting those goals. From the clinician's standpoint, information regarding the benefits and risks of potential treatment options based on current evidence and professional experience is provided to patients. From the patient's standpoint, information on personal values, preferences, and social roles is provided to clinicians. SDM is a sort of "wisdom" in the context of making autonomous decisions in uncertain, difficult situations through interactions and cooperation between patients and clinicians. Joint development of EBM and SDM will help facilitate patient-clinician relationships and improve the quality of healthcare.

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

Science.gov (United States)

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

Application of ann-based decision making pattern recognition to fishing operations

Energy Technology Data Exchange (ETDEWEB)

Akhlaghinia, M.; Torabi, F.; Wilton, R.R. [University of Regina, Saskatchewan (Canada). Faculty of Engineering. Dept. of Petroleum Engineering], e-mail: Farshid.Torabi@uregina.ca

2010-10-15

Decision making is a crucial part of fishing operations. Proper decisions should be made to prevent wasted time and associated costs on unsuccessful operations. This paper presents a novel model to help drilling managers decide when to commence and when to quit a fishing operation. A decision making model based on Artificial Neural Network (ANN) has been developed that utilizes Pattern Recognition based on 181 fishing incidents from one of the most fish-prone fields of the southwest of Iran. All parameters chosen to train the ANN-Based Pattern Recognition Tool are assumed to play a role in the success of the fishing operation and are therefore used to decide whether a fishing operation should be performed or not. If the tool deems the operation suitable for consideration, a cost analysis of the fishing operation can then be performed to justify its overall cost. (author)

Public participation in decision-making for contaminated sites

International Nuclear Information System (INIS)

Till, J.E.; Sharp, S.L.

2000-01-01

Public participation is critical in environmental decision-making. This paper provides three examples of public participation in the decision making process. The first example illustrates the effectiveness of public involvement when incorporated at the beginning of a project. The second example shows the loss of trust by a community resulting from the lack of public involvement. The third example demonstrates public involvement in making risk-based decisions for corrective action in a non-radiological situation. The first site is the Los Alamos National Laboratory where a lawsuit filed by local citizens led to an independent audit of the laboratory's compliance with the Clean Air Act for radionuclides. The audit team involved the public extensively, resulting in close interaction during the audit and a better understanding by the public of the regulations. The second site is the Rocky Flats Plant nuclear weapons facility, which is being decommissioned and the surrounding property will ultimately be available for public use. The Department of Energy proposed a cleanup level but the level was developed with little public input and has been criticized widely by local residents. As a result, the target cleanup levels are being reevaluated by an independent contractor with oversight from a panel of local members of the public. Working with the independent contractor, the panel proposed new cleanup standards to the Department of Energy. The third site is a bulk oil and terminal where chemicals have migrated offsite into a residential area. Facility owners have initiated a public involvement program to help the community understand the potential risks involved and alternatives for remedial action. The public is playing a key role in the risk-based decision making process. Each of these examples illustrates the importance of public participation in different situations. (author)

Decision and Inhibitory Trees for Decision Tables with Many-Valued Decisions

KAUST Repository

Azad, Mohammad

2018-06-06

inconsistency of decision tables. We also analyze the time complexity of decision and inhibitory trees over arbitrary sets of attributes represented by information systems in the frameworks of local (when we can use in trees only attributes from problem description) and global (when we can use in trees arbitrary attributes from the information system) approaches.

FINANCIAL MANAGEMENT AND LOCAL ECONOMIC DEVELOPMENT AN ALTERNATIVE FOR NEW FUNDING SOURCES OF THE LOCAL COMMUNITIES

Directory of Open Access Journals (Sweden)

Filip Petru

2010-12-01

Full Text Available This paper intends to answer mainly the questions: What are the consequences of the taxation base increase? What forms does the taxation base have? What can local authorities do in order to make certain areas attractive? Which are the specific players involved in the local economic development? Also, beyond the rigours imposed by the mathematical presentation of the sustainable economic development, we appreciate that for the financial management, too, knowing the gear determined by the allocation of public resources and generation of additional revenues will be very useful in establishing and underlying the decisions to invest in the public infrastructure and, also, to calculate the time period in which these can be depreciated especially based on the financial flows from supplementary revenues.

THE ACCOUNTING INFORMATION SUPPORT FOR THE FINANCIAL DECISION

Directory of Open Access Journals (Sweden)

CARUNTU GENU ALEXANDRU

2017-11-01

Full Text Available The complexity of economic life, in the conditions of the competition imposed by the market economy, determines the increase of the role of accounting information in the current and prospective decisions and implicitly the obtained results. In basing and substantiating decisions, accounting plays an essential role. Regardless of the level at which the manager is located, the manager manages his area of responsibility, triggering actions that, through consumption of resources, lead to economic gains. The accounting information is intended for the manager, who must respond to the allocation of resources entrusted by investors to achieve the objectives set and how the allocated resources have been used. The notion of users of accounting information can not be limited to the groups analyzed so far. The evolution of a firm and its decisions is of interest to all those who make economic decisions based on their relationship with this entity and their knowledge of it. Thus, the policy makers of local communities are concerned about the contribution of society to the development of the local economy (jobs, training, taxes, etc., environmental and consumer protection efforts are focused on the consequences of the company's activity, competitors want to assess the position of the enterprise on the market , consumers want to know whether there is a monopoly situation and to what extent they may be exploited, and researchers are generally interested in the form, content and quality of annual reports.

Risk-based decision making and risk management of European Union regional programs

Directory of Open Access Journals (Sweden)

Michalopoulos Evangelos

2008-01-01

Full Text Available This paper presents a generalized method for management decision making incorporating risk assessment techniques. The risk based decision making methodology is applied to European Union expenditure programs used to implement its regional policy, such as the community support framework, community initiatives, special initiatives and other European policies. An example is presented for the development of an audit (inspection program in the region of West Macedonia, Greece, during the implementation of the 3rd Community Structural Support Framework Operational Program. The generic nature of the method permits its use in the management of similar European regional programs in Greece and other European countries. It is also applicable to many other industries interested in applying risk-based management decisions to physical or process based systems. .

Microprocessor-based, on-line decision aid for resolving conflicting nuclear reactor instrumentation

International Nuclear Information System (INIS)

Alesso, H.P.

1981-01-01

We describe one design for a microprocessor-based, on-line decision aid for identifying and resolving false, conflicting, or misleading instrument indications resulting from certain systems interactions for a pressurized water reactor. The system processes sensor signals from groups of instruments that track together under nominal transient and certain accident conditions, and alarms when they do not track together. We examine multiple-casualty systems interaction and formulate a trial grouping of variables that track together under specified conditions. A two-of-three type redundancy check of key variables provides alarm and indication of conflicting information when one signal suddenly tracks in opposition due to multiple casualty, instrument failure, and/or locally abnormal conditions. Since a vote count of two of three variables in conflict as inconclusive evidence, the system is not designed to provide tripping or corrective action, but improves the operator/instrument interface by providing additional and partially digested information

Decision boxes for clinicians to support evidence-based practice and shared decision making: the user experience

Directory of Open Access Journals (Sweden)

Giguere Anik

2012-08-01

-making process were added with the intent of clarifying the tool’s purpose. Information about the risks and benefits according to risk levels was added to the Decision Boxes, to try to ease the adaptation of the information to individual patients. Conclusion Results will guide the development of the eight remaining Decision Boxes. A future study will evaluate the effect of Decision Boxes on the integration of evidence-based and shared decision making principles in clinical practice.

The boundaries of instance-based learning theory for explaining decisions from experience.

Science.gov (United States)

Gonzalez, Cleotilde

2013-01-01

Most demonstrations of how people make decisions in risky situations rely on decisions from description, where outcomes and their probabilities are explicitly stated. But recently, more attention has been given to decisions from experience where people discover these outcomes and probabilities through exploration. More importantly, risky behavior depends on how decisions are made (from description or experience), and although prospect theory explains decisions from description, a comprehensive model of decisions from experience is yet to be found. Instance-based learning theory (IBLT) explains how decisions are made from experience through interactions with dynamic environments (Gonzalez et al., 2003). The theory has shown robust explanations of behavior across multiple tasks and contexts, but it is becoming unclear what the theory is able to explain and what it does not. The goal of this chapter is to start addressing this problem. I will introduce IBLT and a recent cognitive model based on this theory: the IBL model of repeated binary choice; then I will discuss the phenomena that the IBL model explains and those that the model does not. The argument is for the theory's robustness but also for clarity in terms of concrete effects that the theory can or cannot account for. Copyright © 2013 Elsevier B.V. All rights reserved.

Can Online Forums Be Designed to Empower Local Communities?

Directory of Open Access Journals (Sweden)

Kerill Dunne

2011-07-01

Full Text Available There has been a growing concern regarding political disengagement among citizens within western representative democracies. This concern has brought about calls for local communities to be empowered by giving citizens more control over local decision making. The objective of this paper is to examine if local political online forums can be built to empower local communities. That is to say, this paper will test if the E-Democracy.org’s Local Issues Forum Guidebook recommendations (A to do list for building successful online forums actually work and produce forums which facilitate citizens to have a greater say on local decision making and thus, induce empowerment. In order to test these recommendations a two-pronged methodological approach was taken. Firstly, using these recommendations an online forum was constructed in-conjunction with a local authority within the UK. Secondly, the recommendations were tested again except in this second approach a sample of online forums from around the world was examined. This paper argues that the E-Democracy.org’s recommendations do not always produce forums which empower local communities - Based on lessons learned from both experiments new guidelines are provided.

Operator models for delivering municipal solid waste management services in developing countries: Part B: Decision support.

Science.gov (United States)

Soós, Reka; Whiteman, Andrew D; Wilson, David C; Briciu, Cosmin; Nürnberger, Sofia; Oelz, Barbara; Gunsilius, Ellen; Schwehn, Ekkehard

2017-08-01

This is the second of two papers reporting the results of a major study considering 'operator models' for municipal solid waste management (MSWM) in emerging and developing countries. Part A documents the evidence base, while Part B presents a four-step decision support system for selecting an appropriate operator model in a particular local situation. Step 1 focuses on understanding local problems and framework conditions; Step 2 on formulating and prioritising local objectives; and Step 3 on assessing capacities and conditions, and thus identifying strengths and weaknesses, which underpin selection of the operator model. Step 4A addresses three generic questions, including public versus private operation, inter-municipal co-operation and integration of services. For steps 1-4A, checklists have been developed as decision support tools. Step 4B helps choose locally appropriate models from an evidence-based set of 42 common operator models ( coms); decision support tools here are a detailed catalogue of the coms, setting out advantages and disadvantages of each, and a decision-making flowchart. The decision-making process is iterative, repeating steps 2-4 as required. The advantages of a more formal process include avoiding pre-selection of a particular com known to and favoured by one decision maker, and also its assistance in identifying the possible weaknesses and aspects to consider in the selection and design of operator models. To make the best of whichever operator models are selected, key issues which need to be addressed include the capacity of the public authority as 'client', management in general and financial management in particular.

NATO Guide for Judgement-Based Operational Analysis in Defence Decision Making : Executive Leaflet

NARCIS (Netherlands)

Wijnmalen, D.J.D.; et al

2012-01-01

Judgment plays an important role in all Operational Analysis (OA). NATO practitioners have determined that approaches in OA that are based on human judgement are increasingly critical to defence decision making. The purpose of the NATO Guide for Judgement-Based OA in Defence Decision Making is to

Knowledge-based reasoning in the Paladin tactical decision generation system

Science.gov (United States)

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.

Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

International Nuclear Information System (INIS)

Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; 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. (paper)

A decision support system-based procedure for evaluation and ...

Indian Academy of Sciences (India)

with an overview of the web-based Decision Support System (DSS) developed to facilitate its wide adop- tion. .... contributes significant catchment management and water supply functions .... experience in engagement and facilitation methods.

Decision optimization of case-based computer-aided decision systems using genetic algorithms with application to mammography

International Nuclear Information System (INIS)

Mazurowski, Maciej A; Habas, Piotr A; Zurada, Jacek M; Tourassi, Georgia D

2008-01-01

This paper presents an optimization framework for improving case-based computer-aided decision (CB-CAD) systems. The underlying hypothesis of the study is that each example in the knowledge database of a medical decision support system has different importance in the decision making process. A new decision algorithm incorporating an importance weight for each example is proposed to account for these differences. The search for the best set of importance weights is defined as an optimization problem and a genetic algorithm is employed to solve it. The optimization process is tailored to maximize the system's performance according to clinically relevant evaluation criteria. The study was performed using a CAD system developed for the classification of regions of interests (ROIs) in mammograms as depicting masses or normal tissue. The system was constructed and evaluated using a dataset of ROIs extracted from the Digital Database for Screening Mammography (DDSM). Experimental results show that, according to receiver operator characteristic (ROC) analysis, the proposed method significantly improves the overall performance of the CAD system as well as its average specificity for high breast mass detection rates

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Science.gov (United States)

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Directory of Open Access Journals (Sweden)

Jianzhong Wang

Full Text Available Recently, Sparse Representation-based Classification (SRC has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW demonstrate the effectiveness of LCJDSRC.

Visual Appearance-Based Unmanned Vehicle Sequential Localization

Directory of Open Access Journals (Sweden)

Wei Liu

2013-01-01

Full Text Available Localizationis of vital importance for an unmanned vehicle to drive on the road. Most of the existing algorithms are based on laser range finders, inertial equipment, artificial landmarks, distributing sensors or global positioning system(GPS information. Currently, the problem of localization with vision information is most concerned. However, vision-based localization techniquesare still unavailable for practical applications. In this paper, we present a vision-based sequential probability localization method. This method uses the surface information of the roadside to locate the vehicle, especially in the situation where GPS information is unavailable. It is composed of two step, first, in a recording stage, we construct a ground truthmap with the appearance of the roadside environment. Then in an on-line stage, we use a sequential matching approach to localize the vehicle. In the experiment, we use two independent cameras to observe the environment, one is left-orientated and the other is right. SIFT features and Daisy features are used to represent for the visual appearance of the environment. The experiment results show that the proposed method could locate the vehicle in a complicated, large environment with high reliability.

Controlling Chronic Diseases Through Evidence-Based Decision Making: A Group-Randomized Trial.

Science.gov (United States)

Brownson, Ross C; Allen, Peg; Jacob, Rebekah R; deRuyter, Anna; Lakshman, Meenakshi; Reis, Rodrigo S; Yan, Yan

2017-11-30

Although practitioners in state health departments are ideally positioned to implement evidence-based interventions, few studies have examined how to build their capacity to do so. The objective of this study was to explore how to increase the use of evidence-based decision-making processes at both the individual and organization levels. We conducted a 2-arm, group-randomized trial with baseline data collection and follow-up at 18 to 24 months. Twelve state health departments were paired and randomly assigned to intervention or control condition. In the 6 intervention states, a multiday training on evidence-based decision making was conducted from March 2014 through March 2015 along with a set of supplemental capacity-building activities. Individual-level outcomes were evidence-based decision making skills of public health practitioners; organization-level outcomes were access to research evidence and participatory decision making. Mixed analysis of covariance models was used to evaluate the intervention effect by accounting for the cluster randomized trial design. Analysis was performed from March through May 2017. Participation 18 to 24 months after initial training was 73.5%. In mixed models adjusted for participant and state characteristics, the intervention group improved significantly in the overall skill gap (P = .01) and in 6 skill areas. Among the 4 organizational variables, only access to evidence and skilled staff showed an intervention effect (P = .04). Tailored and active strategies are needed to build capacity at the individual and organization levels for evidence-based decision making. Our study suggests several dissemination interventions for consideration by leaders seeking to improve public health practice.

Ontology based decision system for breast cancer diagnosis

Science.gov (United States)

Trabelsi Ben Ameur, Soumaya; Cloppet, Florence; Wendling, Laurent; Sellami, Dorra

2018-04-01

In this paper, we focus on analysis and diagnosis of breast masses inspired by expert concepts and rules. Accordingly, a Bag of Words is built based on the ontology of breast cancer diagnosis, accurately described in the Breast Imaging Reporting and Data System. To fill the gap between low level knowledge and expert concepts, a semantic annotation is developed using a machine learning tool. Then, breast masses are classified into benign or malignant according to expert rules implicitly modeled with a set of classifiers (KNN, ANN, SVM and Decision Tree). This semantic context of analysis offers a frame where we can include external factors and other meta-knowledge such as patient risk factors as well as exploiting more than one modality. Based on MRI and DECEDM modalities, our developed system leads a recognition rate of 99.7% with Decision Tree where an improvement of 24.7 % is obtained owing to semantic analysis.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

Science.gov (United States)

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

Ambient Sound-Based Collaborative Localization of Indeterministic Devices

NARCIS (Netherlands)

Kamminga, Jacob Wilhelm; Le Viet Duc, L Duc; Havinga, Paul J.M.

2016-01-01

Localization is essential in wireless sensor networks. To our knowledge, no prior work has utilized low-cost devices for collaborative localization based on only ambient sound, without the support of local infrastructure. The reason may be the fact that most low-cost devices are indeterministic and

Understanding evidence: a statewide survey to explore evidence-informed public health decision-making in a local government setting.

Science.gov (United States)

Armstrong, Rebecca; Waters, Elizabeth; Moore, Laurence; Dobbins, Maureen; Pettman, Tahna; Burns, Cate; Swinburn, Boyd; Anderson, Laurie; Petticrew, Mark

2014-12-14

The value placed on types of evidence within decision-making contexts is highly dependent on individuals, the organizations in which the work and the systems and sectors they operate in. Decision-making processes too are highly contextual. Understanding the values placed on evidence and processes guiding decision-making is crucial to designing strategies to support evidence-informed decision-making (EIDM). This paper describes how evidence is used to inform local government (LG) public health decisions. The study used mixed methods including a cross-sectional survey and interviews. The Evidence-Informed Decision-Making Tool (EvIDenT) survey was designed to assess three key domains likely to impact on EIDM: access, confidence, and organizational culture. Other elements included the usefulness and influence of sources of evidence (people/groups and resources), skills and barriers, and facilitators to EIDM. Forty-five LGs from Victoria, Australia agreed to participate in the survey and up to four people from each organization were invited to complete the survey (n = 175). To further explore definitions of evidence and generate experiential data on EIDM practice, key informant interviews were conducted with a range of LG employees working in areas relevant to public health. In total, 135 responses were received (75% response rate) and 13 interviews were conducted. Analysis revealed varying levels of access, confidence and organizational culture to support EIDM. Significant relationships were found between domains: confidence, culture and access to research evidence. Some forms of evidence (e.g. community views) appeared to be used more commonly and at the expense of others (e.g. research evidence). Overall, a mixture of evidence (but more internal than external evidence) was influential in public health decision-making in councils. By comparison, a mixture of evidence (but more external than internal evidence) was deemed to be useful in public health decision

Risk-based decision-making regarding mixed waste disposal systems

International Nuclear Information System (INIS)

Roberds, W.J.

1991-01-01

This paper reports on an efficient approach that has been developed for making rational and defensible decisions among a variety of options (e.g., remedial actions, engineered barriers designs/operational controls, inventory limitations, site investigations and research) for mixed-waste disposal systems, which consist of multiple interacting sites (active, inactive and/or future) with multiple pathways. Such decisions are based on maximizing the satisfaction of identified objectives (including the reliability vis a vis specified criteria), explicitly considering tradeoffs among objectives as well as uncertainties in the consequences of any option

Tactical decision making under stress (TADMUS) decision support system

OpenAIRE

Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.

1996-01-01

A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes and cognitive analysis of the decision making problems faced by Navy tactical officers in a shipboard Combat Information Center. Baseline testing in high intensity, peace keeping, littoral scenarios indicated...

Decision makers, scientists and the public as stakeholders: the connection between traffic intervention policy and air quality in a local context.

Science.gov (United States)

Weiand, L.; von Schneidemesser, E.; Schmitz, S.; Niehoff, N.

2017-12-01

Urban mobility is a key issue to make cities more inclusive, safer, and more environmentally friendly. To ensure a sustainable future, local policy should, among other actions, aim to improve access to sustainable transport systems and enhance mobility opportunities, while at the same time addressing critical environmental and health targets. In order to assess whether these objectives are met, measures should be informed and evaluated from a social and environmental perspective. Citizens' opinions and the acceptance of environmental policies are crucial to successful implementation of urban mobility measures. The complexity of urban air quality issues require transparent decision-making processes that are grounded in evidence-based research and embrace local knowledge. From this basis, our research group and the city council collaborated to assess a new policy action intended to address environmental and health targets. This talk will present the results from the assessment of this new policy, that was implemented in large part to alleviate air quality exceedances, from the perspective of public acceptability of the measure and the approach taken by the city council to implement the measure. Parallel to assessing the effect of this policy on the recorded levels of air pollution and traffic counts, we conducted a social survey to examine public opinions of this measure, as well as the link between air quality awareness and mobility decisions. 4661 responses were collected over a one month period. Survey participants were those most affected by the traffic measure, including commuters and local residents. The results show that there is an overall low acceptance rate of the measure (8%) as well as low concern for air quality (2,90 - where 1 = not concerned and 6 = very concerned). We also found that there is a negative relationship between air quality rating and air quality concern. A similar approach was taken to understand climate change concern, which will be

Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

KAUST Repository

Delimata, Paweł; Marszał-Paszek, Barbara; Moshkov, Mikhail; Paszek, Piotr; Skowron, Andrzej; Suraj, Zbigniew

2010-01-01

the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory

Unreliable gut feelings can lead to correct decisions: The somatic marker hypothesis in non-linear decision chains

Directory of Open Access Journals (Sweden)

Manuel eBedia

2012-10-01

Full Text Available Dual system approaches of decision making examine the interaction between affective/intuitive and deliberative processes underlying value judgment. Decisions are arise from a combination of relatively explicit capabilities for abstract reasoning and relatively implicit evolved domain-general as well as learned domain-specific affective responses. One such approach, the somatic markers hypothesis (SMH, expresses these processes as a system of evolved primary emotions supplemented by associations between affect and experience that accrue over lifetime, or somatic markers (SMs. In this view, SMs are useful only if their local capability to predict the value of an action is above a baseline equal to the predictive capability of the combined rational and primary emotional subsystems. We argue that decision making has often been conceived of as a linear process: the effect of decision sequences is additive, local utility is cumulative, and there is no strong environmental feedback. This widespread assumption has consequences for answering questions regarding the relative weight between the systems and their interaction within a cognitive architecture. We introduce a mathematical formalization of the SMH and study it in situations of dynamic, nonlinear decision chains using a discrete-time stochastic model. We find, contrary to expectations, that decision making events can interact non-additively with the environment in apparently paradoxical ways. We find that primary emotions are represented globally over and above their local weight, showing a tendency for overcaution in situated decision chains. We also show that because they tend to counteract this trend, poorly attuned somatic markers that by themselves do not locally enhance decision making, can still produce an overall positive effect. This result has developmental and evolutionary implications since, by promoting exploratory behavior, SMs are beneficial even at early stages when experiential

Coevolution Based Adaptive Monte Carlo Localization (CEAMCL

Directory of Open Access Journals (Sweden)

Luo Ronghua

2008-11-01

Full Text Available An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot's pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robot's pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL. Experiments have been carried out to prove the efficiency of the new localization algorithm.

A theory-based decision aid for patients with cancer: results of feasibility and acceptability testing of DecisionKEYS for cancer.

Science.gov (United States)

Hollen, Patricia J; Gralla, Richard J; Jones, Randy A; Thomas, Christopher Y; Brenin, David R; Weiss, Geoffrey R; Schroen, Anneke T; Petroni, Gina R

2013-03-01

Appropriate utilization of treatment is a goal for all patients undergoing cancer treatment. Proper treatment maximizes benefit and limits exposure to unnecessary measures. This report describes findings of the feasibility and acceptability of implementing a short, clinic-based decision aid and presents an in-depth clinical profile of the participants. This descriptive study used a prospective, quantitative approach to obtain the feasibility and acceptability of a decision aid (DecisionKEYS for Balancing Choices) for use in clinical settings. It combined results of trials of patients with three different common malignancies. All groups used the same decision aid series. Participants included 80 patients with solid tumors (22 with newly diagnosed breast cancer, 19 with advanced prostate cancer, and 39 with advanced lung cancer) and their 80 supporters as well as their physicians and nurses, for a total of 160 participants and 10 health professionals. The decision aid was highly acceptable to patient and supporter participants in all diagnostic groups. It was feasible for use in clinic settings; the overall value was rated highly. Of six physicians, all found the interactive format with the help of the nurse as feasible and acceptable. Nurses also rated the decision aid favorably. This intervention provides the opportunity to enhance decision making about cancer treatment and warrants further study including larger and more diverse groups. Strengths of the study included a theoretical grounding, feasibility testing of a practical clinic-based intervention, and summative evaluation of acceptability of the intervention by patient and supporter pairs. Further research also is needed to test the effectiveness of the decision aid in diverse clinical settings and to determine if this intervention can decrease overall costs.

Long-term health outcomes of a decision aid: data from a randomized trial of adjuvant! In women with localized breast cancer.

Science.gov (United States)

Vickers, Andrew J; Elkin, Elena B; Peele, Pamela B; Dickler, Maura; Siminoff, Laura A

2009-01-01

Women with localized breast cancer face difficult decisions about adjuvant therapy. Several decision aids are available to help women choose between treatment options. Decision aids are known to affect treatment choices and may therefore affect patient survival. The authors aimed to model the effects of the Adjuvant! decision aid on expected survival in women with early stage breast cancer. Data were obtained from a randomized trial of Adjuvant! (n = 395). To calculate the effects of the decision aid on survival, the authors used the Adjuvant! survival predictions as a surrogate endpoint. Data from each arm were entered separately into statistical models to estimate change in survival associated with receiving the Adjuvant! decision aid. Most women (approximately 85%) chose a treatment option that maximized predicted survival. The effects of the decision aid on outcome could not be modeled because a small number of women (n = 12, 3%) chose treatment options associated with a large (5%-14%) loss in survival. These women-most typically estrogen receptor positive but refusing hormonal therapy-were equally divided between Adjuvant! and control groups and were not distinguished by medical or demographic factors. Expected benefit from treatment is a key variable in understanding patient behavior. A small number of women refuse adjuvant treatment associated with large increases in predicted survival, even when they are explicitly informed about the degree of benefit they would forgo. Investigation of the effects of decision aids on cancer survival is unlikely to be fruitful due to power considerations.

Dashboard visualizations: Supporting real-time throughput decision-making.

Science.gov (United States)

Franklin, Amy; Gantela, Swaroop; Shifarraw, Salsawit; Johnson, Todd R; Robinson, David J; King, Brent R; Mehta, Amit M; Maddow, Charles L; Hoot, Nathan R; Nguyen, Vickie; Rubio, Adriana; Zhang, Jiajie; Okafor, Nnaemeka G

2017-07-01

Providing timely and effective care in the emergency department (ED) requires the management of individual patients as well as the flow and demands of the entire department. Strategic changes to work processes, such as adding a flow coordination nurse or a physician in triage, have demonstrated improvements in throughput times. However, such global strategic changes do not address the real-time, often opportunistic workflow decisions of individual clinicians in the ED. We believe that real-time representation of the status of the entire emergency department and each patient within it through information visualizations will better support clinical decision-making in-the-moment and provide for rapid intervention to improve ED flow. This notion is based on previous work where we found that clinicians' workflow decisions were often based on an in-the-moment local perspective, rather than a global perspective. Here, we discuss the challenges of designing and implementing visualizations for ED through a discussion of the development of our prototype Throughput Dashboard and the potential it holds for supporting real-time decision-making. Copyright © 2017. Published by Elsevier Inc.

40 CFR 761.298 - Decisions based on PCB concentration measurements resulting from sampling.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Decisions based on PCB concentration... Cleanup and On-Site Disposal of Bulk PCB Remediation Waste and Porous Surfaces in Accordance With § 761.61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a) For...

IMPLEMENTATION OF GIS-BASED MULTICRITERIA DECISION ANALYSIS WITH VB IN ArcGIS

OpenAIRE

DERYA OZTURK; FATMAGUL BATUK

2011-01-01

This article focuses on the integration of multicriteria decision analysis (MCDA) and geographical information systems (GIS) and introduces a tool, GIS–MCDA, written in visual basic in ArcGIS for GIS-based MCDA. The GIS–MCDA deals with raster-based data sets and includes standardization, weighting and decision analysis methods, and sensitivity analysis. Simple additive weighting, weighted product method, technique for order preference by similarity to ideal solution, compromise programming, a...

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

Science.gov (United States)

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…

A framework for production of systematic review based briefings to support evidence-informed decision-making.

Science.gov (United States)

Chambers, Duncan; Wilson, Paul

2012-07-09

We have developed a framework for translating existing sources of synthesized and quality-assessed evidence, primarily systematic reviews, into actionable messages in the form of short accessible briefings. The service aims to address real-life problems in response to requests from decision-makers.Development of the framework was based on a scoping review of existing resources and our initial experience with two briefing topics, including models of service provision for young people with eating disorders. We also drew on previous experience in dissemination research and practice. Where appropriate, we made use of the SUPporting POlicy relevant Reviews and Trials (SUPPORT) tools for evidence-informed policymaking. To produce a product that it is fit for this purpose it has been necessary to go beyond a traditional summary of the available evidence relating to effectiveness. Briefings have, therefore, included consideration of cost effectiveness, local applicability, implications relating to local service delivery, budgets, implementation and equity. Our first evidence briefings produced under this framework cover diagnostic endoscopy by specialist nurses and integrated care pathways in mental healthcare settings. The framework will enable researchers to present and contextualize evidence from systematic reviews and other sources of synthesized and quality-assessed evidence. The approach is designed to address the wide range of questions of interest to decision-makers, especially those commissioning services or managing service delivery and organization in primary or secondary care. Evaluation of the use and usefulness of the evidence briefings we produce is an integral part of the framework and will help to fill a gap in the literature.

Neural correlates of conventional and harm/welfare-based moral decision-making.

Science.gov (United States)

White, Stuart F; Zhao, Hui; Leong, Kelly Kimiko; Smetana, Judith G; Nucci, Larry P; Blair, R James R

2017-12-01

The degree to which social norms are processed by a unitary system or dissociable systems remains debated. Much research on children's social-cognitive judgments has supported the distinction between "moral" (harm/welfare-based) and "conventional" norms. However, the extent to which these norms are processed by dissociable neural systems remains unclear. To address this issue, 23 healthy participants were scanned with functional magnetic resonance imaging (fMRI) while they rated the wrongness of harm/welfare-based and conventional transgressions and neutral vignettes. Activation significantly greater than the neutral vignette baseline was observed in regions implicated in decision-making regions including rostral/ventral medial frontal, anterior insula and dorsomedial frontal cortices when evaluating both harm/welfare-based and social-conventional transgressions. Greater activation when rating harm/welfare-based relative to social-conventional transgressions was seen through much of ACC and bilateral inferior frontal gyrus. Greater activation was observed in superior temporal gyrus, bilateral middle temporal gyrus, left PCC, and temporal-parietal junction when rating social-conventional transgressions relative to harm/welfare-based transgressions. These data suggest that decisions regarding the wrongness of actions, irrespective of whether they involve care/harm-based or conventional transgressions, recruit regions generally implicated in affect-based decision-making. However, there is neural differentiation between harm/welfare-based and conventional transgressions. This may reflect the particular importance of processing the intent of transgressors of conventional norms and perhaps the greater emotional content or salience of harm/welfare-based transgressions.

Video-based training to improve perceptual-cognitive decision-making performance of Australian football umpires.

Science.gov (United States)

Larkin, Paul; Mesagno, Christopher; Berry, Jason; Spittle, Michael; Harvey, Jack

2018-02-01

Decision-making is a central component of the in-game performance of Australian football umpires; however, current umpire training focuses largely on physiological development with decision-making skills development conducted via explicit lecture-style meetings with limited practice devoted to making actual decisions. Therefore, this study investigated the efficacy of a video-based training programme, aimed to provide a greater amount of contextualised visual experiences without explicit instruction, to improve decision-making skills of umpires. Australian football umpires (n = 52) were recruited from metropolitan and regional Division 1 competitions. Participants were randomly assigned to an intervention or control group and classified according to previous umpire game experience (i.e., experienced; less experienced). The intervention group completed a 12-week video-based decision-making training programme, with decision-making performance assessed at pre-training, and 1-week retention and 3-week retention periods. The control group did not complete any video-based training. Results indicated a significant Group (intervention; Control) × Test interaction (F(1, 100) = 3.98; P = 0.02, partial ῆ 2  = 0.074), with follow-up pairwise comparisons indicating significant within-group differences over time for the intervention group. In addition, decision-making performance of the less experienced umpires in the intervention group significantly improved (F(2, 40) = 5.03, P = 0.01, partial ῆ 2  = 0.201). Thus, video-based training programmes may be a viable adjunct to current training programmes to hasten decision-making development, especially for less experienced umpires.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

Directory of Open Access Journals (Sweden)

Mohammad S. Islam

2017-01-01

Full Text Available Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs for robust movement decoding of Parkinson’s disease (PD and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value at about 0.729±0.16 for decoding movement from the resting state and about 0.671±0.14 for decoding left and right visually cued movements.

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

Energy Technology Data Exchange (ETDEWEB)

Luo, Y; McShan, D; Schipper, M; Matuszak, M; Ten Haken, R [University of Michigan, Ann Arbor, MI (United States); Kong, F [Georgia Regents University, Augusta, GA (Georgia)

2014-06-01

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more

Local coding based matching kernel method for image classification.

Directory of Open Access Journals (Sweden)

Yan Song

Full Text Available This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

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

Science.gov (United States)

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…

Fiber Bragg grating based arterial localization device

Science.gov (United States)

Ho, Siu Chun Michael; Li, Weijie; Razavi, Mehdi; Song, Gangbing

2017-06-01

A critical first step to many surgical procedures is locating and gaining access to a patients vascular system. Vascular access allows the deployment of other surgical instruments and also the monitoring of many physiological parameters. Current methods to locate blood vessels are predominantly based on the landmark technique coupled with ultrasound, fluoroscopy, or Doppler. However, even with experience and technological assistance, locating the required blood vessel is not always an easy task, especially with patients that present atypical anatomy or suffer from conditions such as weak pulsation or obesity that make vascular localization difficult. With recent advances in fiber optic sensors, there is an opportunity to develop a new tool that can make vascular localization safer and easier. In this work, the authors present a new fiber Bragg grating (FBG) based vascular access device that specializes in arterial localization. The device estimates the location towards a local artery based on the bending of a needle inserted near the tissue surrounding the artery. Experimental results obtained from an artificial circulatory loop and a mock artery show the device works best for lower angles of needle insertion and can provide an approximately 40° range of estimation towards the location of a pulsating source (e.g. an artery).

Implications of Decision Making Research for Decision Support and Displays

OpenAIRE

Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.

1998-01-01

To appear in J. A. Cannon-Bowers & E. Salas (Eds.), Decision Making Under Stress: Implications for Training and Simulation. A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes, and cognitive analysis was conducted of the decision making problems faced by Navy ...

A decision support system for planning biomass-based energy production

Energy Technology Data Exchange (ETDEWEB)

Frombo, Francesco; Robba, Michela [DIST, Department of Communication, Computer and System Sciences, University of Genoa, Via Opera Pia 13, 16145 Genova (Italy); Renewable Energy Laboratory, Modelling and Optimization, Via A. Magliotto 2, 17100 Savona (Italy); Minciardi, Riccardo; Sacile, Roberto [DIST, Department of Communication, Computer and System Sciences, University of Genoa, Via Opera Pia 13, 16145 Genova (Italy)

2009-03-15

Environmental decision support systems (EDSS) are recognized as valuable tools for environmental planning and management. In this paper, a geographic information system (GIS)-based EDSS for the optimal planning of forest biomass use for energy production is presented. A user-friendly interface allows the creation of Scenarios and the running of the developed decision and environmental models. In particular, the optimization model regards decisions over a long-term period (e.g. years) and includes decision variables related to plant locations, conversion processes (pyrolisis, gasification, combustion), harvested biomass. Moreover, different energy products and different definitions of the harvesting and pre-treatment operations are taken into account. The correct management of the forest is considered through specific constraints, security factors, and procedures for parcel selection. The EDSS features and capabilities are described in detail, with specific reference to a case study. Discussion and further research are reported. (author)

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

Science.gov (United States)

Yu, Peter Paul

2015-03-01

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

Use of decision criteria based on expected values to support decision-making in a production assurance and safety setting

International Nuclear Information System (INIS)

Aven, T.; Flage, R.

2009-01-01

We consider decision problems related to production assurance and safety. The issue is to what extent we should use decision criteria based on expected values, such as the expected net present value (E[NPV]) and the expected cost per expected number of saved lives (ICAF), to guide the decision. Such criteria are recognised as practical tools for supporting decision-making under uncertainty, but is uncertainty adequately taken into account by these criteria? Based on the prevailing practice and the existing literature, we conclude that there is a need for a clarification of the rationale of these criteria. Adjustments of the standard approaches have been suggested to reflect risks and uncertainties, but can cautionary and precautionary concerns be replaced by formulae and mechanical procedures? These issues are discussed in the present paper, particularly addressing the company level. We argue that the search for such formulae and procedures should be replaced by a more balanced perspective acknowledging that there will always be a need for management review and judgment beyond the realm of the analyses. Most of the suggested adjustments of the E[NPV] and ICAF approaches should be avoided. They add more confusion than value.

Comparison of Subset-Based Local and Finite Element-Based Global Digital Image Correlation

KAUST Repository

Pan, Bing; Wang, B.; Lubineau, Gilles; Moussawi, Ali

2015-01-01

Digital image correlation (DIC) techniques require an image matching algorithm to register the same physical points represented in different images. Subset-based local DIC and finite element-based (FE-based) global DIC are the two primary image matching methods that have been extensively investigated and regularly used in the field of experimental mechanics. Due to its straightforward implementation and high efficiency, subset-based local DIC has been used in almost all commercial DIC packages. However, it is argued by some researchers that FE-based global DIC offers better accuracy because of the enforced continuity between element nodes. We propose a detailed performance comparison between these different DIC algorithms both in terms of measurement accuracy and computational efficiency. Then, by measuring displacements of the same calculation points using the same calculation algorithms (e.g., correlation criterion, initial guess estimation, subpixel interpolation, optimization algorithm and convergence conditions) and identical calculation parameters (e.g., subset or element size), the performances of subset-based local DIC and two FE-based global DIC approaches are carefully compared in terms of measurement error and computational efficiency using both numerical tests and real experiments. A detailed examination of the experimental results reveals that, when subset (element) size is not very small and the local deformation within a subset (element) can be well approximated by the shape function used, standard subset-based local DIC approach not only provides better results in measured displacements, but also demonstrates much higher computation efficiency. However, several special merits of FE-based global DIC approaches are indicated.

Comparison of Subset-Based Local and Finite Element-Based Global Digital Image Correlation

KAUST Repository

Pan, Bing

2015-02-12

Digital image correlation (DIC) techniques require an image matching algorithm to register the same physical points represented in different images. Subset-based local DIC and finite element-based (FE-based) global DIC are the two primary image matching methods that have been extensively investigated and regularly used in the field of experimental mechanics. Due to its straightforward implementation and high efficiency, subset-based local DIC has been used in almost all commercial DIC packages. However, it is argued by some researchers that FE-based global DIC offers better accuracy because of the enforced continuity between element nodes. We propose a detailed performance comparison between these different DIC algorithms both in terms of measurement accuracy and computational efficiency. Then, by measuring displacements of the same calculation points using the same calculation algorithms (e.g., correlation criterion, initial guess estimation, subpixel interpolation, optimization algorithm and convergence conditions) and identical calculation parameters (e.g., subset or element size), the performances of subset-based local DIC and two FE-based global DIC approaches are carefully compared in terms of measurement error and computational efficiency using both numerical tests and real experiments. A detailed examination of the experimental results reveals that, when subset (element) size is not very small and the local deformation within a subset (element) can be well approximated by the shape function used, standard subset-based local DIC approach not only provides better results in measured displacements, but also demonstrates much higher computation efficiency. However, several special merits of FE-based global DIC approaches are indicated.

Prerequisites for data-based decision making in the classroom: Research evidence and practical illustrations

NARCIS (Netherlands)

Hoogland, Inge; Schildkamp, Kim; van der Kleij, Fabienne; Heitink, Maaike Christine; Kippers, Wilma Berdien; Veldkamp, Bernard P.; Dijkstra, Anne M.

2016-01-01

Data-based decision making can lead to increased student learning. The desired effects of increased student learning can only be realized if data-based decision making is implemented successfully. Therefore, a systematic literature review was conducted to identify prerequisites of such successful

A range-based predictive localization algorithm for WSID networks

Science.gov (United States)

Liu, Yuan; Chen, Junjie; Li, Gang

2017-11-01

Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Science.gov (United States)

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.

The need to go beyond analysis in making risk-based decisions

Energy Technology Data Exchange (ETDEWEB)

Ahearne, J.F. [The Sigma XI Center, Research Triangle Park, NC (United States)

1999-12-01

As a physicist, I prefer the R = P x C, with the inclusion of a risk magnifier when appropriate. However, I also accept this is inadequate. For risk-based decisions to be acceptable in a democratic society, there must be widespread agreement on the criteria to be used, the process by which the decision is reached, and the linkage between the criteria and the decision. These demand a transparent process. Armour wrote: 'To date, efforts directed toward facility siting conflicts have focused almost exclusively on the 'public acceptance' factor (and neglected the legitimacy of the process] - the sad reality is that these strategies have not beenall that effective. Moreover, given that the underlying motivation is to 'gain public acceptance' such strategies have often worsened the facility siting problems when used by proponents who were unable, in appearance or in fact, to tread the fine line between manipulating public opinion and liberating it ... the issue of the legitimacy of the decision making process had tended to be taken for granted. Generally speaking, policy makers have failed to seriously question and have not responded well to others who have dared to question the established roles and principles of our conventional processes of decision making.' Finally, acceptance also requires agreement that the issues to be decided are the appropriate issues. Often the decision-makers concentrate on issues that are not the ones the public views as the most important. Sometimes it is because the public wants other alternatives examined. Sometimes it is because the public does not accept the necessity to decide now. And sometimes it is because the public does not trust those who have assumed responsibility for making the decision. The analytic community has grown in size and skill over the last 20 years. The science community has produced a better understanding of health effects and exposure pathways. The engineering community has designed

The need to go beyond analysis in making risk-based decisions

International Nuclear Information System (INIS)

Ahearne, J.F.

1999-01-01

As a physicist, I prefer the R = P x C, with the inclusion of a risk magnifier when appropriate. However, I also accept this is inadequate. For risk-based decisions to be acceptable in a democratic society, there must be widespread agreement on the criteria to be used, the process by which the decision is reached, and the linkage between the criteria and the decision. These demand a transparent process. Armour wrote: 'To date, efforts directed toward facility siting conflicts have focused almost exclusively on the 'public acceptance' factor (and neglected the legitimacy of the process] - the sad reality is that these strategies have not been all that effective. Moreover, given that the underlying motivation is to 'gain public acceptance' such strategies have often worsened the facility siting problems when used by proponents who were unable, in appearance or in fact, to tread the fine line between manipulating public opinion and liberating it ... the issue of the legitimacy of the decision making process had tended to be taken for granted. Generally speaking, policy makers have failed to seriously question and have not responded well to others who have dared to question the established roles and principles of our conventional processes of decision making.' Finally, acceptance also requires agreement that the issues to be decided are the appropriate issues. Often the decision-makers concentrate on issues that are not the ones the public views as the most important. Sometimes it is because the public wants other alternatives examined. Sometimes it is because the public does not accept the necessity to decide now. And sometimes it is because the public does not trust those who have assumed responsibility for making the decision. The analytic community has grown in size and skill over the last 20 years. The science community has produced a better understanding of health effects and exposure pathways. The engineering community has designed safer systems. However, the

Reputation-based secure sensor localization in wireless sensor networks.

Science.gov (United States)

He, Jingsha; Xu, Jing; Zhu, Xingye; Zhang, Yuqiang; Zhang, Ting; Fu, Wanqing

2014-01-01

Location information of sensor nodes in wireless sensor networks (WSNs) is very important, for it makes information that is collected and reported by the sensor nodes spatially meaningful for applications. Since most current sensor localization schemes rely on location information that is provided by beacon nodes for the regular sensor nodes to locate themselves, the accuracy of localization depends on the accuracy of location information from the beacon nodes. Therefore, the security and reliability of the beacon nodes become critical in the localization of regular sensor nodes. In this paper, we propose a reputation-based security scheme for sensor localization to improve the security and the accuracy of sensor localization in hostile or untrusted environments. In our proposed scheme, the reputation of each beacon node is evaluated based on a reputation evaluation model so that regular sensor nodes can get credible location information from highly reputable beacon nodes to accomplish localization. We also perform a set of simulation experiments to demonstrate the effectiveness of the proposed reputation-based security scheme. And our simulation results show that the proposed security scheme can enhance the security and, hence, improve the accuracy of sensor localization in hostile or untrusted environments.

Computer-based tools for decision support at the Hanford Site

International Nuclear Information System (INIS)

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

Computer-based tools for decision support at the Hanford Site

Energy Technology Data Exchange (ETDEWEB)

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.

Computer-based tools for decision support at the Hanford Site

Energy Technology Data Exchange (ETDEWEB)

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.

Tactical decision games - developing scenario-based training for decision-making in distributed teams

OpenAIRE

Lauche, K.; Crichton, M.; Bayerl, P.S.

2009-01-01

Team training should reflect the increasing complexity of decision-making environments. Guidelines for scenario-based training were adopted for a distributed setting and tested in a pilot training session with a distributed team in the offshore oil industry. Participants valued the scenario as challenging and useful, but also highlighted problems of distributed communication. The findings were used to improve the training as well as current use of the technology in the organisation. Research ...

Impact of a web-based prostate cancer treatment decision aid on patient-reported decision process parameters: results from the Prostate Cancer Patient Centered Care trial.

Science.gov (United States)

Cuypers, Maarten; Lamers, Romy E D; Kil, Paul J M; van de Poll-Franse, Lonneke V; de Vries, Marieke

2018-05-12

To compare patients' evaluation of the treatment decision-making process in localized prostate cancer between counseling that included an online decision aid (DA) and standard counseling. Eighteen Dutch hospitals were randomized to DA counseling (n = 235) or the control group with standard counseling (n = 101) in a pragmatic, cluster randomized controlled trial. The DA was provided to patients at, or soon after diagnosis. Decisional conflict, involvement, knowledge, and satisfaction with information were assessed with a questionnaire after treatment decision-making. Anxiety and depression served as covariates. The levels of decision involvement and conflict were comparable between patients in both groups. Patients with a DA felt more knowledgeable but scored equally well on a knowledge test as patients without a DA. Small significant negative effects were found on satisfaction with information and preparation for decision-making. A preference for print over online and depression and anxiety symptoms was negatively associated with satisfaction and conflict scores in the DA group. The DA aimed to support shared decision-making, while outcomes for a majority of DA users were comparable to patients who received standard counseling. Patients, who are less comfortable with the online DA format or experience anxiety or depression symptoms, could require more guidance toward shared decision-making. To evaluate long-term DA effects, follow-up evaluation on treatment satisfaction and decisional regret will be done.

Enhancing emotion-based learning in decision-making under uncertainty.

Science.gov (United States)

Alarcón, David; Amián, Josué G; Sánchez-Medina, José A

2015-01-01

The Iowa Gambling Task (IGT) is widely used to study decision-making differences between several clinical and healthy populations. Unlike the healthy participants, clinical participants have difficulty choosing between advantageous options, which yield long-term benefits, and disadvantageous options, which give high immediate rewards but lead to negative profits. However, recent studies have found that healthy participants avoid the options with a higher frequency of losses regardless of whether or not they are profitable in the long run. The aim of this study was to control for the confounding effect of the frequency of losses between options to improve the performance of healthy participants on the IGT. Eighty healthy participants were randomly assigned to the original IGT or a modified version of the IGT that diminished the gap in the frequency of losses between options. The participants who used the modified IGT version learned to make better decisions based on long-term profit, as indicated by an earlier ability to discriminate good from bad options, and took less time to make their choices. This research represents an advance in the study of decision making under uncertainty by showing that emotion-based learning is improved by controlling for the loss-frequency bias effect.

Experiential Knowledge Complements an LCA-Based Decision Support Framework

Directory of Open Access Journals (Sweden)

Heng Yi Teah

2015-09-01

Full Text Available A shrimp farmer in Taiwan practices innovation through trial-and-error for better income and a better environment, but such farmer-based innovation sometimes fails because the biological mechanism is unclear. Systematic field experimentation and laboratory research are often too costly, and simulating ground conditions is often too challenging. To solve this dilemma, we propose a decision support framework that explicitly utilizes farmer experiential knowledge through a participatory approach to alternatively estimate prospective change in shrimp farming productivity, and to co-design options for improvement. Data obtained from the farmer enable us to quantitatively analyze the production cost and greenhouse gas (GHG emission with a life cycle assessment (LCA methodology. We used semi-quantitative graphical representations of indifference curves and mixing triangles to compare and show better options for the farmer. Our results empower the farmer to make decisions more systematically and reliably based on the frequency of heterotrophic bacteria application and the revision of feed input. We argue that experiential knowledge may be less accurate due to its dependence on varying levels of farmer experience, but this knowledge is a reasonable alternative for immediate decision-making. More importantly, our developed framework advances the scope of LCA application to support practically important yet scientifically uncertain cases.

A novel computer based expert decision making model for prostate cancer disease management.

Science.gov (United States)

Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D

2005-12-01

We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42

Apathy and Emotion-Based Decision-Making in Amnesic Mild Cognitive Impairment and Alzheimer's Disease

OpenAIRE

Bayard, Sophie; Jacus, Jean-Pierre; Raffard, Stéphane; Gely-Nargeot, Marie-Christine

2014-01-01

Background. Apathy and reduced emotion-based decision-making are two behavioral modifications independently described in Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI). Objectives. The aims of this study were to investigate decision-making based on emotional feedback processing in AD and aMCI and to study the impact of reduced decision-making performances on apathy. Methods. We recruited 20 patients with AD, 20 participants with aMCI, and 20 healthy controls. All parti...

School characteristics influencing the implementation of a data-based decision making intervention

NARCIS (Netherlands)

van Geel, Marieke Johanna Maria; Visscher, Arend J.; Teunis, B.

2017-01-01

There is an increasing global emphasis on using data for decision making, with a growing body of research on interventions aimed at implementing and sustaining data-based decision making (DBDM) in schools. Yet, little is known about the school features that facilitate or hinder the implementation of

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

Science.gov (United States)

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464

Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

Science.gov (United States)

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

Directory of Open Access Journals (Sweden)

Ning Yu

2011-12-01

Full Text Available In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

An Agent-Based Model of Farmer Decision Making in Jordan

Science.gov (United States)

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.

The value of precision for image-based decision support in weed management

DEFF Research Database (Denmark)

Franco de los Ríos, Camilo; Pedersen, Søren Marcus; Papaharalampos, Haris

2017-01-01

Decision support methodologies in precision agriculture should integrate the different dimensions composing the added complexity of operational decision problems. Special attention has to be given to the adequate knowledge extraction techniques for making sense of the collected data, processing...... the information for assessing decision makers and farmers in the efficient and sustainable management of the field. Focusing on weed management, the integration of operational aspects for weed spraying is an open challenge for modeling the farmers’ decision problem, identifying satisfactory solutions...... for the implementation of automatic weed recognition procedures. The objective of this paper is to develop a decision support methodology for detecting the undesired weed from aerial images, building an image-based viewpoint consisting in relevant operational knowledge for applying precision spraying. In this way...

ComTrustO: Composite Trust-Based Ontology Framework for Information and Decision Fusion

Science.gov (United States)

2015-07-06

11] presents a methodological approach for ontology management allowing development of extensible ontologies and the mapping from ontologies to...ComTrustO: Composite Trust-based Ontology Framework for Information and Decision Fusion Alessandro Oltramari Carnegie Mellon University Pittsburgh... ontology -based framework for information fusion, as a support system for human decision makers. In particular, we build upon the concept of composite

Optimization of approximate decision rules relative to number of misclassifications

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2012-01-01

In the paper, we study an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the number of misclassifications. We introduce an uncertainty measure J(T) which is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. The presented algorithm constructs a directed acyclic graph Δγ(T). Based on this graph we can describe the whole set of so-called irredundant γ-decision rules. We can optimize rules from this set according to the number of misclassifications. Results of experiments with decision tables from the UCI Machine Learning Repository are presented. © 2012 The authors and IOS Press. All rights reserved.

Optimization of approximate decision rules relative to number of misclassifications

KAUST Repository

Amin, Talha

2012-12-01

In the paper, we study an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the number of misclassifications. We introduce an uncertainty measure J(T) which is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. The presented algorithm constructs a directed acyclic graph Δγ(T). Based on this graph we can describe the whole set of so-called irredundant γ-decision rules. We can optimize rules from this set according to the number of misclassifications. Results of experiments with decision tables from the UCI Machine Learning Repository are presented. © 2012 The authors and IOS Press. All rights reserved.

NATO Guide for Judgement-Based Operational Analysis in Defence Decision Making : Client-Oriented Volume

NARCIS (Netherlands)

Wijnmalen, D.J.D.; et al

2012-01-01

Judgment plays an important role in all Operational Analysis (OA). NATO practitioners have determined that approaches in OA that are based on human judgement are increasingly critical to defence decision making. The purpose of the NATO Guide for Judgement-Based OA in Defence Decision Making is to

Optimal condition-based maintenance decisions for systems with dependent stochastic degradation of components

International Nuclear Information System (INIS)

Hong, H.P.; Zhou, W.; Zhang, S.; Ye, W.

2014-01-01

Components in engineered systems are subjected to stochastic deterioration due to the operating environmental conditions, and the uncertainty in material properties. The components need to be inspected and possibly replaced based on preventive or failure replacement criteria to provide the intended and safe operation of the system. In the present study, we investigate the influence of dependent stochastic degradation of multiple components on the optimal maintenance decisions. We use copula to model the dependent stochastic degradation of components, and formulate the optimal decision problem based on the minimum expected cost rule and the stochastic dominance rules. The latter is used to cope with decision maker's risk attitude. We illustrate the developed probabilistic analysis approach and the influence of the dependency of the stochastic degradation on the preferred decisions through numerical examples

Joint federal research and development process to meet state and local needs. Part 1. Science and technology and political decision making

Energy Technology Data Exchange (ETDEWEB)

Wise, H F; Smith, L K; Einsweiler, R C; Jensen, D E

1980-10-01

This part of the handbook addresses the basic how to do it - how states and local governments can identify complex and cross-cutting issues and develop and manage scientific and technical resources in seeking policy solutions to such issues. The following subjects are discussed: background statement of the issue; the research/decision-making process; defining problems and identifying research components; research and decision-making strategies; how to identify existing knowledge or ongoing research in the area of policy concern; and managing multi-disciplinary research. The fourteen agencies involved in this effort include: US Departments of Energy, Agriculture, Transportation, Housing and Urban Development, Environmental Protection Agency, and National Science Foundation. (PSB)

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

Science.gov (United States)

Ren, Peijia; Xu, Zeshui; Hao, Zhinan

2017-09-01

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.

Detecting Structural Metadata with Decision Trees and Transformation-Based Learning

National Research Council Canada - National Science Library

Kim, Joungbum; Schwarm, Sarah E; Ostendorf, Mari

2004-01-01

.... Specifically, combinations of decision trees and language models are used to predict sentence ends and interruption points and given these events transformation based learning is used to detect edit...

Decision-cache based XACML authorisation and anonymisation for XML documents

OpenAIRE

Ulltveit-Moe, Nils; Oleshchuk, Vladimir A

2012-01-01

Author's version of an article in the journal: Computer Standards and Interfaces. Also available from the publisher at: http://dx.doi.org/10.1016/j.csi.2011.10.007 This paper describes a decision cache for the eXtensible Access Control Markup Language (XACML) that supports fine-grained authorisation and anonymisation of XML based messages and documents down to XML attribute and element level. The decision cache is implemented as an XACML obligation service, where a specification of the XML...

Simulation-based algorithms for Markov decision processes

CERN Document Server

Chang, Hyeong Soo; Fu, Michael C; Marcus, Steven I

2013-01-01

Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.  Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical solution of the resulting models intractable.  In other cases, the system of interest is too complex to allow explicit specification of some of the MDP model parameters, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based algorithms have been developed to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function.  Specific approaches include adaptive sampling, evolutionary policy iteration, evolutionary random policy search, and model reference adaptive search. This substantially enlarged new edition reflects the latest developments in novel ...

Decision-Making in Audiology: Balancing Evidence-Based Practice and Patient-Centered Care

Science.gov (United States)

Clemesha, Jennifer; Lundmark, Erik; Crome, Erica; Barr, Caitlin; McMahon, Catherine M.

2017-01-01

Health-care service delivery models have evolved from a practitioner-centered approach toward a patient-centered ideal. Concurrently, increasing emphasis has been placed on the use of empirical evidence in decision-making to increase clinical accountability. The way in which clinicians use empirical evidence and client preferences to inform decision-making provides an insight into health-care delivery models utilized in clinical practice. The present study aimed to investigate the sources of information audiologists use when discussing rehabilitation choices with clients, and discuss the findings within the context of evidence-based practice and patient-centered care. To assess the changes that may have occurred over time, this study uses a questionnaire based on one of the few studies of decision-making behavior in audiologists, published in 1989. The present questionnaire was completed by 96 audiologists who attended the World Congress of Audiology in 2014. The responses were analyzed using qualitative and quantitative approaches. Results suggest that audiologists rank clinical test results and client preferences as the most important factors for decision-making. Discussion with colleagues or experts was also frequently reported as an important source influencing decision-making. Approximately 20% of audiologists mentioned utilizing research evidence to inform decision-making when no clear solution was available. Information shared at conferences was ranked low in terms of importance and reliability. This study highlights an increase in awareness of concepts associated with evidence-based practice and patient-centered care within audiology settings, consistent with current research-to-practice dissemination pathways. It also highlights that these pathways may not be sufficient for an effective clinical implementation of these practices. PMID:28752808

Water distribution network segmentation based on group multi-criteria decision approach

Directory of Open Access Journals (Sweden)

Marcele Elisa Fontana

Full Text Available Abstract A correct Network Segmentation (NS is necessary to perform proper maintenance activities in water distribution networks (WDN. For this, usually, isolation valves are allocating near the ends of pipes, blocking the flow of water. However, the allocation of valves increases costs substantially for the water supply companies. Additionally, other criteria should be taking account to analyze the benefits of the valves allocation. Thus, the problem is to define an alternative of NS which shows a good compromise in these different criteria. Moreover, usually, in this type of decision, there is more than one decision-maker involved, who can have different viewpoints. Therefore, this paper presents a model to support group decision-making, based on a multi-criteria method, in order to support the decision making procedure in the NS problem. As result, the model is able to find a solution that shows the best compromise regarding the benefits, costs, and the decision makers' preferences.

Differentiated instruction in a data-based decision-making context

NARCIS (Netherlands)

Faber, Janke M.; Glas, Cees A.W.; Visscher, Adrie J.

2018-01-01

In this study, the relationship between differentiated instruction, as an element of data-based decision making, and student achievement was examined. Classroom observations (n = 144) were used to measure teachers’ differentiated instruction practices and to predict the mathematical achievement of

Hard Decision Fusion based Cooperative Spectrum Sensing in Cognitive Radio System

Directory of Open Access Journals (Sweden)

N. Armi N.M. Saad

2013-09-01

Full Text Available Cooperative spectrum sensing was proposed to combat fading, noise uncertainty, shadowing, and even hidden node problem due to primary users (PUs activity that is not spatially localized. It improves the probability of detection by collaborating to detect PUs signal in cognitive radio (CR system as well. This paper studies cooperative spectrum sensing and signal detection in CR system by implementing hard decision combining in data fusion centre. Through computer simulation, we evaluate the performances of cooperative spectrum sensing and signal detection by employing OR and AND rules as decision combining. Energy detector is used to observe the presence of primary user (PU signal. Those results are compared to non-cooperative signal detection for evaluation. They show that cooperative technique has better performance than non-cooperative. Moreover, signal to noise ratio (SNR with greater than or equal 10 dB and 15 collaborated users in CR system has optimal value for probability of detection.

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Directory of Open Access Journals (Sweden)

Jiangyi Qin

Full Text Available 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.

The effect of the PROSPER partnership model on cultivating local stakeholder knowledge of evidence-based programs: a five-year longitudinal study of 28 communities.

Science.gov (United States)

Crowley, D Max; Greenberg, Mark T; Feinberg, Mark E; Spoth, Richard L; Redmond, Cleve R

2012-02-01

A substantial challenge in improving public health is how to facilitate the local adoption of evidence-based interventions (EBIs). To do so, an important step is to build local stakeholders' knowledge and decision-making skills regarding the adoption and implementation of EBIs. One EBI delivery system, called PROSPER (PROmoting School-community-university Partnerships to Enhance Resilience), has effectively mobilized community prevention efforts, implemented prevention programming with quality, and consequently decreased youth substance abuse. While these results are encouraging, another objective is to increase local stakeholder knowledge of best practices for adoption, implementation and evaluation of EBIs. Using a mixed methods approach, we assessed local stakeholder knowledge of these best practices over 5 years, in 28 intervention and control communities. Results indicated that the PROSPER partnership model led to significant increases in expert knowledge regarding the selection, implementation, and evaluation of evidence-based interventions. Findings illustrate the limited programming knowledge possessed by members of local prevention efforts, the difficulty of complete knowledge transfer, and highlight one method for cultivating that knowledge.

Unreliable Gut Feelings Can Lead to Correct Decisions: The Somatic Marker Hypothesis in Non-Linear Decision Chains

Science.gov (United States)

Bedia, Manuel G.; Di Paolo, Ezequiel

2012-01-01

Dual-process approaches of decision-making examine the interaction between affective/intuitive and deliberative processes underlying value judgment. From this perspective, decisions are supported by a combination of relatively explicit capabilities for abstract reasoning and relatively implicit evolved domain-general as well as learned domain-specific affective responses. One such approach, the somatic markers hypothesis (SMH), expresses these implicit processes as a system of evolved primary emotions supplemented by associations between affect and experience that accrue over lifetime, or somatic markers. In this view, somatic markers are useful only if their local capability to predict the value of an action is above a baseline equal to the predictive capability of the combined rational and primary emotional subsystems. We argue that decision-making has often been conceived of as a linear process: the effect of decision sequences is additive, local utility is cumulative, and there is no strong environmental feedback. This widespread assumption can have consequences for answering questions regarding the relative weight between the systems and their interaction within a cognitive architecture. We introduce a mathematical formalization of the SMH and study it in situations of dynamic, non-linear decision chains using a discrete-time stochastic model. We find, contrary to expectations, that decision-making events can interact non-additively with the environment in apparently paradoxical ways. We find that in non-lethal situations, primary emotions are represented globally over and above their local weight, showing a tendency for overcautiousness in situated decision chains. We also show that because they tend to counteract this trend, poorly attuned somatic markers that by themselves do not locally enhance decision-making, can still produce an overall positive effect. This result has developmental and evolutionary implications since, by promoting exploratory behavior

Unreliable gut feelings can lead to correct decisions: the somatic marker hypothesis in non-linear decision chains.

Science.gov (United States)

Bedia, Manuel G; Di Paolo, Ezequiel

2012-01-01

Dual-process approaches of decision-making examine the interaction between affective/intuitive and deliberative processes underlying value judgment. From this perspective, decisions are supported by a combination of relatively explicit capabilities for abstract reasoning and relatively implicit evolved domain-general as well as learned domain-specific affective responses. One such approach, the somatic markers hypothesis (SMH), expresses these implicit processes as a system of evolved primary emotions supplemented by associations between affect and experience that accrue over lifetime, or somatic markers. In this view, somatic markers are useful only if their local capability to predict the value of an action is above a baseline equal to the predictive capability of the combined rational and primary emotional subsystems. We argue that decision-making has often been conceived of as a linear process: the effect of decision sequences is additive, local utility is cumulative, and there is no strong environmental feedback. This widespread assumption can have consequences for answering questions regarding the relative weight between the systems and their interaction within a cognitive architecture. We introduce a mathematical formalization of the SMH and study it in situations of dynamic, non-linear decision chains using a discrete-time stochastic model. We find, contrary to expectations, that decision-making events can interact non-additively with the environment in apparently paradoxical ways. We find that in non-lethal situations, primary emotions are represented globally over and above their local weight, showing a tendency for overcautiousness in situated decision chains. We also show that because they tend to counteract this trend, poorly attuned somatic markers that by themselves do not locally enhance decision-making, can still produce an overall positive effect. This result has developmental and evolutionary implications since, by promoting exploratory behavior

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

Science.gov (United States)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-12-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning

Effectiveness of a Case-Based Computer Program on Students' Ethical Decision Making.

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Park, Eun-Jun; Park, Mihyun

2015-11-01

The aim of this study was to test the effectiveness of a case-based computer program, using an integrative ethical decision-making model, on the ethical decision-making competency of nursing students in South Korea. This study used a pre- and posttest comparison design. Students in the intervention group used a computer program for case analysis assignments, whereas students in the standard group used a traditional paper assignment for case analysis. The findings showed that using the case-based computer program as a complementary tool for the ethics courses offered at the university enhanced students' ethical preparedness and satisfaction with the course. On the basis of the findings, it is recommended that nurse educators use a case-based computer program as a complementary self-study tool in ethics courses to supplement student learning without an increase in course hours, particularly in terms of analyzing ethics cases with dilemma scenarios and exercising ethical decision making. Copyright 2015, SLACK Incorporated.

Multicriteria decision-making method based on a cosine similarity ...

African Journals Online (AJOL)

the cosine similarity measure is often used in information retrieval, citation analysis, and automatic classification. However, it scarcely deals with trapezoidal fuzzy information and multicriteria decision-making problems. For this purpose, a cosine similarity measure between trapezoidal fuzzy numbers is proposed based on ...

Technical Note: Application of Decision Theory Based Criteria for ...

African Journals Online (AJOL)

Technical Note: Application of Decision Theory Based Criteria for Structural Appraisal of a Building during Construction. ... Nigerian Journal of Technology ... reliability of concrete in a structure during construction, a case study of laboratory block for College of Continuing Education, University of Port Harcourt, Rivers State.

ADDIS: A decision support system for evidence-based medicine

NARCIS (Netherlands)

G. van Valkenhoef (Gert); T. Tervonen (Tommi); T. Zwinkels (Tijs); B. de Brock (Bert); H.L. Hillege (Hans)

2013-01-01

textabstractClinical trials are the main source of information for the efficacy and safety evaluation of medical treatments. Although they are of pivotal importance in evidence-based medicine, there is a lack of usable information systems providing data-analysis and decision support capabilities for

Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale.

Science.gov (United States)

Li, Qingsheng; Diao, Yuzhu; Gong, Zaiwu; Hu, Aqin

2018-03-02

Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging (GLHWAA) operator integration method after determining the index weight based on the grey correlation.

Nurses' decision making in heart failure management based on heart failure certification status.

Science.gov (United States)

Albert, Nancy M; Bena, James F; Buxbaum, Denise; Martensen, Linda; Morrison, Shannon L; Prasun, Marilyn A; Stamp, Kelly D

Research findings on the value of nurse certification were based on subjective perceptions or biased by correlations of certification status and global clinical factors. In heart failure, the value of certification is unknown. Examine the value of certification based nurses' decision-making. Cross-sectional study of nurses who completed heart failure clinical vignettes that reflected decision-making in clinical heart failure scenarios. Statistical tests included multivariable linear, logistic and proportional odds logistic regression models. Of nurses (N = 605), 29.1% were heart failure certified, 35.0% were certified in another specialty/job role and 35.9% were not certified. In multivariable modeling, nurses certified in heart failure (versus not heart failure certified) had higher clinical vignette scores (p = 0.002), reflecting higher evidence-based decision making; nurses with another specialty/role certification (versus no certification) did not (p = 0.62). Heart failure certification, but not in other specialty/job roles was associated with decisions that reflected delivery of high-quality care. Copyright © 2018 Elsevier Inc. All rights reserved.

Community-Based Monitoring in Response to Local Concerns: Creating Usable Knowledge for Water Management in Rural Land

Directory of Open Access Journals (Sweden)

Adriana C. Flores-Díaz

2018-04-01

Full Text Available Water resources around the world are being affected by increasing demand for human consumption as well as by industrial and agricultural use. Water quality has an impact on our quality of life, so effective monitoring provides the necessary data to allow decision makers to address critical water-related issues. This study (1 analyzes water knowledge generated by a community-based water monitoring (CBWM network within a world heritage site; (2 discusses the extent to which monitoring responds to community concerns about water; and (3 indicates challenges in the generation of local usable knowledge. Using information generated over 6.5 years by a local monitoring network, we calculated a water quality index (WQI and generated a time-series analysis using the breaks for additive season and trend (Bfast algorithm. Results were grouped by specific community and institutional concerns about water. Springs under good management practices had low pollution levels, while others used for drinking and recreation had high fecal bacterial counts. Monitoring provided data about Escherichia coli counts exceeding legal limits, and about conditions of alkalinity and dissolved oxygen that represent a risk for the freshwater ecosystems. This study demonstrates how CBWM schemes can be a means of generating knowledge of water resources that can enhance the understanding of water dynamics and inform users’ decisions at local–regional levels.

A framework for production of systematic review based briefings to support evidence-informed decision-making

Directory of Open Access Journals (Sweden)

Chambers Duncan

2012-07-01

Full Text Available Abstract Background We have developed a framework for translating existing sources of synthesized and quality-assessed evidence, primarily systematic reviews, into actionable messages in the form of short accessible briefings. The service aims to address real-life problems in response to requests from decision-makers. Development of the framework was based on a scoping review of existing resources and our initial experience with two briefing topics, including models of service provision for young people with eating disorders. We also drew on previous experience in dissemination research and practice. Where appropriate, we made use of the SUPporting POlicy relevant Reviews and Trials (SUPPORT tools for evidence-informed policymaking. Findings To produce a product that it is fit for this purpose it has been necessary to go beyond a traditional summary of the available evidence relating to effectiveness. Briefings have, therefore, included consideration of cost effectiveness, local applicability, implications relating to local service delivery, budgets, implementation and equity. Our first evidence briefings produced under this framework cover diagnostic endoscopy by specialist nurses and integrated care pathways in mental healthcare settings. Conclusions The framework will enable researchers to present and contextualize evidence from systematic reviews and other sources of synthesized and quality-assessed evidence. The approach is designed to address the wide range of questions of interest to decision-makers, especially those commissioning services or managing service delivery and organization in primary or secondary care. Evaluation of the use and usefulness of the evidence briefings we produce is an integral part of the framework and will help to fill a gap in the literature.

MODIS-Based Products for Operational Decision Support Systems, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — SMH Consulting proposes to develop a web-based decision support system to assist in Rapid Assessment, Monitoring, and Management (RAMM-DSS) on a regional scale. SMH...

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

Science.gov (United States)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.