Sample records for quantify uncertain emergency
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Quantify uncertain emergency search techniques (QUEST) -- Theory and user's guide
International Nuclear Information System (INIS)
Johnson, M.M.; Goldsby, M.E.; Plantenga, T.D.; Porter, T.L.; West, T.H.; Wilcox, W.B.; Hensley, W.K.
1998-01-01
As recent world events show, criminal and terrorist access to nuclear materials is a growing national concern. The national laboratories are taking the lead in developing technologies to counter these potential threats to the national security. Sandia National laboratories, with support from Pacific Northwest National Laboratory and the Bechtel Nevada, Remote Sensing Laboratory, has developed QUEST (a model to Quantify Uncertain Emergency Search Techniques), to enhance the performance of organizations in the search for lost or stolen nuclear material. In addition, QUEST supports a wide range of other applications, such as environmental monitoring, nuclear facilities inspections, and searcher training. QUEST simulates the search for nuclear materials and calculates detector response for various source types and locations. The probability of detecting a radioactive source during a search is a function of many different variables, including source type, search location and structure geometry (including shielding), search dynamics (path and speed), and detector type and size. Through calculation of dynamic detector response, QUEST makes possible quantitative comparisons of various sensor technologies and search patterns. The QUEST model can be used as a tool to examine the impact of new detector technologies, explore alternative search concepts, and provide interactive search/inspector training
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QUEST: A model to quantify uncertain emergency search techniques, theory and application
International Nuclear Information System (INIS)
Johnson, M.M.; Goldsby, M.E.; Plantenga, T.D.; Wilcox, W.B.; Hensley, W.K.
1996-01-01
As recent world events show, criminal and terrorist access to nuclear materials is a growing national concern. The national laboratories are taking the lead in developing technologies to counter these potential threats to our national security. Sandia National Laboratories, with support from Pacific Northwest Laboratory and the Remote Sensing Laboratory, has developed QUEST (a model to Quantify Uncertain Emergency Search Techniques), to enhance the performance of organizations in the search for lost or stolen nuclear material. In addition, QUEST supports a wide range of other applications, such as environmental monitoring, nuclear facilities inspections, and searcher training. QUEST simulates the search for nuclear materials and calculates detector response fro various source types and locations. The probability of detecting a radioactive source during a search is a function of many different variables. Through calculation of dynamic detector response, QUEST makes possible quantitative comparisons of various sensor technologies and search patterns. The QUEST model can be used to examine the impact of new detector technologies, explore alternative search concepts, and provide interactive search/inspector training
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The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments
Directory of Open Access Journals (Sweden)
Jin Qin
2017-02-01
Full Text Available The reasonable utilization of limited resources is critical to realize the sustainable developments. In the initial 72-h crucial rescue period after the disaster, emergency supplies have always been insufficient and the demands in the affected area have always been uncertain. In order to improve timeliness, utilization and sustainability of emergency service, the allocation of the emergency supplies and the emergency vehicle routes should be determined simultaneously. Assuming the uncertain demands follow normal distribution, an optimization model for the emergency vehicle routing, by considering the insufficient supplies and the uncertain demands, is developed. The objective function is applied to minimize the total costs, including the penalty costs induced by more or less supplies than the actual demands at all demand points, as well as the constraints of the time windows and vehicle load capacity taken into account. In more details, a solution method for the model, based on the genetic algorithm, is proposed, which solves the problem in two stages. A numerical example is presented to demonstrate the efficiency and validity of the proposed model and algorithm.
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Quantifying uncertainty in Gulf of Mexico forecasts stemming from uncertain initial conditions
Iskandarani, Mohamed
2016-06-09
Polynomial Chaos (PC) methods are used to quantify the impacts of initial conditions uncertainties on oceanic forecasts of the Gulf of Mexico circulation. Empirical Orthogonal Functions are used as initial conditions perturbations with their modal amplitudes considered as uniformly distributed uncertain random variables. These perturbations impact primarily the Loop Current system and several frontal eddies located in its vicinity. A small ensemble is used to sample the space of the modal amplitudes and to construct a surrogate for the evolution of the model predictions via a nonintrusive Galerkin projection. The analysis of the surrogate yields verification measures for the surrogate\\'s reliability and statistical information for the model output. A variance analysis indicates that the sea surface height predictability in the vicinity of the Loop Current is limited to about 20 days. © 2016. American Geophysical Union. All Rights Reserved.
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Emulation of a complex global aerosol model to quantify sensitivity to uncertain parameters
Directory of Open Access Journals (Sweden)
L. A. Lee
2011-12-01
Full Text Available Sensitivity analysis of atmospheric models is necessary to identify the processes that lead to uncertainty in model predictions, to help understand model diversity through comparison of driving processes, and to prioritise research. Assessing the effect of parameter uncertainty in complex models is challenging and often limited by CPU constraints. Here we present a cost-effective application of variance-based sensitivity analysis to quantify the sensitivity of a 3-D global aerosol model to uncertain parameters. A Gaussian process emulator is used to estimate the model output across multi-dimensional parameter space, using information from a small number of model runs at points chosen using a Latin hypercube space-filling design. Gaussian process emulation is a Bayesian approach that uses information from the model runs along with some prior assumptions about the model behaviour to predict model output everywhere in the uncertainty space. We use the Gaussian process emulator to calculate the percentage of expected output variance explained by uncertainty in global aerosol model parameters and their interactions. To demonstrate the technique, we show examples of cloud condensation nuclei (CCN sensitivity to 8 model parameters in polluted and remote marine environments as a function of altitude. In the polluted environment 95 % of the variance of CCN concentration is described by uncertainty in the 8 parameters (excluding their interaction effects and is dominated by the uncertainty in the sulphur emissions, which explains 80 % of the variance. However, in the remote region parameter interaction effects become important, accounting for up to 40 % of the total variance. Some parameters are shown to have a negligible individual effect but a substantial interaction effect. Such sensitivities would not be detected in the commonly used single parameter perturbation experiments, which would therefore underpredict total uncertainty. Gaussian process
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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)
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Wind farm investment risks under uncertain CDM benefit in China
International Nuclear Information System (INIS)
Yang, Ming; Nguyen, Francois; T'Serclaes, Philippine de; Buchner, Barbara
2010-01-01
China has set an ambitious target to increase its wind power capacity by 35 GW from 2007 to 2020. The country's hunger for clean power provides great opportunities for wind energy investors. However, risks from China's uncertain electricity market regulation and an uncertain energy policy framework, mainly due to uncertain Clean Development Mechanism (CDM) benefits, prevent foreign investors from investing in China's wind energy. The objectives of this paper are to: (1) quantify wind energy investment risk premiums in an uncertain international energy policy context and (2) evaluate the impact of uncertain CDM benefits on the net present values of wind power projects. With four scenarios, this study simulates possible prices of certified emissions reductions (CERs) from wind power projects. Project net present values (NPVs) have been calculated. The project risk premiums are drawn from different and uncertain CER prices. Our key findings show that uncertain CDM benefits will significantly affect the project NPVs. This paper concludes that the Chinese government needs revising its tariff incentives, most likely by introducing fixed feed-in tariffs (FITs), and re-examining its CDM-granting policy and its wind project tax rates, to facilitate wind power development and enable China to achieve its wind energy target. (author)
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75 FR 54802 - Requirement of a Statement Disclosing Uncertain Tax Positions
2010-09-09
... return. Corporations that prepare financial statements are required by generally accepted accounting principles to identify and quantify all uncertain tax positions as described in Financial Accounting..., including International Financial Reporting Standards and country-specific generally accepted accounting...
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Tsallis’ non-extensive free energy as a subjective value of an uncertain reward
Takahashi, Taiki
2009-03-01
Recent studies in neuroeconomics and econophysics revealed the importance of reward expectation in decision under uncertainty. Behavioral neuroeconomic studies have proposed that the unpredictability and the probability of an uncertain reward are distinctly encoded as entropy and a distorted probability weight, respectively, in the separate neural systems. However, previous behavioral economic and decision-theoretic models could not quantify reward-seeking and uncertainty aversion in a theoretically consistent manner. In this paper, we have: (i) proposed that generalized Helmholtz free energy in Tsallis’ non-extensive thermostatistics can be utilized to quantify a perceived value of an uncertain reward, and (ii) empirically examined the explanatory powers of the models. Future study directions in neuroeconomics and econophysics by utilizing the Tsallis’ free energy model are discussed.
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Multiple point statistical simulation using uncertain (soft) conditional data
Hansen, Thomas Mejer; Vu, Le Thanh; Mosegaard, Klaus; Cordua, Knud Skou
2018-05-01
Geostatistical simulation methods have been used to quantify spatial variability of reservoir models since the 80s. In the last two decades, state of the art simulation methods have changed from being based on covariance-based 2-point statistics to multiple-point statistics (MPS), that allow simulation of more realistic Earth-structures. In addition, increasing amounts of geo-information (geophysical, geological, etc.) from multiple sources are being collected. This pose the problem of integration of these different sources of information, such that decisions related to reservoir models can be taken on an as informed base as possible. In principle, though difficult in practice, this can be achieved using computationally expensive Monte Carlo methods. Here we investigate the use of sequential simulation based MPS simulation methods conditional to uncertain (soft) data, as a computational efficient alternative. First, it is demonstrated that current implementations of sequential simulation based on MPS (e.g. SNESIM, ENESIM and Direct Sampling) do not account properly for uncertain conditional information, due to a combination of using only co-located information, and a random simulation path. Then, we suggest two approaches that better account for the available uncertain information. The first make use of a preferential simulation path, where more informed model parameters are visited preferentially to less informed ones. The second approach involves using non co-located uncertain information. For different types of available data, these approaches are demonstrated to produce simulation results similar to those obtained by the general Monte Carlo based approach. These methods allow MPS simulation to condition properly to uncertain (soft) data, and hence provides a computationally attractive approach for integration of information about a reservoir model.
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Uncertain differential equations
Yao, Kai
2016-01-01
This book introduces readers to the basic concepts of and latest findings in the area of differential equations with uncertain factors. It covers the analytic method and numerical method for solving uncertain differential equations, as well as their applications in the field of finance. Furthermore, the book provides a number of new potential research directions for uncertain differential equation. It will be of interest to researchers, engineers and students in the fields of mathematics, information science, operations research, industrial engineering, computer science, artificial intelligence, automation, economics, and management science.
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Ranking Queries on Uncertain Data
Hua, Ming
2011-01-01
Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task. Ranking queries (also known as top-k queries) are often natural and useful in analyzing uncertain data. Ranking Queries on Uncertain Data discusses the motivations/applications, challenging problems, the fundamental principles, and the evaluation algorith
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Time-optimal path planning in uncertain flow fields using ensemble method
Wang, Tong
2016-01-06
An ensemble-based approach is developed to conduct time-optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where a set deterministic predictions is used to model and quantify uncertainty in the predictions. In the operational setting, much about dynamics, topography and forcing of the ocean environment is uncertain, and as a result a single path produced by a model simulation has limited utility. To overcome this limitation, we rely on a finitesize ensemble of deterministic forecasts to quantify the impact of variability in the dynamics. The uncertainty of flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each the resulting realizations of the uncertain current field, we predict the optimal path by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of sampling strategy, and develop insight into extensions dealing with regional or general circulation models. In particular, the ensemble method enables us to perform a statistical analysis of travel times, and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
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Quantifying uncertainty in Gulf of Mexico forecasts stemming from uncertain initial conditions
Iskandarani, Mohamed; Le Hé naff, Matthieu; Srinivasan, Ashwanth; Knio, Omar
2016-01-01
Polynomial Chaos (PC) methods are used to quantify the impacts of initial conditions uncertainties on oceanic forecasts of the Gulf of Mexico circulation. Empirical Orthogonal Functions are used as initial conditions perturbations with their modal
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Uncertain programming models for portfolio selection with uncertain returns
Zhang, Bo; Peng, Jin; Li, Shengguo
2015-10-01
In an indeterminacy economic environment, experts' knowledge about the returns of securities consists of much uncertainty instead of randomness. This paper discusses portfolio selection problem in uncertain environment in which security returns cannot be well reflected by historical data, but can be evaluated by the experts. In the paper, returns of securities are assumed to be given by uncertain variables. According to various decision criteria, the portfolio selection problem in uncertain environment is formulated as expected-variance-chance model and chance-expected-variance model by using the uncertainty programming. Within the framework of uncertainty theory, for the convenience of solving the models, some crisp equivalents are discussed under different conditions. In addition, a hybrid intelligent algorithm is designed in the paper to provide a general method for solving the new models in general cases. At last, two numerical examples are provided to show the performance and applications of the models and algorithm.
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Quantifying Information Flow During Emergencies
Gao, Liang; Song, Chaoming; Gao, Ziyou; Barabási, Albert-László; Bagrow, James P.; Wang, Dashun
2014-02-01
Recent advances on human dynamics have focused on the normal patterns of human activities, with the quantitative understanding of human behavior under extreme events remaining a crucial missing chapter. This has a wide array of potential applications, ranging from emergency response and detection to traffic control and management. Previous studies have shown that human communications are both temporally and spatially localized following the onset of emergencies, indicating that social propagation is a primary means to propagate situational awareness. We study real anomalous events using country-wide mobile phone data, finding that information flow during emergencies is dominated by repeated communications. We further demonstrate that the observed communication patterns cannot be explained by inherent reciprocity in social networks, and are universal across different demographics.
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Flexible Procurement of Services with Uncertain Durations using Redundancy
Stein, S; Gerding, E; Rogers, A; Larson, K; Jennings, NR
2009-01-01
Emerging service-oriented technologies allow software agents to automatically procure distributed services to complete complex tasks. However, in many application scenarios, service providers demand financial remuneration, execution times are uncertain and consumers have deadlines for their tasks. In this paper, we address these issues by developing a novel approach that dynamically procures multiple, redundant services over time, in order to ensure success by the deadline. Specifically, we f...
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Path planning in uncertain flow fields using ensemble method
Wang, Tong
2016-08-20
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
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Quantification of uncertain outcomes from site characterization: Insights from the ESF-AS
International Nuclear Information System (INIS)
Boyle, W.J.; Parrish, D.K.; Beccue, P.C.
1992-01-01
As part of the Exploratory Studies Facility Alternatives Study (ESF-AS) the uncertain outcomes from site characterization were quantified using a probabilistic tree known as ''Nature's Tree.'' Nature's Tree distinguished the true characteristics of the Yucca Mountain site from the perceived characteristics deduced from testing. Bayesian probabilistic calculations converted probabilities in Nature's Tree to the probabilistic estimates required for the comparative analysis of Exploratory Studies Facility-repository options. Experts on characterization testing explicitly addressed several site characterization issues that are considered implicitly in many site characterization programs
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Quantifying emission reduction contributions by emerging economics
Energy Technology Data Exchange (ETDEWEB)
Moltmann, Sara; Hagemann, Markus; Eisbrenner, Katja; Hoehne, Niklas [Ecofys GmbH, Koeln (Germany); Sterk, Wolfgang; Mersmann, Florian; Ott, Hermann E.; Watanabe, Rie [Wuppertal Institut (Germany)
2011-04-15
Further action is needed that goes far beyond what has been agreed so far under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol to 'prevent dangerous anthropogenic interference with the climate system', the ultimate objective of the UNFCCC. It is out of question that developed countries (Annex I countries) will have to take a leading role. They will have to commit to substantial emission reductions and financing commitments due to their historical responsibility and their financial capability. However, the stabilisation of the climate system will require global emissions to peak within the next decade and decline well below half of current levels by the middle of the century. It is hence a global issue and, thus, depends on the participation of as many countries as possible. This report provides a comparative analysis of greenhouse gas (GHG) emissions, including their national climate plans, of the major emitting developing countries Brazil, China, India, Mexico, South Africa and South Korea. It includes an overview of emissions and economic development, existing national climate change strategies, uses a consistent methodology for estimating emission reduction potential, costs of mitigation options, provides an estimate of the reductions to be achieved through the national climate plans and finally provides a comparison of the results to the allocation of emission rights according to different global effort-sharing approaches. In addition, the report discusses possible nationally appropriate mitigation actions (NAMAs) the six countries could take based on the analysis of mitigation options. This report is an output of the project 'Proposals for quantifying emission reduction contributions by emerging economies' by Ecofys and the Wuppertal Institute for the Federal Environment Agency in Dessau. It builds upon earlier joint work ''Proposals for contributions of emerging economies to the climate
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Uncertain data envelopment analysis
Wen, Meilin
2014-01-01
This book is intended to present the milestones in the progression of uncertain Data envelopment analysis (DEA). Chapter 1 gives some basic introduction to uncertain theories, including probability theory, credibility theory, uncertainty theory and chance theory. Chapter 2 presents a comprehensive review and discussion of basic DEA models. The stochastic DEA is introduced in Chapter 3, in which the inputs and outputs are assumed to be random variables. To obtain the probability distribution of a random variable, a lot of samples are needed to apply the statistics inference approach. Chapter 4
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Visualization of Uncertain Contour Trees
DEFF Research Database (Denmark)
Kraus, Martin
2010-01-01
Contour trees can represent the topology of large volume data sets in a relatively compact, discrete data structure. However, the resulting trees often contain many thousands of nodes; thus, many graph drawing techniques fail to produce satisfactory results. Therefore, several visualization methods...... were proposed recently for the visualization of contour trees. Unfortunately, none of these techniques is able to handle uncertain contour trees although any uncertainty of the volume data inevitably results in partially uncertain contour trees. In this work, we visualize uncertain contour trees...... by combining the contour trees of two morphologically filtered versions of a volume data set, which represent the range of uncertainty. These two contour trees are combined and visualized within a single image such that a range of potential contour trees is represented by the resulting visualization. Thus...
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Challenges in quantifying biosphere-atmosphere exchange of nitrogen species
Energy Technology Data Exchange (ETDEWEB)
Sutton, M.A. [Centre for Ecology and Hydrology (CEH), Edinburgh Research Station, Bush Estate, Penicuik, EH26 0QB (United Kingdom)], E-mail: ms@ceh.ac.uk; Nemitz, E. [Centre for Ecology and Hydrology (CEH), Edinburgh Research Station, Bush Estate, Penicuik, EH26 0QB (United Kingdom); Erisman, J.W. [ECN, Clean Fossil Fuels, PO Box 1, 1755 ZG Petten (Netherlands); Beier, C. [Riso National Laboratory, PO Box 49, DK-4000 Roskilde (Denmark); Bahl, K. Butterbach [Institute of Meteorology and Climate Research, Atmos. Environ. Research (IMK-IFU), Research Centre Karlsruhe GmbH, Kreuzeckbahnstr. 19, 82467 Garmisch-Partenkirchen (Germany); Cellier, P. [INRA Unite Mixte de Recherche, 78850 Thiverval-Grignon (France); Vries, W. de [Alterra, Green World Research, PO Box 47, 6700 AA Wageningen (Netherlands); Cotrufo, F. [Dip. Scienze Ambientali, Seconda Universita degli Studi di Napoli, via Vivaldi 43, 81100 Caserta (Italy); Skiba, U.; Di Marco, C.; Jones, S. [Centre for Ecology and Hydrology (CEH), Edinburgh Research Station, Bush Estate, Penicuik, EH26 0QB (United Kingdom); Laville, P.; Soussana, J.F.; Loubet, B. [INRA Unite Mixte de Recherche, 78850 Thiverval-Grignon (France); Twigg, M.; Famulari, D. [Centre for Ecology and Hydrology (CEH), Edinburgh Research Station, Bush Estate, Penicuik, EH26 0QB (United Kingdom); Whitehead, J.; Gallagher, M.W. [School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Williamson Building, Oxford Road, Manchester, M13 9PL (United Kingdom); Neftel, A.; Flechard, C.R. [Agroscope FAL Reckenholz, Federal Research Station for Agroecology and Agriculture, PO Box, CH 8046 Zurich (Switzerland)] (and others)
2007-11-15
Recent research in nitrogen exchange with the atmosphere has separated research communities according to N form. The integrated perspective needed to quantify the net effect of N on greenhouse-gas balance is being addressed by the NitroEurope Integrated Project (NEU). Recent advances have depended on improved methodologies, while ongoing challenges include gas-aerosol interactions, organic nitrogen and N{sub 2} fluxes. The NEU strategy applies a 3-tier Flux Network together with a Manipulation Network of global-change experiments, linked by common protocols to facilitate model application. Substantial progress has been made in modelling N fluxes, especially for N{sub 2}O, NO and bi-directional NH{sub 3} exchange. Landscape analysis represents an emerging challenge to address the spatial interactions between farms, fields, ecosystems, catchments and air dispersion/deposition. European up-scaling of N fluxes is highly uncertain and a key priority is for better data on agricultural practices. Finally, attention is needed to develop N flux verification procedures to assess compliance with international protocols. - Current N research is separated by form; the challenge is to link N components, scales and issues.
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Data Envelopment Analysis with Uncertain Inputs and Outputs
Directory of Open Access Journals (Sweden)
Meilin Wen
2014-01-01
Full Text Available Data envelopment analysis (DEA, as a useful management and decision tool, has been widely used since it was first invented by Charnes et al. in 1978. On the one hand, the DEA models need accurate inputs and outputs data. On the other hand, in many situations, inputs and outputs are volatile and complex so that they are difficult to measure in an accurate way. The conflict leads to the researches of uncertain DEA models. This paper will consider DEA in uncertain environment, thus producing a new model based on uncertain measure. Due to the complexity of the new uncertain DEA model, an equivalent deterministic model is presented. Finally, a numerical example is presented to illustrate the effectiveness of the uncertain DEA model.
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Optimized maritime emergency resource allocation under dynamic demand.
Directory of Open Access Journals (Sweden)
Wenfen Zhang
Full Text Available Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.
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CKD of Uncertain Etiology: A Systematic Review.
Lunyera, Joseph; Mohottige, Dinushika; Von Isenburg, Megan; Jeuland, Marc; Patel, Uptal D; Stanifer, John W
2016-03-07
Epidemics of CKD of uncertain etiology (CKDu) are emerging around the world. Highlighting common risk factors for CKD of uncertain etiology across various regions and populations may be important for health policy and public health responses. We searched PubMed, Embase, Scopus and Web of Science databases to identify published studies on CKDu. The search was generated in January of 2015; no language or date limits were used. We used a vote-counting method to evaluate exposures across all studies. We identified 1607 articles, of which 26 met inclusion criteria. Eighteen (69%) were conducted in known CKDu-endemic countries: Sri Lanka (38%), Nicaragua (19%), and El Salvador (12%). The other studies were from India, Japan, Australia, Mexico, Sweden, Tunisia, Tanzania, and the United States. Heavy metals, heat stress, and dietary exposures were reported across all geographic regions. In south Asia, family history, agrochemical use, and heavy metal exposures were reported most frequently, whereas altitude and temperature were reported only in studies from Central America. Across all regions, CKDu was most frequently associated with a family history of CKDu, agricultural occupation, men, middle age, snake bite, and heavy metal exposure. Studies examining etiologies of CKDu have reported many exposures that are heterogeneous and vary by region. To identify etiologies of CKDu, designing consistent and comparative multisite studies across high-risk populations may help elucidate the importance of region-specific versus global risk factors. Copyright © 2016 by the American Society of Nephrology.
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Compete, coordinate, and cooperate: How to exploit uncertain environments with social interaction.
Schulze, Christin; Newell, Ben R
2015-10-01
Countless decisions, from the trivial to the crucial, are made in complex social contexts while facing uncertain consequences. Yet a large portion of decision making research focuses on either the effects of social interaction or the effects of environmental uncertainty by examining strategic games against others or individual games against nature. Drawing a connection between these approaches, the authors extend a standard individual choice paradigm to include social interaction with 1 other person. In this paradigm, 2 competing decision makers repeatedly select among 2 options, each offering a particular probability of a fixed payoff. When both players choose the same, correct option, the payoff is evenly split; when they choose different options, the player choosing the correct option receives the full payoff. The addition of this social dimension gives players an opportunity to fully exploit an uncertain environment via cooperation: By consistently choosing opposite options, two players can exploit the uncertain environment more effectively than a single player could. We present 2 experiments that manipulate environmental (Experiment 1) and social (Experiment 2) aspects of the paradigm. In Experiment 1, the outcome probabilities were either known or unknown to participants; in Experiment 2, participants' attention was drawn to individual or group gains by introducing either within- or between-group competition. Efficient cooperation did not emerge spontaneously in Experiment 1. Instead, most people probability maximized, mirroring the behavior observed in individual choice. By contrast, between--group competition in Experiment 2 facilitated efficient-but not always equitable--exploitation of uncertain environments. This work links the concepts of individual risky choice and strategic decision making under both environmental and social uncertainty. (c) 2015 APA, all rights reserved).
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(Approximate) Uncertain Skylines
DEFF Research Database (Denmark)
Afshani, Peyman; Agarwal, Pankaj K.; Arge, Lars Allan
2011-01-01
Given a set of points with uncertain locations, we consider the problem of computing the probability of each point lying on the skyline, that is, the probability that it is not dominated by any other input point. If each point’s uncertainty is described as a probability distribution over a discre...
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(Approximate) Uncertain Skylines
DEFF Research Database (Denmark)
Afshani, Peyman; Agarwal, Pankaj K.; Arge, Lars
2013-01-01
Given a set of points with uncertain locations, we consider the problem of computing the probability of each point lying on the skyline, that is, the probability that it is not dominated by any other input point. If each point’s uncertainty is described as a probability distribution over a discre...
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Numerical solution of uncertain neutron diffusion equation for ...
Indian Academy of Sciences (India)
The concept of fuzziness is hybridised with ... impreciseness, vagueness, experimental error and different operating conditions affected by the system. ... But the presence of uncertain parameters makes the system uncertain and we get uncer-.
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Application of Fuzzy Theory to Radiological Emergency Preparedness
International Nuclear Information System (INIS)
Han, Moon Hee; Jeong, Hyo Joon; Kim, Eun Han; Suh, Kyung Suk; Hwang, Won Tae
2005-01-01
Emergency preparedness for nuclear facility is considered as an important part for public health and safety. In an emergency, it is not easy to get the information which is needed for the operation of an emergency system. Even though the lack of the information, decision-maker should make an early decision for the public. And the real situation is often not crisp and deterministic. The concept of fuzzy set provides the mathematical formulations which can characterize the uncertain variables in the models related to radiological emergency preparedness. And it provides a method which can describe the characteristics of uncertain variables represented by the fuzzy membership functions, and the effects of distribution can be handled with the fuzzy relation and the fuzzy reasoning. By the application of linguistic variables and fuzzy algorithms, it is possible to provide an approximate and effective tool to describe the system which is too complex or ill defined to use precise mathematical analysis
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International Nuclear Information System (INIS)
Mirkhani, Sh.; Saboohi, Y.
2012-01-01
Highlights: ► An existing bottom-up deterministic energy system model (ESM) has limited capability in handling the uncertainties. ► Uncertainty has been modeled based on GBM. Probabilistic scenarios are generated based on Cox–Ross method. ► A multistage stochastic model has been developed where scenarios are integrated in the energy system model. ► A distributed generation system has been introduced as a case study where fuel price is considered as an uncertain parameter. - Abstract: A deterministic energy supply model with bottom-up structure has limited capability in handling the uncertainties. To enhance the applicability of such a model in an uncertain environment two main issues have been investigated in the present paper. First, a binomial lattice is generated based on the stochastic nature of the source of uncertainty. Second, an energy system model (ESM) has been reformulated as a multistage stochastic problem. The result of the application of the modified energy model encompasses all uncertain outcomes together and enables optimal timing of capacity expansion. The performance of the model has been demonstrated with the help of a case study. The case study has been formulated on the assumption that a gas fired engine competes with renewable energy technologies in an uncertain environment where the price of natural gas is volatile. The result of stochastic model has then been compared with those of a deterministic model by studying the expected value of perfect information (EVPI) and the value of stochastic solution (VSS). Finally the results of the sensitivity analysis have been discussed where the characteristics of uncertainty of the price of fuel are varied.
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Neural basis of uncertain cue processing in trait anxiety.
Zhang, Meng; Ma, Chao; Luo, Yanyan; Li, Ji; Li, Qingwei; Liu, Yijun; Ding, Cody; Qiu, Jiang
2016-02-19
Individuals with high trait anxiety form a non-clinical group with a predisposition for an anxiety-related bias in emotional and cognitive processing that is considered by some to be a prerequisite for psychiatric disorders. Anxious individuals tend to experience more worry under uncertainty, and processing uncertain information is an important, but often overlooked factor in anxiety. So, we decided to explore the brain correlates of processing uncertain information in individuals with high trait anxiety using the learn-test paradigm. Behaviorally, the percentages on memory test and the likelihood ratios of identifying novel stimuli under uncertainty were similar to the certain fear condition, but different from the certain neutral condition. The brain results showed that the visual cortex, bilateral fusiform gyrus, and right parahippocampal gyrus were active during the processing of uncertain cues. Moreover, we found that trait anxiety was positively correlated with the BOLD signal of the right parahippocampal gyrus during the processing of uncertain cues. No significant results were found in the amygdala during uncertain cue processing. These results suggest that memory retrieval is associated with uncertain cue processing, which is underpinned by over-activation of the right parahippocampal gyrus, in individuals with high trait anxiety.
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Learning from uncertain curves
DEFF Research Database (Denmark)
Mallasto, Anton; Feragen, Aasa
2017-01-01
We introduce a novel framework for statistical analysis of populations of nondegenerate Gaussian processes (GPs), which are natural representations of uncertain curves. This allows inherent variation or uncertainty in function-valued data to be properly incorporated in the population analysis. Us...
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Chernobyl, the true, the false and the uncertain
International Nuclear Information System (INIS)
1996-04-01
This work makes the part between the true and the false information in France about the Chernobyl accident that have been read in different newspapers during the last years. This document is divide in three parts: what is true, what is false, what is uncertain. In each part are noticed extracts from newspapers face to the synthesis of thoughts about them. It is the fourth edition, the first one was in April 1990, the second one was in 1992 after a report from IAEA on the radiological consequences, the third edition was born in 1994 with the emergence of thyroid cancers especially among children, this fourth edition of 1996 takes into account the sanitary report given by the World Health Organisation experts in 1995. It confirms the progression of thyroid cancers and the absence of any other cancer as well leukemia. (N.C.)
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Diversified models for portfolio selection based on uncertain semivariance
Chen, Lin; Peng, Jin; Zhang, Bo; Rosyida, Isnaini
2017-02-01
Since the financial markets are complex, sometimes the future security returns are represented mainly based on experts' estimations due to lack of historical data. This paper proposes a semivariance method for diversified portfolio selection, in which the security returns are given subjective to experts' estimations and depicted as uncertain variables. In the paper, three properties of the semivariance of uncertain variables are verified. Based on the concept of semivariance of uncertain variables, two types of mean-semivariance diversified models for uncertain portfolio selection are proposed. Since the models are complex, a hybrid intelligent algorithm which is based on 99-method and genetic algorithm is designed to solve the models. In this hybrid intelligent algorithm, 99-method is applied to compute the expected value and semivariance of uncertain variables, and genetic algorithm is employed to seek the best allocation plan for portfolio selection. At last, several numerical examples are presented to illustrate the modelling idea and the effectiveness of the algorithm.
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Decision Making in Uncertain Rural Scenarios by means of Fuzzy TOPSIS Method
Directory of Open Access Journals (Sweden)
Eva Armero
2011-01-01
Full Text Available A great deal of uncertain information which is difficult to quantify is taken into account by farmers and experts in the enterprise when making decisions. We are interested in the problems of the implementation of a rabbit-breeding farm. One of the first decisions to be taken refers to the design or type of structure for housing the animals, which is determined by the level of environmental control sought to be maintained in its interior. A farmer was consulted, and his answers were incorporated into the analysis, by means of the fuzzy TOPSIS methodology. The main purpose of this paper is to study the problem by means of the fuzzy TOPSIS method as multicriteria decision making, when the information was given in linguistic terms.
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Robust Control with Enlaeged Interval of Uncertain Parameters
Directory of Open Access Journals (Sweden)
Marek Keresturi
2002-01-01
Full Text Available Robust control is advantageous for systems with defined interval of uncertain parameters. This can be substantially enlarged dividing it into a few sub-intervals. Corresponding controllers for each of them may be set after approximate identification of some uncertain plant parameters. The paper deals with application of the pole region assignment method for position control of the crane crab. The same track form is required for uncertain burden mass and approximate value of rope length. Measurement of crab position and speed is supposed, burden deviation angle is observed. Simulation results have verified feasibility of this design procedure.
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Directory of Open Access Journals (Sweden)
Martin Hilbert
2017-01-01
Full Text Available Evolving biological and socioeconomic populations can sometimes increase their growth rate by cooperatively redistributing resources among their members. In unchanging environments, this simply comes down to reallocating resources to fitter types. In uncertain and fluctuating environments, cooperation cannot always outperform blind competitive selection. When can it? The conditions depend on the particular shape of the fitness landscape. The article derives a single measure that quantifies by how much an intervention in stochastic environments can possibly outperform the blind forces of natural selection. It is a multivariate and multilevel measure that essentially quantifies the amount of complementary variety between different population types and environmental states. The more complementary the fitness of types in different environmental states, the proportionally larger the potential benefit of strategic cooperation over competitive selection. With complementary variety, holding population shares constant will always outperform natural and market selection (including bet-hedging, portfolio management, and stochastic switching. The result can be used both to determine the acceptable cost of learning the details of a fitness landscape and to design multilevel classification systems of population types and environmental states that maximize population growth. Two empirical cases are explored, one from the evolving economy and the other one from migrating birds.
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Processing Uncertain RFID Data in Traceability Supply Chains
Directory of Open Access Journals (Sweden)
Dong Xie
2014-01-01
Full Text Available Radio Frequency Identification (RFID is widely used to track and trace objects in traceability supply chains. However, massive uncertain data produced by RFID readers are not effective and efficient to be used in RFID application systems. Following the analysis of key features of RFID objects, this paper proposes a new framework for effectively and efficiently processing uncertain RFID data, and supporting a variety of queries for tracking and tracing RFID objects. We adjust different smoothing windows according to different rates of uncertain data, employ different strategies to process uncertain readings, and distinguish ghost, missing, and incomplete data according to their apparent positions. We propose a comprehensive data model which is suitable for different application scenarios. In addition, a path coding scheme is proposed to significantly compress massive data by aggregating the path sequence, the position, and the time intervals. The scheme is suitable for cyclic or long paths. Moreover, we further propose a processing algorithm for group and independent objects. Experimental evaluations show that our approach is effective and efficient in terms of the compression and traceability queries.
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Processing uncertain RFID data in traceability supply chains.
Xie, Dong; Xiao, Jie; Guo, Guangjun; Jiang, Tong
2014-01-01
Radio Frequency Identification (RFID) is widely used to track and trace objects in traceability supply chains. However, massive uncertain data produced by RFID readers are not effective and efficient to be used in RFID application systems. Following the analysis of key features of RFID objects, this paper proposes a new framework for effectively and efficiently processing uncertain RFID data, and supporting a variety of queries for tracking and tracing RFID objects. We adjust different smoothing windows according to different rates of uncertain data, employ different strategies to process uncertain readings, and distinguish ghost, missing, and incomplete data according to their apparent positions. We propose a comprehensive data model which is suitable for different application scenarios. In addition, a path coding scheme is proposed to significantly compress massive data by aggregating the path sequence, the position, and the time intervals. The scheme is suitable for cyclic or long paths. Moreover, we further propose a processing algorithm for group and independent objects. Experimental evaluations show that our approach is effective and efficient in terms of the compression and traceability queries.
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Rigid multibody system dynamics with uncertain rigid bodies
Energy Technology Data Exchange (ETDEWEB)
Batou, A., E-mail: anas.batou@univ-paris-est.fr; Soize, C., E-mail: christian.soize@univ-paris-est.fr [Universite Paris-Est, Laboratoire Modelisation et Simulation Multi Echelle, MSME UMR 8208 CNRS (France)
2012-03-15
This paper is devoted to the construction of a probabilistic model of uncertain rigid bodies for multibody system dynamics. We first construct a stochastic model of an uncertain rigid body by replacing the mass, the center of mass, and the tensor of inertia by random variables. The prior probability distributions of the stochastic model are constructed using the maximum entropy principle under the constraints defined by the available information. The generators of independent realizations corresponding to the prior probability distribution of these random quantities are further developed. Then several uncertain rigid bodies can be linked to each other in order to calculate the random response of a multibody dynamical system. An application is proposed to illustrate the theoretical development.
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Quantifying Anthropogenic Dust Emissions
Webb, Nicholas P.; Pierre, Caroline
2018-02-01
Anthropogenic land use and land cover change, including local environmental disturbances, moderate rates of wind-driven soil erosion and dust emission. These human-dust cycle interactions impact ecosystems and agricultural production, air quality, human health, biogeochemical cycles, and climate. While the impacts of land use activities and land management on aeolian processes can be profound, the interactions are often complex and assessments of anthropogenic dust loads at all scales remain highly uncertain. Here, we critically review the drivers of anthropogenic dust emission and current evaluation approaches. We then identify and describe opportunities to: (1) develop new conceptual frameworks and interdisciplinary approaches that draw on ecological state-and-transition models to improve the accuracy and relevance of assessments of anthropogenic dust emissions; (2) improve model fidelity and capacity for change detection to quantify anthropogenic impacts on aeolian processes; and (3) enhance field research and monitoring networks to support dust model applications to evaluate the impacts of disturbance processes on local to global-scale wind erosion and dust emissions.
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Active fault diagnosis in closed-loop uncertain systems
DEFF Research Database (Denmark)
Niemann, Hans Henrik
2006-01-01
Fault diagnosis of parametric faults in closed-loop uncertain systems by using an auxiliary input vector is considered in this paper, i.e. active fault diagnosis (AFD). The active fault diagnosis is based directly on the socalled fault signature matrix, related to the YJBK (Youla, Jabr, Bongiorno...... and Kucera) parameterization. Conditions are given for exact detection and isolation of parametric faults in closed-loop uncertain systems....
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Cluster synchronization transmission of different external signals in discrete uncertain network
Li, Chengren; Lü, Ling; Chen, Liansong; Hong, Yixuan; Zhou, Shuang; Yang, Yiming
2018-07-01
We research cluster synchronization transmissions of different external signals in discrete uncertain network. Based on the Lyapunov theorem, the network controller and the identification law of uncertain adjustment parameter are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain adjustment parameter. In our technical scheme, the network nodes in each cluster and the transmitted external signal can be different, and they allow the presence of uncertain parameters in the network. Especially, we are free to choose the clustering topologies, the cluster number and the node number in each cluster.
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Early emergence of anthropogenically forced heat waves in the western United States and Great Lakes
Lopez, Hosmay; West, Robert; Dong, Shenfu; Goni, Gustavo; Kirtman, Ben; Lee, Sang-Ki; Atlas, Robert
2018-05-01
Climate projections for the twenty-first century suggest an increase in the occurrence of heat waves. However, the time at which externally forced signals of anthropogenic climate change (ACC) emerge against background natural variability (time of emergence (ToE)) has been challenging to quantify, which makes future heat-wave projections uncertain. Here we combine observations and model simulations under present and future forcing to assess how internal variability and ACC modulate US heat waves. We show that ACC dominates heat-wave occurrence over the western United States and Great Lakes regions, with ToE that occurred as early as the 2020s and 2030s, respectively. In contrast, internal variability governs heat waves in the northern and southern Great Plains, where ToE occurs in the 2050s and 2070s; this later ToE is believed to be a result of a projected increase in circulation variability, namely the Great Plain low-level jet. Thus, greater mitigation and adaptation efforts are needed in the Great Lakes and western United States regions.
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Institute of Scientific and Technical Information of China (English)
LI Xin; MA Xiaodong
2017-01-01
Land use structure optimization (LUSO) is an important issue for land use planning.In order for land use planning to have reasonable flexibility,uncertain optimization should be applied for LUSO.In this paper,the researcher first expounded the uncertainties of LUSO.Based on this,an interval programming model was developed,of which interval variables were to hold land use uncertainties.To solve the model,a heuristics based on Genetic Algorithm was designed according to Pareto Optimum principle with a confidence interval under given significance level to represent LUSO result.Proposed method was applied to a real case of Yangzhou,an eastern city in China.The following conclusions were reached.1) Different forms of uncertainties ranged from certainty to indeterminacy lay in the five steps of LUSO,indicating necessary need of comprehensive approach to quantify them.2) With regards to trade-offs of conflicted objectives and preferences to uncertainties,our proposed model displayed good ability of making planning decision process transparent,therefore providing an effective tool for flexible land use planning compiling.3) Under uncertain conditions,land use planning effectiveness can be primarily enhanced by flexible management with reserved space to percept and hold uncertainties in advance.
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MAGDM linear-programming models with distinct uncertain preference structures.
Xu, Zeshui S; Chen, Jian
2008-10-01
Group decision making with preference information on alternatives is an interesting and important research topic which has been receiving more and more attention in recent years. The purpose of this paper is to investigate multiple-attribute group decision-making (MAGDM) problems with distinct uncertain preference structures. We develop some linear-programming models for dealing with the MAGDM problems, where the information about attribute weights is incomplete, and the decision makers have their preferences on alternatives. The provided preference information can be represented in the following three distinct uncertain preference structures: 1) interval utility values; 2) interval fuzzy preference relations; and 3) interval multiplicative preference relations. We first establish some linear-programming models based on decision matrix and each of the distinct uncertain preference structures and, then, develop some linear-programming models to integrate all three structures of subjective uncertain preference information provided by the decision makers and the objective information depicted in the decision matrix. Furthermore, we propose a simple and straightforward approach in ranking and selecting the given alternatives. It is worth pointing out that the developed models can also be used to deal with the situations where the three distinct uncertain preference structures are reduced to the traditional ones, i.e., utility values, fuzzy preference relations, and multiplicative preference relations. Finally, we use a practical example to illustrate in detail the calculation process of the developed approach.
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Emergency response network design for hazardous materials transportation with uncertain demand
Directory of Open Access Journals (Sweden)
Kamran Shahanaghi
2012-10-01
Full Text Available Transportation of hazardous materials play an essential role on keeping a friendly environment. Every day, a substantial amount of hazardous materials (hazmats, such as flammable liquids and poisonous gases, need to be transferred prior to consumption or disposal. Such transportation may result in unsuitable events for people and environment. Emergency response network is designed for this reason where specialist responding teams resolve any issue as quickly as possible. This study proposes a new multi-objective model to locate emergency response centers for transporting the hazardous materials. Since many real-world applications are faced with uncertainty in input parameters, the proposed model of this paper also assumes that reference and demand to such centre is subject to uncertainty, where demand is fuzzy random. The resulted problem formulation is modelled as nonlinear non-convex mixed integer programming and we used NSGAII method to solve the resulted problem. The performance of the proposed model is examined with several examples using various probability distribution and they are compared with the performance of other existing method.
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Uncertain relational reasoning in the parietal cortex.
Ragni, Marco; Franzmeier, Imke; Maier, Simon; Knauff, Markus
2016-04-01
The psychology of reasoning is currently transitioning from the study of deductive inferences under certainty to inferences that have degrees of uncertainty in both their premises and conclusions; however, only a few studies have explored the cortical basis of uncertain reasoning. Using transcranial magnetic stimulation (TMS), we show that areas in the right superior parietal lobe (rSPL) are necessary for solving spatial relational reasoning problems under conditions of uncertainty. Twenty-four participants had to decide whether a single presented order of objects agreed with a given set of indeterminate premises that could be interpreted in more than one way. During the presentation of the order, 10-Hz TMS was applied over the rSPL or a sham control site. Right SPL TMS during the inference phase disrupted performance in uncertain relational reasoning. Moreover, we found differences in the error rates between preferred mental models, alternative models, and inconsistent models. Our results suggest that different mechanisms are involved when people reason spatially and evaluate different kinds of uncertain conclusions. Copyright © 2016 Elsevier Inc. All rights reserved.
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Uncertain multi-attribute decision making methods and applications
Xu, Zeshui
2015-01-01
This book introduces methods for uncertain multi-attribute decision making including uncertain multi-attribute group decision making and their applications to supply chain management, investment decision making, personnel assessment, redesigning products, maintenance services, military system efficiency evaluation. Multi-attribute decision making, also known as multi-objective decision making with finite alternatives, is an important component of modern decision science. The theory and methods of multi-attribute decision making have been extensively applied in engineering, economics, management and military contexts, such as venture capital project evaluation, facility location, bidding, development ranking of industrial sectors and so on. Over the last few decades, great attention has been paid to research on multi-attribute decision making in uncertain settings, due to the increasing complexity and uncertainty of supposedly objective aspects and the fuzziness of human thought. This book can be used as a ref...
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Nonlinear robust hierarchical control for nonlinear uncertain systems
Directory of Open Access Journals (Sweden)
Leonessa Alexander
1999-01-01
Full Text Available A nonlinear robust control-system design framework predicated on a hierarchical switching controller architecture parameterized over a set of moving nominal system equilibria is developed. Specifically, using equilibria-dependent Lyapunov functions, a hierarchical nonlinear robust control strategy is developed that robustly stabilizes a given nonlinear system over a prescribed range of system uncertainty by robustly stabilizing a collection of nonlinear controlled uncertain subsystems. The robust switching nonlinear controller architecture is designed based on a generalized (lower semicontinuous Lyapunov function obtained by minimizing a potential function over a given switching set induced by the parameterized nominal system equilibria. The proposed framework robustly stabilizes a compact positively invariant set of a given nonlinear uncertain dynamical system with structured parametric uncertainty. Finally, the efficacy of the proposed approach is demonstrated on a jet engine propulsion control problem with uncertain pressure-flow map data.
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Robust Optimization-Based Generation Self-Scheduling under Uncertain Price
Directory of Open Access Journals (Sweden)
Xiao Luo
2011-01-01
Full Text Available This paper considers generation self-scheduling in electricity markets under uncertain price. Based on the robust optimization (denoted as RO methodology, a new self-scheduling model, which has a complicated max-min optimization structure, is set up. By using optimal dual theory, the proposed model is reformulated to an ordinary quadratic and quadratic cone programming problems in the cases of box and ellipsoidal uncertainty, respectively. IEEE 30-bus system is used to test the new model. Some comparisons with other methods are done, and the sensitivity with respect to the uncertain set is analyzed. Comparing with the existed uncertain self-scheduling approaches, the new method has twofold characteristics. First, it does not need a prediction of distribution of random variables and just requires an estimated value and the uncertain set of power price. Second, the counterpart of RO corresponding to the self-scheduling is a simple quadratic or quadratic cone programming. This indicates that the reformulated problem can be solved by many ordinary optimization algorithms.
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Uncertain sightings and the extinction of the Ivory-billed Woodpecker.
Solow, Andrew; Smith, Woollcott; Burgman, Mark; Rout, Tracy; Wintle, Brendan; Roberts, David
2012-02-01
The extinction of a species can be inferred from a record of its sightings. Existing methods for doing so assume that all sightings in the record are valid. Often, however, there are sightings of uncertain validity. To date, uncertain sightings have been treated in an ad hoc way, either excluding them from the record or including them as if they were certain. We developed a Bayesian method that formally accounts for such uncertain sightings. The method assumes that valid and invalid sightings follow independent Poisson processes and use noninformative prior distributions for the rate of valid sightings and for a measure of the quality of uncertain sightings. We applied the method to a recently published record of sightings of the Ivory-billed Woodpecker (Campephilus principalis). This record covers the period 1897-2010 and contains 39 sightings classified as certain and 29 classified as uncertain. The Bayes factor in favor of extinction was 4.03, which constitutes substantial support for extinction. The posterior distribution of the time of extinction has 3 main modes in 1944, 1952, and 1988. The method can be applied to sighting records of other purportedly extinct species. ©2011 Society for Conservation Biology.
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Robust control synthesis for uncertain dynamical systems
Byun, Kuk-Whan; Wie, Bong; Sunkel, John
1989-01-01
This paper presents robust control synthesis techniques for uncertain dynamical systems subject to structured parameter perturbation. Both QFT (quantitative feedback theory) and H-infinity control synthesis techniques are investigated. Although most H-infinity-related control techniques are not concerned with the structured parameter perturbation, a new way of incorporating the parameter uncertainty in the robust H-infinity control design is presented. A generic model of uncertain dynamical systems is used to illustrate the design methodologies investigated in this paper. It is shown that, for a certain noncolocated structural control problem, use of both techniques results in nonminimum phase compensation.
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A FTA-based method for risk decision-making in emergency response
DEFF Research Database (Denmark)
Liu, Yang; Li, Hongyan
2014-01-01
Decision-making problems in emergency response are usually risky and uncertain due to the limited decision data and possible evolvement of emergency scenarios. This paper focuses on a risk decisionmaking problem in emergency response with several distinct characteristics including dynamic...... evolvement process of emergency, multiple scenarios, and impact of response actions on the emergency scenarios. A method based on Fault Tree Analysis (FTA) is proposed to solve the problem. By analyzing the evolvement process of emergency, the Fault Tree (FT) is constructed to describe the logical relations...
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Entity resolution for uncertain data
Ayat, N.; Akbarinia, R.; Afsarmanesh, H.; Valduriez, P.
2012-01-01
Entity resolution (ER), also known as duplicate detection or record matching, is the problem of identifying the tuples that represent the same real world entity. In this paper, we address the problem of ER for uncertain data, which we call ERUD. We propose two different approaches for the ERUD
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Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems
Directory of Open Access Journals (Sweden)
Xinbo Zhang
2014-01-01
Full Text Available A polymorphic uncertain linear programming (PULP model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.
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Passivity analysis and synthesis for uncertain time-delay systems
Directory of Open Access Journals (Sweden)
Magdi S. Mahmoud
2001-01-01
Full Text Available In this paper, we investigate the robust passivity analysis and synthesis problems for a class of uncertain time-delay systems. This class of systems arises in the modelling effort of studying water quality constituents in fresh stream. For the analysis problem, we derive a sufficient condition for which the uncertain time-delay system is robustly stable and strictly passive for all admissible uncertainties. The condition is given in terms of a linear matrix inequality. Both the delay-independent and delay-dependent cases are considered. For the synthesis problem, we propose an observer-based design method which guarantees that the closed-loop uncertain time-delay system is stable and strictly passive for all admissible uncertainties. Several examples are worked out to illustrate the developed theory.
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Fuzzy controller for an uncertain dynamical system
DEFF Research Database (Denmark)
Kulczycki, P.; Wisniewski, Rafal
2002-01-01
The present paper deals with the time-optimal control for mechanical systems with uncertain load. A fuzzy approach is used in the design of suboptimal feedback controllers, robust with respect to the load. Statistical kernel estimators are used for the specification of crucial parameters. The met......The present paper deals with the time-optimal control for mechanical systems with uncertain load. A fuzzy approach is used in the design of suboptimal feedback controllers, robust with respect to the load. Statistical kernel estimators are used for the specification of crucial parameters....... The methodology proposed in this work may be easily adopted to other modeling uncertainties of mechanical systems, e.g. motion resistance....
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Simplex sliding mode control for nonlinear uncertain systems via chaos optimization
International Nuclear Information System (INIS)
Lu, Zhao; Shieh, Leang-San; Chen, Guanrong; Coleman, Norman P.
2005-01-01
As an emerging effective approach to nonlinear robust control, simplex sliding mode control demonstrates some attractive features not possessed by the conventional sliding mode control method, from both theoretical and practical points of view. However, no systematic approach is currently available for computing the simplex control vectors in nonlinear sliding mode control. In this paper, chaos-based optimization is exploited so as to develop a systematic approach to seeking the simplex control vectors; particularly, the flexibility of simplex control is enhanced by making the simplex control vectors dependent on the Euclidean norm of the sliding vector rather than being constant, which result in both reduction of the chattering and speedup of the convergence. Computer simulation on a nonlinear uncertain system is given to illustrate the effectiveness of the proposed control method
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Synchronization transmission of laser pattern signal within uncertain switched network
Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan
2017-06-01
We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.
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Landscape architectural research in Canada: developing a certain future in uncertain times.
Directory of Open Access Journals (Sweden)
Douglas Paterson
1995-03-01
Full Text Available LANDSCAPE ARCHITECTURAL RESEARCH in Canada is defined by the uncertain and complex global issues of the times, the significant theoretical and methodological debates facing the world of research in general, and the increased academic pressures for research in a less well-funded and more constricting research environment. It is also affected by the political environment in which its few researchers are outnumbered by the larger disciplines and professions which seem to be getting bigger all the time, and by its own internal struggles between its disciplinary and professional roles. Landscape architectural research efforts in Canada are, as such, both vigorous and hesitant, aggressive yet underfunded, well focused yet somewhat uncertain in their ultimate intention. This paper begins with a brief examination of the present context of our research. It next looks at the basic problems that have and continue to plague design research. With these contextual issues established, the paper then recounts a brief history of the profession and its emerging educational-research base in Canada and gives an overview of current research efforts. It concludes by suggesting several important directions that are needed in Canadian landscape architectural research over' the next 10 years. It is hoped that this personal, historical account of research efforts, problems and opportunities in Canada will allow others in the Asia-Pacific region to recognise the similarities to their own situations.
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An artificial bee colony algorithm for uncertain portfolio selection.
Chen, Wei
2014-01-01
Portfolio selection is an important issue for researchers and practitioners. In this paper, under the assumption that security returns are given by experts' evaluations rather than historical data, we discuss the portfolio adjusting problem which takes transaction costs and diversification degree of portfolio into consideration. Uncertain variables are employed to describe the security returns. In the proposed mean-variance-entropy model, the uncertain mean value of the return is used to measure investment return, the uncertain variance of the return is used to measure investment risk, and the entropy is used to measure diversification degree of portfolio. In order to solve the proposed model, a modified artificial bee colony (ABC) algorithm is designed. Finally, a numerical example is given to illustrate the modelling idea and the effectiveness of the proposed algorithm.
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Robust lyapunov controller for uncertain systems
Laleg-Kirati, Taous-Meriem; Elmetennani, Shahrazed
2017-01-01
Various examples of systems and methods are provided for Lyapunov control for uncertain systems. In one example, a system includes a process plant and a robust Lyapunov controller configured to control an input of the process plant. The robust
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An Artificial Bee Colony Algorithm for Uncertain Portfolio Selection
Chen, Wei
2014-01-01
Portfolio selection is an important issue for researchers and practitioners. In this paper, under the assumption that security returns are given by experts’ evaluations rather than historical data, we discuss the portfolio adjusting problem which takes transaction costs and diversification degree of portfolio into consideration. Uncertain variables are employed to describe the security returns. In the proposed mean-variance-entropy model, the uncertain mean value of the return is ...
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Millennial Teachers and Multiculturalism: Considerations for Teaching in Uncertain Times
Hallman, Heidi L.
2017-01-01
Purpose: This paper aims to explore the intersection of generational traits of millennial teachers, multiculturalism and teaching in an era of Uncertain Times. Uncertain Times, as a framework for the paper, characterizes changing aspects of the current era in which we live, such as the rise of the internet and interconnectivity, globalization and…
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The role of uncertain self-esteem in self-handicapping.
Harris, R N; Snyder, C R
1986-08-01
In this article, the hypothesis that some individuals confronted with an intellectual evaluation use a lack of preparation as a "self-handicapping" strategy (Jones & Berglas, 1978) was studied. Sex and both level and certainty of self-esteem were examined in regard to the self-handicapping strategy of lack of effort. Subjects were 54 men and 54 women, certain and uncertain, high and low self-esteem college students, who believed that the experiment was designed to update local norms for a nonverbal test of intellectual ability. After subjects' level of state anxiety was assessed, they were instructed in the benefits of practicing for the evaluation. Subsequently, subjects' state anxiety and preparatory efforts (the primary dependent variables) were measured. Subjects' practice, self-protective attributions, and related affect supported a self-handicapping interpretation for uncertain males but not for uncertain females.
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Adaptive observer based synchronization of a class of uncertain chaotic systems
International Nuclear Information System (INIS)
Bowong, S.; Yamapi, R.
2005-05-01
This study addresses the adaptive synchronization of a class of uncertain chaotic systems in the drive-response framework. For a class of uncertain chaotic systems with unknown parameters and external disturbances, a robust adaptive observer based response system is constructed to synchronize the uncertain chaotic system. Lyapunov stability theory and Barbalat lemma ensure the global synchronization between the drive and response systems even if Lipschitz constants on function matrices and bounds on uncertainties are unknown. Numerical simulation of the Genesio-Tesi system verifies the effectiveness of the proposed method. (author)
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Quality Measures in Uncertain Data Management
de Keijzer, Ander; van Keulen, Maurice; Prade, H.; Subrahmanian, V.S.
2007-01-01
Many applications deal with data that is uncertain. Some examples are applications dealing with sensor information, data integration applications and healthcare applications. Instead of these applications having to deal with the uncertainty, it should be the responsibility of the DBMS to manage all
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Robust scheduling in an uncertain environment
Wilson, M.
2016-01-01
This thesis presents research on scheduling in an uncertain environment, which forms a part of the rolling stock life cycle logistics applied research and development program funded by Dutch railway industry companies. The focus therefore lies on scheduling of maintenance operations on rolling stock
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CMAC-based adaptive backstepping synchronization of uncertain chaotic systems
International Nuclear Information System (INIS)
Lin, C.-M.; Peng, Y.-F.; Lin, M.-H.
2009-01-01
This study proposes an adaptive backstepping control system for synchronizing uncertain chaotic system by using cerebellar model articulation controller (CMAC). CMAC is a nonlinear network with simple computation, good generalization capability and fast learning property. The proposed CMAC-based adaptive backstepping control (CABC) system uses backstepping method and adaptive cerebellar model articulation controller (ACMAC) for synchronizing uncertain chaotic system. Finally, simulation results for the Genesio system are presented to illustrate the effectiveness of the proposed control system.
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Enabling time-dependent uncertain eco-weights for road networks
DEFF Research Database (Denmark)
Hu, Jilin; Yang, Bin; Jensen, Christian S.
2017-01-01
travel costs. Based on the techniques above, different histogram aggregation methods are proposed to accurately estimate time-dependent GHG emissions for routes. Based on a 200-million GPS record data set collected from 150 vehicles in Denmark over two years, a comprehensive empirical study is conducted...... transportation. The foundation of eco-routing is a weighted-graph representation of a road network in which road segments, or edges, are associated with eco-weights that capture the GHG emissions caused by traversing the edges. Due to the dynamics of traffic, the eco-weights are best modeled as being time...... dependent and uncertain. We formalize the problem of assigning a time-dependent, uncertain eco-weight to each edge in a road network based on historical GPS records. In particular, a sequence of histograms is employed to describe the uncertain eco-weight of an edge at different time intervals. Compression...
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Airline Overbooking Problem with Uncertain No-Shows
Directory of Open Access Journals (Sweden)
Chunxiao Zhang
2014-01-01
Full Text Available This paper considers an airline overbooking problem of a new single-leg flight with discount fare. Due to the absence of historical data of no-shows for a new flight, and various uncertain human behaviors or unexpected events which causes that a few passengers cannot board their aircraft on time, we fail to obtain the probability distribution of no-shows. In this case, the airlines have to invite some domain experts to provide belief degree of no-shows to estimate its distribution. However, human beings often overestimate unlikely events, which makes the variance of belief degree much greater than that of the frequency. If we still regard the belief degree as a subjective probability, the derived results will exceed our expectations. In order to deal with this uncertainty, the number of no-shows of new flight is assumed to be an uncertain variable in this paper. Given the chance constraint of social reputation, an overbooking model with discount fares is developed to maximize the profit rate based on uncertain programming theory. Finally, the analytic expression of the optimal booking limit is obtained through a numerical example, and the results of sensitivity analysis indicate that the optimal booking limit is affected by flight capacity, discount, confidence level, and parameters of the uncertainty distribution significantly.
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Preparing for an Uncertain Forecast
Karolak, Eric
2011-01-01
Navigating the world of government relations and public policy can be a little like predicting the weather. One can't always be sure what's in store or how it will affect him/her down the road. But there are common patterns and a few basic steps that can help one best prepare for a change in the forecast. Though the forecast is uncertain, early…
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Possible world based consistency learning model for clustering and classifying uncertain data.
Liu, Han; Zhang, Xianchao; Zhang, Xiaotong
2018-06-01
Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good. In this paper, we propose a novel possible world based consistency learning model for uncertain data, which can be extended both for clustering and classifying uncertain data. This model utilizes the consistency principle to learn a consensus affinity matrix for uncertain data, which can make full use of the information across different possible worlds and then improve the clustering and classification performance. Meanwhile, this model imposes a new rank constraint on the Laplacian matrix of the consensus affinity matrix, thereby ensuring that the number of connected components in the consensus affinity matrix is exactly equal to the number of classes. This also means that the clustering and classification results can be directly obtained without any post-processing procedure. Furthermore, for the clustering and classification tasks, we respectively derive the efficient optimization methods to solve the proposed model. Experimental results on real benchmark datasets and real world uncertain datasets show that the proposed model outperforms the state-of-the-art uncertain data clustering and classification algorithms in effectiveness and performs competitively in efficiency. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Brouns, S.; van der Schuit, K.C.H.; Stassen, P.; Lambooij, S.L.E.; Dieleman, Jeanne P.; Vanderfeesten, I.T.P.; Haak, H.
2017-01-01
Background Emergency department (ED) crowding leads to prolonged emergency department length of stay (ED-LOS) and adverse patient outcomes. No uniform definition of ED crowding exists. Several scores have been developed to quantify ED crowding; the best known is the Emergency Department Work Index
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Uncertain Environmental Footprint of Current and Future Battery Electric Vehicles.
Cox, Brian; Mutel, Christopher L; Bauer, Christian; Mendoza Beltran, Angelica; van Vuuren, Detlef P
2018-04-17
The future environmental impacts of battery electric vehicles (EVs) are very important given their expected dominance in future transport systems. Previous studies have shown these impacts to be highly uncertain, though a detailed treatment of this uncertainty is still lacking. We help to fill this gap by using Monte Carlo and global sensitivity analysis to quantify parametric uncertainty and also consider two additional factors that have not yet been addressed in the field. First, we include changes to driving patterns due to the introduction of autonomous and connected vehicles. Second, we deeply integrate scenario results from the IMAGE integrated assessment model into our life cycle database to include the impacts of changes to the electricity sector on the environmental burdens of producing and recharging future EVs. Future EVs are expected to have 45-78% lower climate change impacts than current EVs. Electricity used for charging is the largest source of variability in results, though vehicle size, lifetime, driving patterns, and battery size also strongly contribute to variability. We also show that it is imperative to consider changes to the electricity sector when calculating upstream impacts of EVs, as without this, results could be overestimated by up to 75%.
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Representation and management of temporal and uncertain knowledge
International Nuclear Information System (INIS)
Chen, Ziqiang
1993-01-01
This thesis contributes to the investigation of uncertain temporal knowledge representation and management, especially for process verification and supervisor systems design. The evolution of process behaviour is time dependent and information describing this temporal evolution is uncertain/imprecise. In Artificial Intelligence, time and uncertainty have been, since long-time, considered as two of the most difficult research fields. Furthermore, these two fields, even different, may be present in an interactive way. We now try to deal with this special kind of uncertainty: temporal uncertainty. Integrating time and uncertainty brings out study issues of temporal information representation, events ordering and temporal reasoning under uncertainty. The investigation of these problems has been guided by preserving the intrinsic properties of time. The main contribution of this thesis can be summarised as follows: (1) unified representation of uncertainty and imprecision over temporal information; (2) formal structuring of time under uncertainty; (3) formalising fuzzy temporal reasoning system; (4) modelling temporal evolution of process, providing associated reasoning mechanism to verify the process evolution, modelling fuzzy temporal Petri nets; (5) design and implementation of SURTEL, a programming tool for dealing with uncertain temporal information and knowledge. (author) [fr
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Lee, Victor R.
2013-01-01
The Quantified Self (QS) movement is a growing global effort to use new mobile and wearable technologies to automatically obtain personal data about everyday activities. The social and material infrastructure associated with the Quantified Self (QS) movement provides a number of ideas that educational technologists should consider incorporating…
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Robust tracking control of uncertain Duffing-Holmes control systems
International Nuclear Information System (INIS)
Sun, Y.-J.
2009-01-01
In this paper, the notion of virtual stabilizability for dynamical systems is introduced and the virtual stabilizability of uncertain Duffing-Holmes control systems is investigated. Based on the time-domain approach with differential inequality, a tracking control is proposed such that the states of uncertain Duffing-Holmes control system track the desired trajectories with any pre-specified exponential decay rate and convergence radius. Moreover, we present an algorithm to find such a tracking control. Finally, a numerical example is provided to illustrate the use of the main results.
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Synchronization of uncertain time-varying network based on sliding mode control technique
Lü, Ling; Li, Chengren; Bai, Suyuan; Li, Gang; Rong, Tingting; Gao, Yan; Yan, Zhe
2017-09-01
We research synchronization of uncertain time-varying network based on sliding mode control technique. The sliding mode control technique is first modified so that it can be applied to network synchronization. Further, by choosing the appropriate sliding surface, the identification law of uncertain parameter, the adaptive law of the time-varying coupling matrix element and the control input of network are designed, it is sure that the uncertain time-varying network can synchronize effectively the synchronization target. At last, we perform some numerical simulations to demonstrate the effectiveness of the proposed results.
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Investment risks under uncertain climate change policy
International Nuclear Information System (INIS)
Blyth, William; Bradley, Richard; Yang, Ming; Bunn, Derek; Clarke, Charlie; Wilson, Tom
2007-01-01
This paper describes results from a model of decision-making under uncertainty using a real options methodology, developed by the International Energy Agency (IEA). The model represents investment decisions in power generation from the perspective of a private company. The investments are subject to uncertain future climate policy, which is treated as an external risk factor over which the company has no control. The aims of this paper are to (i) quantify these regulatory risks in order to improve understanding of how policy uncertainty may affect investment behaviour by private companies and (ii) illustrate the effectiveness of the real options approach as a policy analysis tool. The study analysed firms' investment options of coal- and gas-fired power plants and carbon capture and storage (CCS) technologies. Policy uncertainty is represented as an exogenous event that creates uncertainty in the carbon price. Our findings indicate that climate policy uncertainty creates a risk premium for power generation investments. In the case of gas- and coal-fired power generation, the risk premium would lead to an increase in electricity prices of 5-10% in order to stimulate investment. In the case of CCS, the risk premium would increase the carbon price required to stimulate investment by 16-37% compared to a situation of perfect certainty. The option to retrofit CCS acts as a hedge against high future carbon prices, and could accelerate investment in coal plant. This paper concludes that to minimise investment risks in low carbon technologies, policy-makers should aim to provide some long-term regulatory certainty. (author)
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Uncertain estimation of activity measurement in Nuclear Medicine
International Nuclear Information System (INIS)
Lopez Diaz, A.; Palau, S.P.A.; Cardenas, T.A.I.; Garcia, A.I.; Tulio, H.A.
2007-01-01
Full text: Accuracy and precision of dose is mandatory in radiopharmaceutical therapy procedures to guarantee the treatment success. The evaluation of uncertain in dose measurement in NM lab becomes a very important step, moreover if the operational parameters change between different equipment. In order to assure the traceability of activity measurements, and the quality assurance of dose administration, the behavior of two dose calibrator Capintec CRC-15R and PTW Curimentor 3, were studied. Accuracy, precision, linearity of activity response and reproducibility, and the activity uncertain determination with a second lab source were determined. Accuracy was evaluate using Tc 99m and I 131 Pstandard source (Secondary Standard Laboratory), for 10R vial (V) and 5 ml syringe (S) geometry, obtaining 1.3% (V-I 131 ), 1.4% (V -Tc 99m ), 0.8% (S -Tc 99m ) for CRC-15R and 2.3% (V-I 131 ), 1.1%(V-Tc 99m ), 1.0% (S-Tc 99m ) for Curimentor 3. Precision and Reproducibility was calculate using Cs 137 source. The reproducibility of CRC-15R and Curimentor 3 was less than 1.1% and 1.2 % respectively, during all evaluation time. The linearity of activity response was evaluate only for Tc 99m , and the results obtained were CRC 15R (672.97mCi 0.07 mCi, 1.3 % like mayor deviation) and Curimentor 3 (670.91mCi 0.08 mCi; 0.6 % like mayor deviation). To calculate the uncertain was use I 131 sources, the influences of calibration factor, linearity to activity, precision, reproducibility, background, half live time took into account. The typical combine uncertain for I 131 activity of was 2.24% for CRC-15R and 2.41% for Curimentor 3. The results were traceable between two equipment, no statistical significant differences were found for all tests. The equipment have a proper performance in the checked parameters, showing compliance with AIEA and National Authorities recommendation. Conclusion: The two equipmentcan be used in NM services with high level of traceability and confidence, with
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Functional brain networks involved in decision-making under certain and uncertain conditions
Energy Technology Data Exchange (ETDEWEB)
Farrar, Danielle C.; Moss, Mark B.; Killiany, Ronald J. [Boston University School of Medicine, Department of Anatomy and Neurobiology, Boston, MA (United States); Mian, Asim Z. [Boston University School of Medicine, Department of Radiology, Boston, MA (United States); Budson, Andrew E. [VA Boston Healthcare System, Boston, MA (United States)
2018-01-15
The aim of this study was to describe imaging markers of decision-making under uncertain conditions in normal individuals, in order to provide baseline activity to compare to impaired decision-making in pathological states. In this cross-sectional study, 19 healthy subjects ages 18-35 completed a novel decision-making card-matching task using a Phillips T3 Scanner and a 32-channel head coil. Functional data were collected in six functional runs. In one condition of the task, the participant was certain of the rule to apply to match the cards; in the other condition, the participant was uncertain. We performed cluster-based comparison of the two conditions using FSL fMRI Expert Analysis Tool and network-based analysis using MATLAB. The uncertain > certain comparison yielded three clusters - a midline cluster that extended through the midbrain, the thalamus, bilateral prefrontal cortex, the striatum, and bilateral parietal/occipital clusters. The certain > uncertain comparison yielded bilateral clusters in the insula, parietal and temporal lobe, as well as a medial frontal cluster. A larger, more connected functional network was found in the uncertain condition. The involvement of the insula, parietal cortex, temporal cortex, ventromedial prefrontal cortex, and orbitofrontal cortex of the certain condition reinforces the notion that certainty is inherently rewarding. For the uncertain condition, the involvement of the prefrontal cortex, parietal cortex, striatum, thalamus, amygdala, and hippocampal involvement was expected, as these are areas involved in resolving uncertainty and rule updating. The involvement of occipital cortical involvement and midbrain involvement may be attributed to increased visual attention and increased motor control. (orig.)
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Functional brain networks involved in decision-making under certain and uncertain conditions
International Nuclear Information System (INIS)
Farrar, Danielle C.; Moss, Mark B.; Killiany, Ronald J.; Mian, Asim Z.; Budson, Andrew E.
2018-01-01
The aim of this study was to describe imaging markers of decision-making under uncertain conditions in normal individuals, in order to provide baseline activity to compare to impaired decision-making in pathological states. In this cross-sectional study, 19 healthy subjects ages 18-35 completed a novel decision-making card-matching task using a Phillips T3 Scanner and a 32-channel head coil. Functional data were collected in six functional runs. In one condition of the task, the participant was certain of the rule to apply to match the cards; in the other condition, the participant was uncertain. We performed cluster-based comparison of the two conditions using FSL fMRI Expert Analysis Tool and network-based analysis using MATLAB. The uncertain > certain comparison yielded three clusters - a midline cluster that extended through the midbrain, the thalamus, bilateral prefrontal cortex, the striatum, and bilateral parietal/occipital clusters. The certain > uncertain comparison yielded bilateral clusters in the insula, parietal and temporal lobe, as well as a medial frontal cluster. A larger, more connected functional network was found in the uncertain condition. The involvement of the insula, parietal cortex, temporal cortex, ventromedial prefrontal cortex, and orbitofrontal cortex of the certain condition reinforces the notion that certainty is inherently rewarding. For the uncertain condition, the involvement of the prefrontal cortex, parietal cortex, striatum, thalamus, amygdala, and hippocampal involvement was expected, as these are areas involved in resolving uncertainty and rule updating. The involvement of occipital cortical involvement and midbrain involvement may be attributed to increased visual attention and increased motor control. (orig.)
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Engagement and Uncertainty: Emerging Technologies Challenge the Work of Engagement
Eaton, Weston; Wright, Wynne; Whyte, Kyle; Gasteyer, Stephen P.; Gehrke, Pat J.
2014-01-01
Universities' increasing applications of science and technology to address a wide array of societal problems may serve to thwart democratic engagement strategies. For emerging technologies, such challenges are particularly salient, as knowledge is incomplete and application and impact are uncertain or contested. Insights from science and…
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Robust output feedback H-infinity control and filtering for uncertain linear systems
Chang, Xiao-Heng
2014-01-01
"Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique. Though primarily intended for graduate students in control and filtering, the book can also serve as a valuable reference work for researchers wishing to explore the area of robust H-infinity control and filtering of uncertain systems. Dr. Xiao-Heng Chang is a Professor at the College of Engineering, Bohai University, China.
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Update on uncertain etiology of chronic kidney disease in Sri Lanka's north-central dry zone.
Wanigasuriya, Kamani
2014-04-01
This manuscript updates a review previously published in a local journal in 2012, about a new form of chronic kidney disease that has emerged over the past two decades in the north-central dry zone of Sri Lanka, where the underlying causes remain undetermined. Disease burden is higher in this area, particularly North Central Province, and affects a rural and disadvantaged population involved in rice-paddy farming. Over the last decade several studies have been carried out to estimate prevalence and identify determinants of this chronic kidney disease of uncertain etiology. Summarize the available evidence on prevalence, clinical profile and risk factors of chronic kidney disease of uncertain etiology in the north-central region of Sri Lanka. PubMed search located 16 manuscripts published in peer-reviewed journals. Three peer-reviewed abstracts of presentations at national scientific conferences were also included in the review. Disease prevalence was 5.1%-16.9% with more severe disease seen in men than in women. Patients with mild to moderate stages of disease were asymptomatic or had nonspecific symptoms; urinary sediments were bland; 24-hour urine protein excretion was urine, and mycotoxins detected in foods were below maximum statutory limits. Calcium-bicarbonate-type water with high levels of fluoride was predominant in endemic regions. Significantly high levels of cadmium in urine of cases compared to controls, as well as the disease's dose-related response to these levels, has drawn attention to this element as a possible contributing factor. Familial clustering of patients is suggestive of a polygenic inheritance pattern comparable to that associated with diseases of multifactorial etiology. Available data suggest that chronic kidney disease of uncertain etiology is an environmentally acquired disease, but to date no definitive causal factor has been identified. Geographic distribution and research findings suggest a multifactorial etiology.
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International Nuclear Information System (INIS)
Wu Xiangjun; Lu Hongtao
2011-01-01
Highlights: → Adaptive generalized function projective lag synchronization (AGFPLS) is proposed. → Two uncertain chaos systems are lag synchronized up to a scaling function matrix. → The synchronization speed is sensitively influenced by the control gains. → The AGFPLS scheme is robust against noise perturbation. - Abstract: In this paper, a novel projective synchronization scheme called adaptive generalized function projective lag synchronization (AGFPLS) is proposed. In the AGFPLS method, the states of two different chaotic systems with fully uncertain parameters are asymptotically lag synchronized up to a desired scaling function matrix. By means of the Lyapunov stability theory, an adaptive controller with corresponding parameter update rule is designed for achieving AGFPLS between two diverse chaotic systems and estimating the unknown parameters. This technique is employed to realize AGFPLS between uncertain Lue chaotic system and uncertain Liu chaotic system, and between Chen hyperchaotic system and Lorenz hyperchaotic system with fully uncertain parameters, respectively. Furthermore, AGFPLS between two different uncertain chaotic systems can still be achieved effectively with the existence of noise perturbation. The corresponding numerical simulations are performed to demonstrate the validity and robustness of the presented synchronization method.
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Management of Uncertain Data - towards unattended integration
de Keijzer, Ander
2008-01-01
In recent years, the need to support uncertain data has increased. Sensor applications, for example, are dealing with the inherent uncertainty about the readings of the sensors. Current database management systems are not equipped to deal with this uncertainty, other than as a user defined
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Chance constrained uncertain classification via robust optimization
Ben-Tal, A.; Bhadra, S.; Bhattacharayya, C.; Saketha Nat, J.
2011-01-01
This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out
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Licensing Uncertain Patents: Per-Unit Royalty vs Up-Front Fee
Encaoua , David; Lefouili , Yassine
2008-01-01
ED EPS; In this paper we examine the implications of uncertainty over patent validity on patentholders' licensing strategies. Two licensing mechanisms are examined: per-unit royalty and up-front fee.We provide conditions under which uncertain patents are licensed in order to avoid patent litigation. It is shown that while it is possible for the patentholder to reap som e "extra profit" by selling an uncertain patent under the pure per-unit royalty regime, the opportunity to do so does not exi...
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Synchronization of uncertain chaotic systems using a single transmission channel
International Nuclear Information System (INIS)
Feng Yong; Yu Xinghuo; Sun Lixia
2008-01-01
This paper proposes a robust sliding mode observer for synchronization of uncertain chaotic systems with multi-nonlinearities. A new control strategy is proposed for the construction of the robust sliding mode observer, which can avoid the strict conditions in the design process of Walcott-Zak observer. A new method of multi-dimensional signal transmission via single transmission channel is proposed and applied to chaos synchronization of uncertain chaotic systems with multi-nonlinearities. The simulation results are presented to validate the method
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Constructor:synthesizing information about uncertain variables.
Energy Technology Data Exchange (ETDEWEB)
Tucker, W. Troy (Applied Biomathematics, Setauket, NY); Ferson, Scott (Applied Biomathematics, Setauket, NY); Hajagos, Janos (Applied Biomathematics, Setauket, NY); Myers, David S. (Applied Biomathematics, Setauket, NY)
2005-09-01
Constructor is software for the Microsoft Windows microcomputer environment that facilitates the collation of empirical information and expert judgment for the specification of probability distributions, probability boxes, random sets or Dempster-Shafer structures from data, qualitative shape information, constraints on moments, order statistics, densities, and coverage probabilities about uncertain unidimensional quantities. These quantities may be real-valued, integer-valued or logical values.
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International Nuclear Information System (INIS)
Chakraverty, S.; Nayak, S.
2013-01-01
Highlights: • Uncertain neutron diffusion equation of bare square homogeneous reactor is studied. • Proposed interval arithmetic is extended for fuzzy numbers. • The developed fuzzy arithmetic is used to handle uncertain parameters. • Governing differential equation is modelled by modified fuzzy finite element method. • Fuzzy critical eigenvalues and effective multiplication factors are investigated. - Abstract: The scattering of neutron collision inside a reactor depends upon geometry of the reactor, diffusion coefficient and absorption coefficient etc. In general these parameters are not crisp and hence we get uncertain neutron diffusion equation. In this paper we have investigated the above equation for a bare square homogeneous reactor. Here the uncertain governing differential equation is modelled by a modified fuzzy finite element method. Using modified fuzzy finite element method, obtained eigenvalues and effective multiplication factors are studied. Corresponding results are compared with the classical finite element method in special cases and various uncertain results have been discussed
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Uncertain climate policy and the green paradox
Smulders, Sjak A.; Tsur, Y.; Zemel, A.; Moser, E.; Semmler, W.; Tragler, G.; Veliov, V.
2014-01-01
Unintended consequences of announcing a climate policy well in advance of its implementation have been studied in a variety of situations. We show that a phenomenon akin to the so-called “Green-Paradox” holds also when the policy implementation date is uncertain. Governments are compelled, by
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Sensitivity in risk analyses with uncertain numbers.
Energy Technology Data Exchange (ETDEWEB)
Tucker, W. Troy; Ferson, Scott
2006-06-01
Sensitivity analysis is a study of how changes in the inputs to a model influence the results of the model. Many techniques have recently been proposed for use when the model is probabilistic. This report considers the related problem of sensitivity analysis when the model includes uncertain numbers that can involve both aleatory and epistemic uncertainty and the method of calculation is Dempster-Shafer evidence theory or probability bounds analysis. Some traditional methods for sensitivity analysis generalize directly for use with uncertain numbers, but, in some respects, sensitivity analysis for these analyses differs from traditional deterministic or probabilistic sensitivity analyses. A case study of a dike reliability assessment illustrates several methods of sensitivity analysis, including traditional probabilistic assessment, local derivatives, and a ''pinching'' strategy that hypothetically reduces the epistemic uncertainty or aleatory uncertainty, or both, in an input variable to estimate the reduction of uncertainty in the outputs. The prospects for applying the methods to black box models are also considered.
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Modelling of risk events with uncertain likelihoods and impacts in large infrastructure projects
DEFF Research Database (Denmark)
Schjær-Jacobsen, Hans
2010-01-01
to prevent future budget overruns. One of the central ideas is to introduce improved risk management processes and the present paper addresses this particular issue. A relevant cost function in terms of unit prices and quantities is developed and an event impact matrix with uncertain impacts from independent......This paper presents contributions to the mathematical core of risk and uncertainty management in compliance with the principles of New Budgeting laid out in 2008 by the Danish Ministry of Transport to be used in large infrastructure projects. Basically, the new principles are proposed in order...... uncertain risk events is used to calculate the total uncertain risk budget. Cost impacts from the individual risk events on the individual project activities are kept precisely track of in order to comply with the requirements of New Budgeting. Additionally, uncertain likelihoods for the occurrence of risk...
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When, not if: the inescapability of an uncertain climate future.
Ballard, Timothy; Lewandowsky, Stephan
2015-11-28
Climate change projections necessarily involve uncertainty. Analysis of the physics and mathematics of the climate system reveals that greater uncertainty about future temperature increases is nearly always associated with greater expected damages from climate change. In contrast to those normative constraints, uncertainty is frequently cited in public discourse as a reason to delay mitigative action. This failure to understand the actual implications of uncertainty may incur notable future costs. It is therefore important to communicate uncertainty in a way that improves people's understanding of climate change risks. We examined whether responses to projections were influenced by whether the projection emphasized uncertainty in the outcome or in its time of arrival. We presented participants with statements and graphs indicating projected increases in temperature, sea levels, ocean acidification and a decrease in arctic sea ice. In the uncertain-outcome condition, statements reported the upper and lower confidence bounds of the projected outcome at a fixed time point. In the uncertain time-of-arrival condition, statements reported the upper and lower confidence bounds of the projected time of arrival for a fixed outcome. Results suggested that people perceived the threat as more serious and were more likely to encourage mitigative action in the time-uncertain condition than in the outcome-uncertain condition. This finding has implications for effectively communicating the climate change risks to policy-makers and the general public. © 2015 The Author(s).
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International Nuclear Information System (INIS)
Xu Yuhua; Zhou Wuneng; Fang Jian'an; Lu Hongqian
2009-01-01
This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.
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Energy Technology Data Exchange (ETDEWEB)
Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teacher' s College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Lu Hongqian [Shandong Institute of Light Industry, Shandong Jinan 250353 (China)
2009-12-28
This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.
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Altered brain activation and connectivity during anticipation of uncertain threat in trait anxiety.
Geng, Haiyang; Wang, Yi; Gu, Ruolei; Luo, Yue-Jia; Xu, Pengfei; Huang, Yuxia; Li, Xuebing
2018-06-08
In the research field of anxiety, previous studies generally focus on emotional responses following threat. A recent model of anxiety proposes that altered anticipation prior to uncertain threat is related with the development of anxiety. Behavioral findings have built the relationship between anxiety and distinct anticipatory processes including attention, estimation of threat, and emotional responses. However, few studies have characterized the brain organization underlying anticipation of uncertain threat and its role in anxiety. In the present study, we used an emotional anticipation paradigm with functional magnetic resonance imaging (fMRI) to examine the aforementioned topics by employing brain activation and general psychophysiological interactions (gPPI) analysis. In the activation analysis, we found that high trait anxious individuals showed significantly increased activation in the thalamus, middle temporal gyrus (MTG), and dorsomedial prefrontal cortex (dmPFC), as well as decreased activation in the precuneus, during anticipation of uncertain threat compared to the certain condition. In the gPPI analysis, the key regions including the amygdala, dmPFC, and precuneus showed altered connections with distributed brain areas including the ventromedial prefrontal cortex (vmPFC), dorsolateral prefrontal cortex (dlPFC), inferior parietal sulcus (IPS), insula, para-hippocampus gyrus (PHA), thalamus, and MTG involved in anticipation of uncertain threat in anxious individuals. Taken together, our findings indicate that during the anticipation of uncertain threat, anxious individuals showed altered activations and functional connectivity in widely distributed brain areas, which may be critical for abnormal perception, estimation, and emotion reactions during the anticipation of uncertain threat. © 2018 Wiley Periodicals, Inc.
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The re-emergence of tuberculosis: what have we learnt from molecular epidemiology?
Borgdorff, M.W.; Soolingen, D. van
2013-01-01
Tuberculosis (TB) has re-emerged over the past two decades: in industrialized countries in association with immigration, and in Africa owing to the human immunodeficiency virus epidemic. Drug-resistant TB is a major threat worldwide. The variable and uncertain impact of TB control necessitates not
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Probabilistic logic networks a comprehensive framework for uncertain inference
Goertzel, Ben; Goertzel, Izabela Freire; Heljakka, Ari
2008-01-01
This comprehensive book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. A broad scope of reasoning types are considered.
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Uncertain Portfolio Selection with Background Risk and Liquidity Constraint
Directory of Open Access Journals (Sweden)
Jia Zhai
2017-01-01
Full Text Available This paper discusses an uncertain portfolio selection problem with consideration of background risk and asset liquidity. In addition, the transaction costs are also considered. The security returns, background asset return, and asset liquidity are estimated by experienced experts instead of historical data. Regarding them as uncertain variables, a mean-risk model with background risk, liquidity, and transaction costs is proposed for portfolio selection and the crisp forms of the model are provided when security returns obey different uncertainty distributions. Moreover, for better understanding of the impact of background risk and liquidity on portfolio selection, some important theorems are proved. Finally, numerical experiments are presented to illustrate the modeling idea.
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Emergency Managers Confront Climate Change
Directory of Open Access Journals (Sweden)
John R. Labadie
2011-08-01
Full Text Available Emergency managers will have to deal with the impending, uncertain, and possibly extreme effects of climate change. Yet, many emergency managers are not aware of the full range of possible effects, and they are unsure of their place in the effort to plan for, adapt to, and cope with those effects. This may partly reflect emergency mangers’ reluctance to get caught up in the rancorous—and politically-charged—debate about climate change, but it mostly is due to the worldview shared by most emergency managers. We focus on: extreme events; acute vs. chronic hazards (floods vs. droughts; a shorter event horizon (5 years vs. 75–100 years; and a shorter planning and operational cycle. This paper explores the important intersection of emergency management, environmental management, and climate change mitigation and adaptation. It examines the different definitions of terms common to all three fields, the overlapping strategies used in all three fields, and the best means of collaboration and mutual re-enforcement among the three to confront and solve the many possible futures that we may face in the climate change world.
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Chaos synchronization of uncertain Genesio-Tesi chaotic systems with deadzone nonlinearity
International Nuclear Information System (INIS)
Sun, Y.-J.
2009-01-01
In this Letter, the concept of practical synchronization is introduced and the chaos synchronization of uncertain Genesio-Tesi chaotic systems with deadzone nonlinearity is investigated. Based on the time-domain approach, a tracking control is proposed to realize chaos synchronization for the uncertain Genesio-Tesi chaotic systems with deadzone nonlinearity. Moreover, the guaranteed exponential convergence rate and convergence radius can be pre-specified. Finally, a numerical example is provided to illustrate the feasibility and effectiveness of the obtained result.
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Function Projective Synchronization in Discrete-Time Chaotic System with Uncertain Parameters
International Nuclear Information System (INIS)
Chen Yong; Li Xin
2009-01-01
The function projective synchronization of discrete-time chaotic systems is presented. Based on backstepping design with three controllers, a systematic, concrete and automatic scheme is developed to investigate function projective synchronization (FPS) of discrete-time chaotic systems with uncertain parameters. With the aid of symbolic-numeric computation, we use the proposed scheme to illustrate FPS between two identical 3D Henon-like maps with uncertain parameters. Numeric simulations are used to verify the effectiveness of our scheme. (general)
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Robust Stabilization of Nonlinear Systems with Uncertain Varying Control Coefficient
Directory of Open Access Journals (Sweden)
Zaiyue Yang
2014-01-01
Full Text Available This paper investigates the stabilization problem for a class of nonlinear systems, whose control coefficient is uncertain and varies continuously in value and sign. The study emphasizes the development of a robust control that consists of a modified Nussbaum function to tackle the uncertain varying control coefficient. By such a method, the finite-time escape phenomenon has been prevented when the control coefficient is crossing zero and varying its sign. The proposed control guarantees the asymptotic stabilization of the system and boundedness of all closed-loop signals. The control performance is illustrated by a numerical simulation.
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Frequent Symptom Sets Identification from Uncertain Medical Data in Differentially Private Way
Directory of Open Access Journals (Sweden)
Zhe Ding
2017-01-01
Full Text Available Data mining techniques are applied to identify hidden patterns in large amounts of patient data. These patterns can assist physicians in making more accurate diagnosis. For different physical conditions of patients, the same physiological index corresponds to a different symptom association probability for each patient. Data mining technologies based on certain data cannot be directly applied to these patients’ data. Patient data are sensitive data. An adversary with sufficient background information can make use of the patterns mined from uncertain medical data to obtain the sensitive information of patients. In this paper, a new algorithm is presented to determine the top K most frequent itemsets from uncertain medical data and to protect data privacy. Based on traditional algorithms for mining frequent itemsets from uncertain data, our algorithm applies sparse vector algorithm and the Laplace mechanism to ensure differential privacy for the top K most frequent itemsets for uncertain medical data and the expected supports of these frequent itemsets. We prove that our algorithm can guarantee differential privacy in theory. Moreover, we carry out experiments with four real-world scenario datasets and two synthetic datasets. The experimental results demonstrate the performance of our algorithm.
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A model for the inverse 1-median problem on trees under uncertain costs
Directory of Open Access Journals (Sweden)
Kien Trung Nguyen
2016-01-01
Full Text Available We consider the problem of justifying vertex weights of a tree under uncertain costs so that a prespecified vertex become optimal and the total cost should be optimal in the uncertainty scenario. We propose a model which delivers the information about the optimal cost which respect to each confidence level \\(\\alpha \\in [0,1]\\. To obtain this goal, we first define an uncertain variable with respect to the minimum cost in each confidence level. If all costs are independently linear distributed, we present the inverse distribution function of this uncertain variable in \\(O(n^{2}\\log n\\ time, where \\(n\\ is the number of vertices in the tree.
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Quantifying Burnout among Emergency Medicine Professionals.
Wilson, William; Raj, Jeffrey Pradeep; Narayan, Girish; Ghiya, Murtuza; Murty, Shakuntala; Joseph, Bobby
2017-01-01
Burnout is a syndrome explained as serious emotional depletion with poor adaptation at work due to prolonged occupational stress. It has three principal components namely emotional exhaustion(EE), depersonalization(DP) and diminished feelings of personal accomplishment(PA). Thus, we aimed at measuring the degree of burnout in doctors and nurses working in emergency medicine department (EMD) of 4 select tertiary care teaching hospitals in South India. A cross sectional survey was conducted among EMD professionals using a 30-item standardized pilot tested questionnaire as well as the Maslach burnout inventory. Univariate and Multivariate analyses were conducted using binary logistic regression models to identify predictors of burnout. Total number of professionals interviewed were 105 of which 71.5% were women and 51.4% were doctors. Majority (78.1%) belonged to the age group 20-30 years. Prevalence of moderate to severe burnout in the 3 principal components EE, DP and PA were 64.8%, 71.4% and 73.3% respectively. After multivariate analysis, the risk factors [adjusted odds ratio (95% confidence intervals) for DP included facing more criticism [3.57(1.25,10.19)], disturbed sleep [6.44(1.45,28.49)] and being short tempered [3.14(1.09,9.09)]. While there were no statistically significant risk factors for EE, being affected by mortality [2.35(1.12,3.94)] and fear of medication errors [3.61(1.26, 10.37)] appeared to be significant predictors of PA. Degree of burn out among doctors and nurses is moderately high in all of the three principal components and some of the predictors identified were criticism, disturbed sleep, short tempered nature, fear of committing errors and witnessing death in EMD.
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Robust Optimization for Household Load Scheduling with Uncertain Parameters
Directory of Open Access Journals (Sweden)
Jidong Wang
2018-04-01
Full Text Available Home energy management systems (HEMS face many challenges of uncertainty, which have a great impact on the scheduling of home appliances. To handle the uncertain parameters in the household load scheduling problem, this paper uses a robust optimization method to rebuild the household load scheduling model for home energy management. The model proposed in this paper can provide the complete robust schedules for customers while considering the disturbance of uncertain parameters. The complete robust schedules can not only guarantee the customers’ comfort constraints but also cooperatively schedule the electric devices for cost minimization and load shifting. Moreover, it is available for customers to obtain multiple schedules through setting different robust levels while considering the trade-off between the comfort and economy.
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Synchronization and parameter estimations of an uncertain Rikitake system
International Nuclear Information System (INIS)
Aguilar-Ibanez, Carlos; Martinez-Guerra, Rafael; Aguilar-Lopez, Ricardo; Mata-Machuca, Juan L.
2010-01-01
In this Letter we address the synchronization and parameter estimation of the uncertain Rikitake system, under the assumption the state is partially known. To this end we use the master/slave scheme in conjunction with the adaptive control technique. Our control approach consists of proposing a slave system which has to follow asymptotically the uncertain Rikitake system, refereed as the master system. The gains of the slave system are adjusted continually according to a convenient adaptation control law, until the measurable output errors converge to zero. The convergence analysis is carried out by using the Barbalat's Lemma. Under this context, uncertainty means that although the system structure is known, only a partial knowledge of the corresponding parameter values is available.
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Quantifying risk of overharvest when implementation is uncertain
Eriksen, Lasse Frost; Moa, Pål Fossland; Nilsen, Erlend Birkeland
2017-01-01
1. Sustainable harvest management implies an ability to control harvest rates. This is challenging in systems that have limited control of resources and resource users, which is often the case in small game harvest management. The difference between management strategies and actual harvest bag size (i.e. implementation uncertainty) may be substantial, but few studies have explored this. 2. We investigated how different management strategies and ecosystem variables affected realised harve...
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A New Bi-Directional Projection Model Based on Pythagorean Uncertain Linguistic Variable
Huidong Wang; Shifan He; Xiaohong Pan
2018-01-01
To solve the multi-attribute decision making (MADM) problems with Pythagorean uncertain linguistic variable, an extended bi-directional projection method is proposed. First, we utilize the linguistic scale function to convert uncertain linguistic variable and provide a new projection model, subsequently. Then, to depict the bi-directional projection method, the formative vectors of alternatives and ideal alternatives are defined. Furthermore, a comparative analysis with projection model is co...
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Energy pricing under uncertain supply
International Nuclear Information System (INIS)
Serra, P.J.
1997-01-01
This paper introduces a new pricing system - based on the Chilean tariff regulations - to deal with an uncertain energy supply. It consists of a basic rate for each unit actually consumed and a compensation that the utilities pay their customers for each unit of energy that they voluntarily reduce below their normal consumption during an energy shortage. Within the framework of a model that portrays the stylized facts of the Chilean electric system, and assumes risk-neutral agents, this paper shows the equivalency of the new pricing system with both contingent pricing and priority pricing. (Author)
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The Uncertain of Scientific Process
Directory of Open Access Journals (Sweden)
Jovina dÁvila Bordoni
2016-10-01
Full Text Available The study assesses the existence of certainty in the scientific process, it seeks the truth, however, faced with the unknown, causes uncertainties and doubts. We used the bibliographical research, in which it systematized the scientific literature on epistemology and knowledge related to the scientific process and the uncertainties that surround him. The scientific process, though continuously seeks the truth, will not attain perfection, because the researcher deals with the unknown. The science seeks constantly new knowledge and progress with the criticism of the mistakes, seeks the truth, however these are provisional. It is concluded that all scientific knowledge is uncertain.
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Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks.
Cox, Louis Anthony Tony
2015-10-01
Decision biases can distort cost-benefit evaluations of uncertain risks, leading to risk management policy decisions with predictably high retrospective regret. We argue that well-documented decision biases encourage learning aversion, or predictably suboptimal learning and premature decision making in the face of high uncertainty about the costs, risks, and benefits of proposed changes. Biases such as narrow framing, overconfidence, confirmation bias, optimism bias, ambiguity aversion, and hyperbolic discounting of the immediate costs and delayed benefits of learning, contribute to deficient individual and group learning, avoidance of information seeking, underestimation of the value of further information, and hence needlessly inaccurate risk-cost-benefit estimates and suboptimal risk management decisions. In practice, such biases can create predictable regret in selection of potential risk-reducing regulations. Low-regret learning strategies based on computational reinforcement learning models can potentially overcome some of these suboptimal decision processes by replacing aversion to uncertain probabilities with actions calculated to balance exploration (deliberate experimentation and uncertainty reduction) and exploitation (taking actions to maximize the sum of expected immediate reward, expected discounted future reward, and value of information). We discuss the proposed framework for understanding and overcoming learning aversion and for implementing low-regret learning strategies using regulation of air pollutants with uncertain health effects as an example. © 2015 Society for Risk Analysis.
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Quantifying Burnout among Emergency Medicine Professionals
Directory of Open Access Journals (Sweden)
William Wilson
2017-01-01
Full Text Available Background: Burnout is a syndrome explained as serious emotional depletion with poor adaptation at work due to prolonged occupational stress. It has three principal components namely emotional exhaustion(EE, depersonalization(DP and diminished feelings of personal accomplishment(PA. Thus, we aimed at measuring the degree of burnout in doctors and nurses working in emergency medicine department (EMD of 4 select tertiary care teaching hospitals in South India. Methods: A cross sectional survey was conducted among EMD professionals using a 30-item standardized pilot tested questionnaire as well as the Maslach burnout inventory. Univariate and Multivariate analyses were conducted using binary logistic regression models to identify predictors of burnout. Results: Total number of professionals interviewed were 105 of which 71.5% were women and 51.4% were doctors. Majority (78.1% belonged to the age group 20-30 years. Prevalence of moderate to severe burnout in the 3 principal components EE, DP and PA were 64.8%, 71.4% and 73.3% respectively. After multivariate analysis, the risk factors [adjusted odds ratio (95% confidence intervals for DP included facing more criticism [3.57(1.25,10.19], disturbed sleep [6.44(1.45,28.49] and being short tempered [3.14(1.09,9.09]. While there were no statistically significant risk factors for EE, being affected by mortality [2.35(1.12,3.94] and fear of medication errors [3.61(1.26, 10.37] appeared to be significant predictors of PA. Conclusion: Degree of burn out among doctors and nurses is moderately high in all of the three principal components and some of the predictors identified were criticism, disturbed sleep, short tempered nature, fear of committing errors and witnessing death in EMD.
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Emergency motorcycle: has it a place in a medical emergency system?
Soares-Oliveira, Miguel; Egipto, Paula; Costa, Isabel; Cunha-Ribeiro, Luis Manuel
2007-07-01
In an emergency medical service system, response time is an important factor in determining the prognosis of a victim. There are well-documented increases in response time in urban areas, mainly during rush hour. Because prehospital emergency care is required to be efficient and swift, alternative measures to achieve this goal should be addressed. We report our experience with a medical emergency motorcycle (MEM) and propose major criteria for dispatching it. This work presents a prospective analysis of the data relating to MEM calls from July 2004 to December 2005. The analyzed parameters were age, sex, reason for call, action, and need for subsequent transport. A comparison was made of the need to activate more means and, if so, whether the MEM was the first to arrive. There were 1972 calls. The average time of arrival at destination was 4.4 +/- 2.5 minutes. The main action consisted of administration of oxygen (n = 626), immobilization (n = 118), and control of hemorrhage (n = 101). In 63% of cases, MEM arrived before other emergency vehicles. In 355 cases (18%), there was no need for transport. The MEM can intervene in a wide variety of clinical situations and a quick response is guaranteed. Moreover, in specific situations, MEM safely and efficiently permits better management of emergency vehicles. We propose that it should be dispatched mainly in the following situations: true life-threatening cases and uncertain need for an ambulance.
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Nishijima, Daniel K; Dinh, Tu; May, Larissa; Yadav, Kabir; Gaddis, Gary M; Cone, David C
2014-01-01
Every year since 2000, Academic Emergency Medicine (AEM) has presented a one-day consensus conference to generate a research agenda for advancement of a scientific topic. One of the 12 annual issues of AEM is reserved for the proceedings of these conferences. The purpose of this study was to measure academic productivity of these conferences by evaluating subsequent federal research funding received by authors of conference manuscripts and calculating citation counts of conference papers. This was a cross-sectional study. In 2012, the NIH RePORTER system was searched to identify subsequent federal funding obtained by authors of the consensus conference issues from 2000 to 2010. Funded projects were coded as related or unrelated to conference topic. Citation counts for all conference manuscripts were quantified using Scopus and Google Scholar. Simple descriptive statistics were reported. Eight hundred fifty-two individual authors contributed to 280 papers published in the 11 consensus conference issues. One hundred thirty-seven authors (16%) obtained funding for 318 projects. A median of 22 topic-related projects per conference (range 10-97) accounted for a median of $20,488,331 per conference (range $7,779,512 to $122,918,205). The average (± SD) number of citations per paper was 15.7 ± 20.5 in Scopus and 23.7 ± 32.6 in Google Scholar. The authors of consensus conference manuscripts obtained significant federal grant support for follow-up research related to conference themes. In addition, the manuscripts generated by these conferences were frequently cited. Conferences devoted to research agenda development appear to be an academically worthwhile endeavor.
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Inferring about the extinction of a species using certain and uncertain sightings.
Kodikara, Saritha; Demirhan, Haydar; Stone, Lewi
2018-04-07
The sighting record of threatened species is often used to infer the possibility of extinction. Most of these sightings have uncertain validity. Solow and Beet(2014) developed two models using a Bayesian approach which allowed for uncertainty in the sighting record by formally incorporating both certain and uncertain sightings, but in different ways. Interestingly, the two methods give completely different conclusions concerning the extinction of the Ivory-billed Woodpecker. We further examined these two methods to provide a mathematical explanation, and to explore in more depth, as to why the results differed from one another. It was found that the first model was more sensitive to the last uncertain sighting, while the second was more sensitive to the last certain sighting. The difficulties in choosing the appropriate model are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Episodes of care: is emergency medicine ready?
Wiler, Jennifer L; Beck, Dennis; Asplin, Brent R; Granovsky, Michael; Moorhead, John; Pilgrim, Randy; Schuur, Jeremiah D
2012-05-01
Optimizing resource use, eliminating waste, aligning provider incentives, reducing overall costs, and coordinating the delivery of quality care while improving outcomes have been major themes of health care reform initiatives. Recent legislation contains several provisions designed to move away from the current fee-for-service payment mechanism toward a model that reimburses providers for caring for a population of patients over time while shifting more financial risk to providers. In this article, we review current approaches to episode of care development and reimbursement. We describe the challenges of incorporating emergency medicine into the episode of care approach and the uncertain influence this delivery model will have on emergency medicine care, including quality outcomes. We discuss the limitations of the episode of care payment model for emergency services and advocate retention of the current fee-for-service payment model, as well as identify research gaps that, if addressed, could be used to inform future policy decisions of emergency medicine health policy leaders. We then describe a meaningful role for emergency medicine in an episode of care setting. Copyright © 2011. Published by Mosby, Inc.
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Adapting environmental management to uncertain but inevitable change.
Nicol, Sam; Fuller, Richard A; Iwamura, Takuya; Chadès, Iadine
2015-06-07
Implementation of adaptation actions to protect biodiversity is limited by uncertainty about the future. One reason for this is the fear of making the wrong decisions caused by the myriad future scenarios presented to decision-makers. We propose an adaptive management (AM) method for optimally managing a population under uncertain and changing habitat conditions. Our approach incorporates multiple future scenarios and continually learns the best management strategy from observations, even as conditions change. We demonstrate the performance of our AM approach by applying it to the spatial management of migratory shorebird habitats on the East Asian-Australasian flyway, predicted to be severely impacted by future sea-level rise. By accounting for non-stationary dynamics, our solution protects 25,000 more birds per year than the current best stationary approach. Our approach can be applied to many ecological systems that require efficient adaptation strategies for an uncertain future. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
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Uncertain R and D, backstop technology and GHGs stabilization
International Nuclear Information System (INIS)
Bosetti, Valentina; Tavoni, Massimo
2009-01-01
This paper analyses optimal investments in innovation when dealing with a stringent climate target and with the uncertain effectiveness of R and D. The innovation needed to achieve the deep cut in emissions is modeled by a backstop carbon-free technology whose cost depends on R and D investments. To better represent the process of technological progress, we assume that R and D effectiveness is uncertain. By means of a simple analytical model, we show how accounting for the uncertainty that characterizes technological advancement yields higher investments in innovation and lower policy costs. We then confirm the results via a numerical analysis performed with a stochastic version of WITCH, an energy-economy-climate model. The results stress the importance of a correct specification of the technological change process in economy-climate models. (author)
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Stability analysis of fuzzy parametric uncertain systems.
Bhiwani, R J; Patre, B M
2011-10-01
In this paper, the determination of stability margin, gain and phase margin aspects of fuzzy parametric uncertain systems are dealt. The stability analysis of uncertain linear systems with coefficients described by fuzzy functions is studied. A complexity reduced technique for determining the stability margin for FPUS is proposed. The method suggested is dependent on the order of the characteristic polynomial. In order to find the stability margin of interval polynomials of order less than 5, it is not always necessary to determine and check all four Kharitonov's polynomials. It has been shown that, for determining stability margin of FPUS of order five, four, and three we require only 3, 2, and 1 Kharitonov's polynomials respectively. Only for sixth and higher order polynomials, a complete set of Kharitonov's polynomials are needed to determine the stability margin. Thus for lower order systems, the calculations are reduced to a large extent. This idea has been extended to determine the stability margin of fuzzy interval polynomials. It is also shown that the gain and phase margin of FPUS can be determined analytically without using graphical techniques. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
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International Nuclear Information System (INIS)
Park, J.; Jung, W.
2006-01-01
In this study, the appropriateness of the task complexity (TACOM) measure that can quantify the complexity of emergency tasks was investigated by comparing subjective workload scores with the associated TACOM scores. To this end, based on the NASA-TLX (task load index) technique, 18 operators were asked to subjectively estimate perceived workload for 23 emergency tasks that were specified in the emergency operating procedures of the reference nuclear power plants. As the result of comparisons, it was observed that subjective workload scores increase in proportion to the increase of TACOM scores. Therefore, it is expect that the TACOM measure can be used as a serviceable method to quantify the complexity of emergency tasks. (authors)
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Energy Technology Data Exchange (ETDEWEB)
Park, J.; Jung, W. [Integrated Safety Assessment Div., Korea Atomic Energy Research Inst., P.O.Box 105, Duckjin-Dong, Yusong-Ku, Taejon, 305-600 (Korea, Republic of)
2006-07-01
In this study, the appropriateness of the task complexity (TACOM) measure that can quantify the complexity of emergency tasks was investigated by comparing subjective workload scores with the associated TACOM scores. To this end, based on the NASA-TLX (task load index) technique, 18 operators were asked to subjectively estimate perceived workload for 23 emergency tasks that were specified in the emergency operating procedures of the reference nuclear power plants. As the result of comparisons, it was observed that subjective workload scores increase in proportion to the increase of TACOM scores. Therefore, it is expect that the TACOM measure can be used as a serviceable method to quantify the complexity of emergency tasks. (authors)
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Energy trading and pricing in microgrids with uncertain energy supply
DEFF Research Database (Denmark)
Ma, Kai; Hu, Shubing; Yang, Jie
2017-01-01
This paper studies an energy trading and pricing problem for microgrids with uncertain energy supply. The energy provider with the renewable energy (RE) generation (wind power) determines the energy purchase from the electricity markets and the pricing strategy for consumers to maximize its profi....... In particular, the uncertainty of the energy supply from the energy provider is considered. Simulation results show that the energy provider can obtain more profit using the proposed decision-making scheme.......This paper studies an energy trading and pricing problem for microgrids with uncertain energy supply. The energy provider with the renewable energy (RE) generation (wind power) determines the energy purchase from the electricity markets and the pricing strategy for consumers to maximize its profit...
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Novel density-based and hierarchical density-based clustering algorithms for uncertain data.
Zhang, Xianchao; Liu, Han; Zhang, Xiaotong
2017-09-01
Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing
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Investment under Uncertain Climate Policy
DEFF Research Database (Denmark)
Barradale, Merrill Jones
2014-01-01
This paper introduces the concept of payment probability as an important component of carbon risk (the financial risk associated with CO2 emissions under uncertain climate policy). In modeling power plant investment decisions, most existing literature uses the expected carbon price (e.g., the price...... actually be faced in the case of a particular investment. This concept helps explain both the surge of activity in 2005–2006 and the subsequent decline in interest in coal-fired power plant development in the U.S. The data for this case study comes from an extensive online survey of 700 U.S. energy...... design better incentives for investing in low-carbon technologies...
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The property investigation of the numerical code TIGER for the uncertain analysis
International Nuclear Information System (INIS)
Ebina, Takanori; Ohi, Takao
2008-03-01
In order to obtain the information concerning the safety of the geological disposal under various geological environments, the sensitivity analysis that considers the uncertainty of parameters resulting from the insufficiency of knowledge and information plays an important role. The numerical code TIGER allows the physical and chemical properties within the system to vary with time in the radionuclide migration analysis from vitrified glass to rock and these function is useful for understanding the effect of the property change of each barrier in such sensitivity analysis. Therefore, at this study, some typical processing methods with the engineered barrier system and the host rock were developed at fast, and through the comparison with the calculation time, the step of preprocessing and postprocessing, the most suitable method was considered. After this consideration, the interrelation between the calculation accuracy and the calculation time at the most suitable method was examined for the purpose of using this method to the uncertain analysis. In addition, the STRIDER that was the program to make the input file for the uncertain analysis with setting random parameter and do the preprocessing and the postprocessing, was improved for the uncertain analysis. Through this consideration, the information of the best processing method, the calculation accuracy, and the analysis tool was arranged for an uncertain analysis using TIGER. (author)
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Adaptive synchronization of Rossler system with uncertain parameters
International Nuclear Information System (INIS)
Park, Ju H.
2005-01-01
This article addresses control for the chaos synchronization of Rossler systems with three uncertain parameters. Based on the Lyapunov stability theory, an adaptive control law is derived to make the states of two identical Rossler systems asymptotically synchronized. A numerical simulations is presented to show the effectiveness of the proposed chaos synchronization scheme
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Screening of French groundwater for regulated and emerging contaminants.
Lopez, Benjamin; Ollivier, Patrick; Togola, Anne; Baran, Nicole; Ghestem, Jean-Philippe
2015-06-15
Nationwide screening of 411 emerging contaminants and other regulated compounds, including parent molecules and transformation products (TPs) having various uses and origins, was done at 494 groundwater sites throughout France during two sampling campaigns in the Spring and the Fall of 2011. One hundred and eighty substances (44% of the targeted compounds) were quantified in at least one sampling point. These included pharmaceuticals, industrial products, pesticides, their transformation products and other emerging compounds. Fifty-five compounds were quantified in more than 1% of the samples. Both regulated and emerging compounds were found. Among the unregulated compounds, acetaminophen, carbamazepine, perfluorinated compounds, dioxins/furans, tolyltriazole, bisphenol A, triazine transformation products, and caffeine were quantified in more than 10% of the samples analyzed. Concentrations exceeding the threshold of toxicological concern of 0.1 μg/L were found for tolyltriazole, bisphenol A and some of the triazine transformation products (DEDIA). These new results should help the water resource managers and environmental regulators develop sound policies regarding the occurrence and distribution of regulated and emerging contaminants in groundwater. Copyright © 2015 Elsevier B.V. All rights reserved.
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Emergency Vehicle Scheduling Problem with Time Utility in Disasters
Directory of Open Access Journals (Sweden)
Xiaobing Gan
2015-01-01
Full Text Available This paper presents a flexible emergency rescue system which is chiefly composed of three parts, namely, disaster assistance center, relief vehicles, and disaster areas. A novel objective of utility maximization is used to evaluate the entire system in disasters. Considering the uncertain road conditions in the relief distribution, we implement triangular fuzzy number to calculate the vehicle velocity. As a consequence, a fuzzy mathematical model is built to maximize the utility of emergency rescue system and then converted to the crisp counterpart. Finally, the results of numerical experiments obtained by particle swarm optimization (PSO prove the validity of this proposed mathematical model.
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Generalization from uncertain and imprecise data
Energy Technology Data Exchange (ETDEWEB)
Bouchon-Meunier, B.; Marsala, C.; Rifqi, M. [Universite P. et M. Curie, Paris (France); Ramdani, M. [Universite P. et M. Curie, Paris (France)]|[Faculte des Sciences et Techniques, Mohammadia (Morocco)
1996-12-31
Most of the knowledge available about a given system is imperfect, which means imprecise, uncertain, qualitative, expressed in natural language with words which are generally vague. Some pieces of knowledge are numerical, obtained by means of measurements with more or less precise devices. They can also be incomplete, with unknown values for some elements of the system. Classification of objects, decision-making according to the description of the system, are well known problems which can be approached by various ways. Methods based on a generalization process appear very efficient when a list of already solved cases is available and sufficiently representative of all the possible cases. In this paper, we focus on the case where fuzzy sets are used to represent imperfect knowledge because of the capability of fuzzy sets to help managing imprecise data, possibly submitted to some non probabilistic uncertainty such as a subjective doubt. Fuzzy sets also present the interesting property to establish an interface between numerical and symbolic data and are interesting to use when both types of data are present. We suppose that the objects of the system are described by means of attributes, the value of which can be imprecise, uncertain or undetermined. Our purpose is to find rules enabling us to attach a class to any object of the system. We focus this study on two generalization methods based on the knowledge of a training set of objects associated with their descriptions and their classes.
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International Nuclear Information System (INIS)
Yun, Hae-Bum; Masri, Sami F
2009-01-01
A reliable structural health monitoring methodology (SHM) is proposed to detect relatively small changes in uncertain nonlinear systems. A total of 4000 physical tests were performed using a complex nonlinear magneto-rheological (MR) damper. With the effective (or 'genuine') changes and uncertainties in the system characteristics of the semi-active MR damper, which were precisely controlled with known means and standard deviation of the input current, the tested MR damper was identified with the restoring force method (RFM), a non-parametric system identification method involving two-dimensional orthogonal polynomials. Using the identified RFM coefficients, both supervised and unsupervised pattern recognition techniques (including support vector classification and k-means clustering) were employed to detect system changes in the MR damper. The classification results showed that the identified coefficients with orthogonal basis function can be used as reliable indicators for detecting (small) changes, interpreting the physical meaning of the detected changes without a priori knowledge of the monitored system and quantifying the uncertainty bounds of the detected changes. The classification errors were analyzed using the standard detection theory to evaluate the performance of the developed SHM methodology. An optimal classifier design procedure was also proposed and evaluated to minimize type II (or 'missed') errors
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When, not if: The inescapability of an uncertain future
Lewandowsky, S.; Ballard, T.
2014-12-01
Uncertainty is an inherent feature of most scientific endeavours, and many political decisions must be made in the presence of scientific uncertainty. In the case of climate change, there is evidence that greater scientific uncertainty increases the risk associated with the impact of climate change. Scientific uncertainty thus provides an impetus for cutting emissions rather than delaying action. In contrast to those normative considerations, uncertainty is frequently cited in political and public discourse as a reason to delay mitigation. We examine ways in which this gap between public and scientific understanding of uncertainty can be bridged. In particular, we sought ways to communicate uncertainty in a way that better calibrates people's risk perceptions with the projected impact of climate change. We report two behavioural experiments in which uncertainty about the future was expressed either as outcome uncertainty or temporal uncertainty. The conventional presentation of uncertainty involves uncertainty about an outcome at a given time—for example, the range of possible sea level rise (say 50cm +/- 20cm) by a certain date. An alternative presentation of the same situation presents a certain outcome ("sea levels will rise by 50cm") but places the uncertainty into the time of arrival ("this may occur as early as 2040 or as late as 2080"). We presented participants with a series of statements and graphs indicating projected increases in temperature, sea levels, ocean acidification, and a decrease in artic sea ice. In the uncertain magnitude condition, the statements and graphs reported the upper and lower confidence bounds of the projected magnitude and the mean projected time of arrival. In the uncertain time of arrival condition, they reported the upper and lower confidence bounds of the projected time of arrival and the mean projected magnitude. The results show that when uncertainty was presented as uncertain time of arrival rather than an uncertain
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Multiobjective Location Routing Problem considering Uncertain Data after Disasters
Directory of Open Access Journals (Sweden)
Keliang Chang
2017-01-01
Full Text Available The relief distributions after large disasters play an important role for rescue works. After disasters there is a high degree of uncertainty, such as the demands of disaster points and the damage of paths. The demands of affected points and the velocities between two points on the paths are uncertain in this article, and the robust optimization method is applied to deal with the uncertain parameters. This paper proposes a nonlinear location routing problem with half-time windows and with three objectives. The affected points can be visited more than one time. The goals are the total costs of the transportation, the satisfaction rates of disaster nodes, and the path transport capacities which are denoted by vehicle velocities. Finally, the genetic algorithm is applied to solve a number of numerical examples, and the results show that the genetic algorithm is very stable and effective for this problem.
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An index for quantifying flocking behavior.
Quera, Vicenç; Herrando, Salvador; Beltran, Francesc S; Salas, Laura; Miñano, Meritxell
2007-12-01
One of the classic research topics in adaptive behavior is the collective displacement of groups of organisms such as flocks of birds, schools of fish, herds of mammals, and crowds of people. However, most agent-based simulations of group behavior do not provide a quantitative index for determining the point at which the flock emerges. An index was developed of the aggregation of moving individuals in a flock and an example was provided of how it can be used to quantify the degree to which a group of moving individuals actually forms a flock.
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quantification of emergency action levels for research reactor
International Nuclear Information System (INIS)
Wu Zhongwang; Qu Jingyuan; Liu Yuanzhong; Xi Shuren
2000-01-01
Emergency action level (EAL) technical criteria or parameters for emergency conditions classes. Reference methodology for development of EAL in foreign countries, in process of developed and reviewed emergency plan of home several research reactors, the author thought that should be taken initiating conditions which result in emergency conditions quantified some instrumental readings or alarm thresholds, in order to distinguish and confirm emergency conditions and provide technical bases for emergency response actions. Then based on this principle, revised or developed emergency plans of INET Tsinghua University, promote development of work for emergency plan of research reactors
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Energy demand projections based on an uncertain dynamic system modeling approach
International Nuclear Information System (INIS)
Dong, S.
2000-01-01
Today, China has become the world's second largest pollution source of CO 2 . Owing to coal-based energy consumption, it is estimated that 85--90% of the SO 2 and CO 2 emission of China results from coal use. With high economic growth and increasing environmental concerns, China's energy consumption in the next few decades has become an issue of active concern. Forecasting of energy demand over long periods, however, is getting more complex and uncertain. It is believed that the economic and energy systems are chaotic and nonlinear. Traditional linear system modeling, used mostly in energy demand forecasts, therefore, is not a useful approach. In view of uncertainty and imperfect information about future economic growth and energy development, an uncertain dynamic system model, which has the ability to incorporate and absorb the nature of an uncertain system with imperfect or incomplete information, is developed. Using the model, the forecasting of energy demand in the next 25 years is provided. The model predicts that China's energy demand in 2020 will be about 2,700--3,000 Mtce, coal demand 3,500 Mt, increasing by 128% and 154%, respectively, compared with that of 1995
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An Uncertain Wage Contract Model with Adverse Selection and Moral Hazard
Directory of Open Access Journals (Sweden)
Xiulan Wang
2014-01-01
it can be characterized as an uncertain variable. Moreover, the employee's effort is unobservable to the employer, and the employee can select her effort level to maximize her utility. Thus, an uncertain wage contract model with adverse selection and moral hazard is established to maximize the employer's expected profit. And the model analysis mainly focuses on the equivalent form of the proposed wage contract model and the optimal solution to this form. The optimal solution indicates that both the employee's effort level and the wage increase with the employee's ability. Lastly, a numerical example is given to illustrate the effectiveness of the proposed model.
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Invariant set computation for constrained uncertain discrete-time systems
Athanasopoulos, N.; Bitsoris, G.
2010-01-01
In this article a novel approach to the determination of polytopic invariant sets for constrained discrete-time linear uncertain systems is presented. First, the problem of stabilizing a prespecified initial condition set in the presence of input and state constraints is addressed. Second, the
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Uncertain input data problems and the worst scenario method
Czech Academy of Sciences Publication Activity Database
Hlaváček, Ivan
2007-01-01
Roč. 52, č. 3 (2007), s. 187-196 ISSN 0862-7940 R&D Projects: GA ČR GA201/04/1503 Institutional research plan: CEZ:AV0Z10190503 Keywords : uncertain input data * the worst-case approach * fuzzy sets Subject RIV: BA - General Mathematics
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Robust output synchronization of heterogeneous nonlinear agents in uncertain networks.
Yang, Xi; Wan, Fuhua; Tu, Mengchuan; Shen, Guojiang
2017-11-01
This paper investigates the global robust output synchronization problem for a class of nonlinear multi-agent systems. In the considered setup, the controlled agents are heterogeneous and with both dynamic and parametric uncertainties, the controllers are incapable of exchanging their internal states with the neighbors, and the communication network among agents is defined by an uncertain simple digraph. The problem is pursued via nonlinear output regulation theory and internal model based design. For each agent, the input-driven filter and the internal model compose the controller, and the decentralized dynamic output feedback control law is derived by using backstepping method and the modified dynamic high-gain technique. The theoretical result is applied to output synchronization problem for uncertain network of Lorenz-type agents. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
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Rios, Kimberly; Markman, Keith D; Schroeder, Juliana; Dyczewski, Elizabeth A
2014-08-01
Building on findings that self-uncertainty motivates attempts to restore certainty about the self, particularly in ways that highlight one's distinctiveness from others, we show that self-uncertainty, relative to uncertainty in general, increases creative generation among individualists. In Studies 1 to 3, high (but not low) individualists performed better on a creative generation task after being primed with self-uncertainty as opposed to general uncertainty. In Study 4, this effect emerged only among those who were told that the task measured creative as opposed to analytical thinking, suggesting that the positive effects of self-uncertainty on performance are specific to tasks that bolster perceptions of uniqueness. In Study 5, self-uncertain individualists experienced a restoration of self-clarity after being induced to think about themselves as more (vs. less) creative. Implications for compensatory responses to self-uncertainty and factors that influence creativity are discussed. © 2014 by the Society for Personality and Social Psychology, Inc.
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Global exponential stability of uncertain fuzzy BAM neural networks with time-varying delays
International Nuclear Information System (INIS)
Syed Ali, M.; Balasubramaniam, P.
2009-01-01
In this paper, the Takagi-Sugeno (TS) fuzzy model representation is extended to the stability analysis for uncertain Bidirectional Associative Memory (BAM) neural networks with time-varying delays using linear matrix inequality (LMI) theory. A novel LMI-based stability criterion is obtained by LMI optimization algorithms to guarantee the exponential stability of uncertain BAM neural networks with time-varying delays which are represented by TS fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples.
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Le Coz, Jérôme; Renard, Benjamin; Bonnifait, Laurent; Branger, Flora; Le Boursicaud, Raphaël; Horner, Ivan; Mansanarez, Valentin; Lang, Michel; Vigneau, Sylvain
2015-04-01
request to the authors. J. Le Coz, B. Renard, L. Bonnifait, F. Branger, R. Le Boursicaud (2014). Combining hydraulic knowledge and uncertain gaugings in the estimation of hydrometric rating curves: a Bayesian approach, Journal of Hydrology, 509, 573-587.
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Synchronizing a class of uncertain chaotic systems
International Nuclear Information System (INIS)
Chen Maoyin; Zhou Donghua; Shang Yun
2005-01-01
This Letter deals with the synchronization of a class of uncertain chaotic systems in the drive-response framework. A robust adaptive observer based response system is designed to synchronize a given chaotic system with unknown parameters and external disturbances. Lyapunov stability ensures the global synchronization between the drive and response systems even if Lipschitz constants on function matrices and bounds on uncertainties are unknown. Numerical simulation of Genesio-Tesi system verifies the effectiveness of this scheme
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Broadening the study of inductive reasoning: confirmation judgments with uncertain evidence.
Mastropasqua, Tommaso; Crupi, Vincenzo; Tentori, Katya
2010-10-01
Although evidence in real life is often uncertain, the psychology of inductive reasoning has, so far, been confined to certain evidence. The present study extends previous research by investigating whether people properly estimate the impact of uncertain evidence on a given hypothesis. Two experiments are reported, in which the uncertainty of evidence is explicitly (by means of numerical values) versus implicitly (by means of ambiguous pictures) manipulated. The results show that people's judgments are highly correlated with those predicted by normatively sound Bayesian measures of impact. This sensitivity to the degree of evidential uncertainty supports the centrality of inductive reasoning in cognition and opens the path to the study of this issue in more naturalistic settings.
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Improving Evidence on Private Giving in Emerging Economies ...
International Development Research Centre (IDRC) Digital Library (Canada)
... gaps on amounts and sources. There is also a lack of research on regulations and policies that support or discourage private giving. This research project will explore philanthropic cooperation in emerging and developing country contexts by quantifying financial flows from emerging economies to developing countries.
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The quantified self a sociology of self-tracking
Lupton, Deborah
2016-01-01
With the advent of digital devices and software, self-tracking practices have gained new adherents and have spread into a wide array of social domains. The Quantified Self movement has emerged to promote 'self knowledge through numbers'. In this ground-breaking book, Deborah Lupton critically analyses the social, cultural and political dimensions of contemporary self-tracking and identifies the concepts of selfhood, human embodiment and the value of data that underpin them.
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A New Bi-Directional Projection Model Based on Pythagorean Uncertain Linguistic Variable
Directory of Open Access Journals (Sweden)
Huidong Wang
2018-04-01
Full Text Available To solve the multi-attribute decision making (MADM problems with Pythagorean uncertain linguistic variable, an extended bi-directional projection method is proposed. First, we utilize the linguistic scale function to convert uncertain linguistic variable and provide a new projection model, subsequently. Then, to depict the bi-directional projection method, the formative vectors of alternatives and ideal alternatives are defined. Furthermore, a comparative analysis with projection model is conducted to show the superiority of bi-directional projection method. Finally, an example of graduate’s job option is given to demonstrate the effectiveness and feasibility of the proposed method.
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Restructuring Electricity Markets when Demand is Uncertain
DEFF Research Database (Denmark)
Boom, Anette; Buehler, Stefan
2006-01-01
We examine the effects of reorganizing electricity markets on capacity investments, retail prices and welfare when demand is uncertain. We study the following market configurations: (i) integrated monopoly, (ii) integrated duopoly with wholesale trade, and (iii) separated duopoly with wholesale...... trade. Assuming that wholesale prices can react to changes in retail prices (but not vice versa), we find that generators install sufficient capacity to serve retail demand in each market configuration, thus avoiding blackouts. Furthermore, aggregate capacity levels and retail prices...
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A Robust Service Selection Method Based on Uncertain QoS
Directory of Open Access Journals (Sweden)
Yanping Chen
2016-01-01
Full Text Available Nowadays, the number of Web services on the Internet is quickly increasing. Meanwhile, different service providers offer numerous services with the similar functions. Quality of Service (QoS has become an important factor used to select the most appropriate service for users. The most prominent QoS-based service selection models only take the certain attributes into account, which is an ideal assumption. In the real world, there are a large number of uncertain factors. In particular, at the runtime, QoS may become very poor or unacceptable. In order to solve the problem, a global service selection model based on uncertain QoS was proposed, including the corresponding normalization and aggregation functions, and then a robust optimization model adopted to transform the model. Experiment results show that the proposed method can effectively select services with high robustness and optimality.
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Adaptive control of a quadrotor aerial vehicle with input constraints and uncertain parameters
Tran, Trong-Toan; Ge, Shuzhi Sam; He, Wei
2018-05-01
In this paper, we address the problem of adaptive bounded control for the trajectory tracking of a Quadrotor Aerial Vehicle (QAV) while the input saturations and uncertain parameters with the known bounds are simultaneously taken into account. First, to deal with the underactuated property of the QAV model, we decouple and construct the QAV model as a cascaded structure which consists of two fully actuated subsystems. Second, to handle the input constraints and uncertain parameters, we use a combination of the smooth saturation function and smooth projection operator in the control design. Third, to ensure the stability of the overall system of the QAV, we develop the technique for the cascaded system in the presence of both the input constraints and uncertain parameters. Finally, the region of stability of the closed-loop system is constructed explicitly, and our design ensures the asymptotic convergence of the tracking errors to the origin. The simulation results are provided to illustrate the effectiveness of the proposed method.
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Yuan, Chengzhi; Licht, Stephen; He, Haibo
2017-09-26
In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.
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Valuation of American Call Option Considering Uncertain Volatility
Czech Academy of Sciences Publication Activity Database
Hlaváček, Ivan
2010-01-01
Roč. 2, č. 2 (2010), s. 211-221 ISSN 2070-0733 R&D Projects: GA AV ČR(CZ) IAA100190803 Institutional research plan: CEZ:AV0Z10190503 Keywords : American options * parabolic variational inequality * uncertain parameter Subject RIV: BA - General Mathematics Impact factor: 0.510, year: 2010 http://www.global-sci.org/aamm/readabs.php?vol=2&no=2&doc=211&year=2010&ppage=221
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Quantifying the evolution of individual scientific impact.
Sinatra, Roberta; Wang, Dashun; Deville, Pierre; Song, Chaoming; Barabási, Albert-László
2016-11-04
Despite the frequent use of numerous quantitative indicators to gauge the professional impact of a scientist, little is known about how scientific impact emerges and evolves in time. Here, we quantify the changes in impact and productivity throughout a career in science, finding that impact, as measured by influential publications, is distributed randomly within a scientist's sequence of publications. This random-impact rule allows us to formulate a stochastic model that uncouples the effects of productivity, individual ability, and luck and unveils the existence of universal patterns governing the emergence of scientific success. The model assigns a unique individual parameter Q to each scientist, which is stable during a career, and it accurately predicts the evolution of a scientist's impact, from the h-index to cumulative citations, and independent recognitions, such as prizes. Copyright © 2016, American Association for the Advancement of Science.
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Directory of Open Access Journals (Sweden)
Cheng-Hsiung Yang
2013-01-01
Full Text Available A new symplectic chaos synchronization of chaotic systems with uncertain chaotic parameters is studied. The traditional chaos synchronizations are special cases of the symplectic chaos synchronization. A sufficient condition is given for the asymptotical stability of the null solution of error dynamics and a parameter difference. The symplectic chaos synchronization with uncertain chaotic parameters may be applied to the design of secure communication systems. Finally, numerical results are studied for symplectic chaos synchronized from two identical Lorenz-Stenflo systems in three different cases.
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Feature-Based versus Category-Based Induction with Uncertain Categories
Griffiths, Oren; Hayes, Brett K.; Newell, Ben R.
2012-01-01
Previous research has suggested that when feature inferences have to be made about an instance whose category membership is uncertain, feature-based inductive reasoning is used to the exclusion of category-based induction. These results contrast with the observation that people can and do use category-based induction when category membership is…
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Liu, Zhengmin; Liu, Peide
2017-04-01
The Bonferroni mean (BM) was originally introduced by Bonferroni and generalised by many other researchers due to its capacity to capture the interrelationship between input arguments. Nevertheless, in many situations, interrelationships do not always exist between all of the attributes. Attributes can be partitioned into several different categories and members of intra-partition are interrelated while no interrelationship exists between attributes of different partitions. In this paper, as complements to the existing generalisations of BM, we investigate the partitioned Bonferroni mean (PBM) under intuitionistic uncertain linguistic environments and develop two linguistic aggregation operators: intuitionistic uncertain linguistic partitioned Bonferroni mean (IULPBM) and its weighted form (WIULPBM). Then, motivated by the ideal of geometric mean and PBM, we further present the partitioned geometric Bonferroni mean (PGBM) and develop two linguistic geometric aggregation operators: intuitionistic uncertain linguistic partitioned geometric Bonferroni mean (IULPGBM) and its weighted form (WIULPGBM). Some properties and special cases of these proposed operators are also investigated and discussed in detail. Based on these operators, an approach for multiple attribute decision-making problems with intuitionistic uncertain linguistic information is developed. Finally, a practical example is presented to illustrate the developed approach and comparison analyses are conducted with other representative methods to verify the effectiveness and feasibility of the developed approach.
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Directory of Open Access Journals (Sweden)
Said Broumi
2015-03-01
Full Text Available The interval neutrosophic uncertain linguistic variables can easily express the indeterminate and inconsistent information in real world, and TOPSIS is a very effective decision making method more and more extensive applications. In this paper, we will extend the TOPSIS method to deal with the interval neutrosophic uncertain linguistic information, and propose an extended TOPSIS method to solve the multiple attribute decision making problems in which the attribute value takes the form of the interval neutrosophic uncertain linguistic variables and attribute weight is unknown. Firstly, the operational rules and properties for the interval neutrosophic variables are introduced. Then the distance between two interval neutrosophic uncertain linguistic variables is proposed and the attribute weight is calculated by the maximizing deviation method, and the closeness coefficients to the ideal solution for each alternatives. Finally, an illustrative example is given to illustrate the decision making steps and the effectiveness of the proposed method.
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Parametric optimal control of uncertain systems under an optimistic value criterion
Li, Bo; Zhu, Yuanguo
2018-01-01
It is well known that the optimal control of a linear quadratic model is characterized by the solution of a Riccati differential equation. In many cases, the corresponding Riccati differential equation cannot be solved exactly such that the optimal feedback control may be a complex time-oriented function. In this article, a parametric optimal control problem of an uncertain linear quadratic model under an optimistic value criterion is considered for simplifying the expression of optimal control. Based on the equation of optimality for the uncertain optimal control problem, an approximation method is presented to solve it. As an application, a two-spool turbofan engine optimal control problem is given to show the utility of the proposed model and the efficiency of the presented approximation method.
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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.
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Distributed Robustness Analysis of Interconnected Uncertain Systems Using Chordal Decomposition
DEFF Research Database (Denmark)
Pakazad, Sina Khoshfetrat; Hansson, Anders; Andersen, Martin Skovgaard
2014-01-01
Large-scale interconnected uncertain systems commonly have large state and uncertainty dimensions. Aside from the heavy computational cost of performing robust stability analysis in a centralized manner, privacy requirements in the network can also introduce further issues. In this paper, we util...
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Application of dynamic uncertain causality graph in spacecraft fault diagnosis: Logic cycle
Yao, Quanying; Zhang, Qin; Liu, Peng; Yang, Ping; Zhu, Ma; Wang, Xiaochen
2017-04-01
Intelligent diagnosis system are applied to fault diagnosis in spacecraft. Dynamic Uncertain Causality Graph (DUCG) is a new probability graphic model with many advantages. In the knowledge expression of spacecraft fault diagnosis, feedback among variables is frequently encountered, which may cause directed cyclic graphs (DCGs). Probabilistic graphical models (PGMs) such as bayesian network (BN) have been widely applied in uncertain causality representation and probabilistic reasoning, but BN does not allow DCGs. In this paper, DUGG is applied to fault diagnosis in spacecraft: introducing the inference algorithm for the DUCG to deal with feedback. Now, DUCG has been tested in 16 typical faults with 100% diagnosis accuracy.
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Transitioning nuclear fuel cycles with uncertain fast reactor costs
Energy Technology Data Exchange (ETDEWEB)
Phathanapirom, U.B., E-mail: bphathanapirom@utexas.edu; Schneider, E.A.
2016-06-15
This paper applies a novel decision making methodology to a case study involving choices leading to the transition from the current once-through light water reactor fuel cycle to one relying on continuous recycle of plutonium and minor actinides in fast reactors in the face of uncertain fast reactor capital costs. Unique to this work is a multi-stage treatment of a range of plausible trajectories for the evolution of fast reactor capital costs over time, characterized by first-of-a-kind penalties as well as time- and unit-based learning. The methodology explicitly incorporates uncertainties in key parameters into the decision-making process by constructing a stochastic model and embedding uncertainties as bifurcations in the decision tree. “Hedging” strategies are found by applying a choice criterion to select courses of action which mitigate “regrets”. These regrets are calculated by evaluating the performance of all possible transition strategies for every feasible outcome of the uncertain parameter. The hedging strategies are those that preserve the most flexibility for adjusting the fuel cycle strategy in response to new information as uncertainties are resolved.
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Transitioning nuclear fuel cycles with uncertain fast reactor costs
International Nuclear Information System (INIS)
Phathanapirom, U.B.; Schneider, E.A.
2016-01-01
This paper applies a novel decision making methodology to a case study involving choices leading to the transition from the current once-through light water reactor fuel cycle to one relying on continuous recycle of plutonium and minor actinides in fast reactors in the face of uncertain fast reactor capital costs. Unique to this work is a multi-stage treatment of a range of plausible trajectories for the evolution of fast reactor capital costs over time, characterized by first-of-a-kind penalties as well as time- and unit-based learning. The methodology explicitly incorporates uncertainties in key parameters into the decision-making process by constructing a stochastic model and embedding uncertainties as bifurcations in the decision tree. “Hedging” strategies are found by applying a choice criterion to select courses of action which mitigate “regrets”. These regrets are calculated by evaluating the performance of all possible transition strategies for every feasible outcome of the uncertain parameter. The hedging strategies are those that preserve the most flexibility for adjusting the fuel cycle strategy in response to new information as uncertainties are resolved.
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Quantifying resilience for resilience engineering of socio technical systems
Häring, Ivo; Ebenhöch, Stefan; Stolz, Alexander
2016-01-01
Resilience engineering can be defined to comprise originally technical, engineering and natural science approaches to improve the resilience and sustainability of socio technical cyber-physical systems of various complexities with respect to disruptive events. It is argued how this emerging interdisciplinary technical and societal science approach may contribute to civil and societal security research. In this context, the article lists expected benefits of quantifying resilience. Along the r...
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Schmidt, Christian; Wagner, Sven; Burger, Martin; van Rienen, Ursula; Wolters, Carsten H.
2015-08-01
Objective. Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique to modify neural excitability. Using multi-array tDCS, we investigate the influence of inter-individually varying head tissue conductivity profiles on optimal electrode configurations for an auditory cortex stimulation. Approach. In order to quantify the uncertainty of the optimal electrode configurations, multi-variate generalized polynomial chaos expansions of the model solutions are used based on uncertain conductivity profiles of the compartments skin, skull, gray matter, and white matter. Stochastic measures, probability density functions, and sensitivity of the quantities of interest are investigated for each electrode and the current density at the target with the resulting stimulation protocols visualized on the head surface. Main results. We demonstrate that the optimized stimulation protocols are only comprised of a few active electrodes, with tolerable deviations in the stimulation amplitude of the anode. However, large deviations in the order of the uncertainty in the conductivity profiles could be noted in the stimulation protocol of the compensating cathodes. Regarding these main stimulation electrodes, the stimulation protocol was most sensitive to uncertainty in skull conductivity. Finally, the probability that the current density amplitude in the auditory cortex target region is supra-threshold was below 50%. Significance. The results suggest that an uncertain conductivity profile in computational models of tDCS can have a substantial influence on the prediction of optimal stimulation protocols for stimulation of the auditory cortex. The investigations carried out in this study present a possibility to predict the probability of providing a therapeutic effect with an optimized electrode system for future auditory clinical and experimental procedures of tDCS applications.
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Adaptive synchronization of hyperchaotic Chen system with uncertain parameters
International Nuclear Information System (INIS)
Park, Ju H.
2005-01-01
This article addresses control for the chaos synchronization of hyperchaotic Chen system with five uncertain parameters. Based on the Lyapunov stability theory, an adaptive control law is derived to make the states of two identical hyperchaotic Chen systems asymptotically synchronized. Finally, a numerical simulations is presented to show the effectiveness of the proposed chaos synchronization scheme
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Effects of a training workshop on suicide prevention among emergency room nurses.
Kishi, Yasuhiro; Otsuka, Kotaro; Akiyama, Keiko; Yamada, Tomoki; Sakamoto, Yumiko; Yanagisawa, Yaeko; Morimura, Hiroshi; Kawanishi, Chiaki; Higashioka, Hiroaki; Miyake, Yasushi; Thurber, Steven
2014-01-01
Suicide attempts are frequently encountered by emergency department nurses. Such encounters can potentially provide a foundation for secondary suicide prevention. The aim of the present investigation was to evaluate the effect of a 7-hr training program for emergency room nursing personnel in Japan. In all, 52 nurses completed the questionnaires before the workshop and 1 month after the workshop. The nurses' understanding of and willingness to care for suicidal patients positively changed. It is feasible to provide a 7-hr, relatively short, workshop on suicidal prevention aimed at emergency medical staff and to improve attitudes during a follow-up of 1 month. It is uncertain whether the positive attitudes of emergency nurses toward suicide and/or educational interventions could impact the outcomes of these interventions. Further studies are needed to address these important questions in this field.
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Vessels Route Planning Problem with Uncertain Data
Directory of Open Access Journals (Sweden)
Tomasz Neumann
2016-09-01
Full Text Available The purpose of this paper is to find a solution for route planning in a transport networks, where the costs of tracks, factor of safety and travel time are ambiguous. This approach is based on the Dempster-Shafer theory and well known Dijkstra's algorithm. In this approach important are the influencing factors of the mentioned coefficients using uncertain possibilities presented by probability intervals. Based on these intervals the quality intervals of each route can be determined. Applied decision rules can be described by the end user.
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Chernobyl, the true, the false and the uncertain; Tchernobyl: le vrai, le faux et l'incertain
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-04-01
This work makes the part between the true and the false information in France about the Chernobyl accident that have been read in different newspapers during the last years. This document is divide in three parts: what is true, what is false, what is uncertain. In each part are noticed extracts from newspapers face to the synthesis of thoughts about them. It is the fourth edition, the first one was in April 1990, the second one was in 1992 after a report from IAEA on the radiological consequences, the third edition was born in 1994 with the emergence of thyroid cancers especially among children, this fourth edition of 1996 takes into account the sanitary report given by the World Health Organisation experts in 1995. It confirms the progression of thyroid cancers and the absence of any other cancer as well leukemia. (N.C.)
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Quantifying Complexity in Quantum Phase Transitions via Mutual Information Complex Networks.
Valdez, Marc Andrew; Jaschke, Daniel; Vargas, David L; Carr, Lincoln D
2017-12-01
We quantify the emergent complexity of quantum states near quantum critical points on regular 1D lattices, via complex network measures based on quantum mutual information as the adjacency matrix, in direct analogy to quantifying the complexity of electroencephalogram or functional magnetic resonance imaging measurements of the brain. Using matrix product state methods, we show that network density, clustering, disparity, and Pearson's correlation obtain the critical point for both quantum Ising and Bose-Hubbard models to a high degree of accuracy in finite-size scaling for three classes of quantum phase transitions, Z_{2}, mean field superfluid to Mott insulator, and a Berzinskii-Kosterlitz-Thouless crossover.
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Quantifying Complexity in Quantum Phase Transitions via Mutual Information Complex Networks
Valdez, Marc Andrew; Jaschke, Daniel; Vargas, David L.; Carr, Lincoln D.
2017-12-01
We quantify the emergent complexity of quantum states near quantum critical points on regular 1D lattices, via complex network measures based on quantum mutual information as the adjacency matrix, in direct analogy to quantifying the complexity of electroencephalogram or functional magnetic resonance imaging measurements of the brain. Using matrix product state methods, we show that network density, clustering, disparity, and Pearson's correlation obtain the critical point for both quantum Ising and Bose-Hubbard models to a high degree of accuracy in finite-size scaling for three classes of quantum phase transitions, Z2, mean field superfluid to Mott insulator, and a Berzinskii-Kosterlitz-Thouless crossover.
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Taha, Ahmad Fayez
Transportation networks, wearable devices, energy systems, and the book you are reading now are all ubiquitous cyber-physical systems (CPS). These inherently uncertain systems combine physical phenomena with communication, data processing, control and optimization. Many CPSs are controlled and monitored by real-time control systems that use communication networks to transmit and receive data from systems modeled by physical processes. Existing studies have addressed a breadth of challenges related to the design of CPSs. However, there is a lack of studies on uncertain CPSs subject to dynamic unknown inputs and cyber-attacks---an artifact of the insertion of communication networks and the growing complexity of CPSs. The objective of this dissertation is to create secure, computational foundations for uncertain CPSs by establishing a framework to control, estimate and optimize the operation of these systems. With major emphasis on power networks, the dissertation deals with the design of secure computational methods for uncertain CPSs, focusing on three crucial issues---(1) cyber-security and risk-mitigation, (2) network-induced time-delays and perturbations and (3) the encompassed extreme time-scales. The dissertation consists of four parts. In the first part, we investigate dynamic state estimation (DSE) methods and rigorously examine the strengths and weaknesses of the proposed routines under dynamic attack-vectors and unknown inputs. In the second part, and utilizing high-frequency measurements in smart grids and the developed DSE methods in the first part, we present a risk mitigation strategy that minimizes the encountered threat levels, while ensuring the continual observability of the system through available, safe measurements. The developed methods in the first two parts rely on the assumption that the uncertain CPS is not experiencing time-delays, an assumption that might fail under certain conditions. To overcome this challenge, networked unknown input
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Uncertain deduction and conditional reasoning.
Evans, Jonathan St B T; Thompson, Valerie A; Over, David E
2015-01-01
There has been a paradigm shift in the psychology of deductive reasoning. Many researchers no longer think it is appropriate to ask people to assume premises and decide what necessarily follows, with the results evaluated by binary extensional logic. Most every day and scientific inference is made from more or less confidently held beliefs and not assumptions, and the relevant normative standard is Bayesian probability theory. We argue that the study of "uncertain deduction" should directly ask people to assign probabilities to both premises and conclusions, and report an experiment using this method. We assess this reasoning by two Bayesian metrics: probabilistic validity and coherence according to probability theory. On both measures, participants perform above chance in conditional reasoning, but they do much better when statements are grouped as inferences, rather than evaluated in separate tasks.
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Extreme-Scale Stochastic Particle Tracing for Uncertain Unsteady Flow Analysis
Energy Technology Data Exchange (ETDEWEB)
Guo, Hanqi; He, Wenbin; Seo, Sangmin; Shen, Han-Wei; Peterka, Tom
2016-11-13
We present an efficient and scalable solution to estimate uncertain transport behaviors using stochastic flow maps (SFM,) for visualizing and analyzing uncertain unsteady flows. SFM computation is extremely expensive because it requires many Monte Carlo runs to trace densely seeded particles in the flow. We alleviate the computational cost by decoupling the time dependencies in SFMs so that we can process adjacent time steps independently and then compose them together for longer time periods. Adaptive refinement is also used to reduce the number of runs for each location. We then parallelize over tasks—packets of particles in our design—to achieve high efficiency in MPI/thread hybrid programming. Such a task model also enables CPU/GPU coprocessing. We show the scalability on two supercomputers, Mira (up to 1M Blue Gene/Q cores) and Titan (up to 128K Opteron cores and 8K GPUs), that can trace billions of particles in seconds.
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Mean-Variance portfolio optimization when each asset has individual uncertain exit-time
Directory of Open Access Journals (Sweden)
Reza Keykhaei
2016-12-01
Full Text Available The standard Markowitz Mean-Variance optimization model is a single-period portfolio selection approach where the exit-time (or the time-horizon is deterministic. In this paper we study the Mean-Variance portfolio selection problem with uncertain exit-time when each has individual uncertain xit-time, which generalizes the Markowitz's model. We provide some conditions under which the optimal portfolio of the generalized problem is independent of the exit-times distributions. Also, it is shown that under some general circumstances, the sets of optimal portfolios in the generalized model and the standard model are the same.
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Directory of Open Access Journals (Sweden)
Fengjiao Wu
2016-01-01
Full Text Available The robust fuzzy control for fractional-order hydroturbine regulating system is studied in this paper. First, the more practical fractional-order hydroturbine regulating system with uncertain parameters and random disturbances is presented. Then, on the basis of interval matrix theory and fractional-order stability theorem, a fuzzy control method is proposed for fractional-order hydroturbine regulating system, and the stability condition is expressed as a group of linear matrix inequalities. Furthermore, the proposed method has good robustness which can process external random disturbances and uncertain parameters. Finally, the validity and superiority are proved by the numerical simulations.
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Fault tolerant control for uncertain systems with parametric faults
DEFF Research Database (Denmark)
Niemann, Hans Henrik; Poulsen, Niels Kjølstad
2006-01-01
A fault tolerant control (FTC) architecture based on active fault diagnosis (AFD) and the YJBK (Youla, Jarb, Bongiorno and Kucera)parameterization is applied in this paper. Based on the FTC architecture, fault tolerant control of uncertain systems with slowly varying parametric faults...... is investigated. Conditions are given for closed-loop stability in case of false alarms or missing fault detection/isolation....
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Bindeman, I N; Zakharov, D O; Palandri, J; Greber, N D; Dauphas, N; Retallack, G J; Hofmann, A; Lackey, J S; Bekker, A
2018-05-01
The history of the growth of continental crust is uncertain, and several different models that involve a gradual, decelerating, or stepwise process have been proposed 1-4 . Even more uncertain is the timing and the secular trend of the emergence of most landmasses above the sea (subaerial landmasses), with estimates ranging from about one billion to three billion years ago 5-7 . The area of emerged crust influences global climate feedbacks and the supply of nutrients to the oceans 8 , and therefore connects Earth's crustal evolution to surface environmental conditions 9-11 . Here we use the triple-oxygen-isotope composition of shales from all continents, spanning 3.7 billion years, to provide constraints on the emergence of continents over time. Our measurements show a stepwise total decrease of 0.08 per mille in the average triple-oxygen-isotope value of shales across the Archaean-Proterozoic boundary. We suggest that our data are best explained by a shift in the nature of water-rock interactions, from near-coastal in the Archaean era to predominantly continental in the Proterozoic, accompanied by a decrease in average surface temperatures. We propose that this shift may have coincided with the onset of a modern hydrological cycle owing to the rapid emergence of continental crust with near-modern average elevation and aerial extent roughly 2.5 billion years ago.
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Directory of Open Access Journals (Sweden)
Liu Heng
Full Text Available This paper investigates a method to identify uncertain system parameters and unknown topological structure in general complex networks with or without time delay. A complex network, which has uncertain topology and unknown parameters, is designed as a drive network, and a known response complex network with an input controller is designed to identify the drive network. Under the proposed input controller, the drive network and the response network can achieve anticipatory projective synchronization when the system is steady. Lyapunov theorem and Barbǎlat's lemma guarantee the stability of synchronization manifold between two networks. When the synchronization is achieved, the system parameters and topology in response network can be changed to equal with the parameters and topology in drive network. A numerical example is given to show the effectiveness of the proposed method.
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Role of diagnostic laparoscopy in chronic abdominal conditions with uncertain diagnosis
Directory of Open Access Journals (Sweden)
Amandeep S Nar
2014-01-01
Full Text Available Introduction: Laparoscopy has proved to be an important tool in the minimally invasive exploration of selected patients with chronic abdominal disorders, whose diagnosis remains uncertain, despite exploring the requisite laboratory and imaging investigations like ultrasonography, computed tomography (CT scan, and the like. Materials and Methods: Diagnostic Laparoscopy was conducted on 120 patients, admitted to the Departments of Surgery and Gynecology, Dayanand Medical College and Hospital, Ludhiana, with an uncertain diagnosis after four weeks of onset of symptoms. Conclusion: With laparoscopy providing tissue diagnosis, and helping to achieve the final diagnosis without any significant complication and less operative time, it can be safely concluded that diagnostic laparoscopy is a safe, quick, and effective adjunct to non-surgical diagnostic modalities, for establishing a conclusive diagnosis, but whether it will replace imaging studies as a primary modality for diagnosis needs more evidence.
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Robust digital controllers for uncertain chaotic systems: A digital redesign approach
Energy Technology Data Exchange (ETDEWEB)
Ababneh, Mohammad [Department of Controls, FMC Kongsberg Subsea, FMC Energy Systems, Houston, TX 77067 (United States); Barajas-Ramirez, Juan-Gonzalo [CICESE, Depto. De Electronica y Telecomunicaciones, Ensenada, BC, 22860 (Mexico); Chen Guanrong [Centre for Chaos Control and Synchronization, Department of Electronic Engineering, City University of Hong Kong (China); Shieh, Leang S. [Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204-4005 (United States)
2007-03-15
In this paper, a new and systematic method for designing robust digital controllers for uncertain nonlinear systems with structured uncertainties is presented. In the proposed method, a controller is designed in terms of the optimal linear model representation of the nominal system around each operating point of the trajectory, while the uncertainties are decomposed such that the uncertain nonlinear system can be rewritten as a set of local linear models with disturbed inputs. Applying conventional robust control techniques, continuous-time robust controllers are first designed to eliminate the effects of the uncertainties on the underlying system. Then, a robust digital controller is obtained as the result of a digital redesign of the designed continuous-time robust controller using the state-matching technique. The effectiveness of the proposed controller design method is illustrated through some numerical examples on complex nonlinear systems--chaotic systems.
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Directory of Open Access Journals (Sweden)
Xing Yin
2011-01-01
uncertain periodic switched recurrent neural networks with time-varying delays. When uncertain discrete-time recurrent neural network is a periodic system, it is expressed as switched neural network for the finite switching state. Based on the switched quadratic Lyapunov functional approach (SQLF and free-weighting matrix approach (FWM, some linear matrix inequality criteria are found to guarantee the delay-dependent asymptotical stability of these systems. Two examples illustrate the exactness of the proposed criteria.
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Angelo, Joseph A
2011-01-01
Quantifying Matter explains how scientists learned to measure matter and quantify some of its most fascinating and useful properties. It presents many of the most important intellectual achievements and technical developments that led to the scientific interpretation of substance. Complete with full-color photographs, this exciting new volume describes the basic characteristics and properties of matter. Chapters include:. -Exploring the Nature of Matter. -The Origin of Matter. -The Search for Substance. -Quantifying Matter During the Scientific Revolution. -Understanding Matter's Electromagnet
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International Nuclear Information System (INIS)
Li, Lixiang; Li, Weiwei; Kurths, Jürgen; Luo, Qun; Yang, Yixian; Li, Shudong
2015-01-01
For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method
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ON A NUMERICAL ALGORITHM FOR UNCERTAIN SYSTEM ∫ Φ ...
African Journals Online (AJOL)
Administrator
Science World Journal Vol 7 (No 1) 2012 www.scienceworldjournal.org. ISSN 1597-6343. On a Numerical Algorithm for Uncertain System. Newton's Algorithm. Step 1 Calculate. )(),().(k k k. xAxgxF. Step 2. Check if ε. <. )(k xg for a predetermined ,ε if so stop, else. Step3. Set k k. PxA. )( = )(k xg. -. Step4. Set k k k. Px x. +. = +1.
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Emerging Technologies for Environmental Remediation: Integrating Data and Judgment.
Bates, Matthew E; Grieger, Khara D; Trump, Benjamin D; Keisler, Jeffrey M; Plourde, Kenton J; Linkov, Igor
2016-01-05
Emerging technologies present significant challenges to researchers, decision-makers, industry professionals, and other stakeholder groups due to the lack of quantitative risk, benefit, and cost data associated with their use. Multi-criteria decision analysis (MCDA) can support early decisions for emerging technologies when data is too sparse or uncertain for traditional risk assessment. It does this by integrating expert judgment with available quantitative and qualitative inputs across multiple criteria to provide relative technology scores. Here, an MCDA framework provides preliminary insights on the suitability of emerging technologies for environmental remediation by comparing nanotechnology and synthetic biology to conventional remediation methods. Subject matter experts provided judgments regarding the importance of criteria used in the evaluations and scored the technologies with respect to those criteria. The results indicate that synthetic biology may be preferred over nanotechnology and conventional methods for high expected benefits and low deployment costs but that conventional technology may be preferred over emerging technologies for reduced risks and development costs. In the absence of field data regarding the risks, benefits, and costs of emerging technologies, structuring evidence-based expert judgment through a weighted hierarchy of topical questions may be helpful to inform preliminary risk governance and guide emerging technology development and policy.
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Numerical Solution of Uncertain Beam Equations Using Double Parametric Form of Fuzzy Numbers
Directory of Open Access Journals (Sweden)
Smita Tapaswini
2013-01-01
Full Text Available Present paper proposes a new technique to solve uncertain beam equation using double parametric form of fuzzy numbers. Uncertainties appearing in the initial conditions are taken in terms of triangular fuzzy number. Using the single parametric form, the fuzzy beam equation is converted first to an interval-based fuzzy differential equation. Next, this differential equation is transformed to crisp form by applying double parametric form of fuzzy number. Finally, the same is solved by homotopy perturbation method (HPM to obtain the uncertain responses subject to unit step and impulse loads. Obtained results are depicted in terms of plots to show the efficiency and powerfulness of the methodology.
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Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays
Syed Ali, M.; Balasubramaniam, P.
2008-07-01
In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB.
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Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays
International Nuclear Information System (INIS)
Syed Ali, M.; Balasubramaniam, P.
2008-01-01
In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB
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Optimal core acquisition and remanufacturing policies under uncertain core quality fractions
Teunter, R.H.; Flapper, S.D.P.
2011-01-01
Cores acquired by a remanufacturer are typically highly variable in quality. Even if the expected fractions of the various quality levels are known, then the exact fractions when acquiring cores are still uncertain. Our model incorporates this uncertainty in determining optimal acquisition decisions
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Crisis and emergency risk communication as an integrative model.
Reynolds, Barbara; W Seeger, Matthew
2005-01-01
This article describes a model of communication known as crisis and emergency risk communication (CERC). The model is outlined as a merger of many traditional notions of health and risk communication with work in crisis and disaster communication. The specific kinds of communication activities that should be called for at various stages of disaster or crisis development are outlined. Although crises are by definition uncertain, equivocal, and often chaotic situations, the CERC model is presented as a tool health communicators can use to help manage these complex events.
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Chattering-free fuzzy sliding-mode control strategy for uncertain chaotic systems
International Nuclear Information System (INIS)
Yau, H.-T.; Chen, C.-L.
2006-01-01
This paper proposes a chattering-free fuzzy sliding-mode control (FSMC) strategy for uncertain chaotic systems. A fuzzy logic control is used to replace the discontinuous sign function of the reaching law in traditional sliding-mode control (SMC), and hence a control input without chattering is obtained in the chaotic systems with uncertainties. Base on the Lyapunov stability theory, we address the design schemes of integration fuzzy sliding-mode control, where the reaching law is proposed by a set of linguistic rules and the control input is chattering free. The Genesio chaotic system is used to test the proposed control strategy and the simulation results show the FSMC not only can control the uncertain chaotic behaviors to a desired state without oscillator very fast, but also the switching function is smooth without chattering. This result implies that this strategy is feasible and effective for chaos control
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Performance-Driven Robust Identification and Control of Uncertain Dynamical Systems
Energy Technology Data Exchange (ETDEWEB)
Basar, Tamer
2001-10-29
The grant DEFG02-97ER13939 from the Department of Energy has supported our research program on robust identification and control of uncertain dynamical systems, initially for the three-year period June 15, 1997-June 14, 2000, which was then extended on a no-cost basis for another year until June 14, 2001. This final report provides an overview of our research conducted during this period, along with a complete list of publications supported by the Grant. Within the scope of this project, we have studied fundamental issues that arise in modeling, identification, filtering, control, stabilization, control-based model reduction, decomposition and aggregation, and optimization of uncertain systems. The mathematical framework we have worked in has allowed the system dynamics to be only partially known (with the uncertainties being of both parametric or structural nature), and further the dynamics to be perturbed by unknown dynamic disturbances. Our research over these four years has generated a substantial body of new knowledge, and has led to new major developments in theory, applications, and computational algorithms. These have all been documented in various journal articles and book chapters, and have been presented at leading conferences, as to be described. A brief description of the results we have obtained within the scope of this project can be found in Section 3. To set the stage for the material of that section, we first provide in the next section (Section 2) a brief description of the issues that arise in the control of uncertain systems, and introduce several criteria under which optimality will lead to robustness and stability. Section 4 contains a list of references cited in these two sections. A list of our publications supported by the DOE Grant (covering the period June 15, 1997-June 14, 2001) comprises Section 5 of the report.
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Adaptive synchronization of a new hyperchaotic system with uncertain parameters
International Nuclear Information System (INIS)
Gao Tiegang; Chen Zengqiang; Yuan Zhuzhi; Yu Dongchuan
2007-01-01
This paper discusses control for the master-slave synchronization of a new hyperchaos with five uncertain parameters. An adaptive control law is derived to make the states of two identical hyperchaotic systems asymptotically synchronized based on the Lyapunov stability theory. Finally, a numerical simulation is presented to verify the effectiveness of the proposed synchronization scheme
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Optimal Order Strategy in Uncertain Demands with Free Shipping Option
Directory of Open Access Journals (Sweden)
Qing-Chun Meng
2014-01-01
Full Text Available Free shipping with conditions has become one of the most effective marketing tools; more and more companies especially e-business companies prefer to offer free shipping to buyers whenever their orders exceed the minimum quantity specified by them. But in practice, the demands of buyers are uncertain, which are affected by weather, season, and many other factors. Firstly, we model the centralization ordering problem of retailers who face stochastic demands when suppliers offer free shipping, in which limited distributional information such as known mean, support, and some deviation measures of the random data is needed only. Then, based on the linear decision rule mainly for stochastic programming, we analyze the optimal order strategies of retailers and discuss the approximate solution. Further, we present the core allocation between all retailers via dual and cooperative game theory. The existence of core shows that each retailer is pleased to cooperate with others in the centralization problem. Finally, a numerical example is implemented to discuss how uncertain data and parameters affect the optimal solution.
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International Nuclear Information System (INIS)
Novak Pintarič, Zorka; Kravanja, Zdravko
2015-01-01
This paper presents a robust computational methodology for the synthesis and design of flexible HEN (Heat Exchanger Networks) having large numbers of uncertain parameters. This methodology combines several heuristic methods which progressively lead to a flexible HEN design at a specific level of confidence. During the first step, a HEN topology is generated under nominal conditions followed by determining those points critical for flexibility. A significantly reduced multi-scenario model for flexible HEN design is formulated at the nominal point with the flexibility constraints at the critical points. The optimal design obtained is tested by stochastic Monte Carlo optimization and the flexibility index through solving one-scenario problems within a loop. This presented methodology is novel regarding the enormous reduction of scenarios in HEN design problems, and computational effort. Despite several simplifications, the capability of designing flexible HENs with large numbers of uncertain parameters, which are typical throughout industry, is not compromised. An illustrative case study is presented for flexible HEN synthesis comprising 42 uncertain parameters. - Highlights: • Methodology for HEN (Heat Exchanger Network) design under uncertainty is presented. • The main benefit is solving HENs having large numbers of uncertain parameters. • Drastically reduced multi-scenario HEN design problem is formulated through several steps. • Flexibility of HEN is guaranteed at a specific level of confidence.
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Quantifying Correlation Uncertainty Risk in Credit Derivatives Pricing
Directory of Open Access Journals (Sweden)
Colin Turfus
2018-04-01
Full Text Available We propose a simple but practical methodology for the quantification of correlation risk in the context of credit derivatives pricing and credit valuation adjustment (CVA, where the correlation between rates and credit is often uncertain or unmodelled. We take the rates model to be Hull–White (normal and the credit model to be Black–Karasinski (lognormal. We summarise recent work furnishing highly accurate analytic pricing formulae for credit default swaps (CDS including with defaultable Libor flows, extending this to the situation where they are capped and/or floored. We also consider the pricing of contingent CDS with an interest rate swap underlying. We derive therefrom explicit expressions showing how the dependence of model prices on the uncertain parameter(s can be captured in analytic formulae that are readily amenable to computation without recourse to Monte Carlo or lattice-based computation. In so doing, we crucially take into account the impact on model calibration of the uncertain (or unmodelled parameters.
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Adaptive variable structure control for uncertain chaotic systems containing dead-zone nonlinearity
International Nuclear Information System (INIS)
Yan, J.-J.; Shyu, K.-K.; Lin, J.-S.
2005-01-01
This paper addresses a practical tracking problem for a class of uncertain chaotic systems with dead-zone nonlinearity in the input function. Based on the Lyapunov stability theorem and Barbalat lemma, an adaptive variable structure controller (AVSC) is proposed to ensure the occurrence of the sliding mode even though the control input contains a dead-zone. Also it is worthy of note that the proposed AVSC involves no information of the upper bound of uncertainty. Thus, the limitation of knowing the bound of uncertainty in advance is certainly released. Furthermore, in the sliding mode, the investigated uncertain chaotic system remains insensitive to the uncertainty, and behaves like a linear system. Finally, a well-known Duffing-Holmes chaotic system is used to demonstrate the feasibility of the proposed AVSC
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Magnetic resonance imaging features of extremity sarcomas of uncertain differentiation
International Nuclear Information System (INIS)
Stacy, G.S.; Nair, L.
2007-01-01
The purpose of this review is to illustrate the pertinent clinical and imaging features of extremity sarcomas of uncertain differentiation, including synovial sarcoma, epithelioid sarcoma, clear-cell sarcoma, and alveolar soft part sarcoma. These tumours should be considered in the differential diagnosis when a soft-tissue mass is encountered in the extremity of an adolescent or young adult
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Zi, Bin; Zhou, Bin
2016-07-01
For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .
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Robust control of uncertain dynamic systems a linear state space approach
Yedavalli, Rama K
2014-01-01
This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems. In model-based control design and analysis, mathematical models can never completely represent the “real world” system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into the models. This book directly addresses these issues from a deterministic uncertainty viewpoint and focuses on the interval parameter characterization of uncertain systems. Various tools of analysis and design are presented in a consolidated manner. This volume fills a current gap in published works by explicitly addressing the subject of control of dynamic systems from linear state space framework, namely using a time-domain, matrix-theory based approach. This book also: Presents and formulates the robustness problem in a linear state space model framework Illustrates various systems level methodologies with examples and...
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An Uncertain QFD Approach for the Strategic Management of Logistics Services
Directory of Open Access Journals (Sweden)
Shengpeng Yang
2016-01-01
Full Text Available Due to customers’ growing concern about logistics performances related to products, logistics service increasingly contributes to the core competence of an enterprise or product, which calls an appropriate tool to develop effective strategic actions to improve logistics performances and gain customer satisfaction. Therefore, an uncertain quality function deployment (QFD approach for selecting the most effective strategic actions in terms of efficiency to meet the customer requirements is developed in this paper, which integrates uncertainty theory into the traditional QFD methodology in order to rationally deal with imprecise information inherently involved in the QFD process. The framework and systematic procedures of the approach are presented in the context of logistics services. Specifically, the calculations for the prioritization of strategic actions are discussed in detail, in which uncertain variables are used to capture the linguistic judgements given by customers and experts. Applications of the proposed approach are presented as well for illustration.
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Quantifiers and working memory
Szymanik, J.; Zajenkowski, M.
2010-01-01
The paper presents a study examining the role of working memory in quantifier verification. We created situations similar to the span task to compare numerical quantifiers of low and high rank, parity quantifiers and proportional quantifiers. The results enrich and support the data obtained
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Quantifiers and working memory
Szymanik, J.; Zajenkowski, M.
2009-01-01
The paper presents a study examining the role of working memory in quantifier verification. We created situations similar to the span task to compare numerical quantifiers of low and high rank, parity quantifiers and proportional quantifiers. The results enrich and support the data obtained
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Uncertain CERN cash means UK physicists face grant freeze.
1996-01-01
Britain's funding agency Particle Physics and Astronomy Research Council is uncertain about its ability to cover membership costs to the European Laboratory for Particle Physics (CERN). This has resulted in suspension of research grants to university physicists and astronomers. Funding will be available only for genuine hardship, and for major national and international astronomical projects that have already been sanctioned. The new four-year rolling grants to university-based particle physics group is withheld.
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Density Estimation in Several Populations With Uncertain Population Membership
Ma, Yanyuan
2011-09-01
We devise methods to estimate probability density functions of several populations using observations with uncertain population membership, meaning from which population an observation comes is unknown. The probability of an observation being sampled from any given population can be calculated. We develop general estimation procedures and bandwidth selection methods for our setting. We establish large-sample properties and study finite-sample performance using simulation studies. We illustrate our methods with data from a nutrition study.
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R&D Collaboration with Uncertain Intellectual Property Rights
DEFF Research Database (Denmark)
Czarnitzki, Dirk; Hussinger, Katrin; Schneider, Cédric
2015-01-01
—uncertain intellectual property rights (IPRs) lead to reduced collaboration between firms and can, hence, hinder knowledge production. This has implications for technology policy as R&D collaborations are exempt from antitrust legislation in order to increase R&D in the economy. We argue that a functional IPR system......Patent pendencies create uncertainty in research and development (R&D) collaboration, which can result in a threat of expropriation of unprotected knowledge, reduced bargaining power and enhanced search costs. We show that—depending of the type of collaboration partner and the size of the company...
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R&D Collaboration with Uncertain Intellectual Property Rights
DEFF Research Database (Denmark)
Czarnitzki, Dirk; Hussinger, Katrin; Schneider, Cédric
- uncertain intellectual property rights (IPR) lead to reduced collaboration between firms and may hinder the production of knowledge. This has implications for technology policy as R&D collaborations are exempt from anti-trust legislation in order to increase R&D in the economy. We argue that a functional......Patent pendencies create uncertainty in research and development (R&D) collaboration agreements, resulting in a threat of expropriation of unprotected knowledge by potential partners, reduced bargaining power and enhanced search costs. In this paper, we show that - depending of the type of partner...
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Ch. Vlek (Charles)
2009-01-01
textabstractPrecautionary judgment, decision, and action are needed in situations involving serious uncertain risk. Examples are mountain climbing, nanotechnology, global warming, and international terrorism. The history of the Precautionary Principle (PP) shows that its proponents and opponents
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On the C(R) stability of uncertain singularly perturbed systems
International Nuclear Information System (INIS)
Sun, Y.-J.
2009-01-01
In this paper, a simple criterion for the C(R) stability of uncertain singularly perturbed systems is proposed. Such a criterion can be easily checked by some algebraic inequality. The upper bound of the singular perturbation parameter ε is also given by estimating the unique positive zero of specific function. Finally, a numerical example is provided to illustrate the main result
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Identifying and Quantifying Emergent Behavior Through System of Systems Modeling and Simulation
2015-09-01
the similarities and differences between Agent Based Modeling ( ABM ) and Equation Based Modeling (EBM). Both modeling approaches “simulate a system by...entities. For the latter difference, EBM focuses on the system level observables, while ABM defines behaviors at the individual agent level and observes...EMERGENT BEHAVIOR THROUGH SYSTEM OF SYSTEMS MODELING AND SIMULATION by Mary Ann Cummings September 2015 Dissertation Supervisor: Man-Tak Shing
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On existence of control for a class of uncertain dynamical systems ...
African Journals Online (AJOL)
In this paper we prove the existence of control for input bounded uncertain dynamical system, modeled on Euclidean spaces of dimensions n and m. We apply the Conjugate Gradient Method (C.G.M) in generating algorithms to compute control signals for the class of problem under consideration. Keywords: Control ...
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On robust control of uncertain chaotic systems: a sliding-mode synthesis via chaotic optimization
International Nuclear Information System (INIS)
Lu Zhao; Shieh Leangsan; Chen GuanRong
2003-01-01
This paper presents a novel Lyapunov-based control approach which utilizes a Lyapunov function of the nominal plant for robust tracking control of general multi-input uncertain nonlinear systems. The difficulty of constructing a control Lyapunov function is alleviated by means of predefining an optimal sliding mode. The conventional schemes for constructing sliding modes of nonlinear systems stipulate that the system of interest is canonical-transformable or feedback-linearizable. An innovative approach that exploits a chaotic optimizing algorithm is developed thereby obtaining the optimal sliding manifold for the control purpose. Simulations on the uncertain chaotic Chen's system illustrate the effectiveness of the proposed approach
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Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian
2011-04-01
This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.
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DEFF Research Database (Denmark)
Pakazad, Sina Khoshfetrat; Hansson, Anders; Andersen, Martin Skovgaard
2013-01-01
We consider a class of convex feasibility problems where the constraints that describe the feasible set are loosely coupled. These problems arise in robust stability analysis of large, weakly interconnected uncertain systems. To facilitate distributed implementation of robust stability analysis o...
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Koorehdavoudi, Hana; Bogdan, Paul
2016-06-01
Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.
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Towards electricity markets accommodating uncertain offers
DEFF Research Database (Denmark)
Papakonstantinou, Athanasios; Pinson, Pierre
2014-01-01
formulation of an electricity market, based on the Continuous Ranked Probability Score (CRPS) reduces the impact of poor estimates for both the stochastic producers and the system operator. We introduce a simulation setting which first demonstrates that impact and then proceed to illustrate the main features......The use of renewable energy sources of energy and in particular wind and solar has been on the rise over the last decades with plans to increase it even more. Such developments introduce significant challenges in existing power systems and can result in high electricity prices and costly...... infrastructure investments. In this paper we propose a new electricity market mechanism whereby the uncertain and dynamic nature of wind power and other stochastic sources is embedded in the market mechanism itself, by modelling producers’ bids as probabilistic estimates. An extension on the bilevel programming...
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75 FR 78160 - Requirement of a Statement Disclosing Uncertain Tax Positions
2010-12-15
... amendments to the Income Tax Regulations (26 CFR part 1) under section 6012 relating to the returns of income... every person liable for income tax to make the returns required by regulation. Section 6012 requires... corporations to file a schedule disclosing uncertain tax positions related to the tax return as required by the...
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Simulation optimization based ant colony algorithm for the uncertain quay crane scheduling problem
Directory of Open Access Journals (Sweden)
Naoufal Rouky
2019-01-01
Full Text Available This work is devoted to the study of the Uncertain Quay Crane Scheduling Problem (QCSP, where the loading /unloading times of containers and travel time of quay cranes are considered uncertain. The problem is solved with a Simulation Optimization approach which takes advantage of the great possibilities offered by the simulation to model the real details of the problem and the capacity of the optimization to find solutions with good quality. An Ant Colony Optimization (ACO meta-heuristic hybridized with a Variable Neighborhood Descent (VND local search is proposed to determine the assignments of tasks to quay cranes and the sequences of executions of tasks on each crane. Simulation is used inside the optimization algorithm to generate scenarios in agreement with the probabilities of the distributions of the uncertain parameters, thus, we carry out stochastic evaluations of the solutions found by each ant. The proposed optimization algorithm is tested first for the deterministic case on several well-known benchmark instances. Then, in the stochastic case, since no other work studied exactly the same problem with the same assumptions, the Simulation Optimization approach is compared with the deterministic version. The experimental results show that the optimization algorithm is competitive as compared to the existing methods and that the solutions found by the Simulation Optimization approach are more robust than those found by the optimization algorithm.
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Decision Making Under Uncertain Categorization
Directory of Open Access Journals (Sweden)
Stephanie Ying-Fen Chen
2014-09-01
Full Text Available Two experiments investigated how category information is used in decision making under uncertainty and whether the framing of category information influences how it is used. Subjects were presented with vignettes in which the categorization of a critical item was ambiguous and were asked to choose among a set of actions with the goal of attaining the desired outcome for the main character in the story. The normative decision making strategy was to base the decision on all possible categories; however, research on a related topic, category-based induction, has found that people often only consider a single category when making predictions when categorization is uncertain. These experiments found that subjects tend to consider multiple categories when making decisions, but do so both when it is and is not appropriate, suggesting that use of multiple categories is not driven by an understanding of what categories are and are not relevant to the decision. Similarly, although a framing manipulation increased the rate of multiple-category use, it did so in situations in which multiple-category use was and was not appropriate.
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A framework for the analysis of vibrations of structures with uncertain attachments
International Nuclear Information System (INIS)
Li, Shuo; Mace, Brian R.; Halkyard, Roger; Ferguson, Neil S.
2016-01-01
Attachments affect the dynamic response of an assembled structure. When engineers are modelling structures, small attachments will often not be included in the “bare” model, especially in the initial design stages. The location of these attachments might be poorly known, yet they affect the response of the structure. This paper considers how attachments jointed to the structure at uncertain points, can be included in the dynamic model of a structure. Two approaches are proposed. In the time domain, a combination of component mode synthesis, characteristic constraint modes and modal analysis gives a computationally efficient basis for subsequent analysis using, for example, Monte Carlo simulation. The frequency domain approach is based on assembly of frequency response functions of bare structure and attachment. Numerical examples of a beam and a plate with a point mass added at an uncertain location are considered and predictions compared with experiment results. (paper)
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Grey-Theory-Based Optimization Model of Emergency Logistics Considering Time Uncertainty.
Qiu, Bao-Jian; Zhang, Jiang-Hua; Qi, Yuan-Tao; Liu, Yang
2015-01-01
Natural disasters occur frequently in recent years, causing huge casualties and property losses. Nowadays, people pay more and more attention to the emergency logistics problems. This paper studies the emergency logistics problem with multi-center, multi-commodity, and single-affected-point. Considering that the path near the disaster point may be damaged, the information of the state of the paths is not complete, and the travel time is uncertainty, we establish the nonlinear programming model that objective function is the maximization of time-satisfaction degree. To overcome these drawbacks: the incomplete information and uncertain time, this paper firstly evaluates the multiple roads of transportation network based on grey theory and selects the reliable and optimal path. Then simplify the original model under the scenario that the vehicle only follows the optimal path from the emergency logistics center to the affected point, and use Lingo software to solve it. The numerical experiments are presented to show the feasibility and effectiveness of the proposed method.
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The role of computed tomography in uncertain obstructive jaundice
International Nuclear Information System (INIS)
Saito, Yoshihiro; Yoshino, Toyoaki; Takayanagi, Ryuichi; Negishi, Ken; Tanaka, Teruhiko; Ito, Ichiro.
1985-01-01
42 patients with uncertain obstructive jaundice were examined by computed tomography (CT). CT correctly diagnosed obstructive jaundice in 97% of 37 proven cases and the accuracy of CT in determing the level of obstruction was also 97%. But the sensitivity of CT in determing the cause of obstructive jaundice was 62.5%, particularly poor in common bile duct stone (61.5%), inflammation of common bile duct (0%), and common bile duct carcinoma (50%). All cases of diagnosed malignant tumors were inoperable. (author)
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Path Integration Applied to Structural Systems with Uncertain Properties
DEFF Research Database (Denmark)
Nielsen, Søren R.K.; Köylüoglu, H. Ugur
Path integration (cell-to-cell mapping) method is applied to evaluate the joint probability density function (jpdf) of the response of the structural systems, with uncertain properties, subject to white noise excitation. A general methodology to deal with uncertainties is outlined and applied...... to the friction controlled slip of a structure on a foundation where the friction coefficient is modelled as a random variable. Exact results derived using the total probability theorem are compared to the ones obtained via path integration....
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[Treatment of aerobic vaginitis and clinically uncertain causes of vulvovaginal discomfort].
Cepický, P; Malina, J; Kuzelová, M
2003-11-01
The treatment of clinically uncertain conditions of vaginal discomforts with a mixed preparation of nifuratel + nystatin (Macmiror complex) and the relation of uncertain conditions to aerobic vaginitis. A prospective study. Gynecology-Obstetrics Outpatient Department LEVRET Ltd., AescuLab Ltd., Laboratory of Microbiology, Prague. 50 women with vaginal discomfort, causes of which had not been clarified by gynecological examination, determination of pH and the amine test, were examined by vaginal smears using microscopy. The results were evaluated in relation to aerobic vaginitis in a pure form or in combination with other nosological units. The authors also evaluated results of therapy by oral nifuratel (Macmiror tbl) 3 x 200 mg daily and a vaginal combined preparation containing nifuratel 500 mg + nystatin 200 kIU (Macmiror complex 500 glo vag) for the period of 7 days. In 50 women candida was demonstrated 24 times, presence of key cells 11 times, lactobacillus nine times with more than 50 in the field, six women were affected by aerobic vaginitis. In all these cases the pH was 4.8 or higher, leukocytes were significantly represented in all cases (> 15 in the field), as well as gram-negative bacteria and/or cocci (> 30 in the field), indicating a combined picture of mycosis, anaerobic vaginosis or lactobacillosis with aerobic vaginitis. The therapy was successful in all cases, the relapse of complaints during one month occurred in three cases. Aerobic vaginitis in a pure form or with anaerobic vaginosis, mycosis or lactobacillosis is frequently concealed under clinically uncertain pictures of vulvo-vaginal discomfort. The therapy by a combination of nifurated 3 x 200 mg orally together with the combined vaginal preparation nifuratel 500 mg + nystatin 200 kIU for the period of 7 days exerts high effect and a low number of relapses.
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A MODIFIED GENETIC ALGORITHM FOR FINDING FUZZY SHORTEST PATHS IN UNCERTAIN NETWORKS
Directory of Open Access Journals (Sweden)
A. A. Heidari
2016-06-01
Full Text Available In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.
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Antonopoulou, Katerina; Nandhakumar, Joe; Begkos, Christos
2016-01-01
In this paper we explore the emergence of business model for digital innovation projects without predetermined usage and uncertain market potential. We studied a firm, which was producing and launching digital platforms for managing organizational operations. Drawing on a case study of developing this digital platform, we identified three recurring calculative and narrative practices: ideating; concocting; aligning. We argue that through these practices various epistemic objects (which we cal...
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Using reference trajectories to predicted uncertain systems: exemplified on a power plant
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Stoustrup, Jakob; Mataji, B.
2007-01-01
This paper presents a method for prediction of uncertain closed loop systems, where the uncertainties are depending on operating points. Such model uncertainties are often present when complicated non-linear systems are predicted. The method uses precomputed mean and variances of the prediction e...
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Forest Conservation in Costa Rica: when nonuse benefits are uncertain but rising
Bulte, E.H.; Soest, van D.P.; Kooten, van G.C.; Schipper, R.A.
2002-01-01
Stochastic dynamic programming is used to investigate optimal holding of primary tropical forest in humid Costa Rica when future nonuse benefits of forest conservation are uncertain and increasing. The quasi-option value of maintaining primary forests is included as a component of investment in
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Quantifying Supply Risk at a Cellulosic Biorefinery
Energy Technology Data Exchange (ETDEWEB)
Hansen, Jason K [Idaho National Laboratory; Jacobson, Jacob Jordan [Idaho National Laboratory; Cafferty, Kara Grace [Idaho National Laboratory; Lamers, Patrick [Idaho National Laboratory; Roni, MD S [Idaho National Laboratory
2015-03-01
In order to increase the sustainability and security of the nation’s energy supply, the U.S. Department of Energy through its Bioenergy Technology Office has set a vision for one billion tons of biomass to be processed for renewable energy and bioproducts annually by the year 2030. The Renewable Fuels Standard limits the amount of corn grain that can be used in ethanol conversion sold in the U.S, which is already at its maximum. Therefore making the DOE’s vision a reality requires significant growth in the advanced biofuels industry where currently three cellulosic biorefineries convert cellulosic biomass to ethanol. Risk mitigation is central to growing the industry beyond its infancy to a level necessary to achieve the DOE vision. This paper focuses on reducing the supply risk that faces a firm that owns a cellulosic biorefinery. It uses risk theory and simulation modeling to build a risk assessment model based on causal relationships of underlying, uncertain, supply driving variables. Using the model the paper quantifies supply risk reduction achieved by converting the supply chain from a conventional supply system (bales and trucks) to an advanced supply system (depots, pellets, and trains). Results imply that the advanced supply system reduces supply system risk, defined as the probability of a unit cost overrun, from 83% in the conventional system to 4% in the advanced system. Reducing cost risk in this nascent industry improves the odds of realizing desired growth.
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Quantifying Supply Risk at a Cellulosic Biorefinery
Energy Technology Data Exchange (ETDEWEB)
Hansen, Jason K.; Jacobson, Jacob J.; Cafferty, Kara G.; Lamers, Patrick; Roni, Mohammad S.
2015-07-01
In order to increase the sustainability and security of the nation’s energy supply, the U.S. Department of Energy through its Bioenergy Technology Office has set a vision for one billion tons of biomass to be processed for renewable energy and bioproducts annually by the year 2030. The Renewable Fuels Standard limits the amount of corn grain that can be used in ethanol conversion sold in the U.S, which is already at its maximum. Therefore making the DOE’s vision a reality requires significant growth in the advanced biofuels industry where currently three cellulosic biorefineries convert cellulosic biomass to ethanol. Risk mitigation is central to growing the industry beyond its infancy to a level necessary to achieve the DOE vision. This paper focuses on reducing the supply risk that faces a firm that owns a cellulosic biorefinery. It uses risk theory and simulation modeling to build a risk assessment model based on causal relationships of underlying, uncertain, supply driving variables. Using the model the paper quantifies supply risk reduction achieved by converting the supply chain from a conventional supply system (bales and trucks) to an advanced supply system (depots, pellets, and trains). Results imply that the advanced supply system reduces supply system risk, defined as the probability of a unit cost overrun, from 83% in the conventional system to 4% in the advanced system. Reducing cost risk in this nascent industry improves the odds of realizing desired growth.
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Quantifying motion for pancreatic radiotherapy margin calculation
International Nuclear Information System (INIS)
Whitfield, Gillian; Jain, Pooja; Green, Melanie; Watkins, Gillian; Henry, Ann; Stratford, Julie; Amer, Ali; Marchant, Thomas; Moore, Christopher; Price, Patricia
2012-01-01
Background and purpose: Pancreatic radiotherapy (RT) is limited by uncertain target motion. We quantified 3D patient/organ motion during pancreatic RT and calculated required treatment margins. Materials and methods: Cone-beam computed tomography (CBCT) and orthogonal fluoroscopy images were acquired post-RT delivery from 13 patients with locally advanced pancreatic cancer. Bony setup errors were calculated from CBCT. Inter- and intra-fraction fiducial (clip/seed/stent) motion was determined from CBCT projections and orthogonal fluoroscopy. Results: Using an off-line CBCT correction protocol, systematic (random) setup errors were 2.4 (3.2), 2.0 (1.7) and 3.2 (3.6) mm laterally (left–right), vertically (anterior–posterior) and longitudinally (cranio-caudal), respectively. Fiducial motion varied substantially. Random inter-fractional changes in mean fiducial position were 2.0, 1.6 and 2.6 mm; 95% of intra-fractional peak-to-peak fiducial motion was up to 6.7, 10.1 and 20.6 mm, respectively. Calculated clinical to planning target volume (CTV–PTV) margins were 1.4 cm laterally, 1.4 cm vertically and 3.0 cm longitudinally for 3D conformal RT, reduced to 0.9, 1.0 and 1.8 cm, respectively, if using 4D planning and online setup correction. Conclusions: Commonly used CTV–PTV margins may inadequately account for target motion during pancreatic RT. Our results indicate better immobilisation, individualised allowance for respiratory motion, online setup error correction and 4D planning would improve targeting.
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Technology Proliferation: Acquisition Strategies and Opportunities for an Uncertain Future
2018-04-20
COVERED (From - To) 07/31/17 to 04/09/18 Technology Proliferation: Acquisition Strategies and Opportunities for an Uncertain Future Colonel Heather A...efficient and expeditious fielding of technologically superior capabilities. In today’s environment, it is commonplace for private industry to be the...first to develop and deploy technologies that can be adopted for defense systems. The result is that the Department of Defense (DoD) is largely a
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Directory of Open Access Journals (Sweden)
Yilmaz Asli
2011-08-01
Full Text Available Abstract Mesothelioma of tunica vaginalis is a rare neoplasm, typically demonstrating frankly malignant morphology and aggressive behavior. Rare cases of well-differentiated papillary mesotheliomas have also been reported, which, in contrast, demonstrate indolent behavior. There are, however, cases which do not fit into the well-differentiated or diffuse malignant mesothelioma categories and can be considered mesothelioma of tunica vaginalis of "uncertain malignant potential", which is an emerging diagnostic category. A 57-year-old man presented with a neoplasm in a hydrocele sac. The neoplasm was non-invasive, but showed focal complex and solid growth and it was difficult to categorize either as well-differentiated papillary mesotheliomas or malignant mesothelioma. After the initial limited resection, the patient underwent radical orchiectomy with hemiscrotectomy and is alive and without disease progression after 6 years. Documentation of these rare tumors will allow their distinction from true malignant mesotheliomas and will facilitate the development of specific treatment recommendations.
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Robust lyapunov controller for uncertain systems
Laleg-Kirati, Taous-Meriem
2017-02-23
Various examples of systems and methods are provided for Lyapunov control for uncertain systems. In one example, a system includes a process plant and a robust Lyapunov controller configured to control an input of the process plant. The robust Lyapunov controller includes an inner closed loop Lyapunov controller and an outer closed loop error stabilizer. In another example, a method includes monitoring a system output of a process plant; generating an estimated system control input based upon a defined output reference; generating a system control input using the estimated system control input and a compensation term; and adjusting the process plant based upon the system control input to force the system output to track the defined output reference. An inner closed loop Lyapunov controller can generate the estimated system control input and an outer closed loop error stabilizer can generate the system control input.
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International Nuclear Information System (INIS)
Jing, Wang; Zhen-Yu, Tan; Xi-Kui, Ma; Jin-Feng, Gao
2009-01-01
A novel adaptive observer-based control scheme is presented for synchronization and suppression of a class of uncertain chaotic system. First, an adaptive observer based on an orthogonal neural network is designed. Subsequently, the sliding mode controllers via the proposed adaptive observer are proposed for synchronization and suppression of the uncertain chaotic systems. Theoretical analysis and numerical simulation show the effectiveness of the proposed scheme. (general)
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On the robust optimization to the uncertain vaccination strategy problem
International Nuclear Information System (INIS)
Chaerani, D.; Anggriani, N.; Firdaniza
2014-01-01
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented
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Global sensitivity analysis in stochastic simulators of uncertain reaction networks.
Navarro Jimenez, M; Le Maître, O P; Knio, O M
2016-12-28
Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.
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On the robust optimization to the uncertain vaccination strategy problem
Energy Technology Data Exchange (ETDEWEB)
Chaerani, D., E-mail: d.chaerani@unpad.ac.id; Anggriani, N., E-mail: d.chaerani@unpad.ac.id; Firdaniza, E-mail: d.chaerani@unpad.ac.id [Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Padjadjaran Indonesia, Jalan Raya Bandung Sumedang KM 21 Jatinangor Sumedang 45363 (Indonesia)
2014-02-21
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.
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Global sensitivity analysis in stochastic simulators of uncertain reaction networks
Navarro, María
2016-12-26
Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.
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Hellberg, Samantha N; Levit, Jeremy D; Robinson, Mike J F
2018-01-30
Gambling disorder (GD) frequently co-occurs with alcohol use and anxiety disorders, suggesting possible shared mechanisms. Recent research suggests reward uncertainty may powerfully enhance attraction towards reward cues. Here, we examined the effects of adolescent ethanol exposure, anxiety, and reward uncertainty on cue-triggered motivation. Male and female adolescent rats were given free access to ethanol or control jello for 20days. Following withdrawal, rats underwent autoshaping on a certain (100%-1) or uncertain (50%-1-2-3) reward contingency, followed by single-session conditioned reinforcement and progressive ratio tasks, and 7days of omission training, during which lever pressing resulted in omission of reward. Finally, anxiety levels were quantified on the elevated plus maze. Here, we found that uncertainty narrowed cue attraction by significantly increasing the ratio of sign-tracking to goal-tracking, particularly amongst control jello and high anxiety animals, but not in animals exposed to ethanol during adolescence. In addition, attentional bias towards the lever cue was more persistent under uncertain conditions following omission training. We also found that females consumed more ethanol, and that uncertainty mitigated the anxiolytic effects of ethanol exposure observed in high ethanol intake animals under certainty conditions. Our results further support that reward uncertainty biases attraction towards reward cues, suggesting also that heightened anxiety may enhance vulnerability to the effects of reward uncertainty. Chronic, elevated alcohol consumption may contribute to heightened anxiety levels, while high anxiety may promote the over-attribution of incentive value to reward cues, highlighting possible mechanisms that may drive concurrent anxiety, heavy drinking, and problematic gambling. Copyright © 2017 Elsevier B.V. All rights reserved.
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Quantifying the Modern City: Emerging Technologies and Big Data for Active Living Research
Directory of Open Access Journals (Sweden)
Deepti Adlakha
2017-05-01
Full Text Available Opportunities and infrastructure for active living are an important aspect of a community’s design, livability, and health. Features of the built environment influence active living and population levels of physical activity, but objective study of the built environment influence on active living behaviors is challenging. The use of emerging technologies for active living research affords new and promising means to obtain objective data on physical activity behaviors and improve the precision and accuracy of measurements. This is significant for physical activity promotion because precise measurements can enable detailed examinations of where, when, and how physical activity behaviors actually occur, thus enabling more effective targeting of particular behavior settings and environments. The aim of this focused review is to provide an overview of trends in emerging technologies that can profoundly change our ability to understand environmental determinants of active living. It discusses novel technological approaches and big data applications to measure and track human behaviors that may have broad applications across the fields of urban planning, public health, and spatial epidemiology.
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Directory of Open Access Journals (Sweden)
Li-lian Huang
2013-01-01
Full Text Available The synchronization of nonlinear uncertain chaotic systems is investigated. We propose a sliding mode state observer scheme which combines the sliding mode control with observer theory and apply it into the uncertain chaotic system with unknown parameters and bounded interference. Based on Lyapunov stability theory, the constraints of synchronization and proof are given. This method not only can realize the synchronization of chaotic systems, but also identify the unknown parameters and obtain the correct parameter estimation. Otherwise, the synchronization of chaotic systems with unknown parameters and bounded external disturbances is robust by the design of the sliding surface. Finally, numerical simulations on Liu chaotic system with unknown parameters and disturbances are carried out. Simulation results show that this synchronization and parameter identification has been totally achieved and the effectiveness is verified very well.
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Directory of Open Access Journals (Sweden)
John Rice
2008-11-01
Full Text Available This paper provides some strong support for existing literature in an under-researched context (the emerging economies of the former Soviet Union and Central and Eastern Europe. We develop and apply a model linking Board formation and environmental uncertainty, finding some partial support for our anticipated relationships in the area of Board establishment and perceived financial sector uncertainly, although no support for our anticipated relationship between governmental sector uncertainty and Board formation. research is supportive of the broad assertion that strategy in emerging economies is different and a ‘one size fits all’ (generally American approach to the questions we ask regarding strategy in emerging regions will rarely provide accurate insights for management academics and practitioners with an interest in understanding and improving management decisions in the context of emerging economies
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Green taxes and uncertain timing of technological change
International Nuclear Information System (INIS)
Aronsson, T.
2001-01-01
This paper concerns the role of environmental taxation in a model with endogenous technological change, where the latter implies that natural inputs become more productive. The timing of technological change is, in turn, uncertain and the likelihood of discovering the new technology is related to the amount of resources spent on R and D. The analysis is based on a dynamic general equilibrium model. One purpose of the paper is to design a policy so as to internalize the external effects arising from pollution and R and D. Another is to develop cost benefit rules for green tax reforms, when the initial equilibrium is suboptimal
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Uncertain Dynamics, Correlation Effects, and Robust Investment Decisions
DEFF Research Database (Denmark)
Flor, Christian Riis; Hesel, Søren
2015-01-01
We analyze a firm's investment problem when the dynamics of project value and investment cost are uncertain. We provide an explicit solution using a robust method for an ambiguity averse firm taking this into account. Ambiguity aversion regarding a common risk factor impacts differently than...... ambiguity aversion regarding investment cost residual risk. Correlation between project value and investment cost matters; ambiguity aversion regarding common risk can decrease the investment probability only if correlation is positive. Ambiguity aversion regarding residual risk always increases...... the investment probability. When only project value is risky, volatility can monotonically decrease the investment threshold; this does not hold with the multiple prior method....
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Funk, Sebastian; Bogich, Tiffany L; Jones, Kate E; Kilpatrick, A Marm; Daszak, Peter
2013-01-01
The proper allocation of public health resources for research and control requires quantification of both a disease's current burden and the trend in its impact. Infectious diseases that have been labeled as "emerging infectious diseases" (EIDs) have received heightened scientific and public attention and resources. However, the label 'emerging' is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled "emerging," and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health.
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Adaptive synchronization of uncertain chaotic colpitts oscillators based on parameter identification
International Nuclear Information System (INIS)
Fotsin, H.B.; Daafouz, J.
2005-01-01
This Letter uses systematic tools from recent papers to design non-linear observers for synchronization of a chaotic colpitts oscillator both in the non adaptive and adaptive cases. It is shown that all parameters of a totally uncertain model of the oscillator can be estimated through adaptive synchronization. A strategy for practical implementation of a secure communication strategy is also discussed
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Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.
Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo
2015-01-01
Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency.
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Information Extraction, Data Integration, and Uncertain Data Management: The State of The Art
Habib, Mena Badieh; van Keulen, Maurice
2011-01-01
Information Extraction, data Integration, and uncertain data management are different areas of research that got vast focus in the last two decades. Many researches tackled those areas of research individually. However, information extraction systems should have integrated with data integration
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Risk assessment of salt contamination of groundwater under uncertain aquifer properties
Litvinenko, Alexander
2017-10-01
One of the central topics in hydrogeology and environmental science is the investigation of salinity-driven groundwater flow in heterogeneous porous media. Our goals are to model and to predict pollution of water resources. We simulate a density driven groundwater flow with uncertain porosity and permeability. This strongly non-linear model describes the unstable transport of salt water with building ‘fingers’-shaped patterns. The computation requires a very fine unstructured mesh and, therefore, high computational resources. We run the highly-parallel multigrid solver, based on ug4, on supercomputer Shaheen II. A MPI-based parallelization is done in the geometrical as well as in the stochastic spaces. Every scenario is computed on 32 cores and requires a mesh with ~8M grid points and 1500 or more time steps. 200 scenarios are computed concurrently. The total number of cores in parallel computation is 200x32=6400. The main goal of this work is to estimate propagation of uncertainties through the model, to investigate sensitivity of the solution to the input uncertain parameters. Additionally, we demonstrate how the multigrid ug4-based solver can be applied as a black-box in the uncertainty quantification framework.
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International Nuclear Information System (INIS)
Park, Jin Kyun; Jung, Won Dea
2006-11-01
Previous studies have continuously pointed out that human performance is a decisive factor affecting the safety of complicated process systems. Subsequently, as the result of extensive efforts, it has been revealed that the provision of procedures is one of the most effective countermeasures, especially if human operators have to carry out their tasks under a very stressful environment. That is, since good procedures are helpful to not only enhance the performance of human operators but also the reduction of the possibility of a human error through stipulating detailed tasks to be done by human operators. Ironically, it has been emphasized that the performance of human operators could be impaired due to complicated procedures, because procedures directly govern the physical as well as cognitive behavior of human operators by institutionalizing detailed actions. Therefore, it is a prerequisite to develop a systematic framework that properly evaluate the complexity of tasks described in procedures. For this reason, a measure called TACOM (Task Complexity) that can quantify the complexity of emergency tasks described in the emergency operating procedures (EOPs) of NPPs has been developed. In this report, a technical background as well as practical steps to quantify the complexity of tasks were presented with a series of studies that were conducted to ensure the validity of the TACOM measure. As a result of validation studies, since it is shown that the TACOM measure seem to properly quantify the complexity of emergency tasks, it is desirable that the TACOM measure plays an important role in improving the performance of human operators
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Energy Technology Data Exchange (ETDEWEB)
Park, Jin Kyun; Jung, Won Dea
2006-11-15
Previous studies have continuously pointed out that human performance is a decisive factor affecting the safety of complicated process systems. Subsequently, as the result of extensive efforts, it has been revealed that the provision of procedures is one of the most effective countermeasures, especially if human operators have to carry out their tasks under a very stressful environment. That is, since good procedures are helpful to not only enhance the performance of human operators but also the reduction of the possibility of a human error through stipulating detailed tasks to be done by human operators. Ironically, it has been emphasized that the performance of human operators could be impaired due to complicated procedures, because procedures directly govern the physical as well as cognitive behavior of human operators by institutionalizing detailed actions. Therefore, it is a prerequisite to develop a systematic framework that properly evaluate the complexity of tasks described in procedures. For this reason, a measure called TACOM (Task Complexity) that can quantify the complexity of emergency tasks described in the emergency operating procedures (EOPs) of NPPs has been developed. In this report, a technical background as well as practical steps to quantify the complexity of tasks were presented with a series of studies that were conducted to ensure the validity of the TACOM measure. As a result of validation studies, since it is shown that the TACOM measure seem to properly quantify the complexity of emergency tasks, it is desirable that the TACOM measure plays an important role in improving the performance of human operators.
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基于不确定时间区间TBN的洪水漫坝风险分析%Risk Analysis of Flood Overtopping Based on Uncertain Time Interval TBN
Institute of Scientific and Technical Information of China (English)
涂传飞; 王剑; 王红卫
2013-01-01
In the process of flood overtopping,the uncertainty of events' duration time caused by state uncertainty of natural conditions,dam and emergency measures,and the effect of emergency measures are both key factors that affect the flood overtopping risk.The traditional time interval was transformed into an uncertain time interval and an uncertain time interval Temporal Bayesian Network (TBN) was proposed.After that,a new inferring algorithm of the TBN was discussed.On the basis,flood overtopping risk analysis model,in which emergency measures were considered,was established.Finally,the simulation result shows that the model can accumulate information,judge the importance of each emergency measure,express the state uncertainty and time uncertainty which both exist in the process of flood overtopping and accordingly increase the accuracy of flood overtopping risk analysis.%洪水漫坝过程中,自然条件、坝体及应急处置等状态的不确定性所导致的事件持续时间的不确定性,以及应急处置措施的效果是影响漫坝风险的关键因素.首先将传统时间区间改造为不确定时间区间,提出了一种不确定时间区间时间贝叶斯网络(TBN),并推导了该TBN的推理算法.在此基础上构建了考虑应急处置措施的洪水漫坝风险分析模型.仿真结果表明该模型具有信息时间累积能力,能判断各应急处置措施的重要程度,表达了洪水漫坝过程中同时存在的状态不确定性和时间不确定性,提高了漫坝风险分析的精度.
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IP Controller Design for Uncertain Two-Mass Torsional System Using Time-Frequency Analysis
Directory of Open Access Journals (Sweden)
Jing Cui
2018-01-01
Full Text Available With the development of industrial production, drive systems are demanded for larger inertias of motors and load machines, whereas shafts should be lightweight. In this situation, it will excite mechanical vibrations in load side, which is harmful for industrial production when the motor works. Because of the complexity of the flexible shaft, it is often difficult to calculate stiffness coefficient of the flexible shaft. Furthermore, only the velocity of driving side could be measured, whereas the driving torque, the load torque, and the velocity of load side are immeasurable. Therefore, it is inconvenient to design the controller for the uncertain system. In this paper, a low-order IP controller is designed for an uncertain two-mass torsional system based on polynomial method and time-frequency analysis (TFA. IP controller parameters are calculated by inertias of driving side and load side as well as the resonant frequency based on polynomial method. Therein, the resonant frequency is identified using the time-frequency analysis (TFA of the velocity step response of the driving side under the open-loop system state, which can not only avoid harmful persistent start-stop excitation signal of the traditional method, but also obtain high recognition accuracy under the condition of weak vibration signal submerged in noise. The effectiveness of the designed IP controller is verified by groups of experiments. Experimental results show that good performance for vibration suppression is obtained for uncertain two-mass torsional system in a medium-low shaft stiffness condition.
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Knobloch, Hans Wilhelm
2014-01-01
This book presents a survey on recent attempts to treat classical regulator design problems in case of an uncertain dynamics. It is shown that source of the uncertainty can be twofold: (i) The system is under the influence of an exogenous disturbance about which one has only incomplete - or none - information. (ii) A portion of the dynamical law is unspecified - due to imperfect modeling. Both cases are described by the state space model in a unified way “Disturbance Attenuation for Uncertain Control Systems” presents a variety of approaches to the design problem in the presence of a (partly) unknown disturbance signal. There is a clear philosophy underlying each approach which can be characterized by either one of the following terms: Adaptive Control, Worst Case Design, Dissipation Inequalities. .
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Design of Robust AMB Controllers for Rotors Subjected to Varying and Uncertain Seal Forces
DEFF Research Database (Denmark)
Lauridsen, Jonas Skjødt; Santos, Ilmar
2017-01-01
This paper demonstrates the design and simulation results of model based controllers for AMB systems, subjectedto uncertain and changing dynamic seal forces. Specifically, a turbocharger with a hole-pattern seal mounted acrossthe balance piston is considered. The dynamic forces of the seal, which...... are dependent on the operational conditions,have a significant effect on the overall system dynamics. Furthermore, these forces are considered uncertain.The nominal and the uncertainty representation of the seal model are established using results from conventionalmodelling approaches, i.e. CFD and Bulkflow......, and experimental results. Three controllers are synthesized: I) AnH∞ controller based on nominal plant representation, II) A µ controller, designed to be robust against uncertaintiesin the dynamic seal model and III) a Linear Parameter Varying (LPV) controller, designed to provide a unifiedperformance over a large...
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Intelligent diagnosis of jaundice with dynamic uncertain causality graph model*
Hao, Shao-rui; Geng, Shi-chao; Fan, Lin-xiao; Chen, Jia-jia; Zhang, Qin; Li, Lan-juan
2017-01-01
Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A “chaining” inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure. PMID:28471111
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Intelligent diagnosis of jaundice with dynamic uncertain causality graph model.
Hao, Shao-Rui; Geng, Shi-Chao; Fan, Lin-Xiao; Chen, Jia-Jia; Zhang, Qin; Li, Lan-Juan
2017-05-01
Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A "chaining" inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.
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Strict Constraint Feasibility in Analysis and Design of Uncertain Systems
Crespo, Luis G.; Giesy, Daniel P.; Kenny, Sean P.
2006-01-01
This paper proposes a methodology for the analysis and design optimization of models subject to parametric uncertainty, where hard inequality constraints are present. Hard constraints are those that must be satisfied for all parameter realizations prescribed by the uncertainty model. Emphasis is given to uncertainty models prescribed by norm-bounded perturbations from a nominal parameter value, i.e., hyper-spheres, and by sets of independently bounded uncertain variables, i.e., hyper-rectangles. These models make it possible to consider sets of parameters having comparable as well as dissimilar levels of uncertainty. Two alternative formulations for hyper-rectangular sets are proposed, one based on a transformation of variables and another based on an infinity norm approach. The suite of tools developed enable us to determine if the satisfaction of hard constraints is feasible by identifying critical combinations of uncertain parameters. Since this practice is performed without sampling or partitioning the parameter space, the resulting assessments of robustness are analytically verifiable. Strategies that enable the comparison of the robustness of competing design alternatives, the approximation of the robust design space, and the systematic search for designs with improved robustness characteristics are also proposed. Since the problem formulation is generic and the solution methods only require standard optimization algorithms for their implementation, the tools developed are applicable to a broad range of problems in several disciplines.
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Directory of Open Access Journals (Sweden)
Xin-Gang Zhao
2013-01-01
Full Text Available For a class of continuous-time Markovian jump linear uncertain systems with partly known transition rates and input quantization, the H2 state-feedback control design is considered. The elements in the transition rates matrix include completely known, boundary known, and completely unknown ones. First, an H2 cost index for Markovian jump linear uncertain systems is introduced; then by introducing a new matrix inequality condition, sufficient conditions are formulated in terms of linear matrix inequalities (LMIs for the H2 control of the Markovian jump linear uncertain systems. Less conservativeness is achieved than the result obtained with the existing technique. Finally, a numerical example is given to verify the validity of the theoretical results.
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International Nuclear Information System (INIS)
Lien, C.-H.
2007-01-01
This article considers non-fragile guaranteed cost control problem for a class of uncertain neutral system with time-varying delays in both state and control input. Delay-dependent criteria are proposed to guarantee the robust stabilization of systems. Linear matrix inequality (LMI) optimization approach is used to solve the non-fragile guaranteed cost control problem. Non-fragile guaranteed cost control for unperturbed neutral system is considered in the first step. Robust non-fragile guaranteed cost control for uncertain neutral system is designed directly from the unperturbed condition. An efficient approach is proposed to design the non-fragile guaranteed cost control for uncertain neutral systems. LMI toolbox of Matlab is used to implement the proposed results. Finally, a numerical example is illustrated to show the usefulness of the proposed results
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Strong practical stability and stabilization of uncertain discrete linear repetitive processes
Czech Academy of Sciences Publication Activity Database
Dabkowski, Pavel; Galkowski, K.; Bachelier, O.; Rogers, E.; Kummert, A.; Lam, J.
2013-01-01
Roč. 20, č. 2 (2013), s. 220-233 ISSN 1070-5325 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10750506 Institutional support: RVO:67985556 Keywords : strong practical stability * stabilization * uncertain discrete linear repetitive processes * linear matrix inequality Subject RIV: BC - Control Systems Theory Impact factor: 1.424, year: 2013 http://onlinelibrary.wiley.com/doi/10.1002/nla.812/abstract
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Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai
2015-07-01
The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.
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Directory of Open Access Journals (Sweden)
Ming-Feng Yang
2016-01-01
Full Text Available Nowadays, in order to achieve advantages in supply chain management, how to keep inventory in adequate level and how to enhance customer service level are two critical practices for decision makers. Generally, uncertain lead time and defective products have much to do with inventory and service level. Therefore, this study mainly aims at developing a multiechelon integrated just-in-time inventory model with uncertain lead time and imperfect quality to enhance the benefits of the logistics model. In addition, the Ant Colony Algorithm (ACA is established to determine the optimal solutions. Moreover, based on our proposed model and analysis, the ACA is more efficient than Particle Swarm Optimization (PSO and Lingo in SMEIJI model. An example is provided in this study to illustrate how production run and defective rate have an effect on system costs. Finally, the results of our research could provide some managerial insights which support decision makers in real-world operations.
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Animal biometrics: quantifying and detecting phenotypic appearance.
Kühl, Hjalmar S; Burghardt, Tilo
2013-07-01
Animal biometrics is an emerging field that develops quantified approaches for representing and detecting the phenotypic appearance of species, individuals, behaviors, and morphological traits. It operates at the intersection between pattern recognition, ecology, and information sciences, producing computerized systems for phenotypic measurement and interpretation. Animal biometrics can benefit a wide range of disciplines, including biogeography, population ecology, and behavioral research. Currently, real-world applications are gaining momentum, augmenting the quantity and quality of ecological data collection and processing. However, to advance animal biometrics will require integration of methodologies among the scientific disciplines involved. Such efforts will be worthwhile because the great potential of this approach rests with the formal abstraction of phenomics, to create tractable interfaces between different organizational levels of life. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Quantifying alkane emissions in the Eagle Ford Shale using boundary layer enhancement
Roest, Geoffrey; Schade, Gunnar
2017-09-01
The Eagle Ford Shale in southern Texas is home to a booming unconventional oil and gas industry, the climate and air quality impacts of which remain poorly quantified due to uncertain emission estimates. We used the atmospheric enhancement of alkanes from Texas Commission on Environmental Quality volatile organic compound monitors across the shale, in combination with back trajectory and dispersion modeling, to quantify C2-C4 alkane emissions for a region in southern Texas, including the core of the Eagle Ford, for a set of 68 days from July 2013 to December 2015. Emissions were partitioned into raw natural gas and liquid storage tank sources using gas and headspace composition data, respectively, and observed enhancement ratios. We also estimate methane emissions based on typical ethane-to-methane ratios in gaseous emissions. The median emission rate from raw natural gas sources in the shale, calculated as a percentage of the total produced natural gas in the upwind region, was 0.7 % with an interquartile range (IQR) of 0.5-1.3 %, below the US Environmental Protection Agency's (EPA) current estimates. However, storage tanks contributed 17 % of methane emissions, 55 % of ethane, 82 % percent of propane, 90 % of n-butane, and 83 % of isobutane emissions. The inclusion of liquid storage tank emissions results in a median emission rate of 1.0 % (IQR of 0.7-1.6 %) relative to produced natural gas, overlapping the current EPA estimate of roughly 1.6 %. We conclude that emissions from liquid storage tanks are likely a major source for the observed non-methane hydrocarbon enhancements in the Northern Hemisphere.
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The impact of uncertain threat on affective bias: Individual differences in response to ambiguity.
Neta, Maital; Cantelon, Julie; Haga, Zachary; Mahoney, Caroline R; Taylor, Holly A; Davis, F Caroline
2017-12-01
Individuals who operate under highly stressful conditions (e.g., military personnel and first responders) are often faced with the challenge of quickly interpreting ambiguous information in uncertain and threatening environments. When faced with ambiguity, it is likely adaptive to view potentially dangerous stimuli as threatening until contextual information proves otherwise. One laboratory-based paradigm that can be used to simulate uncertain threat is known as threat of shock (TOS), in which participants are told that they might receive mild but unpredictable electric shocks while performing an unrelated task. The uncertainty associated with this potential threat induces a state of emotional arousal that is not overwhelmingly stressful, but has widespread-both adaptive and maladaptive-effects on cognitive and affective function. For example, TOS is thought to enhance aversive processing and abolish positivity bias. Importantly, in certain situations (e.g., when walking home alone at night), this anxiety can promote an adaptive state of heightened vigilance and defense mobilization. In the present study, we used TOS to examine the effects of uncertain threat on valence bias, or the tendency to interpret ambiguous social cues as positive or negative. As predicted, we found that heightened emotional arousal elicited by TOS was associated with an increased tendency to interpret ambiguous cues negatively. Such negative interpretations are likely adaptive in situations in which threat detection is critical for survival and should override an individual's tendency to interpret ambiguity positively in safe contexts. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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DEFF Research Database (Denmark)
Ahmadi, Mohamadreza; Mojallali, Hamed; Wisniewski, Rafal
2012-01-01
This paper addresses the robust stability and control problem of uncertain piecewise linear switched systems where, instead of the conventional Carathe ́odory solutions, we allow for Filippov solutions. In other words, in contrast to the previous studies, solutions with infinite switching in fini...... algorithm is proposed to surmount the aforementioned matrix inequality conditions....... time along the facets and on faces of arbitrary dimensions are also taken into account. Firstly, based on earlier results, the stability problem of piecewise linear systems with Filippov solutions is translated into a number of linear matrix inequality feasibility tests. Subsequently, a set of matrix...... inequalities are brought forward, which determines the asymptotic stability of the Filippov solutions of a given uncertain piecewise linear system. Afterwards, bilinear matrix inequality conditions for synthesizing a robust controller with a guaranteed H∞ per- formance are formulated. Finally, a V-K iteration...
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Quantifying the Value of Perfect Information in Emergency Vaccination Campaigns.
Directory of Open Access Journals (Sweden)
Naomi V Bradbury
2017-02-01
Full Text Available Foot-and-mouth disease outbreaks in non-endemic countries can lead to large economic costs and livestock losses but the use of vaccination has been contentious, partly due to uncertainty about emergency FMD vaccination. Value of information methods can be applied to disease outbreak problems such as FMD in order to investigate the performance improvement from resolving uncertainties. Here we calculate the expected value of resolving uncertainty about vaccine efficacy, time delay to immunity after vaccination and daily vaccination capacity for a hypothetical FMD outbreak in the UK. If it were possible to resolve all uncertainty prior to the introduction of control, we could expect savings of £55 million in outbreak cost, 221,900 livestock culled and 4.3 days of outbreak duration. All vaccination strategies were found to be preferable to a culling only strategy. However, the optimal vaccination radius was found to be highly dependent upon vaccination capacity for all management objectives. We calculate that by resolving the uncertainty surrounding vaccination capacity we would expect to return over 85% of the above savings, regardless of management objective. It may be possible to resolve uncertainty about daily vaccination capacity before an outbreak, and this would enable decision makers to select the optimal control action via careful contingency planning.
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International Nuclear Information System (INIS)
Wang, Cong; Zhang, Hong-li; Fan, Wen-hui
2017-01-01
In this paper, we propose a new method to improve the safety of secure communication. This method uses the generalized dislocated lag projective synchronization and function projective synchronization to form a new generalized dislocated lag function projective synchronization. Moreover, this paper takes the examples of fractional order Chen system and Lü system with uncertain parameters as illustration. As the parameters of the two systems are uncertain, the nonlinear controller and parameter update algorithms are designed based on the fractional stability theory and adaptive control method. Moreover, this synchronization form and method of control are applied to secure communication via chaotic masking modulation. Many information signals can be recovered and validated. Finally, simulations are used to show the validity and feasibility of the proposed scheme.
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Directory of Open Access Journals (Sweden)
Ling Zhang
2012-01-01
Full Text Available We study a multi-period mean-variance portfolio selection problem with an uncertain time horizon and serial correlations. Firstly, we embed the nonseparable multi-period optimization problem into a separable quadratic optimization problem with uncertain exit time by employing the embedding technique of Li and Ng (2000. Then we convert the later into an optimization problem with deterministic exit time. Finally, using the dynamic programming approach, we explicitly derive the optimal strategy and the efficient frontier for the dynamic mean-variance optimization problem. A numerical example with AR(1 return process is also presented, which shows that both the uncertainty of exit time and the serial correlations of returns have significant impacts on the optimal strategy and the efficient frontier.
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Neural basis for generalized quantifier comprehension.
McMillan, Corey T; Clark, Robin; Moore, Peachie; Devita, Christian; Grossman, Murray
2005-01-01
Generalized quantifiers like "all cars" are semantically well understood, yet we know little about their neural representation. Our model of quantifier processing includes a numerosity device, operations that combine number elements and working memory. Semantic theory posits two types of quantifiers: first-order quantifiers identify a number state (e.g. "at least 3") and higher-order quantifiers additionally require maintaining a number state actively in working memory for comparison with another state (e.g. "less than half"). We used BOLD fMRI to test the hypothesis that all quantifiers recruit inferior parietal cortex associated with numerosity, while only higher-order quantifiers recruit prefrontal cortex associated with executive resources like working memory. Our findings showed that first-order and higher-order quantifiers both recruit right inferior parietal cortex, suggesting that a numerosity component contributes to quantifier comprehension. Moreover, only probes of higher-order quantifiers recruited right dorsolateral prefrontal cortex, suggesting involvement of executive resources like working memory. We also observed activation of thalamus and anterior cingulate that may be associated with selective attention. Our findings are consistent with a large-scale neural network centered in frontal and parietal cortex that supports comprehension of generalized quantifiers.
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Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong
2017-04-01
This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.
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Neural correlates of uncertain decision making: ERP evidence from the Iowa Gambling Task
Directory of Open Access Journals (Sweden)
Ji-fang eCui
2013-11-01
Full Text Available In our daily life, it is very common to make decisions in uncertain situations. The Iowa Gambling Task (IGT has been widely used in laboratory studies because of its good simulation of uncertainty in real life activities. The present study aimed to examine the neural correlates of uncertain decision making with the IGT. Twenty-six university students completed this study. An adapted IGT was administered to them, and the EEG data were recorded. The adapted IGT we used allowed us to analyze the choice evaluation, response selection, and feedback evaluation stages of uncertain decision making within the same paradigm. In the choice evaluation stage, the advantageous decks evoked larger P3 amplitude in the left hemisphere, while the disadvantageous decks evoked larger P3 in the right hemisphere. In the response selection stage, the response of pass (the card was not turned over; the participants neither won nor lost money evoked larger negativity preceding the response compared to that of play (the card was turned over; the participant either won or lost money. In the feedback evaluation stage, feedback-related negativity was only sensitive to the valence (win/loss but not the magnitude (large/small of the outcome, and P3 was sensitive to both the valence and the magnitude of the outcome. These results were consistent with the notion that a positive somatic state was represented in the left hemisphere and a negative somatic state was represented in the right hemisphere. There were also anticipatory ERP effects that guided the participants’ responses and provided evidence for the somatic marker hypothesis with more precise timing.
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Directory of Open Access Journals (Sweden)
Eva Parga-Dans
2017-03-01
Full Text Available Recent studies of innovation highlight the importance of external knowledge sourcing. Existing empirical works are based on national surveys and specific industries. The present study contributes to the analysis of strategies for sourcing external knowledge, based on a specific case study and moment in time: the Spanish archaeological sector and its emergence as a new business activity. Our results show that external knowledge sourcing involves diverse mechanisms, agents and two main strategies: cooperation and knowledge acquisition. In an expanding knowledge-based sector emerging in an uncertain context and whose sources of knowledge are scattered, innovation strategy should focus on the search for external knowledge –cooperation and acquisition strategies-, rather than on internal sources.
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Semi-Coercive Variational Inequalities with Uncertain Input Data. Applications to Shaloow Shells
Czech Academy of Sciences Publication Activity Database
Hlaváček, Ivan; Lovíšek, J.
2005-01-01
Roč. 15, č. 2 (2005), s. 273-299 ISSN 0218-2025 R&D Projects: GA ČR(CZ) GA201/01/1200; GA ČR(CZ) GA201/02/1058 Institutional research plan: CEZ:AV0Z10190503 Keywords : control of variational inequalities * uncertain input data * shallow elastic shells Subject RIV: BA - General Mathematics Impact factor: 1.248, year: 2005
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GROUP-BUYING ONLINE AUCTION AND OPTIMAL INVENTORY POLICY IN UNCERTAIN MARKET
Institute of Scientific and Technical Information of China (English)
Jian CHEN; Yunhui LIU; Xiping SONG
2004-01-01
In this paper we consider a group-buying online auction (GBA) model for a monopolistic manufacturer selling novel products in the uncertain market. Firstly, we introduce the bidder's dominant strategy, after which we optimize the GBA price curve and the production volume together.Finally, we compare the GBA with the traditional posted pricing mechanism and find that the GBA is highly probable to be advantageous over the posted pricing mechanism in some appropriate market environments.
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Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
Directory of Open Access Journals (Sweden)
Yongchao Hou
2014-01-01
Full Text Available Uncertain statistics is a methodology for collecting and interpreting the expert’s experimental data by uncertainty theory. In order to estimate uncertainty distributions, an optimization model based on analytic hierarchy process (AHP and interpolation method is proposed in this paper. In addition, the principle of least squares method is presented to estimate uncertainty distributions with known functional form. Finally, the effectiveness of this method is illustrated by an example.
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Peay, Holly L; Hollin, Ilene; Fischer, Ryan; Bridges, John F P
2014-05-01
importance. A total of 119 DMD caregivers completed the BWS instrument; they were predominately biological mothers (67.2%), married (89.9%), and white (91.6%). Treatment effect on muscle function was the most important among experimental attributes (28.7%), followed by risk of heart arrhythmia (22.4%) and risk of bleeding (21.2%). Having additional postapproval data was relatively the least important attribute (2.3%). We present a model process for advocacy organizations aiming to promote patient-centered drug development. The community-engaged approach was successfully used to develop and implement a survey to measure caregiver preferences. Caregivers were willing to accept a serious risk when balanced with a noncurative treatment, even absent improvement in life span. These preferences should inform the Food and Drug Administration's benefit-risk assessment of emerging DMD therapies. This study highlights the synergistic integration of traditional advocacy methods and scientific approach to quantify benefit-risk preferences. Copyright © 2014 The Authors. Published by EM Inc USA.. All rights reserved.
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International Nuclear Information System (INIS)
Stripling, H.F.; McClarren, R.G.; Kuranz, C.C.; Grosskopf, M.J.; Rutter, E.; Torralva, B.R.
2011-01-01
We present a method for calibrating the uncertain inputs to a computer model using available experimental data. The goal of the procedure is to produce posterior distributions of the uncertain inputs such that when samples from the posteriors are used as inputs to future model runs, the model is more likely to replicate (or predict) the experimental response. The calibration is performed by sampling the space of the uncertain inputs, using the computer model (or, more likely, an emulator for the computer model) to assign weights to the samples, and applying the weights to produce the posterior distributions and generate predictions of new experiments within confidence bounds. The method is similar to the Markov chain Monte Carlo (MCMC) calibration methods with independent sampling with the exception that we generate samples beforehand and replace the candidate acceptance routine with a weighting scheme. We apply our method to the calibration of a Hyades 2D model of laser energy deposition in beryllium. We employ a Bayesian Multivariate Adaptive Regression Splines (BMARS) emulator as a surrogate for Hyades 2D. We treat a range of uncertainties in our system, including uncertainties in the experimental inputs, experimental measurement error, and systematic experimental timing errors. The results of the calibration are posterior distributions that both agree with intuition and improve the accuracy and decrease the uncertainty in experimental predictions. (author)
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Dynamic response of structures with uncertain parameters
International Nuclear Information System (INIS)
Cai, Z H; Liu, Y; Yang, Y
2010-01-01
In this paper, an interval method for the dynamic response of structures with uncertain parameters is presented. In the presented method, the structural physical and geometric parameters and loads can be considered as interval variables. The structural stiffness matrix, mass matrix and loading vectors are described as the sum of two parts corresponding to the deterministic matrix and the uncertainty of the interval parameters. The interval problem is then transformed into approximate deterministic one. The Laplace transform is used to transform the equations of the dynamic system into linear algebra equations. The Maclaurin series expansion is applied on the modified dynamic equation in order to deal with the linear algebra equations. Numerical examples are studied by the presented interval method for the cases with and without damping. The upper bound and lower bound of the dynamic responses of the examples are compared, and it shows that the presented method is effective.
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Melioration as rational choice: sequential decision making in uncertain environments.
Sims, Chris R; Neth, Hansjörg; Jacobs, Robert A; Gray, Wayne D
2013-01-01
Melioration-defined as choosing a lesser, local gain over a greater longer term gain-is a behavioral tendency that people and pigeons share. As such, the empirical occurrence of meliorating behavior has frequently been interpreted as evidence that the mechanisms of human choice violate the norms of economic rationality. In some environments, the relationship between actions and outcomes is known. In this case, the rationality of choice behavior can be evaluated in terms of how successfully it maximizes utility given knowledge of the environmental contingencies. In most complex environments, however, the relationship between actions and future outcomes is uncertain and must be learned from experience. When the difficulty of this learning challenge is taken into account, it is not evident that melioration represents suboptimal choice behavior. In the present article, we examine human performance in a sequential decision-making experiment that is known to induce meliorating behavior. In keeping with previous results using this paradigm, we find that the majority of participants in the experiment fail to adopt the optimal decision strategy and instead demonstrate a significant bias toward melioration. To explore the origins of this behavior, we develop a rational analysis (Anderson, 1990) of the learning problem facing individuals in uncertain decision environments. Our analysis demonstrates that an unbiased learner would adopt melioration as the optimal response strategy for maximizing long-term gain. We suggest that many documented cases of melioration can be reinterpreted not as irrational choice but rather as globally optimal choice under uncertainty.
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Feature inference with uncertain categorization: Re-assessing Anderson's rational model.
Konovalova, Elizaveta; Le Mens, Gaël
2017-09-18
A key function of categories is to help predictions about unobserved features of objects. At the same time, humans are often in situations where the categories of the objects they perceive are uncertain. In an influential paper, Anderson (Psychological Review, 98(3), 409-429, 1991) proposed a rational model for feature inferences with uncertain categorization. A crucial feature of this model is the conditional independence assumption-it assumes that the within category feature correlation is zero. In prior research, this model has been found to provide a poor fit to participants' inferences. This evidence is restricted to task environments inconsistent with the conditional independence assumption. Currently available evidence thus provides little information about how this model would fit participants' inferences in a setting with conditional independence. In four experiments based on a novel paradigm and one experiment based on an existing paradigm, we assess the performance of Anderson's model under conditional independence. We find that this model predicts participants' inferences better than competing models. One model assumes that inferences are based on just the most likely category. The second model is insensitive to categories but sensitive to overall feature correlation. The performance of Anderson's model is evidence that inferences were influenced not only by the more likely category but also by the other candidate category. Our findings suggest that a version of Anderson's model which relaxes the conditional independence assumption will likely perform well in environments characterized by within-category feature correlation.
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Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models
Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri
2015-09-01
Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.
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2018-04-01
Reports an error in "The impact of uncertain threat on affective bias: Individual differences in response to ambiguity" by Maital Neta, Julie Cantelon, Zachary Haga, Caroline R. Mahoney, Holly A. Taylor and F. Caroline Davis ( Emotion , 2017[Dec], Vol 17[8], 1137-1143). In this article, the copyright attribution was incorrectly listed under the Creative Commons CC-BY license due to production-related error. The correct copyright should be "In the public domain." The online version of this article has been corrected. (The following abstract of the original article appeared in record 2017-40275-001.) Individuals who operate under highly stressful conditions (e.g., military personnel and first responders) are often faced with the challenge of quickly interpreting ambiguous information in uncertain and threatening environments. When faced with ambiguity, it is likely adaptive to view potentially dangerous stimuli as threatening until contextual information proves otherwise. One laboratory-based paradigm that can be used to simulate uncertain threat is known as threat of shock (TOS), in which participants are told that they might receive mild but unpredictable electric shocks while performing an unrelated task. The uncertainty associated with this potential threat induces a state of emotional arousal that is not overwhelmingly stressful, but has widespread-both adaptive and maladaptive-effects on cognitive and affective function. For example, TOS is thought to enhance aversive processing and abolish positivity bias. Importantly, in certain situations (e.g., when walking home alone at night), this anxiety can promote an adaptive state of heightened vigilance and defense mobilization. In the present study, we used TOS to examine the effects of uncertain threat on valence bias, or the tendency to interpret ambiguous social cues as positive or negative. As predicted, we found that heightened emotional arousal elicited by TOS was associated with an increased tendency to
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Institute of Scientific and Technical Information of China (English)
Guo Jiansheng; Wang Zutong; Zheng Mingfa; Wang Ying
2014-01-01
Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.
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Adaptive Neural Output Feedback Control for Uncertain Robot Manipulators with Input Saturation
Directory of Open Access Journals (Sweden)
Rong Mei
2017-01-01
Full Text Available This paper presents an adaptive neural output feedback control scheme for uncertain robot manipulators with input saturation using the radial basis function neural network (RBFNN and disturbance observer. First, the RBFNN is used to approximate the system uncertainty, and the unknown approximation error of the RBFNN and the time-varying unknown external disturbance of robot manipulators are integrated as a compounded disturbance. Then, the state observer and the disturbance observer are proposed to estimate the unmeasured system state and the unknown compounded disturbance based on RBFNN. At the same time, the adaptation technique is employed to tackle the control input saturation problem. Utilizing the estimate outputs of the RBFNN, the state observer, and the disturbance observer, the adaptive neural output feedback control scheme is developed for robot manipulators using the backstepping technique. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis and the asymptotically convergent tracking error is obtained under the integrated effect of the system uncertainty, the unmeasured system state, the unknown external disturbance, and the input saturation. Finally, numerical simulation results are presented to illustrate the effectiveness of the proposed adaptive neural output feedback control scheme for uncertain robot manipulators.
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Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation
Directory of Open Access Journals (Sweden)
Hongzhi Hu
2015-01-01
Full Text Available Due to the extensive social influence, public health emergency has attracted great attention in today’s society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event’s social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback based on ACP simulation system which was successfully applied to the analysis of A (H1N1 Flu emergency.
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Directory of Open Access Journals (Sweden)
Zhengfeng Huang
2013-01-01
Full Text Available Various factors can make predicting bus passenger demand uncertain. In this study, a bilevel programming model for optimizing bus frequencies based on uncertain bus passenger demand is formulated. There are two terms constituting the upper-level objective. The first is transit network cost, consisting of the passengers’ expected travel time and operating costs, and the second is transit network robustness performance, indicated by the variance in passenger travel time. The second term reflects the risk aversion of decision maker, and it can make the most uncertain demand be met by the bus operation with the optimal transit frequency. With transit link’s proportional flow eigenvalues (mean and covariance obtained from the lower-level model, the upper-level objective is formulated by the analytical method. In the lower-level model, the above two eigenvalues are calculated by analyzing the propagation of mean transit trips and their variation in the optimal strategy transit assignment process. The genetic algorithm (GA used to solve the model is tested in an example network. Finally, the model is applied to determining optimal bus frequencies in the city of Liupanshui, China. The total cost of the transit system in Liupanshui can be reduced by about 6% via this method.
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2008-07-21
been well investigated in the past. LE CHATELIER -BRAUN’S PRINCIPLE provides a basis for response against perturbations for systems in equilibrium, as...layer from the low level voltage fluctuation. (Fig. 3) Fig 3: Airplane as an example of engineered robust system In principle , robustness of the...as fundamental architectural principle Since the system will be used under hostile and uncertain environments, robustness shall be the major
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Robust Hinf control of uncertain switched systems defined on polyhedral sets with Filippov solutions
DEFF Research Database (Denmark)
Ahmadi, Mohamadreza; Mojallali, Hamed; Wisniewski, Rafal
2012-01-01
This paper considers the control problem of a class of uncertain switched systems defined on polyhedral sets known as piecewise linear systems where, instead of the conventional Carathe ́odory solutions, Filippov solutions are studied. In other words, in contrast to the previous studies, solutions...
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Navigation of autonomous vehicles for oil spill cleaning in dynamic and uncertain environments
Jin, Xin; Ray, Asok
2014-04-01
In the context of oil spill cleaning by autonomous vehicles in dynamic and uncertain environments, this paper presents a multi-resolution algorithm that seamlessly integrates the concepts of local navigation and global navigation based on the sensory information; the objective here is to enable adaptive decision making and online replanning of vehicle paths. The proposed algorithm provides a complete coverage of the search area for clean-up of the oil spills and does not suffer from the problem of having local minima, which is commonly encountered in potential-field-based methods. The efficacy of the algorithm is tested on a high-fidelity player/stage simulator for oil spill cleaning in a harbour, where the underlying oil weathering process is modelled as 2D random-walk particle tracking. A preliminary version of this paper was presented by X. Jin and A. Ray as 'Coverage Control of Autonomous Vehicles for Oil Spill Cleaning in Dynamic and Uncertain Environments', Proceedings of the American Control Conference, Washington, DC, June 2013, pp. 2600-2605.
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Partnership Selection Involving Mixed Types of Uncertain Preferences
Directory of Open Access Journals (Sweden)
Li-Ching Ma
2013-01-01
Full Text Available Partnership selection is an important issue in management science. This study proposes a general model based on mixed integer programming and goal-programming analytic hierarchy process (GP-AHP to solve partnership selection problems involving mixed types of uncertain or inconsistent preferences. The proposed approach is designed to deal with crisp, interval, step, fuzzy, or mixed comparison preferences, derive crisp priorities, and improve multiple solution problems. The degree of fulfillment of a decision maker’s preferences is also taken into account. The results show that the proposed approach keeps more solution ratios within the given preferred intervals and yields less deviation. In addition, the proposed approach can treat incomplete preference matrices with flexibility in reducing the number of pairwise comparisons required and can also be conveniently developed into a decision support system.
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Probabilistic Graph Layout for Uncertain Network Visualization.
Schulz, Christoph; Nocaj, Arlind; Goertler, Jochen; Deussen, Oliver; Brandes, Ulrik; Weiskopf, Daniel
2017-01-01
We present a novel uncertain network visualization technique based on node-link diagrams. Nodes expand spatially in our probabilistic graph layout, depending on the underlying probability distributions of edges. The visualization is created by computing a two-dimensional graph embedding that combines samples from the probabilistic graph. A Monte Carlo process is used to decompose a probabilistic graph into its possible instances and to continue with our graph layout technique. Splatting and edge bundling are used to visualize point clouds and network topology. The results provide insights into probability distributions for the entire network-not only for individual nodes and edges. We validate our approach using three data sets that represent a wide range of network types: synthetic data, protein-protein interactions from the STRING database, and travel times extracted from Google Maps. Our approach reveals general limitations of the force-directed layout and allows the user to recognize that some nodes of the graph are at a specific position just by chance.
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Gauging Metallicity of Diffuse Gas under an Uncertain Ionizing Radiation Field
Chen, Hsiao-Wen; Johnson, Sean D.; Zahedy, Fakhri S.; Rauch, Michael; Mulchaey, John S.
2017-06-01
Gas metallicity is a key quantity used to determine the physical conditions of gaseous clouds in a wide range of astronomical environments, including interstellar and intergalactic space. In particular, considerable effort in circumgalactic medium (CGM) studies focuses on metallicity measurements because gas metallicity serves as a critical discriminator for whether the observed heavy ions in the CGM originate in chemically enriched outflows or in more chemically pristine gas accreted from the intergalactic medium. However, because the gas is ionized, a necessary first step in determining CGM metallicity is to constrain the ionization state of the gas which, in addition to gas density, depends on the ultraviolet background radiation field (UVB). While it is generally acknowledged that both the intensity and spectral slope of the UVB are uncertain, the impact of an uncertain spectral slope has not been properly addressed in the literature. This Letter shows that adopting a different spectral slope can result in an order of magnitude difference in the inferred CGM metallicity. Specifically, a harder UVB spectrum leads to a higher estimated gas metallicity for a given set of observed ionic column densities. Therefore, such systematic uncertainties must be folded into the error budget for metallicity estimates of ionized gas. An initial study shows that empirical diagnostics are available for discriminating between hard and soft ionizing spectra. Applying these diagnostics helps reduce the systematic uncertainties in CGM metallicity estimates.
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Gauging Metallicity of Diffuse Gas under an Uncertain Ionizing Radiation Field
Energy Technology Data Exchange (ETDEWEB)
Chen, Hsiao-Wen; Zahedy, Fakhri S. [Department of Astronomy and Astrophysics, The University of Chicago, 5640 S Ellis Avenue, Chicago, IL 60637 (United States); Johnson, Sean D. [Department of Astrophysics, Princeton University, Princeton, NJ (United States); Rauch, Michael; Mulchaey, John S., E-mail: hchen@oddjob.uchicago.edu [The Observatories of the Carnegie Institution for Science, 813 Santa Barbara Street, Pasadena, CA 91101 (United States)
2017-06-20
Gas metallicity is a key quantity used to determine the physical conditions of gaseous clouds in a wide range of astronomical environments, including interstellar and intergalactic space. In particular, considerable effort in circumgalactic medium (CGM) studies focuses on metallicity measurements because gas metallicity serves as a critical discriminator for whether the observed heavy ions in the CGM originate in chemically enriched outflows or in more chemically pristine gas accreted from the intergalactic medium. However, because the gas is ionized, a necessary first step in determining CGM metallicity is to constrain the ionization state of the gas which, in addition to gas density, depends on the ultraviolet background radiation field (UVB). While it is generally acknowledged that both the intensity and spectral slope of the UVB are uncertain, the impact of an uncertain spectral slope has not been properly addressed in the literature. This Letter shows that adopting a different spectral slope can result in an order of magnitude difference in the inferred CGM metallicity. Specifically, a harder UVB spectrum leads to a higher estimated gas metallicity for a given set of observed ionic column densities. Therefore, such systematic uncertainties must be folded into the error budget for metallicity estimates of ionized gas. An initial study shows that empirical diagnostics are available for discriminating between hard and soft ionizing spectra. Applying these diagnostics helps reduce the systematic uncertainties in CGM metallicity estimates.
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A design control structure for architectural firms in a highly complex and uncertain situation
Schijlen, J.T.H.A.M.; Otter, den A.F.H.J.; Pels, H.J.
2011-01-01
A large architectural firm in a highly complex and uncertain production situation asked to improve its existing ?production control? system for design projects. To that account a research and design project of nine months at the spot was defined. The production control in the organization was based
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Quantifying alkane emissions in the Eagle Ford Shale using boundary layer enhancement
Directory of Open Access Journals (Sweden)
G. Roest
2017-09-01
Full Text Available The Eagle Ford Shale in southern Texas is home to a booming unconventional oil and gas industry, the climate and air quality impacts of which remain poorly quantified due to uncertain emission estimates. We used the atmospheric enhancement of alkanes from Texas Commission on Environmental Quality volatile organic compound monitors across the shale, in combination with back trajectory and dispersion modeling, to quantify C2–C4 alkane emissions for a region in southern Texas, including the core of the Eagle Ford, for a set of 68 days from July 2013 to December 2015. Emissions were partitioned into raw natural gas and liquid storage tank sources using gas and headspace composition data, respectively, and observed enhancement ratios. We also estimate methane emissions based on typical ethane-to-methane ratios in gaseous emissions. The median emission rate from raw natural gas sources in the shale, calculated as a percentage of the total produced natural gas in the upwind region, was 0.7 % with an interquartile range (IQR of 0.5–1.3 %, below the US Environmental Protection Agency's (EPA current estimates. However, storage tanks contributed 17 % of methane emissions, 55 % of ethane, 82 % percent of propane, 90 % of n-butane, and 83 % of isobutane emissions. The inclusion of liquid storage tank emissions results in a median emission rate of 1.0 % (IQR of 0.7–1.6 % relative to produced natural gas, overlapping the current EPA estimate of roughly 1.6 %. We conclude that emissions from liquid storage tanks are likely a major source for the observed non-methane hydrocarbon enhancements in the Northern Hemisphere.
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Fourier phasing with phase-uncertain mask
International Nuclear Information System (INIS)
Fannjiang, Albert; Liao, Wenjing
2013-01-01
Fourier phasing is the problem of retrieving Fourier phase information from Fourier intensity data. The standard Fourier phase retrieval (without a mask) is known to have many solutions which cause the standard phasing algorithms to stagnate and produce wrong or inaccurate solutions. In this paper Fourier phase retrieval is carried out with the introduction of a randomly fabricated mask in measurement and reconstruction. Highly probable uniqueness of solution, up to a global phase, was previously proved with exact knowledge of the mask. Here the uniqueness result is extended to the case where only rough information about the mask’s phases is assumed. The exponential probability bound for uniqueness is given in terms of the uncertainty-to-diversity ratio of the unknown mask. New phasing algorithms alternating between the object update and the mask update are systematically tested and demonstrated to have the capability of recovering both the object and the mask (within the object support) simultaneously, consistent with the uniqueness result. Phasing with a phase-uncertain mask is shown to be robust with respect to the correlation in the mask as well as the Gaussian and Poisson noises. (paper)
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A framework to quantify uncertainty in simulations of oil transport in the ocean
Gonçalves, Rafael C.
2016-03-02
An uncertainty quantification framework is developed for the DeepC Oil Model based on a nonintrusive polynomial chaos method. This allows the model\\'s output to be presented in a probabilistic framework so that the model\\'s predictions reflect the uncertainty in the model\\'s input data. The new capability is illustrated by simulating the far-field dispersal of oil in a Deepwater Horizon blowout scenario. The uncertain input consisted of ocean current and oil droplet size data and the main model output analyzed is the ensuing oil concentration in the Gulf of Mexico. A 1331 member ensemble was used to construct a surrogate for the model which was then mined for statistical information. The mean and standard deviations in the oil concentration were calculated for up to 30 days, and the total contribution of each input parameter to the model\\'s uncertainty was quantified at different depths. Also, probability density functions of oil concentration were constructed by sampling the surrogate and used to elaborate probabilistic hazard maps of oil impact. The performance of the surrogate was constantly monitored in order to demarcate the space-time zones where its estimates are reliable. © 2016. American Geophysical Union.
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A framework to quantify uncertainty in simulations of oil transport in the ocean
Gonç alves, Rafael C.; Iskandarani, Mohamed; Srinivasan, Ashwanth; Thacker, W. Carlisle; Chassignet, Eric; Knio, Omar
2016-01-01
An uncertainty quantification framework is developed for the DeepC Oil Model based on a nonintrusive polynomial chaos method. This allows the model's output to be presented in a probabilistic framework so that the model's predictions reflect the uncertainty in the model's input data. The new capability is illustrated by simulating the far-field dispersal of oil in a Deepwater Horizon blowout scenario. The uncertain input consisted of ocean current and oil droplet size data and the main model output analyzed is the ensuing oil concentration in the Gulf of Mexico. A 1331 member ensemble was used to construct a surrogate for the model which was then mined for statistical information. The mean and standard deviations in the oil concentration were calculated for up to 30 days, and the total contribution of each input parameter to the model's uncertainty was quantified at different depths. Also, probability density functions of oil concentration were constructed by sampling the surrogate and used to elaborate probabilistic hazard maps of oil impact. The performance of the surrogate was constantly monitored in order to demarcate the space-time zones where its estimates are reliable. © 2016. American Geophysical Union.
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Risk assessment of salt contamination of groundwater under uncertain aquifer properties
Litvinenko, Alexander; Keyes, David E.; Logashenko, Dmitry; Tempone, Raul; Wittum, Gabriel
2017-01-01
requires a mesh with ~8M grid points and 1500 or more time steps. 200 scenarios are computed concurrently. The total number of cores in parallel computation is 200x32=6400. The main goal of this work is to estimate propagation of uncertainties through the model, to investigate sensitivity of the solution to the input uncertain parameters. Additionally, we demonstrate how the multigrid ug4-based solver can be applied as a black-box in the uncertainty quantification framework.
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Woolhouse, Mark
2017-07-01
Transmissibility is the defining characteristic of infectious diseases. Quantifying transmission matters for understanding infectious disease epidemiology and designing evidence-based disease control programs. Tracing individual transmission events can be achieved by epidemiological investigation coupled with pathogen typing or genome sequencing. Individual infectiousness can be estimated by measuring pathogen loads, but few studies have directly estimated the ability of infected hosts to transmit to uninfected hosts. Individuals' opportunities to transmit infection are dependent on behavioral and other risk factors relevant given the transmission route of the pathogen concerned. Transmission at the population level can be quantified through knowledge of risk factors in the population or phylogeographic analysis of pathogen sequence data. Mathematical model-based approaches require estimation of the per capita transmission rate and basic reproduction number, obtained by fitting models to case data and/or analysis of pathogen sequence data. Heterogeneities in infectiousness, contact behavior, and susceptibility can have substantial effects on the epidemiology of an infectious disease, so estimates of only mean values may be insufficient. For some pathogens, super-shedders (infected individuals who are highly infectious) and super-spreaders (individuals with more opportunities to transmit infection) may be important. Future work on quantifying transmission should involve integrated analyses of multiple data sources.
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Directory of Open Access Journals (Sweden)
Hao Zhang
2017-01-01
Full Text Available The problem of locating distribution centers for delivering fresh food as a part of electronic commerce is a strategic decision problem for enterprises. This paper establishes a model for locating distribution centers that considers the uncertainty of customer demands for fresh goods in terms of time-sensitiveness and freshness. Based on the methodology of robust optimization in dealing with uncertain problems, this paper optimizes the location model in discrete demand probabilistic scenarios. In this paper, an improved fruit fly optimization algorithm is proposed to solve the distribution center location problem. An example is given to show that the proposed model and algorithm are robust and can effectively handle the complications caused by uncertain demand. The model proposed in this paper proves valuable both theoretically and practically in the selection of locations of distribution centers.
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Mobayen, Saleh
2018-06-01
This paper proposes a combination of composite nonlinear feedback and integral sliding mode techniques for fast and accurate chaos synchronization of uncertain chaotic systems with Lipschitz nonlinear functions, time-varying delays and disturbances. The composite nonlinear feedback method allows accurate following of the master chaotic system and the integral sliding mode control provides invariance property which rejects the perturbations and preserves the stability of the closed-loop system. Based on the Lyapunov- Krasovskii stability theory and linear matrix inequalities, a novel sufficient condition is offered for the chaos synchronization of uncertain chaotic systems. This method not only guarantees the robustness against perturbations and time-delays, but also eliminates reaching phase and avoids chattering problem. Simulation results demonstrate that the suggested procedure leads to a great control performance. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
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Design of Distributed Engine Control Systems with Uncertain Delay.
Directory of Open Access Journals (Sweden)
Xiaofeng Liu
Full Text Available Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS. Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.
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Design of Distributed Engine Control Systems with Uncertain Delay.
Liu, Xiaofeng; Li, Yanxi; Sun, Xu
Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.
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Exponential Synchronization of Uncertain Complex Dynamical Networks with Delay Coupling
International Nuclear Information System (INIS)
Wang Lifu; Kong Zhi; Jing Yuanwei
2010-01-01
This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches. (general)
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Learning experiences on role-emerging placements: an exploration from the students' perspective.
Dancza, Karina; Warren, Alison; Copley, Jodie; Rodger, Sylvia; Moran, Monica; McKay, Elizabeth; Taylor, Ann
2013-12-01
Occupational therapy educators are challenged to provide students with practical experiences which prepare them for ever changing health-care contexts on graduation. Role-emerging placements have been widely used internationally to help meet this challenge, but research into the learning experiences of students during these innovative placements is limited. This research investigated the enablers and barriers to learning from the perspectives of students on such placements from two European universities. Two separate qualitative studies tracked 10 final year students. Interviews explored their learning experiences prior to, during and after an eight- or 10-week role-emerging placement in a range of settings. Four themes emerged, which were (1) adapting to less doing, more thinking and planning; (2) understanding the complexity of collaboration and making it work; (3) emotional extremes; and (4) realising and using the occupational therapy perspective. These placements presented a 'roller coaster' of authentic learning experiences which created the opportunity for students to use occupation in practice and develop skills for collaborative working in an interprofessional environment. Whereas students viewed their role-emerging placement experiences positively, challenges included the emotional responses of students and placement pace. Findings suggest the need for supportive student placement experiences in both established and role-emerging areas to prepare students for a range of opportunities in an uncertain future. © 2013 Occupational Therapy Australia.
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Ang, A L; Wong, R X; Zhuang, Q Y; Linn, Y C
2012-08-01
Eosinophilia is commonly encountered during clinical practice. Some can be attributed to well-defined causes while others cannot. Optimal management of hypereosinophilia with unknown aetiology is uncertain as the natural history is not well described. We retrospectively studied patients with hypereosinophilia (>5 × 10(9)/L) and described the characteristics, natural history and treatment of those with eosinophilia of uncertain aetiology. There were 141 patients with hypereosinophilia: 87 with well-defined causes, 54 with uncertain aetiology. The latter was managed as hypereosinophilic syndrome (HES) (n = 5), idiopathic hypereosinophilia (IH) (n = 11), presumptive helminthic infection (n = 11) and reactive eosinophilia (n = 5), while 22 were insufficiently investigated and did not have definite working diagnoses. Their median age and peak eosinophil count were 64 (22 to 94) years and 10.0 (5.2-33.9) × 10(9)/L respectively. Forty-six per cent had symptoms attributable to eosinophilia, with the HES and insufficiently investigated groups having the highest (100%) and lowest (27%) percentages respectively. HES and IH patients were most extensively investigated. All 14 HES or IH patients who received steroids responded. All presumptive helminthic infection patients received mebendazole: nine responded, and two had unassessable responses. For the remaining patients, seven received steroids and all responded; one received mebendazole but defaulted; 19 were not treated: 11 resolved spontaneously. No non-HES patients developed eosinophilia-related organ dysfunction. No mortality was caused by hypereosinophilia. Patients with hypereosinophilia of uncertain aetiology can be empirically managed according to working diagnoses derived from history taking, examination and selective investigations. Most patients have benign short-term outcomes, but longer monitoring is required to assess long-term outcomes from untreated hypereosinophilia. © 2011 The Authors. Internal Medicine
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Chinese experience on medical response to radiation emergencies
International Nuclear Information System (INIS)
Liu, Ying; Qin, Bin; Lei, Cuiping; Chen, Huifang; Han, Yuhong
2008-01-01
Full text: Chinese Center for Medical Response to Radiation Emergency (CCMRRE) was established in 1992, based on the National Institute for Radiological Protection, China CDC (NIRP, China CDC). CCMRRE is a liaison of WHO/REMPAN and functions as a national and professional institute for medical preparedness and response to emergencies involving radioactive material. CCMRRE participates in drafting National Medical Assistant Program for Radiation Emergency and relevant technical documents, develops preventive measures and technique means of medical preparedness and response to radiation emergency. CCMRRE is responsible for medical response to radiological or nuclear accident on national level. CCMRRE holds training courses, organizes drills and provides technical support to local medical organizations in practicing medical preparedness and response to radiation emergency. CCMRRE collects, analyzes and exchanges information on medical response to radiological and nuclear emergency and establishes relevant database. CCMRRE also guides and participates in radiation pollution monitoring on accident sites. In the past ten years, we accumulate much knowledge and experience on medical response to radiation emergencies. In this context, we will discuss Xinzhou Accident, which took place in 1992 and involved in three deaths, and Ha'erbin Accident that took place in 2005 and involved one death. A father and two brothers in Xinzhou Accident died of over-exposed to 60 Co source and misdiagnosis and improper treatment, which indicates that most general practitioners are uncertain about the health consequences of exposure to ionizing radiation and the medical management of exposed patients. When Ha'erbin Accident happened in 2005, the local hospital gave the right diagnosis and treatment based on the clinic symptoms and signs, which prevent more people suffering from over-expose to 192 Ir source. The distinct changes comes from the education and training to primary doctors related
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Using Multiple Linear Regression Techniques to Quantify Carbon ...
African Journals Online (AJOL)
komla
Process and statistical models of productivity, though useful, are often ... The carbon balance of terrestrial ecosystems is uncertain, in part due to discrepancies and errors in .... The ecological data were collected through field work to include both .... Computer-aided Multivariate Analysis, Life Learning Publications, Belmont,.
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Human Rights Education before the Challenges of the Emerging Human Rights of the 21st Century
Gloria Ramirez
2006-01-01
This article examines Human Rights Education vis-a-vis the challenges of the emerging human rights of the 21st century. It discusses the difficult situation of HRE in the uncertain and insecure times of globalization and permanent violence particularly after the September 11 attacks. In spite of these unfavorable circumstances, it can be concluded that HRE has gained ground in the agenda of NGO´s to become a demand formulated hand in hand with the fight for democracy and peace. Due to the fac...
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Directory of Open Access Journals (Sweden)
Shih-Yu Li
2013-01-01
Full Text Available We expose the chaotic attractors of time-reversed nonlinear system, further implement its behavior on electronic circuit, and apply the pragmatical asymptotically stability theory to strictly prove that the adaptive synchronization of given master and slave systems with uncertain parameters can be achieved. In this paper, the variety chaotic motions of time-reversed Lorentz system are investigated through Lyapunov exponents, phase portraits, and bifurcation diagrams. For further applying the complex signal in secure communication and file encryption, we construct the circuit to show the similar chaotic signal of time-reversed Lorentz system. In addition, pragmatical asymptotically stability theorem and an assumption of equal probability for ergodic initial conditions (Ge et al., 1999, Ge and Yu, 2000, and Matsushima, 1972 are proposed to strictly prove that adaptive control can be accomplished successfully. The current scheme of adaptive control—by traditional Lyapunov stability theorem and Barbalat lemma, which are used to prove the error vector—approaches zero, as time approaches infinity. However, the core question—why the estimated or given parameters also approach to the uncertain parameters—remains without answer. By the new stability theory, those estimated parameters can be proved approaching the uncertain values strictly, and the simulation results are shown in this paper.
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A New Fast Nonsingular Terminal Sliding Mode Control for a Class of Second-Order Uncertain Systems
Directory of Open Access Journals (Sweden)
Linjie Xin
2016-01-01
Full Text Available This paper considers the robust and adaptive nonsingular terminal sliding mode (NTSM control for a class of second-order uncertain systems. First, a new fast NTSM was proposed which had global fast convergence rate in the sliding phase. Then, a new form of robust NTSM controller was designed to handle a wider class of second-order uncertain systems. Moreover, an exponential-decline switching gain was introduced for chattering suppression. After that, a double sliding surfaces control scheme was constructed to combine the NTSM control with the adaptive technique. The benefit is that a strict demonstration can be given for the stagnation problem in the stability analysis of NTSM. Finally, a case study for tracking control of a variable-length pendulum was performed to verify the proposed controllers.
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Arino, Yosuke; Akimoto, Keigo; Sano, Fuminori; Homma, Takashi; Oda, Junichiro; Tomoda, Toshimasa
2016-05-24
Although solar radiation management (SRM) might play a role as an emergency geoengineering measure, its potential risks remain uncertain, and hence there are ethical and governance issues in the face of SRM's actual deployment. By using an integrated assessment model, we first present one possible methodology for evaluating the value arising from retaining an SRM option given the uncertainty of climate sensitivity, and also examine sensitivities of the option value to SRM's side effects (damages). Reflecting the governance challenges on immediate SRM deployment, we assume scenarios in which SRM could only be deployed with a limited degree of cooling (0.5 °C) only after 2050, when climate sensitivity uncertainty is assumed to be resolved and only when the sensitivity is found to be high (T2x = 4 °C). We conduct a cost-effectiveness analysis with constraining temperature rise as the objective. The SRM option value is originated from its rapid cooling capability that would alleviate the mitigation requirement under climate sensitivity uncertainty and thereby reduce mitigation costs. According to our estimates, the option value during 1990-2049 for a +2.4 °C target (the lowest temperature target level for which there were feasible solutions in this model study) relative to preindustrial levels were in the range between $2.5 and $5.9 trillion, taking into account the maximum level of side effects shown in the existing literature. The result indicates that lower limits of the option values for temperature targets below +2.4 °C would be greater than $2.5 trillion.
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Senevirathna, Lalantha; Abeysekera, Tilak; Nanayakkara, Shanika; Chandrajith, Rohana; Ratnatunga, Neelakanthi; Harada, Kouji H; Hitomi, Toshiaki; Komiya, Toshiyuki; Muso, Eri; Koizumi, Akio
2012-05-01
The alarming rise in the prevalence of chronic kidney disease of uncertain etiology (CKDu) among the low socioeconomic farming community in the North Central Province of Sri Lanka has been recognized as an emerging public health issue in the country. This study sought to determine the possible factors associated with the progression and mortality of CKDu. The study utilized a single-center cohort registered in 2003 and followed up until 2009 in a regional clinic in the endemic region, and used a Cox proportional hazards model. We repeatedly found an association between disease progression and hypertension. Men were at higher risk of CKDu than women. A significant proportion of the patients in this cohort were underweight, which emphasized the need for future studies on the nutritional status of these patients. Compared with findings in western countries and other regions of Asia, we identified hypertension as a major risk factor for progression of CKDu in this cohort.
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The Fallacy of Quantifying Risk
2012-09-01
Defense AT&L: September–October 2012 18 The Fallacy of Quantifying Risk David E. Frick, Ph.D. Frick is a 35-year veteran of the Department of...a key to risk analysis was “choosing the right technique” of quantifying risk . The weakness in this argument stems not from the assertion that one...of information about the enemy), yet achiev- ing great outcomes. Attempts at quantifying risk are not, in and of themselves, objectionable. Prudence
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International Nuclear Information System (INIS)
Sadjadi, S.J.; Omrani, H.
2008-01-01
This paper presents Data Envelopment Analysis (DEA) model with uncertain data for performance assessment of electricity distribution companies. During the past two decades, DEA has been widely used for benchmarking the electricity distribution companies. However, there is no study among many existing DEA approaches where the uncertainty in data is allowed and, at the same time, the distribution of the random data is permitted to be unknown. The proposed method of this paper develops a new DEA method with the consideration of uncertainty on output parameters. The method is based on the adaptation of recently developed robust optimization approaches proposed by Ben-Tal and Nemirovski [2000. Robust solutions of linear programming problems contaminated with uncertain data. Mathematical Programming 88, 411-421] and Bertsimas et al. [2004. Robust linear optimization under general norms. Operations Research Letters 32, 510-516]. The results are compared with an existing parametric Stochastic Frontier Analysis (SFA) using data from 38 electricity distribution companies in Iran to show the effects of the data uncertainties on the performance of DEA outputs. The results indicate that the robust DEA approach can be a relatively more reliable method for efficiency estimating and ranking strategies
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Dynamic IQC-Based Control of Uncertain LFT Systems With Time-Varying State Delay.
Yuan, Chengzhi; Wu, Fen
2016-12-01
This paper presents a new exact-memory delay control scheme for a class of uncertain systems with time-varying state delay under the integral quadratic constraint (IQC) framework. The uncertain system is described as a linear fractional transformation model including a state-delayed linear time-invariant (LTI) system and time-varying structured uncertainties. The proposed exact-memory delay controller consists of a linear state-feedback control law and an additional term that captures the delay behavior of the plant. We first explore the delay stability and the L 2 -gain performance using dynamic IQCs incorporated with quadratic Lyapunov functions. Then, the design of exact-memory controllers that guarantee desired L 2 -gain performance is examined. The resulting delay control synthesis conditions are formulated in terms of linear matrix inequalities, which are convex on all design variables including the scaling matrices associated with the IQC multipliers. The IQC-based exact-memory control scheme provides a novel approach for delay control designs via convex optimization, and advances existing control methods in two important ways: 1) better controlled performance and 2) simplified design procedure with less computational cost. The effectiveness and advantages of the proposed approach have been demonstrated through numerical studies.
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Dynamical Scheduling and Robust Control in Uncertain Environments with Petri Nets for DESs
Directory of Open Access Journals (Sweden)
Dimitri Lefebvre
2017-10-01
Full Text Available This paper is about the incremental computation of control sequences for discrete event systems in uncertain environments where uncontrollable events may occur. Timed Petri nets are used for this purpose. The aim is to drive the marking of the net from an initial value to a reference one, in minimal or near-minimal time, by avoiding forbidden markings, deadlocks, and dead branches. The approach is similar to model predictive control with a finite set of control actions. At each step only a small area of the reachability graph is explored: this leads to a reasonable computational complexity. The robustness of the resulting trajectory is also evaluated according to a risk probability. A sufficient condition is provided to compute robust trajectories. The proposed results are applicable to a large class of discrete event systems, in particular in the domains of flexible manufacturing. However, they are also applicable to other domains as communication, computer science, transportation, and traffic as long as the considered systems admit Petri Nets (PNs models. They are suitable for dynamical deadlock-free scheduling and reconfiguration problems in uncertain environments.
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German emergency management concept
International Nuclear Information System (INIS)
Burkart, K.
1993-01-01
The advantages and disadvantages of the margin and start-up value concepts (according to ICRP 40 and EU-ordinances) are explained, and it is demonstrated that the two concepts are combinable. The combined concept has the advantage of immediately providing, if required, intervention levels for the various measures to be taken, and of obliging those persons concerned with emergency protection to study and quantify, already at the planning stage, the influence of a range of accident conditions on the decision on measures. In this context, the use of computerized decision support systems which are currently being developed is indispensable. (orig./DG) [de
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Fuzzy Backstepping Sliding Mode Control for Mismatched Uncertain System
Directory of Open Access Journals (Sweden)
H. Q. Hou
2014-06-01
Full Text Available Sliding mode controllers have succeeded in many control problems that the conventional control theories have difficulties to deal with; however it is practically impossible to achieve high-speed switching control. Therefore, in this paper an adaptive fuzzy backstepping sliding mode control scheme is derived for mismatched uncertain systems. Firstly fuzzy sliding mode controller is designed using backstepping method based on the Lyapunov function approach, which is capable of handling mismatched problem. Then fuzzy sliding mode controller is designed using T-S fuzzy model method, it can improve the performance of the control systems and their robustness. Finally this method of control is applied to nonlinear system as a case study; simulation results are also provided the performance of the proposed controller.
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Multilateral Telecoordinated Control of Multiple Robots With Uncertain Kinematics.
Zhai, Di-Hua; Xia, Yuanqing
2017-06-06
This paper addresses the telecoordinated control of multiple robots in the simultaneous presence of asymmetric time-varying delays, nonpassive external forces, and uncertain kinematics/dynamics. To achieve the control objective, a neuroadaptive controller with utilizing prescribed performance control and switching control technique is developed, where the basic idea is to employ the concept of motion synchronization in each pair of master-slave robots and among all slave robots. By using the multiple Lyapunov-Krasovskii functionals method, the state-independent input-to-output practical stability of the closed-loop system is established. Compared with the previous approaches, the new design is straightforward and easier to implement and is applicable to a wider area. Simulation results on three pairs of three degrees-of-freedom robots confirm the theoretical findings.
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Engel, Y.; Dimitrova, N.G.; Khapova, S.N.; Elfring, T.
2014-01-01
Entrepreneurs' initial strategy choices are made in the face of inherently uncertain and fundamentally unpredictable futures. Yet, unlike experts, novice entrepreneurs still tend to rely on predictions and forecasts as they move their ideas through t h e venture creation process. This study examines
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Vliet, van M.; Kok, K.
2015-01-01
Water management strategies in times of global change need to be developed within a complex and uncertain environment. Scenarios are often used to deal with uncertainty. A novel backcasting methodology has been tested in which a normative objective (e.g. adaptive water management) is backcasted
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Sliding mode control for uncertain unified chaotic systems with input nonlinearity
International Nuclear Information System (INIS)
Chiang, T.-Y.; Hung, M.-L.; Yan, J.-J.; Yang, Y.-S.; Chang, J.-F.
2007-01-01
This paper investigates the stabilization problem for a class of unified chaotic systems subject to uncertainties and input nonlinearity. Using the sliding mode control technique, a robust control law is established which stabilizes the uncertain unified chaotic systems even when the nonlinearity in the actuators is present. A novel adaptive switching surface is introduced to simplify the task of assigning the stability of the closed-loop system in the sliding mode motion. An illustrative example is given to demonstrate the effectiveness of the proposed sliding mode control design
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The step complexity measure for emergency operating procedures - comparing with simulation data
International Nuclear Information System (INIS)
Park, Jinkyun; Jung, Wondea; Kim, Jaewhan; Ha, Jaejoo; Shin, Yunghwa
2001-01-01
In complex systems, such as nuclear power plants (NPPs) or airplane control systems, human errors play a major role in many accidents. Therefore, to prevent occurrences of accidents or to ensure system safety, extensive effort has been made to identify significant factors that cause human errors. According to related studies, written manuals or operating procedures are revealed as one of the most important factors, and complexity or understandability of a procedure is pointed out as one of the major reasons that make procedure-related human errors. Many qualitative checklists are suggested to evaluate emergency operating procedures (EOPs) of NPPs. However, since qualitative evaluations using checklists have some drawbacks, a quantitative measure that can quantify the complexity of EOPs is imperative to compensate for them. In order to quantify the complexity of EOPs, Park et al. suggested the step complexity (SC) measure to quantify the complexity of a step included in EOPs. In this paper, to ensure the appropriateness of the SC measure, SC scores are compared with averaged step performance time data obtained from emergency training records. The total number of available records is 36, and training scenarios are the loss of coolant accident and the excess steam dump event. The number of scenario is 18 each. From these emergency training records, step performance time data for 39 steps are retrieved, and they are compared with estimated SC scores of them. In addition, several questions that are needed to clarify the appropriateness of the SC measure are also discussed. As a result, it was observed that estimated SC scores and step performance time data have a statistically meaningful correlation. Thus, it can be concluded that the SC measure can quantify the complexity of steps included in EOPs
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Control uncertain Genesio-Tesi chaotic system: Adaptive sliding mode approach
International Nuclear Information System (INIS)
Dadras, Sara; Momeni, Hamid Reza
2009-01-01
An adaptive sliding mode control (ASMC) technique is introduced in this paper for a chaotic dynamical system (Genesio-Tesi system). Using the sliding mode control technique, a sliding surface is determined and the control law is established. An adaptive sliding mode control law is derived to make the states of the Genesio-Tesi system asymptotically track and regulate the desired state. The designed control scheme can control the uncertain chaotic behaviors to a desired state without oscillating very fast and guarantee the property of asymptotical stability. An illustrative simulation result is given to demonstrate the effectiveness of the proposed adaptive sliding mode control design.
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uncertain dynamic systems on time scales
Directory of Open Access Journals (Sweden)
V. Lakshmikantham
1995-01-01
Full Text Available A basic feedback control problem is that of obtaining some desired stability property from a system which contains uncertainties due to unknown inputs into the system. Despite such imperfect knowledge in the selected mathematical model, we often seek to devise controllers that will steer the system in a certain required fashion. Various classes of controllers whose design is based on the method of Lyapunov are known for both discrete [4], [10], [15], and continuous [3–9], [11] models described by difference and differential equations, respectively. Recently, a theory for what is known as dynamic systems on time scales has been built which incorporates both continuous and discrete times, namely, time as an arbitrary closed sets of reals, and allows us to handle both systems simultaneously [1], [2], [12], [13]. This theory permits one to get some insight into and better understanding of the subtle differences between discrete and continuous systems. We shall, in this paper, utilize the framework of the theory of dynamic systems on time scales to investigate the stability properties of conditionally invariant sets which are then applied to discuss controlled systems with uncertain elements. For the notion of conditionally invariant set and its stability properties, see [14]. Our results offer a new approach to the problem in question.
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Exponential convergence rate estimation for uncertain delayed neural networks of neutral type
International Nuclear Information System (INIS)
Lien, C.-H.; Yu, K.-W.; Lin, Y.-F.; Chung, Y.-J.; Chung, L.-Y.
2009-01-01
The global exponential stability for a class of uncertain delayed neural networks (DNNs) of neutral type is investigated in this paper. Delay-dependent and delay-independent criteria are proposed to guarantee the robust stability of DNNs via LMI and Razumikhin-like approaches. For a given delay, the maximal allowable exponential convergence rate will be estimated. Some numerical examples are given to illustrate the effectiveness of our results. The simulation results reveal significant improvement over the recent results.
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Nguyen, Nhan
2013-01-01
This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.
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Talaei, Behzad; Jagannathan, Sarangapani; Singler, John
2018-04-01
In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.
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Heunen, Chris
2008-01-01
We consider categorical logic on the category of Hilbert spaces. More generally, in fact, any pre-Hilbert category suffices. We characterise closed subobjects, and prove that they form orthomodular lattices. This shows that quantum logic is just an incarnation of categorical logic, enabling us to establish an existential quantifier for quantum logic, and conclude that there cannot be a universal quantifier.
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Quantifying the relationship between financial news and the stock market.
Alanyali, Merve; Moat, Helen Susannah; Preis, Tobias
2013-12-20
The complex behavior of financial markets emerges from decisions made by many traders. Here, we exploit a large corpus of daily print issues of the Financial Times from 2(nd) January 2007 until 31(st) December 2012 to quantify the relationship between decisions taken in financial markets and developments in financial news. We find a positive correlation between the daily number of mentions of a company in the Financial Times and the daily transaction volume of a company's stock both on the day before the news is released, and on the same day as the news is released. Our results provide quantitative support for the suggestion that movements in financial markets and movements in financial news are intrinsically interlinked.
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Choi, Yun Ho; Yoo, Sung Jin
2018-06-01
This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
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Hyun, J. Y.; Yang, Y. C. E.; Tidwell, V. C.; Macknick, J.
2017-12-01
Modeling human behaviors and decisions in water resources management is a challenging issue due to its complexity and uncertain characteristics that affected by both internal (such as stakeholder's beliefs on any external information) and external factors (such as future policies and weather/climate forecast). Stakeholders' decision regarding how much water they need is usually not entirely rational in the real-world cases, so it is not quite suitable to model their decisions with a centralized (top-down) approach that assume everyone in a watershed follow the same order or pursue the same objective. Agent-based modeling (ABM) uses a decentralized approach (bottom-up) that allow each stakeholder to make his/her own decision based on his/her own objective and the belief of information acquired. In this study, we develop an ABM which incorporates the psychological human decision process by the theory of risk perception. The theory of risk perception quantifies human behaviors and decisions uncertainties using two sequential methodologies: the Bayesian Inference and the Cost-Loss Problem. The developed ABM is coupled with a regulation-based water system model: Riverware (RW) to evaluate different human decision uncertainties in water resources management. The San Juan River Basin in New Mexico (Figure 1) is chosen as a case study area, while we define 19 major irrigation districts as water use agents and their primary decision is to decide the irrigated area on an annual basis. This decision will be affected by three external factors: 1) upstream precipitation forecast (potential amount of water availability), 2) violation of the downstream minimum flow (required to support ecosystems), and 3) enforcement of a shortage sharing plan (a policy that is currently undertaken in the region for drought years). Three beliefs (as internal factors) that correspond to these three external factors will also be considered in the modeling framework. The objective of this study is
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Allowances for evolving coastal flood risk under uncertain local sea-level rise
Buchanan, M. K.; Kopp, R. E.; Oppenheimer, M.; Tebaldi, C.
2015-12-01
Sea-level rise (SLR) causes estimates of flood risk made under the assumption of stationary mean sea level to be biased low. However, adjustments to flood return levels made assuming fixed increases of sea level are also inaccurate when applied to sea level that is rising over time at an uncertain rate. To accommodate both the temporal dynamics of SLR and their uncertainty, we develop an Average Annual Design Life Level (AADLL) metric and associated SLR allowances [1,2]. The AADLL is the flood level corresponding to a time-integrated annual expected probability of occurrence (AEP) under uncertainty over the lifetime of an asset; AADLL allowances are the adjustment from 2000 levels that maintain current risk. Given non-stationary and uncertain SLR, AADLL flood levels and allowances provide estimates of flood protection heights and offsets for different planning horizons and different levels of confidence in SLR projections in coastal areas. Allowances are a function primarily of local SLR and are nearly independent of AEP. Here we employ probabilistic SLR projections [3] to illustrate the calculation of AADLL flood levels and allowances with a representative set of long-duration tide gauges along U.S. coastlines. [1] Rootzen et al., 2014, Water Resources Research 49: 5964-5972. [2] Hunter, 2013, Ocean Engineering 71: 17-27. [3] Kopp et al., 2014, Earth's Future 2: 383-406.
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Tsunami hazard assessments with consideration of uncertain earthquakes characteristics
Sepulveda, I.; Liu, P. L. F.; Grigoriu, M. D.; Pritchard, M. E.
2017-12-01
The uncertainty quantification of tsunami assessments due to uncertain earthquake characteristics faces important challenges. First, the generated earthquake samples must be consistent with the properties observed in past events. Second, it must adopt an uncertainty propagation method to determine tsunami uncertainties with a feasible computational cost. In this study we propose a new methodology, which improves the existing tsunami uncertainty assessment methods. The methodology considers two uncertain earthquake characteristics, the slip distribution and location. First, the methodology considers the generation of consistent earthquake slip samples by means of a Karhunen Loeve (K-L) expansion and a translation process (Grigoriu, 2012), applicable to any non-rectangular rupture area and marginal probability distribution. The K-L expansion was recently applied by Le Veque et al. (2016). We have extended the methodology by analyzing accuracy criteria in terms of the tsunami initial conditions. Furthermore, and unlike this reference, we preserve the original probability properties of the slip distribution, by avoiding post sampling treatments such as earthquake slip scaling. Our approach is analyzed and justified in the framework of the present study. Second, the methodology uses a Stochastic Reduced Order model (SROM) (Grigoriu, 2009) instead of a classic Monte Carlo simulation, which reduces the computational cost of the uncertainty propagation. The methodology is applied on a real case. We study tsunamis generated at the site of the 2014 Chilean earthquake. We generate earthquake samples with expected magnitude Mw 8. We first demonstrate that the stochastic approach of our study generates consistent earthquake samples with respect to the target probability laws. We also show that the results obtained from SROM are more accurate than classic Monte Carlo simulations. We finally validate the methodology by comparing the simulated tsunamis and the tsunami records for
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Plastic plate bending problem with friction on the boundary and uncertain input data
Czech Academy of Sciences Publication Activity Database
Hlaváček, Ivan
2010-01-01
Roč. 31, č. 4 (2010), s. 414-439 ISSN 0163-0563 R&D Projects: GA AV ČR(CZ) IAA100190803 Institutional research plan: CEZ:AV0Z10190503 Keywords : anti- optimization * deformation theory of plasticity * Kačanov method * uncertain input data * worst scenario Subject RIV: BA - General Mathematics Impact factor: 0.687, year: 2010 http://www.tandfonline.com/doi/abs/10.1080/01630563.2010.483311
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Fengjiao Wu; Guitao Zhang; Zhengzhong Wang
2016-01-01
The robust fuzzy control for fractional-order hydroturbine regulating system is studied in this paper. First, the more practical fractional-order hydroturbine regulating system with uncertain parameters and random disturbances is presented. Then, on the basis of interval matrix theory and fractional-order stability theorem, a fuzzy control method is proposed for fractional-order hydroturbine regulating system, and the stability condition is expressed as a group of linear matrix inequalities. ...
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Chaos control and duration time of a class of uncertain chaotic systems
International Nuclear Information System (INIS)
Bowong, Samuel; Moukam Kakmeni, F.M.
2003-01-01
This Letter presents a robust control scheme for a class of uncertain chaotic systems in the canonical form, with unknown nonlinearities. To cope with the uncertainties, we combine Lyapunov methodology with observer design. The proposed strategy comprises an exponential linearizing feedback and an uncertainty estimator. The developed control scheme allows chaos suppression. The advantage of this method over the existing results is that the control time is explicitly computed. Simulations studies are conducted to verify the effectiveness of the scheme
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Directory of Open Access Journals (Sweden)
Steffie H A Brouns
Full Text Available Emergency department (ED crowding leads to prolonged emergency department length of stay (ED-LOS and adverse patient outcomes. No uniform definition of ED crowding exists. Several scores have been developed to quantify ED crowding; the best known is the Emergency Department Work Index (EDWIN. Research on the EDWIN is often applied to limited settings and conducted over a short period of time.To explore whether the EDWIN as a measure can track occupancy at a Dutch ED over the course of one year and to identify fluctuations in ED occupancy per hour, day, and month. Secondary objective is to investigate the discriminatory value of the EDWIN in detecting crowding, as compared with the occupancy rate and prolonged ED-LOS.A retrospective cohort study of all ED visits during the period from September 2010 to August 2011 was performed in one hospital in the Netherlands. The EDWIN incorporates the number of patients per triage level, physicians, treatment beds and admitted patients to quantify ED crowding. The EDWIN was adjusted to emergency care in the Netherlands: modified EDWIN (mEDWIN. ED crowding was defined as the 75th percentile of mEDWIN per hour, which was ≥0.28.In total, 28,220 ED visits were included in the analysis. The median mEDWIN per hour was 0.15 (Interquartile range (IQR 0.05-0.28; median mEDWIN per patient was 0.25 (IQR 0.15-0.39. The EDWIN was higher on Wednesday (0.16 than on other days (0.14-0.16, p<0.001, and a peak in both mEDWIN (0.30-0.33 and ED crowding (52.9-63.4% was found between 13:00-18:00 h. A comparison of the mEDWIN with the occupancy rate revealed an area under the curve (AUC of 0.86 (95%CI 0.85-0.87. The AUC of mEDWIN compared with a prolonged ED-LOS (≥4 hours was 0.50 (95%CI 0.40-0.60.The mEDWIN was applicable at a Dutch ED. The mEDWIN was able to identify fluctuations in ED occupancy. In addition, the mEDWIN had high discriminatory power for identification of a busy ED, when compared with the occupancy rate.
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Bare quantifier fronting as contrastive topicalization
Directory of Open Access Journals (Sweden)
Ion Giurgea
2015-11-01
Full Text Available I argue that indefinites (in particular bare quantifiers such as ‘something’, ‘somebody’, etc. which are neither existentially presupposed nor in the restriction of a quantifier over situations, can undergo topicalization in a number of Romance languages (Catalan, Italian, Romanian, Spanish, but only if the sentence contains “verum” focus, i.e. focus on a high degree of certainty of the sentence. I analyze these indefinites as contrastive topics, using Büring’s (1999 theory (where the term ‘S-topic’ is used for what I call ‘contrastive topic’. I propose that the topic is evaluated in relation to a scalar set including generalized quantifiers such as {lP $x P(x, lP MANYx P(x, lP MOSTx P(x, lP “xP(x} or {lP $xP(x, lP P(a, lP P(b …}, and that the contrastive topic is the weakest generalized quantifier in this set. The verum focus, which is part of the “comment” that co-occurs with the “Topic”, introduces a set of alternatives including degrees of certainty of the assertion. The speaker asserts that his claim is certainly true or highly probable, contrasting it with stronger claims for which the degree of probability is unknown. This explains the observation that in downward entailing contexts, the fronted quantified DPs are headed by ‘all’ or ‘many’, whereas ‘some’, small numbers or ‘at least n’ appear in upward entailing contexts. Unlike other cases of non-specific topics, which are property topics, these are quantifier topics: the topic part is a generalized quantifier, the comment is a property of generalized quantifiers. This explains the narrow scope of the fronted quantified DP.
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On Uncertain Ice: The Future of Arctic Shipping and the Northwest Passage
Directory of Open Access Journals (Sweden)
Whitney Lackenbauer
2014-12-01
Full Text Available The Arctic sea-ice is in a state of rapid decline. Barriers to navigation that once doomed the likes of Sir John Franklin and closed the shortcut to the Orient now seem to be melting away. The prospect of shorter, transpolar transportation routes linking Asian and Western markets has inspired excitement and fear, and particularly the latter when it comes to Canadian sovereignty. This paper confirms recent studies suggesting that, in spite of the general trend towards reduced ice cover in the Arctic Basin, environmental variability, scarce infrastructure and other navigational aids, and uncertain economics make it unlikely that the Northwest Passage will emerge as a viable trans-shipping route in the foreseeable future. Instead, the region is likely to witness a steady increase in resource, resupply, and tourist destinational shipping. Accordingly, concerns that this increased activity will adversely affect Canadian sovereignty are misplaced. Rather than calling into question Canadian control, foreign vessels engaged in local activities are likely to reinforce Canada’s legal position by demonstrating an international acceptance of Canadian laws and regulations. Rather than worrying about the “sovereignty” ramifications of Arctic shipping, the Canadian government should focus its short – and medium – term energies on the practical requirements of developing and maintaining safe shipping routes. At the heart of this requirement is ensuring that such activity is beneficial to Inuit, whose traditional “highways” will double as transits routes for resource carriers and cruise liners. If developed with an eye to those most directly affected, Canada’s Arctic waters can become a well-managed route to an increasingly attractive region, making our Arctic a destination rather than mere space through which to pass.
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Vlek, Charles
2010-01-01
Rational decision theory could be more fully exploited for the prudent management of uncertain-risk situations. After an integrative circumscription of the precautionary principle (PP), 10 key issues are discussed covering assessment, decision and control. In view of this, a variety of
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The Importance of Studying Past Extreme Floods to Prepare for Uncertain Future Extremes
Burges, S. J.
2016-12-01
Hoyt and Langbein, 1955 in their book `Floods' wrote: " ..meteorologic and hydrologic conditions will combine to produce superfloods of unprecedented magnitude. We have every reason to believe that in most rivers past floods may not be an accurate measure of ultimate flood potentialities. It is this superflood with which we are always most concerned". I provide several examples to offer some historical perspective on assessing extreme floods. In one example, flooding in the Miami Valley, OH in 1913 claimed 350 lives. The engineering and socio-economic challenges facing the Morgan Engineering Co in how to mitigate against future flood damage and loss of life when limited information was available provide guidance about ways to face an uncertain hydroclimate future, particularly one of a changed climate. A second example forces us to examine mixed flood populations and illustrates the huge uncertainty in assigning flood magnitude and exceedance probability to extreme floods in such cases. There is large uncertainty in flood frequency estimates; knowledge of the total flood hydrograph, not the peak flood flow rate alone, is what is needed for hazard mitigation assessment or design. Some challenges in estimating the complete flood hydrograph in an uncertain future climate, including demands on hydrologic models and their inputs, are addressed.
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A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.
Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing
2018-03-07
The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.
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Emergency Physicians as Good Samaritans: Survey of Frequency, Locations, Supplies and Medications
Directory of Open Access Journals (Sweden)
Taylor W. Burkholder, MD, MPH
2016-01-01
Full Text Available Introduction: Little is known about the frequency and locations in which emergency physicians (EPs are bystanders to an accident or emergency; equally uncertain is which contents of an “emergency kit” may be useful during such events. The aim of this study was to describe the frequency and locations of Good Samaritan acts by EPs and also determine which emergency kit supplies and medications were most commonly used by Good Samaritans. Methods: We conducted an electronic survey among a convenience sample of EPs in Colorado. Results: Respondents reported a median frequency of 2.0 Good Samaritan acts per five years of practice, with the most common locations being sports and entertainment events (25%, road traffic accidents (21%, and wilderness settings (19%. Of those who had acted as Good Samaritans, 86% reported that at least one supply would have been useful during the most recent event, and 66% reported at least one medication would have been useful. The most useful supplies were gloves (54%, dressings (34%, and a stethoscope (20%, while the most useful medications were oxygen (19%, intravenous fluids (17%, and epinephrine (14%. Conclusion: The majority of EPs can expect to provide Good Samaritan care during their careers and would be better prepared by carrying a kit with common supplies and medications where they are most likely to use them.
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Multidominance, ellipsis, and quantifier scope
Temmerman, Tanja Maria Hugo
2012-01-01
This dissertation provides a novel perspective on the interaction between quantifier scope and ellipsis. It presents a detailed investigation of the scopal interaction between English negative indefinites, modals, and quantified phrases in ellipsis. One of the crucial observations is that a negative
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Connected Car: Quantified Self becomes Quantified Car
Directory of Open Access Journals (Sweden)
Melanie Swan
2015-02-01
Full Text Available The automotive industry could be facing a situation of profound change and opportunity in the coming decades. There are a number of influencing factors such as increasing urban and aging populations, self-driving cars, 3D parts printing, energy innovation, and new models of transportation service delivery (Zipcar, Uber. The connected car means that vehicles are now part of the connected world, continuously Internet-connected, generating and transmitting data, which on the one hand can be helpfully integrated into applications, like real-time traffic alerts broadcast to smartwatches, but also raises security and privacy concerns. This paper explores the automotive connected world, and describes five killer QS (Quantified Self-auto sensor applications that link quantified-self sensors (sensors that measure the personal biometrics of individuals like heart rate and automotive sensors (sensors that measure driver and passenger biometrics or quantitative automotive performance metrics like speed and braking activity. The applications are fatigue detection, real-time assistance for parking and accidents, anger management and stress reduction, keyless authentication and digital identity verification, and DIY diagnostics. These kinds of applications help to demonstrate the benefit of connected world data streams in the automotive industry and beyond where, more fundamentally for human progress, the automation of both physical and now cognitive tasks is underway.
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Robust DEA under discrete uncertain data: a case study of Iranian electricity distribution companies
Hafezalkotob, Ashkan; Haji-Sami, Elham; Omrani, Hashem
2015-06-01
Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA). However, the real-world problems often deal with imprecise or ambiguous data. In this paper, we propose a novel robust data envelopment model (RDEA) to investigate the efficiencies of decision-making units (DMU) when there are discrete uncertain input and output data. The method is based upon the discrete robust optimization approaches proposed by Mulvey et al. (1995) that utilizes probable scenarios to capture the effect of ambiguous data in the case study. Our primary concern in this research is evaluating electricity distribution companies under uncertainty about input/output data. To illustrate the ability of proposed model, a numerical example of 38 Iranian electricity distribution companies is investigated. There are a large amount ambiguous data about these companies. Some electricity distribution companies may not report clear and real statistics to the government. Thus, it is needed to utilize a prominent approach to deal with this uncertainty. The results reveal that the RDEA model is suitable and reliable for target setting based on decision makers (DM's) preferences when there are uncertain input/output data.
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Directory of Open Access Journals (Sweden)
Jimyung Kang
2017-10-01
Full Text Available Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of virtual generator, the amount of load reduction includes inevitable uncertainty, because it consists of a very large number of independent energy customers. While they may reduce energy today, they might not tomorrow. In this circumstance, a DSRP must choose a proper set of these uncertain customers to achieve the exact preferred amount of load curtailment. In this paper, the customer selection problem for a service provider that consists of uncertain responses of customers is defined and solved. The uncertainty of energy reduction is fully considered in the formulation with data-driven probability distribution modeling and stochastic programming technique. The proposed optimization method that utilizes only the observed load data provides a realistic and applicable solution to a demand response system. The performance of the proposed optimization is verified with real demand response event data in Korea, and the results show increased and stabilized performance from the service provider’s perspective.
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Workplace Violence and Harassment Against Emergency Medicine Residents
Schnapp, Benjamin H.; Slovis, Benjamin H.; Shah, Anar D.; Fant, Abra L.; Gisondi, Michael A.; Shah, Kaushal H.; Lech, Christie A.
2016-01-01
Introduction: Several studies have shown that workplace violence in the emergency department (ED) iscommon. Residents may be among the most vulnerable staff, as they have the least experience with thesevolatile encounters. The goal for this study was to quantify and describe acts of violence against emergencymedicine (EM) residents by patients and visitors and to identify perceived barriers to safety. Methods: This cross-sectional survey study queried EM residents at mul...
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Shofa, M. J.; Moeis, A. O.; Restiana, N.
2018-04-01
MRP as a production planning system is appropriate for the deterministic environment. Unfortunately, most production systems such as customer demands are stochastic, so that MRP is inappropriate at the time. Demand-Driven MRP (DDMRP) is new approach for production planning system dealing with demand uncertainty. The objective of this paper is to compare the MRP and DDMRP for purchased part under long lead time and uncertain demand in terms of average inventory levels. The evaluation is conducted through a discrete event simulation with the long lead time and uncertain demand scenarios. The next step is evaluating the performance of DDMRP by comparing the inventory level of DDMRP with MRP. As result, DDMRP is more effective production planning than MRP in terms of average inventory levels.
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ZAFFAGNINI, STEFANO; LOPOMO, NICOLA; SIGNORELLI, CECILIA; MUCCIOLI, GIULIO MARIA MARCHEGGIANI; BONANZINGA, TOMMASO; GRASSI, ALBERTO; RAGGI, FEDERICO; VISANI, ANDREA; MARCACCI, MAURILIO
2014-01-01
The main purpose of this article was to describe in detail, from the perspective of the clinical end user, a previously presented non-invasive methodology, applied in the treatment of anterior cruciate ligament injury, in which inertial sensors are used to quantify the pivot shift test. The outcomes obtained and relative considerations were compared with findings emerging from a review of the relevant updated literature. The detailed description here provided covers the system, the parameters...
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Qiu, Xin; Miikkulainen, Risto
2018-01-01
Optimization problems with uncertain fitness functions are common in the real world, and present unique challenges for evolutionary optimization approaches. Existing issues include excessively expensive evaluation, lack of solution reliability, and incapability in maintaining high overall fitness during optimization. Using conversion rate optimization as an example, this paper proposes a series of new techniques for addressing these issues. The main innovation is to augment evolutionary algor...
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Directory of Open Access Journals (Sweden)
Hua Chen
2013-01-01
Full Text Available The practical stabilization problem is addressed for a class of uncertain nonholonomic mobile robots with uncalibrated visual parameters. Based on the visual servoing kinematic model, a new switching controller is presented in the presence of parametric uncertainties associated with the camera system. In comparison with existing methods, the new design method is directly used to control the original system without any state or input transformation, which is effective to avoid singularity. Under the proposed control law, it is rigorously proved that all the states of closed-loop system can be stabilized to a prescribed arbitrarily small neighborhood of the zero equilibrium point. Furthermore, this switching control technique can be applied to solve the practical stabilization problem of a kind of mobile robots with uncertain parameters (and angle measurement disturbance which appeared in some literatures such as Morin et al. (1998, Hespanha et al. (1999, Jiang (2000, and Hong et al. (2005. Finally, the simulation results show the effectiveness of the proposed controller design approach.
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Parameter-dependent PWQ Lyapunov function stability criteria for uncertain piecewise linear systems
Directory of Open Access Journals (Sweden)
Morten Hovd
2018-01-01
Full Text Available The calculation of piecewise quadratic (PWQ Lyapunov functions is addressed in view of stability analysis of uncertain piecewise linear dynamics. As main contribution, the linear matrix inequality (LMI approach proposed in (Johansson and Rantzer, 1998 for the stability analysis of PWL and PWA dynamics is extended to account for parametric uncertainty based on a improved relaxation technique. The results are applied for the analysis of a Phase Locked Loop (PLL benchmark and the ability to guarantee a stability region in the parameter space well beyond the state of the art is demonstrated.
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Stabilization of constrained uncertain systems by an off-line approach using zonotopes
Directory of Open Access Journals (Sweden)
Walid Hamdi
2018-01-01
Full Text Available In this paper, stabilization of uncertain systems was established using zonotopic sets. The obtained state feedback control laws are computed by an off-line approach reducing computational burdens. The resolution of a robust model predictive control (MPC allows computing a sequence of state feedback control laws corresponding to a sequence of zonotopic invariant sets. The implemented control laws are then calculated by linear interpolation between the state feedback gains corresponding to the nested pre-computed zonotopic sets. The proposed interpolation with the use of zonotopic sets achieves better control performances.
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Functional assays for analysis of variants of uncertain significance in BRCA2
DEFF Research Database (Denmark)
Guidugli, Lucia; Carreira, Aura; Caputo, Sandrine M
2014-01-01
Missense variants in the BRCA2 gene are routinely detected during clinical screening for pathogenic mutations in patients with a family history of breast and ovarian cancer. These subtle changes frequently remain of unknown clinical significance because of the lack of genetic information that may...... of uncertain significance analyzed, and describe a validation set of (genetically) proven pathogenic and neutral missense variants to serve as a golden standard for the validation of each assay. Guidelines are proposed to enable implementation of laboratory-based methods to assess the impact of the variant...
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Gavrilescu, M.; Demnerová, K.; Aamand, J.; Agathos, S.; Fava, F.
2015-01-01
Emerging pollutants reach the environment from various anthropogenic sources and are distributed throughout environmental matrices. Although great advances have been made in the detection and analysis of trace pollutants during recent decades, due to the continued development and refinement of specific techniques, a wide array of undetected contaminants of emerging environmental concern need to be identified and quantified in various environmental components and biological tissues. These poll...
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Climate mitigation under an uncertain technology future: A TIAM-World analysis
International Nuclear Information System (INIS)
Labriet, Maryse; Kanudia, Amit; Loulou, Richard
2012-01-01
This paper explores the impacts of long-term technology and climate uncertainties on the optimal evolution of the World energy system. Stochastic programming with the TIAM-World model is used for a parametric analysis of hedging strategies, varying the probabilities associated to each of two contrasted technology outlooks. The parametric analysis constitutes an original supplement to the computation of hedging strategies by identifying technologies that are robust under a broad range of probabilities of the two technology outlooks. Natural gas appears to be one of the most appealing robust options in an uncertain technological context, especially in China, given its relatively low emissions and the low capital cost of associated technologies. Natural gas and some other options are in fact considered as “super-hedging” actions, penetrating more in the hedging solution than in any of the deterministic scenarios. Nuclear power and CCS use are less robust: they depend much more on either the level of the climate target or the probabilities of the technology outlooks. The analysis also shows that technological uncertainty has a greater impact under milder climate targets than under more severe ones. Future research might consider a larger set of possible technology outlooks, as well as specific analyses focused on key characteristics of low-carbon technologies. - Highlights: ► The hedging strategy is not an average of deterministic strategies. ► The hedging offers a mix of abatement actions that cannot easily be found otherwise. ► Natural gas is an appealing choice in an uncertain context, especially in China. ► China reduces its emissions only when options in other countries are exhausted.
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Probabilistic Dynamics for Integrated Analysis of Accident Sequences considering Uncertain Events
Directory of Open Access Journals (Sweden)
Robertas Alzbutas
2015-01-01
Full Text Available The analytical/deterministic modelling and simulation/probabilistic methods are used separately as a rule in order to analyse the physical processes and random or uncertain events. However, in the currently used probabilistic safety assessment this is an issue. The lack of treatment of dynamic interactions between the physical processes on one hand and random events on the other hand causes the limited assessment. In general, there are a lot of mathematical modelling theories, which can be used separately or integrated in order to extend possibilities of modelling and analysis. The Theory of Probabilistic Dynamics (TPD and its augmented version based on the concept of stimulus and delay are introduced for the dynamic reliability modelling and the simulation of accidents in hybrid (continuous-discrete systems considering uncertain events. An approach of non-Markovian simulation and uncertainty analysis is discussed in order to adapt the Stimulus-Driven TPD for practical applications. The developed approach and related methods are used as a basis for a test case simulation in view of various methods applications for severe accident scenario simulation and uncertainty analysis. For this and for wider analysis of accident sequences the initial test case specification is then extended and discussed. Finally, it is concluded that enhancing the modelling of stimulated dynamics with uncertainty and sensitivity analysis allows the detailed simulation of complex system characteristics and representation of their uncertainty. The developed approach of accident modelling and analysis can be efficiently used to estimate the reliability of hybrid systems and at the same time to analyze and possibly decrease the uncertainty of this estimate.
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Uncertain Climate Forecasts From Multimodel Ensembles: When to Use Them and When to Ignore Them
Jewson, Stephen; Rowlands, Dan
2010-01-01
Uncertainty around multimodel ensemble forecasts of changes in future climate reduces the accuracy of those forecasts. For very uncertain forecasts this effect may mean that the forecasts should not be used. We investigate the use of the well-known Bayesian Information Criterion (BIC) to make the decision as to whether a forecast should be used or ignored.
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Central Libraries in Uncertain Times.
Kenney, Brian J.
2001-01-01
Discusses security and safety issues for public libraries, especially high-profile central facilities, in light of the September 11 terrorist attacks. Highlights include inspecting bags as patrons enter as well as exit; the need for security guidelines for any type of disaster or emergency; building design; and the importance of communication.…
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Rasouli, S.; Timmermans, H.J.P.
2014-01-01
The aim of this paper is to assess the impact of uncertain travel times as reflected in travel time variability on the outcomes of individuals’ activity–travel scheduling decisions, assuming they are faced with fixed space–time constraints and apply the set of decision rules that they have developed
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Reviewing the History of Pandemic Influenza: Understanding Patterns of Emergence and Transmission
Saunders-Hastings, Patrick R.; Krewski, Daniel
2016-01-01
For centuries, novel strains of influenza have emerged to produce human pandemics, causing widespread illness, death, and disruption. There have been four influenza pandemics in the past hundred years. During this time, globalization processes, alongside advances in medicine and epidemiology, have altered the way these pandemics are experienced. Drawing on international case studies, this paper provides a review of the impact of past influenza pandemics, while examining the evolution of our understanding of, and response to, these viruses. This review argues that pandemic influenza is in part a consequence of human development, and highlights the importance of considering outbreaks within the context of shifting global landscapes. While progress in infectious disease prevention, control, and treatment has improved our ability to respond to such outbreaks, globalization processes relating to human behaviour, demographics, and mobility have increased the threat of pandemic emergence and accelerated global disease transmission. Preparedness planning must continue to evolve to keep pace with this heightened risk. Herein, we look to the past for insights on the pandemic experience, underlining both progress and persisting challenges. However, given the uncertain timing and severity of future pandemics, we emphasize the need for flexible policies capable of responding to change as such emergencies develop. PMID:27929449
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International Nuclear Information System (INIS)
Park, Taeil; Kim, Changyoon; Kim, Hyoungkwan
2014-01-01
Highlights: • A real option-based model for the valuation of CDM projects is proposed. • This study investigates the impact of energy policies on the value of CDM projects. • Level of target emission and its schedule should be carefully designed. • Government subsidy facilitates the implementation of CDM projects. • Period for free emission allowance prevents promoting CDM projects. - Abstract: Emission trading has been considered a primary policy tool for emission reduction. Governments establish national targets for emission reduction and assign emission reduction goals to private entities to accomplish the targets. To attain the goal, private entities should perform offset projects that can produce emission credits or buy emission credits from the market. However, it is not easy for private entities to decide to implement the projects because energy policies associated with emission trading keep changing; thus, the future benefits of the offset projects are quite uncertain. This study presents a real option-based model to investigate how uncertain energy policies affect the financial viability of an offset project. A case study showed that the establishment of a target emission was attractive to the government because it could make the CDM project financially viable with a small amount of government subsidy. In addition, the level of the government subsidy could determine the investment timing for the CDM project. In this context, governments should be cautious in designing energy policies, because even the same energy policies could have different impacts on private entities. Overall, this study is expected to assist private entities in establishing proper investment strategies for CDM projects under uncertain energy policies
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Robust Economic Control Decision Method of Uncertain System on Urban Domestic Water Supply.
Li, Kebai; Ma, Tianyi; Wei, Guo
2018-03-31
As China quickly urbanizes, urban domestic water generally presents the circumstances of both rising tendency and seasonal cycle fluctuation. A robust economic control decision method for dynamic uncertain systems is proposed in this paper. It is developed based on the internal model principle and pole allocation method, and it is applied to an urban domestic water supply system with rising tendency and seasonal cycle fluctuation. To achieve this goal, first a multiplicative model is used to describe the urban domestic water demand. Then, a capital stock and a labor stock are selected as the state vector, and the investment and labor are designed as the control vector. Next, the compensator subsystem is devised in light of the internal model principle. Finally, by using the state feedback control strategy and pole allocation method, the multivariable robust economic control decision method is implemented. The implementation with this model can accomplish the urban domestic water supply control goal, with the robustness for the variation of parameters. The methodology presented in this study may be applied to the water management system in other parts of the world, provided all data used in this study are available. The robust control decision method in this paper is also applicable to deal with tracking control problems as well as stabilization control problems of other general dynamic uncertain systems.
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Directory of Open Access Journals (Sweden)
J. Humberto Pérez-Cruz
2014-01-01
Full Text Available The trajectory tracking for a class of uncertain nonlinear systems in which the number of possible states is equal to the number of inputs and each input is preceded by an unknown symmetric deadzone is considered. The unknown dynamics is identified by means of a continuous time recurrent neural network in which the control singularity is conveniently avoided by guaranteeing the invertibility of the coupling matrix. Given this neural network-based mathematical model of the uncertain system, a singularity-free feedback linearization control law is developed in order to compel the system state to follow a reference trajectory. By means of Lyapunov-like analysis, the exponential convergence of the tracking error to a bounded zone can be proven. Likewise, the boundedness of all closed-loop signals can be guaranteed.
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A. Mirzazadeh
2011-01-01
The inventory models, generally, are derived with considering two methods: (1) minimizing the average annual cost or (2) minimizing the discounted cost. This paper compares the optimal ordering policies determined by these methods under uncertain inflationary situations. The inventory and shortages behavior have been analyzed with using the differential equations. The numerical examples are used to illustrate the theoretical results. A detailed analysis on the models parameters has been perfo...
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Step Complexity Measure for Emergency Operating Procedures - Determining Weighting Factors
International Nuclear Information System (INIS)
Park, Jinkyun; Jung, Wondea; Kim, Jaewhan; Ha, Jaejoo
2003-01-01
In complex systems, such as nuclear power plants (NPPs) or airplane control systems, human error has been regarded as the primary cause of many events. Therefore, to ensure system safety, extensive effort has been made to identify the significant factors that can cause human error. According to related studies, written manuals or operating procedures are revealed as one of the important factors, and the understandability is pointed out as one of the major reasons for procedure-related human errors.Many qualitative checklists have been suggested to evaluate emergency operating procedures (EOPs) of NPPs so as to minimize procedure-related human errors. However, since qualitative evaluations using checklists have some drawbacks, a quantitative measure that can quantify the complexity of EOPs is indispensable.From this necessity, Park et al. suggested the step complexity (SC) measure to quantify the complexity of procedural steps included in EOPs. To verify the appropriateness of the SC measure, averaged step performance time data obtained from emergency training records of the loss-of-coolant accident (LOCA) and the excess steam demand event were compared with estimated SC scores. However, although averaged step performance time data and estimated SC scores show meaningful correlation, some important issues such as determining proper weighting factors have to be clarified to ensure the appropriateness of the SC measure. These were not properly dealt with due to a lack of backup data.In this paper, to resolve one of the important issues, emergency training records are additionally collected and analyzed in order to determine proper weighting factors. The total number of collected records is 66, and the training scenarios cover five emergency conditions including the LOCA, the steam generator tube rupture, the loss of all feedwater, the loss of off-site power, and the station blackout. From these records, average step performance time data are retrieved, and new
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Valuing Interest Rate Swap Contracts in Uncertain Financial Market
Directory of Open Access Journals (Sweden)
Chen Xiao
2016-11-01
Full Text Available Swap is a financial contract between two counterparties who agree to exchange one cash flow stream for another, according to some predetermined rules. When the cash flows are fixed rate interest and floating rate interest, the swap is called an interest rate swap. This paper investigates two valuation models of the interest rate swap contracts in the uncertain financial market. The new models are based on belief degrees, and require relatively less historical data compared to the traditional probability models. The first valuation model is designed for a mean-reversion term structure, while the second is designed for a term structure with hump effect. Explicit solutions are developed by using the Yao–Chen formula. Moreover, a numerical method is designed to calculate the value of the interest rate swap alternatively. Finally, two examples are given to show their applications and comparisons.
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Probabilistic confidence for decisions based on uncertain reliability estimates
Reid, Stuart G.
2013-05-01
Reliability assessments are commonly carried out to provide a rational basis for risk-informed decisions concerning the design or maintenance of engineering systems and structures. However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities. For uncertain probabilities of failure, a measure of 'probabilistic confidence' has been proposed to reflect the concern that uncertainty about the true probability of failure could result in a system or structure that is unsafe and could subsequently fail. The paper describes how the concept of probabilistic confidence can be applied to evaluate and appropriately limit the probabilities of failure attributable to particular uncertainties such as design errors that may critically affect the dependability of risk-acceptance decisions. This approach is illustrated with regard to the dependability of structural design processes based on prototype testing with uncertainties attributable to sampling variability.
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Towards a Framework for Self-Adaptive Reliable Network Services in Highly-Uncertain Environments
DEFF Research Database (Denmark)
Grønbæk, Lars Jesper; Schwefel, Hans-Peter; Ceccarelli, Andrea
2010-01-01
In future inhomogeneous, pervasive and highly dynamic networks, end-nodes may often only rely on unreliable and uncertain observations to diagnose hidden network states and decide upon possible remediation actions. Inherent challenges exists to identify good and timely decision strategies to impr...... execution (and monitoring) of remediation actions. We detail the motivations to the ODDR design, then we present its architecture, and finally we describe our current activities towards the realization and assessment of the framework services and the main results currently achieved....
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Chen, Yun; Yang, Hui
2013-01-01
Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.
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Quantifying drug-protein binding in vivo
International Nuclear Information System (INIS)
Buchholz, B; Bench, G; Keating III, G; Palmblad, M; Vogel, J; Grant, P G; Hillegonds, D
2004-01-01
Accelerator mass spectrometry (AMS) provides precise quantitation of isotope labeled compounds that are bound to biological macromolecules such as DNA or proteins. The sensitivity is high enough to allow for sub-pharmacological (''micro-'') dosing to determine macromolecular targets without inducing toxicities or altering the system under study, whether it is healthy or diseased. We demonstrated an application of AMS in quantifying the physiologic effects of one dosed chemical compound upon the binding level of another compound in vivo at sub-toxic doses [4].We are using tissues left from this study to develop protocols for quantifying specific binding to isolated and identified proteins. We also developed a new technique to quantify nanogram to milligram amounts of isolated protein at precisions that are comparable to those for quantifying the bound compound by AMS
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Engineering risk assessment for emergency disposal projects of sudden water pollution incidents.
Shi, Bin; Jiang, Jiping; Liu, Rentao; Khan, Afed Ullah; Wang, Peng
2017-06-01
Without an engineering risk assessment for emergency disposal in response to sudden water pollution incidents, responders are prone to be challenged during emergency decision making. To address this gap, the concept and framework of emergency disposal engineering risks are reported in this paper. The proposed risk index system covers three stages consistent with the progress of an emergency disposal project. Fuzzy fault tree analysis (FFTA), a logical and diagrammatic method, was developed to evaluate the potential failure during the process of emergency disposal. The probability of basic events and their combination, which caused the failure of an emergency disposal project, were calculated based on the case of an emergency disposal project of an aniline pollution incident in the Zhuozhang River, Changzhi, China, in 2014. The critical events that can cause the occurrence of a top event (TE) were identified according to their contribution. Finally, advices on how to take measures using limited resources to prevent the failure of a TE are given according to the quantified results of risk magnitude. The proposed approach could be a potential useful safeguard for the implementation of an emergency disposal project during the process of emergency response.
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Quantifier Scope in Categorical Compositional Distributional Semantics
Directory of Open Access Journals (Sweden)
Mehrnoosh Sadrzadeh
2016-08-01
Full Text Available In previous work with J. Hedges, we formalised a generalised quantifiers theory of natural language in categorical compositional distributional semantics with the help of bialgebras. In this paper, we show how quantifier scope ambiguity can be represented in that setting and how this representation can be generalised to branching quantifiers.
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Adaptive Observer-Based Fault-Tolerant Control Design for Uncertain Systems
Directory of Open Access Journals (Sweden)
Huaming Qian
2015-01-01
Full Text Available This study focuses on the design of the robust fault-tolerant control (FTC system based on adaptive observer for uncertain linear time invariant (LTI systems. In order to improve robustness, rapidity, and accuracy of traditional fault estimation algorithm, an adaptive fault estimation algorithm (AFEA using an augmented observer is presented. By utilizing a new fault estimator model, an improved AFEA based on linear matrix inequality (LMI technique is proposed to increase the performance. Furthermore, an observer-based state feedback fault-tolerant control strategy is designed, which guarantees the stability and performance of the faulty system. Moreover, the adaptive observer and the fault-tolerant controller are designed separately, whose performance can be considered, respectively. Finally, simulation results of an aircraft application are presented to illustrate the effectiveness of the proposed design methods.
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Ogle, K.; Fell, M.; Barber, J. J.
2016-12-01
Empirical, field studies of plant functional traits have revealed important trade-offs among pairs or triplets of traits, such as the leaf (LES) and wood (WES) economics spectra. Trade-offs include correlations between leaf longevity (LL) vs specific leaf area (SLA), LL vs mass-specific leaf respiration rate (RmL), SLA vs RmL, and resistance to breakage vs wood density. Ordination analyses (e.g., PCA) show groupings of traits that tend to align with different life-history strategies or taxonomic groups. It is unclear, however, what underlies such trade-offs and emergent spectra. Do they arise from inherent physiological constraints on growth, or are they more reflective of environmental filtering? The relative importance of these mechanisms has implications for predicting biogeochemical cycling, which is influenced by trait distributions of the plant community. We address this question using an individual-based model of tree growth (ACGCA) to quantify the theoretical trait space of trees that emerges from physiological constraints. ACGCA's inputs include 32 physiological, anatomical, and allometric traits, many of which are related to the LES and WES. We fit ACGCA to 1.6 million USFS FIA observations of tree diameters and heights to obtain vectors of trait values that produce realistic growth, and we explored the structure of this trait space. No notable correlations emerged among the 496 trait pairs, but stepwise regressions revealed complicated multi-variate structure: e.g., relationships between pairs of traits (e.g., RmL and SLA) are governed by other traits (e.g., LL, radiation-use efficiency [RUE]). We also simulated growth under various canopy gap scenarios that impose varying degrees of environmental filtering to explore the multi-dimensional trait space (hypervolume) of trees that died vs survived. The centroid and volume of the hypervolumes differed among dead and live trees, especially under gap conditions leading to low mortality. Traits most predictive
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A guide for functional analysis of BRCA1 variants of uncertain significance
DEFF Research Database (Denmark)
Millot, Gaël A; Carvalho, Marcelo A; Caputo, Sandrine M
2012-01-01
of these variants, the effect on protein function is unknown making it difficult to infer the consequences on risks of breast and ovarian cancers. Thus, many individuals undergoing genetic testing for BRCA1 mutations receive test results reporting a variant of uncertain clinical significance (VUS), leading...... to issues in risk assessment, counseling, and preventive care. Here, we describe functional assays for BRCA1 to directly or indirectly assess the impact of a variant on protein conformation or function and how these results can be used to complement genetic data to classify a VUS as to its clinical...
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Auckland regional emergency medicine trainee mentoring uptake survey.
Nicholls, Gordon Michael Mike; Lawrey, Emma; Jones, Peter
2017-10-01
The primary objective of this study is to quantify how many Auckland region emergency medicine (EM) trainees would like a formal mentoring programme. The secondary objectives were to quantify how many Auckland region EM trainees would like to participate in a formal mentoring programme; to determine trainees' current understanding of mentoring; how trainees prefer mentors to be allocated; why trainees may want a mentor; what mentees perceive would be good qualities in a mentor; and trainees' prior experience with mentoring. Online survey of EM trainees in the Auckland region in June 2015. Of 61 potential respondents, 40 (65.6%) respondents replied to the survey. Of the 40, 38 (95%; 95% confidence interval (CI) 82.6-99.5) respondents indicated they would like some form of mentoring system, and of the 38, 25 (65.8%; 95% CI 49.8-78.9) preferred this to be formal. Of the 38, 19 (50%; 95% CI 34.9-65.2) currently wanted assistance obtaining a mentor. Of the 40, 30 (75%; 95% CI 59.6-86.0) are not currently in any form of mentoring relationship. Respondents believed that mentors would be most beneficial in critical incidents, career development and with work/life balance. The attributes participants considered most important in a mentor were respecting confidentiality, being honest and the ability to provide constructive feedback. Many EM trainees in Auckland want a formal mentoring system and would like a mentor. Appropriate mentor-mentee matching through a formalised voluntary system, with adequate mentor training, may enable the Auckland region to develop a suitable mentoring programme for EM trainees. © 2017 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.
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A Framework for Modeling Emerging Diseases to Inform Management.
Russell, Robin E; Katz, Rachel A; Richgels, Katherine L D; Walsh, Daniel P; Grant, Evan H C
2017-01-01
The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.
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Transient Stability Assessment of Power Systems With Uncertain Renewable Generation: Preprint
Energy Technology Data Exchange (ETDEWEB)
Villegas Pico, Hugo Nestor [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Aliprantis, Dionysios C. [Purdue University; Lin, Xiaojun [Purdue University
2017-08-09
The transient stability of a power system depends heavily on its operational state at the moment of a fault. In systems where the penetration of renewable generation is significant, the dispatch of the conventional fleet of synchronous generators is uncertain at the time of dynamic security analysis. Hence, the assessment of transient stability requires the solution of a system of nonlinear ordinary differential equations with unknown initial conditions and inputs. To this end, we set forth a computational framework that relies on Taylor polynomials, where variables are associated with the level of renewable generation. This paper describes the details of the method and illustrates its application on a nine-bus test system.
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A robust optimization model for blood supply chain in emergency situations
Directory of Open Access Journals (Sweden)
Meysam Fereiduni
2016-09-01
Full Text Available In this paper, a multi-period model for blood supply chain in emergency situation is presented to optimize decisions related to locate blood facilities and distribute blood products after natural disasters. In disastrous situations, uncertainty is an inseparable part of humanitarian logistics and blood supply chain as well. This paper proposes a robust network to capture the uncertain nature of blood supply chain during and after disasters. This study considers donor points, blood facilities, processing and testing labs, and hospitals as the components of blood supply chain. In addition, this paper makes location and allocation decisions for multiple post disaster periods through real data. The study compares the performances of “p-robust optimization” approach and “robust optimization” approach and the results are discussed.
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Directory of Open Access Journals (Sweden)
Javad Nematian
2015-04-01
Full Text Available Vertex and p-center problems are two well-known types of the center problem. In this paper, a p-center problem with uncertain demand-weighted distance will be introduced in which the demands are considered as fuzzy random variables (FRVs and the objective of the problem is to minimize the maximum distance between a node and its nearest facility. Then, by introducing new methods, the proposed problem is converted to deterministic integer programming (IP problems where these methods will be obtained through the implementation of the possibility theory and fuzzy random chance-constrained programming (FRCCP. Finally, the proposed methods are applied for locating bicycle stations in the city of Tabriz in Iran as a real case study. The computational results of our study show that these methods can be implemented for the center problem with uncertain frameworks.
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Quantifying sound quality in loudspeaker reproduction
Beerends, John G.; van Nieuwenhuizen, Kevin; van den Broek, E.L.
2016-01-01
We present PREQUEL: Perceptual Reproduction Quality Evaluation for Loudspeakers. Instead of quantifying the loudspeaker system itself, PREQUEL quantifies the overall loudspeakers' perceived sound quality by assessing their acoustic output using a set of music signals. This approach introduces a
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Pruyt, E.; Coumou, J.
2012-01-01
Lyme disease due to infection with Lyme borreliosis poses an uncertain dynamic threat to the Dutch and their public health system. This risk was used to develop and illustrate two variants of a National Risk Assessment approaches for slumbering/latent risks. This paper explains and illustrates the
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Is Time Predictability Quantifiable?
DEFF Research Database (Denmark)
Schoeberl, Martin
2012-01-01
Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst......-case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only...... compare the worst-case execution time bounds of different architectures....
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Directory of Open Access Journals (Sweden)
Jing Zhou
2014-01-01
Full Text Available According to the characteristics of emergency repair in overhead transmission line accidents, a complexity quantification method for emergency repair scheme is proposed based on the entropy method in software engineering, which is improved by using group AHP (analytical hierarchical process method and Petri net. Firstly, information structure chart model and process control flowchart model could be built by Petri net. Then impact factors on complexity of emergency repair scheme could be quantified into corresponding entropy values, respectively. Finally, by using group AHP method, weight coefficient of each entropy value would be given before calculating the overall entropy value for the whole emergency repair scheme. By comparing group AHP weighting method with average weighting method, experiment results for the former showed a stronger correlation between quantified entropy values of complexity and the actual consumed time in repair, which indicates that this new method is more valid.
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Dynamics Model Applied to Pricing Options with Uncertain Volatility
Directory of Open Access Journals (Sweden)
Lorella Fatone
2012-01-01
model is proposed. The data used to test the calibration problem included observations of asset prices over a finite set of (known equispaced discrete time values. Statistical tests were used to estimate the statistical significance of the two parameters of the Black-Scholes model: the volatility and the drift. The effects of these estimates on the option pricing problem were investigated. In particular, the pricing of an option with uncertain volatility in the Black-Scholes framework was revisited, and a statistical significance was associated with the price intervals determined using the Black-Scholes-Barenblatt equations. Numerical experiments involving synthetic and real data were presented. The real data considered were the daily closing values of the S&P500 index and the associated European call and put option prices in the year 2005. The method proposed here for calibrating the Black-Scholes dynamics model could be extended to other science and engineering models that may be expressed in terms of stochastic dynamical systems.
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Hypercube algorithms suitable for image understanding in uncertain environments
International Nuclear Information System (INIS)
Huntsberger, T.L.; Sengupta, A.
1988-01-01
Computer vision in a dynamic environment needs to be fast and able to tolerate incomplete or uncertain intermediate results. An appropriately chose representation coupled with a parallel architecture addresses both concerns. The wide range of numerical and symbolic processing needed for robust computer vision can only be achieved through a blend of SIMD and MIMD processing techniques. The 1024 element hypercube architecture has these capabilities, and was chosen as the test-bed hardware for development of highly parallel computer vision algorithms. This paper presents and analyzes parallel algorithms for color image segmentation and edge detection. These algorithms are part of a recently developed computer vision system which uses multiple valued logic to represent uncertainty in the imaging process and in intermediate results. Algorithms for the extraction of three dimensional properties of objects using dynamic scene analysis techniques within the same framework are examined. Results from experimental studies using a 1024 element hypercube implementation of the algorithm as applied to a series of natural scenes are reported
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Developing a crevice chemistry control target from uncertain data
International Nuclear Information System (INIS)
Millett, P.J.
1996-01-01
It has been generally accepted that the corrosion of steam generator tubing could be reduced if the local pH in regions where impurities concentrate could be controlled. The practice of molar ratio control is based on this assumption. Direct measurement of the crevice chemistry is not possible at this time. Deterministic models based on bulk water conditions are quite uncertain, due to both the variability of crevices in the steam generator and the level of impurities in the bulk water which are often below or at the level of detection. The current methodology for assessing the crevice chemistry is to monitor the hideout return chemistry when the plant shuts down. This approach also has its shortcomings, but may provide sufficient data to evaluate whether the crevice pH is in a desirable range. In this paper, an approach for establishing a target crevice chemistry based on the plant data which is believed to be the most certain or reliable is presented
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Impact of uncertain reference-frame motions in plate kinematic reconstructions
DEFF Research Database (Denmark)
Iaffaldano, Giampiero; Stein, Seth
2017-01-01
Geoscientists infer past plate motions, which serve as fundamental constraints for a range of studies, from observations of magnetic isochrons as well as hotspots tracks on the ocean floor and, for stages older than the Cretaceous, from paleomagnetic data. These observations effectively represent...... time-integrals of past plate motions but, because they are made at present, yield plate kinematics naturally tied to a present-day reference-frame, which may be another plate or a hotspots system. These kinematics are therefore different than those occurred at the time when the rocks acquired...... – in a temporal sense – and prone to noise. This limitation is commonly perceived to hamper the correction of plate kinematic reconstructions for RFAMs, but the extent to which this may be the case has not been explored. Here we assess the impact of uncertain RFAMs on kinematic reconstructions using synthetic...
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Modern medicine and the "uncertain body": from corporeality to hyperreality?
Williams, S J
1997-10-01
This paper (re)considers the role of medical technology at three interrelated levels: first, the extent to which medical technology renders our bodies increasingly "uncertain" at the turn of the century; second, the analytical purchase which the notion of the (medical) cyborg provides regarding contemporary forms of human embodiment; and finally, at a broader level, the issues this raises in relation to a (late) modernist or postmodernist reading of contemporary medical practice. Key themes here include the plastic body, the bionic body, communal/interchangeable bodies, (genetically) engineered/ chosen bodies, and virtual bodies. The paper concludes with a critical appraisal of these themes and issues, arguing for a late modernist position on medical technology as both a positive and negative rationalising force, and a "life political agenda" in which the "all-too-human" quality of human nature is seen as inviolable.
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Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad
2013-01-01
, we simplify state prediction for the MPC. Consequently, the control problem of the nonlinear system is simplified into a quadratic programming. We consider uncertainty in the wind propagation time, which is the traveling time of wind from the LIDAR measurement point to the rotor. An algorithm based......The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined...... on wind speed estimation and measurements from the LIDAR is devised to find an estimate of the delay and compensate for it before it is used in the controller. Comparisons between the MPC with error compensation, the MPC without error compensation and an MPC with re-linearization at each sample point...
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Decisions with Uncertain Consequences-A Total Ordering on Loss-Distributions.
Rass, Stefan; König, Sandra; Schauer, Stefan
2016-01-01
Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action can be modeled by a random variable, then the decision problem boils down to comparing different effects (random variables) by comparing their distribution functions. Although the full space of probability distributions cannot be ordered, a properly restricted subset of distributions can be totally ordered in a practically meaningful way. We call these loss-distributions, since they provide a substitute for the concept of loss-functions in decision theory. This article introduces the theory behind the necessary restrictions and the hereby constructible total ordering on random loss variables, which enables decisions under uncertainty of consequences. Using data obtained from simulations, we demonstrate the practical applicability of our approach.
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AN UNCERTAIN FEDERALISM: THE STATES AND THE AFFORDABLE CARE ACT.
Plein, L Christopher
2014-01-01
This article provides an initial assessment of the Affordable Care Act's recent implementation experience in the states. Drawing on state-level and regional analyses that have been coordinated by the ACA Implementation Network--a cooperative effort involving researchers in 35 states--this article highlights the uncertain policy environment associated with the politics and complexities of the ACA. Understanding the ACA implementation experience requires an appreciation for political context, but must also take into account underlying demographic, market, and state administrative capacity issues in the states. There are indications that the ACA implementation experience is moving from a highly charged partisan nature to a more accommodating posture long associated with intergovernmental relations between the federal and state government in health and human services administration. In short, the key questions going forward will turn on how, not whether, the ACA is implemented.
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A Modeling and Experiment Framework for the Emergency Management in AHC Transmission
Directory of Open Access Journals (Sweden)
Bin Chen
2014-01-01
Full Text Available Emergency management is crucial to finding effective ways to minimize or even eliminate the damage of emergent events, but there still exists no quantified method to study the events by computation. Statistical algorithms, such as susceptible-infected-recovered (SIR models on epidemic transmission, ignore many details, thus always influencing the spread of emergent events. In this paper, we first propose an agent-based modeling and experiment framework to model the real world with the emergent events. The model of the real world is called artificial society, which is composed of agent model, agent activity model, and environment model, and it employs finite state automata (FSA as its modeling paradigm. An artificial campus, on which a series of experiments are done to analyze the key factors of the acute hemorrhagic conjunctivitis (AHC transmission, is then constructed to illustrate how our method works on the emergency management. Intervention measures and optional configurations (such as the isolation period of them for the emergency management are also given through the evaluations in these experiments.
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Similarity estimators for irregular and age uncertain time series
Rehfeld, K.; Kurths, J.
2013-09-01
Paleoclimate time series are often irregularly sampled and age uncertain, which is an important technical challenge to overcome for successful reconstruction of past climate variability and dynamics. Visual comparison and interpolation-based linear correlation approaches have been used to infer dependencies from such proxy time series. While the first is subjective, not measurable and not suitable for the comparison of many datasets at a time, the latter introduces interpolation bias, and both face difficulties if the underlying dependencies are nonlinear. In this paper we investigate similarity estimators that could be suitable for the quantitative investigation of dependencies in irregular and age uncertain time series. We compare the Gaussian-kernel based cross correlation (gXCF, Rehfeld et al., 2011) and mutual information (gMI, Rehfeld et al., 2013) against their interpolation-based counterparts and the new event synchronization function (ESF). We test the efficiency of the methods in estimating coupling strength and coupling lag numerically, using ensembles of synthetic stalagmites with short, autocorrelated, linear and nonlinearly coupled proxy time series, and in the application to real stalagmite time series. In the linear test case coupling strength increases are identified consistently for all estimators, while in the nonlinear test case the correlation-based approaches fail. The lag at which the time series are coupled is identified correctly as the maximum of the similarity functions in around 60-55% (in the linear case) to 53-42% (for the nonlinear processes) of the cases when the dating of the synthetic stalagmite is perfectly precise. If the age uncertainty increases beyond 5% of the time series length, however, the true coupling lag is not identified more often than the others for which the similarity function was estimated. Age uncertainty contributes up to half of the uncertainty in the similarity estimation process. Time series irregularity
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Similarity estimators for irregular and age-uncertain time series
Rehfeld, K.; Kurths, J.
2014-01-01
Paleoclimate time series are often irregularly sampled and age uncertain, which is an important technical challenge to overcome for successful reconstruction of past climate variability and dynamics. Visual comparison and interpolation-based linear correlation approaches have been used to infer dependencies from such proxy time series. While the first is subjective, not measurable and not suitable for the comparison of many data sets at a time, the latter introduces interpolation bias, and both face difficulties if the underlying dependencies are nonlinear. In this paper we investigate similarity estimators that could be suitable for the quantitative investigation of dependencies in irregular and age-uncertain time series. We compare the Gaussian-kernel-based cross-correlation (gXCF, Rehfeld et al., 2011) and mutual information (gMI, Rehfeld et al., 2013) against their interpolation-based counterparts and the new event synchronization function (ESF). We test the efficiency of the methods in estimating coupling strength and coupling lag numerically, using ensembles of synthetic stalagmites with short, autocorrelated, linear and nonlinearly coupled proxy time series, and in the application to real stalagmite time series. In the linear test case, coupling strength increases are identified consistently for all estimators, while in the nonlinear test case the correlation-based approaches fail. The lag at which the time series are coupled is identified correctly as the maximum of the similarity functions in around 60-55% (in the linear case) to 53-42% (for the nonlinear processes) of the cases when the dating of the synthetic stalagmite is perfectly precise. If the age uncertainty increases beyond 5% of the time series length, however, the true coupling lag is not identified more often than the others for which the similarity function was estimated. Age uncertainty contributes up to half of the uncertainty in the similarity estimation process. Time series irregularity
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Dermal Squamomelanocytic Tumor: Neoplasm of Uncertain Biological Potential
Directory of Open Access Journals (Sweden)
Mirsad Dorić
2008-05-01
Full Text Available We report a case of exceedingly rare cutaneous neoplasm with histological features of malignancy and uncertain biological potential. The nodular, darkly pigmented facial tumor with central exulceration, size 12x10x7 mm, of the skin 61-year-old man preauricular left was completely exised.Histologically tumor consists of atypical squamous cells, which express signs of moderate to significant pleomorphism, mitotically active, with foci forming of parakeratotic horn cysts (“pearls”. Characteristically tumor also consists of large number of atypical melanocytes with multifocal pattern, inserted between atypical squamous cells, and which contain large amount of dark brown pigment melanin. Immunohistochemically, squamous cells stain positively with keratin (CK116, melanocytes were stained with S -100 protein, HMB 45, and vimentin, but failed to stain with CK 116.To our knowledge this is the sixth reported case in world literature. The follow-up time of four years no evidence of recurrence or metastasis, similar all reported cases, but it is too short period in estimation to guarantee a benign course. However, it appears that this group of neoplasm may have different prognosis from pure squamous carcinoma or malignant melanoma.
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Bayesian inference on genetic merit under uncertain paternity
Directory of Open Access Journals (Sweden)
Tempelman Robert J
2003-09-01
Full Text Available Abstract A hierarchical animal model was developed for inference on genetic merit of livestock with uncertain paternity. Fully conditional posterior distributions for fixed and genetic effects, variance components, sire assignments and their probabilities are derived to facilitate a Bayesian inference strategy using MCMC methods. We compared this model to a model based on the Henderson average numerator relationship (ANRM in a simulation study with 10 replicated datasets generated for each of two traits. Trait 1 had a medium heritability (h2 for each of direct and maternal genetic effects whereas Trait 2 had a high h2 attributable only to direct effects. The average posterior probabilities inferred on the true sire were between 1 and 10% larger than the corresponding priors (the inverse of the number of candidate sires in a mating pasture for Trait 1 and between 4 and 13% larger than the corresponding priors for Trait 2. The predicted additive and maternal genetic effects were very similar using both models; however, model choice criteria (Pseudo Bayes Factor and Deviance Information Criterion decisively favored the proposed hierarchical model over the ANRM model.
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Tinker, Sarah C; Moe, Christine L; Klein, Mitchel; Flanders, W Dana; Uber, Jim; Amirtharajah, Appiah; Singer, Philip; Tolbert, Paige E
2010-01-01
The extent to which drinking water turbidity measurements indicate the risk of gastrointestinal illness is not well understood. Despite major advances in drinking water treatment and delivery, infectious disease can still be transmitted through drinking water in the United States, and it is important to have reliable indicators of microbial water quality to inform public health decisions. The objective of our study was to assess the relationship between gastrointestinal illness, quantified through emergency department visits, and drinking water quality, quantified as raw water and filtered water turbidity measured at the treatment plant. We examined the relationship between turbidity levels of raw and filtered surface water measured at eight major drinking water treatment plants in the metropolitan area of Atlanta, Georgia, and over 240,000 emergency department visits for gastrointestinal illness during 1993-2004 among the population served by these plants. We fit Poisson time-series statistical regression models that included turbidity in a 21-day distributed lag and that controlled for meteorological factors and long-term time trends. For filtered water turbidity, the results were consistent with no association with emergency department visits for gastrointestinal illness. We observed a modest association between raw water turbidity and emergency department visits for gastrointestinal illness. Our results suggest that source water quality may contribute modestly to endemic gastrointestinal illness in the study area. The association between turbidity and emergency department visits for gastrointestinal illness was only observed when raw water turbidity was considered; filtered water turbidity may not serve as a reliable indicator of modest pathogen risk at all treatment plants.
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Quantifying Selective Pressures Driving Bacterial Evolution Using Lineage Analysis
Lambert, Guillaume; Kussell, Edo
2015-01-01
Organisms use a variety of strategies to adapt to their environments and maximize long-term growth potential, but quantitative characterization of the benefits conferred by the use of such strategies, as well as their impact on the whole population's rate of growth, remains challenging. Here, we use a path-integral framework that describes how selection acts on lineages—i.e., the life histories of individuals and their ancestors—to demonstrate that lineage-based measurements can be used to quantify the selective pressures acting on a population. We apply this analysis to Escherichia coli bacteria exposed to cyclical treatments of carbenicillin, an antibiotic that interferes with cell-wall synthesis and affects cells in an age-dependent manner. While the extensive characterization of the life history of thousands of cells is necessary to accurately extract the age-dependent selective pressures caused by carbenicillin, the same measurement can be recapitulated using lineage-based statistics of a single surviving cell. Population-wide evolutionary pressures can be extracted from the properties of the surviving lineages within a population, providing an alternative and efficient procedure to quantify the evolutionary forces acting on a population. Importantly, this approach is not limited to age-dependent selection, and the framework can be generalized to detect signatures of other trait-specific selection using lineage-based measurements. Our results establish a powerful way to study the evolutionary dynamics of life under selection and may be broadly useful in elucidating selective pressures driving the emergence of antibiotic resistance and the evolution of survival strategies in biological systems.
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Danaher, J.; Nyholm, S.R.; Earp, B.
2018-01-01
The growth of self-tracking and personal surveillance has given rise to the Quantified Self movement. Members of this movement seek to enhance their personal well-being, productivity, and self-actualization through the tracking and gamification of personal data. The technologies that make this
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Quantifying the uncertainty in heritability.
Furlotte, Nicholas A; Heckerman, David; Lippert, Christoph
2014-05-01
The use of mixed models to determine narrow-sense heritability and related quantities such as SNP heritability has received much recent attention. Less attention has been paid to the inherent variability in these estimates. One approach for quantifying variability in estimates of heritability is a frequentist approach, in which heritability is estimated using maximum likelihood and its variance is quantified through an asymptotic normal approximation. An alternative approach is to quantify the uncertainty in heritability through its Bayesian posterior distribution. In this paper, we develop the latter approach, make it computationally efficient and compare it to the frequentist approach. We show theoretically that, for a sufficiently large sample size and intermediate values of heritability, the two approaches provide similar results. Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large.
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Catalytic wet peroxide oxidation in the removal of emerging micropollutants
Gomes, Helder; Ribeiro, Rui; García, Juan; Frontistis, Zacharias; Mantzavinos, Dionissios; Silva, Adrián; Faria, Joaquim
2016-01-01
Several contaminants of emerging concern (CECs), with negative impact on water security, have been recently identified and quantified in different water sources [1]. Among them, antibiotics are receiving particular attention due to the possible development of antibiotic resistant bacteria and/or resistance genes (ARB&ARG). Conventional urban wastewater treatment plants are unable to cope with most of these compounds, thus allowing their systematic propagation throughout the urban water cycle....
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Abel, Gary A; Mendonca, Silvia C; McPhail, Sean; Zhou, Yin; Elliss-Brookes, Lucy; Lyratzopoulos, Georgios
2017-06-01
Emergency diagnosis of cancer is common and aetiologically complex. The proportion of emergency presenters who have consulted previously with relevant symptoms is uncertain. To examine how many patients with cancer, who were diagnosed as emergencies, have had previous primary care consultations with relevant symptoms; and among those, to examine how many had multiple consultations. Secondary analysis of patient survey data from the 2010 English Cancer Patient Experience Survey (CPES), previously linked to population-based data on diagnostic route. For emergency presenters with 18 different cancers, associations were examined for two outcomes (prior GP consultation status; and 'three or more consultations' among prior consultees) using logistic regression. Among 4647 emergency presenters, 1349 (29%) reported no prior consultations, being more common in males (32% versus 25% in females, P <0.001), older (44% in ≥85 versus 30% in 65-74-year-olds, P <0.001), and the most deprived (35% versus 25% least deprived, P = 0.001) patients; and highest/lowest for patients with brain cancer (46%) and mesothelioma (13%), respectively ( P <0.001 for overall variation by cancer site). Among 3298 emergency presenters with prior consultations, 1356 (41%) had three or more consultations, which were more likely in females ( P <0.001), younger ( P <0.001), and non-white patients ( P = 0.017) and those with multiple myeloma, and least likely for patients with leukaemia ( P <0.001). Contrary to suggestions that emergency presentations represent missed diagnoses, about one-third of emergency presenters (particularly those in older and more deprived groups) have no prior GP consultations. Furthermore, only about one-third report multiple (three or more) consultations, which are more likely in 'harder-to-suspect' groups. © British Journal of General Practice 2017.
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International Nuclear Information System (INIS)
Cinzano, P.; Falchi, F.
2014-01-01
In this paper we review new available indicators useful to quantify and monitor light pollution, defined as the alteration of the natural quantity of light in the night environment due to introduction of manmade light. With the introduction of recent radiative transfer methods for the computation of light pollution propagation, several new indicators become available. These indicators represent a primary step in light pollution quantification, beyond the bare evaluation of the night sky brightness, which is an observational effect integrated along the line of sight and thus lacking the three-dimensional information. - Highlights: • We review new available indicators useful to quantify and monitor light pollution. • These indicators are a primary step in light pollution quantification. • These indicators allow to improve light pollution mapping from a 2D to a 3D grid. • These indicators allow carrying out a tomography of light pollution. • We show an application of this technique to an Italian region
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Recent emergency planning trends in Canada
International Nuclear Information System (INIS)
Howieson, J.Q.; Ali, F.B.
1988-01-01
Two significant reviews have recently been completed which have affected the approach to emergency planning in Canada. The two reviews have occurred in the province of Ontario where 21 of Canada's 23 reactors are located. Both reviews (one dealing with safety in general, and the other specifically with emergency planning) were performed for the Government of Ontario and were primarily motivated by the severe consequences of the accident at Chernobyl. It was determined that two tiers of emergency planning are needed: (i) the first tier (termed the Maximum Planning Accident or MPA) provides for detailed planning for accidents which can be quantitatively determined to be as low as once in 10 5 station-years. (about once in 10 6 reactor-years for Ontario Hydro's multi-unit sites). For this tier, planning assures public exposure to radioactive doses is kept less than the Protective Action Levels. (ii) the second tier (termed the Worst Credible Radiation Emission or WCRE) provides for planning for accidents which are lower in frequency or whose frequency cannot be quantified (e.g., gross human error or hostile action). For this tier, planning protects against the onset of early morbidity (sickness) and the onset of early mortality (death) in a member of the public
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Influence of climate factors on emergency visits for childhood asthma attack.
Hashimoto, Mitsuo; Fukuda, Taiki; Shimizu, Tetsuya; Watanabe, Shou; Watanuki, Satoshi; Eto, Yoshikatsu; Urashima, Mitsuyoshi
2004-02-01
Asthma attack shows strong seasonality. The purpose of the present study was to quantify the contribution of climate variables and other seasonal factors on the incidence of emergency visits for childhood asthma in Tokyo, Japan. The number of children who visited emergency rooms at Jikei university hospitals in Tokyo during 1998-2002 (5559 visits) was retrieved retrospectively from files from the Department of Pediatrics, and compared with 45 climate parameters from the Meteorological Agency using multiple regression models with a stepwise backward elimination approach. The number of visits (3.7 +/- 3.1) per night increased significantly when climate conditions showed a rapid decrease from higher barometric pressure, from higher air temperature and from higher humidity, as well as lower wind speed. The best-fit model demonstrated that a 22% variation in the number of visits was explained by a linear relationship with 12 climate variables, which increased to 36% after adjusting for calendar month and day of the week. Moreover, when the number of asthma visits was cut off at nine per night, the area under the receiver operator characteristics curve was 0.91 (95% CI: 0.89-0.94) in the multiple logistic regression model using the same variables. These results suggest that these models might quantify contributions of specific climate conditions and other seasonal factors on the number of emergency visits per night for childhood asthma attack in Tokyo, Japan.
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International Nuclear Information System (INIS)
Park, Ju H.
2007-01-01
The paper addresses control problem for the modified projective synchronization of the Genesio-Tesi chaotic systems with three uncertain parameters. An adaptive control law is derived to make the states of two identical Genesio-Tesi systems asymptotically synchronized up to specific ratios. The stability analysis in the paper is proved using a well-known Lyapunov stability theory. A numerical simulation is presented to show the effectiveness of the proposed chaos synchronization scheme
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Garner, G. G.; Keller, K.
2017-12-01
Sea-level rise poses considerable risks to coastal communities, ecosystems, and infrastructure. Decision makers are faced with deeply uncertain sea-level projections when designing a strategy for coastal adaptation. The traditional methods have provided tremendous insight into this decision problem, but are often silent on tradeoffs as well as the effects of tail-area events and of potential future learning. Here we reformulate a simple sea-level rise adaptation model to address these concerns. We show that Direct Policy Search yields improved solution quality, with respect to Pareto-dominance in the objectives, over the traditional approach under uncertain sea-level rise projections and storm surge. Additionally, the new formulation produces high quality solutions with less computational demands than the traditional approach. Our results illustrate the utility of multi-objective adaptive formulations for the example of coastal adaptation, the value of information provided by observations, and point to wider-ranging application in climate change adaptation decision problems.
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Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun
2017-07-01
In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.
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Decisions with Uncertain Consequences-A Total Ordering on Loss-Distributions.
Directory of Open Access Journals (Sweden)
Stefan Rass
Full Text Available Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action can be modeled by a random variable, then the decision problem boils down to comparing different effects (random variables by comparing their distribution functions. Although the full space of probability distributions cannot be ordered, a properly restricted subset of distributions can be totally ordered in a practically meaningful way. We call these loss-distributions, since they provide a substitute for the concept of loss-functions in decision theory. This article introduces the theory behind the necessary restrictions and the hereby constructible total ordering on random loss variables, which enables decisions under uncertainty of consequences. Using data obtained from simulations, we demonstrate the practical applicability of our approach.
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Overview of Emerging Contaminants and Associated Human Health Effects
Lei, Meng; Zhang, Lun; Lei, Jianjun; Zong, Liang; Li, Jiahui; Wu, Zheng; Wang, Zheng
2015-01-01
In recent decades, because of significant progress in the analysis and detection of trace pollutants, emerging contaminants have been discovered and quantified in living beings and diverse environmental substances; however, the adverse effects of environmental exposure on the general population are largely unknown. This review summarizes the conclusions of the comprehensive epidemic literature and representative case reports relevant to emerging contaminants and the human body to address concerns about potential harmful health effects in the general population. The most prevalent emerging contaminants include perfluorinated compounds, water disinfection byproducts, gasoline additives, manufactured nanomaterials, human and veterinary pharmaceuticals, and UV-filters. Rare but statistically meaningful connections have been reported for a number of contaminants and cancer and reproductive risks. Because of contradictions in the outcomes of some investigations and the limited number of articles, no significant conclusions regarding the relationship between adverse effects on humans and extents of exposure can be drawn at this time. Here, we report that the current evidence is not conclusive and comprehensive and suggest prospective cohort studies in the future to evaluate the associations between human health outcomes and emerging environmental contaminants. PMID:26713315
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Overview of Emerging Contaminants and Associated Human Health Effects
Directory of Open Access Journals (Sweden)
Meng Lei
2015-01-01
Full Text Available In recent decades, because of significant progress in the analysis and detection of trace pollutants, emerging contaminants have been discovered and quantified in living beings and diverse environmental substances; however, the adverse effects of environmental exposure on the general population are largely unknown. This review summarizes the conclusions of the comprehensive epidemic literature and representative case reports relevant to emerging contaminants and the human body to address concerns about potential harmful health effects in the general population. The most prevalent emerging contaminants include perfluorinated compounds, water disinfection byproducts, gasoline additives, manufactured nanomaterials, human and veterinary pharmaceuticals, and UV-filters. Rare but statistically meaningful connections have been reported for a number of contaminants and cancer and reproductive risks. Because of contradictions in the outcomes of some investigations and the limited number of articles, no significant conclusions regarding the relationship between adverse effects on humans and extents of exposure can be drawn at this time. Here, we report that the current evidence is not conclusive and comprehensive and suggest prospective cohort studies in the future to evaluate the associations between human health outcomes and emerging environmental contaminants.
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The doctor-patient relationship as a toolkit for uncertain clinical decisions.
Diamond-Brown, Lauren
2016-06-01
Medical uncertainty is a well-recognized problem in healthcare, yet how doctors make decisions in the face of uncertainty remains to be understood. This article draws on interdisciplinary literature on uncertainty and physician decision-making to examine a specific physician response to uncertainty: using the doctor-patient relationship as a toolkit. Additionally, I ask what happens to this process when the doctor-patient relationship becomes fragmented. I answer these questions by examining obstetrician-gynecologists' narratives regarding how they make decisions when faced with uncertainty in childbirth. Between 2013 and 2014, I performed 21 semi-structured interviews with obstetricians in the United States. Obstetricians were selected to maximize variation in relevant physician, hospital, and practice characteristics. I began with grounded theory and moved to analytical coding of themes in relation to relevant literature. My analysis renders it evident that some physicians use the doctor-patient relationship as a toolkit for dealing with uncertainty. I analyze how this process varies for physicians in different models of care by comparing doctors' experiences in models with continuous versus fragmented doctor-patient relationships. My key findings are that obstetricians in both models appealed to the ideal of patient-centered decision-making to cope with uncertain decisions, but in practice physicians in fragmented care faced a number of challenges to using the doctor-patient relationship as a toolkit for decision-making. These challenges led to additional uncertainties and in some cases to poor outcomes for doctors and/or patients; they also raised concerns about the reproduction of inequality. Thus organization of care delivery mitigates the efficacy of doctors' use of the doctor-patient relationship toolkit for uncertain decisions. These findings have implications for theorizing about decision-making under conditions of medical uncertainty, for understanding
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Jiang, Jiefeng; Egner, Tobias
2014-01-01
Resolving conflicting sensory and motor representations is a core function of cognitive control, but it remains uncertain to what degree control over different sources of conflict is implemented by shared (domain general) or distinct (domain specific) neural resources. Behavioral data suggest conflict–control to be domain specific, but results from neuroimaging studies have been ambivalent. Here, we employed multivoxel pattern analyses that can decode a brain region's informational content, allowing us to distinguish incidental activation overlap from actual shared information processing. We trained independent sets of “searchlight” classifiers on functional magnetic resonance imaging data to decode control processes associated with stimulus-conflict (Stroop task) and ideomotor-conflict (Simon task). Quantifying the proportion of domain-specific searchlights (capable of decoding only one type of conflict) and domain-general searchlights (capable of decoding both conflict types) in each subject, we found both domain-specific and domain-general searchlights, though the former were more common. When mapping anatomical loci of these searchlights across subjects, neural substrates of stimulus- and ideomotor-specific conflict–control were found to be anatomically consistent across subjects, whereas the substrates of domain-general conflict–control were not. Overall, these findings suggest a hybrid neural architecture of conflict–control that entails both modular (domain specific) and global (domain general) components. PMID:23402762
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Evaluating the benefits of coordinated emerging flexible resources in electricity markets
International Nuclear Information System (INIS)
Heydarian-Forushani, E.; Golshan, M.E.H.; Siano, Pierluigi
2017-01-01
Highlights: •Variable renewable energy sources create a flexibility gap in power system operation. •BESs, PEV PLs and DR are modeled as flexible options. •DR programs have remarkable impacts in terms of cost and emission reduction. •PEV PL is not a favorable flexible option by its own due to uncertain behavior of PEV owners. •Coordinated operation of PEV PLs and BESs under TOU program is the most effective generation mixture. -- Abstract: Increasing share of variable renewable energy sources (VRESs) with the aim of tackling climate changes impose several techno-economic challenges to power system operation. VRESs reduce the available flexibility by displacing existing flexible units due to their priority in dispatch and simultaneously enhance the need for additional flexibility due to their uncertain nature. In this light, the system is faced with a flexibility gap. One way to cover the created flexibility gap is the incorporation of emerging flexible resources into power systems operation. On this basis, this paper proposes a comprehensive flexible generation portfolio including bulk energy storages (BESs), plug-in electric vehicle parking lots (PEV PLs), and demand response (DR) programs. A stochastic market-based model is proposed to coordinate the interactions among these flexibility providers considering different sets of uncertainty, such as wind power generation and PEV owner’s behavior. Finally, various generation mixtures are prioritized based on the system operator’s economic, technical, and environmental desires to provide a guideline to opt the most effective generation mixture in the context of flexibility promotion.
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Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System
Directory of Open Access Journals (Sweden)
Guofeng Tong
2014-04-01
Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.
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Quantifying the Impacts of Digital Rights Management and E-Book Pricing on the E-Book Reader Market
Jin-Hyuk Kim; Tin Cheuk Leung
2013-01-01
The demand for electronic books (e-books) and the e-book readers are complementary. On the one hand, the emergence of e-book readers such as Amazon's Kindle has triggered the recent growth of the e-book market. On the other hand, several issues in the e-book market can affect the future of the e-book reader market. Considering this complementarity, this paper quantifies the impact of digital rights management (DRM) and discounted e-book pricing on the demand for e-book readers. We collect con...
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DEFF Research Database (Denmark)
Fetene, Gebeyehu Manie
The problem of peak load arises when demand fluctuates over time while the pro- duction technology is not flexible (or making it flexible is economically inefficient) and/or when a product is non-storable (or storage cost is huge). Peak load is a com- mon problem in consumption of public utilities......, on the one hand, observed cost saving benefit of postponing the time of charging to off-peak lower fee of charging and, on the other hand, the cost of delay in departure time for planned trips and uncertain cost of late charging associated with likelihood occur- rence of unanticipated trip before the car...... of electricity. The electric vehicle (EV) users choice of time of charging problem under PLP is different from that of general households using energy for house appliances since there is uncertain cost to the former as- sociated with likelihood occurrence of unanticipated trips such as visiting hospital...
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Quantifying preferences of farmers and veterinarians for national animal health programs
Borne, van den Bart H.P.; Soest, van Felix J.S.; Reist, Martin; Hogeveen, Henk
2017-01-01
Bovine udder health in Switzerland is of a relatively high level. However, antimicrobial usage (AMU) seems high in comparison to other European countries also. A new udder health and AMU improvement program could improve this situation but it is uncertain whether there is support from the field.
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Quantifying Evaporation in a Permeable Pavement System
Studies quantifying evaporation from permeable pavement systems are limited to a few laboratory studies and one field application. This research quantifies evaporation for a larger-scale field application by measuring the water balance from lined permeable pavement sections. Th...
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International Nuclear Information System (INIS)
Souza, Fernando O.; Palhares, Reinaldo M.; Ekel, Petr Ya.
2009-01-01
This paper deals with the stability analysis of delayed uncertain Cohen-Grossberg neural networks (CGNN). The proposed methodology consists in obtaining new robust stability criteria formulated as linear matrix inequalities (LMIs) via the Lyapunov-Krasovskii theory. Particularly one stability criterion is derived from the selection of a parameter-dependent Lyapunov-Krasovskii functional, which allied with the Gu's discretization technique and a simple strategy that decouples the system matrices from the functional matrices, assures a less conservative stability condition. Two computer simulations are presented to support the improved theoretical results.
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The global and domestic politics of health policy in emerging nations.
Gómez, Eduardo J; Ruger, Jennifer Prah
2015-02-01
In recent years, several emerging nations with burgeoning economies and in transition to democracy have pursued health policy innovations. As these nations have integrated into the world economy through bilateral trade and diplomacy, they have also become increasingly exposed to international pressures and norms and focused on more effective, equitable health care systems. There are several lessons learned from the case studies of Brazil, Ghana, India, China, Vietnam, and Thailand in this special issue on the global and domestic politics of health policy in emerging nations. For the countries examined, although sensitive to international preferences, domestic governments preferred to implement policy on their own and at their own pace. During the policy-making and implementation process, international and domestic actors played different roles in health policy making vis-à-vis other reform actors -- at times the state played an intermediary role. In several countries, civil society also played a central role in designing and implementing policy at all levels of government. International institutions also have a number of mechanisms and strategies in their tool box to influence a country's domestic health governance, and they use them, particularly in the context of an uncertain state or internal discordance within the state. Copyright © 2015 by Duke University Press.
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Quantifying the burden of vampire bat rabies in Peruvian livestock.
Directory of Open Access Journals (Sweden)
Julio A Benavides
2017-12-01
Full Text Available Knowledge of infectious disease burden is necessary to appropriately allocate resources for prevention and control. In Latin America, rabies is among the most important zoonoses for human health and agriculture, but the burden of disease attributed to its main reservoir, the common vampire bat (Desmodus rotundus, remains uncertain.We used questionnaires to quantify under-reporting of livestock deaths across 40 agricultural communities with differing access to health resources and epidemiological histories of vampire bat rabies (VBR in the regions of Apurimac, Ayacucho and Cusco in southern Peru. Farmers who believed VBR was absent from their communities were one third as likely to report livestock deaths from disease as those who believed VBR was present, and under-reporting increased with distance from reporting offices. Using generalized mixed-effect models that captured spatial autocorrelation in reporting, we project 4.6 (95% CI: 4.4-8.2 rabies cases per reported case and identify geographic areas with potentially greater VBR burden than indicated by official reports. Spatially-corrected models estimate 505-724 cattle deaths from VBR in our study area during 2014 (421-444 deaths/100,000 cattle, costing US$121,797-171,992. Cost benefit analysis favoured vaccinating all cattle over the current practice of partial vaccination or halting vaccination all together.Our study represents the first estimate of the burden of VBR in Latin America to incorporate data on reporting rates. We confirm the long-suspected cost of VBR to small-scale farmers and show that vaccinating livestock is a cost-effective solution to mitigate the burden of VBR. More generally, results highlight that ignoring geographic variation in access to health resources can bias estimates of disease burden and risk.
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Analyzing complex networks evolution through Information Theory quantifiers
International Nuclear Information System (INIS)
Carpi, Laura C.; Rosso, Osvaldo A.; Saco, Patricia M.; Ravetti, Martin Gomez
2011-01-01
A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.
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Understanding the value of emergency care: a framework incorporating stakeholder perspectives.
Sharp, Adam L; Cobb, Enesha M; Dresden, Scott M; Richardson, Derek K; Sabbatini, Amber K; Sauser, Kori; Kocher, Keith E
2014-09-01
In the face of escalating spending, measuring and maximizing the value of health services has become an important focus of health reform. Recent initiatives aim to incentivize high-value care through provider and hospital payment reform, but the role of the emergency department (ED) remains poorly defined. To achieve an improved understanding of the value of emergency care, we have developed a framework that incorporates the perspectives of stakeholders in the delivery of health services. A pragmatic review of the literature informed the design of this framework to standardize the definition of value in emergency care and discuss outcomes and costs from different stakeholder perspectives. The viewpoint of patient, provider, payer, health system, and society is each used to assess value for emergency medical conditions. We found that the value attributed to emergency care differs substantially by stakeholder perspective. Potential targets to improve ED value may be aimed at improving outcomes or controlling costs, depending on the acuity of the clinical condition. The value of emergency care varies by perspective, and a better understanding is achieved when specific outcomes and costs can be identified, quantified, and measured. Using this framework can help stakeholders find common ground to prioritize which costs and outcomes to target for research, quality improvement efforts, and future health policy impacting emergency care. Copyright © 2014 Elsevier Inc. All rights reserved.
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International Nuclear Information System (INIS)
Sheng Li; Yang Huizhong
2009-01-01
This paper considers the robust stability of a class of uncertain Markovian jumping Cohen-Grossberg neural networks (UMJCGNNs) with mixed time-varying delays. The parameter uncertainties are norm-bounded and the mixed time-varying delays comprise discrete and distributed time delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. An example is given to show the effectiveness of the proposed results.
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Deriving the expected utility of a predictive model when the utilities are uncertain.
Cooper, Gregory F; Visweswaran, Shyam
2005-01-01
Predictive models are often constructed from clinical databases with the goal of eventually helping make better clinical decisions. Evaluating models using decision theory is therefore natural. When constructing a model using statistical and machine learning methods, however, we are often uncertain about precisely how the model will be used. Thus, decision-independent measures of classification performance, such as the area under an ROC curve, are popular. As a complementary method of evaluation, we investigate techniques for deriving the expected utility of a model under uncertainty about the model's utilities. We demonstrate an example of the application of this approach to the evaluation of two models that diagnose coronary artery disease.
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Finite-Time H∞ Filtering for Linear Continuous Time-Varying Systems with Uncertain Observations
Directory of Open Access Journals (Sweden)
Huihong Zhao
2012-01-01
Full Text Available This paper is concerned with the finite-time H∞ filtering problem for linear continuous time-varying systems with uncertain observations and ℒ2-norm bounded noise. The design of finite-time H∞ filter is equivalent to the problem that a certain indefinite quadratic form has a minimum and the filter is such that the minimum is positive. The quadratic form is related to a Krein state-space model according to the Krein space linear estimation theory. By using the projection theory in Krein space, the finite-time H∞ filtering problem is solved. A numerical example is given to illustrate the performance of the H∞ filter.
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Robles-Medranda, Carlos; Vargas, Maria; Ospina, Jesenia; Puga-Tejada, Miguel; Valero, Manuel; Soria, Miguel; Bravo, Gladys; Robles-Jara, Carlos; Lukashok, Hannah Pitanga
2017-08-16
To evaluate the clinical impact of confocal laser endomicroscopy (CLE) in the diagnosis and management of patients with an uncertain diagnosis. A retrospective chart review was performed. Patients who underwent CLE between November 2013 and October 2015 and exhibited a poor correlation between endoscopic and histological findings were included. Baseline characteristics, indications, previous diagnostic studies, findings at the time of CLE, clinical management and histological results were analyzed. Interventions based on CLE findings were also analyzed. We compared the diagnostic accuracy of CLE and target biopsies of surgical specimens. A total of 144 patients were included. Of these, 51% (74/144) were female. The mean age was 51 years old. In all, 41/144 (28.4%) lesions were neoplastic (13 bile duct, 10 gastric, 8 esophageal, 6 colonic, 1 duodenal, 1 rectal, 1 ampulloma and 1 pancreatic). The sensitivity, specificity, positive predictive value, negative predictive value, and observed agreement when CLE was used to detect N-lesions were 85.37%, 87.38%, 72.92%, 93.75% and 86.81%, respectively. Cohen's Kappa was 69.20%, thus indicating good agreement. Changes in management were observed in 54% of the cases. CLE is a new diagnostic tool that has a significant clinical impact on the diagnosis and treatment of patients with uncertain diagnosis.
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Robust finite-time chaos synchronization of uncertain permanent magnet synchronous motors.
Chen, Qiang; Ren, Xuemei; Na, Jing
2015-09-01
In this paper, a robust finite-time chaos synchronization scheme is proposed for two uncertain third-order permanent magnet synchronous motors (PMSMs). The whole synchronization error system is divided into two cascaded subsystems: a first-order subsystem and a second-order subsystem. For the first subsystem, we design a finite-time controller based on the finite-time Lyapunov stability theory. Then, according to the backstepping idea and the adding a power integrator technique, a second finite-time controller is constructed recursively for the second subsystem. No exogenous forces are required in the controllers design but only the direct-axis (d-axis) and the quadrature-axis (q-axis) stator voltages are used as manipulated variables. Comparative simulations are provided to show the effectiveness and superior performance of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
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Exponentially asymptotical synchronization in uncertain complex dynamical networks with time delay
Energy Technology Data Exchange (ETDEWEB)
Luo Qun; Yang Han; Li Lixiang; Yang Yixian [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Han Jiangxue, E-mail: luoqun@bupt.edu.c [National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China)
2010-12-10
Over the past decade, complex dynamical network synchronization has attracted more and more attention and important developments have been made. In this paper, we explore the scheme of globally exponentially asymptotical synchronization in complex dynamical networks with time delay. Based on Lyapunov stability theory and through defining the error function between adjacent nodes, four novel adaptive controllers are designed under four situations where the Lipschitz constants of the state function in nodes are known or unknown and the network structure is certain or uncertain, respectively. These controllers could not only globally asymptotically synchronize all nodes in networks, but also ensure that the error functions do not exceed the pre-scheduled exponential function. Finally, simulations of the synchronization among the chaotic system in the small-world and scale-free network structures are presented, which prove the effectiveness and feasibility of our controllers.
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Directory of Open Access Journals (Sweden)
Jonathan eChabout
2013-08-01
Full Text Available In social environments, choosing between multiple rewards is modulated by the uncertainty of the situation. Here, we compared how mice interact with a conspecific and how they use acoustic communication during this interaction in a 3 chambers task (no social threat was possible and a Social Interaction Task, SIT (uncertain situation as two mice interact freely. We further manipulated the motivational state of the mice to see how they rank natural rewards such as social contact, food, and novelty seeking. We previously showed that beta2-subunit containing nicotinic receptors -2*nAChRs- are required for establishing reward ranking between social interaction, novelty exploration, and food consumption in social situations with high uncertainty. Knockout mice for 2*nAChRs -2-/-mice- exhibit profound impairment in making social flexible choices, as compared to control -WT- mice.Our current data shows that being confronted with a conspecific in a socially safe environment as compared to a more uncertain environment, drastically reduced communication between the two mice, and changed their way to deal with a social conspecific. Furthermore, we demonstrated for the first time, that 2-/- mice had the same motivational ranking than WT mice when placed in a socially safe environment. Therefore,2*nAChRs are not necessary for integrating social information or social rewards per se, but are important for making choices, only in a socially uncertain environment.This seems particularly important in the context of Social Neuroscience, as numerous animal models are used to provide novel insights and to test promising novel treatments of human pathologies affecting social and communication processes, among which Autistic spectrum disorders and schizophrenia.
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Quantifying forecast quality of IT business value
Eveleens, J.L.; van der Pas, M.; Verhoef, C.
2012-01-01
This article discusses how to quantify the forecasting quality of IT business value. We address a common economic indicator often used to determine the business value of project proposals, the Net Present Value (NPV). To quantify the forecasting quality of IT business value, we develop a generalized
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International Nuclear Information System (INIS)
Shahnazi, Reza; Haghani, Adel; Jeinsch, Torsten
2015-01-01
An observer-based output feedback adaptive fuzzy controller is proposed to stabilize a class of uncertain chaotic systems with unknown time-varying time delays, unknown actuator nonlinearities and unknown external disturbances. The actuator nonlinearity can be backlash-like hysteresis or dead-zone. Based on universal approximation property of fuzzy systems the unknown nonlinear functions are approximated by fuzzy systems, where the consequent parts of fuzzy rules are tuned with adaptive schemes. The proposed method does not need the availability of the states and an observer based output feedback approach is proposed to estimate the states. To have more robustness and at the same time to alleviate chattering an adaptive discontinuous structure is suggested. Semi-global asymptotic stability of the overall system is ensured by proposing a suitable Lyapunov–Krasovskii functional candidate. The approach is applied to stabilize the time-delayed Lorenz chaotic system with uncertain dynamics amid significant disturbances. Analysis of simulations reveals the effectiveness of the proposed method in terms of coping well with the modeling uncertainties, nonlinearities in actuators, unknown time-varying time-delays and unknown external disturbances while maintaining asymptotic convergence
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Quantifying quantum coherence with quantum Fisher information.
Feng, X N; Wei, L F
2017-11-14
Quantum coherence is one of the old but always important concepts in quantum mechanics, and now it has been regarded as a necessary resource for quantum information processing and quantum metrology. However, the question of how to quantify the quantum coherence has just been paid the attention recently (see, e.g., Baumgratz et al. PRL, 113. 140401 (2014)). In this paper we verify that the well-known quantum Fisher information (QFI) can be utilized to quantify the quantum coherence, as it satisfies the monotonicity under the typical incoherent operations and the convexity under the mixing of the quantum states. Differing from most of the pure axiomatic methods, quantifying quantum coherence by QFI could be experimentally testable, as the bound of the QFI is practically measurable. The validity of our proposal is specifically demonstrated with the typical phase-damping and depolarizing evolution processes of a generic single-qubit state, and also by comparing it with the other quantifying methods proposed previously.
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Carey, Irene; Shouls, Susanna; Bristowe, Katherine; Morris, Michelle; Briant, Linda; Robinson, Carole; Caulkin, Ruth; Griffiths, Mathew; Clark, Kieron; Koffman, Jonathan; Hopper, Adrian
2015-12-01
Despite preferences to the contrary, 53% of deaths in England occur in hospital. Difficulties in managing clinical uncertainty can result in delayed recognition that a person may be approaching the end of life, and a failure to address his/her preferences. Planning and shared decision-making for hospital patients need to improve where an underlying condition responds poorly to acute medical treatment and there is a risk of dying in the next 1-2 months. This paper suggests an approach to improve this care. A care bundle (the AMBER care bundle) was designed by a multiprofessional development team, which included service users, utilising the model for improvement following an initial scoping exercise. The care bundle includes two identification questions, four subsequent time restricted actions and systematic daily follow-up. This paper describes the development and implementation of a care bundle. From August 2011 to July 2012, 638 patients received care supported by the AMBER care bundle. In total 42.8% died in hospital and a further 14.5% were readmitted as emergencies within 30 days of discharge. Clinical outcome measures are in development. It has been possible to develop a care bundle addressing a complex area of care which can be a lever for cultural change. The implementation of the AMBER care bundle has the potential to improve care of clinically uncertain hospital patients who may be approaching the end of life by supporting their recognition and prompting discussion of their preferences. Outcomes associated with its use are currently being formally evaluated. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
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Analyzing complex networks evolution through Information Theory quantifiers
Energy Technology Data Exchange (ETDEWEB)
Carpi, Laura C., E-mail: Laura.Carpi@studentmail.newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Rosso, Osvaldo A., E-mail: rosso@fisica.ufmg.b [Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Chaos and Biology Group, Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires (Argentina); Saco, Patricia M., E-mail: Patricia.Saco@newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Hidraulica, Facultad de Ciencias Exactas, Ingenieria y Agrimensura, Universidad Nacional de Rosario, Avenida Pellegrini 250, Rosario (Argentina); Ravetti, Martin Gomez, E-mail: martin.ravetti@dep.ufmg.b [Departamento de Engenharia de Producao, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, Belo Horizonte (31270-901), MG (Brazil)
2011-01-24
A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.
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Uncertain Governance and Resilient Subjects in the Risk Society
Directory of Open Access Journals (Sweden)
Pat O'Malley
2013-04-01
Full Text Available Over the past decade or so, a series of new or revitalised strategies have been promoted to govern the highly uncertain threats that risk appears no longer able to prevent. Most owe their ascendancy to the lessons of 9/11, and the ‘bureaucratising of imagination’ that US sources have proposed as a response, by centring the possible, or even merely imaginable, rather than the statistically probable. Precaution, preparedness and speculative pre-emption have been particularly prominent, although new hybrid statistical and speculative techniques have broadened risk techniques to cope with labile conditions of high uncertainty. But while diverse, each establishes a negative and defensive framework of ‘freedom from’ that has been associated with creating a ’neurotic subject’. In the past decade, programs of resilience, and particularly resiliency training, have been developed with the aim of creating subjects able to thrive and prosper under conditions of extreme uncertainty. They constitute a form of governance promoting a positive ‘freedom to’. Reflecting many of the assumptions and goals of neo-liberal politics, resiliency has already emerged as a principal technology for military and business, and may be the answer to the neo-liberal dream of a society of extreme entrepreneurs. Durante la última década, se han promovido varias estrategias nuevas o renovadas destinadas a gestionar amenazas que el riesgo ya no parece capaz de prevenir. La mayoría deben su predominancia a las lecciones aprendidas tras el 11-S, y la “burocratización de la imaginación” que las fuentes estadounidenses han propuesto como respuesta, predominando lo posible, o incluso simplemente lo imaginable, por encima de lo estadísticamente probable. Han predominado la precaución, preparación y especulación preventivas, aunque las nuevas técnicas estadísticas y especulativas híbridas han ampliado las técnicas de riesgo para hacer frente a las
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Tinker, Sarah C.; Moe, Christine L.; Klein, Mitchel; Flanders, W. Dana; Uber, Jim; Amirtharajah, Appiah; Singer, Philip; Tolbert, Paige E.
2013-01-01
Background The extent to which drinking water turbidity measurements indicate the risk of gastrointestinal illness is not well-understood. Despite major advances in drinking water treatment and delivery, infectious disease can still be transmitted through drinking water in the U.S., and it is important to have reliable indicators of microbial water quality to inform public health decisions. The objective of our study was to assess the relationship between gastrointestinal illness, quantified through emergency department visits, and drinking water quality, quantified as raw water and filtered water turbidity measured at the treatment plant. Methods We examined the relationship between turbidity levels of raw and filtered surface water measured at eight major drinking water treatment plants in the metropolitan area of Atlanta, Georgia, and over 240 000 emergency department visits for gastrointestinal illness during 1993–2004 among the population served by these plants. We fit Poisson time-series statistical regression models that included turbidity in a 21-day distributed lag and that controlled for meteorological factors and long-term time trends. Results For filtered water turbidity, the results were consistent with no association with emergency department visits for gastrointestinal illness. We observed a modest association between raw water turbidity and emergency department visits for gastrointestinal illness. This association was not observed for all treatment plants in plant-specific analyses. Conclusions Our results suggest that source water quality may contribute modestly to endemic gastrointestinal illness in the study area. The association between turbidity and emergency department visits for gastrointestinal illness was only observed when raw water turbidity was considered; filtered water turbidity may not serve as a reliable indicator of modest pathogen risk at all treatment plants. PMID:18941478
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Léchappé, V.; Moulay, E.; Plestan, F.
2018-06-01
The stability of a prediction-based controller for linear time-invariant (LTI) systems is studied in the presence of time-varying input and output delays. The uncertain delay case is treated as well as the partial state knowledge case. The reduction method is used in order to prove the convergence of the closed-loop system including the state observer, the predictor and the plant. Explicit conditions that guarantee the closed-loop stability are given, thanks to a Lyapunov-Razumikhin analysis. Simulations illustrate the theoretical results.
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Fitness landscape complexity and the emergence of modularity in neural networks
Lowell, Jessica
Previous research has shown that the shape of the fitness landscape can affect the evolution of modularity. We evolved neural networks to solve different tasks with different fitness landscapes, using NEAT, a popular neuroevolution algorithm that quantifies similarity between genomes in order to divide them into species. We used this speciation mechanism as a means to examine fitness landscape complexity, and to examine connections between fitness landscape complexity and the emergence of modularity.
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Lesions of uncertain malignant potential in the breast (B3): what do we know?
International Nuclear Information System (INIS)
Purushothaman, H.N.; Lekanidi, K.; Shousha, S.; Wilson, R.
2016-01-01
Breast lesions classified as of uncertain malignant potential (B3) on biopsy form a diverse group of abnormalities, which pose a diagnostic and management challenge. In this paper, we discuss the imaging and pathology features as well as the management of the most controversial B3 lesions, consisting of papillary lesions, complex sclerosing lesions/radial scars, lobular intraepithelial neoplasia, and atypical epithelial proliferation of ductal type. As there is an association with malignancy at the time of diagnosis, as well as an increase in the risk of subsequent development of cancer, a multidisciplinary discussion is almost always required to tailor treatment.
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Natural Gas: Investment Strategies In An Uncertain World
International Nuclear Information System (INIS)
Soliman, M.; Darwish, M.
2004-01-01
Natural Gas investment projects in developing countries (of which Egypt is a typical example) are one of the key industries in the evolving and continually changing energy market. It seems clear that the natural gas industry today is no longer limited by national boundaries, and that countries as well as organizations need to have an adaptive investment strategy and a global perspective if they are to survive and prosper in this . uncertain world. Many strategies will succeed or fail on the basis of their ability to deal with this dynamic environment. Strategy decisions are by their nature complex, and involve many imponderables. The selection of a course of action depends on the availability and interpretation of information, analysis, intuition, emotion, political awareness and many other factors. Different individuals and groups emphasize different aspects and, in the sense that a strategy decision is an advance into tbe unknown, there is no correct course of action; all that can be done is to interpret the current situation, form expectations about the future, and act according to personal views on risk and the likely course of events. It is usually possible to identify courses of action which are unlikely to be successful, and in that sense the strategy process can have real benefits in helping to avoid disastrous courses of action
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Entrepreneurship, Emerging Technologies, Emerging Markets
Thukral, Inderpreet S.; Von Ehr, James; Walsh, Steven Thomas; Groen, Arend J.; van der Sijde, Peter; Adham, Khairul Akmaliah
2008-01-01
Academics and practitioners alike have long understood the benefits, if not the risks, of both emerging markets and emerging technologies.Yet it is only recently that foresighted firms have embraced emerging technologies and emerging markets through entrepreneurial activity. Emerging technologies
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Lyapunov-based control of limit cycle oscillations in uncertain aircraft systems
Bialy, Brendan
Store-induced limit cycle oscillations (LCO) affect several fighter aircraft and is expected to remain an issue for next generation fighters. LCO arises from the interaction of aerodynamic and structural forces, however the primary contributor to the phenomenon is still unclear. The practical concerns regarding this phenomenon include whether or not ordnance can be safely released and the ability of the aircrew to perform mission-related tasks while in an LCO condition. The focus of this dissertation is the development of control strategies to suppress LCO in aircraft systems. The first contribution of this work (Chapter 2) is the development of a controller consisting of a continuous Robust Integral of the Sign of the Error (RISE) feedback term with a neural network (NN) feedforward term to suppress LCO behavior in an uncertain airfoil system. The second contribution of this work (Chapter 3) is the extension of the development in Chapter 2 to include actuator saturation. Suppression of LCO behavior is achieved through the implementation of an auxiliary error system that features hyperbolic functions and a saturated RISE feedback control structure. Due to the lack of clarity regarding the driving mechanism behind LCO, common practice in literature and in Chapters 2 and 3 is to replicate the symptoms of LCO by including nonlinearities in the wing structure, typically a nonlinear torsional stiffness. To improve the accuracy of the system model a partial differential equation (PDE) model of a flexible wing is derived (see Appendix F) using Hamilton's principle. Chapters 4 and 5 are focused on developing boundary control strategies for regulating the bending and twisting deformations of the derived model. The contribution of Chapter 4 is the construction of a backstepping-based boundary control strategy for a linear PDE model of an aircraft wing. The backstepping-based strategy transforms the original system to a exponentially stable system. A Lyapunov-based stability
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A spatial theory for emergent multiple predator-prey interactions in food webs.
Northfield, Tobin D; Barton, Brandon T; Schmitz, Oswald J
2017-09-01
Predator-prey interaction is inherently spatial because animals move through landscapes to search for and consume food resources and to avoid being consumed by other species. The spatial nature of species interactions necessitates integrating spatial processes into food web theory and evaluating how predators combine to impact their prey. Here, we present a spatial modeling approach that examines emergent multiple predator effects on prey within landscapes. The modeling is inspired by the habitat domain concept derived from empirical synthesis of spatial movement and interactions studies. Because these principles are motivated by synthesis of short-term experiments, it remains uncertain whether spatial contingency principles hold in dynamical systems. We address this uncertainty by formulating dynamical systems models, guided by core habitat domain principles, to examine long-term multiple predator-prey spatial dynamics. To describe habitat domains, we use classical niche concepts describing resource utilization distributions, and assume species interactions emerge from the degree of overlap between species. The analytical results generally align with those from empirical synthesis and present a theoretical framework capable of demonstrating multiple predator effects that does not depend on the small spatial or temporal scales typical of mesocosm experiments, and help bridge between empirical experiments and long-term dynamics in natural systems.
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Nonsingular Terminal Sliding Mode Control of Uncertain Second-Order Nonlinear Systems
Directory of Open Access Journals (Sweden)
Minh-Duc Tran
2015-01-01
Full Text Available This paper presents a high-performance nonsingular terminal sliding mode control method for uncertain second-order nonlinear systems. First, a nonsingular terminal sliding mode surface is introduced to eliminate the singularity problem that exists in conventional terminal sliding mode control. By using this method, the system not only can guarantee that the tracking errors reach the reference value in a finite time with high-precision tracking performance but also can overcome the complex-value and the restrictions of the exponent (the exponent should be fractional number with an odd numerator and an odd denominator in traditional terminal sliding mode. Then, in order to eliminate the chattering phenomenon, a super-twisting higher-order nonsingular terminal sliding mode control method is proposed. The stability of the closed-loop system is established using the Lyapunov theory. Finally, simulation results are presented to illustrate the effectiveness of the proposed method.
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Exponential stability result for discrete-time stochastic fuzzy uncertain neural networks
International Nuclear Information System (INIS)
Mathiyalagan, K.; Sakthivel, R.; Marshal Anthoni, S.
2012-01-01
This Letter addresses the stability analysis problem for a class of uncertain discrete-time stochastic fuzzy neural networks (DSFNNs) with time-varying delays. By constructing a new Lyapunov–Krasovskii functional combined with the free weighting matrix technique, a new set of delay-dependent sufficient conditions for the robust exponential stability of the considered DSFNNs is established in terms of Linear Matrix Inequalities (LMIs). Finally, numerical examples with simulation results are provided to illustrate the applicability and usefulness of the obtained theory. -- Highlights: ► Applications of neural networks require the knowledge of dynamic behaviors. ► Exponential stability of discrete-time stochastic fuzzy neural networks is studied. ► Linear matrix inequality optimization approach is used to obtain the result. ► Delay-dependent stability criterion is established in terms of LMIs. ► Examples with simulation are provided to show the effectiveness of the result.
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Peres, David J.; Cancelliere, Antonino; Greco, Roberto; Bogaard, Thom A.
2018-03-01
Uncertainty in rainfall datasets and landslide inventories is known to have negative impacts on the assessment of landslide-triggering thresholds. In this paper, we perform a quantitative analysis of the impacts of uncertain knowledge of landslide initiation instants on the assessment of rainfall intensity-duration landslide early warning thresholds. The analysis is based on a synthetic database of rainfall and landslide information, generated by coupling a stochastic rainfall generator and a physically based hydrological and slope stability model, and is therefore error-free in terms of knowledge of triggering instants. This dataset is then perturbed according to hypothetical reporting scenarios that allow simulation of possible errors in landslide-triggering instants as retrieved from historical archives. The impact of these errors is analysed jointly using different criteria to single out rainfall events from a continuous series and two typical temporal aggregations of rainfall (hourly and daily). The analysis shows that the impacts of the above uncertainty sources can be significant, especially when errors exceed 1 day or the actual instants follow the erroneous ones. Errors generally lead to underestimated thresholds, i.e. lower than those that would be obtained from an error-free dataset. Potentially, the amount of the underestimation can be enough to induce an excessive number of false positives, hence limiting possible landslide mitigation benefits. Moreover, the uncertain knowledge of triggering rainfall limits the possibility to set up links between thresholds and physio-geographical factors.
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Directory of Open Access Journals (Sweden)
D. J. Peres
2018-03-01
Full Text Available Uncertainty in rainfall datasets and landslide inventories is known to have negative impacts on the assessment of landslide-triggering thresholds. In this paper, we perform a quantitative analysis of the impacts of uncertain knowledge of landslide initiation instants on the assessment of rainfall intensity–duration landslide early warning thresholds. The analysis is based on a synthetic database of rainfall and landslide information, generated by coupling a stochastic rainfall generator and a physically based hydrological and slope stability model, and is therefore error-free in terms of knowledge of triggering instants. This dataset is then perturbed according to hypothetical reporting scenarios that allow simulation of possible errors in landslide-triggering instants as retrieved from historical archives. The impact of these errors is analysed jointly using different criteria to single out rainfall events from a continuous series and two typical temporal aggregations of rainfall (hourly and daily. The analysis shows that the impacts of the above uncertainty sources can be significant, especially when errors exceed 1 day or the actual instants follow the erroneous ones. Errors generally lead to underestimated thresholds, i.e. lower than those that would be obtained from an error-free dataset. Potentially, the amount of the underestimation can be enough to induce an excessive number of false positives, hence limiting possible landslide mitigation benefits. Moreover, the uncertain knowledge of triggering rainfall limits the possibility to set up links between thresholds and physio-geographical factors.
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Quantifying Confidence in Model Predictions for Hypersonic Aircraft Structures
2015-03-01
represents the number of samples and k is the number of uncertain input factors [67]. The exploration of the input space is performed using Sobol ...Computer Physics Communications, 181, 259-270. [68] Sobol ’, I.M. (1967). “On the distribution of points in a cube and the approximate evaluation of...integrals.” USSR Comput. Maths. Math. Phys., 7, 86-112. [69] Sobol ’, I.M. (1976). “Uniformly distributed sequences with an addition uniform property
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Quantifying requirements volatility effects
Kulk, G.P.; Verhoef, C.
2008-01-01
In an organization operating in the bancassurance sector we identified a low-risk IT subportfolio of 84 IT projects comprising together 16,500 function points, each project varying in size and duration, for which we were able to quantify its requirements volatility. This representative portfolio
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Thermosensory reversal effect quantified
Bergmann Tiest, W.M.; Kappers, A.M.L.
2008-01-01
At room temperature, some materials feel colder than others due to differences in thermal conductivity, heat capacity and geometry. When the ambient temperature is well above skin temperature, the roles of 'cold' and 'warm' materials are reversed. In this paper, this effect is quantified by
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Ansari, Sereena; Boyle, Adrian
2017-02-01
Domestic abuse represents a serious public health and human rights concern. Interventions to reduce the risk of abuse include staff training and standardized documentation improving detection and adherence to referral pathways. Interventional studies have been conducted in primary care, maternity and outpatient settings. Women disclosing abuse in emergency departments differ from women attending other healthcare settings, and it is unclear whether these interventions can be transferred to the emergency care setting. This review examines interventional studies to evaluate the effectiveness of emergency department-based interventions in reducing domestic abuse-related morbidity. Medline, EMBASE, CINAHL, PsycINFO and Cochrane Library were searched, according to prespecified selection criteria. Study quality was assessed using the Jadad scale. Of 273 search results, nine were eligible for review. Interventions involving staff training demonstrated benefits in subjective measures, such as staff knowledge regarding abuse, but no changes in clinical practice, based on detection and referral rates. When staff training was implemented in conjunction with supporting system changes - for example, standardized documentation for assessment and referral - clinically relevant improvements were noted. Interventions centred around staff training are insufficient to bring about improvements in the management and, thus, outcome of patients suffering abuse. Instead, system changes, such as standardized documentation and referral pathways, supported by training, may bring about beneficial changes. It remains uncertain whether surrogate outcomes employed by most studies translate to changes in abuse-related morbidity: the ultimate goal.
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Directory of Open Access Journals (Sweden)
Junxuan Chen
2014-03-01
Full Text Available In the view of the current cockpit information interaction, facilities and other characteristics are increasingly multifarious; the early layout evaluation methods based on single or partial components, often cause comprehensive evaluation unilateral, leading to the problems of long development period and low efficiency. Considering the fuzziness of ergonomic evaluation and diversity of evaluation information attributes, we refine and build an evaluation system based on the characteristics of the current cockpit man-machine layout and introduce the different types of uncertain linguistic multiple attribute combination decision making (DTULDM method in the cockpit layout evaluation process. Meanwhile, we also establish an aircraft cockpit ergonomic layout evaluation model. Finally, an experiment about cockpit layout evaluation is given, and the result demonstrates that the proposed method about cockpit ergonomic layout evaluation is feasible and effective.
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Jiang, Jiefeng; Egner, Tobias
2014-07-01
Resolving conflicting sensory and motor representations is a core function of cognitive control, but it remains uncertain to what degree control over different sources of conflict is implemented by shared (domain general) or distinct (domain specific) neural resources. Behavioral data suggest conflict-control to be domain specific, but results from neuroimaging studies have been ambivalent. Here, we employed multivoxel pattern analyses that can decode a brain region's informational content, allowing us to distinguish incidental activation overlap from actual shared information processing. We trained independent sets of "searchlight" classifiers on functional magnetic resonance imaging data to decode control processes associated with stimulus-conflict (Stroop task) and ideomotor-conflict (Simon task). Quantifying the proportion of domain-specific searchlights (capable of decoding only one type of conflict) and domain-general searchlights (capable of decoding both conflict types) in each subject, we found both domain-specific and domain-general searchlights, though the former were more common. When mapping anatomical loci of these searchlights across subjects, neural substrates of stimulus- and ideomotor-specific conflict-control were found to be anatomically consistent across subjects, whereas the substrates of domain-general conflict-control were not. Overall, these findings suggest a hybrid neural architecture of conflict-control that entails both modular (domain specific) and global (domain general) components. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Lactate level, aetiology and mortality of adult patients in an emergency department
DEFF Research Database (Denmark)
Pedersen, Mathilde; Brandt, Vibeke Schnack; Holler, Jon Gitz
2015-01-01
BACKGROUND: Increased lactate is associated with high mortality among patients with suspected infection or trauma in the emergency department (ED), but the association with patients with other aetiologies is less well described. The aim of this study was to describe the relation between lactate......, lactate level showed to be useful in patients with infection (0.78, 95% CI 0.73 to 0.84), trauma (0.78, 95% CI 0.65 to 0.92), cardiac diseases (0.83, 95% CI 0.75 to 0.91) and gastrointestinal diseases (0.83, 95% CI 0.68 to 0.98). Lactate level was not useful in neurological (0.58, 95% CI 0.50 to 0.......67) and respiratory disease (0.64, 95% CI 0.55 to 0.74), and of uncertain value in the remaining diagnostic groups. CONCLUSIONS: Among adult ED patients, the prognostic value of lactate varies between diagnostic groups....
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Thermosensory reversal effect quantified
Bergmann Tiest, W.M.; Kappers, A.M.L.
2008-01-01
At room temperature, some materials feel colder than others due to differences in thermal conductivity, heat capacity and geometry. When the ambient temperature is well above skin temperature, the roles of ‘cold’ and ‘warm’ materials are reversed. In this paper, this effect is quantified by
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Quantifying IT estimation risks
Kulk, G.P.; Peters, R.J.; Verhoef, C.
2009-01-01
A statistical method is proposed for quantifying the impact of factors that influence the quality of the estimation of costs for IT-enabled business projects. We call these factors risk drivers as they influence the risk of the misestimation of project costs. The method can effortlessly be
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Quantifying Quantum-Mechanical Processes.
Hsieh, Jen-Hsiang; Chen, Shih-Hsuan; Li, Che-Ming
2017-10-19
The act of describing how a physical process changes a system is the basis for understanding observed phenomena. For quantum-mechanical processes in particular, the affect of processes on quantum states profoundly advances our knowledge of the natural world, from understanding counter-intuitive concepts to the development of wholly quantum-mechanical technology. Here, we show that quantum-mechanical processes can be quantified using a generic classical-process model through which any classical strategies of mimicry can be ruled out. We demonstrate the success of this formalism using fundamental processes postulated in quantum mechanics, the dynamics of open quantum systems, quantum-information processing, the fusion of entangled photon pairs, and the energy transfer in a photosynthetic pigment-protein complex. Since our framework does not depend on any specifics of the states being processed, it reveals a new class of correlations in the hierarchy between entanglement and Einstein-Podolsky-Rosen steering and paves the way for the elaboration of a generic method for quantifying physical processes.
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Jayatilake, Nihal; Mendis, Shanthi; Maheepala, Palitha; Mehta, Firdosi R
2013-08-27
This study describes chronic kidney disease of uncertain aetiology (CKDu), which cannot be attributed to diabetes, hypertension or other known aetiologies, that has emerged in the North Central region of Sri Lanka. A cross-sectional study was conducted, to determine the prevalence of and risk factors for CKDu. Arsenic, cadmium, lead, selenium, pesticides and other elements were analysed in biological samples from individuals with CKDu and compared with age- and sex-matched controls in the endemic and non-endemic areas. Food, water, soil and agrochemicals from both areas were analysed for heavy metals. The age-standardised prevalence of CKDu was 12.9% (95% confidence interval [CI] = 11.5% to 14.4%) in males and 16.9% (95% CI = 15.5% to 18.3%) in females. Severe stages of CKDu were more frequent in males (stage 3: males versus females = 23.2% versus 7.4%; stage 4: males versus females = 22.0% versus 7.3%; P 39 years and those who farmed (chena cultivation) (OR [odds ratio] = 1.926, 95% CI = 1.561 to 2.376 and OR = 1.195, 95% CI = 1.007 to 1.418 respectively, P CKDu (1.039 μg/g) compared with controls in the endemic and non-endemic areas (0.646 μg/g, P CKDu stage (P CKDu were at levels known to cause kidney damage. Food items from the endemic area contained cadmium and lead above reference levels. Serum selenium was CKDu and pesticides residues were above reference levels in 31.6% of those with CKDu. These results indicate chronic exposure of people in the endemic area to low levels of cadmium through the food chain and also to pesticides. Significantly higher urinary excretion of cadmium in individuals with CKDu, and the dose-effect relationship between urine cadmium concentration and CKDu stages suggest that cadmium exposure is a risk factor for the pathogensis of CKDu. Deficiency of selenium and genetic susceptibility seen in individuals with CKDu suggest that they may be predisposing factors for the development of CKDu.
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Carbon dioxide quantified by the infrared in evaluation of respiratory activity of wheat seeds
Directory of Open Access Journals (Sweden)
João Alexandre Lopes Dranski
Full Text Available ABSTRACT The objective of this study was to develop and validate the methodology of carbon dioxide concentration in the evaluation of vigor of Triticum aestivum L. seeds based on infrared spectroscopy. The proposed method quantifies CO2 content using a drag system and exhaustion to the gas released by the seeds. Samples of 50 seeds of six lots of cultivar CD 123 were incubated at temperatures of 15, 25 and 40 °C. The CO2 content released after 1, 3, 6, 9, 12 and 24 h of incubation were quantified. Additionally, the percentage of normal seedlings emerged in the field were evaluated. The simple correlation coefficients were evaluated among tests. After determining the reading conditions, the precision and accuracy of the proposed method were evaluated, using 15 lots of seeds. For the evaluation of the respiratory activity in Triticum aestivum seeds, a sample of 25 seeds, incubated at 25 °C for a minimum of 12 h is recommended since it allows to classify lots with different levels of vigor and predict the establishment of seedlings in the field, being the appropriate method for measuring CO2 as it externalizes precision between successive measurements and agreement with the reference method.
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2015-02-01
Landpower in an Uncertain Strategic Environment, June 1-3, 2014 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d...3: THE ARMY AS PART OF THE JOINT, INTERAGENCY, AND INTERGOVERNMENTAL TEAM Panelists: Lieutenant General Edward Cardon , Commander, U.S. Army
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Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems
International Nuclear Information System (INIS)
Chang Weider; Yan Junjuh
2005-01-01
A robust adaptive PID controller design motivated from the sliding mode control is proposed for a class of uncertain chaotic systems in this paper. Three PID control gains, K p , K i , and K d , are adjustable parameters and will be updated online with an adequate adaptation mechanism to minimize a previously designed sliding condition. By introducing a supervisory controller, the stability of the closed-loop PID control system under with the plant uncertainty and external disturbance can be guaranteed. Finally, a well-known Duffing-Holmes chaotic system is used as an illustrative to show the effectiveness of the proposed robust adaptive PID controller
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Directory of Open Access Journals (Sweden)
Daqi Zhu
2008-11-01
Full Text Available This paper introduces a novel thruster fault diagnosis and accommodation system for open-frame underwater vehicles with abrupt faults. The proposed system consists of two subsystems: a fault diagnosis subsystem and a fault accommodation sub-system. In the fault diagnosis subsystem a ICMAC(Improved Credit Assignment Cerebellar Model Articulation Controllers neural network is used to realize the on-line fault identification and the weighting matrix computation. The fault accommodation subsystem uses a control algorithm based on weighted pseudo-inverse to find the solution of the control allocation problem. To illustrate the proposed method effective, simulation example, under multi-uncertain abrupt faults, is given in the paper.
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Robust extended Kalman filter of discrete-time Markovian jump nonlinear system under uncertain noise
International Nuclear Information System (INIS)
Zhu, Jin; Park, Jun Hong; Lee, Kwan Soo; Spiryagin, Maksym
2008-01-01
This paper examines the problem of robust extended Kalman filter design for discrete -time Markovian jump nonlinear systems with noise uncertainty. Because of the existence of stochastic Markovian switching, the state and measurement equations of underlying system are subject to uncertain noise whose covariance matrices are time-varying or un-measurable instead of stationary. First, based on the expression of filtering performance deviation, admissible uncertainty of noise covariance matrix is given. Secondly, two forms of noise uncertainty are taken into account: Non- Structural and Structural. It is proved by applying game theory that this filter design is a robust mini-max filter. A numerical example shows the validity of the method
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Directory of Open Access Journals (Sweden)
Heli Hu
2014-01-01
Full Text Available The design of the dynamic output feedback H∞ control for uncertain interconnected systems of neutral type is investigated. In the framework of Lyapunov stability theory, a mathematical technique dealing with the nonlinearity on certain matrix variables is developed to obtain the solvability conditions for the anticipated controller. Based on the corresponding LMIs, the anticipated gains for dynamic output feedback can be achieved by solving some algebraic equations. Also, the norm of the transfer function from the disturbance input to the controlled output is less than the given index. A numerical example and the simulation results are given to show the effectiveness of the proposed method.
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Dynamics of emerging organic pollutants from a municipal landfill
Le Guern, Cécile; Béchet, Béatrice; Lépinay, Alexandra; Conil, Pierre
2017-04-01
In large cities, municipal landfills may have received waste coming from hospitals, but also green waste. The corresponding anthroposol might thus be a source of organic emerging substances such as pharmaceutical or phytosanitary substances. The occurrence and fate of organic emerging substances from such a former landfill in urban areas has been studied as part of a research program dealing with the observation and the monitoring of the environment. Of the 261 substances sought (30 pharmaceutical molecules, 223 phytosanitary products and 8 other emerging substances), 11 pharmaceutical molecules in particular have been quantified in the leachates, 2 endocrine disruptors (bisphenol A and triclosan) and 10 phytosanitary substances. Most of these substances are found also in groundwater immediately downstream of the site (including carbamazepine) at concentrations ranging between 0.1 µg/l and 10 µg/l. The number of detected substances appears much smaller a few hundred meters far from the landfill (bisphenol A and diclofenac in particularly, with concentrations ranging from 0.1 to 1 µg/l and about 0.1 µg/l respectively). Natural attenuation occurs during transfer in the plume, as observed for PAHs or metals. Several mechanisms may explain the natural attenuation of the substances.
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Elliot, A J; Hughes, H E; Hughes, T C; Locker, T E; Brown, R; Sarran, C; Clewlow, Y; Murray, V; Bone, A; Catchpole, M; McCloskey, B; Smith, G E
2014-08-01
This study illustrates the potential of using emergency department attendance data, routinely accessed as part of a national syndromic surveillance system, to monitor the impact of thunderstorm asthma. The Emergency Department Syndromic Surveillance System (EDSSS) routinely monitors anonymised attendance data on a daily basis across a sentinel network of 35 emergency departments. Attendance data for asthma, wheeze and difficulty breathing are analysed on a daily basis. A statistically significant spike in asthma attendances in two EDSSS emergency departments in London was detected on 23 July 2013, coinciding with a series of large violent thunderstorms across southern England. There was also an increase in the reported severity of these attendances. This preliminary report illustrates the potential of the EDSSS to monitor the impact of thunderstorms on emergency department asthma attendances. Further work will focus on how this system can be used to quantify the impact on emergency departments, thus potentially improving resource planning and also adding to the thunderstorm asthma evidence-base. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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Randomized Algorithms for Analysis and Control of Uncertain Systems With Applications
Tempo, Roberto; Dabbene, Fabrizio
2013-01-01
The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten. Features: · self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis; · ...
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Short-sighted confession decisions: the role of uncertain and delayed consequences.
Yang, Yueran; Madon, Stephanie; Guyll, Max
2015-02-01
Suspects have a propensity to focus on short-term contingencies, giving disproportionate weight to the proximal consequences that are delivered by police during an interrogation, and too little consideration to the distal (and often more severe) consequences that may be levied by the judicial system if they are convicted. In this research, the authors examined whether the perceived uncertainty and temporal distance of distal consequences contribute to this propensity. Using the repetitive question paradigm (Madon et al., 2012), participants (N = 209) were interviewed about 20 prior criminal and unethical behaviors and were required to admit or deny each one. Participants' denials and admissions were paired with both a proximal consequence and a distal consequence, respectively. Results indicated that the distal consequence had less impact on participants' admission decisions when it was uncertain and temporally remote. These results provide evidence that the perceived uncertainty and temporal distance of future punishment are key factors that lead suspects to confess to crimes in exchange for short-term gains.
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Eccles, D. M.; Mitchell, G.; Monteiro, A. N. A.; Schmutzler, R.; Couch, F. J.; Spurdle, A. B.; Gómez-García, E. B.
2015-01-01
BackgroundIncreasing use of BRCA1/2 testing for tailoring cancer treatment and extension of testing to tumour tissue for somatic mutation is moving BRCA1/2 mutation screening from a primarily prevention arena delivered by specialist genetic services into mainstream oncology practice. A considerable number of gene tests will identify rare variants where clinical significance cannot be inferred from sequence information alone. The proportion of Variants of Uncertain clinical Significance (VUS) ...
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Anatomy of Alternating Quantifier Satisfiability (Work in progress)
DEFF Research Database (Denmark)
Dung, Phan Anh; Bjørner, Nikolaj; Monniaux, David
We report on work in progress to generalize an algorithm recently introduced in [10] for checking satisfiability of formulas with quantifier alternation. The algorithm uses two auxiliary procedures: a procedure for producing a candidate formula for quantifier elimination and a procedure for elimi...
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International Nuclear Information System (INIS)
Abdallh, A.; Crevecoeur, G.; Dupré, L.
2012-01-01
The magnetic characteristics of the electromagnetic devices' core materials can be recovered by solving an inverse problem, where sets of measurements need to be properly interpreted using a forward numerical model of the device. However, the uncertainties of the geometrical parameter values in the forward model lead to appreciable recovery errors in the recovered values of the material parameters. In this paper, we propose an effective inverse approach technique, in which the influences of the uncertainties in the geometrical model parameters are minimized. In this proposed approach, the cost function that needs to be minimized is adapted with respect to the uncertain geometrical model parameters. The proposed methodology is applied onto the identification of the magnetizing B–H curve of the magnetic material of an EI core inductor. The numerical results show a significant reduction of the recovery errors in the identified magnetic material parameter values. Moreover, the proposed methodology is validated by solving an inverse problem starting from real magnetic measurements. - Highlights: ► A new method to minimize the influence of the uncertain parameters in inverse problems is proposed. ► The technique is based on adapting iteratively the objective function that needs to be minimized. ► The objective function is adapted by the model response sensitivity to the uncertain parameters. ► The proposed technique is applied for recovering the B–H curve of an EI core inductor material. ► The error in the inverse problem solution is dramatically reduced using the proposed methodology.
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A Bi-Objective Green Closed Loop Supply Chain Design Problem with Uncertain Demand
Directory of Open Access Journals (Sweden)
Ming Liu
2018-03-01
Full Text Available With the development of e-commerce, competition among enterprises is becoming fiercer. Furthermore, environmental problems can no longer be ignored. To address these challenges, we devise a green closed loop supply chain (GCLSC with uncertain demand. In the problem, two conflict objectives and recycling the used products are considered. To solve this problem, a mathematical model is formulated with the chance constraint, and the ϵ -constraint method is adapted to obtain the true Pareto front for small sized problems. For larger sized problems, the non-dominated sorting genetic algorithm (NSGA-II and the multi-objective simulated annealing method (MOSA are developed. Numerous computational experiments can help manufacturers make better production and sales plans to keep competitive advantage and protect the environment.
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Robust stability analysis of uncertain stochastic neural networks with interval time-varying delay
International Nuclear Information System (INIS)
Feng Wei; Yang, Simon X.; Fu Wei; Wu Haixia
2009-01-01
This paper addresses the stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded, and the delay factor is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. A sufficient condition is derived such that for all admissible uncertainties, the considered neural network is robustly, globally, asymptotically stable in the mean square. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), which can be effectively solved by some standard numerical packages. Finally, numerical examples are provided to demonstrate the usefulness of the proposed criteria.
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Analytic Model Predictive Control of Uncertain Nonlinear Systems: A Fuzzy Adaptive Approach
Directory of Open Access Journals (Sweden)
Xiuyan Peng
2015-01-01
Full Text Available A fuzzy adaptive analytic model predictive control method is proposed in this paper for a class of uncertain nonlinear systems. Specifically, invoking the standard results from the Moore-Penrose inverse of matrix, the unmatched problem which exists commonly in input and output dimensions of systems is firstly solved. Then, recurring to analytic model predictive control law, combined with fuzzy adaptive approach, the fuzzy adaptive predictive controller synthesis for the underlying systems is developed. To further reduce the impact of fuzzy approximation error on the system and improve the robustness of the system, the robust compensation term is introduced. It is shown that by applying the fuzzy adaptive analytic model predictive controller the rudder roll stabilization system is ultimately uniformly bounded stabilized in the H-infinity sense. Finally, simulation results demonstrate the effectiveness of the proposed method.
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The Role of Quantifier Alternations in Cut Elimination
DEFF Research Database (Denmark)
Gerhardy, Philipp
2005-01-01
Extending previous results on the complexity of cut elimination for the sequent calculus LK, we discuss the role of quantifier alternations and develop a measure to describe the complexity of cut elimination in terms of quantifier alternations in cut formulas and contractions on such formulas...
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The Cramér-Rao Bounds and Sensor Selection for Nonlinear Systems with Uncertain Observations.
Wang, Zhiguo; Shen, Xiaojing; Wang, Ping; Zhu, Yunmin
2018-04-05
This paper considers the problems of the posterior Cramér-Rao bound and sensor selection for multi-sensor nonlinear systems with uncertain observations. In order to effectively overcome the difficulties caused by uncertainty, we investigate two methods to derive the posterior Cramér-Rao bound. The first method is based on the recursive formula of the Cramér-Rao bound and the Gaussian mixture model. Nevertheless, it needs to compute a complex integral based on the joint probability density function of the sensor measurements and the target state. The computation burden of this method is relatively high, especially in large sensor networks. Inspired by the idea of the expectation maximization algorithm, the second method is to introduce some 0-1 latent variables to deal with the Gaussian mixture model. Since the regular condition of the posterior Cramér-Rao bound is unsatisfied for the discrete uncertain system, we use some continuous variables to approximate the discrete latent variables. Then, a new Cramér-Rao bound can be achieved by a limiting process of the Cramér-Rao bound of the continuous system. It avoids the complex integral, which can reduce the computation burden. Based on the new posterior Cramér-Rao bound, the optimal solution of the sensor selection problem can be derived analytically. Thus, it can be used to deal with the sensor selection of a large-scale sensor networks. Two typical numerical examples verify the effectiveness of the proposed methods.
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Hecht, J. S.; Kirshen, P. H.; Vogel, R. M.
2016-12-01
Making long-term floodplain management decisions under uncertain climate change is a major urban planning challenge of the 21stcentury. To support these efforts, we introduce a screening-level optimization model that identifies adaptation portfolios by minimizing the regrets associated with their flood-control and damage costs under different climate change trajectories that are deeply uncertain, i.e. have probabilities that cannot be specified plausibly. This mixed integer program explicitly considers the coupled damage-reduction impacts of different floodwall designs and property-scale investments (first-floor elevation, wet floodproofing of basements, permanent retreat and insurance), recommends implementation schedules, and assesses impacts to stakeholders residing in three types of homes. An application to a stylized municipality illuminates many nonlinear system dynamics stemming from large fixed capital costs, infrastructure design thresholds, and discharge-depth-damage relationships. If stakeholders tolerate mild damage, floodwalls that fully protect a community from large design events are less cost-effective than portfolios featuring both smaller floodwalls and property-scale measures. Potential losses of property tax revenue from permanent retreat motivate municipal property-tax initiatives for adaptation financing. Yet, insurance incentives for first-floor elevation may discourage locally financed floodwalls, in turn making lower-income residents more vulnerable to severe flooding. A budget constraint analysis underscores the benefits of flexible floodwall designs with low incremental expansion costs while near-optimal solutions demonstrate the scheduling flexibility of many property-scale measures. Finally, an equity analysis shows the importance of evaluating the overpayment and under-design regrets of recommended adaptation portfolios for each stakeholder and contrasts them to single-scenario model results.
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Energy Technology Data Exchange (ETDEWEB)
Gomez-Magan, J. J.; Fernandez, I.; Gil, J.; Marrao, H.
2013-07-01
Work has been applied DAKOTA-SCAIS-MAAP-R for a loss of coolant in the primary sequence analysis, considering parameters and times uncertain, in a 3L-PWR plant Westinghouse design; which allows to verify the security analysis where temporary uncertainty represents an important parameter.
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Analytical chemistry methods were developed to quantify numerous emerging contaminants (ECs), such as pharmaceuticals (i.e., tamoxifen, tamoxifen metabolites, aromatase inhibitors, antibiotics, illicit drugs, over-the-counter drugs) in aqueous samples (wastewater, surface waters)...